Effective Lagrangians and Triple Boson Couplings

合集下载

Ultracapacitor - Battery Energy Storage System for Hybrid Electric Vehicles

ii
ACKNOWLEDGEMENT
This research was supported by a research grant from DaimlerChrysler, AG and by NASA Grant NAG3-2790 under subcontract from Bowling Green State University.
APPENDIX II: SYSTEM SCHEMATICS...................................................................... 69
ivபைடு நூலகம்
List of Figures
Figure 1.1 Figure 1.2 Figure 4.1 Figure 4.2 Figure 5.1 Figure 5.2 Figure 6.1 Figure 6.2 Figure 7.1 Figure 7.2 Figure 7.3 Figure 7.4 Figure 7.5 Figure 7.6 Figure 7.7 Figure 7.8 Figure 7.9 Figure 7.10 Figure 8.1 Figure 8.2 Figure 8.3 Figure 8.4 Figure 8.5 Figure 8.6 Figure 8.7 Figure 8.8 Figure 8.9 Figure 8.10 Hybrid Fuel Cell – Ultracapacitor ESS Hybrid Battery-Ultracapacitor ESS Equivalent circuit of a parallel battery/UC Hybrid UC-Battery Simulated Discharge Current Waveforms Proposed Hybrid Battery-UC ESS Simulated Constant Power Pulse First Battery Charging Method Second Battery Charging Method The Proposed Performance Characterization Method ICE Efficiency Map and The Power Split Rule Battery Charging and Routine Message Transmission Algorithm Analog Interface and Vehicle Simulation Algorithm Secondary Microcontroller Algorithms PC Monitor Software screen shot ABC-150 ROS Algorithm Battery Voltage Sense signal conditioning IR2118 Based Relay Driver Circuit LEM Current Sensor signal manipulation circuit Results for 300A / 5 sec. test currents Results for 300A / 8 sec. test currents Results for the Idle-Stop Test StampPlot Pro screen capture Simulator results to demonstrate battery charging and 52 53 54 55 56 57 Simulator results to demonstrate Power Assist Mode Simulator results to demonstrate Motor Only Mode Simulator results to demonstrate regenerative braking Buck Regulator Parallel Battery Charging System Results of the Parallel Battery Charger 2 2 11 12 15 18 20 21 26 31 34 35 39 40 43 44 45 46 48 49 50 51

Effective lagrangians for QCD at high density

a r X i v :h e p -t h /0108195v 1 27 A u g 2001Effective lagrangians for QCD at high densityRoberto CasalbuoniDipartimento di Fisica dell’Universita’di Firenze and Sezione INFN,L.go E.Fermi 2,50125Firenze,Italy.E-mail:casalbuoni@ﬁ.infn.itAbstract.We describe low energy physics in the CFL and LOFF phases by means of effective lagrangians.In the CFL case we present also how to derive expressions for the parameters appearing in the lagrangian via weak coupling calculations taking advantage of the dimensional reduction of fermion physics around the Fermi surface.The Goldstone boson of the LOFF phase turns out to be a phonon satisfying an anisotropic dispersion relation.INTRODUCTION Ideas about color superconductivity go back to almost 25years ago [1],but only recently this phenomenon has received a lot of attention (for recent reviews see ref.[2]).The naive expectation is that at very high density,due to the asymptotic freedom,quarks would form a Fermi sphere of almost free fermions.However,Bardeen,Cooper and Schrieffer proved that the Fermi surface of free fermions is unstable in presence of an attractive,arbitrary small,interaction.Since in QCD the gluon exchange in the ¯3channel is attractive one expects the formation of a coherent state of particle/hole pairs (Cooper pairs).For a careful description of the formation of the condensates and of the approximations involved in going from asymptotic densities to ﬁnite ones it is useful to see the contribution of K.Rajagopal at this meeting [3].The phase structure of QCD at high density depends on the number of ﬂavors and there are two very interesting cases,corresponding to two massless ﬂavors (2SC)[1,4]and to three massless ﬂavors (CFL)[5,6]respectively.In this talk we will be mainly concerned with the latter case.Thetwo cases correspond to very different patterns of symmetry breaking.If we denote left-and right-handed quark ﬁelds by ψαiL (R )with α=1,2,3,the SU (3)c color index,and i =1,···,N f the ﬂavor index (N f is the number of massless ﬂavors),in the 2SC phase we have the following structure for the condensate (C =i γ2γ0is the charge-conjugation matrix) q αiL (R )Cq βjL (R ) ∝εi j εαβ3.(1)The condensate breaks the color group SU (3)c down to the subgroup SU (2)c but it does not break any ﬂavor symmetry.Although the baryon number,B ,is broken,there is a combination of B and of the broken color generator,T 8,which is unbroken in the 2SC phase.Therefore no massless Goldstone bosons are present in this phase.On the other hand,ﬁve gluon ﬁelds acquire mass whereas three are left massless.It is worth to notice that for the electric charge the situation is very similar to the one for the baryon number.Again a linear combination of the broken electric charge and of the broken generatorT8is unbroken in the2SC phase.The condensate(1)gives rise to a gap,∆,for quarksof color1and2,whereas the two quarks of color3remain un-gapped(massless).Theresulting effective low-energy theory has been described in[7].In this contribution wewill be mainly interested in the formulation of the effective theory for the three masslessquarks case.At high density it has been shown that the following condensate is formed[5,6]qαiL(R)CqβjL(R) ∝εi jXεαβX+κ(δiαδjβ+δiβδjα).(2) Due to the Fermi statistics,the condensate must be symmetric in color andﬂavor.Asa consequence the two terms appearing in eq.(2)correspond to the(¯3,¯3)and(6,6)channels of SU(3)c⊗SU(3)L(R).It turns out thatκis small[5,8,9]and therefore the condensation occurs mainly in the(¯3,¯3)channel.The expression(2)shows that theground state is left invariant by a simultaneous transformation of SU(3)c and SU(3)L(R).This is called Color Flavor Locking(CFL).The symmetry breaking pattern isSU(3)c⊗SU(3)L⊗SU(3)R⊗U(1)B⊗U(1)A↓(3)SU(3)c+L+R⊗Z2⊗Z2The U(1)A symmetry is broken at the quantum level by the anomaly,but it gets restoredat very high density since the instanton contribution is suppressed[10,8,11].TheZ2symmetries arise since the condensate is left invariant by a change of sign of theleft-and/or right-handedﬁelds.As for the2SC case the electric charge is broken buta linear combination with the broken color generator T8annihilates the ground state.On the contrary the baryon number is broken.Therefore there are8+2broken globalsymmetries giving rise to10Goldstone bosons.The one associated to U(1)A getsmassless only at very high density.The color group is completely broken and all thegauge particles acquire mass.Also all the fermions are gapped.We will show in the following how to construct an effective lagrangian describing the Goldstone bosons,and how to compute their couplings in the high density limit where the QCD coupling gets weaker.Aﬁnal problem we will discuss has to do with the fact that when quarks(in particular the strange quark)are massive,their chemical potentials cannot be all equal. This situation has been modeled out in[12].If the Fermi surfaces of differentﬂavors are too far apart,BCS pairing does not occur.However it might be favorable for different quarks to pair each of one lying at its own Fermi surface and originating a pair of non-zero total momentum.This is the LOFF stateﬁrst studied by the authors of ref.[13]in the context of electron superconductivity in the presence of magnetic impurities.Since the Cooper pair has non-zero momentum the condensate breaks space symmetries and we will show that in the low-energy spectrum a massless particle,a phonon,the Goldstone boson of the broken translational symmetry,is present.We will construct the effective lagrangian also for this case.EFFECTIVE THEORY FOR THE CFL PHASEWe start introducing the Goldstoneﬁelds as the phases of the condensates in the(¯3,¯3) channel[14,15]X iα≈εi jkεαβγ q jβL q kγL ∗,Y iα≈εi jkεαβγ q jβR q kγR ∗.(4) Since quarks belong to the representation(3,3)of SU(3)c⊗SU(3)L(R)and transform under U(1)B⊗U(1)A according toq L→e i(α+β)q L,q R→e i(α−β)q R,e iα∈U(1)B,e iβ∈U(1)A,(5) the transformation properties of theﬁelds X and Y under the total symmetry group G=SU(3)c⊗SU(3)L⊗SU(3)R⊗U(1)B⊗U(1)A are(g c∈SU(3)c,g L(R)∈SU(3)L(R)) X→g c Xg T L e−2i(α+β),Y→g c Y g T R e−2i(α−β).(6) Theﬁelds X and Y are U(3)matrices and as such they describe9+9=18ﬁelds. Eight of theseﬁelds are eaten up by the gauge bosons,producing eight massive gauge particles.Therefore we get the right number of Goldstone bosons,10=18−10.These ﬁelds correspond to the breaking of the global symmetries in G(18generators)to the symmetry group of the ground state H=SU(3)c+L+R⊗Z2⊗Z2(8generators).For the following it is convenient to separate the U(1)factors in X and Y deﬁningﬁelds belonging to SU(3)X=ˆXe2i(φ+θ),Y=ˆY e2i(φ−θ),ˆX,ˆY∈SU(3).(7) Theﬁeldsφandθcan also be described through the determinants of X and Yd X=det(X)=e6i(φ+θ),d Y=det(Y)=e6i(φ−θ),(8) The transformation properties under G areˆX→gc ˆXg TL,ˆY→g cˆY g T R,φ→φ−α,θ→θ−β.(9)The breaking of the global symmetry can be discussed in terms of gauge invariantﬁelds given by d X,d Y andΣi j=∑α(ˆY jα)∗ˆX iα→Σ=ˆY†ˆX.(10)TheΣﬁeld describes the8Goldstone bosons corresponding to the breaking of the chiral symmetry SU(3)L⊗SU(3)R,as it is made clear by the transformation properties ofΣT,ΣT→g LΣT g†R.That isΣT transforms exactly as the usual chiralﬁeld.The other two ﬁelds d X and d Y provide the remaining two Goldstone bosons related to the breaking of the U(1)factors.In order to build up an invariant lagrangian,it is convenient to deﬁne the following currentsJµX=ˆXDµˆX†=ˆX(∂µˆX†+ˆX†gµ),JµY=ˆY DµˆY†=ˆY(∂µˆY†+ˆY†gµ),(11)with gµ=ig s g aµT a/2the gluonﬁeld and T a=λa/2the SU(3)c generators.These currents have simple transformation properties under the full symmetry group G,JµX,Y→g c JµX,Y g†c.The most general lagrangian,up to two derivative terms,invariant under G,the rotation group O(3)(Lorentz invariance is broken by the chemical potential term)and the parity transformation deﬁned asˆX↔ˆY,φ→φ,θ→−θ,is[14]L=−F2T4Tr J0X+J0Y)2 +12(∂0θ)2(12)+F2S4Tr J X+ J Y)2 −v2φ2| ∇θ|2.Using SU(3)c color gauge invariance we can chooseˆX=ˆY†,making8of the Goldstone bosons disappear and giving mass to the gluons.The properly normalized Goldstone bosons,Πa,are given in this gauge byˆX=ˆY†=e iΠa T a/F T,(13) and expanding eq.(12)at the lowest order in theﬁelds we getL≈12(∂0φ)2+12|∇Πa|2−v2φ2|∇θ|2,(14)with v=F s/F T.The gluons g a0and g a i acquire Debye and Meissner masses given bym2D=αT g2s F2T,m2M=αS v2g2s F2T.(15) It should be stressed that these are not the true rest masses of the gluons,since there is a large wave function renormalization effect making the gluon masses of order of the gap∆,rather thanµ(see later)[16].Since this description is supposed to be valid at low energies(we expect much below the gap∆),we could also decouple the gluons solving their classical equations of motion neglecting the kinetic term.The result from eq.(12) isgµ=−14 Tr[˙Σ˙Σ†]−v2Tr[ ∇Σ· ∇Σ†] +12 ˙θ2−v2φ| ∇θ|2 .(17) Notice that theﬁrst term is nothing but the chiral lagrangian except for the breaking of the Lorentz invariance.This is a way of seeing the quark-hadron continuity,that is the continuity between the CFL and the nuclear matter phases in threeﬂavor QCD.The identiﬁcation is perfect if one realizes that in nuclear matter the pairing may occur in such a way to give rise to a superﬂuid due to the breaking of the baryon number as it happens in the CFL phase[17].FERMIONS NEAR THE FERMI SURFACEWe will introduce now the formalism described in ref.[18]in order to evaluate theparameters appearing in the effective lagrangian.This formulation is based on theobservation that,at very high-density,the energy spectrum of a massless fermion isdescribed by states|± with energies E±=−µ±| p whereµis the quark number chemical potential.For energies much lower than the Fermi energyµ,only the states|+ close to the Fermi surface.i.e.with| p|≈µ,can be excited.On the contrary,the states|− have E−≈−2µand therefore decouple.This can be seen more formally by writing the four-momentum of the fermion aspµ=µvµ+ℓµ,(18)where vµ=(0, v F),and v F is the Fermi velocity deﬁned as v F=∂E/∂ p| p= pF .Formassless fermions| v F|=1.Since the hamiltonian for a massless Dirac fermion in a chemical potentialµisH=−µ+ α· p, α=γ0 γ,(19) one hasH=−µ(1− α· v F)+ α· ℓ.(20) Then,it is convenient to introduce the projection operatorsP±=1± α· v F2 ψ(x)= |ℓ|<µd4ℓ2γν 2gµν−Vµ˜Vν−˜VµVν .(26)We notice that theﬁelds appearing in this expression are evaluated at the same Fermi velocity because off-diagonal terms are canceled by the rapid oscillations of the exponential factor in theµ→∞limit.This behavior can be referred to as the Fermi velocity super-selection rule.At the leading order in1/µone hasiiV·Dψ+=0,ψ−=−ψ†+(D/⊥)2ψ+ .(28)2µThe previous remarks apply to any theory describing massless fermions at high density.The next step will be to couple this theory in a SU(3)L⊗SU(3)R⊗SU(3)c invariant way to Nambu-Goldstone bosons(NGB)describing the appropriate breaking for the CFL phase(we will not discuss here the determination of the parameters relevant for the U(1)A,Bﬁelds,see[11]).Using a gradient expansion we get an explicit expression for the decay coupling constant of the Nambu-Goldstone boson as well for their velocity. The invariant coupling between fermions and Goldstoneﬁelds reproducing the sym-metry breaking pattern of eq.(2)is proportional toγ1Tr[ψT LˆX†]C Tr[ψLˆX†]+γ2Tr[ψT L CˆX†ψLˆX†]+h.c.,(29) with an analogous expression for the right-handedﬁelds.Here the spinors are meant to be Dirac spinors.The trace is operating over the group indices of the spinors and of the Goldstoneﬁelds.Since the vacuum expectation value of the Goldstoneﬁelds is ˆX = ˆY =1,we see that this coupling induces the right breaking of the symmetry. In the following we will consider only the caseγ2=−γ1∝∆/2,where∆is the gap parameter.Since the transformation properties under the symmetry group of theﬁelds atﬁxed Fermi velocity do not differ from those of the quarkﬁelds,for both left-handed and right-handedﬁelds we get the effective lagrangian density1L=∑v F√Here λa (a =1,...,8)are the Gell-Mann matrices normalized as follows:Tr (λa λb )=2δab and λ9=8π1V ·p ˜V ·p −∆2A ˜V ·p −∆A −∆A V ·p .(34)We are now in position to evaluate the self-energy of the Goldstone bosons through their coupling to the fermions at the Fermi surface.There are two one-loop contributions[16],one from the coupling Πχχand a tadpole from the coupling ΠΠχχ(see eq.(30).The tadpole diagram contributes only to the mass term and it is essential to cancel the external momentum independent term arising from the other diagram.Therefore,as expected,the mass of the NGB’s is zero.The contribution at the second order in the momentum expansion is given byi 21−8ln24π8∑a =1Πa V ·p ˜V ·p Πa .(35)Integrating over the velocities and going back to the coordinate space we getL kin eff =21−8ln23| ∇Πa |2 .(36)We can now determine the decay coupling constant F T through the requirement of getting the canonical normalization for the kinetic term;this impliesF 2T =µ2(21−8ln2)a result obtained by many authors using different methods(for a complete list of the relevant papers see theﬁrst reference of[2]).We see also that v2=1/3.The other constants appearing in our effective lagrangian can be obtained via a direct calculation of m D and m M[16].This is done evaluating the one-loop contribution to the gluon self-energy.Also in this case there are two contributions,one coming from the gauge coupling to the fermions,whereas the other arises from the next-to leading(inµ)sea-gull contribution to the fermion effective lagrangian in eq.(28).The results weﬁnd are [16,11]1m2D=g2s F2T,m2M=3is a direct consequence of the integration over the Fermi velocity.Therefore it is completely general and applies to all the NGB’s in the theory, including the ones associated to the breaking of U(1)V and U(1)A(v2φ=v2θ=1/3); needless to say that higher order terms in the expansion1/µcould change this result. The breaking of the Lorentz invariance exhibited by the pion velocity different from one,can be seen also in the matrix element 0|J aµ|Πb .Its evaluation gives[16]0|J aµ|Πb =iF Tδab˜pµ,˜pµ=(p0, p/3).(40) The current is conserved,as a consequence of the dispersion relation satisﬁed by NGB’s.THE LOFF PHASEWe shall now consider massless quarks of three colors and two differentﬂavors.Atﬁnite densities we introduce two chemical potentials,µ1andµ2,for the two species in order to mimic the different mass case.We writeµ1−µ2=δµ≪µ=µ1+µ2The condensation in the LOFF phase gives rise to two breaking terms in the fermion lagrangian characterized by two gap parameters∆(s)and∆(v)−12 ˙Φ2−∞∑n=1c n(| ∇Φ|2)n .(44)HereΦmust be thought as a function of the phononﬁeldφ.Using| ∇Φ(x)|2=4q2+4q f2| ∇φ(x)|2,(45)at the lowest order in the derivatives of the phononﬁeldφwe get(neglecting a constant term):L(φ,∂µφ)=1。

用密度函数理论和杜比宁方程研究活性炭纤维多段充填机理

密度函数理论和杜比宁方程可以用来研究活性炭纤维在多段充填过程中的吸附行为。

密度函数理论是一种分子统计力学理论，它建立在分子统计学和热力学的基础上，用来研究一种系统中分子的分布。

杜比宁方程是一种描述分子吸附行为的方程，它可以用来计算吸附层的厚度、吸附速率和吸附能量等参数。

在研究活性炭纤维多段充填过程中，可以使用密度函数理论和杜比宁方程来研究纤维表面的分子结构和吸附行为。

通过分析密度函数和杜比宁方程的解，可以得出纤维表面的分子结构以及纤维吸附的分子的种类、数量和能量。

这些信息有助于更好地理解活性炭纤维的多段充填机理。

在研究活性炭纤维的多段充填机理时，还可以使用其他理论和方法来帮助我们更好地了解这一过程。

例如，可以使用扫描电子显微镜(SEM)和透射电子显微镜(TEM)等技术来观察纤维表面的形貌和结构。

可以使用X射线衍射(XRD)和傅里叶变换红外光谱(FTIR)等技术来确定纤维表面的化学成分和结构。

还可以使用氮气吸附(BET)和旋转氧吸附(BJH)等技术来测量纤维表面的比表面积和孔结构。

通过综合运用密度函数理论、杜比宁方程和其他理论和方法，可以更全面地了解活性炭纤维的多段充填机理，从而更好地控制和优化多段充填的过程。

在研究活性炭纤维多段充填机理时，还可以使用温度敏感性测试方法来研究充填过程中纤维表面的动力学性质。

例如，可以使用动态氧吸附(DAC)或旋转杆氧吸附(ROTA)等技术来测量温度对纤维表面吸附性能的影响。

通过对比不同温度下纤维表面的吸附性能，可以更好地了解充填过程中纤维表面的动力学性质。

此外，还可以使用分子动力学模拟方法来研究纤维表面的吸附行为。

例如，可以使用拉曼光谱或红外光谱等技术来测量纤维表面的分子吸附构型。

然后，使用分子动力学模拟方法来模拟不同分子吸附构型下的纤维表面的动力学性质，帮助我们更好地了解活性炭纤维的多段充填机理。

最近鲁棒优化进展Recent Advances in Robust Optimization and Robustness An Overview

Recent Advances in Robust Optimization and Robustness:An OverviewVirginie Gabrel∗and C´e cile Murat†and Aur´e lie Thiele‡July2012AbstractThis paper provides an overview of developments in robust optimization and robustness published in the aca-demic literature over the pastﬁve years.1IntroductionThis review focuses on papers identiﬁed by Web of Science as having been published since2007(included),be-longing to the area of Operations Research and Management Science,and having‘robust’and‘optimization’in their title.There were exactly100such papers as of June20,2012.We have completed this list by considering 726works indexed by Web of Science that had either robustness(for80of them)or robust(for646)in their title and belonged to the Operations Research and Management Science topic area.We also identiﬁed34PhD disserta-tions dated from the lastﬁve years with‘robust’in their title and belonging to the areas of operations research or management.Among those we have chosen to focus on the works with a primary focus on management science rather than system design or optimal control,which are broadﬁelds that would deserve a review paper of their own, and papers that could be of interest to a large segment of the robust optimization research community.We feel it is important to include PhD dissertations to identify these recent graduates as the new generation trained in robust optimization and robustness analysis,whether they have remained in academia or joined industry.We have also added a few not-yet-published preprints to capture ongoing research efforts.While many additional works would have deserved inclusion,we feel that the works selected give an informative and comprehensive view of the state of robustness and robust optimization to date in the context of operations research and management science.∗Universit´e Paris-Dauphine,LAMSADE,Place du Mar´e chal de Lattre de Tassigny,F-75775Paris Cedex16,France gabrel@lamsade.dauphine.fr Corresponding author†Universit´e Paris-Dauphine,LAMSADE,Place du Mar´e chal de Lattre de Tassigny,F-75775Paris Cedex16,France mu-rat@lamsade.dauphine.fr‡Lehigh University,Industrial and Systems Engineering Department,200W Packer Ave Bethlehem PA18015,USA aure-lie.thiele@2Theory of Robust Optimization and Robustness2.1Deﬁnitions and BasicsThe term“robust optimization”has come to encompass several approaches to protecting the decision-maker against parameter ambiguity and stochastic uncertainty.At a high level,the manager must determine what it means for him to have a robust solution:is it a solution whose feasibility must be guaranteed for any realization of the uncertain parameters?or whose objective value must be guaranteed?or whose distance to optimality must be guaranteed? The main paradigm relies on worst-case analysis:a solution is evaluated using the realization of the uncertainty that is most unfavorable.The way to compute the worst case is also open to debate:should it use aﬁnite number of scenarios,such as historical data,or continuous,convex uncertainty sets,such as polyhedra or ellipsoids?The answers to these questions will determine the formulation and the type of the robust counterpart.Issues of over-conservatism are paramount in robust optimization,where the uncertain parameter set over which the worst case is computed should be chosen to achieve a trade-off between system performance and protection against uncertainty,i.e.,neither too small nor too large.2.2Static Robust OptimizationIn this framework,the manager must take a decision in the presence of uncertainty and no recourse action will be possible once uncertainty has been realized.It is then necessary to distinguish between two types of uncertainty: uncertainty on the feasibility of the solution and uncertainty on its objective value.Indeed,the decision maker generally has different attitudes with respect to infeasibility and sub-optimality,which justiﬁes analyzing these two settings separately.2.2.1Uncertainty on feasibilityWhen uncertainty affects the feasibility of a solution,robust optimization seeks to obtain a solution that will be feasible for any realization taken by the unknown coefﬁcients;however,complete protection from adverse realiza-tions often comes at the expense of a severe deterioration in the objective.This extreme approach can be justiﬁed in some engineering applications of robustness,such as robust control theory,but is less advisable in operations research,where adverse events such as low customer demand do not produce the high-proﬁle repercussions that engineering failures–such as a doomed satellite launch or a destroyed unmanned robot–can have.To make the robust methodology appealing to business practitioners,robust optimization thus focuses on obtaining a solution that will be feasible for any realization taken by the unknown coefﬁcients within a smaller,“realistic”set,called the uncertainty set,which is centered around the nominal values of the uncertain parameters.The goal becomes to optimize the objective,over the set of solutions that are feasible for all coefﬁcient values in the uncertainty set.The speciﬁc choice of the set plays an important role in ensuring computational tractability of the robust problem and limiting deterioration of the objective at optimality,and must be thought through carefully by the decision maker.A large branch of robust optimization focuses on worst-case optimization over a convex uncertainty set.The reader is referred to Bertsimas et al.(2011a)and Ben-Tal and Nemirovski(2008)for comprehensive surveys of robust optimization and to Ben-Tal et al.(2009)for a book treatment of the topic.2.2.2Uncertainty on objective valueWhen uncertainty affects the optimality of a solution,robust optimization seeks to obtain a solution that performs well for any realization taken by the unknown coefﬁcients.While a common criterion is to optimize the worst-case objective,some studies have investigated other robustness measures.Roy(2010)proposes a new robustness criterion that holds great appeal for the manager due to its simplicity of use and practical relevance.This framework,called bw-robustness,allows the decision-maker to identify a solution which guarantees an objective value,in a maximization problem,of at least w in all scenarios,and maximizes the probability of reaching a target value of b(b>w).Gabrel et al.(2011)extend this criterion from aﬁnite set of scenarios to the case of an uncertainty set modeled using intervals.Kalai et al.(2012)suggest another criterion called lexicographicα-robustness,also deﬁned over aﬁnite set of scenarios for the uncertain parameters,which mitigates the primary role of the worst-case scenario in deﬁning the solution.Thiele(2010)discusses over-conservatism in robust linear optimization with cost uncertainty.Gancarova and Todd(2012)studies the loss in objective value when an inaccurate objective is optimized instead of the true one, and shows that on average this loss is very small,for an arbitrary compact feasible region.In combinatorial optimization,Morrison(2010)develops a framework of robustness based on persistence(of decisions)using the Dempster-Shafer theory as an evidence of robustness and applies it to portfolio tracking and sensor placement.2.2.3DualitySince duality has been shown to play a key role in the tractability of robust optimization(see for instance Bertsimas et al.(2011a)),it is natural to ask how duality and robust optimization are connected.Beck and Ben-Tal(2009) shows that primal worst is equal to dual best.The relationship between robustness and duality is also explored in Gabrel and Murat(2010)when the right-hand sides of the constraints are uncertain and the uncertainty sets are represented using intervals,with a focus on establishing the relationships between linear programs with uncertain right hand sides and linear programs with uncertain objective coefﬁcients using duality theory.This avenue of research is further explored in Gabrel et al.(2010)and Remli(2011).2.3Multi-Stage Decision-MakingMost early work on robust optimization focused on static decision-making:the manager decided at once of the values taken by all decision variables and,if the problem allowed for multiple decision stages as uncertainty was realized,the stages were incorporated by re-solving the multi-stage problem as time went by and implementing only the decisions related to the current stage.As theﬁeld of static robust optimization matured,incorporating–ina tractable manner–the information revealed over time directly into the modeling framework became a major area of research.2.3.1Optimal and Approximate PoliciesA work going in that direction is Bertsimas et al.(2010a),which establishes the optimality of policies afﬁne in the uncertainty for one-dimensional robust optimization problems with convex state costs and linear control costs.Chen et al.(2007)also suggests a tractable approximation for a class of multistage chance-constrained linear program-ming problems,which converts the original formulation into a second-order cone programming problem.Chen and Zhang(2009)propose an extension of the Afﬁnely Adjustable Robust Counterpart framework described in Ben-Tal et al.(2009)and argue that its potential is well beyond what has been in the literature so far.2.3.2Two stagesBecause of the difﬁculty in incorporating multiple stages in robust optimization,many theoretical works have focused on two stages.Regarding two-stage problems,Thiele et al.(2009)presents a cutting-plane method based on Kelley’s algorithm for solving convex adjustable robust optimization problems,while Terry(2009)provides in addition preliminary results on the conditioning of a robust linear program and of an equivalent second-order cone program.Assavapokee et al.(2008a)and Assavapokee et al.(2008b)develop tractable algorithms in the case of robust two-stage problems where the worst-case regret is minimized,in the case of interval-based uncertainty and scenario-based uncertainty,respectively,while Minoux(2011)provides complexity results for the two-stage robust linear problem with right-hand-side uncertainty.2.4Connection with Stochastic OptimizationAn early stream in robust optimization modeled stochastic variables as uncertain parameters belonging to a known uncertainty set,to which robust optimization techniques were then applied.An advantage of this method was to yield approaches to decision-making under uncertainty that were of a level of complexity similar to that of their deterministic counterparts,and did not suffer from the curse of dimensionality that afﬂicts stochastic and dynamic programming.Researchers are now making renewed efforts to connect the robust optimization and stochastic opti-mization paradigms,for instance quantifying the performance of the robust optimization solution in the stochastic world.The topic of robust optimization in the context of uncertain probability distributions,i.e.,in the stochastic framework itself,is also being revisited.2.4.1Bridging the Robust and Stochastic WorldsBertsimas and Goyal(2010)investigates the performance of static robust solutions in two-stage stochastic and adaptive optimization problems.The authors show that static robust solutions are good-quality solutions to the adaptive problem under a broad set of assumptions.They provide bounds on the ratio of the cost of the optimal static robust solution to the optimal expected cost in the stochastic problem,called the stochasticity gap,and onthe ratio of the cost of the optimal static robust solution to the optimal cost in the two-stage adaptable problem, called the adaptability gap.Chen et al.(2007),mentioned earlier,also provides a robust optimization perspective to stochastic programming.Bertsimas et al.(2011a)investigates the role of geometric properties of uncertainty sets, such as symmetry,in the power ofﬁnite adaptability in multistage stochastic and adaptive optimization.Duzgun(2012)bridges descriptions of uncertainty based on stochastic and robust optimization by considering multiple ranges for each uncertain parameter and setting the maximum number of parameters that can fall within each range.The corresponding optimization problem can be reformulated in a tractable manner using the total unimodularity of the feasible set and allows for aﬁner description of uncertainty while preserving tractability.It also studies the formulations that arise in robust binary optimization with uncertain objective coefﬁcients using the Bernstein approximation to chance constraints described in Ben-Tal et al.(2009),and shows that the robust optimization problems are deterministic problems for modiﬁed values of the coefﬁcients.While many results bridging the robust and stochastic worlds focus on giving probabilistic guarantees for the solutions generated by the robust optimization models,Manuja(2008)proposes a formulation for robust linear programming problems that allows the decision-maker to control both the probability and the expected value of constraint violation.Bandi and Bertsimas(2012)propose a new approach to analyze stochastic systems based on robust optimiza-tion.The key idea is to replace the Kolmogorov axioms and the concept of random variables as primitives of probability theory,with uncertainty sets that are derived from some of the asymptotic implications of probability theory like the central limit theorem.The authors show that the performance analysis questions become highly structured optimization problems for which there exist efﬁcient algorithms that are capable of solving problems in high dimensions.They also demonstrate that the proposed approach achieves computationally tractable methods for(a)analyzing queueing networks,(b)designing multi-item,multi-bidder auctions with budget constraints,and (c)pricing multi-dimensional options.2.4.2Distributionally Robust OptimizationBen-Tal et al.(2010)considers the optimization of a worst-case expected-value criterion,where the worst case is computed over all probability distributions within a set.The contribution of the work is to deﬁne a notion of robustness that allows for different guarantees for different subsets of probability measures.The concept of distributional robustness is also explored in Goh and Sim(2010),with an emphasis on linear and piecewise-linear decision rules to reformulate the original problem in aﬂexible manner using expected-value terms.Xu et al.(2012) also investigates probabilistic interpretations of robust optimization.A related area of study is worst-case optimization with partial information on the moments of distributions.In particular,Popescu(2007)analyzes robust solutions to a certain class of stochastic optimization problems,using mean-covariance information about the distributions underlying the uncertain parameters.The author connects the problem for a broad class of objective functions to a univariate mean-variance robust objective and,subsequently, to a(deterministic)parametric quadratic programming problem.The reader is referred to Doan(2010)for a moment-based uncertainty model for stochastic optimization prob-lems,which addresses the ambiguity of probability distributions of random parameters with a minimax decision rule,and a comparison with data-driven approaches.Distributionally robust optimization in the context of data-driven problems is the focus of Delage(2009),which uses observed data to deﬁne a”well structured”set of dis-tributions that is guaranteed with high probability to contain the distribution from which the samples were drawn. Zymler et al.(2012a)develop tractable semideﬁnite programming(SDP)based approximations for distributionally robust individual and joint chance constraints,assuming that only theﬁrst-and second-order moments as well as the support of the uncertain parameters are given.Becker(2011)studies the distributionally robust optimization problem with known mean,covariance and support and develops a decomposition method for this family of prob-lems which recursively derives sub-policies along projected dimensions of uncertainty while providing a sequence of bounds on the value of the derived policy.Robust linear optimization using distributional information is further studied in Kang(2008).Further,Delage and Ye(2010)investigates distributional robustness with moment uncertainty.Speciﬁcally,uncertainty affects the problem both in terms of the distribution and of its moments.The authors show that the resulting problems can be solved efﬁciently and prove that the solutions exhibit,with high probability,best worst-case performance over a set of distributions.Bertsimas et al.(2010)proposes a semideﬁnite optimization model to address minimax two-stage stochastic linear problems with risk aversion,when the distribution of the second-stage random variables belongs to a set of multivariate distributions with knownﬁrst and second moments.The minimax solutions provide a natural distribu-tion to stress-test stochastic optimization problems under distributional ambiguity.Cromvik and Patriksson(2010a) show that,under certain assumptions,global optima and stationary solutions of stochastic mathematical programs with equilibrium constraints are robust with respect to changes in the underlying probability distribution.Works such as Zhu and Fukushima(2009)and Zymler(2010)also study distributional robustness in the context of speciﬁc applications,such as portfolio management.2.5Connection with Risk TheoryBertsimas and Brown(2009)describe how to connect uncertainty sets in robust linear optimization to coherent risk measures,an example of which is Conditional Value-at-Risk.In particular,the authors show the link between polyhedral uncertainty sets of a special structure and a subclass of coherent risk measures called distortion risk measures.Independently,Chen et al.(2007)present an approach for constructing uncertainty sets for robust opti-mization using new deviation measures that capture the asymmetry of the distributions.These deviation measures lead to improved approximations of chance constraints.Dentcheva and Ruszczynski(2010)proposes the concept of robust stochastic dominance and shows its applica-tion to risk-averse optimization.They consider stochastic optimization problems where risk-aversion is expressed by a robust stochastic dominance constraint and develop necessary and sufﬁcient conditions of optimality for such optimization problems in the convex case.In the nonconvex case,they derive necessary conditions of optimality under additional smoothness assumptions of some mappings involved in the problem.2.6Nonlinear OptimizationRobust nonlinear optimization remains much less widely studied to date than its linear counterpart.Bertsimas et al.(2010c)presents a robust optimization approach for unconstrained non-convex problems and problems based on simulations.Such problems arise for instance in the partial differential equations literature and in engineering applications such as nanophotonic design.An appealing feature of the approach is that it does not assume any speciﬁc structure for the problem.The case of robust nonlinear optimization with constraints is investigated in Bertsimas et al.(2010b)with an application to radiation therapy for cancer treatment.Bertsimas and Nohadani (2010)further explore robust nonconvex optimization in contexts where solutions are not known explicitly,e.g., have to be found using simulation.They present a robust simulated annealing algorithm that improves performance and robustness of the solution.Further,Boni et al.(2008)analyzes problems with uncertain conic quadratic constraints,formulating an approx-imate robust counterpart,and Zhang(2007)provide formulations to nonlinear programming problems that are valid in the neighborhood of the nominal parameters and robust to theﬁrst order.Hsiung et al.(2008)present tractable approximations to robust geometric programming,by using piecewise-linear convex approximations of each non-linear constraint.Geometric programming is also investigated in Shen et al.(2008),where the robustness is injected at the level of the algorithm and seeks to avoid obtaining infeasible solutions because of the approximations used in the traditional approach.Interval uncertainty-based robust optimization for convex and non-convex quadratic programs are considered in Li et al.(2011).Takeda et al.(2010)studies robustness for uncertain convex quadratic programming problems with ellipsoidal uncertainties and proposes a relaxation technique based on random sampling for robust deviation optimization sserre(2011)considers minimax and robust models of polynomial optimization.A special case of nonlinear problems that are linear in the decision variables but convex in the uncertainty when the worst-case objective is to be maximized is investigated in Kawas and Thiele(2011a).In that setting,exact and tractable robust counterparts can be derived.A special class of nonconvex robust optimization is examined in Kawas and Thiele(2011b).Robust nonconvex optimization is examined in detail in Teo(2007),which presents a method that is applicable to arbitrary objective functions by iteratively moving along descent directions and terminates at a robust local minimum.3Applications of Robust OptimizationWe describe below examples to which robust optimization has been applied.While an appealing feature of robust optimization is that it leads to models that can be solved using off-the-shelf software,it is worth pointing the existence of algebraic modeling tools that facilitate the formulation and subsequent analysis of robust optimization problems on the computer(Goh and Sim,2011).3.1Production,Inventory and Logistics3.1.1Classical logistics problemsThe capacitated vehicle routing problem with demand uncertainty is studied in Sungur et al.(2008),with a more extensive treatment in Sungur(2007),and the robust traveling salesman problem with interval data in Montemanni et al.(2007).Remli and Rekik(2012)considers the problem of combinatorial auctions in transportation services when shipment volumes are uncertain and proposes a two-stage robust formulation solved using a constraint gener-ation algorithm.Zhang(2011)investigates two-stage minimax regret robust uncapacitated lot-sizing problems with demand uncertainty,in particular showing that it is polynomially solvable under the interval uncertain demand set.3.1.2SchedulingGoren and Sabuncuoglu(2008)analyzes robustness and stability measures for scheduling in a single-machine environment subject to machine breakdowns and embeds them in a tabu-search-based scheduling algorithm.Mittal (2011)investigates efﬁcient algorithms that give optimal or near-optimal solutions for problems with non-linear objective functions,with a focus on robust scheduling and service operations.Examples considered include parallel machine scheduling problems with the makespan objective,appointment scheduling and assortment optimization problems with logit choice models.Hazir et al.(2010)considers robust scheduling and robustness measures for the discrete time/cost trade-off problem.3.1.3Facility locationAn important question in logistics is not only how to operate a system most efﬁciently but also how to design it. Baron et al.(2011)applies robust optimization to the problem of locating facilities in a network facing uncertain demand over multiple periods.They consider a multi-periodﬁxed-charge network location problem for which they ﬁnd the number of facilities,their location and capacities,the production in each period,and allocation of demand to facilities.The authors show that different models of uncertainty lead to very different solution network topologies, with the model with box uncertainty set opening fewer,larger facilities.?investigate a robust version of the location transportation problem with an uncertain demand using a2-stage formulation.The resulting robust formulation is a convex(nonlinear)program,and the authors apply a cutting plane algorithm to solve the problem exactly.Atamt¨u rk and Zhang(2007)study the networkﬂow and design problem under uncertainty from a complexity standpoint,with applications to lot-sizing and location-transportation problems,while Bardossy(2011)presents a dual-based local search approach for deterministic,stochastic,and robust variants of the connected facility location problem.The robust capacity expansion problem of networkﬂows is investigated in Ordonez and Zhao(2007),which provides tractable reformulations under a broad set of assumptions.Mudchanatongsuk et al.(2008)analyze the network design problem under transportation cost and demand uncertainty.They present a tractable approximation when each commodity only has a single origin and destination,and an efﬁcient column generation for networks with path constraints.Atamt¨u rk and Zhang(2007)provides complexity results for the two-stage networkﬂow anddesign plexity results for the robust networkﬂow and network design problem are also provided in Minoux(2009)and Minoux(2010).The problem of designing an uncapacitated network in the presence of link failures and a competing mode is investigated in Laporte et al.(2010)in a railway application using a game theoretic perspective.Torres Soto(2009)also takes a comprehensive view of the facility location problem by determining not only the optimal location but also the optimal time for establishing capacitated facilities when demand and cost parameters are time varying.The models are solved using Benders’decomposition or heuristics such as local search and simulated annealing.In addition,the robust networkﬂow problem is also analyzed in Boyko(2010),which proposes a stochastic formulation of minimum costﬂow problem aimed atﬁnding network design andﬂow assignments subject to uncertain factors,such as network component disruptions/failures when the risk measure is Conditional Value at Risk.Nagurney and Qiang(2009)suggests a relative total cost index for the evaluation of transportation network robustness in the presence of degradable links and alternative travel behavior.Further,the problem of locating a competitive facility in the plane is studied in Blanquero et al.(2011)with a robustness criterion.Supply chain design problems are also studied in Pan and Nagi(2010)and Poojari et al.(2008).3.1.4Inventory managementThe topic of robust multi-stage inventory management has been investigated in detail in Bienstock and Ozbay (2008)through the computation of robust basestock levels and Ben-Tal et al.(2009)through an extension of the Afﬁnely Adjustable Robust Counterpart framework to control inventories under demand uncertainty.See and Sim (2010)studies a multi-period inventory control problem under ambiguous demand for which only mean,support and some measures of deviations are known,using a factor-based model.The parameters of the replenishment policies are obtained using a second-order conic programming problem.Song(2010)considers stochastic inventory control in robust supply chain systems.The work proposes an inte-grated approach that combines in a single step dataﬁtting and inventory optimization–using histograms directly as the inputs for the optimization model–for the single-item multi-period periodic-review stochastic lot-sizing problem.Operation and planning issues for dynamic supply chain and transportation networks in uncertain envi-ronments are considered in Chung(2010),with examples drawn from emergency logistics planning,network design and congestion pricing problems.3.1.5Industry-speciﬁc applicationsAng et al.(2012)proposes a robust storage assignment approach in unit-load warehouses facing variable supply and uncertain demand in a multi-period setting.The authors assume a factor-based demand model and minimize the worst-case expected total travel in the warehouse with distributional ambiguity of demand.A related problem is considered in Werners and Wuelﬁng(2010),which optimizes internal transports at a parcel sorting center.Galli(2011)describes the models and algorithms that arise from implementing recoverable robust optimization to train platforming and rolling stock planning,where the concept of recoverable robustness has been deﬁned in。

energy position Ec Ev of semiconductors

American Mineralogist, Volume 85, pages 543–556, 20000003-004X/00/0304–543$05.00543I NTRODUCTIONThe importance of synthetic semiconductors to chemical and industrial processes has spurred a large research effort to understand the fundamentals of photochemical processes and to develop new photocatalysts. For example, synthetic photocatalysts can promote processes such as photodecompo-sition of organic and inorganic contaminants (Borgarello et al.1988; Brinkley and Engel 1998; Fox 1988; Pelizzetti et al. 1988;Serpone et al. 1988a, 1988b), photosynthesis of organic com-pounds from carbon dioxide and other inorganic substrates (Anpo et al. 1997; Inoue et al. 1979; Kanemoto et al. 1996),photodecomposition of water to hydrogen and oxygen (Lauermann et al. 1987; Reber and Meier 1984), and photore-duction of dinitrogen to ammonia (Augugliaro and Palmisano 1988; Bickley et al. 1988; Schrauzer and Guth 1977; Soria et al. 1991).In contrast, there has been relatively little research on the photocatalytic properties of mineral semiconductors. There is,however, a growing recognition of the role semiconducting minerals may play as catalysts of redox reactions in natural environments and engineered systems designed to degrade haz-ardous chemicals (Schoonen et al. 1998; Selli et al. 1996;Stumm and Morgan 1995; Sulzberger 1990). Hence, the ques-The absolute energy positions of conduction and valence bands ofselected semiconducting mineralsY ONG X U AND M ARTIN A.A. S CHOONEN *Department of Geosciences, State University of New York at Stony Brook, Stony Brook, New York 11794-2100, U.S.A.A BSTRACTThe absolute energy positions of conduction and valence band edges were compiled for about 50each semiconducting metal oxide and metal sulfide minerals. The relationships between energy levels at mineral semiconductor-electrolyte interfaces and the activities of these minerals as a cata-lyst or photocatalyst in aqueous redox reactions are reviewed. The compilation of band edge ener-gies is based on experimental flatband potential data and complementary empirical calculations from electronegativities of constituent elements. Whereas most metal oxide semiconductors have valence band edges 1 to 3 eV below the H 2O oxidation potential (relative to absolute vacuum scale),energies for conduction band edges are close to, or lower than, the H 2O reduction potential. These oxide minerals are strong photo-oxidation catalysts in aqueous solutions, but are limited in their reducing power. Non-transition metal sulfides generally have higher conduction and valence band edge energies than metal oxides; therefore, valence band holes in non-transition metal sulfides are less oxidizing, but conduction band electrons are exceedingly reducing. Most transition-metal sul-fides, however, are characterized by small band gaps (<1 eV) and band edges situated within or close to the H 2O stability potentials. Hence, both the oxidizing power of the valence band holes and the reducing power of the conduction band electrons are lower than those of non-transition metal sulfides.tion arises of whether semiconducting minerals could promote these same processes. If so, these minerals could play an im-portant role in the fate of contaminants and the chemical com-positions of atmosphere and hydrosphere of the early earth. Although all the processes mentioned above are photo-chemical processes, there is also evidence for non-photolytic catalysis of redox reactions by semiconductors (Xu 1997; Xu and Schoonen 1995; Xu et al. 1996, 1999). Semiconductors can act as a conduit for electrons between the aqueous reac-tants. Because no illumination is needed for non-photo cata-lytic processes, this mechanism may be important beneath the photic zone in aquatic systems.In photochemical reactions, as well as the non-photochemi-cal mechanism outlined in our earlier work, the crucial step is the transfer of electrons between the semiconductor and sorbed reactants. As pointed out by Morrison (1990), electrons can only be transferred between those energetic states in the semi-conductor and the electrolyte that are at approximately the same energy level. The energy level of energetic states of sorbates undergoing an electron transfer can be approximated by the standard redox potential (E 0), whereas relevant energy levels for a semiconductor are the top of the valence band (E V ) and the bottom of the conduction band (E C ). The relative energet-ics of E V and E C vs. E 0 is the fundamental property of an elec-trolyte/semiconductor system that dictates whether an electron transfer between the semiconductor and sorbate is feasible.Although band gap (E g ) is well known for most semicon-ductors, unfortunately, E V and E C have not been determined ac-*E-mail: mschoonen@XU AND SCHOONEN: SEMICONDUCTING OXIDES AND SULFIDES544curately for most semiconducting minerals. Furthermore, E V and E C values are often presented in ways that prevent a straight-forward comparison to the redox potentials of aqueous elec-trolytes. For example, in both the materials science and applied physics literature, it is customary to express the energy posi-tion of band edges with respect to the energy level midway in the band gap of the material (i.e., the Fermi level of the mate-rial), rather than on the absolute vacuum scale (AVS). In con-trast, geochemical and electrochemical literature typically reports standard redox potentials for aqueous redox couples with respect to the normal hydrogen electrode (NHE). To com-pare the energy levels of sorbates to the band edges of a semi-conductor, however, it is necessary to have all energy levels of interest (i.e., E 0, E C , E V ) expressed on a common energy scale,such as the absolute vacuum scale or the normal hydrogen elec-trode scale.The objective here is to (1) provide a compilation of the absolute energy positions of valence and conduction band edges of semiconducting metal oxide and metal sulfide minerals and (2) address the relationship between these energy positions and the catalytic activities of these minerals in various heteroge-neous electron transfer processes. For those minerals for which band edge energies have not been determined experimentally,the band edge energies were calculated using an empirical re-lationship based on the electronegativity of the elements (But-ler and Ginley 1978). More extensive reviews on the interactions between semiconductor and electrolyte and photochemistry involving semiconductors can be found elsewhere (Balzani and Scandola 1989; Bockris and Khan 1993; Grätzel 1988; Kish 1989; Lewis and Rosenbluth 1989; Mills and Le Hunte 1997;Nozik and Memming 1996; Morrison 1990; Nozik 1978; Smithand Nozik 1997; Stumm and Morgan 1995; Stumm and Sulzberger 1992; Waite 1990).T HEORETICAL BACKGROUNDEnergetics of semiconductor/electrolyte interfaces For the purpose of this study we briefly review the elec-tronic band structure of semiconductors and the energetics of the semiconductor/electrolyte interface. Comprehensive treat-ments of this topic are by Bockris and Khan (1993), Grätzel (1989), Morrison (1990), and Nozik (1978).The electronic structure of semiconductors is characterized by the presence of a bandgap (E g ), which is essentially an en-ergy interval with very few electronic states (i.e., low density of states) between the valence band and the conduction band,which each have a high density of states (Borg and Dienes 1992). In the context of electron transfer between semiconduc-tors and aqueous redox species, it is crucial to identify the high-est occupied and the lowest unoccupied electronic levels in the semiconductor because those are the energy levels involved in the transfer. In most semiconductors, all electronic levels in the valence band are occupied whereas the levels in the con-duction band are empty. Hence, the highest occupied electronic level coincides with the top of the valence band. The energy of valence band edge, E V , is a measure of the ionization potential,I , of the bulk material. The lowest unoccupied electronic level in most semiconductors coincides with the bottom of the con-duction band. Where the band edge energy, E C , is a measure of the electron affinity, A , of the compound. The Fermi level or energy, E F , represents the chemical potential of electrons in a semiconductor. In essence, the Fermi level is the absolute elec-tronegativity, –χ, of a pristine semiconductor, a value whichF IGURE 1. (a ) Position of the conduction band edge (E C ), the valence band edge (E V ) and the intrinsic Fermi level (E F ) of a semiconductor with respect to vacuum as the zero energy reference. A is electron affinity; χ is electronegativity; I is ionization energy; E g is band gap. (b )Position of energy levels at the interface of an n-type semiconductor and an aqueous electrolyte on the absolute vacuum energy scale (AVS) and with respect to normal hydrogen electrode (NHE). The E CS and E VS represent the conduction band edge and valence band edge at the interface;U ft is the flatband potential; V H is the potential drop of the Helmholtz layer; V B is the band bending; E F is the Fermi level of the system at equilibrium; ΔE F is the difference between the Fermi level and the conduction band edge; E 0F,redox , is the standard Fermi level of the redox couple; E unoc and E oc , are energies of unoccupied states and occupied states of the redox couple; and λis the reorganization energy.XU AND SCHOONEN: SEMICONDUCTING OXIDES AND SULFIDES 545corresponds to the energy halfway between the conduction and valence band edges (Fig. 1a). The relationship between band edge energies and electronegativity can be expressed as:E C = –A = –χ + 0.5 E g (1a)andE V = –I = –χ –0.5 E g(1b)Incorporation of impurities in the structure of a semiconductor leads to the presence of electron acceptor state levels and/or donor state levels within the bandgap. The presence of donor or acceptor state levels changes the position of E F so that E F lies just above E V for p -type semiconductors (presence of ac-ceptor states) and E F lies just below E C for n -type semiconduc-tors (presence of donor states) (Morrison 1990).The next step is to define the energy levels of sorbates. Aque-ous redox species exchanging electrons with a semiconductor mineral can either accept (A + e – → A –) or donate (D → D + + e –)electrons. Upon electron transfer from or to an aqueous species,the electronic structure of the species changes. Upon the accep-tance of an electron, a previously unoccupied electronic level becomes occupied, whereas upon electron donation an elec-tron is removed from an occupied level. For an electron accep-tor (A/A –), it is the energy level of the lowest unoccupied level,E unoc , that is of importance, whereas for an electron donor (D/D +)the highest occupied energy level, E oc , is of importance. Because of the polar nature of water molecules, H 2O dipoles in the solva-tion shell of a redox species will re-orientate when there is a change in the charge of the redox species. The re-orientation of the solvation shell will result in an addition energy gain or loss when an electron is transferred from or to an aqueous redox spe-cies. The free energy change associated with this re-orientation process is known as reorganization energy (λ). V alues for λ range from a few tenths of an eV up to 2 eV . Furthermore, thermal fluctuation of the solvation structure cause a corresponding ther-mal distribution of the energy levels of both E oc and E unoc , see Figure 1b (Bockris and Khan 1993; Grätzel 1989; Morrison 1990). Whereas these energy distributions are difficult to quan-tify, it is helpful to make use of the notion that the redox poten-tial, E redox , of a redox couple undergoing a one-electron transition (e.g., A/A – or D/D +) lies midway between the maxima in E oc and E unoc for these species. The Fermi level of electrons of a redox couple (E F,redox ) is equivalent to the redox potential of aqueous redox couples (E redox ) on the absolute energy scale; hence, this can be expressed as:E E E T a a F,A/A A/A A/A oA AR −−−−==+ln()(2a)E E E T a a F D/D D/D D/D o D DR +,ln()+++==+(2b)where E 0 is the standard redox potential of the aqueous redox couple with respect to the Normal Hydrogen Electrode (NHE).The Fermi level of NHE at 25 °C is –4.5 eV with respect to the vacuum level (Bockris and Khan 1993).The distribution of energy states in a redox couple (Fig. 1b)becomes more complicated if the redox couple undergoes a multi-electron tranfer, because each one-electron step has apopulation of two energy states (E oc and E unoc ) associated withit. Instead of standard redox potential of the overall reaction,the standard potential of each one-electron steps should be con-sidered for a multi-electron transfer reaction. So for a two-elec-tron transition, such as CO 2 + 2e – + 2H + = HCOOH, the standard potentials of the CO 2/CO 2·– and CO 2·–/HCOOH redox couples should be used (CO 2·– represents a CO 2 radical group with a charge of –1). The standard redox potentials for the one-elec-tron steps are mostly unavailable because the intermediate prod-ucts are often unstable. Using E 0 for the overall reaction invariably leads to a misleading comparison of energy levels between semiconductor and aqueous species. This arises from the fact that E 0 for the overall reaction does not lie midway between the maximum of E oc and E unoc populations associated with each of the one-electron transitions. For example, E 0 forCO 2/CO 2·–is estimated to lie at –2 V (NHE), whereas E 0 for CO 2/HCOOH equals –0.61 V(NHE) (Tributsch 1989).When a semiconductor is placed in a solution containing redox species, electrons will be transferred across the semi-conductor/electrolyte interface until the chemical potentials,i.e., Fermi levels, of electrons in the solid and the solution are equalized. The interfacial electron transfer generates a space charge layer in the semiconductor, and conduction and valence band edges are bent such that a potential barrier is established against further electron transfer across the interface. As a re-sult, the energies of conduction and valence band edges at the semiconductor/electrolyte interface, (E CS and E VS , respectively),deviate from their bulk values (E C and E V ). The difference be-tween E CS and E C or E V and E VS is known as band bending, V B (Fig. 1b). The thickness of the space charge layer typically ranges from 100 Å to several microns depending on the con-ductivity of the semiconductor and the amount of band bend-ing. On the solution side of the interface, the Helmholtz double layer will develop due to the sorption of counter-ions onto the charged surface of the semiconductor. The thickness of the Helmholtz layer is typically on the order of 1 Å (Morrison 1990). The Helmholtz layer results in an additional potential drop inside the semiconductor space charge layer so that the band bending adjusts to make the net rate of electron transfer across the interface equal to zero at equilibrium. Hence, the band edge positions of the semiconductor at the interface can-not be determined unless the additional potential drop associ-ated with the Helmholtz layer is quantified (Morrison 1990).To link the energy levels of the semiconductor and the elec-trolyte, an experimentally measurable quantity, flatband po-tential (U ft ), is essential. U ft is the electrode potential measured with respect to a reference electrode (e.g., normal hydrogen electrode, NHE) in an electrolyte/semiconductor system when the potential drop across the space charge layer becomes zero.U ft can be expressed as (Nozik 1978):U ft (NHE) = A + ΔE F + V H + E 0( 3)where ΔE F is the difference between the Fermi level and ma-jority carrier band edge (E C for a n-type semiconductor, and E V for a p-type semiconductor), V H is the potential drop across the Helmholtz layer, and E 0 is the scale factor relating the refer-ence electrode redox level to the A VS (E 0 = –4.5 V for NHE,Bockris and Khan 1993). Because U ft is determined not onlyXU AND SCHOONEN: SEMICONDUCTING OXIDES AND SULFIDES 546by intrinsic properties of the semiconductor (A andΔE F), but also by the electrolyte (V H), U ft is a property of the interface.Note that V H is fixed and independent of both the externally applied voltage across the semiconductor-electrolyte interface and the changes in redox condition of the system, provided the composition changes associated with electron transfer do not affect the equilibrium distribution of ions adsorbed onto the semiconductor. The independence of V H on the interfacial charge transfer is caused by the high charge density and small width of the Helmholtz layer relative to the semiconductor space charge layer (Morrison 1990). As a result, the potential drop across the interface caused by the electron transfer occurs pre-dominantly within the semiconductor space charge layer, whereas the V H remains essentially constant. Consequently, at a given electrolyte composition and semiconductor, U ft is a characteristic parameter independent of the electron transfer process. On the other hand, the potential drop within the Helmholtz layer depends on the adsorption/desorption equi-librium of electrolyte ions at the semiconductor surface. When the net adsorbed charge within the Helmholtz layer is zero, i.e., at the zero point of charge, (pH ZPC), V H is also zero. The flatband potential at the pH ZPC (U ft0) equals the intrinsic Fermi level of the semiconductor, and is the only meaningful flatband potential. Under conditions other than pH ZPC, flatbands are not really flat but contain the band bending induced by the Helmholtz layer. Hence, band edge energies can be calculated from U ft0measurements combined with E g data and an inde-pendent estimate of ΔE F (Nozik 1978).pH Dependence of band edges at semiconductor/electro-lyte interfacesFor semiconducting metal oxides, U ft varies with pH fol-lowing a linear relation known as the Nernstian relation (But-ler and Ginley 1978; Halouani and Deschavres 1982; Matsumoto et al. 1989; Morrison 1990):U fb = U fb0 + 2.303R T/(pH ZPC – pH)F(4) where R is the gas constant, T is temperature, and F is the Fara-day constant. At 25 °C and 1 atm, the Nernstian relation leads to a variation of 0.059 V/pH (Fig. 2a). It is generally accepted that the Nernstian dependence indicates that H+ and OH– are potential determining ions (PDI) adsorbed on the solid surface within the Helmholtz layer (Butler and Ginley 1978).For metal-sulfide semiconductors, the pH dependence of U fb appears more complicated than that for metal-oxides, and has not been as thoroughly studied. One unresolved issue is which ions are PDIs. If ions other than H+ and OH– are PDIs, the specific sorption of these ions can affect V H. For example, Ginley and Butler (1978) showed that dissolved sulfide (H2S and HS–) is a PDI for CdS, whereas our research has shown that dissolved sulfide and dissolved ferrous iron are PDIs for iron sulfides (Bebié et al. 1998; Dekkers and Schoonen 1994). For CdS, the flat band shows a variation in pH dependence from 0 to 59 mV/pH (Ginley and Butler 1978), with the slope depending on the concentrations of metal ions and dissolved sulfide ions. Minoura et al. (1977) reported that U ft varies with crystal face. For FeS2 and ZnS, however, the pH dependence is reported to be consistent with the Nernstian relation (Chen et al. 1991; Fan et al. 1983). We speculate that U ft for metal sul-fide semiconductors may follow the Nernstian pH dependence in aqueous solutions with low concentrations of metal ions and/ or dissolved sulfide, but that the pH dependence will switch to non-Nernstian behavior when specific sorption of metal ions and sulfide becomes important. More research in the surface chemistry of metal sulfides is needed to resolve the apparent inconsistencies highlighted above.The pH-E H relationship defined by the Nernstian slope is characterized by a constant fugacity of hydrogen, as illustrated in Figure 2b:log.fE FTHH2pHR=−−222303(5a) orlog f peH222=−−pH(5b) The constant hydrogen fugacity defined by the Equations 5a or 5b indicates a constant redox state for a linear combination of pH and E H in the Nernstian slope. On a pH-E H diagram, it is the linear combination of E H(or pe) and pH that describes the re-dox state of an aqueous redox system and not E H (or pe) alone; see also Anderson and Crerar (1993). Hence, we believe that the pH dependence of semiconductor flatband potential given by the Nernstian slope is consistent with a constant reducingF IGURE 2. pH dependence of the conduction band edge and valence band edge of pyrite in an aqueous electrolyte solution described by (a), a pH-Eh diagram, and (b) a pH-log f H2diagram. The E C and E V follow the Nernstian relation, which has a variation of 0.059V/pH at 25 °C at 1atm, and lies parallel to the water stability limits.XU AND SCHOONEN: SEMICONDUCTING OXIDES AND SULFIDES547 (oxidizing) power of the (photo)electrons (holes) in a semi-conductor. It is noteworthy that the flat-band potentials forsemiconductors are parallel to the stability limits of water inan E H-pH diagram if they follow the Nernstian behavior. Iflog f H2 is used as the parameter defining the redox conditionof a semiconductor/electrolyte system, as shown in Figure 2b, both the band edges and water stability limits are inde-pendent of pH. Hence, a pH-E H pair can be replaced with a single variable, the fugacity of hydrogen, to define the redox condition of the system.Temperature and pressure dependence of band edge energiesBecause semiconductors can catalyze non-photoreactions as well as photoreactions, their catalytic activity may extend to subsurface geochemical processes, such as in hydrothermal systems. To evaluate the potential of semiconductors as cata-lysts in subsurface environments, it is important to understand the effects of temperature and pressure on the band energies.In contrast to aqueous redox couples, which often show a considerable temperature dependence for E redox, the electronic structure of a semiconductor undergoes little change with tem-perature and pressure provided that no phase transition occurs. For example, the measured bandgap changes over temperature (d E g/d T) for PbS and ZnO range from +4 × 10–4 eV/K to –9.5 ×10–4 eV/K, respectively (Gonzalez et al. 1995). For most semi-conductors, the variation of the bandgap with pressure is also very small in the pressure ranges of interest. The experimental determined variation rates (d E g/d P) are in the order of 0.01–0.1 eV/GPa (Gonzalez et al. 1995). Therefore, the reducing power of a (photo)electron and the oxidation power of a hole are essentially constant with temperature and pressure, unless the solid itself undergoes a phase transition and changes the electronic structure altogether.Although temperature and pressure have negligible effect on the bulk band structure of semiconductors in the T-P ranges of interest, they may have a more pronounced effect on inter-facial energetics. As shown in Equation 4 the Nernstian slope is temperature dependent. Perhaps more importantly, the pH ZPC of semiconductors is also temperature dependent. Schoonen (1994) estimated pH ZPC values for several metal oxides up to 350 °C based on extrapolation of low-temperature (<95 °C) experimental data. These calculations indicate that pH ZPC values shift down by 1 to 2 pH units as temperature rises from 25 °C to 200 to 300 °C, but beyond 200 to 300 °C the pH ZPC shifts back to higher values. This general trend was confirmed experimentally for rutile up to 250 °C by Machesky et al. (1994). A 2-pH-unit decrease in pH ZPC between 25 and 250 °C would result in a shift of interfacial band edge energies to a higher energy level (with respect to vacuum) by about 0.25 eV. However, the exact tem-perature dependence of pH ZPC of semiconductors is largely un-known and more experimental investigations are needed.B AND EDGES OF SEMICONDUCTING OXIDE ANDSULFIDE MINERALSThe conduction band edges and bandgaps for common ox-ide and sulfide semiconducting minerals are given in Tables 1 and 2. This compilation includes data obtained from two dif-ferent methods: photo-electrochemical measurements, and empirical calculation based on electronegativity of constituent atoms. A comparison of experimental and empirically calcu-lated conduction band edges is shown in Figure 3. The trends in the energy positions of band edges for metal oxides and metal sulfides will be discussed below separately. Determination methodsBand edges can be derived experimentally from the flatband potential measurement using various (photo)electrochemical techniques. The classic method for flatband potential determi-nation, which is still considered as the most reliable technique, is the Schottky-Mott method (Nozik 1978). Another common method is the determination of anodic photocurrent onset po-tential by evaluating the photocurrent-potential plot (Arico et al. 1990; Butler 1977). More recently, the photocurrent-volt-age measurements have been extensively used in semiconduc-tor particle systems with electrochemical charge-collection techniques. The advantage of this technique is that the varia-tion of the steady-state photocurrent can be measured as a func-tion of pH. This allows for the estimation of interfacial energetics of the particulate system (Chen et al. 1991; Leland and Bard 1987). It is noteworthy that colloidal particles have a larger bandgap than large crystals due to the quantum size ef-fect, which results in a higher energy position of the conduc-tion band edge (Ward and Bard 1982).In the last two decades, quantitative quantum mechanical calculations have been carried out for a large number ofsemiconductor minerals (Folkerts et al. 1987; Huang and ChingF IGURE 3. Correlation between the empirically calculated conduction band edge energy and the measured flatband potential at pH ZPC for semiconducting metal oxide and sulfide minerals in absolute vacuum scale. The sources of the experimental data are given in the Tables 1 and 2.XU AND SCHOONEN: SEMICONDUCTING OXIDES AND SULFIDES5481993; Lauer et al. 1984; Santoni et al. 1992; Schroer et al. 1993;Temmerman et al. 1993). In principle, band energies can be derived from these calculations. In many studies, however, band edges are presented with the Fermi level as an arbitrary refer-ence point. Hence, although detailed electronic structures of valence and conduction band have been derived, absolute en-ergies of band edges with respect to vacuum cannot be obtained from these calculations. In the few reports in which the abso-T ABLE 1. Absolute electronegativity (x ), band gap (E g ), energy levels of caluculated conduction band edge (E CB ) and flatband potentialat pH ZPC (U ft 0) with respect to Absolute Vacuum Scale (AVS), and measured or estimated pH ZPC for semiconducting metal oxide mineralsMineralx E g E CB U ft0PH ZPC Ref. for Ref. foreV eV eV eV E g ,U ft 0pH ZPCAg 2O 5.29 1.20–4.6911.20a aAlTiO 35.44 3.60–3.648.23b BaTiO 3 5.12 3.30–4.58–4.219.00c aBi 2O 36.23 2.80–4.83–4.82 6.20d CdO 5.71 2.20–4.61–4.6211.60c aCdFe 2O 45.83 2.30–4.68–4.897.22c Ce 2O 35.20 2.40–4.008.85i CoO 5.69 2.60–4.397.59bCoTiO 35.76 2.25–4.647.41k Cr 2O 35.68 3.50–3.938.10b a CuO 5.81 1.70–4.96–4.899.50c aCu 2O5.32 2.20–4.228.53e CuTiO 35.81 2.99–4.327.29k FeO 5.53 2.40–4.338.00bFe 2O 35.88 2.20–4.78–4.698.60c a Fe 3O 45.780.10–5.736.50f a FeOOH 6.38 2.60–5.089.70g lFeTiO 35.69 2.80–4.29–4.566.30a a Ga 2O 35.35 4.80–2.958.47b HgO6.08 1.90–5.137.30b a Hg 2Nb 2O 7 6.21 1.80–5.31–5.05 6.25hHg 2Ta 2O 76.24 1.80–5.34 6.17h In 2O 35.28 2.80–3.888.64b KNbO 3 5.29 3.30–3.648.62bKTaO 35.32 3.50–3.57–3.708.55h La 2O 35.28 5.50–2.5310.40i m LaTi 2O 7 5.90 4.00–3.907.06bLiNbO 35.52 3.50–3.778.02b LiTaO 35.55 4.00–3.557.94b MgTiO 3 5.60 3.70–3.757.81b MnO 5.29 3.60–3.498.61bMnO 25.950.25–5.83 4.60j l MnTiO 3 5.59 3.10–4.047.83bNb 2O 56.29 3.40–4.59–4.16 6.06h Nd 2O 35.21 4.70–2.878.81i NiO 5.75 3.50–4.0010.30b a NiTiO 3 5.79 2.18–4.707.34d PbO 5.42 2.80–4.02–4.468.29d PbFe 12O 19 5.85 2.30–4.70–5.207.17c PdO 5.79 1.00–5.297.34bPr 2O 35.19 3.90–3.248.87i Sb 2O 36.32 3.00–4.82 5.98bSm 2O 35.26 4.40–3.078.69i SnO 5.69 4.20–3.597.59b SnO 26.25 3.50–4.50–4.55 4.30d aSrTiO 34.94 3.40–3.24–3.618.60c a Ta 2O 56.33 4.00–4.33–3.89 2.90a a Tb 2O 3 5.33 3.80–3.448.50iTiO 25.81 3.20–4.21–4.16 5.80k a Tl 2O 35.35 1.60–4.558.47b V 2O 56.10 2.80–4.70–4.84 6.54cWO 36.59 2.70–5.24–5.290.43a a Yb2O 35.47 4.90–3.028.15i YFeO 3 5.60 2.60–4.30–4.607.81a ZnO 5.79 3.20–4.19–3.918.80d aZnTiO 35.80 3.06–4.277.31k ZrO 2 5.91 5.00–3.41–3.086.70a aNotes: a = Butler and Ginley 1978; b = Quarto et al. 1997; c = Nozik 1978; d = Halouani and Deschavers 1982; e = Rodriguez et al. 1998; f = Zhang and Satpathy 1991; g = Brezonik 1993; h = Kung et al. 1977; i = Shelykh et al. 1996; j = Shuey 1975; k = Oosawa et al. 1989; l = Sverjensky 1994,m = Yoon et al. 1979.lute band energies were given, the discrepancies between cal-culated and measured band edges were as large as a few eV (Bullett 1982; Caldas et al. 1984; Fazzio et al. 1984; Tian and Shen 1989).In a much simpler approach, Butler and Ginley (1978) pro-posed that band edges at the semiconductor/electrolyte inter-face can be predicted from the electronegativity of the semiconductor. This method was based on Equations 4 and 5。

等离激元共振峰英文

等离激元共振峰英文全文共四篇示例，供读者参考第一篇示例：Plasmon Resonance PeakIntroductionPlasmon resonance is a collective oscillation of free electrons in a material that occurs when the frequency of incident light matches the natural frequency of the electrons in the material. This phenomenon is often observed in metallic nanoparticles, where the conduction electrons can be excited by incident electromagnetic radiation. One of the most prominent features of plasmon resonance is the appearance of a distinct peak in the absorption or scattering spectra of the material, known as the plasmon resonance peak or plasmon resonance band.第二篇示例：Plasmon resonance refers to the collective oscillation of free electrons in a metal when it is subjected to electromagnetic radiation. This phenomenon, also known as surface plasmon resonance (SPR), has been extensively studied and applied invarious fields such as sensing, imaging, and light manipulation. One of the key features of plasmon resonance is the emergence of a characteristic peak in the absorption or scattering spectrum, known as the plasmon resonance peak or plasmon resonance band. In this article, we will focus on a specific type of plasmon resonance peak – the localized surface plasmon resonance peak, which is commonly referred to as the plasmon resonance peak.第三篇示例：Plasmonic resonance peak, also known as localized surface plasmon resonance (LSPR) peak, is a phenomenon in which free electrons in a metal nanoparticle oscillate collectively in response to incident light. This oscillation creates a strong electromagnetic field enhancement around the nanoparticle, leading to enhanced light-matter interactions. The spectral position of the plasmonic resonance peak, known as the plasmon resonance wavelength, depends on the size, shape, composition, and surrounding environment of the nanoparticle.第四篇示例：One specific type of surface plasmon resonance that has attracted attention is the localized surface plasmon resonance (LSPR) peak. LSPR peaks manifest as sharp extinction peaks inthe absorption or scattering spectra of metal nanoparticles due to the resonance between incident light and the localized surface plasmons on the nanoparticle surface. These peaks are highly sensitive to the size, shape, and composition of the nanoparticle, making them an excellent candidate for various applications such as chemical sensing, biological detection, and single molecule analysis.。

Teece(蒂斯)——动态能力与战略管理中译版

Teece动态能力与战略管理*大卫·蒂斯加里·皮萨诺Amy Shuen【作者简介】大卫·蒂斯（David J. Teece）, 坎特伯雷大学文学学士，宾夕法尼亚大学文学硕士，宾夕法尼亚大学经济学博士。

现为加利福尼亚大学伯克利分校Haas商学院Thomas W. Tusher 全球商务讲座教授，管理、创新与组织研究所所长。

·蒂斯教授的主要研究领域包括：公司战略与公共政策，技术创新，知识管理与知识产权，规制与反托拉斯经济学以及电信、计算机与能源问题等。

·蒂斯教授累计出版和发表的论文与著作超过200篇（部），根据Science Watch杂志的统计，他位列1995到2005十年中经济学和管理学领域文章引用率最高的前十位学者。

他还是Industrial and Corporate Change杂志的编辑与创立者之一。

加里·皮萨诺（Gary Pisano），耶鲁大学文学学士，加利福尼亚大学伯克利分校博士。

现为哈佛大学商学院Harry E. Figgie, Jr.工商管理讲座教授，技术与运作管理系系主任。

皮萨诺教授的研究兴趣主要为生物技术与制药产业的技术战略，产品与过程开发管理，组织学习，垂直整合与外包战略等问题。

皮萨诺教授在国际一流期刊中发表了超过25篇学术论文，已出版的著作有：《研发工厂》，《运作、战略与技术》和《科技企业：生物技术的前景，现实与未来》。

Amy Shuen，耶鲁大学理学学士，哈佛大学MBA，加利福尼亚大学伯克利分校博士。

现为Silicon Valley Strategy Group总裁和CEO。

在此之前，她曾任教于宾夕法尼亚大学沃顿商学院和加利福尼亚大学伯克利分校Haas商学院。

【摘要】动态能力框架分析了在高速技术变迁环境中，企业获取财富和创造财富的根源与方法。

本文认为，这些企业的竞争优势由一些独特的过程（协调和组织方式）所确定。

T.W. ANDERSON (1971). The Statistical Analysis of Time Series. Series in Probability and Ma

425 BibliographyH.A KAIKE(1974).Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes.Annals Institute Statistical Mathematics,vol.26,pp.363-387. B.D.O.A NDERSON and J.B.M OORE(1979).Optimal rmation and System Sciences Series, Prentice Hall,Englewood Cliffs,NJ.T.W.A NDERSON(1971).The Statistical Analysis of Time Series.Series in Probability and Mathematical Statistics,Wiley,New York.R.A NDRE-O BRECHT(1988).A new statistical approach for the automatic segmentation of continuous speech signals.IEEE Trans.Acoustics,Speech,Signal Processing,vol.ASSP-36,no1,pp.29-40.R.A NDRE-O BRECHT(1990).Reconnaissance automatique de parole`a partir de segments acoustiques et de mod`e les de Markov cach´e s.Proc.Journ´e es Etude de la Parole,Montr´e al,May1990(in French).R.A NDRE-O BRECHT and H.Y.S U(1988).Three acoustic labellings for phoneme based continuous speech recognition.Proc.Speech’88,Edinburgh,UK,pp.943-950.U.A PPEL and A.VON B RANDT(1983).Adaptive sequential segmentation of piecewise stationary time rmation Sciences,vol.29,no1,pp.27-56.L.A.A ROIAN and H.L EVENE(1950).The effectiveness of quality control procedures.Jal American Statis-tical Association,vol.45,pp.520-529.K.J.A STR¨OM and B.W ITTENMARK(1984).Computer Controlled Systems:Theory and rma-tion and System Sciences Series,Prentice Hall,Englewood Cliffs,NJ.M.B AGSHAW and R.A.J OHNSON(1975a).The effect of serial correlation on the performance of CUSUM tests-Part II.Technometrics,vol.17,no1,pp.73-80.M.B AGSHAW and R.A.J OHNSON(1975b).The inﬂuence of reference values and estimated variance on the ARL of CUSUM tests.Jal Royal Statistical Society,vol.37(B),no3,pp.413-420.M.B AGSHAW and R.A.J OHNSON(1977).Sequential procedures for detecting parameter changes in a time-series model.Jal American Statistical Association,vol.72,no359,pp.593-597.R.K.B ANSAL and P.P APANTONI-K AZAKOS(1986).An algorithm for detecting a change in a stochastic process.IEEE rmation Theory,vol.IT-32,no2,pp.227-235.G.A.B ARNARD(1959).Control charts and stochastic processes.Jal Royal Statistical Society,vol.B.21, pp.239-271.A.E.B ASHARINOV andB.S.F LEISHMAN(1962).Methods of the statistical sequential analysis and their radiotechnical applications.Sovetskoe Radio,Moscow(in Russian).M.B ASSEVILLE(1978).D´e viations par rapport au maximum:formules d’arrˆe t et martingales associ´e es. Compte-rendus du S´e minaire de Probabilit´e s,Universit´e de Rennes I.M.B ASSEVILLE(1981).Edge detection using sequential methods for change in level-Part II:Sequential detection of change in mean.IEEE Trans.Acoustics,Speech,Signal Processing,vol.ASSP-29,no1,pp.32-50.426B IBLIOGRAPHY M.B ASSEVILLE(1982).A survey of statistical failure detection techniques.In Contribution`a la D´e tectionS´e quentielle de Ruptures de Mod`e les Statistiques,Th`e se d’Etat,Universit´e de Rennes I,France(in English). M.B ASSEVILLE(1986).The two-models approach for the on-line detection of changes in AR processes. In Detection of Abrupt Changes in Signals and Dynamical Systems(M.Basseville,A.Benveniste,eds.). Lecture Notes in Control and Information Sciences,LNCIS77,Springer,New York,pp.169-215.M.B ASSEVILLE(1988).Detecting changes in signals and systems-A survey.Automatica,vol.24,pp.309-326.M.B ASSEVILLE(1989).Distance measures for signal processing and pattern recognition.Signal Process-ing,vol.18,pp.349-369.M.B ASSEVILLE and A.B ENVENISTE(1983a).Design and comparative study of some sequential jump detection algorithms for digital signals.IEEE Trans.Acoustics,Speech,Signal Processing,vol.ASSP-31, no3,pp.521-535.M.B ASSEVILLE and A.B ENVENISTE(1983b).Sequential detection of abrupt changes in spectral charac-teristics of digital signals.IEEE rmation Theory,vol.IT-29,no5,pp.709-724.M.B ASSEVILLE and A.B ENVENISTE,eds.(1986).Detection of Abrupt Changes in Signals and Dynamical Systems.Lecture Notes in Control and Information Sciences,LNCIS77,Springer,New York.M.B ASSEVILLE and I.N IKIFOROV(1991).A uniﬁed framework for statistical change detection.Proc.30th IEEE Conference on Decision and Control,Brighton,UK.M.B ASSEVILLE,B.E SPIAU and J.G ASNIER(1981).Edge detection using sequential methods for change in level-Part I:A sequential edge detection algorithm.IEEE Trans.Acoustics,Speech,Signal Processing, vol.ASSP-29,no1,pp.24-31.M.B ASSEVILLE, A.B ENVENISTE and G.M OUSTAKIDES(1986).Detection and diagnosis of abrupt changes in modal characteristics of nonstationary digital signals.IEEE rmation Theory,vol.IT-32,no3,pp.412-417.M.B ASSEVILLE,A.B ENVENISTE,G.M OUSTAKIDES and A.R OUG´E E(1987a).Detection and diagnosis of changes in the eigenstructure of nonstationary multivariable systems.Automatica,vol.23,no3,pp.479-489. M.B ASSEVILLE,A.B ENVENISTE,G.M OUSTAKIDES and A.R OUG´E E(1987b).Optimal sensor location for detecting changes in dynamical behavior.IEEE Trans.Automatic Control,vol.AC-32,no12,pp.1067-1075.M.B ASSEVILLE,A.B ENVENISTE,B.G ACH-D EVAUCHELLE,M.G OURSAT,D.B ONNECASE,P.D OREY, M.P REVOSTO and M.O LAGNON(1993).Damage monitoring in vibration mechanics:issues in diagnos-tics and predictive maintenance.Mechanical Systems and Signal Processing,vol.7,no5,pp.401-423.R.V.B EARD(1971).Failure Accommodation in Linear Systems through Self-reorganization.Ph.D.Thesis, Dept.Aeronautics and Astronautics,MIT,Cambridge,MA.A.B ENVENISTE and J.J.F UCHS(1985).Single sample modal identiﬁcation of a nonstationary stochastic process.IEEE Trans.Automatic Control,vol.AC-30,no1,pp.66-74.A.B ENVENISTE,M.B ASSEVILLE and G.M OUSTAKIDES(1987).The asymptotic local approach to change detection and model validation.IEEE Trans.Automatic Control,vol.AC-32,no7,pp.583-592.A.B ENVENISTE,M.M ETIVIER and P.P RIOURET(1990).Adaptive Algorithms and Stochastic Approxima-tions.Series on Applications of Mathematics,(A.V.Balakrishnan,I.Karatzas,M.Yor,eds.).Springer,New York.A.B ENVENISTE,M.B ASSEVILLE,L.E L G HAOUI,R.N IKOUKHAH and A.S.W ILLSKY(1992).An optimum robust approach to statistical failure detection and identiﬁcation.IFAC World Conference,Sydney, July1993.B IBLIOGRAPHY427 R.H.B ERK(1973).Some asymptotic aspects of sequential analysis.Annals Statistics,vol.1,no6,pp.1126-1138.R.H.B ERK(1975).Locally most powerful sequential test.Annals Statistics,vol.3,no2,pp.373-381.P.B ILLINGSLEY(1968).Convergence of Probability Measures.Wiley,New York.A.F.B ISSELL(1969).Cusum techniques for quality control.Applied Statistics,vol.18,pp.1-30.M.E.B IVAIKOV(1991).Control of the sample size for recursive estimation of parameters subject to abrupt changes.Automation and Remote Control,no9,pp.96-103.R.E.B LAHUT(1987).Principles and Practice of Information Theory.Addison-Wesley,Reading,MA.I.F.B LAKE and W.C.L INDSEY(1973).Level-crossing problems for random processes.IEEE r-mation Theory,vol.IT-19,no3,pp.295-315.G.B ODENSTEIN and H.M.P RAETORIUS(1977).Feature extraction from the encephalogram by adaptive segmentation.Proc.IEEE,vol.65,pp.642-652.T.B OHLIN(1977).Analysis of EEG signals with changing spectra using a short word Kalman estimator. Mathematical Biosciences,vol.35,pp.221-259.W.B¨OHM and P.H ACKL(1990).Improved bounds for the average run length of control charts based on ﬁnite weighted sums.Annals Statistics,vol.18,no4,pp.1895-1899.T.B OJDECKI and J.H OSZA(1984).On a generalized disorder problem.Stochastic Processes and their Applications,vol.18,pp.349-359.L.I.B ORODKIN and V.V.M OTTL’(1976).Algorithm forﬁnding the jump times of random process equation parameters.Automation and Remote Control,vol.37,no6,Part1,pp.23-32.A.A.B OROVKOV(1984).Theory of Mathematical Statistics-Estimation and Hypotheses Testing,Naouka, Moscow(in Russian).Translated in French under the title Statistique Math´e matique-Estimation et Tests d’Hypoth`e ses,Mir,Paris,1987.G.E.P.B OX and G.M.J ENKINS(1970).Time Series Analysis,Forecasting and Control.Series in Time Series Analysis,Holden-Day,San Francisco.A.VON B RANDT(1983).Detecting and estimating parameters jumps using ladder algorithms and likelihood ratio test.Proc.ICASSP,Boston,MA,pp.1017-1020.A.VON B RANDT(1984).Modellierung von Signalen mit Sprunghaft Ver¨a nderlichem Leistungsspektrum durch Adaptive Segmentierung.Doctor-Engineer Dissertation,M¨u nchen,RFA(in German).S.B RAUN,ed.(1986).Mechanical Signature Analysis-Theory and Applications.Academic Press,London. L.B REIMAN(1968).Probability.Series in Statistics,Addison-Wesley,Reading,MA.G.S.B RITOV and L.A.M IRONOVSKI(1972).Diagnostics of linear systems of automatic regulation.Tekh. Kibernetics,vol.1,pp.76-83.B.E.B RODSKIY and B.S.D ARKHOVSKIY(1992).Nonparametric Methods in Change-point Problems. Kluwer Academic,Boston.L.D.B ROEMELING(1982).Jal Econometrics,vol.19,Special issue on structural change in Econometrics. L.D.B ROEMELING and H.T SURUMI(1987).Econometrics and Structural Change.Dekker,New York. D.B ROOK and D.A.E VANS(1972).An approach to the probability distribution of Cusum run length. Biometrika,vol.59,pp.539-550.J.B RUNET,D.J AUME,M.L ABARR`E RE,A.R AULT and M.V ERG´E(1990).D´e tection et Diagnostic de Pannes.Trait´e des Nouvelles Technologies,S´e rie Diagnostic et Maintenance,Herm`e s,Paris(in French).428B IBLIOGRAPHY S.P.B RUZZONE and M.K AVEH(1984).Information tradeoffs in using the sample autocorrelation function in ARMA parameter estimation.IEEE Trans.Acoustics,Speech,Signal Processing,vol.ASSP-32,no4, pp.701-715.A.K.C AGLAYAN(1980).Necessary and sufﬁcient conditions for detectability of jumps in linear systems. IEEE Trans.Automatic Control,vol.AC-25,no4,pp.833-834.A.K.C AGLAYAN and R.E.L ANCRAFT(1983).Reinitialization issues in fault tolerant systems.Proc.Amer-ican Control Conf.,pp.952-955.A.K.C AGLAYAN,S.M.A LLEN and K.W EHMULLER(1988).Evaluation of a second generation reconﬁgu-ration strategy for aircraftﬂight control systems subjected to actuator failure/surface damage.Proc.National Aerospace and Electronic Conference,Dayton,OH.P.E.C AINES(1988).Linear Stochastic Systems.Series in Probability and Mathematical Statistics,Wiley, New York.M.J.C HEN and J.P.N ORTON(1987).Estimation techniques for tracking rapid parameter changes.Intern. Jal Control,vol.45,no4,pp.1387-1398.W.K.C HIU(1974).The economic design of cusum charts for controlling normal mean.Applied Statistics, vol.23,no3,pp.420-433.E.Y.C HOW(1980).A Failure Detection System Design Methodology.Ph.D.Thesis,M.I.T.,L.I.D.S.,Cam-bridge,MA.E.Y.C HOW and A.S.W ILLSKY(1984).Analytical redundancy and the design of robust failure detection systems.IEEE Trans.Automatic Control,vol.AC-29,no3,pp.689-691.Y.S.C HOW,H.R OBBINS and D.S IEGMUND(1971).Great Expectations:The Theory of Optimal Stop-ping.Houghton-Mifﬂin,Boston.R.N.C LARK,D.C.F OSTH and V.M.W ALTON(1975).Detection of instrument malfunctions in control systems.IEEE Trans.Aerospace Electronic Systems,vol.AES-11,pp.465-473.A.C OHEN(1987).Biomedical Signal Processing-vol.1:Time and Frequency Domain Analysis;vol.2: Compression and Automatic Recognition.CRC Press,Boca Raton,FL.J.C ORGE and F.P UECH(1986).Analyse du rythme cardiaque foetal par des m´e thodes de d´e tection de ruptures.Proc.7th INRIA Int.Conf.Analysis and optimization of Systems.Antibes,FR(in French).D.R.C OX and D.V.H INKLEY(1986).Theoretical Statistics.Chapman and Hall,New York.D.R.C OX and H.D.M ILLER(1965).The Theory of Stochastic Processes.Wiley,New York.S.V.C ROWDER(1987).A simple method for studying run-length distributions of exponentially weighted moving average charts.Technometrics,vol.29,no4,pp.401-407.H.C S¨ORG¨O and L.H ORV´ATH(1988).Nonparametric methods for change point problems.In Handbook of Statistics(P.R.Krishnaiah,C.R.Rao,eds.),vol.7,Elsevier,New York,pp.403-425.R.B.D AVIES(1973).Asymptotic inference in stationary gaussian time series.Advances Applied Probability, vol.5,no3,pp.469-497.J.C.D ECKERT,M.N.D ESAI,J.J.D EYST and A.S.W ILLSKY(1977).F-8DFBW sensor failure identiﬁcation using analytical redundancy.IEEE Trans.Automatic Control,vol.AC-22,no5,pp.795-803.M.H.D E G ROOT(1970).Optimal Statistical Decisions.Series in Probability and Statistics,McGraw-Hill, New York.J.D ESHAYES and D.P ICARD(1979).Tests de ruptures dans un mod`e pte-Rendus de l’Acad´e mie des Sciences,vol.288,Ser.A,pp.563-566(in French).B IBLIOGRAPHY429 J.D ESHAYES and D.P ICARD(1983).Ruptures de Mod`e les en Statistique.Th`e ses d’Etat,Universit´e deParis-Sud,Orsay,France(in French).J.D ESHAYES and D.P ICARD(1986).Off-line statistical analysis of change-point models using non para-metric and likelihood methods.In Detection of Abrupt Changes in Signals and Dynamical Systems(M. Basseville,A.Benveniste,eds.).Lecture Notes in Control and Information Sciences,LNCIS77,Springer, New York,pp.103-168.B.D EVAUCHELLE-G ACH(1991).Diagnostic M´e canique des Fatigues sur les Structures Soumises`a des Vibrations en Ambiance de Travail.Th`e se de l’Universit´e Paris IX Dauphine(in French).B.D EVAUCHELLE-G ACH,M.B ASSEVILLE and A.B ENVENISTE(1991).Diagnosing mechanical changes in vibrating systems.Proc.SAFEPROCESS’91,Baden-Baden,FRG,pp.85-89.R.D I F RANCESCO(1990).Real-time speech segmentation using pitch and convexity jump models:applica-tion to variable rate speech coding.IEEE Trans.Acoustics,Speech,Signal Processing,vol.ASSP-38,no5, pp.741-748.X.D ING and P.M.F RANK(1990).Fault detection via factorization approach.Systems and Control Letters, vol.14,pp.431-436.J.L.D OOB(1953).Stochastic Processes.Wiley,New York.V.D RAGALIN(1988).Asymptotic solutions in detecting a change in distribution under an unknown param-eter.Statistical Problems of Control,Issue83,Vilnius,pp.45-52.B.D UBUISSON(1990).Diagnostic et Reconnaissance des Formes.Trait´e des Nouvelles Technologies,S´e rie Diagnostic et Maintenance,Herm`e s,Paris(in French).A.J.D UNCAN(1986).Quality Control and Industrial Statistics,5th edition.Richard D.Irwin,Inc.,Home-wood,IL.J.D URBIN(1971).Boundary-crossing probabilities for the Brownian motion and Poisson processes and techniques for computing the power of the Kolmogorov-Smirnov test.Jal Applied Probability,vol.8,pp.431-453.J.D URBIN(1985).Theﬁrst passage density of the crossing of a continuous Gaussian process to a general boundary.Jal Applied Probability,vol.22,no1,pp.99-122.A.E MAMI-N AEINI,M.M.A KHTER and S.M.R OCK(1988).Effect of model uncertainty on failure detec-tion:the threshold selector.IEEE Trans.Automatic Control,vol.AC-33,no12,pp.1106-1115.J.D.E SARY,F.P ROSCHAN and D.W.W ALKUP(1967).Association of random variables with applications. Annals Mathematical Statistics,vol.38,pp.1466-1474.W.D.E WAN and K.W.K EMP(1960).Sampling inspection of continuous processes with no autocorrelation between successive results.Biometrika,vol.47,pp.263-280.G.F AVIER and A.S MOLDERS(1984).Adaptive smoother-predictors for tracking maneuvering targets.Proc. 23rd Conf.Decision and Control,Las Vegas,NV,pp.831-836.W.F ELLER(1966).An Introduction to Probability Theory and Its Applications,vol.2.Series in Probability and Mathematical Statistics,Wiley,New York.R.A.F ISHER(1925).Theory of statistical estimation.Proc.Cambridge Philosophical Society,vol.22, pp.700-725.M.F ISHMAN(1988).Optimization of the algorithm for the detection of a disorder,based on the statistic of exponential smoothing.In Statistical Problems of Control,Issue83,Vilnius,pp.146-151.R.F LETCHER(1980).Practical Methods of Optimization,2volumes.Wiley,New York.P.M.F RANK(1990).Fault diagnosis in dynamic systems using analytical and knowledge based redundancy -A survey and new results.Automatica,vol.26,pp.459-474.430B IBLIOGRAPHY P.M.F RANK(1991).Enhancement of robustness in observer-based fault detection.Proc.SAFEPRO-CESS’91,Baden-Baden,FRG,pp.275-287.P.M.F RANK and J.W¨UNNENBERG(1989).Robust fault diagnosis using unknown input observer schemes. In Fault Diagnosis in Dynamic Systems-Theory and Application(R.Patton,P.Frank,R.Clark,eds.). International Series in Systems and Control Engineering,Prentice Hall International,London,UK,pp.47-98.K.F UKUNAGA(1990).Introduction to Statistical Pattern Recognition,2d ed.Academic Press,New York. S.I.G ASS(1958).Linear Programming:Methods and Applications.McGraw Hill,New York.W.G E and C.Z.F ANG(1989).Extended robust observation approach for failure isolation.Int.Jal Control, vol.49,no5,pp.1537-1553.W.G ERSCH(1986).Two applications of parametric time series modeling methods.In Mechanical Signature Analysis-Theory and Applications(S.Braun,ed.),chap.10.Academic Press,London.J.J.G ERTLER(1988).Survey of model-based failure detection and isolation in complex plants.IEEE Control Systems Magazine,vol.8,no6,pp.3-11.J.J.G ERTLER(1991).Analytical redundancy methods in fault detection and isolation.Proc.SAFEPRO-CESS’91,Baden-Baden,FRG,pp.9-22.B.K.G HOSH(1970).Sequential Tests of Statistical Hypotheses.Addison-Wesley,Cambridge,MA.I.N.G IBRA(1975).Recent developments in control charts techniques.Jal Quality Technology,vol.7, pp.183-192.J.P.G ILMORE and R.A.M C K ERN(1972).A redundant strapdown inertial reference unit(SIRU).Jal Space-craft,vol.9,pp.39-47.M.A.G IRSHICK and H.R UBIN(1952).A Bayes approach to a quality control model.Annals Mathematical Statistics,vol.23,pp.114-125.A.L.G OEL and S.M.W U(1971).Determination of the ARL and a contour nomogram for CUSUM charts to control normal mean.Technometrics,vol.13,no2,pp.221-230.P.L.G OLDSMITH and H.W HITFIELD(1961).Average run lengths in cumulative chart quality control schemes.Technometrics,vol.3,pp.11-20.G.C.G OODWIN and K.S.S IN(1984).Adaptive Filtering,Prediction and rmation and System Sciences Series,Prentice Hall,Englewood Cliffs,NJ.R.M.G RAY and L.D.D AVISSON(1986).Random Processes:a Mathematical Approach for Engineers. Information and System Sciences Series,Prentice Hall,Englewood Cliffs,NJ.C.G UEGUEN and L.L.S CHARF(1980).Exact maximum likelihood identiﬁcation for ARMA models:a signal processing perspective.Proc.1st EUSIPCO,Lausanne.D.E.G USTAFSON, A.S.W ILLSKY,J.Y.W ANG,M.C.L ANCASTER and J.H.T RIEBWASSER(1978). ECG/VCG rhythm diagnosis using statistical signal analysis.Part I:Identiﬁcation of persistent rhythms. Part II:Identiﬁcation of transient rhythms.IEEE Trans.Biomedical Engineering,vol.BME-25,pp.344-353 and353-361.F.G USTAFSSON(1991).Optimal segmentation of linear regression parameters.Proc.IFAC/IFORS Symp. Identiﬁcation and System Parameter Estimation,Budapest,pp.225-229.T.H¨AGGLUND(1983).New Estimation Techniques for Adaptive Control.Ph.D.Thesis,Lund Institute of Technology,Lund,Sweden.T.H¨AGGLUND(1984).Adaptive control of systems subject to large parameter changes.Proc.IFAC9th World Congress,Budapest.B IBLIOGRAPHY431 P.H ALL and C.C.H EYDE(1980).Martingale Limit Theory and its Application.Probability and Mathemat-ical Statistics,a Series of Monographs and Textbooks,Academic Press,New York.W.J.H ALL,R.A.W IJSMAN and J.K.G HOSH(1965).The relationship between sufﬁciency and invariance with applications in sequential analysis.Ann.Math.Statist.,vol.36,pp.576-614.E.J.H ANNAN and M.D EISTLER(1988).The Statistical Theory of Linear Systems.Series in Probability and Mathematical Statistics,Wiley,New York.J.D.H EALY(1987).A note on multivariate CuSum procedures.Technometrics,vol.29,pp.402-412.D.M.H IMMELBLAU(1970).Process Analysis by Statistical Methods.Wiley,New York.D.M.H IMMELBLAU(1978).Fault Detection and Diagnosis in Chemical and Petrochemical Processes. Chemical Engineering Monographs,vol.8,Elsevier,Amsterdam.W.G.S.H INES(1976a).A simple monitor of a system with sudden parameter changes.IEEE r-mation Theory,vol.IT-22,no2,pp.210-216.W.G.S.H INES(1976b).Improving a simple monitor of a system with sudden parameter changes.IEEE rmation Theory,vol.IT-22,no4,pp.496-499.D.V.H INKLEY(1969).Inference about the intersection in two-phase regression.Biometrika,vol.56,no3, pp.495-504.D.V.H INKLEY(1970).Inference about the change point in a sequence of random variables.Biometrika, vol.57,no1,pp.1-17.D.V.H INKLEY(1971).Inference about the change point from cumulative sum-tests.Biometrika,vol.58, no3,pp.509-523.D.V.H INKLEY(1971).Inference in two-phase regression.Jal American Statistical Association,vol.66, no336,pp.736-743.J.R.H UDDLE(1983).Inertial navigation system error-model considerations in Kalmanﬁltering applica-tions.In Control and Dynamic Systems(C.T.Leondes,ed.),Academic Press,New York,pp.293-339.J.S.H UNTER(1986).The exponentially weighted moving average.Jal Quality Technology,vol.18,pp.203-210.I.A.I BRAGIMOV and R.Z.K HASMINSKII(1981).Statistical Estimation-Asymptotic Theory.Applications of Mathematics Series,vol.16.Springer,New York.R.I SERMANN(1984).Process fault detection based on modeling and estimation methods-A survey.Auto-matica,vol.20,pp.387-404.N.I SHII,A.I WATA and N.S UZUMURA(1979).Segmentation of nonstationary time series.Int.Jal Systems Sciences,vol.10,pp.883-894.J.E.J ACKSON and R.A.B RADLEY(1961).Sequential and tests.Annals Mathematical Statistics, vol.32,pp.1063-1077.B.J AMES,K.L.J AMES and D.S IEGMUND(1988).Conditional boundary crossing probabilities with appli-cations to change-point problems.Annals Probability,vol.16,pp.825-839.M.K.J EERAGE(1990).Reliability analysis of fault-tolerant IMU architectures with redundant inertial sen-sors.IEEE Trans.Aerospace and Electronic Systems,vol.AES-5,no.7,pp.23-27.N.L.J OHNSON(1961).A simple theoretical approach to cumulative sum control charts.Jal American Sta-tistical Association,vol.56,pp.835-840.N.L.J OHNSON and F.C.L EONE(1962).Cumulative sum control charts:mathematical principles applied to their construction and use.Parts I,II,III.Industrial Quality Control,vol.18,pp.15-21;vol.19,pp.29-36; vol.20,pp.22-28.432B IBLIOGRAPHY R.A.J OHNSON and M.B AGSHAW(1974).The effect of serial correlation on the performance of CUSUM tests-Part I.Technometrics,vol.16,no.1,pp.103-112.H.L.J ONES(1973).Failure Detection in Linear Systems.Ph.D.Thesis,Dept.Aeronautics and Astronautics, MIT,Cambridge,MA.R.H.J ONES,D.H.C ROWELL and L.E.K APUNIAI(1970).Change detection model for serially correlated multivariate data.Biometrics,vol.26,no2,pp.269-280.M.J URGUTIS(1984).Comparison of the statistical properties of the estimates of the change times in an autoregressive process.In Statistical Problems of Control,Issue65,Vilnius,pp.234-243(in Russian).T.K AILATH(1980).Linear rmation and System Sciences Series,Prentice Hall,Englewood Cliffs,NJ.L.V.K ANTOROVICH and V.I.K RILOV(1958).Approximate Methods of Higher Analysis.Interscience,New York.S.K ARLIN and H.M.T AYLOR(1975).A First Course in Stochastic Processes,2d ed.Academic Press,New York.S.K ARLIN and H.M.T AYLOR(1981).A Second Course in Stochastic Processes.Academic Press,New York.D.K AZAKOS and P.P APANTONI-K AZAKOS(1980).Spectral distance measures between gaussian pro-cesses.IEEE Trans.Automatic Control,vol.AC-25,no5,pp.950-959.K.W.K EMP(1958).Formula for calculating the operating characteristic and average sample number of some sequential tests.Jal Royal Statistical Society,vol.B-20,no2,pp.379-386.K.W.K EMP(1961).The average run length of the cumulative sum chart when a V-mask is used.Jal Royal Statistical Society,vol.B-23,pp.149-153.K.W.K EMP(1967a).Formal expressions which can be used for the determination of operating character-istics and average sample number of a simple sequential test.Jal Royal Statistical Society,vol.B-29,no2, pp.248-262.K.W.K EMP(1967b).A simple procedure for determining upper and lower limits for the average sample run length of a cumulative sum scheme.Jal Royal Statistical Society,vol.B-29,no2,pp.263-265.D.P.K ENNEDY(1976).Some martingales related to cumulative sum tests and single server queues.Stochas-tic Processes and Appl.,vol.4,pp.261-269.T.H.K ERR(1980).Statistical analysis of two-ellipsoid overlap test for real time failure detection.IEEE Trans.Automatic Control,vol.AC-25,no4,pp.762-772.T.H.K ERR(1982).False alarm and correct detection probabilities over a time interval for restricted classes of failure detection algorithms.IEEE rmation Theory,vol.IT-24,pp.619-631.T.H.K ERR(1987).Decentralizedﬁltering and redundancy management for multisensor navigation.IEEE Trans.Aerospace and Electronic systems,vol.AES-23,pp.83-119.Minor corrections on p.412and p.599 (May and July issues,respectively).R.A.K HAN(1978).Wald’s approximations to the average run length in cusum procedures.Jal Statistical Planning and Inference,vol.2,no1,pp.63-77.R.A.K HAN(1979).Someﬁrst passage problems related to cusum procedures.Stochastic Processes and Applications,vol.9,no2,pp.207-215.R.A.K HAN(1981).A note on Page’s two-sided cumulative sum procedures.Biometrika,vol.68,no3, pp.717-719.B IBLIOGRAPHY433 V.K IREICHIKOV,V.M ANGUSHEV and I.N IKIFOROV(1990).Investigation and application of CUSUM algorithms to monitoring of sensors.In Statistical Problems of Control,Issue89,Vilnius,pp.124-130(in Russian).G.K ITAGAWA and W.G ERSCH(1985).A smoothness prior time-varying AR coefﬁcient modeling of non-stationary covariance time series.IEEE Trans.Automatic Control,vol.AC-30,no1,pp.48-56.N.K LIGIENE(1980).Probabilities of deviations of the change point estimate in statistical models.In Sta-tistical Problems of Control,Issue83,Vilnius,pp.80-86(in Russian).N.K LIGIENE and L.T ELKSNYS(1983).Methods of detecting instants of change of random process prop-erties.Automation and Remote Control,vol.44,no10,Part II,pp.1241-1283.J.K ORN,S.W.G ULLY and A.S.W ILLSKY(1982).Application of the generalized likelihood ratio algorithm to maneuver detection and estimation.Proc.American Control Conf.,Arlington,V A,pp.792-798.P.R.K RISHNAIAH and B.Q.M IAO(1988).Review about estimation of change points.In Handbook of Statistics(P.R.Krishnaiah,C.R.Rao,eds.),vol.7,Elsevier,New York,pp.375-402.P.K UDVA,N.V ISWANADHAM and A.R AMAKRISHNAN(1980).Observers for linear systems with unknown inputs.IEEE Trans.Automatic Control,vol.AC-25,no1,pp.113-115.S.K ULLBACK(1959).Information Theory and Statistics.Wiley,New York(also Dover,New York,1968). K.K UMAMARU,S.S AGARA and T.S¨ODERSTR¨OM(1989).Some statistical methods for fault diagnosis for dynamical systems.In Fault Diagnosis in Dynamic Systems-Theory and Application(R.Patton,P.Frank,R. Clark,eds.).International Series in Systems and Control Engineering,Prentice Hall International,London, UK,pp.439-476.A.K USHNIR,I.N IKIFOROV and I.S AVIN(1983).Statistical adaptive algorithms for automatic detection of seismic signals-Part I:One-dimensional case.In Earthquake Prediction and the Study of the Earth Structure,Naouka,Moscow(Computational Seismology,vol.15),pp.154-159(in Russian).L.L ADELLI(1990).Diffusion approximation for a pseudo-likelihood test process with application to de-tection of change in stochastic system.Stochastics and Stochastics Reports,vol.32,pp.1-25.T.L.L A¨I(1974).Control charts based on weighted sums.Annals Statistics,vol.2,no1,pp.134-147.T.L.L A¨I(1981).Asymptotic optimality of invariant sequential probability ratio tests.Annals Statistics, vol.9,no2,pp.318-333.D.G.L AINIOTIS(1971).Joint detection,estimation,and system identiﬁrmation and Control, vol.19,pp.75-92.M.R.L EADBETTER,G.L INDGREN and H.R OOTZEN(1983).Extremes and Related Properties of Random Sequences and Processes.Series in Statistics,Springer,New York.L.L E C AM(1960).Locally asymptotically normal families of distributions.Univ.California Publications in Statistics,vol.3,pp.37-98.L.L E C AM(1986).Asymptotic Methods in Statistical Decision Theory.Series in Statistics,Springer,New York.E.L.L EHMANN(1986).Testing Statistical Hypotheses,2d ed.Wiley,New York.J.P.L EHOCZKY(1977).Formulas for stopped diffusion processes with stopping times based on the maxi-mum.Annals Probability,vol.5,no4,pp.601-607.H.R.L ERCHE(1980).Boundary Crossing of Brownian Motion.Lecture Notes in Statistics,vol.40,Springer, New York.L.L JUNG(1987).System Identiﬁcation-Theory for the rmation and System Sciences Series, Prentice Hall,Englewood Cliffs,NJ.。

Analysis_of_multistage_amplifier-frequency_compensation

Analysis of Multistage Amplifier–FrequencyCompensationKa Nang Leung and Philip K.T.Mok,Member,IEEEAbstract—Frequency-compensation techniques of single-,two-and three-stage amplifiers based on Miller pole splitting and pole–zero cancellation are reanalyzed.The assumptions made, transfer functions,stability criteria,bandwidths,and important design issues of most of the reported topologies are included. Several proposed methods to improve the published topologies are given.In addition,simulations and experimental results are provided to verify the analysis and to prove the effectiveness of the proposed methods.Index Terms—Damping-factor-control frequency compen-sation,multipath nested Miller compensation,multipath zero cancellation,multistage amplifier,nested Gm-C compensation, nested Miller compensation,simple Miller compensation.I.I NTRODUCTIONM ULTISTAGE amplifiers are urgently needed with the advance in technologies,due to the fact that single-stage cascode amplifier is no longer suitable in low-voltage designs. Moreover,short-channel effect of the sub-micron CMOS transistor causes output-impedance degradation and hence gain of an amplifier is reduced dramatically.Therefore,many frequency-compensation topologies have been reported to stabilize the multistage amplifiers[1]–[26].Most of these topologies are based on pole splitting and pole–zero can-cellation using capacitor and resistor.Both analytical and experimental works have been given to prove the effectiveness of these topologies,especially on two-stage Miller compen-sated amplifiers.However,the discussions in some topologies are focused only on the stability criteria,but detailed design information such as some important assumptions are missing. As a result,if the provided stability criteria cannot stabilize the amplifier successfully,circuit designers usually choose the parameters of the compensation network by trial and error and thus optimum compensation cannot be achieved.In fact,there are not many discussions on the comparison of the existing compensation topologies.Therefore,the differences as well as the pros and cons of the topologies should be inves-tigated in detail.This greatly helps the designers in choosing a suitable compensation technique for a particular design condi-tion such as low-power design,variable output capacitance or variable output current.Manuscript received March9,2000;revised February6,2001.This work was supported by the Research Grant Council of Hong Kong,China under grant HKUST6007/97E.This paper was recommended by Associate Editor N.M.K. Rao.The authors are with the Department of Electrical and Electronic Engineering, The Hong Kong University of Science and Technology,Clear Water Bay,Hong Kong(e-mail:eemok@t.hk).Publisher Item Identifier S1057-7122(01)07716-9.Moreover,practical considerations on the compensation tech-niquesof(a)(b)(c)(d)(e)(f)(g)(h)(i)(j)Fig.1.Studied and proposed frequency-compensation topologies.(a)SMC.(b)SMCNR.(c)MZC.(d)NMC.(e)NMCNR.(f)MNMC.(g)NGCC.(h)NMCF.(i)DFCFC1.(j)DFCFC2.accuracy.In this paper,there are three common assumptionsmade for all studied and proposed topologies.1)The gains of all stages are much greater than one(i.e.,LEUNG et al.:ANALYSIS OF MULTISTAGE AMPLIFIER–FREQUENCY COMPENSATION1043 Assumption1holds true in amplifier designs for most ampli-fiers except those driving small load resistance.If this assump-tion cannot be satisfied,numerical analysis using computers isrequired.Moreover,the parasitic capacitances of the tiny-geom-etry transistors in advanced technologies are small and this val-idates assumptions2)and3).III.R EVIEW ON S INGLE-S TAGE A MPLIFIERThe single-stage amplifier is said to have excellent frequencyresponse and is widely used in many commercial products.Infact,the advantages can be illustrated by its transferfunctiondue to the single pole,assuming thatGBW(i.e.,andminimum.Therefore,a higher bias current and smaller size for all transis-tors in the signal path are required tolocateand the RHP zeroislocates beforepp pp ppz ppp p1044IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I:FUNDAMENTAL THEORY AND APPLICATIONS,VOL.48,NO.9,SEPTEMBER2001Fig.3.PM versus g=gof a SMC amplifier.From (6)and Fig.3,the PM of a SMC amplifier strongly de-pends ontheto ratio and this,in fact,shows the RHP zero effect on the PM.Physically,the presence of the RHP zero is due to the feedforward small-signal current flowing throughthe compensation capacitor to the output [1]–[11].Ifis large,the small-signal output current is larger than the feed-forward current and the effect of the RHP zero appears only at very high frequencies.Thus,asmallis preferable.However,is limited bythe bias current and size of the input differential pair.To have a good slew rate,the bias current cannot be small.In addition,to have a small offset voltage,the size of input differential pair cannot be too small.Emitter/source degeneration technique isalso not feasible toreducesince it reduces the limited input common-mode range in low-voltage design.Therefore,asmallcannot be obtained easily.From the previous analysis,it is known that the RHP zero degrades the stability significantly.There are many methods to eliminate the RHP zero and improve the bandwidth.The methods involve using voltage buffer [4]–[6]and current buffer [7],[8],a nulling resistor [2],[3],[9]–[11],and MZC technique [12].In this paper,the techniques to be discussed are:1)SMC using nulling resistor (SMCNR)and 2)SMC using MZC.A.SMCNRThe presence of the RHP zero is due to the feedforward small-signal current.One method for reducing the feedforward current and thus eliminating the RHP zero is to increase the impedance of the capacitive path.This can be done by inserting a resistor,called nulling resistor,in series with the compensation capacitor,as shown in Fig.1(b).Most published analyses only focus on the effect of the nulling resistor to the position of the zero but not to the positions of the poles.In fact,when the nulling resistor isincreased to infinity,the compensation network is open-circuit and no pole splitting takes place.Thus,the target of this section is to investigate the limit of the nulling resistor.The transfer function of the SMNCR(,,respectively.It is well-known thatwhenis generally much smallerthananddue to theabsence of the RHP zero.However,many designers prefer to use a nulling resistor withvalue largerthansince an accurate valueofandis not a con-stant and a precise cancellation of the RHP zero by afixed)to cancel the feedforward small-signal current(,,which is independentof.(7)LEUNG et al.:ANALYSIS OF MULTISTAGE AMPLIFIER–FREQUENCY COMPENSATION1045 Moreover,since MZC does not change the positions of thepoles,the same dimension condition ofwhich is obtained by neglecting the RHP zerophase shifting term in(6).Besides,when the output current isincreased,is increased accordingly.The nondominant pole()will move to a higher frequency and a largerPM is obtained.Thus,this compensation topology can stabilizethe amplifier within the quiescent to maximum loading currentrange.In some applications,whereand the PM is about90andand.Apparently,the GBW can be increased to infinity bydecreasingto validate the assumptions on deriving(8),so the fol-lowing condition is required as a compromise:,the transfer function is rewritten as(11),shownat the bottom of the page.The dominant pole is1046IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I:FUNDAMENTAL THEORY AND APPLICATIONS,VOL.48,NO.9,SEPTEMBER2001Fig.5.Equivalent small-signal model of three-stage NMC.From the above equation,GBW.Assuming,and are fixed for a given power consumption,largeand are required.This increases the PM but itreduces the GBW and also increases the capacitor values andthe required chip area simultaneously.For the complex-pole approach,the NMC amplifier in unity-feedback configuration should have the third-order Butterworthfrequency response.Let be the closed-loop transferfunctionandshould be in the followingformat:and areobtained:(or)and the damping factor of the complexpoleis(17)which is one-fourth the bandwidth of a single-stage amplifier.This shows the bandwidth reduction effect of nesting compen-sation.Similar to SMC,the GBW can be improved by alargerand asmaller and asmaller.The PM under the effect of a complex pole[28]is givenbyPM(18)Comparing the required compensation capacitors,the GBWand PM under the same power consumption(i.e.,same,and)of the two approaches,it is concluded that thecomplex-pole approach is better.Moreover,from(15)and(16),smallerand are neededwhen.This validates the previous assumption on neglecting the zerossince the coefficients of the function of zero in(10)are smalland the zeros locate at high frequencies.From another pointof view,therequiredand are small,so the feedfor-ward small-signal current can pass to the output only at veryhigh frequencies.In addition,the output small-signal current ismuch larger than the feedforward currentas.Thus,the zeros give negligible effect to the stability.If theseparate-pole approach is applied,the stability is doubtful sincelarger compensation capacitors are required and this generateszeros close to the unity-gain frequency of the amplifier.To further provethat is necessary inNMC,a HSPICE simulation using the equivalent small-signalmodel of NMC,which is shown in Fig.5,is performed.The cir-cuit parametersare A/V,A/V,is satisfied)and10pF.and,which is set according to(15)and(16),are4pFand1pF,respectively.The simulation result is shown in Fig.6by the solid line.A GBW of4.2MHz and a PM of58from100is notmuch largerthan),therequired is changed from4pFto40pF,according to(15).The frequency response is shownby the dotted line in Fig.6.A RHP zero appears before theunity-gain frequency and causes the magnitude plot to curveupwards.The PM is degraded to30ischanged from50is not much largerthan)and is changed from1pF to20pF accordingto(16).As shown by the dashed line in Fig.6,a frequencypeak,due to small damping factor of the complex pole,appearsand makes the amplifier unstable.The phenomenon can be ex-plained from(10).When is not much largerthan,theterm()of the second-order function in the denomi-nator is small and this causes the complex poles to have a smallLEUNG et al.:ANALYSIS OF MULTISTAGE AMPLIFIER–FREQUENCY COMPENSATION1047Fig.6.HSPICE simulation of NMC (solid:g g and g ;dotted:g is not much larger than g ;dash:g is not much larger than g ).damping factor.Ifis very important and critical to the stability of an NMCamplifier.However,this condition is very difficult to achieve,especially in low-power design.Ifdoes not hold true,the analysis should be re-started from (10).Fromthis equation,sincetheterm is negative,there are one RHP zero and one LHP zero.The RHP zero locates at a lower fre-quency astheand only a LHPzeroand any value closedto is able to locate the RHP zero to a high frequency.Bydefining,the transfer function is rewritten as (20)shownat the bottom of the page.It is notedthatand are obtained as in NMC usingcomplex-pole approach and are givenby(i.e.,1048IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I:FUNDAMENTAL THEORY AND APPLICATIONS,VOL.48,NO.9,SEPTEMBER2001Fig.7.Circuit diagram of the amplifiers(a)NMCNR.(b)NMCF.(c)DFCFC1.(d)DFCFC2.).The GBW is given byGBWdue to the LHP zero.A larger GBW can be obtained byslightly reducing but this reduces the PM.To prove the proposed structure,NMC and NMCNR am-plifiers were implemented in AMS10.8.The circuit diagram of the NMCNR amplifiersare shown in Fig.7(a)and the NMC counterpart has the samecircuitry without the nulling resistor.The chip micrograph isshown in Fig.8.Both amplifiers drive a100pF//25knulling resistor,which is made of poly,is used in the NMCNRamplifier.In NMC,the required is99pF,but inNMCNR is63pF.As presented before,the PM of NMCNRamplifier is larger,so a smaller is used in the implemen-tation to obtain a similar PM as in NMC and a larger GBW.Moreover,this greatly reduces the chip area from0.23mm.The measured results and improvement comparison are tabu-lated in Tables I and II,respectively.Both amplifiers haveW power consumption and)are improvedby+39%,+3is improvedLEUNG et al.:ANALYSIS OF MULTISTAGE AMPLIFIER–FREQUENCY COMPENSATION 1049TABLE IM EASURED R ESULTS OF THE AMPLIFIERSTABLE III MPROVEMENT OF THE P ROPOSED AND P UBLISHED T OPOLOGIES W ITH NMC (,and the chip area.VI.MNMCBesides increasing the power,the multipath technique can be used to increase the bandwidth of an amplifier.In MNMC[12],[16],[19],and [26],a feedforward transconductance stage (FTS)is added to the NMC structure to create a low-fre-quency LHP zero.This zero,called multipath zero,cancels the second nondominant pole to extend the bandwidth.The structure of MNMC is shown in Fig.1(f)and it is limited to three-stage amplifiers but it has potential to extend to more stages.However,power consumption and circuit complexity are increased accordingly since a feedforward input differ-ential stage,as same as MZC,is needed,so this will not be discussed here.The input of the FTS,withtransconductanceand the output is connected to the input of theoutput stage.Again,with the conditionthat,the transfer function is given by (23)at the bottom of the next page.The nondominant poles are givenby1050IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—I:FUNDAMENTAL THEORY AND APPLICATIONS,VOL.48,NO.9,SEPTEMBER2001Fig.9.Simulation results of an MNMC amplifier using equivalent small-signal circuit under the change of g andC =20pF;dash:g =10mA/V andC =1pF)..The explicit dimensionconditionofis,therefore,givenbyin MNMC is much larger thanthat in NMC.This increases the required chip area and reduces the SR dramatically.Therefore,emitter degeneration technique was used in the design of [16].This can reduce theeffective so thatthe is,as a result,smaller.With (24),the positionsofis thefollowing:.The above analysis gives the required valuesof,and,,and.In fact,if this assumption does nothold true,the positions of the poles and the LHP zero are not those previously stated.Moreover,a RHP zero exists and the stability is greatly affected.The analysis and dimension conditions are obtained in static state.Since there is a pole–zero doublet before the unity-gain frequency,the dynamic-state stability should also be consid-ered.Since,in practice,the loading current andcapacitancemay change in some general-purpose amplifiers with Class-AB output stage,it is necessary to consider the stability of theMNMC amplifierwhenis increasedand ,where the ratio isobtained from (24)and (26).Besides,the multipath zero is notchangedwhenand with the condition in (27).It is obviousthat,so MNMC is not affected by changing the loading current and capacitance.To prove the above arguments,a simulation using HSPICE is performed with the equivalent small-signal circuit of an MNMCamplifier.The circuit parametersareA/V,,1M25k 20p F.T h u s,111.25i s c h a n g e d f r o m 1m A /V t o 10m A /V ;a n d 2)a nd i s i n c re a s e d or a r e r e q u i r e d .T h i s c o n d i t i o n n o t o n l y i m -p r o v e s t h e s t a b i l i t y b u t i t a l s o s i m p l i f i e s t h e t r a n s f e r f u n c t i o n .I n f a c t ,a s m e n t i o n e d b e f o r e ,t h i s c o n d i t i o n i s d i f f i c u l t t o a c h i e v e i n l o w -p o w e r d e s i g n ,s o Y o u e t a l .i n t r o d u c e d N G C C [20].N G C C i s a n-s t a g e N G C Ca m p l i f i e r.W i t h t h e c o n d i t i o n t h at w e re ,t h e g e n e r a lf o r m o f a n-s t a g e a m p l i f i e r t h a n N M C .I n t h e s t a b i l i t y c o n d i t i o n s p r o p o s e d b y Y o u e t a l .,t h e s e p a r a t e d -p o l e a p p r o a c h i s u s e d a n d t h e n o n d o m a r e s e t t o s o m e f r e q u e n c i e s s u c h t h a t t h e G B W ,T s a nd p o we r c o n s u m p t i o n a r e a l l o p t i m i z e d .U n d o u b t e d l y ,t h c a t e d t o d o o p t i m i z a t i o n a n a l y t i c a l l y ,s o n u m e u s i n g M A T L A B i s r e q u i r e d .H o w e v e r ,q u e s t i o n s o n p r a c t i c a l c o n s i d e r a t i o n s ,s i n c e i t i s p r ef e r a m i n i m u m s t ag e s a s p o s s i b l e .A s s t a t e d b e f o r e ,t a n o p t i m u m n u m b e r o n d c g a i n ,b a n d w i d th ,a n d s u m p ti o n .T h e r e f o r e ,t h e a n a l y s i s i n t h i s s e c t i o n t h e t h r e e -s t a g e N G C C a m p l i f i e r.T h e s t r u c t u r e oN G C C a m p l i f i e r i s s h o w n i n F i g .1(g )a n d t h e t r a ni s g i v e n b y (29)s h o w n a t t h e b o t t o m o f t h e p a g eb e f o r e a n d a l s o f r o m t h e n u m e r a t o r o f (29),t h e b e e l i m i n a t e d b y s e t t i n g a nd .T h et r a n s f e r f u n c t i o n i s t h e n s i m p l i f i e d t o (30)s h o wo f t h e p a g e .T h e a r r a n g e m e n t o f t h e p o l e s c a n u ss e p a r a t e -p o l e o r c o m p l e x -p o l e a p p r o a c h b u t t h ep r e f e r r e d .I t i s o b v i o u s t h a t t h e d e n o m i n a t o r o s a m e a s (11)b u t t h e d i f f e r e n c e i s t h a t i s n o t r e q u i r e d i n N G C C .T h u s,.A l t h o u g h N G C C i s g o o d i n l o w -p o w e r d e s i g n s ,s t a g e F T S (i .e .,some of them are LHP zeros which,in fact,help to increase the PM.With regard to the above considerations,a new structure, called NMC with feedforward Gm stage(NMCF),is proposed and shown in Fig.1(h).There are only two differences betweenNMCF and NGCC:1)the input-stage FTS is removed and2).Bydefiningand are obtained using thecomplex-pole approach and they are givenby,are smaller than those in NMC,MNMC and NGCCsinceterm is positive andthe term is negative,the LHPzerolocates before the RHPzerofor stability purpose,so the following condition isrequired:(34)The condition states the minimum valueof to obtain anoptimum control of LHP zero.From(31)to(33),the GBW and PM are given byGBW(35)andPM(36)It is shown in(35)that the bandwidth is improved by the pres-enceofmCMOS process was done to prove the proposed structure.TheNMCF amplifier is shown in Fig.7(b)and it is basically thesame as the NMC amplifier.It is noted that the gate of M32,which is the FTS,is connected to the output of the first stage.The output stage is of push-pull typeand,from(35),to double the GBW.The measured results and improvement comparison areshown in Tables I and II,respectively.It is obvious that theimprovement of NMCF over NMC on GBW(),PM()and occupied chip area()are much larger than those in MNMC and NGCCin other designs,which are shown in Table II.The powerconsumption is only increased by6and inverselyproportionaltois removed and the bandwidth of the ampli-fier can be extended substantially.However,the damping factorof the nondominant complex poles,which is originally con-trolledby,cannot be controlled and a frequency peak,which causes the closed-loop amplifier to be unstable,appearsin the magnitude Bode plot[23].To control the damping factorand make the amplifier stable,a damping-factor-control(DFC)block is added.The DFC block is basically a gain stage withdc gain greater than one(i.e.,.The DFC block functions as a frequency-de-pendent capacitor and the amount of the small-signal currentinjected into the DFC block depends on the valueofand(transconductance of the gain stage inside the DFC block).Hence,the damping factor of the nondominant complex polescan be controlled byoptimumand and this makesthe amplifier stable.There are two possible positions to add theDFC block and they are shown in Fig.1(i)for DFCFC1andFig.1(j)for DFCFC2.In addition,both structures have a feed-forward transconductance stage to form a push-pull output stagefor improving large-signal slewing performance.For DFCFC1,the transfer function is given by(37)shown atthe bottom of the next page.It can be seen from(37)that thedamping factor of the nondominant poles can be controlledby.Moreover,the effectofandtransfer functionbut is limitedto tovalidate (37).Sinceis small,the amplifier is not slowed downby.From (37),there are three poles,so the com-plex-pole approach is used.Moreover,since it is preferable to have the same output current capability for boththe -transistor of the output stage,the sizes ofthe -tran-sistor are used in ratio of 3to 1to compensate for the differ-ence in the mobilities of the carriers.Thus,it is reasonable toset,so the dimension conditions are givenby (39)whereis much smaller thanthat in the previous nesting topologies,so the SR is also greatly improved,assuming that the SR is not limited by the outputstage.Moreover,is a decreasing functionof (41)and the PM is about 60times.Ifa little,butthis reduces the PM as a tradeoff.For DFCFC2,bysettingwith the same reason stated previously,the transfer function is given by (42)shown at the bottom of the page.Similar to DFCFC1,the complex-poleapproach is used to achieve the stability.Therefore,the dimen-sion conditions are givenby(43)is a fixed value and is four timesof.Thus,the power consumption of DFCFC2amplifier with certain valueof.Although it is difficult to comparethe GBW of DFCFC2with other topologies since the format is different,it is in general better than others.It is due to the fact that the GBW is inversely proportion to the geometric meanof,which gives a smaller valuethan mdouble-metal double-poly CMOS process.The circuit diagrams are shown in Fig.7(c)for DFCFC1and Fig.7(d)for DFCFC2.The micrograph is,again,shown in Fig.8.In both amplifiers,M41andform the DFC block and M32is the FTS.Moreover,from Table II,the GBW,PM,SR,TIX.S UMMARY OF S TUDIED F REQUENCY C OMPENSATIONT OPOLOGIESA summary on the required stability conditions,resultant GBW and PM for all studied and proposed topologies are given in Table parisons on the topologies are tabulated in Table IV.Moreover,some important points derived from the previous analyzes are summarized as follows.1)The stability-dimension conditions of all topologies arebased on the assumptions stated in Section II.If the as-sumptions cannot be met,numerical method should be used to stabilize the amplifiers.2)With the exception of the single-stage amplifier,alargerandlargestandreducingto ratio and asmallerto ratio.6)For high-speed applications,a larger bias current shouldbe applied to the output stage toincrease.Fig.10.Local feedback circuitry to control the dc operating point of the DFCblock.X.R OBUSTNESS OF THE S TUDIED F REQUENCY C OMPENSATION In IC technologies,the circuit parameters such as transcon-ductance,capacitance and resistance vary from run to run,lot to lot and also according to temperature.The robustness of fre-quency compensation is very important to ensure the stabilities of multistage amplifiers.From the summary in Table III,the required values of com-pensation capacitors depend on the ratio of transconductances of gain stages explicitly for SMC,SMCNR,MZC1,MZC2,NMC,NMCNR,MNMC,NGCC,NMCF,and DFCFC1and implicitly for DFCFC2.The ratio maintains constant for any process varia-tion and temperature effect with good bias current matching and transistor size matching (due to design).One important point is that the valueof50%,in general is not significantto the stability.In MNMC,pole–zero cancellation is used.However,the su-perior tracking technique in MNMC is due to the pole–zero can-cellation based on the ratios of transconductances and compen-sation capacitances.Thus,process variations do not affect the compression of the pole–zero doublet.Although the robustness of the studied topologies are good,the exact value of the GBW will be affected by process varia-tions.Referring to Table III,the GBW’s of all topologies,in-cluding commonly used single-stage and Miller-compensated amplifiers,depend on the transconductance of the output stage.Thus,the GBW will change under the effect of process varia-tions and temperature.XI.C ONCLUSIONSeveral frequency-compensation topologies have been investigated analytically.The pros and cons as well as the design requirements are discussed.To improve NMC and NGCC,NMCNR,and NMCF are proposed and the improved performance is verified by experimental results.In addition,DFCFC has been introduced and it has much better frequency and transient performances than the other published topologies for driving large capacitive loads.Finally,robustness of the studied topologies has been discussed.R EFERENCES[1]J.E.Solomon,“The monolithic op amp:A tutorial study,”IEEE J.Solid-State Circuits ,vol.9,pp.314–332,Dec.1974.[2]P.R.Gray and R.G.Meyer,Analysis and Design of Analog IntegratedCircuits ,2ed.New York:Wiley,1984.[3]W.-H.Ki,L.Der,and m,“Re-examination of pole splitting of ageneric single stage amplifier,”IEEE Trans.Circuits Syst.I ,vol.44,pp.70–74,Jan.1997.[4]Y.P.Tsividis and P.R.Gray,“An integrated NMOS operational amplifierwith internal compensation,”IEEE J.Solid-State Circuits,vol.SC-11, pp.748–753,Dec.1976.[5]G.Smarandoiu,D.A.Hodges,P.R.Gray,and ndsburg,“CMOSpulse-code-modulation voice codec,”IEEE J.Solid-State Circuits,vol.SC-13,pp.504–510,Aug.1978.[6]G.Palmisano and G.Palumbo,“An optimized compensation strategyfor two-stage CMOS OP AMPS,”IEEE Trans.Circuits Syst.I,vol.42, pp.178–182,Mar.1995.[7] B.K.Ahuja,“An improved frequency compensation technique forCMOS operational amplifiers,”IEEE J.Solid-State Circuits,vol.SC-18,no.6,pp.629–633,Dec.1983.[8]G.Palmisano and G.Palumbo,“A compensation strategy for two-stageCMOS opamps based on current buffer,”IEEE Trans.Circuits Syst.I, vol.44,pp.257–262,Mar.1997.[9] D.Senderowicz,D.A.Hodges,and P.R.Gray,“High-performanceNMOS operational amplifier,”IEEE J.Solid-State Circuits,vol.SC-13, pp.760–766,Dec.1978.[10]W.C.Black Jr,D.J.Allstot,and R.A.Reed,“A high performance lowpower CMOS channel filter,”IEEE J.Solid-State Circuits,vol.15,pp.929–938,Dec.1980.[11]P.R.Gray and R.G.Meyer,“MOS operational amplifier design—a tu-torial overview,”IEEE J.Solid-State Circuits,vol.SC-17,pp.969–982, Dec.1982.[12]R.G.H.Eschauzier and J.H.Huijsing,Frequency Compensation Tech-niques for Low-Power Operational Amplifiers.Boston,MA:Kluwer, 1995.[13] E.M.Cherry,“A new result in negative feedback theory and its applica-tions to audio power amplifier,”Int.J.Circuit Theory Appl.,vol.6,no.3,pp.265–288,1978.[14],“Feedback systems,”U.S.Patent4243943,Jan.1981.[15] F.N.L.Op’t Eynde,P.F.M.Ampe,L.Verdeyen,and W.M.C.Sansen,“A CMOS large-swing low-distortion three-stage class AB power am-plifier,”IEEE J.Solid-State Circuits,vol.25,pp.265–273,Feb.1990.[16]R.G.H.Eschauzier,L.P.T.Kerklaan,and J.H.Huijsing,“A100MHz100dB operational amplifier with multipath nested miller compensation structure,”IEEE J.Solid-State Circuits,vol.27,pp.1709–1717,Dec.1992.[17] E.M.Cherry,“Comment on a100MHz100dB operational amplifierwith multipath nested miller compensation structure,”IEEE J.Solid-State Circuits,vol.31,pp.753–754,May1996.[18]S.Pernici,G.Nicollini,and R.Castello,“A CMOS low-distortion fullydifferential power amplifier with double nested Miller compensation,”IEEE J.Solid-State Circuits,vol.28,pp.758–763,July1993.[19]K.-J.de Langen,R.G.H.Eschauzier,G.J.A.van Dijk,and J.H.Hui-jsing,“A1GHz bipolar class-AB operational amplifier with multipath nested Miller compensation for76dB gain,”IEEE J.Solid-State Cir-cuits,vol.32,pp.488–498,Apr.1997.[20] F.You,S.H.K.Embabi,and E.Sánchez-Sinencio,“Multistage ampli-fier topologies with nested gm-C compensation,”IEEE J.Solid-State Circuits,vol.32,pp.2000–2011,Dec.1997.[21]H.-T.Ng,R.M.Ziazadeh,and D.J.Allstot,“A mulitstage amplifiertechnique with embedded frequency compensation,”IEEE J.Solid-State Circuits,vol.34,pp.339–341,Mar.1999.[22]K.N.Leung,P.K.T.Mok,W.H.Ki,and J.K.O.Sin,“Damping-factor-control frequency compensation technique for low-voltage low-power large capacitive load applications,”in Dig.Tech.Papers ISSCC’99,1999, pp.158–159.[23],“Three-stage large capacitive load amplifier with damping-factor-control frequency compensation,”IEEE J.Solid-State Circuits,vol.35, pp.221–230,Feb.2000.[24],“Analysis on alternative structure of damping-factor-control fre-quency compensation,”in Proc.IEEE ISCAS’00,vol.II,May2000,pp.545–548.[25]K.N.Leung,P.K.T.Mok,and W.H.Ki,“Right-half-plane zero re-moval technique for low-voltage low-power nested miller compensation CMOS amplifiers,”in Proc.ICECS’99,vol.II,1999,pp.599–602. [26]J.H.Huijsing,R.Hogervorst,and K.-J.de Langen,“Low-power low-voltage VLSI operational amplifier cells,”IEEE Trans.Circuits Syst.I, vol.42,pp.841–852,Nov.1995.[27]G.C.Temes and Patra,Introduction to Circuit Synthesis andDesign,1ed.New York:McGraw-Hill,1977.[28]J.W.Nilsson,Electric Circuits,4ed.New York:Addison Wesley,1993.[29] B.Y.Kamath,R.G.Meyer,and P.R.Gray,“Relationship between fre-quency response and settling time of operational amplifier,”IEEE J.Solid-State Circuits,vol.SC-9,pp.247–352,Dec.1974.[30] C.T.Chuang,“Analysis of the settling behavior of an operational am-plifier,”IEEE J.Solid-State Circuits,vol.SC-17,pp.74–80,Feb.1982. Ka Nang Leung received the B.Eng.and M.Phil.degrees in electronic engi-neering from the Hong Kong University of Science and Technology(HKUST), Clear Water Bay,Hong Kong,in1996and1998,respectively.He is now working toward the Ph.D.degree in the same department.During the B.Eng.studies,he joined Motorola,Hong Kong,to develop a PDA system as his final year project.In addition,he has developed several frequency-compensation topologies for multistage amplifiers and low dropout regulators in his M.Phil studies.He was a Teaching Assistant in courses on analogue integrated circuits and CMOS VLSI design.His research interests are low-voltage low-power analog designs on low-dropout regulators,bandgap voltage references and CMOS voltage references.In addition,he is interested in developing frequency-compensation topologies for multistage amplifiers and for linear regulators.In1996,he received the Best Teaching Assistant Award from the Department of Electrical and Electronic Engineering at theHKUST.Philip K.T.Mok(S’86–M’95)received theB.A.Sc.,M.A.Sc.,and Ph.D.degrees in electricaland computer engineering from the University ofToronto,Toronto,Canada,in1986,1989,and1995,respectively.From1986to1992,he was a Teaching Assistant,at the University of Toronto,in the electrical engi-neering and industrial engineering departments,andtaught courses in circuit theory,IC engineering andengineering economics.He was also a Research As-sistant in the Integrated Circuit Laboratory at the Uni-versity of Toronto,from1992to1994.He joined the Department of Electrical and Electronic Engineering,the Hong Kong University of Science and Tech-nology,Hong Kong,in January1995as an Assistant Professor.His research interests include semiconductor devices,processing technologies and circuit de-signs for power electronics and telecommunications applications,with current emphasis on power-integrated circuits,low-voltage analog integrated circuits and RF integrated circuits design.Dr.Mok received the Henry G.Acres Medal,the W.S.Wilson Medal and Teaching Assistant Award from the University of Toronto and the Teaching Ex-cellence Appreciation Award twice from the Hong Kong University of Science and Technology.。

研究方法如何在顶级管理学期刊发表论文（五）：方法与结果

研究方法如何在顶级管理学期刊发表论文（五）：方法与结果来源：南开管理评论一旦选择一个有趣而适当的选题，设计并执行一个合理的数据收集，制定一个引人注目的“伏笔”和发展一个坚实的理论，这些艰巨而又令人兴奋的工作完成后，人们就很容易坐视不前、麻痹放松，在各种方法和结果中游走。

接下来的工作似乎很简单直接，也许有点按部就班——向读者报告：（1）如何获得数据以及为什么获得数据；（2）如何分析数据以及发现了什么。

对于AMJ这一系列的关于如何在AMJ发表的叙述性文章，确实有许多读者在等待着它的出版。

因此，如果我们这篇文章缺乏说服力，我们希望它至少能提供一些信息。

作为作者，我们不得不承认，在写这些章节的时候，我们已经屈服于放松注意力的诱惑。

我们听到同事们说，他们把这些部分交给研究团队的初级成员，让他们在草稿写作中“练手”，好像这些部分的重要性不如开头部分、假设发展和讨论部分那么重要。

也许的确如此。

但作为过去两年来现任编辑团队的成员，我们面对这样一个现实：“方法”和“结果”部分，即使不是最关键的部分，也往往在审稿人如何评价稿件方面发挥着重要作用。

如果这些章节并没有对数据收集程序和结果提供清晰、详细的描述，反而常常让审稿人感到困惑，并会就作者使用的研究程序和发现，提出比他们回答更多的问题。

相比之下，一个有效的陈述可以对作者说服读者相信他们的理论论点（或其中的一部分）得到支持的程度产生至关重要的影响。

高质量的“方法”和“结果”部分也传达了表现作者责任心的积极信号。

知道他们在准备这些章节时是谨慎而严谨的，对于讨论是建议拒绝还是建议修改请求的外审来说可能会有所不同。

为了更好地理解审稿人共同关心的问题，我们在任期内对每一封被拒稿件的决定信进行了评估。

我们发现有几个问题在被拒绝的手稿中比在要求修改的手稿中出现的频率要高得多。

我们的评估结果，如果不令人惊讶的话，揭示了这两个部分的一系列非常一致的主要问题，我们总结为“三个度”（3C:Completeness，Clarity，Credibility）：完整度、清晰度和可信度。

A Tutorial on Support Vector Machines for Pattern Recognition

CHRISTOPHER J.C. BURGES
burges@
Bell Laboratories, Lucent Technologies Editor: Usama Fayyad Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SVM solutions are unique and when they are global. We describe how support vector training can be practically implemented, and discuss in detail the kernel mapping technique which is used to construct SVM solutions which are nonlinear in the data. We show how Support Vector machines can have very large (even inﬁnite) VC dimension by computing the VC dimension for homogeneous polynomial and Gaussian radial basis function kernels. While very high VC dimension would normally bode ill for generalization performance, and while at present there exists no theory which shows that good generalization performance is guaranteed for SVMs, there are several arguments which support the observed high accuracy of SVMs, which we review. Results of some experiments which were inspired by these arguments are also presented. We give numerous examples and proofs of most of the key theorems. There is new material, and I hope that the reader will ﬁnd that even old material is cast in a fresh light. Keywords: support vector machines, statistical learning theory, VC dimension, pattern recognition

PACC国际物理学分类表

如何查PACC代码？PACC代码是《Physics Abstracts,Classification and Contents》的缩略。

PACC专业代码是英国科学文摘（INSPEC）用于论文分类的代码。

按照论文的内容将其分为十大类有0000，1000，……5000，……9000表示，例如：凝聚物质由6000及7000表示，其中6000内包括凝聚物质的结构、热学和力学性质，而7000内包括凝聚物质的电子结构、电学、磁学和光学性质。

再仔细分则由6100……6200等表示，例如6100表示液体和固体结构。

而X射线晶体结构测定及精确化技术表示固体结构的测定包含在6100中，而用6110M来表示。

所以要查出某一论文的PACC专业代码，应先确定该论文主要内容属于哪一大类，就在那一大类中找出其代码，其次再找出该论文包括的其它次要内容的代码。

国际物理学分类表PACC（Physics Abstracts, Classification andContents）0000 总论 GENERAL0100 通讯、教育、历史和哲学 communication,education,history,andphilosophy0110 通报、消息和组织活动announcements, news, and organizational activities0110C 通报、消息和颁奖announcements, news, and awards 0110F 会议、演讲和学会conferences, lectures, and institutes 0110H 物理学组织活动physics organizational activities 0130 物理学文献及出版物physics literature and publications0130B 讲稿的出版(进修学院,暑期学校等)publications of lectures (advanced institutes, summer schools, etc.)0130C 会议录 conferenceproceedings 0130E 专著和著作集 monographs,andcollections 0130K 手册和字典handbooks and dictionaries0130L 物理数据、表格汇编collections of physical data, tables0130N 教科书 textbooks0130Q 报告、学位论文、论文reports, dissertations, theses0130R 评论及教学参考论文,资源通讯reviews and tutorial papers, resource letters0130T 书目 bibliographies 0140 教育 education0140D 课程设置与评价course design and evaluation0140E 中小学科学science in elementary and secondary school0140G 课程设置,教学方法,策略和评价curricula, teaching methods, strategies, and evaluation0140J 教师培训 teachertraining0150 教具(包括设备和实验及教学用材料)educational aids(inc.equipment, experiments andteaching approaches to subjects)0150F 视听教具、电影audio and visual aids, films0150H 计算机在教学中的使用instructional computer use0150K 试验理论和技术testing theory and techniques0150M 示范教学的实验和设备demonstration experiments and apparatus 0150P 实验室实验和设备laboratory experiments and apparatus0150Q 实验室课程设置、组织和评价laboratory course design, organization, and evaluation0150T 建筑物和设备 buildingsandfacilities 0155 普通物理 generalphysics 0160 传记、历史和个人笔记biographical, historical, and personal notes 0165 科学史history of science0170 科学哲学 philosophyofscience 0175 科学与社会 scienceandsociety 0190 其他一般论题other topics of general interest0200 物理学中的数学方法mathematical methods in physics0210 代数、集合论和图论algebra, set theory, and graph theory0220 群论(量子力学中的代数方法见0365;基本粒子物理学中的对称见1130)group theory(for algebraic methods in quantummechanics, see 0365; for symmetries inelementary particle physics, see 1130)0230 函数论,分析function theory, analysis0240 几何学、微分几何学和拓扑学(0400相对论与引力)geometry, differential geometry, andtopology(0400 relativity and gravitation)0250 概率论、随机过程和统计学(0500统计物理学)probability theory, stochastic processes, andstatistics(0500 statistical physics)0260 数字近似及分析numerical approximation and analysis0270 计算技术(数据处理与计算见0650)computational techniques(for data handling and computation, see 0650)0290 物理学中数学方法的其它论题other topics in mathematical methods in physics0300 经典及量子物理学;力学与场classical and quantum physics; mechanics and fields0320 离散系统的经典力学:一般数学问题(离散系统的应用经典力学见4610;天体力学见9510)classical mechanics of discrete systems: generalmathematical aspects ( for applied classicalmechanics of discrete systems, see 4610; forcelestial mechanics, see 9510)0330 狭义相对论 specialrelativity0340 连续介质经典力学:一般数学问题classical mechanics of continuous media: general mathematical aspects0340D 弹性力学的数学理论(4620连续介质力学,4630固体力学)mathematical theory of elasticity(4620 continuummechanics, and 4630 mechanics of solids)0340G 流体动力学:一般数学问题(4700流体动力学)fluid dynamics; general mathematicalaspects(4700 fluid dynamics)0340K 波和波传播:一般数学问题(4630M机械波和弹性波;4320一般线性声学)waves and wave propagation; generalmathematical aspects(4630M mechanical andelastic waves, 4320 general linear acoustics)0350 经典场论 classicalfieldtheory0350D 麦克斯韦理论:一般数学问题(应用经典电动力学,见4100)Maxwell theory: general mathematical aspects(forapplied classical electrodynamics, see 4100)0350K 其它具体经典场论other special classical field theories0365 量子论;量子力学(0530量子统计力学;相对论性波动方程,见1110)quantum theory; quantum mechanics(0530quantum statistical mechanics;for relativisticwave equations, see 1110)0365B 基础、测量理论、其它理论foundations, theory of measurement, miscellaneous theories0365C 形式论 formalism 0365D 泛函分析方法functional analytical methods0365F 代数方法(0220群论;3115分子物理学中计算方法)algebraic methods(02 20 group theory; 3115calculation methods in molecular physics)0365G 波动方程解:边界态solutions of wave equations: bound state0365N 非相对论性散射理论 nonrelativisticscatteringtheory 0365S 半经典理论和应用semiclassical theories and applications0367 量子信息 Quantuminformation 0370 量子场论(1110场论) theory of quantized fields(1110 field theory)0380 散射的一般理论(1120 S-矩阵论;1180相对论性散射)general theory of scattering(1120 S-matrix theory,and 1180 relativistic scattering)0400 相对论与引力(狭义相对论,见0330;相对论性天体物理学,见9530; 相对论性宇宙学,见9880)relativity and gravitation(for special relarivity,see0330;for relativistic astrophysics,see 9530;forrelativistic cosmology,see 9880)0420 广义相对论(0240几何学和拓扑学)general relativity (0240 geometry and topology) 0420C 基本问题和普通形式论fundamental problems and general formalism0420F 典型的形式论、拉氏函数和变分原理canonical formalism, Lagrangians, and variationalprinciples0420J 方程解solutions to equations0420M 守恒定律和运动方程conservation laws and equations of motion 0430 引力波和辐射:理论gravitational waves and radiation: theory0440 连续介质;电磁及其它混合引力系统continuous media; electromagnetic and othermixed gravitational systems0450 统一场论及其它引力理论unified field theories and other theories of gravitation0455 引力替代理论alternative theories of gravitation0460 引力的量子论quantum theory of gravitation0465 超引力 supergravity0470 黑洞物理学(参见9760L 黑洞) physics of black holes (see also 9760L black holes)0480 广义相对论的实验检验及引力辐射观测experimental tests of general relativity andobservations of gravitational radiation0485 中程力(包括第五和第六力) intermediate range forces (inc.fifth and sixth forces)0490 相对论和引力的其它论题other topics in relativity and gravitation0500 统计物理学和热力学(0250概率论、随机过程和统计学)statistical physics and thermodynamics(0250probability thory,stochastic processes,andstatistics)0520 统计力学 statisticalmechanics 0520D 分子运动论 kinetictheory0520G 经典系综论classical ensemble theory0530 量子统计力学(6700量子流体;7100凝聚物质的电子态)quantum statistic al mechanics(6700 quantumfluids, and 7100 electron states in condensedmatter)0530C 量子系综论quantum ensemble theory0530F 费米子系统和电子气Fermion systems and electron gas 0530J 玻色子系统 Bosonsystems0530L 任意子和仲统计学(量子统计力学)anyons and parastatistics (quantum statistical mechanics)0540 涨落现象、随机过程和布朗运动fluctuation phenomena, random processes, and Brownian motion0545 混沌系统的理论和模型(流体系统中的混沌，见4752)theory and models of chaotic systems(for chaos inflowing systems,see 4752)0547 非线性动力学系统和分岔(流体系统中的分岔，见4752)nonlinear dynamical systems and bifurcations(bifurcations in flowing systems,see 4752)0550 点阵理论和统计学;伊辛问题(7510H伊辛模型)lattice theory and statistics; Ising problems(7510HIsing models)0555 分形(流体系统中的分形，见4752)fractals (fractals in flowing systems,see 4752) 0560 输运过程:理论 transportprocesses:theory 0565 自组织系统 Self-organizedsystems0570 热力学(4460热力学过程;6400状态方程,相平衡和相变;6500凝聚物质的热性质 ; 化学热力学,见8260)thermodynamics(4460 thermodynamic processes;6400 equation s of state, phase equilibria andphase transitions; 6500 thermal properties ofcondensed matter;for chemical thermodynamics,see 8260)0570C 热力学函数及状态方程thermodynamic functions and equations of state0570F 相变:一般问题phase transitions: general aspects 0570J 临界点现象critical point phenomena0570L 非平衡热力学、不可逆过程(3430势能表面;8200物理化学)nonequilibrium thermodynamics, irreversibleprocesses(3430 potential energy surfaces, 8200physical chemistry)0580 经济物理学 Econophysics0590 统计物理学和热力学的其它论题other topics in statistical physics and thermodynamics0600 测量科学、普通实验室技术及测试设备系统Measurement science, general laboratorytechniques, and instrumentation systems0620 基本度量学 metrology 0620D 测量与误差理论measurement and error theory0620F 单位 units 0620H 测量标准和校正measurement standards and calibration 0620J 基本常数测定determination of fundamental constants 0630 基本变量测量measurement of basic variables0630C 空间变量测量(包括空间延伸的所有变量如:直径、重量、厚度、位移、表面拓扑学、粒子尺寸、弥散系统区)spatial variables measurement(inc.measurementof all variables extending in space e.g. diameter,weight, thickness, displacement , surfacetopography, particle size, area of dispersesystems)0630E 质量与密度的测量mass and density measurement0630F 时间与频率的测量(天文学方面的,见9570)time and frequency measurement(for astronomicalaspects see 9570)0630G 速度、加速度和转动测量(流速测量,见4780)velocity, acceleration and rotationmeasurement(for flow velocity measurement see4780)0630L 基本电磁变量测量(0750电学仪器和技术)measurement of basic electromagneticvariables(0750 electrical instruments andtechniques)0630M 机械变量测量(包括弹性模量，力，冲击，应变，应力，力矩和振动)(压力测量，见0630N；声学变量测量，见4385D；固体力学测量，见4630R；粘度测量，见4780；材料试验，8170)measurement of mechanical variables(inc.elasticmoduli,force,shock ,strain,stress,torque,andvibration)(for pressure measurement,see0630N;for acoustic variables measurement,see4385D;for measurement in the mechanics ofsolids, see 4630R;for viscosity measurement,see4780;for materials testing,see 8170)0630N 压力测量(真空测量，见0730D；高压技术，见0735)pressure measurement(for vacuum measurement,see 0730D;for high-pressure techniques, see0735)0650 数据处理和计算(0270计算技术;2980核信息处理;光学数据处理,存贮及检索, 见423 0;地球物理数据采集和存贮,见9365)data handling and computation(0270computational techniques; 2980 nuclearinformation processing;for optical dataprocessing , storage and retrieval see 4230; forgeophysical data acquisition and storage see9365)0650D 数据搜集、处理、记录、数据显示(含数显技术)data gathering, processing, and recording, datadisplays (including digital techniques)0650M 计算装置与技术computing devices and techniques0660 实验室技术 laboratorytechniques 0660E 样品制备 samplepreparation0660J 高速技术(微秒到微微秒) high　speed techniques (microsecond to picosecond)0660S 微检验装置、微定位器和切片机micromanipulators, micropositioners , and microtomes0660V 车间技术(焊接、机械加工、润滑作用和轴承等)workshop techniques ( welding, machining,lubrication, bearings, etc.)0660W 安全(2880辐射监测和防护;8760M辐射剂量测定法;8760P辐射防护)safety( 2880 radiation monitoring and protection,8760M radiation dosimetry, 8760P radiationprotection)0670 普通测试设备 generalinstrumentation 0670D 敏感元件和探测器sensing and detecting devices0670E 试验设备 testingequipment 0670H 显示、记录与指示器display, recording, and indicating instrument s0670M 换能器(电磁辐射换能器见0762;声换能器见4388;液流换能器见4780)transducers(for electromagnetic radiationtransducers see 0762; for acoustic transducers see4388; for flow transducers see 4780)0670T 伺服及控制装置servo and control devices0690 测量科学、普通实验室技术及测试设备系统中的其它论题other topics in measurement science, generallaboratory techniques and instrumentationsystems0700 物理学中普遍使用的专用测试设备与技术(各分支学科的专用测试设备与技术入各自的分支学科)specific instrumentation and techniques of generaluse in physics(within each subdiscipline forspecialized instrumentation and techniques)0710 机械仪器与测量方法(固体力学测量见4630R;材料试验见8170)mechanical instruments and measurementmethods(for measurement in the mechanics of solids, see 4630R; for materials testing, see 8170)0710C 微机械器件和系统(微光学器件和技术，见4283)micromechanical devices and systems (formicrooptical devices and technology,see 4283)0710F 隔振 vibrationisolation0710Y 其他机械仪器和技术(包括摆、陀螺仪、离心器)other mechanical instruments andtechniques(inc.pendulums,gyroscopes,centrifuges)0720 热仪器和技术(4450物质的热性质;4460热力学过程;热辐射的辐射度学和检测, 见 0760D和0762)thermal instruments and techniques(4450 thermalproperties of matter, 4460 thermodynamicprocesses;for radiometry and detection of thermalradiation see 0760D and 0762)0720D 温度测量 thermometry 0720F 量热学 calorimetry 0720H 加热炉 furnaces0720K 高温技术及测试设备;测高温术high　temperature techniques and instrumentation; pyrometry0720M 低温实验法 cryogenics 0725 测湿法 hygrometry0730 真空产生与真空技术(包括低于1个大气压的压力;稀薄气体动力学入4745;8115 G 真空淀积)vacuum production and techniques(inc.pressuresbelow 1atmosphere; 4745 rarefied gas dynamics;8115G vacuum deposition)0730B 排空能力、除气、剩余气体evacuating power, degasification, residual gas 0730C 真空泵 vacuumpumps 0730D 真空计 vacuummeters 0730G 真空设备及试验方法vacuum apparatus and testing methods0730K 辅助设备、器件及材料auxiliary apparatus, hardware and materials0735 高压产生与技术(包括大于1个大气压的压力)high pressure production and techniques(inc.pressures above 1 atmosphere)0750 电学仪器及技术electrical instruments and techniques 0755 磁测量仪器及技术magnetic instruments and techniques0758 磁共振谱仪、辅助仪器和技术(6116N电子顺磁共振和核磁共振测定)magnetic resonance spectrometers, auxiliaryinstruments and techniques(6116N EPR and NMRdeterminations)0760 光学仪器和技术(辐射探测见0762;光谱学和光谱计见0765;全息术见4240;光源和标准见4272;光学透镜和反射系统见4278;光学器件、技术和应用见4280;光学试验和加工技术见4285;辐射谱仪和光谱技术见2930;辐射测量、检测和计数见2970)optical instruments and techniques(for radiationdetection, see 0762; for spectroscopy andspectrometers, see 0765; for holography, see4240; for optical sources and standards, see 4272;for optical lens and mirror systems, see 4278; foroptical devices , techniques and applications, see4280; for optical testing and workshop techniques,see 4285; for radiation spectrometers andspectroscopic techniques, see 29 30; for radiationmeasurement, detection and counting, see 2970)0760D 光度学和辐射度学(包括色度学,辐射探测入0762)photometry and radio metry(inc.colorimetry;0762detection of radiation)0760F 偏振测量术与椭园偏振测量术 polarimetryandellipsometry0760H 折射测量术与反射测量术 refractometryandreflectometry 0760L 干涉量度学 interferometry 0760P 光学显微术 opticalmicroscopy0762 辐射探测(测辐射热计、光电管、红外波与亚毫米波探测)detection of radiation (bolometers, photoelectriccells, IR. and submillimetre waves detection)0765 光谱学与光谱计(包括光声谱术) optical spectroscopy and spectrometers(inc.photoacoustic spectroscopy)0765E 紫外和可见光谱学与光谱仪UV and visible spectroscopy and spectrometers 0765G 红外光谱学与光谱仪IR spectroscopy and spectrometers0768 照相术、照相仪器与技术(光敏材料参见4270;照相过程的化学参见8250)photography, photographic instruments andtechniques(for light sensitive materials see also4270 for chemistry of photographic process seealso 8250)0775 质谱仪与质谱测定技术(质谱化学分析见8280)mass spectrometers and m ass spectrometrytechniques(for mass spectroscopic chemicalanalysis, see 8280)0777 粒子束的产生与处理;(2925基本粒子和核物理中的粒子源和靶;4180粒子束和粒子光学)particle beam production and handling;(2925particle sources and targets in elementary　particle and nuclear physics, 4180 particle beamsand particle optics)0779 扫描探针显微术及其相关技术(包括扫描隧道显微术，原子力显微术、磁力显微术，摩擦力显微术，和近场扫描光学显微术，(结构测定方面，参见6116P)scanning prob e microscopy and relatedtechniques(inc.scanning tunnellingmicroscopy,atomic force microscopy,magneticforce microscopy,friction force microscopy,andnear　field scanning opticalmicroscopy)(structure determination aspects, seealso 6116P)0780 电子与离子显微镜及其技术(6116D凝聚物质中的电子显微术;6116F凝聚物质中的场离子显微术)electron and ion microscopes andtechniques(6116D in condensed matter electronmicroscopy, 6116F field ion microscopy)0781 电子和离子谱仪及其相关技术(参见2930辐射谱仪和光谱技术)electron and ion spectrometers and relatedtechniques(see also 2930 radiation spectrometersan d spectroscopic techniques)0785 X射线与γ射线仪器与技术(包括穆斯堡尔谱仪和技术)X-ray, gamma-ray instruments and techniques(inc.Moessbauer spectrometers and technique s)0788 粒子干涉量度学和中子仪器(粒子束的产生与处理，参见0777;中子谱仪，参见 2930H ，原子干涉量度学，参见3580粒子光学，参见4180)particle interferometry and neutroninstrumentation(for particle beam production andhandling,see 0777;for neutron spectrometers,seealso 2930H;for atomic interferometry,see also3580;for particle optics,see also 4180)0790 专用设备中的其它论题other topics in specialised instrumentation1000 基本粒子物理与场(宇宙线见9440;高能实验技术和设备见 2900)THE PHYSICS OF ELEMENTARY PARTICLESAND FIELDS(for cosmic rays ,see 9440;for highenergy experimental techniques andinstrumentation, see 2900)1100 场和粒子的一般理论(0365量子力学;0370量子场论;0380散射的一般理论)general theory of fields and particles(0365quantum mechanics, 0370 theory of quantizedfields, 0380 general theory of scattering)1110 场论 fieldtheory 1110C 公理法 axiomaticapproach 1110E 拉氏函数和哈密顿函数法Lagrangian and Hamiltonian approach1110G 重正化 renormalization 1110J 渐近问题与特性asymptotic problems and properties1110L 非线性或非局域理论及模型nonlinear or nonlocal theories and models1110M 史文格源理论 Schwingersourcetheory 1110N 规范场论gauge field theories1110Q 相对论性波动方程relativistic wave equations1110S 束缚与非稳定态;贝特-沙耳皮特方程bound and unstable states; Bethe-Salpeterequations1110W 有限温度场论finite temperature field theory1117 弦理论和其他扩展物质理论(包括超弦和膜)theories of strings and other extendedobjects(inc.superstrings and membranes)1120 S-矩阵论 S-matrixtheory 1120D 散射矩阵和微扰论scattering matrix and perturbation theory1120F 色散关系和S矩阵的分析特性dispersion relations and analytic properties of the S-matrix1130 对称和守恒定律(0220群论) symmetry and conservation laws(0220 group theory)1130C 洛伦兹与庞加莱不变性Lorentz and Poincare invariance1130E 电荷共轭、宇称、时间反演和其它分立对称charge conjugation, parity, time reversal and otherdiscrete symmetries1130J SU(2)和SU(3)对称SU(2) and SU(3) symmetries1130K SU(4)对称 SU(4)symmetry 1130L 其他内部对称和高度对称other internal and higher symmetries1130N 非线性对称和动力学对称性(谱生成对称)nonlinear and dynamical symmetries (spectrum　generating symmetries)1130P 超对称 supersymmetry1130Q 自发性对称破缺spontaneous symmetry breaking1130R 手征对称 chiralsymmetries 1140 流及其特性currents and their properties1140D 流的一般理论general theory of currents1140F 流代数的拉格朗日算法Lagrangian approach to current algebras1140H 部分守恒轴矢量流partially conserved axial　vector currents 1150 色散关系与求和定则dispersion relations and sum rules1150E n/d法 n/dmethod 1150G 靴襻 bootstraps 1150J 交叉对称 crossingsymmetries 1150L 求和定则 sumrules1150N 多变量色散关系(包括曼德尔斯坦表象)multivariable dispersion relations(inc.Mandelstamrepresentation)1160 复合角动量;雷其(理论)体系(0380一般散射理论;1240强相互作用中的复合角动量)complex angular momentum; Reggeformalism(0380 general theory of scattering, 1240in strong interactions)1180 相对论性散射理论(0380一般散射理论)relativistic scattering theory (0380 general theoryof scattering)1180C 运动特性(螺旋性和不变振幅、运动奇异性等)kinematical properties (helicity and invariantamplitudes, kinematic singularities, etc.)1180E 部分波分析 partial　wave analysis1180F 近似法(程函近似法,变分原理等) approximations (eikonal approximation, variational principles, etc)1180G 多道散射 multichannelscattering 1180J 多体散射和Faddeev方程Many-body scattering and Faddeev equation 1180L 多次散射 multiplescattering 1190 一般场论和粒子理论的其它论题other topics in general field and particle theory1200 具体理论和相互作用模型;粒子分类系统specific theories and interaction models; particlesystematics1210 统一场论和模型unified field theories and models1210B 电弱理论 electroweaktheories 1210C 统一化标准模型standard model of unification1210D 标准模型以外的统一模型(包括GUTS，颜色模型和SUSY模型)unified models beyond the standardmodel(inc.GUTS,technicolour and SUSY models)1220 电磁相互作用模型models of electromagnetic interactions1220D 量子电动力学的具体计算和极限specific calculations and limits of quantum electrodynamics1220F 量子电动力学的实验检验experimental tests of quantum electrodynamics 1225 引力相互作用模型(0460引力的量models for gravitational interactions(0460子论) quantum theory of gravitation)1230 弱相互作用模型models of weak interactions1230C 中子流 neutralcurrents 1230E 中间玻色子 intermediatebosons 1235 粒子的复合模型composite models of particles1235C 量子色动力学的一般特性(动力学,禁闭等)general properties of quantum chromodynamics(dynamics, confinement, etc.)1235E 量子色动力学在粒子特性和反应中的应用applications of quantum chromodynamics toparticle properties and reactions1235H 粒子的结构和反应的唯象复合模型(部分子模型,口袋模型等)phenomenological composite models of particlestructure and reactions (partons, bags, etc.)1235K 其它复合模型(包括复合夸克模型和轻子模型)other composite models( posite quarksand leptons)1240 强相互作用模型models of strong interactions1240E 统计模型 statisticalmodels1240F 靴襻模型 bootstrapmodels1240H 二重性和双关模型duality and dual models1240K 强子分类方案 hadronclassificationschemes1240M 复合角动量平面;雷其极点和割线(雷其子)(1160复合角动量,雷其体系的一般理论)complex angular momentum plane; Regge polesand cuts (Reggeons)(1160 for general theory)1240P 吸收模型,光学模型和程函模型(衍射和衍射生成模型见1240S)absorptive, optical, and eikonal models(fordiffraction and diffractive production models, see1240S)1240Q 势模型 potentialmodels1240R 边缘碰撞模型(一个或多个粒子交换) peripheral models (one or more particle exchange)1240S 多重边缘碰撞模型和多雷其模型(包括衍射和衍射生成模型)multiperipheral and multi　Reggemodels(inc.diffraction and diffractive productionmodels)1240V 矢量介子优势 Vector-mesondominance 1270 强子质量公式hadron mass formulas1290 其它各种理论设想与模型miscellaneous theoretical ideas and models1300 具体基本粒子反应和唯象论specific elementary particle reactions and phenomenology1310 轻子间的弱相互作用和电磁相互作用weak and electromagnetic interactions of leptons1315 中微子相互作用(包括宇宙射线相互作用)neutrino interactions(inc.interactions involvingcosmic rays)1320 介子的轻子与半轻子衰变leptonic and semileptonic decays of mesons1320C π衰变 pidecays1320E K衰变 Kdecays1320G Ψ/J介子、Υ介子、Φ介子psi/J, upsilon, phi mesons1320H B介子轻子/半轻子衰变 Bmesonleptonic/semileptonicdecays 1320I f介子轻子/半轻子衰变 fmesonleptonic/semileptonicdecays 1320J 其它介子衰变other meson decays1325 介子的强子衰变 hadronicdecaysofmesons 1330 重子的衰变 decaysofbaryons1330C 轻子与半轻子衰变leptonic and semileptonic decays1330E 强子衰变 hadronicdecays 1335 轻子的衰变 decaysofleptons1338 中间玻色子和希格斯玻色子的衰变decays of intermediate and Higgs Bosons1340 电磁过程与特性electromagnetic processes and properties1340D 电磁质量差electromagnetic mass differences1340F 电磁形状因子、电矩和磁矩electromagnetic form factors; electric and magnetic moments1340H 电磁衰变 electromagneticdecays1340K 强相互作用和弱相互作用过程的电磁修正electromagnetic corrections to strong and weakinteraction processes1360 光子及带电轻子与强子的相互作用(中微子相互作用见1315)photon and charged　lepton interactions withhadrons(for neutrino interactions, see 1315)1360F 弹性散射与康普顿散射elastic and Compton scattering1360H 总截面和单举(反应)截面(包括深度非弹性过程)total and inclusive crosssections(inc.deep-inelastic processes)1360K 介子产生 mesonproduction 1360M 介子共振产生 Meson-resonanceproduction 1360P 重子和重子共振产生baryon and baryon resonance production1365 电子-正电子碰撞产生强子hadron production by electron-positron collisions1375 强子诱发的低能和中能反应及散射(能量≤10GeV见1385)Hadron-induced low　energy and intermediate　energy reactions and scattering, energy ≤10GeV( for higher energies, see 1385)1375C 核子-核子相互作用,包括反核子和氘核等(能量≤10GeV;核中的核子-核子相互作用见2130)Nucleon-nucleon interactions, includingantinucleon, deuteron, etc. (energy ≤10GeV)(for n-n interactions in nuclei, see 2130)1375E 超子-核子相互作用(能量≤10GeV)Hyperon-nucleon interactions (energy ≤10 GeV)1375G π介子-重子相互作用(能量≤10GeV) Pion-baryon interactions (energy ≤10 GeV)1375J K介子-重子相互作用(能量≤10GeV) Kaon-baryon interactions (energy ≤10 GeV)1375L 介子-介子相互作用(能量≤10GeV)Meson-meson interactions (energy ≤10 GeV) 1380 光子-光子相互作用和散射Photon-photon interactions and scattering1385 强子诱发的高能和超高能相互作用(能量>10GeV)(低能情况见1375)Hadron-induced high-energy andsuper-high-energy interactions, energy > 10GeV(for low energies, see 1375)1385D 弹性散射(能量=10GeV) elastic scattering (energy = 10 GeV)1385F 非弹性散射、双粒子终态(能量>10GeV)inelastic scattering, two-particle final states(energy > 10 GeV)1385H 非弹性散射、多粒子终态(能量>10GeV)inelastic scattering, many-particle final states(energy>10GeV)1385K 单举反应,包括总截面(能量>10GeV)inclusive reactions, including total cross sections,(energy > 10 GeV)1385M 宇宙射线相互作用(9440宇宙线) cosmic ray interactions(9440 cosmic rays)1385N 强子诱发的高能相互作用(能量>1TeV)hadron induced very high energyinteractions(energy>1 TeV)1387 大Q2基本粒子相互作用中的射流jets in large-Q2 elementary particle interactions 1388 相互作用和散射中的极化polarisation in interactions and scattering1390 基本粒子的具体反应及唯象论的其它论题other topics in specific reactions andphenomenology of elementary particles1400 具体粒子的性质与共振properties of specific particles and resonances1420 重子与重子共振(包括反粒子) baryons and baryon resonances(inc.antiparticles) 1420C 中子 neutrons1420E 质子 protons1420G s=0时的重子共振baryon resonances with s=01420J 超子和超子共振hyperons and hyperon resonances1420P 双重子 dibaryons1440 介子和介子共振mesons and meson resonances1440D π介子 pimesons1440F K介子 Kmesons1440K Ρ介子、Ω介子和η介子rho, omega, and eta mesons1440L d介子和F介子 d and F mesons1440N Ψ/J介子、Υ介子、Φ介子psi/J, upsilon, phi mesons1440P 其它介子 othermesons1460 轻子 leptons1460C 电子和正电子 electronsandpositrons 1460E μ介子 muons1460G 中微子 neutrinos1460J 重轻子 heavyleptons 1480 其它粒子和假设粒子other and hypothetical particles1480A 光子 photons1480D 夸克和胶子 quarksandgluons 1480F 中间玻色子 intermediateBosons 1480H 磁单极子 magneticmonopoles1480J 超对称粒子(包括标量粒子，超粒子和超离子)Supersymmetric particles(inc.scalarparticles,superparticles and superions)1480K 其它(包括快子) others(inc.tachyons)2000 核物理学 NUCLEARPHYSICS 2100 核结构 nuclearstructure2110 核的一般和平均性质;核能级性质(按质量范围分类的具体核的性质见2700)general and average properties of nuclei;properties of nuclear energy levels(for propertiesof specific nuclei listed by mass ranges, see 2700)2110D 结合能和质量binding energy and masses2110F 形状、电荷、半径和形状因子shape, charge, radius and form factor s2110H 自旋、宇称和同位旋spin, parity, and isobaric spin2110J 谱因子 spectroscopicfactors 2110K 电磁矩 electromagneticmoments 2110M 能级密度和结构level density and structure2110P 单粒子能级结构single particle structure in levels2110R 集团能级结构(包括旋转能带) collective structure in levels(inc.rotational bands) 2110S 库仑效应 Coulombeffects2130 核力(1375C核子-核子相互作用) nuclear forces(1375C nucleon-nucleon interactions)2140 少核子系统 Few-nucleonsystems2160 核结构模型与方法(强子的原子和分子见3610)nuclear　structure models and methods(forhadronic atoms and molecules, see 3610)2160C 壳层模型 shellmodel2160E 集体模型 collectivemodels 2160F 群论模型models based on group theory2160G 集团模型 clustermodels 2160J 哈特里-福克和随机-相位近似Hartree-Fock and random-phase approximations 2165 核物质 nuclearmatter 2180 超核 hypernuclei 2190 核结构的其它论题other topics in nuclear structure2300 放射性和电磁跃迁(8255放射化学)radioactivity and electromagnetic transitions(8255 radiochemistry)2320 电磁跃迁 electromagnetictransitions 2320C 寿命和跃迁几率lifetimes and transition probabilities2320E 角分布和校正测量angular distribution and correlation measurements2320G 多极混合比率 multipolemixingratios 2320J 多极矩阵元素 multipolematrixelements 2320L γ跃迁和能级gamma transitions and level energies2320N 内转换和核外效应internal conversion and extranuclear effects 2320Q 核共振荧光nuclear resonance fluorescence2340 β衰变;电子与μ子俘获beta decay; electron and muon capture2340B 弱相互作用和β衰变的轻子特性weak interaction and lepton aspects of beta decay2340H 核矩阵元和从β衰变推断核结构nuclear matrix elements and nuclear structure inferred from beta decay2360 α衰变 alphadecay 2390 核衰变和放射性的其它论题other topics in nuclear decay and radioactivity 2400 核反应和散射:总论nuclear reactions and scattering:general2410 核反应和散射模型与方法nuclear reaction and scattering models and methods2410D 耦合道和多体论方法coupled　channel and many　body　theory methods2410F 平面和扭曲波玻恩近似法Plane- and distorted-wave Born approximations 2410H 光学模型和衍射模型optical and diffraction models2430 共振反应与散射resonance reactions and scattering2430C 巨共振 giantresonances 2430F 同位旋相似共振 isobaricanalogresonances 2450 直接反应 directreactions 2460 统计理论和涨落statistical theory and fluctuations2470 反应和散射中的极化polarization in reactions and scattering2475 裂变的一般性质general properties of fission2485 原子核和核形成过程的夸克模型quark models in nuclei and nuclear processes2490 核反应和散射的其它论题:一般问题other topics in nuclear reactions and scattering:general2500 核反应和散射:具体反应nuclear reactions and scattering:specific reactions2510 少核子系统的核反应与散射nuclear reactions and scattering involving few-nucleon systems2520 光致核反应和光子散射 photonuclearreactions and photon scattering 2530 轻子诱发反应与散射Lepton-induced reactions and scattering 2530C 电子和正电子反应与散射electron and positron reactions and scattering 2530E μ介子反应和散射muon reactions and scattering2530G 中微子反应和散射neutrino reactions and scattering。

Euler–Lagrange equation

Euler–Lagrange equationFrom Wikipedia, the free encyclopediaJump to: navigation, searchIn calculus of variations, the Euler–Lagrange equation, or Lagrange's equation, is a differential equation whose solutions are the functions for which a given functional is stationary. It was developed by Swiss mathematician Leonhard Euler and Italian mathematician Joseph Louis Lagrange in the 1750s.Because a differentiable functional is stationary at its local maxima and minima, the Euler–Lagrange equation is useful for solving optimization problems in which, given some functional, one seeks the function minimizing (or maximizing) it. This is analogous to Fermat's theorem in calculus, stating that where a differentiable function attains its local extrema, its derivative is zero.In Lagrangian mechanics, because of Hamilton's principle of stationary action, the evolution of a physical system is described by the solutions to the Euler–Lagrange equation for the action of the system. In classical mechanics, it is equivalent to Newton's laws of motion, but it has the advantage that it takes the same form in any system of generalized coordinates, and it is better suited to generalizations (see, for example, the "Field theory" section below).Contents1 History∙ 2 Statement∙ 3 Exampleso 3.1 Classical mechanics▪ 3.1.1 Basic method▪ 3.1.2 Particle in a conservative force field o 3.2 Field theory∙ 4 Variations for several functions, several variables, and higher derivativeso 4.1 Single function of single variable with higherderivativeso 4.2 Several functions of one variableo 4.3 Single function of several variableso 4.4 Several functions of several variableso 4.5 Single function of two variables with higher derivatives ∙ 5 Notes∙ 6 References∙7 See alsoHistoryThe Euler–Lagrange equation was developed in the 1750s by Euler and Lagrange in connection with their studies of the tautochrone problem. This is the problem of determining a curve on which a weighted particle will fall to a fixed point in a fixed amount of time, independent of the starting point.Lagrange solved this problem in 1755 and sent the solution to Euler. The two further developed Lagrange's method and applied it to mechanics, which led to the formulation of Lagrangian mechanics. Their correspondence ultimately led to the calculus of variations, a term coined by Euler himself in 1766.[1]StatementThe Euler–Lagrange equation is an equation satisfied by a function q of a real argument t which is a stationary point of the functionalwhere:∙q is the function to be found:such that q is differentiable, q(a) = x a, and q(b) = x b;∙q′ is the derivative of q:TX being the tangent bundle of X (the space of possible values of derivatives of functions with values in X);L is a real-valued function with continuous first partial derivatives:The Euler–Lagrange equation, then, is the ordinary differential equationwhere L x and L v denote the partial derivatives of L with respect to the second and third arguments, respectively.If the dimension of the space X is greater than 1, this is a system of differential equations, one for each component:Derivation of one-dimensionalEuler-Lagrange equationAlternate derivation of one-dimensionalEuler-Lagrange equationExamplesA standard example is finding the real-valued function on the interval [a, b], such that f(a) = c and f(b) = d, the length of whose graph is as short as possible. The length of the graph of f is:the integrand function being 2'1)',,(y y y x L += evax , y , y ′)= (x , f (x ), f ′(x )).The partial derivatives of L are:By substituting these into the Euler –Lagrange equation, we obtainthat is, the function must have constant first derivative, and thus its graph is a straight line .Classical mechanicsBasic methodTo find the equations of motions for a given system, one only has to follow these steps:∙ From the kinetic energy T , and the potential energy V , compute the Lagrangian L = T − V .∙ Compute .∙ Compute and from it, . It is important that be treated as a complete variable in its own right, and not as a derivative. ∙ Equate. This is, of course, the Euler –Lagrange equation.∙Solve the differential equation obtained in the preceding step. At this point, is treated "normally". Note that the above might bea system of equations and not simply one equation.Particle in a conservative force fieldThe motion of a single particle in a conservative force field (for example, the gravitational force) can be determined by requiring the action to be stationary, by Hamilton's principle. The action for this system iswhere x(t) is the position of the particle at time t. The dot above is Newton's notation for the time derivative: thus ẋ(t) is the particle velocity, v(t). In the equation above, L is the Lagrangian (the kinetic energy minus the potential energy):where:∙m is the mass of the particle (assumed to be constant in classical physics);∙v i is the i-th component of the vector v in a Cartesian coordinate system (the same notation will be used for other vectors);∙U is the potential of the conservative force.In this case, the Lagrangian does not vary with its first argument t. (By Noether's theorem, such symmetries of the system correspond to conservation laws. In particular, the invariance of the Lagrangian with respect to time implies the conservation of energy.)By partial differentiation of the above Lagrangian, we find:where the force is F = −∇U (the negative gradient of the potential, by definition of conservative force), and p is the momentum. By substitutingthese into the Euler–Lagrange equation, we obtain a system of second-order differential equations for the coordinates on the particle's trajectory,which can be solved on the interval [t0, t1], given the boundary values x(t0) and x i(t1). In vector notation, this system readsior, using the momentum,which is Newton's second law.Field theoryThis section contains too much jargon and may need simplification or further explanation. Please discuss this issue on the talk page, and/or remove or explain jargon terms used in the article. Editing help is available. (December 2009)Field theories, both classical field theory and quantum field theory, deal with continuous coordinates, and like classical mechanics, has its own Euler–Lagrange equation of motion for a field,where∙is the field, and∙is a vector differential operator:Note: Not all classical fields are assumed commuting/bosonic variables, (like the Dirac field, the Weyl field, the Rarita-Schwinger field) are fermionic and so, when trying to get the field equations from the Lagrangian density, one must choose whether to use the right or the left derivative of the Lagrangian density (which is a boson) with respect to the fields and their first space-time derivatives which arefermionic/anticommuting objects.There are several examples of applying the Euler–Lagrange equation to various Lagrangians:∙Dirac equation;∙Proca equation;∙electromagnetic tensor;∙Korteweg–de Vries equation;∙quantum electrodynamics.Variations for several functions, several variables, and higher derivativesSingle function of single variable with higher derivatives The stationary values of the functionalcan be obtained from the Euler-Lagrange equation[2]Several functions of one variableIf the problem involves finding several functions () of a single independent variable (x) that define an extremum of the functionalthen the corresponding Euler-Lagrange equations are[2]Single function of several variablesA multi-dimensional generalization comes from considering a function on n variables. If Ω is some surface, thenis extremized only if f satisfies the partial differential equationWhen n = 2 and is the energy functional, this leads to the soap-film minimal surface problem.Several functions of several variablesIf there are several unknown functions to be determined and several variables such thatthe system of Euler-Lagrange equations is[2]Single function of two variables with higher derivativesIf there is a single unknown function to be determined that is dependent on two variables and their higher derivatives such thatthe Euler-Lagrange equation is[2]Notes1.^ A short biography of Lagrange2.^ a b c d Courant, R. and Hilbert, D., 1953, Methods of Mathematical Physics:Vol I, Interscience Publishers, New York.References∙Weisstein, Eric W., "Euler-Lagrange Differential Equation" from MathWorld.∙Calculus of Variations on PlanetMath∙Izrail Moiseevish Gelfand (1963). Calculus of Variations. Dover.ISBN0-486-41448-5.∙Calculus of Variations at Example (Provides examples of problems from the calculus of variations that involve theEuler–Lagrange equations.)See also∙Lagrangian mechanics∙Hamiltonian mechanics∙Analytical mechanics∙Beltrami identity。

explanatory sequential mixed method

explanatory sequential mixed method Explanatory Sequential Mixed MethodsIntroduction:Research methodology plays a crucial role in informing decision-making and understanding complex phenomena. Mixed methods research designs have gained popularity in recent years due to their ability to provide a comprehensive and holistic understanding of a research problem. One such design is the explanatory sequential mixed methods approach, which incorporates both quantitative and qualitative components in a sequential manner. This article aims to explain the explanatory sequential mixed methods design, its components, advantages, and limitations, with examples from various research studies.Components of the Explanatory Sequential Mixed Methods Design:The explanatory sequential mixed methods design consists of two distinct phases, namely the quantitative phase and the qualitative phase. In this design, the quantitative component is conducted first and is followed by the qualitative component. The purpose of the quantitative phase is to explore relationships and identify patterns in the data, while the qualitative phase aims to provide a deeper understanding of these relationships and patterns.Quantitative Phase:During the quantitative phase, researchers collect and analyze quantitative data using structured surveys, experiments, orsecondary data sources. The goal is to generate numerical data that can be analyzed using statistical techniques to test hypotheses or patterns. The findings from the quantitative analysis inform the selection of participants and the focus of the qualitative phase.Qualitative Phase:The qualitative phase involves collecting and analyzing qualitative data, such as interviews, observations, or document analysis. The purpose of this phase is to understand the underlying reasons and processes behind the quantitative findings. Qualitative data collection methods allow researchers to gather rich and detailed information that provides context and meaning to the statistical results. The qualitative analysis involves coding, categorizing, and interpreting the data to identify themes and patterns.Integration of Findings:The integration of findings is a crucial step in the explanatory sequential mixed methods design. During this stage, researchers compare and contrast the findings from both the quantitative and qualitative phases to develop a comprehensive understanding of the research problem. This integration can occur in different ways, such as comparing the results side by side, using statistical findings to interpret qualitative data, or using qualitative findings to explain statistical patterns. The aim is to provide a richer and more nuanced understanding of the research topic than could be achieved through a single method or phase.Advantages of the Explanatory Sequential Mixed Methods Design:The explanatory sequential mixed methods design offers several advantages over traditional quantitative or qualitative approaches. Firstly, it provides a more comprehensive understanding of the research problem by combining quantitative and qualitative data. The sequential nature of the design allows researchers to build on the findings from the quantitative phase and explore them in more depth during the qualitative phase. This approach strengthens the validity and reliability of the research findings.Secondly, the design allows researchers to address research questions that require both numerical data and contextual information. Some phenomena cannot be fully understood or explained by numbers alone, and qualitative data can provide valuable insights into the underlying reasons and processes.Thirdly, the design enhances triangulation, which refers to the use of multiple data sources or methods to validate findings. By combining quantitative and qualitative data, researchers can compare and contrast the different perspectives and identify converging or conflicting evidence. This strengthens the overall validity and trustworthiness of the research.Limitations of the Explanatory Sequential Mixed Methods Design:Despite its advantages, the explanatory sequential mixed methods design also has some limitations. Firstly, it requires time and resources to implement both quantitative and qualitative components. Researchers need to consider the feasibility of conducting both phases and ensure that they have the necessaryskills and expertise in both quantitative and qualitative methods.Secondly, the design may face challenges in terms of data integration and interpretation. Combining quantitative and qualitative findings can be complex and may require expertise in both types of data analysis. Researchers need to carefully consider how to integrate the findings in a meaningful and coherent manner.Example Studies:To illustrate the application of the explanatory sequential mixed methods design, three example studies are presented below:1. A study on the effectiveness of a health intervention program uses a quantitative survey to measure participants' health outcomes and satisfaction levels. The qualitative phase involves in-depth interviews with a sub-sample of participants to explore their experiences and perceptions of the program.2. A study on the impact of a teacher training program uses a quantitative pre-test and post-test design to measure changes in students' academic performance. The qualitative phase involves focus group discussions with teachers to understand their perspectives on the program's effectiveness and challenges.3. A study on the factors influencing employee satisfaction and retention uses a quantitative survey to measure employee satisfaction levels. The qualitative phase involves semi-structured interviews with a subset of employees to explore the underlying reasons for their satisfaction or dissatisfaction.Conclusion:The explanatory sequential mixed methods design offers a powerful approach to research that combines the strengths of quantitative and qualitative methods. By integrating numerical data with contextual information, this design provides a comprehensive and holistic understanding of research problems. Despite its limitations, the design has gained popularity due to its ability to address complex research questions and enhance the validity and reliability of findings. Researchers should consider the feasibility and appropriateness of this design for their specific research objectives and resources.。

“理商”测量决策能力量表初步修订(查).docx

硕士学位论文“理商”的测量：决策能力量表初步修订冯田培养类别全日制学号 2472013038 学位类型学术学位一级学科(专业类) 心理学二级学科(专业) 应用心理学研究方向测量与评估指导教师肖玮副教授培养单位医学心理系二O 一六年六月分类号U D C密级目录目录 (1)缩略语表 (4)中文摘要 (5)ABSTRACT (7)前言 (9)文献回顾 (11)1 理性思维能力 (12)2 决策能力 (13)2.1 决策能力概念 (13)2.2 决策的测量 (15)2.3 风险与决策研究 (19)正文 (21)第一部量表的修订形成 (21)1 研究目的 (21)3 翻译及修订 (21)3.1 量表的本土化修订 (21)3.2 正式形成决策能力量表内容及计分 (23)4 预实验 (26)5 第一轮施测 (26)5.1 目的 (26)5.2 方法 (26)5.3 数据处理 (27)5.4 描述性数据分析 (27)5.5 项目分析 (28)6 讨论 (30)6.1 A-DMC修订 (30)6.2 A-DMC中文版与原版描述性数据分析异同 (30)6.3 A-DMC项目分析 (31)第二部分A-DMC量表的信度、效度 (31)1 目的 (31)2 方法 (31)2.1 工具 (31)2.2 被试 (34)2.3 施测过程 (34)2.4 数据的收集、筛查和录入 (34)3 信度 (34)4 效度 (35)4.1 内容效度 (35)4.2 结构效度 (36)4.3 校标效度 (38)3 讨论 (41)5.1 决策能力量表信度良好 (42)5.2 决策能力量表内容效度、结构效度良好 (42)5.3 决策能力量表效标效度良好 (43)第三部分模拟现实情境任务中A-DMC效度的验证 (44)1 研究目的 (44)2 方法 (45)2.1 工具 (45)2.2 统计方法 (48)2.3 研究对象 (48)3 结果分析 (48)3.1 决策能力不同个体分组 (48)3.2 高低不同决策能力个体概率已知的剑桥博弈任务中的表现 (48)3.3 高低不同决策能力个体模糊决策爱荷华博弈任务中的表现 (49)4 讨论 (50)4.1 高决策能力个体决策质量好 (50)4.2 高决策能力个体风险调节能力强 (51)4.3 高决策能力者在模糊决策中学习能力优 (51)4.4 高决策能力者在模糊决策中发现掌握应用规则能力更强 (52)小结 (52)附录 .....................................................................错误！未定义书签。

METHOD OF MANUFACTURING METALS ANDOR GENERATING S

专利名称：METHOD OF MANUFACTURING METALS AND/OR GENERATING SLAG发明人：Sven Santen,Jerome Feinman,Sune Eriksson 申请号：US06/720553申请日：19850405公开号：US04601752A公开日：19860722专利内容由知识产权出版社提供摘要：Finely powdered oxidde ore is introduced (at 17) in a reactor (11), possibly together with slag-formers, and treated in three zones in the reactor. The material is preheated and possibly melted in an upper, oxidizing zone by the combustion of carbon monoxide and hydrogen gas from the middle zone below with a gas containing oxygen. In a middle zone consisting of a slag bath, the preheated and possibly melted oxide material at least partially reduced by the simultaneous injection of carbonaceous material and/or material containing hydrocarbon (15, 16) and thermal energy supplied primarily by means of gas heated in a plasma generator (14). Finally, the material is caused to sink into a lower zone at the bottom of the reactor, from where it is tapped intermittently, together with the slag, through a tapping aperture (19).申请人：SKF STEEL ENGINEERING AB代理机构：Armstrong, Nikaido, Marmelstein & Kubovcik更多信息请下载全文后查看。

APPARATUS AND METHOD FOR COOLING BULK MATERIALS

专利名称：APPARATUS AND METHOD FOR COOLING BULK MATERIALS发明人：LAGAR GARCIA, LUIS,KAESTINGSCHAEFER, GERHARD,BRENTRUP, LUDGER,DILLY,DIRK,DRIEMEIER, GUENTER,KOENNING,LUDWIG,NIEMERG, HERMANN,WILLMS,ELKE,SCHMIDT, ARND,SCHNIEDER, ERICH申请号：EP2007055602申请日：20070606公开号：WO2007141307A3公开日：20080228专利内容由知识产权出版社提供摘要：The invention relates to an apparatus and method for cooling bulk materials, the physical and chemical properties of which depend on the cooling medium, comprising: a. a base through which a cooling medium can flow and on which the bulk material is transported and cooled in the process, b. means for feeding a gaseous, non-oxidizing cooling medium, for example water vapour, c. means for the separate discharge of the heated, non-oxidizing cooling medium, d. a device for the thermal treatment of the discharged, heated, non-oxidizing cooling medium, e. means for recirculating the thermally treated, non-oxidizing cooling medium to the means for feeding the non-oxidizing cooling medium, f. means for feeding a gaseous, oxidizing cooling medium, for example air, g. means for the separate discharge of the heated, oxidizing cooling medium, h. and comprising a plurality of cooler sections and associated means for setting and regulating the cooling medium flows in order to optionally set either non-oxidizingcooling conditions or oxidizing cooling conditions in all the cooler sections or in individual cooler sections.申请人：POLYSIUS AG,LAGAR GARCIA, LUIS,KAESTINGSCHAEFER,GERHARD,BRENTRUP, LUDGER,DILLY, DIRK,DRIEMEIER, GUENTER,KOENNING, LUDWIG,NIEMERG, HERMANN,WILLMS, ELKE,SCHMIDT, ARND,SCHNIEDER, ERICH 更多信息请下载全文后查看。

关于finfet gaa器件的专业书

关于finfet gaa器件的专业书
关于FinFET和GAA器件的专业书有很多，其中一本较为经典的书籍是《The GAAFET Roadmap to 3nm and Beyond》。

这本书详细介绍了GAA（全环栅）纳米片场效应晶体管（FET）和FinFET（鳍式场效应晶体管）的技术发展历程，以及它们在纳米尺度上的应用和挑战。

此外，这本书还展望了未来晶体管技术的发展方向，并提供了关于如何克服当前技术障碍的建议。

此外，还有一本名为《Advanced Nanomaterials: Properties, Devices, and Applications》的书籍也对FinFET和GAA器件进行了介绍。

这本书
涵盖了纳米材料的基本概念、性质、制备方法、表征手段以及在器件中的应用，包括FinFET和GAA器件等。

如果需要更多关于FinFET和GAA器件的专业书籍，建议在学术图书馆或在线书店进行搜索，以获取更全面的信息。

有效质量近似(effectivemassapproximation)百科小物理

有效质量近似（effectivemassapproximatio n）百科小物理
有效质量近似（effectivemassapproximation）
百科小物理
苏霍姆林斯基说：让学生变得聪明的办法，不是补课，不是增加作业量，而是阅读、阅读、再阅读。

学生知识的获取、能力的提高、思想的启迪、情感的熏陶、品质的铸就很大程度上来源于阅读。

我们应该重视它，欢迎阅读有效质量近似(effectivemassapproximation)百科小物理。

有效质量近似（effectivemassapproximation）
有效质量近似(effectivemassapproximation)
固体中电子在晶格势场或再附加有外力作用场中的运动，在用薛定谔(Schrdinger)方程研究电子能量E(K)(能带)时，与牛顿(Newton)力学对比定义的电子有效质量m*为
`M_{ij}^**=hbar^2//[frac{partial^2E(bb{K})}{partial K_ipartialK_j}]`
(i,j=1,2,3)
它是二阶张量形式，这里K是波矢。

在变换到主轴时为：$M_i^**=hbar^2//[partial^2E(bb{K})//partialK_i^2]$，$hbar$为除以2的普朗克常数。

m*中实际包含了晶格场的作用，且与K有关，所以与自由电子质量m有区别。

但电子能谱较复杂时，理论上要精确定出m*值是困难的，因此对多体问题一般也是用近似方法去研究。

这种准经典的m*可与经典牛顿力学比照，可使问题相对简化，将m*可看做参量对待，。