Annealing kinetics of fission tracks in zircon_an experimental study_1995

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Study of the kinetics of nucleation and growth

Study of the kinetics of nucleation and growth

Study of the kinetics of nucleationand growthNucleation and growth are two fundamental processes that occur in many systems, from chemical reactions to the formation of crystals. Understanding the kinetics of nucleation and growth is essential for predicting and controlling the properties of materials. In this article, we will explore the principles behind these processes and examine some of the experimental techniques used to study them.First, let us consider nucleation, which is the process by which a new phase or crystal is formed from a homogeneous solution or gas. Nucleation occurs when the concentration of particles in the solution or gas exceeds a certain critical value, leading to the formation of small clusters of particles. These clusters continue to grow by the addition of more particles until they reach a critical size, at which point they are stable and can continue to grow without further nucleation.The kinetics of nucleation can be described using a variety of models, depending on the nature of the system and the experimental conditions. One commonly used model is the classical nucleation theory, which assumes that the nucleation rate is proportional to the concentration of particles in the solution and the free energy barrier for nucleation. The free energy barrier depends on factors such as the surface energy between the new phase and the existing phase, the size of the critical nucleus, and the temperature of the system.Experimental methods for studying nucleation include microscopy techniques such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM), which can be used to observe the formation and growth of clusters. X-ray diffraction (XRD) can also be used to identify the crystal structure of the new phase.Now let us turn to growth, which is the process by which the clusters formed during nucleation continue to increase in size. Growth occurs when particles in the solution or gas are able to attach to the surface of the cluster and become incorporated into thecrystal lattice. The rate of crystal growth is determined by the concentration of particles in the solution or gas, the surface area of the crystal, and the diffusion coefficient of the particles.The kinetics of growth can be described using the Lifshitz-Slyozov-Wagner (LSW) theory, which assumes that the rate of crystal growth is inversely proportional to the cube of the particle size. This means that smaller particles grow faster than larger particles, leading to a decrease in the overall particle size distribution over time.Experimental methods for studying crystal growth include techniques such as time-resolved XRD, which can be used to monitor the evolution of the crystal structure over time. In situ optical microscopy can also be used to observe the growth of individual crystals in real time.In summary, the study of the kinetics of nucleation and growth is essential for understanding the behavior of materials in a wide range of applications. The principles behind these processes are complex, but can be described using mathematical models such as classical nucleation theory and the LSW theory. A variety of experimental techniques are available to study these processes, including microscopy, XRD, and optical techniques. By combining theoretical models with experimental data, researchers can gain a detailed understanding of the mechanisms behind nucleation and growth, and develop new materials with tailored properties.。

玻璃的流变性与热力学性能

玻璃的流变性与热力学性能

Rheological and thermodynamic behaviors of different calcium aluminosilicate melts with the same non-bridgingoxygen contentM.Solvanga,1,Y.Z.Yueb,*,S.L.Jensen c ,D.B.DingwelldaDepartment of Production,Aalborg University,Aalborg,DenmarkbSection of Chemistry,Department of Life Sciences,Aalborg University,Aalborg,DenmarkcRockwool International A/S,Hedehusene,DenmarkdDepartment of Earth and Environmental Sciences,University of Munich,Munich,GermanyReceived 28July 2003;received in revised form 8January 2004AbstractThe relationships between the chemical composition and the derivative rheological and thermodynamic values have been determined for two melt series in the anorthite–wollastonite–gehlenite (An–Wo–Geh)compatibility triangle.The melt series have 0.5and 1non-bridging oxygens per tetrahedrally coordinated cation (NBO/T),respectively.The influences of the ratio Si/(Si +AlCa 1=2)and NBO/T on the fragility and the configurational entropy at T g are evaluated.Linear dependencies of the viscosity,the glass transition temperature and the fragility on the ratio Si/(Si +AlCa 1=2)are found for the two melt series.A crossover in the viscosity–temperature relationship is observed for both series,i.e.an inverse compositional dependence of viscosity in the high and low viscous range.The crossover presumably reflects different responses of the adjustment of melt structure to the substitution of Al 3þ+1/2Ca 2þfor Si 4þin the low versus the high viscous ranges.The crossover shifts to higher temperature with increasing NBO/T.Ó2004Elsevier B.V.All rights reserved.PACS:65.50;83.70.G;64.70.Pf1.IntroductionUnderstanding rheology and thermodynamics of the calcium aluminosilicate melts is important for the glass fiber industry,especially the stone wool industry,be-cause it is beneficial to revealing the relationships between chemical composition,properties,and micro-structure of glass fibers.Studying the dependencies of fiber properties,fiber quality,fiber drawing ability on melt composition are crucial for optimizing fiber prop-erties (e.g.bio-solubility and mechanical strength of fi-bers)and production conditions.The melts for making the stone fibers are multicomponent systems,each chemical component of which has a different effect on the rheological and thermodynamic properties.In this work,the three-component aluminosilicate systems:i.e.the CaO–Al 2O 3–SiO 2(CAS)systems are investigated.The three components make up approximately 80mol%of the stone wool fibers.Previous investigations of the compositional depen-dence of melt properties in the CAS system have been focused primarily on the metaluminous join SiO 2–CaAl 2O 4,for which the amount of non-bridging oxygen per tetrahedrally coordinated cation (NBO/T)is equal to 0.In contrast,this study is aimed at increasing the knowledge about the ‘peralkaline’field by studying the compositional dependence of melt properties along the lines with NBO/T ¼0.5and 1.This will allow us to study the compositional effect on the rheological and thermodynamic properties at a constant degree of poly-merization and to explore the structural changes along and between the lines.The chemical compositions of the investigated melts are chosen within the anorthite–wol-lastonite–gehlenite (CaAl 2Si 2O 8–CaSiO 3–Ca 2Al 2SiO 7)(An–Wo–Geh)compatibility triangle (see Fig.1).So far*Corresponding author.Tel.:+45-96358522;fax:+45-96350558.E-mail address:yy@bio.auc.dk (Y.Z.Yue).1Present address:Materials Research Department,RisøNational Laboratory,Frederiksborgvej 399,DK-4000Roskilde,Denmark.0022-3093/$-see front matter Ó2004Elsevier B.V.All rights reserved.doi:10.1016/j.jnoncrysol.2004.02.009Journal of Non-Crystalline Solids 336(2004)179–188the rheological and thermodynamic aspects of the melts in this triangle have not been systematically studied. Hence,this work will contribute to broadening and deepening the knowledge about structure and properties of high aluminosilicate melts.The rheological and thermodynamic properties of aluminosilicate melts are determined by the arrange-ment of the tetrahedral structural units in the melt, which relates to the chemical bonding situation within a structural unit and between units.Aluminum differs from silicon,since tetrahedrally coordinated aluminum has to be charge-balanced by either two alkali cations or one earth alkaline cation[1].The charge-balancing ca-tions for the Al3þtetrahedra play a large role in the melt structure.The structural role of the alkali or earth alkaline cations depends on the melt composition,i.e. whether or not Al3þis present in the melt[2].The short range ordering in the aluminosilicate network depends on the composition and the charge-balancing or net-work modifying cations.For aluminosilicates it is as-sumed that an energetically favorably case is a random occurrence of the network forming linkages Si–O–Si,Si–O–Al and Al–O–Al.The principle of Al-avoidance[3] postulates that the Al–O–Si linkage is more favorable than the combination of Si–O–Si and Al–O–Al linkages. This postulate means that the short range ordering is not random(not totally disordered).A tendency towards Al-avoidance is inferred based on29Si MAS NMR line widths in aluminosilicate glasses[4].However the pres-ence of a small amount of Si–O–Si in glasses of anorthite compositions observed by triple quantum MAS NMR spectroscopy[5]suggests some Al–O–Al linkages[6].The aim of this work is to study the compositional dependencies of melt viscosity,glass transition temper-ature(T g),heat capacity(C p)as well as the derivative properties such as activation energy for viscousflow (D H g),fragility[7]and configurational entropy at T g (S cðT gÞ).The paper presents the results of systematic viscometric and calorimetric experiments on the melts covered by the An–Wo–Geh compatibility triangle,and discusses the difference in the structural arrangement in the high compared to that in the low viscous range. 2.Theoretical modelsViscosity is one of the melt properties,which has been studied intensively due to its sensitivity to compositional variation[8].At afixed temperature it varies by orders of magnitude as a function of composition.An increase in temperature decreases the viscosity,as the structural rearrangements in the melt become easier[8].The viscosity–temperature relationship has been de-scribed by various theories.Adam and Gibbs[9]found the correlation between the structural relaxation time of a glass forming melt and the configurational entropy (S c).In their analysis the relaxation time increases with 1=TS c.The S c decreases with decreasing temperature until it vanishes at the Kauzmann temperature.The Adam and Gibbs theory explains the temperature dependence of the relaxation in terms of the temperature dependence of the size of the cooperatively rearranging region[9].In this work the Adam–Gibbs equation(AG equa-tion)wasfitted to experimental viscosity data to derive S cðT gÞ.The AG equation is expressed aslog g¼log g1þBTS cðTÞ;ð1Þwhere g1is a pre-exponential constant and B is a con-stant containing a free-energy barrier which must be crossed by the rearranging group.The constant g1for the glass series studied in this work was obtained by fitting the viscosity data(in the range from g¼0:3to 1011Pa s)to Eq.(1),which equals2.88·10À4Pa s[10]. The viscosity range for the validity of Eq.(1)was dis-cussed in[11].S cðTÞcan be calculated from the equationS cðTÞ¼S cðT gÞþZ TT gD C pðTÞTd T;ð2Þwhere the D C pðTÞis the difference in heat capacity be-tween the liquid and the glassy state.For the silicate systems,the heat capacity of the liquid state,C p l,is only slightly temperature dependent and hence,can be approximately regarded as a constant.In this work,the C p value at T g is assigned as the heat capacity of the glassy state,C p g[10],Therefore,the D C pðTÞð¼C p lÀC p gÞcan also be treated as a constant D C p.Both C p l and C p g may be directly determined from the DSC measurement. Eq.(2)can thus be transformed into the formS cðTÞ¼S cðT gÞþD C p lnTT g:ð3Þ180M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188Introducing Eq.(3)into Eq.(1)leads to the equationlog g¼log g1þBT S cðT gÞþD C p ln Tg;ð4ÞS cðT gÞcan be obtained byfitting Eq.(4)to the viscosity–temperature data.Two contributions to the S cðTÞhave been involved:a chemical and a topological contribu-tion[12].The chemical contribution is independent of temperature,whereas the relative contribution from the topological arrangement increases with temperature. Finally,at high temperatures,the chemical contribution plays a minor role.The topological arrangement is re-flected by the increase of configurational entropy at T over that at T g,and it will increase more in a relative sense for compositions having a higher D C p.Avramov[13–15]proposed a three-parameter equa-tion that is able to predict the change in viscosity as a function of both temperature and composition.The model describes the kinetics of molecular motion in su-percooled melts[13]and the dependence of the viscosity on the entropy of the melt.According to Avramov,the structural units of the system jump with frequencies depending on the activation energy,which they have to overcome.The dependence of the activation energy on temperature is assumed to obey a power decay law [13–15].From this assumption,he proposed the equation describing the dependence of viscosity on temperature:log g¼log g1þe0T rTa;ð5Þwhere g1is a pre-exponent(in Pa s),i.e.the viscosity of a hypothetical liquid state for T!1,e0is the constantequal to log g Tr Àlog g1,a is a fragility index,and T r is areference temperature.In this work,T g is used as T r. Then,e0¼log g TgÀlog g1.The viscosity of silicate meltat T g is g Tg ¼1012Pa s.log g1and e0may be obtained byfitting the viscosity data to Eq.(5).For the melt series studied in this work,the optimal values of log g1and e0, which lead to bestfitting,are found to be)1.7and13.7,respectively,by using the relation log g Tg ¼log g1þe0¼12.Thus,the Avramov equation(AV equation)canbe rewritten aslog g¼À1:7þ13:7T gTa:ð6ÞThe two parameters,log g1and e0,are not sensitive tothe variation in chemical composition of the CAS sys-tems.However,the sensitivity of these parameters to thevariation in chemical composition has not been testedon other melt systems.The comparisons between the AG,the AV,and the VFT(Vogel–Fulcher–Tammann)equations[16–18]were made in[10]with respect to theirfitting qualities tothe viscosity data for the10CAS melts.Then,it wasfound that the order of thefitting quality isVFT<AG<AV,the average residual errors of whichwere0.116,0.113and0.063,respectively[19].3.ExperimentalTen melts covered by the CaAl2Si2O8–CaSiO3–CaAl2SiO7(anorthite–wollastonite–gehlenite)compati-bility triangle and placed along the two lines with NBO/T¼0.5and1,respectively,were synthesized(Fig.1).The melts were synthesized from analytical chemicalsSiO2,Al2O3and CaCO3in a platinum crucible at1898K for3h in a MoSi2box furnace.Subsequently the meltwas quenched on a metal plate.The chemical compo-sitions were analyzed using an X-rayfluorescence spec-trometer(XRF)(Philips1404).The compositions arelisted in Table1.The low viscosities(<104Pa s)were measured by means of a concentric cylinder viscometer in the tem-perature range from1316to1849K at ambient pressure.The viscometer consists of four parts:a furnace,a vis-cometer head,a spindle and a sample crucible.Thefurnace was a MoSi2box furnace(Deltech Inc.ModelDT-31-RS Mode EE)and the viscometer head was aBrookfield model RTVD with a full range torque of7.2·10À2N m,which both were controlled by aTable1The composition of the10CAS samplesSiO2(mol%)Al2O3(mol%)CaO(mol%)Si4þAl3þCa2þCAS149.48.342.30.460.150.39CAS245.610.543.90.410.190.40CAS341.312.746.10.370.220.41CAS437.314.747.90.330.260.42CAS533.016.450.50.280.280.43CAS649.815.135.10.430.260.30CAS744.117.438.50.380.300.33CAS839.519.940.50.330.330.34CAS934.822.542.70.280.370.35CAS1029.424.745.90.240.400.37The compositions are measured using XRF and given in mol%and the cation fraction.M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188181computer.The spindle and the sample crucible were made of Pt80Rh20.The details about both method and equipment are described in[20].The viscometer was calibrated using the National Bureau of Standards (NBS)710standard glass.The high viscosities(107–1012Pa s)were measured using the micropenetration method.The measurements were done in a vertical push-rod dilatometer(B€AHR DIL802V)[21].The Deutsche Glasstechnische Gesell-schaft(DGG)Standard Glass I was used for calibration.A good agreement was achieved between the measured viscosity and standard viscosity values,with the least square R2¼0:996[10].In the intermediate viscous range from104to107Pa s,it was impossible to measure the viscosities,because the strong tendency for the melts to crystallize hindered the measurements.A differential scanning calorimeter(DSC)(Netzsch STA449C)was used to determine T g and C p.The glass samples for the DSC measurements were the ones that had already been measured using the concentric cylin-der viscometer.The samples were drilled out from the viscometer crucible wherein the glass melt was left after finishing the concentric cylinder viscometer measure-ments.The size of the samples for DSC measurements were4·4·1mm.For each composition a baseline was measured with two empty crucibles.Then a standard sapphire sample was measured andfinally the sample was measured in two runs.Thefirst run was made in order to give the sample a defined thermal history,i.e.a given cooling rate that equals to the heating rate.The second run was made for determination of T g and C p. All measurements were done under argon with the heating rate10K/min.The maximum temperature of each measurement was approximately100K above T g. T g and C p were determined from the second DSC up-scan curves.T g was defined as the onset temperature of the glass transition peak on the second DSC upscan curve.4.ResultsThe viscosity–temperature relationships measured by both the micropenetration and the concentric cylinder viscometer methods are shown in Fig.2and also listed in Table2.In Fig.2,a crossover is seen for both melt series with NBO/T¼0.5and1,respectively.The crossover means that all viscosity–temperature curves for each melt series pass through the same viscosity–temperature point.It also means that in the highly viscous range the viscosity increases and in the low viscous range decreases with decreasing Si/ (Si+AlCa1=2)ratio.In other words,the compositional dependence of the viscosity for a constant temperature is opposite in the high compared to the low viscosity range.The crossovers are located at T¼1280K(or 104=T¼7:81)for the line NBO/T¼0.5and at T¼1500K(or104=T¼6:67)for the line NBO/T¼1. The T g values obtained using the DSC are listed in Table3.Fig.3shows the influence of Si/(Si+AlCa1=2) on the two isokom temperatures,T log g¼12and T log g¼0, for the melt series NBO/T¼0.5and1,respectively. T log g¼12is the T g of each melt,since generally T g cor-responds to the viscosity g¼1012Pa s.The inverse slopes shown in Fig.3are just a consequence of the crossover.In classical rate theory,the activation energy may be thought of as a potential energy barrier,which is over-come by atoms when they move from one site to another in the melt[22].Melts with high activation energy show a larger response of viscosity to a temperature change than melts with low activation energy.In this work,the activation energies for viscousflow(D H g)were deter-mined both in the glass transition range and in the high temperature range from1750to1850K(see Table3).D H gðT gÞand D H gðHTÞrefer to the activation energy around T g and in the high temperature range,respec-182M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188tively.The activation energies were obtained byfinding the slope of the ln g vs.1=T linear relationship over a narrow temperature range[10].Fig.4shows linear de-pendences of both D H gðT gÞand D H gðHTÞon the Si/ (Si+AlCa1=2)ratio.The inset of Fig.2shows the viscosity–temperature relationships scaled by T g.The fragility index a for each melt was found byfitting Eq.(6)to the log g vs.1=T data (see Table3).Fig.5shows that the fragility increases with decreasing Si/(Si+AlCa1=2)for both lines.In addition,it is found that a increases with increasing mol%CaO for both lines(Fig.6).The AG equation(Eq.(4))was used tofind the configurational entropy at T g ðS cðT gÞÞand the results are listed in Table3and shown in Fig.7,where it is seen that S cðT gÞdecreases with decreasing Si/(Si+AlCa1=2).Table2Viscosity as a function of temperature measured on the10CAS meltsCAS1CAS2CAS3CAS4CAS5T(K)log g(Pa s)T(K)log g(Pa s)T(K)log g(Pa s)T(K)log g(Pa s)T(K)log g(Pa s) 1052.711.441065.811.201091.510.561106.410.261106.510.61 1065.910.701066.811.121105.39.921119.19.751111.810.55 1095.69.531073.910.791116.19.401133.29.121124.69.95 1112.38.851094.39.981124.39.151143.48.761141.39.19 1132.68.141110.79.281133.18.721158.48.161153.18.701130.28.521144.78.341166.78.171316 3.221150.88.101340 2.851365 2.511389 2.211413 1.941437 1.751437 1.691461 1.511461 1.481486 1.311486 1.281510 1.141510 1.1015340.9815340.9315580.8215580.7815580.7315580.6915830.6915830.6815830.5815830.5416070.5616070.5116070.4516070.4016310.4416310.3416310.3316310.2816550.3216550.2916550.2316550.1616790.2216790.1916790.1316790.0517040.1217040.1017040.051704)0.0517280.0217280.021728)0.041728)0.141752)0.071752)0.061752)0.111752)0.221752)0.26 1776)0.151776)0.131776)0.181776)0.301776)0.34 1801)0.231801)0.201801)0.241801)0.371801)0.41 1825)0.311825)0.251825)0.311825)0.441825)0.48 1849)0.391849)0.311849)0.381849)0.501849)0.53CAS6CAS7CAS8CAS9CAS101099.210.301111.210.261107.110.621121.110.421129.410.43 1116.29.791123.49.831140.29.401139.99.721137.210.05 1133.09.151140.09.151150.38.931155.88.911144.49.81 1151.28.471153.98.661160.48.601168.18.581150.59.48 1164.57.981156.98.451169.98.251185.37.911166.28.931169.78.031173.88.591558 1.1215830.9616070.9116070.8016310.9016310.7716310.6616550.7716550.6416550.4916790.6516790.5316790.4217040.5417040.4217040.3017040.13 17280.4417280.3217280.2117280.02 17520.3417520.2317520.111752)0.011752)0.07 17760.2517760.1417760.031776)0.101776)0.16 18010.1618010.051801)0.061801)0.191801)0.24 18250.071825)0.031825)0.141825)0.271825)0.32 1849)0.021849)0.111849)0.221849)0.351849)0.39M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–1881835.DiscussionThe appearance of the crossover(see Fig.2)and in-verse compositional dependence of D H gðT gÞand D H gðHTÞ(see Fig.4)suggest that the changes in struc-tural arrangement with chemical composition are dif-ferent in the high and low viscosity ranges.The change of viscosity of a silicate melt with temperature is directly associated with that of the frequency of the breaking and bridging of T0–O bonds,where T0stands for tetra-hedrally coordinated cations.With increasing tempera-ture,the breaking of T0–O bonds becomes more frequent,so that the structure units become more mobile and viscosity decreases.According to[23],the changes of viscosity of a melt is also associated with the exchange between different Q n units,where n refers to the number of the oxygens per SiO4or AlO4unit(Q),which are shared with another SiO4or AlO4unit[23].Such ex-change controls viscousflow of melts[23–25].The higher the exchange frequency is,the lower is the vis-cosity of the melt.The exchange frequency depends on the glass composition and hence fragility of a melt.In high temperature region a fragile melt has higher ex-change frequency than a strong one,whereas in low temperature region the former has lower exchange rate than the latter.Consequently,the ratio in the exchange rate between the low and the higher temperature in-creases with substitution of Al3þ+1/2Ca2þfor Si4þ.In the high viscous range,the melt structure is not per-Table3Rheological and thermodynamic quantities of the10CAS meltsT g a(K)D H gðT gÞb(kJ/mol)D H g(HT)b(kJ/mol)a c B d(kJ/mol)S cðT gÞd(J/(mol K)) CAS11043937208 4.18252 6.62CAS21057950170 4.36246 6.52CAS31065991172 4.40254 6.47CAS41075992189 4.61246 6.14CAS510841051175 4.62271 6.84CAS61066881231 3.833027.77CAS71075961219 4.052927.35CAS81082939217 4.252847.09CAS910931002217 4.402907.24CAS1011041036213 4.562847.08a Determined using the DSC,with the heating and cooling rates10K/min.b Estimated in the glass transition region as well as in the high temperature(HT)range1700–1850K.c Found by a least squarefit of the viscosity–temperature data using the Avramov equation[10,13].d Obtained byfitting the Adam–Gibbs equation to the viscosity data[9,10].184M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188turbed in the same way as in the low viscous range where the structural units of the glass melt are mobile and, hence,the diffusion is faster.If temperature is scaled by T g,the crossover disappears as shown in the insets of Fig.2,but the curvatures of the log g vs.T g=T plots,that are quantified by the fragility index a,become different among the glasses.Thus the existence of a crossover implies the difference in the fragility between the differ-ent glasses.The dependence of viscosity on the temperature indicates a high and a low temperature structural arrangement in the melts.The diffusivity is dramatically lower in a high viscous range compared to that in a low viscous range.In the high viscous range(g¼108–1012 Pa s),both the charge-balancing ions and the network-modifying cations(Ca2þ)have the tendency to attract the neighboring tetrahedra of glass former.Recently,it has been experimentally confirmed that the Ca2þions contract the channels in the glass network as reported in [26].Therefore,the structural network becomes stronger with increasing substitution of Al3þ+1/2Ca2þfor Si4þbecause of the role of Ca2þions.In other words,the connection of tetrahedra becomes stronger,and hence the formation of larger clusters is favored,if Al3þ+1/ 2Ca2þsubstitutes for Si4þ.As a result,the viscosity in-creases with that substitution in the high viscous range. In this case,the topological and cooperative rearrange-ments of the melt structure are dominant in influencing the change in viscosity.In the high viscous range,the diffusion of the structural units(e.g.tetrahedral groups and Ca2þions)in the melt become more difficult with increasingly substitution of Al3þ+1/2Ca2þfor Si4þbe-cause of the strengthening of structural network by Ca2þ.That is why D H gðT gÞincreases with decreasing Si/ (Si+AlCa1=2)(see Fig.4).The strengthening of the melt structure is also reflected by the increase in T g with increasingly substitution of Al3þ+1/2Ca2þfor Si4þ(see Fig.3and Table3).This is because a high T g value corresponds to the high strength and/or the high degree of polymerization of the melt structure.In the low viscous range,the strength of the chemical bonds,including both the charge-balancing ions and the network-modifying cations lying in the interstice be-tween the Al-tetrahedrons becomes weaker and more unstable.The diffusion process of the structural units become faster and more dominant with substitution of Al3þ+1/2Ca2þfor Si4þand hence leads to a decrease in viscosity for both of the NBO/T lines(see Fig.3).The crossover can also be explained by the recent study on difference in structural relaxation time andM.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188185calcium mobility for calcium aluminosilicate melts.In [27],it has been found that in the high temperature range the characteristic time of the calcium mobility is the same as the structural relaxation.In contrast,in the low temperature range two kinds of relaxation processes exists.Firstly,a fast process,which corresponds to cal-cium mobility,and secondly,a slow one,which corre-sponds to structural relaxation of the aluminosilicate network.The crossover shifts to higher temperature with increasing NBO/T(see Fig.2).In other words,the temperature range above T g,in which a substitution of Al3þ+1/2Ca2þfor Si4þincreases the viscosity,becomes broader.This suggests that an increase in the concen-tration of Ca2þresults in broadening of the temperature range,in which Ca2þions strengthen the melt structure by attracting the tetrahedra and thus enhancing the grouping of these tetrahedra,i.e.the formation of the clusters.Such structure strengthening is reflected by the fact that the T g values of the melts with NBO/T¼1are higher than those of the melts with NBO/T¼0.5,as shown in Fig.3and Table3.The shift of the crossover also implies that the topological and cooperative rear-rangement of the melt structure in the high viscous range is more predominant and the formation of cluster is more favored for the aluminosilicate melt with more Ca2þcontent than for the melt with less Ca2þcontent, whereas the diffusion of the structural units become more hindered for the former than the latter.The fragility index a shows a linear dependence on both the Si/(Si+AlCa1=2)ratio(see Fig.5)and the CaO content(mol%)(see Fig.6)for both melt series with NBO/T¼0.5and1,respectively.This clearly indicates the sensitivity of fragility to the content of Ca2þin the manner that CaO greatly can increase the fragility of the studied glass melt system.From Fig.5,it can also be seen that the fragility changes more dramatically for melts with NBO/T¼0.5compared to that of melts with NBO/T¼1.In Fig.8,the configurational entropy S cðTÞis com-pared between different melts for a certain value of T=T g. At T=T g¼1:1,S cðTÞslightly increases with increasing Si/(Si+AlCa1=2)ratio,whereas at T=T g¼2,S cðTÞde-creases with increasing Si/(Si+AlCa1=2)ratio.This shows that the dependence of S cðTÞat T=T g¼1:1on the Si/(Si+AlCa1=2)ratio is inverse to that for T=T g¼2.In other words,the compositional dependencies of S cðTÞat T=T g¼1:1and at T=T g¼2are inverse.This indicates a relative change of the ratio between the chemical and topological contributions to the configurational en-tropy.With increasing temperature,the relative chemi-cal contribution to S cðTÞdecreases,while the topological contribution increases(see Eq.(4)).The relative increase in S cðTÞwith increasing temperature is largest for the melt with the lowest Si/(Si+AlCa1=2)ratio(see Fig.8), because it has the highest D C p(see Eq.(4))[10].This is related to the fact that the perturbation of the local structural environment becomes more intense with decreasing the Si/(Si+AlCa1=2)ratio.The increase in concentration of Al3þleads to an increase in degree of disorder of the melt structure.In the low temperature range,the chemical contribution controls the configu-rational entropy,whereas in the high temperature range the topological contribution controls the configurational entropy as also discussed in the work[12,28].Regarding each of the two compositional joins (NBO/T¼0.5and1)as part of a mixing series,a neg-ative deviation from linearity in T g values from the end members is anticipated.In an ideal mixing series,a minimum occurs when half of each end member is mixed.This is analogous to the phenomenon that is clearly seen when dealing with the mixed alkali effect [29].A minimum in T g vs.Si/(Si+AlCa1=2)for the lines NBO/T¼0.5and1is observed[10,30].The increasing amount of Al–O–Si bonds relative to that of Si–O–Si bonds results in the decrease in T g when looking in the direction of decreasing Si/(Si+AlCa1=2)until a mini-mum in T g is reached.The minimum is followed by an increase in T g when additionally decreasing the Si/ (Si+AlCa1=2)ratio.This behavior is attributed to the increasing possibility for the charge-balancing cations and the network modifying cations to attract tetrahe-drons.The formation of clusters becomes easier with decreasing the Si/(Si+AlCa1=2)ratio.The consequence is a strengthening of the melt structure.The occurrence of a minimum in T g for the lines NBO/T¼0.5and1can be understood as a consequence of the mixing effect in the manner that S cðT gÞdepends non-linearly on the Si/(Si–AlCa1=2)ratio,but with a maximum at a certain Si/(Si+AlCa1=2)ratio.The mix-ing effect can be regarded as similar to that of the mixed alkali effect[29].For both melt series with NBO/T¼0.5186M.Solvang et al./Journal of Non-Crystalline Solids336(2004)179–188。

内毛细胞带状突触结构及功能的研究进展

内毛细胞带状突触结构及功能的研究进展

内毛细胞带状突触结构及功能的研究进展陈丽平【摘要】在视网膜及内耳的带状突触通过紧张性释放神经递质传导不同强度的光和声音信息.突触上的囊泡通过快速同步化机制和缓慢但持久的模式释放神经递质.带状突触是一个大的电子致密体,并在突触前膜集结大量的囊泡,其主要结构蛋白是RIBEYE.该骨架结构提供了带状突触-相关蛋白的锚定位置.带状突触具有胞吐、包吞、突触膜融合等功能.现对带状突触结构和功能的最新研究进展予以综述.%Ribbon synapses in the retina and inner ear maintain tonic neurotransmitter release at high rates to transduce a broad bandwidth of light or sound intensities. In ribbon synapses , synaptic vesicles can be released by a slow , sustained mode and by fast ,synchronous mechanisms. Synaptic ribbons are large ,electrondense structures that immobilize numerous synaptic vesicles next to presynaptic release sites. A main component of synaptic ribbons is the protein RIBEYE that has the capability to build the scaffold of the synaptic ribbon via multiple RIBEYE-RIBEYE interactions. The scaffold of the synaptic rihbon provides a docking site for RIBEYE-associated proteins. Multiple functions have been assigned to synaptic ribbons including roles in exocytosis, endocytosis,and synaptic membrane trafficking. Here is to review the recent progress in structure and function of synaptic ribbons research.【期刊名称】《医学综述》【年(卷),期】2011(017)019【总页数】4页(P2899-2902)【关键词】内毛细胞;传入神经;带状突触【作者】陈丽平【作者单位】中国医科大学附属第一医院神经内科,沈阳,110001【正文语种】中文【中图分类】R74耳蜗能够编码不同频率和强度的声音信号,这一过程由内毛细胞及外毛细胞参与。

矿物加工学的现状与发展

矿物加工学的现状与发展

3 矿物加工学科旳形成
• 这就需要综合利用多学科旳知识与新成就 , 寻找新旳学科起点,开发新旳科学技术 , 以实 现矿物资源旳综合利用,包括分离、富集贫细 矿物资源旳新技术工艺和设备,对矿物旳提纯 与精加工,环境旳综合治理,矿物新用途旳开 发等。矿物资源旳利用已不单纯是经过“选矿 ”得到矿产品旳问题,而是综合“加工”利用 旳问题。为此,近几十年来选矿及相邻学科旳 科技工作者在选矿学科及交叉学科领域 , 进行 了大量旳基础理论与工艺技术旳研究。同时, 由于相邻学科旳发展 , 如电化学、量子化学、 表面及胶体化学、紊流力学、生物工程、冶金
2 选矿学科旳形成
• 人类利用矿物资源已经有数千年旳历史。不论是公元前 几千年旳古埃及,还是中世纪旳罗马帝国时代,或者是 中国古代,因为科学技术水平整体落后,社会生产力低, 人类利用旳矿物资源主要是经过手工作业从天然矿石中 得到旳,如淘金、人工溜槽、手动跳汰筛、洗矿槽等原 始重选措施及鹅毛蘸油刮取浮在水面上旳金粉等原始浮 选措施。我国古代将原始旳重选、浮选总结为“澄、淘、 飞、跌”。我国明代宋应星所著《天工开物》(1637 年 ) 一书中,对铁砂和锡砂旳开采选别已经有描述, 见图 1-1 。这些手工作业虽然有近代“表层浮选” 、 “重选”旳影子 , 但还算不上是一门工业技术 , 这种 现象一直延伸到19世纪中期 ndbook of Ore Dressing(1927年第1版,1944年第2 版);Gaudin旳Flotation(1932年第1 版,1957年第2版);澳大利亚旳 Sutherland和Wark旳Principles of Flotation (1955年第1版);原苏联 Bogdmov旳Theory and Technology of Flotation(1959).

Development in fission track-thermal ionization mass spectrometry

Development in fission track-thermal ionization mass spectrometry

DOI: 10.1007/s10967-007-0519-0 Journal of Radioanalytical and Nuclear Chemistry, Vol. 272, No.2 (2007) 299–3020236–5731/USD 20.00Akadémiai Kiadó, Budapest © 2007 Akadémiai Kiadó, BudapestSpringer, DordrechtDevelopment in fission track-thermal ionization mass spectrometryfor particle analysis of safeguards environmental samplesC. G. Lee,1* K. Iguchi,1 J. Inagawa,1D. Suzuki,1 F. Esaka,1 M. Magara,1 S. Sakurai,1K. Watanabe,2 S. Usuda 11 Nuclear Science and Engineering Directorate, Japan Atomic Energy Agency (JAEA), Tokai-mura, Naka-gun, Ibaraki 319-1195, Japan2 Planning and Coordination Office, Japan Atomic Energy Agency (JAEA), Tokai-mura, Naka-gun, Ibaraki 319-1195, Japan(Received June 30, 2006)An improved method of fission track (FT) sample preparation was developed, in which the detector of fission track and the layer containing particles are separated, in order to apply the FT-thermal ionization mass spectrometry (TIMS) for particle analysis of safeguards environmental samples. The developed FT sample enabled us to detect the particle of interest simply by observing the fission tracks. The process of particle identification was difficult due to the discrepancy between the position of the particles and fission tracks, which were observed in the conventional FT sample. The proposed method has significantly resolved this problem.IntroductionEnvironmental sample analysis was adopted by the International Atomic Energy Agency (IAEA) as a new technique for the strengthened safeguards system.1,2 Its objective is to ensure that no undeclared nuclear materials or activities exist at nuclear facilities. One of the analytical methods for environmental sampling is the particle analysis, in which the isotope ratios of nuclear material present in individual particles are measured in swipe samples taken from the inside and outside of nuclear facilities. Secondary ion mass spectrometry (SIMS) is a well-known analytical method for such investigations.3,4 However, it is difficult to analyze submicrometer-diameter particles due to the detection limit of SIMS. The fission track (FT) technique incombination with the thermal ionization mass spectrometry (TIMS) method is effective for the particle analysis of safeguards environmental samples because the isotope ratios of submicrometer-diameter uranium particles can be determined using this combination. In the FT-TIMS method, the FT detector plays a very important role because the detection efficiency mainly depends on its performance. We developed an FT detector within the particles of interest are confined.5 This sample is referred to as a monolayer FT sample in this study. The FT-TIMS method that uses a monolayer FT film sample has several merits such as a high detection efficiency, simplicity of sample preparation, and its possible use as a method for screening uraniumparticles according to their enrichment by controlling the etching time.6 However, the usage of a monolayer FT sample has a few drawbacks: a portion of uraniumparticles may be lost due to dissolution, in addition to* E-mail: lee.chigyu@jaea.go.jptheir loss during the etching process. This may beunavoidable while the particles are present in thedetector.In order to resolve the problems with regard to the monolayer FT film sample, we have developed an effective sample preparation method in which the fission track detector and the layer containing particles are separated. This is referred to as a double-layer FT sample in this study. In the conventional double-layer FT sample, the detection process of the particle of interest is time-consuming and complicated due to the discrepancy between the particle position and the fission tracks, which may be attributed to the stretching induced due to the separation of the detector from the particle layer for etching the detector.Recently, a fission track analysis was developed in order to identify the location of fissile particles in contaminated soil. In this technique, SEM grids electroplated with Th were used to record reference points on a Lexan track detector.7 This method, in comparison to the double-layer FT sample method,involves the use of a more complicated arrangement since the SEM grid is placed between the detector and the particle layer.Therefore, we focused on the development of the method of particle identification from the fission track. In this study, we provide a detailed report on the double-layer FT sample preparation method and the results of isotope ratio measurement by TIMS.Experimental Particle collection In this study, uranium oxide particles of NBL 950a standard reference materials (NU, natural composition)C. G. L EE et al.: D EVELOPMENT IN FISSION TRACK − THERMAL IONIZATION MASS SPECTROMETRY300 were used instead of the swipe samples taken from theinside and outside of nuclear facilities. The particleswere collected on a cotton cloth (TexWipe ®304,10×10 cm 2, Texwipe) by wiping. The collected particleswere recovered onto a polycarbonate membrane filterwith a diameter of 25 mm and a pore size of 0.2 µm(Advantec) using a filtration system.5Preparation of film sample containing particlesThe filter along with the particles was folded andthen placed in a 1 ml volumetric flask. It was then dissolved in a mixture solution containing 1,2-dichloroethane and dichloromethane in the volume ratioof 2 : 3. The mixture was spread on a silica glass platewith a thickness of 0.7 mm and prepared to achieve athickness of 2 µm and an area of 2×2 cm 2. It was thendried at room temperature for a day to form a thinpolycarbonate film containing the particles. The controlof the particle-containing thin-film thickness is one ofthe key factors in the development of the FT samplepreparation method. The thickness can be controlled bythe area of the film sample since the quantity of the filmdissolved in the mixture is known and the solventevaporates entirely. In order to form clear fission trackson the detector, it is desirable to fabricate a thin particlelayer.After the preparation of the thin film sample (particlelayer), the detector made of polycarbonate (Makrofol)with a thickness of 20 µm was stacked on the particlelayer. Then, a part of the detector and a particle layerwere fixed using a heatproof tape with a thickness of100 µm to prevent their tearing during the etchingprocess. Furthermore, another silica glass plate with athickness of 0.7 mm was stacked on top of the detector,as shown in Fig. 1a.Irradiation and etching of the detectorThe assembled stack was placed between two platesof polyethylene and fixed with screws made of nylon inorder to maintain close contact between the particlelayer and the detector (Fig. 1a). This assembly waspacked into an irradiation capsule made of polyethylene,and then, it was irradiated with thermal neutrons of afluence of 8.1014 n .cm –2 at JRR-4 (Japan ResearchReactor-4, JAEA).After irradiation, the detector was etched with 6MNaOH at 55 °C for 8 minutes in order to make thefission track visible under an optical microscope. Asilica glass tool was exclusively used for etching thedetector, as shown in Fig. 1b. By using this tool, onlythe detector can be easily etched without causingmechanical deformation, such as detector stretching dueto handling. Moreover, the particle layer does not stretchduring the etching process because it is fixed on thesilica glass plate. Due to these reasons, the position of the fission tracks and the corresponding particles coincide well. After etching, the detector was carefully rinsed several times with milli-Q water (18.3 M Ω.cm –1); it was then dried. Detection of the particle containing fissile materials In this method, the particles containing fissile materials can be easily detected by locating only the fission tracks on the detector, as shown in Fig. 1c, since the fission tracks and the corresponding particles can be viewed simultaneously with the aid of a transparent and thin particle layer and detector.Fig. 1. Schematic diagram of the particle layer, detector, and silica glasses inside an irradiation capsule (a), schematic side view of the tool made of silica glass for exclusively etching a detector (b), and the method of identification of the particle containing fissile materials from fission tracks (c)C. G. L EE et al.: D EVELOPMENT IN FISSION TRACK − THERMAL IONIZATION MASS SPECTROMETRY301Application to mixed sampleIn order to demonstrate the effectiveness of the developed particle detection method, the mixed samplecontaining uranium particles and dusts was prepared and then analyzed. Figure 2 illustrates the process of uranium particle detection in which the uranium particles and dusts are clearly distinguishable. The black spots surrounded by solid circles indicate the uranium particles, and the corresponding fission tracks are visible on the left side of the particles. On the other hand, the black spots surrounded by dotted circles indicate dusts since the corresponding fission tracks are not observed. However, as shown in Fig. 2, the discrepancy between the position of the fission tracks and the corresponding particles continues to exist. Therefore, it is necessary tofurther resolve this discrepancy in order to detect theparticle of interest more efficiently.After the fission track created by uranium particle has been detected and photographed, a small square portion (50×50 µm 2) of the film containing a uranium particle was cut out using an N 2-laser and then transferred onto a filament of TIMS (TRITON, Thermo electron) for isotope ratio measurement using a micro-manipulate system. Figure 3 shows the results of isotope ratio measurement for the uranium particles detected from the developed double-layer FT sample. The ratios of 235U/238U and 234U/238U were in good agreement with those for their natural composition within an error range of 1.5% and 10%, respectively.Fig. 2. Microscopic image of the fission tracks and the uranium particles of natural composition observed on the same screen in which the particle layer (lower) and the detector (upper) were stacked. Solid circles: uranium particles and dotted circles: dustsC. G. L EE et al.: D EVELOPMENT IN FISSION TRACK − THERMAL IONIZATION MASS SPECTROMETRY302Fig. 3. Results of the isotope ratio measurement of the uranium particles detected by the double-layer FT sample:235U/238U (a) and 234U/238U (b). The ratios were measured with TIMSConclusionsIt was demonstrated in this study that a particle ofinterest can easily be detected from the correspondingfission track owing to the double-layer FT sampledeveloped. This result will allow us to perform isotoperatio measurement for particle analysis in a safeguardsenvironmental sample more efficiently. However, theFT sample preparation method requires furtherimprovement. In particular, the discrepancy between thepositions of the particles and fission tracks must beresolved in order to apply the developed double-layerFT sample to the routine particle analysis in safeguardsenvironmental samples.References 1. D. L. D ONOHUE , Anal. Chem., 74 (2002) 28A. 2. D. L. D ONOHUE , J. Alloy Comp., 271–237 (1998) 11. 3. M. B ETTI , G. T AMBORINI , L. K OCH , Anal Chem., 14 (1999) 2616. 4. G. T AMBORINI , M. B ETTI , V. F ORCINA , T. H IERNAUT , B. G IOVANNONE , L. K OCH , Spectrochim. Acta, B53 (1998) 1289. 5. K. T. E SAKA , F. E SAKA , J. I NAGAWA , K. I GUCHI , C. G. L EE , S. S AKURAI , K. W ATANABE , S. U SUDA , Japan J. Appl. Phys., 43 (2004) L915. 6. K. I GUCHI , K. T. E SAKA , C. G. L EE , J. I NAGAWA , F. E SAKA , T. O NODERA , H. F UKUYAMA , D. S UZUKI , S. S AKURAI , K. W ATANABE , S. U SUDA , Radiat. Meas., 40 (2005) 363. 7. M. H. L EE , M. D OUGLAS , S. B. C LARK , Radiat. Meas., 40 (2005) 37.。

具有阶段结构与时滞的捕食系统模型的永久持续生存和稳定性

具有阶段结构与时滞的捕食系统模型的永久持续生存和稳定性

设 : 年种群 的 出生率 与成 年种 群的密度 成 正 比 , a 。 a O ; 年种 群死亡 率为 幼 为 . ( > )幼 T g

(,> 0 ; )叩 , ) 幼
年种群 到成 年种 群的转 化 率与幼 年种群 的 密度成 正 比 , 为
r0
( n> o ; 年种 群 的死 亡 率为 ; > O ; )成 ( ) 成
r 0
年种 群 消极 反 馈的拥 挤现 象对 目前死 亡率 的影 响为 。 (一 ) " > 0 (3 E 常数 ) 成 年种群 过 去一 1 时期 的经历 ; \
Au 0 8 g 2 0
参 i j ■ ◆0 I ̄ 。 L l i j : i , i j … ¨
具有阶段 结构与时滞的捕食系统模型 的 永久持续生存和稳定性
程惠 东 , 秋 霞 。 孙 常正 波
( 东 科技 大 学 理 学 院 , 东 青 岛 2 6 1 ) 山 山 6 5 0
近年来 时 滞生 态系统 和阶段 结 构种群 动力 系 统 的研 究 已有许 多 成果 。 献 [ ]得 到 单 种群 阶 段结 构 系 文 1
统的 持 久性 的条 件 ; 献[ ] 文献 [ ]研 究 了在 斑 块环 境 中具 有连 续 时滞 和 扩散 效应 的捕 食 者与 食饵 的 动 文 2、 3
Ke r s 3 r l n l u v v l l b ly a y t t t b l y;s a e s r c u e i e a y wo d :f /a el s r ia ;g o a l s mp o i s a i t eT t c i t g t u t F ;t me d l y
摘 要 : 究 了具有 时滞和阶段 结构 的捕 食者一 研 食饵模 型, 得到 了与 时滞有 关的 系统 永久持 续生存 的充分条件 ; 同

1一次型射击粉煤技术

1一次型射击粉煤技术

Chemical Engineering Science62(2007)4983–4991/locate/cesKinetic modeling of Fischer–Tropsch synthesis over Fe.Cu.K.SiO2catalystin slurry phase reactorJie Chang a,Liang Bai a,∗,BoTao Teng b,RongLe Zhang a,Jun Yang c,YuanYuan Xu a,HongWei Xiang a,YongWang Li aa State Key Laboratory of Coal Conversion,Institute of Coal Chemistry,Chinese Academy of Sciences,Taiyuan030001,People’s Republic of Chinab Zhejiang Key Laboratory for Reactive Chemistry on Solid Surfaces,Institute of Physical Chemistry,Zhejiang Normal University,Jinhua321004,People’sRepublic of Chinac Department of Chemistry,Jinan University,Guangzhou510632,People’s Republic of ChinaReceived16June2006;received in revised form15November2006;accepted17December2006Available online8January2007AbstractComprehensive kinetics of slurry phase Fischer–Tropsch synthesis(FTS)on an industrial Fe.Cu.K.SiO2catalyst,in the presence of water–gas shift(WGS),is studied using a stirred tank slurry reactor.A series of rival models for FTS and WGS reaction are derived using Langmuir–Hinshelwood–Hougen–Watson(LHHW)approach.In order to describe the deviation from ideal hydrocarbon distribution,secondary reactions of primary olefin on a separated active site and its chain length dependent solubility in slurry phase are taken into account.It is found that the optimal model is based on the mechanism that the rates of FTS are determined by insertion of methylene(CH2)via the alkylidene propagation mechanism and the rate of WGS reaction is controlled by the desorption of CO2via formate intermediate mechanism.Present model can describe the CO conversions and hydrocarbon distributions consistently and accurately over large interval of reaction conditions (523.563K,1.0.2.5MPa,H2/CO ratio:0.67.1.5,and space velocity:1000.2500ml g−1cat h−1).On the other hand,the success predictions of the deviation from ideal distribution suggest the strong influence on the secondary reactions by the chain length dependent solubility of olefins.᭧2007Elsevier Ltd.All rights reserved.Keywords:Fischer–Tropsch synthesis;Fe.Cu.K.SiO2catalyst;Kinetic modeling;Secondary reaction of olefin1.IntroductionWith the decreasing of crude oil resources,Fischer–Tropsch synthesis(FTS),which supply an opportunity to obtain alter-native fuels from coal and natural gas,has attracted more atten-tions.From viewpoint of chemical engineering,kinetic studies play an important role in the design and scale-up of commer-cial FTS reactors.To achieve an optimum in performance of FTS process,the accurate comprehensive kinetic model which can describe the CO consumption and the product distribution of FTS self-consistently is required.When kinetic studies aim at developing the consumption rate expressions of CO,the information of hydrocarbon production∗Corresponding author.Tel.:+863514124899;fax:+863514124899.E-mail addresses:jie.chang@(J.Chang),lbai@ (L.Bai).0009-2509/$-see front matter᭧2007Elsevier Ltd.All rights reserved. doi:10.1016/j.ces.2006.12.031is always plumed(Vannice,1975;Huff and Satterfield,1984; Van der Laan and Beenackers,2000;Keyser et al.,2000).The common points of these plumed rate expressions are that the formation of monomer is assumed as rate-determining step, and the polymerization characters in FTS reactions are ignored to some extent(Van Steen and Schulz,1999).That is,these lumped consumption kinetic models are not able to describe the whole FTS reaction performance,and the separate distribution model is needed as complements in these cases.In the view of product distribution kinetics for FTS,in which a polymerization-like mechanism is proposed,one of the most important problems is how to explain the devia-tions from classic Anderson–Schulz–Flory(ASF)distribution. The most successful modification is that the effects of the secondary reactions of primary1-olefins on the product distri-butions are taken into account.Van der Laan and Beenackers (1999b)proposed the1-olefin readsorption product distribution4984J.Chang et al./Chemical Engineering Science 62(2007)4983–4991model (ORPDM)accounting for the chain length dependent readsorption of olefins on uniform and homogenous FTS sites.While in the models of Zimmerman et al.(1992),Nowicki et al.(2001),and Schulz and Claeys (1999a),it was assumed that there are two kinds of active sites exist on the iron or cobalt catalysts:one answer for the formation of primary products including normal paraffins and 1-olefins,and the other for the secondary reactions of olefins.As the complement of these modified models,non-intrinsic properties in FTS reactor,for example the increase of solubility of the olefins with increasing carbon number,are regard as the cause of the deviation from ASF law.The comprehensive FTS models,by which the information of CO consumption and product distribution could be described self-consistently,are rather scarce in the literature (Lox and Froment,1993a,b ).Our kinetic research group has also de-veloped some models on iron and cobalt catalysts with the consideration of the secondary reaction of 1-olefins (Wang et al.,2003;Yang et al.,2003;Chang et al.,2005).However the carbon number dependent olefin/paraffin ratio,especially for olefins selectivity with higher molecular weight,still cannot be completely described by these previous models.In present work,the modification of Yang’s (2003)models is taken based on the systematic consideration of the carbon number dependence for the secondary reactions of primary 1-olefins.On the other hand,in order to provide more compatible kinetic data for slurry phase FTS reaction,the kinetic experi-ments are conducted in a laboratory stirred slurry phase reactor.2.Kinetic model with modified olefin readsorption As shown in Fig.1,three kinds of reactions are considered in present FTS kinetic models.They are formation of primary hydrocarbons,secondary reactions of primary 1-olefins,and WGS reaction,correspondingly take place on separated active sites,named as site ,site ,and site ,respectively.2.1.Hydrocarbon formation and secondary reactions The primary FTS reaction is generally believed to be a non-trivial polymerization reaction proceeding via stepwise additionFeed gas : CO+H 2C n H 2n n+1 Secondary hydrogenation : nCO + 2n+1H 2 2 Fig.1.Kinetic scheme of FTS,secondary hydrogenation reaction,and WGS on Fe .Cu .K .SiO 2catalyst.of a single carbon monomer species (Van Steen and Schulz,1999).In present work,six mechanisms are proposed on the basis of various monomer formation and carbon chain propa-gation pathways.The primary olefins are considered to be able to readsorb on the catalyst surface,and then re-enter the reac-tion chains on site or directly hydrogenate to corresponding paraffins on site .The complete set of elementary reactions on site for each model is summarized in Table 1and the common secondary hydrogenation on site was shown in Table 2.The LHHW approach is used to derive rate equations.For each model,the propagation step is identified as the rate-determining step,while all other steps are assumed to be at quasi-equilibrium state.The detailed model expressions on site and their derivation process can be seen elsewhere (Yang et al.,2003).Especially,the treatments about the modified 1-olefin read-sorption in the models should be emphasized.It was suggested that some non-intrinsic properties in slurry FTS reactor,for example the vapor–liquid equilibriums of hydrocarbon com-ponents,will influence the secondary reaction performance of olefins.The results from literatures show that the solubility of hydrocarbons increases exponentially with the chain length (Breman et al.,1994;Donohue et al.,1985).Here,the relation between the olefin gas pressure and the concentration at the catalyst surface is empirically organized as [C n H 2n ]P C n H 2n =1H n=H 0exp (cn)∝exp (cn),(1)where H n is the Henry’s constant for olefin having carbon num-ber n .So an intermediate parameter of effective pressure ofolefin (P ∗C n H 2n)is introduced into the rate expressions to replace real pressure (P ∗Cn H 2n)according to this non-intrinsic property in slurry phase FTS reactor.P ∗C n H 2n=P C n H 2n ×exp (cn).(2)In present work,it is proposed that the readsorbed primary 1-olefins are able to be hydrogenated to corresponding paraffins via an Eley–Rideal mechanism by molecular H 2on separated catalytic site .On the other hand,in order to reduce the number of parameters in kinetic models,the readsorption and desorp-tion on site is considered to have the same values as on typicalJ.Chang et al./Chemical Engineering Science62(2007)4983–49914985 Table1Primary elementary reactions for FTS on siteAlkyl propagation mechanism Alklydiene propagation mechanismModel No.Elementary reactions of FTS Model No.Elementary reactions of FTSFT11CO+ →CO- FT41CO+ →CO-2CO- +H2→H2CO- 2CO- +H2→H2CO-3H2CO- +H2→CH2- +H2O3H2CO- +H2→CH2- +H2O4H2+2 →2H- 4H2+2 →2H-5CH2- +H- →CH3- + 5CH2- +CH2- →CH2CH2- + CH2- +CH3- →CH3CH2- + CH2- +C n-1H2n-2- →C n H2n- +CH2- +C n-1H2n-1- →C n H2n+1- + 6CH2- +H- →CH3- + 6C n H2n+1- +H- →C n H2n+2+2 C n H2n- +H- →C n H2n+1- +7C n H2n+1- ↔C n H2n+H 7CH3- +H- →CH4+2C n H2n+1- +H- →C n H2n+2+28C n H2n- ↔C n H2n+FT21CO+ →CO- FT51CO+ →CO-2CO- + →C- +O- 2CO- + →C- +O-3C- +H2→CH2- 3C- +H2→CH2-4O- +H2→H2O+ 4O- +H2→H2O+5H2+2 →2H- 5H2+2 →2H-6CH2- +H- →CH3- + 6CH2- +CH2- →CH2CH2- + CH2- +CH3- →CH3CH2- + CH2- +C n-1H2n-2- →C n H2n- +CH2- +C n-1H2n-1- →C n H2n+1- + 7CH2- +H- →CH3- + 7C n H2n+1- +H2→C n H2n+2+H- C n H2n- +H- →C n H2n+1- +8C n H2n+1- ↔C n H2n+H 8CH3- +H2→CH4+H-C n H2n+1- +H2→C n H2n+2+H-9C n H2n- ↔C n H2n+FT31CO+ →CO- FT61CO+ →CO-2CO- + →C- +O- 2CO- + →C- +O-3C- +H- →CH- + 3C- +H- →CH- +4CH- +H- →CH2- + 4CH- +H- →CH2- +5CH2- +H- →CH3- + 5CH2- +CH2- →CH2CH2- + CH2- +CH3- →CH3CH2- + CH2- +C n-1H2n-2- →C n H2n- +CH2- +C n-1H2n-1- →C n H2n+1- + 6H2+2 →2H-6H2+2 →2H- 7O- +H- →HO- +7O- +H- →HO- + 8HO- +H- →H2O+28HO- +H- →H2O+2 9CH2- +H- →CH3- +9C n H2n+1- +H- →C n H2n+2+2 C n H2n- +H- →C n H2n+1- +10C n H2n+1- ↔C n H2n+H 10CH3- +H- →CH4+2-C n H2n+1- +H- →C n H2n+2+211C n H2n- ↔C n H2n+Table2Elementary reactions for secondary hydrogenation on siteNo.Elementary reactions of secondary hydrogenation1CO+ ↔CO-2C n H2n+ ↔C n H2n3C n H2n- +H2→C n H2n+2+FTS site .So the mass balance on sites can be given asfollows:−d[C n H2n , ]d t =k h[C n H2n, ]P H2+k t,o[C n H2n, ]−k r,o P∗Cn H2n[ ]=0.(3)Table3Elementary reactions for WGS reaction on siteModels No.Elementary reaction of WGSWGS11CO+ ↔CO-2H2O+2 ↔HO- +H-3CO- +OH- ↔COOH- +4HCOO- ↔H- +CO252H- ↔H2+WGS21CO+ ↔CO-2H2O+ ↔H2O-3CO- +H2O- ↔HCOO- +H-4HCOO- + ↔H- +CO2-5CO2- + ↔CO2+62H- ↔H2+4986J.Chang et al./Chemical Engineering Science 62(2007)4983–4991Then we have the expression for the coverage of alkylidene on site with the consideration of CO inhabitation effects and the rate equation of secondary hydrogenation:[C n H 2n , ]=k r,o P ∗Cn H 2n[ ]k h P H 2+k t,o(n 2),(4)r h,n =k hk r,o P ∗C n H 2n[ ]k h P H 2+k t,oP H 2(n 2),(5)where the vacancy site concentration of site can be given as [ ]=11+K 1P CO +Ni =2k r,o P ∗C i H 2ih H 2t,o.(6)It is pointed out that ethene has a unique performance rather than the other olefins (Schulz and Claeys,1999b ).It has a higher reactivity and larger readsorption constant approximately 10–40times than the other olefins (Iglesia et al.,1991).In our present models,an empirical factor ( )is defined to describe the reac-tivity of ethene to the others.Table 4Operation parameters and resulting quantities No.T P H 2/CO SVMassCO conv.a CO 2selec.a CH 4selec.a C +5selec.a (K)(MPa)ratio (ml g −1h −1)balance (%)(C-mol%)(C-mol%)(C-mol%)(C-mol%)1523 1.450.67200096.2751.6344.780.9752.792523 1.500.912000102.0058.2947.93 1.4548.123523 1.95 1.242000102.0066.9043.93 1.7451.484523 2.50 1.24200095.0071.8037.19 1.6858.785523 2.520.67200099.4152.8042.390.9154.97Re 1b 523 1.530.652000100.0053.1645.28 1.0150.516533 2.000.67200098.8362.2945.34 1.1251.627533 1.500.67200098.8454.4548.29 1.3050.708533 1.500.67100093.2580.7946.09 1.3450.499533 1.540.67150096.9471.1247.57 1.3748.9310533 1.510.67250093.7252.6945.06 1.4751.01115330.96 1.512000104.0051.1655.03 2.0240.1712533 2.030.91200099.3265.2053.99 1.5442.0713533 2.450.672000102.2462.8741.50 1.2455.19Re 2b 533 2.000.652000100.5259.7748.34 1.1650.9114543 2.000.67200096.0174.1343.70 1.3951.78155430.950.912000104.2153.1550.52 1.4445.37165430.95 1.51200098.4561.1249.93 1.6545.1517543 1.99 1.502000102.0075.3046.26 1.6548.8218543 2.47 1.24200097.3374.7744.260.9351.84Re 3b 543 2.000.67200095.7571.6145.77 1.1851.1319553 2.050.67200095.2483.6548.94 1.3848.00205530.96 1.23200098.0457.1749.20 1.8846.7321553 1.47 1.502000101.3569.0647.58 2.2048.01225530.950.65200099.4651.5450.84 1.2046.5123553 2.550.912000101.2073.2048.52 1.2448.33Re 4b 553 1.990.67200096.7578.0747.61 1.3449.20245632.060.67200097.8886.8657.072.1538.32a Carbonmolar selectivity of product is defined as:mole of C -atom in productmole of CO consumed×100%.b Re is the replicate experiment point for first kinetic experiment in every temperature level.2.2.The WGS reactionThe generally accepted mechanism of WGS reaction over iron catalysts is formate intermediate mechanism.The elemen-tary steps of the WGS are summarized in Table 3.The process of the model derivation could be seen in our prior paper (Yang et al.,2003).In addition,Zimmerman and Bukur’s (1990)and Van der Laan and Beenackers’s (2000)kinetic models for WGS are also included among model evaluation in this work.3.Experimental sectionFTS experiments are carried out in a 1dm 3stirred stainless steel autoclave reactor.The spray-dried Fe .Cu .K .SiO 2cata-lyst,which is developed by Institute of Coal Chemistry (ICC,China),is sieved to less than 44 m (325mesh).About 20g of fresh catalyst are added into the autoclave.Liquid paraffin (ca.320g,A.C.,boiling point >613K)is used as the initial solvent.The detailed description of setup and analysis method can be found elsewhere (Bai et al.,2002).Prior to its use,the catalyst is reduced in situ in the auto-clave reactor (518K,2000ml g −1cat h −1,0.5MPa)using syngasJ.Chang et al./Chemical Engineering Science 62(2007)4983–49914987Table 5Optimum comprehensive kinetic model for FTS and WGS in present work (FT4+WGS1)Model Rate expressionsFT4R CH 4=K 1K 2K 3K 6k 7,M K 0.54P 2.5H 2P CO P H 2O [ ]2,R C n H 2n +2=K 1K 2K 3K 6k 7K 4P 3H 2P CO P H 2On i =2i [ ]2+k h k 8,−P ∗C n H 2n [ ]k h P H 2+k 8,+P H 2(n 2),R C n H 2n =K 1K 2K 3k 8,+(1− n )P 2H 2P CO P H 2On i =2i [ ]−k h k 8,−P ∗C n H 2n [ ]k h P H 2+k 8,+P H 2(n 2),whereK ∗3=K 1·K 2·K 3,P ∗C 2H 4= ·P C 2H 4·exp (2c),P ∗C n H 2n=P C n H 2n ·exp (cn)(n 2),n =k 5K 1K 2K 3P 2H 2P CO /P H 2Ok 5K 1K 2K 3P 2H 2P CO /P H 2O +k 7K 6K 4P H 2+k 8,+(1− n )/[ ](n 2),A =k 5K 1K 2K 3P 2H 2P CO /P H 2Ok 5K 1K 2K 3P 2H 2P CO /P H 2O +k 7K 6K 4P H 2+k 8,+[ ],n =k 8,−k 8P ∗Cn H2nn −1AK ∗3P 2H 2P CO /PH 2O +k 8,−5∗32H 2CO H 2O 764H 28,+n i =2( i −2A P C (n −i +2)H 2(n −i +2),[ ]=11+K 1P CO 1+K 2P H 2 1+K 3 1+ N i =2 ij =2 j 1+K 6√K 4P H 2 +√K 4P H 2,[ ]=11+K 1P CO +Ni =2k 8,−P ∗Cn H 2nk P H 2+k 8,+,WGS1R CO 2=k vP CO P H 2OP 0.5H2−P CO 2P 0.5H 2K p1+K v P CO P H 2OP 0.5H 2,K v =K p K WGS ,4K 0.5WGS ,5,k v =k WGS ,4K v ,K WGS ,4=k WGS ,4k WGS ,−4,ln K p =5078.0045T−5.8972089+13.958689×10−4T −27.592844×10−8T 2.(H 2/CO =2).The process is continued until the concentrationof CO 2in the tail gas reaches a steady level,which indicates the active phase is stable.A subsequent stabilization period of 260h is carried out under the reaction condition to avoid the instability during the initial reaction period.The samples used in kinetic regression are accumulated during the steady state of the reaction system for 24h.After each change of the operation conditions,there is a period of 24h to achieve the new stabilization.The overall material balances are typically 100±5%.The process parameters,such as temperature,H 2/CO ration,pressure,and space velocity,are well arranged on the basic of orthogonal design.An L 16(45)scheme is applied here,which including 16sets of experiments.And other eight sets of addi-tive experiments are carried out in order to obtain the influences of the parameters clearly.The experimental operation parame-ters and results are also summarized in Table 4.4.Kinetics modeling discrimination and parameter optimizationThe stirred slurry reactor used for the kinetic experiments is simulated by a perfect mixing flow model consisting of a setof nonlinear algebraic equations:M i,in −M i,out +W cat N R j =1ij R j (K,P )=0(i =1,2,...,N c ).(7)For kinetic regressions,the molar flow rates of main com-positions at reactor outlet are used to definite the optimization objective.They are divided into four parts.In the first part,the molar flow rates of CO,H 2,CO 2,and H 2O,which are usually used in the lumped kinetic studies,are included,respectively.The rest three parts are used to show the hydrocarbon distribu-tion.One of them contains the hydrocarbons with carbon num-ber not larger than 5,which meanly exit in the tail gas phase and can be analyzed by the on-line gas chromatograph.An-other part is the components of hydrocarbons with the carbon number from 9to 11,which is meanly in the cold trap collec-tions.The last part is the C +5lumped fraction,which is known as the effective products of FTS,and the C +20lumped frac-tion,which has effect on the properties of the operation slurry phase.Therefore,the regression target of kinetic models is formu-lated by minimizing the weighted sum of squared residuals,4988J.Chang et al./Chemical Engineering Science62(2007)4983–4991 which contain above four parts exitflow rates:F obj=N expi=1N respj=1w jM i,j,exp−M i,j,calcM i,j,exp2.(8)For all24experimental points,the number of objective func-tions(N resp)for each experiment is21,and the total number of objective functions(N exp×N resp)is504.It should be no-ticed that,greater weights are put on those responses with most accurate measurement and/or with special significance in our regression.Data from all of the kinetic experiments are used in the parameters estimation process.The genetic algorithm,a global optimization method,is used here to estimate the unknown kinetics parameters,followed by the Levenberg–Marquardt method.The temperature dependence of rate constants is evaluated according to the Arrhenius-type equations:k i(T)=k i,0exp(−E i/RT).(9) The discrimination between the rival models is based on the mean absolute relative residuals(MARR),which is defined asMARR=N expi=1N respj=1|M i,j,exp−Mi,j,cal|M i,j,exp×1N exp×N resp×100%.(10)Additionally,statistical F-tests are used to test the confidenceintervals of model,and t-test are used as criterion of parametersin the discriminations(Box et al.,1978).5.Results and discussionThe possible combinations of FTS and WGS models lead-ing to30rival models,which are sequentially evaluated.Themodel(FT4+WGS1),as shown in Table5,is found havingthe minimal MARR value,which also has the statistical signif-icance at the95%probability level with F-value of114.6.Thecomparison between the experimental values and modeling re-sults of some targets are presented in Figs.2–4.The corresponding estimated values of the model parametersare listed in Table6.The apparent activation energy for FTS oniron catalysts are reported to have a value of56.105kJ mol−1(Van der Laan and Beenackers,1999a).In present comprehen-sive model,the corresponding barrier would be the activationenergy of the rate-determining step(CH2–insertion into themetal-alkylidene bond),with a value of73.46kJ mol−1(E5). It indicates the Fischer–Tropsch synthesis has marked poly-merization characters.On the other hand,the high apparentactive energies for hydrocarbon formation and the secondaryreaction suggest the diffusion interference is not significant inthe experiments(Schulz and Claeys,1999a).The energy bar-rier of35.58kJ mol−1for WGS in present work is also ingood agreement with our prior studies and other literature val-ues(27.7.58.43kJ mol−1)(Lox and Froment,1993a,b;Wang et al.,2003;Yang et al.,2003).Fig.2.Parity graph of experimental and modeling COconversion. Fig.3.Parity graph of experimental and modeling CO2formation rates by WGSreaction.Fig.4.Parity graph of experimental and modeling C+5hydrocarbon yield.J.Chang et al./Chemical Engineering Science 62(2007)4983–49914989Table 6Final estimates for the parameters for the kinetic model of FTS in slurry phase (FT4+WGS1)a Parameter Value Dimension t -value Parameter Value Dimensiont -value k 5,00.35×102mol g −1s −1207.9E h 80.66kJ mol −1248.9E 573.46kJ mol −1223.7K 10.74×10−1MPa −1469.9k 7m,00.57×105mol g −1s −181.3K 20.15×102MPa −183.3E 7m,079.60kJ mol −1177.8K 30.19–60.2k 7,00.18×106mol g −1s −1304.6K 40.45×10−3MPa −1152.1E 776.99kJ mol −1151.4K 60.48×10−1–313.6k 8,00.23×102mol g −1s −1395.4c0.38–70.4E 884.11kJ mol −1201.217.49–26.3k −8,00.14×10mol g −1s −1MPa −1111.5k v,0 3.16mol g −1s −1MPa −1.5186.3E −888.69kJ mol −1229.5E v 35.58kJ mol −125.9k h,00.58×102mol g −1s −1MPa −123.1K v18.34MPa −0.552.2a Statisticalcriterions:F 0.05(21,504)=1.80,t 0.05(504)=1.96(Box et al.,1978).Fig. 5.Product distributions for various experiments.Reaction conditions:(a)523K, 1.45MPa,H 2/CO =0.67,GHSV =2000ml g −1cat h −1;(b)533K,1.50MPa,H 2/CO =0.67,GHSV =1000ml g −1cat h −1;(c)543K,0.95MPa;H 2/CO =0.91,GHSV =2000ml g −1cat h −1;(d)553K,0.96MPa,H 2/CO =1.23,GHSV =2000ml g −1cat h −1.Lines are model predictions,and symbols are experimental values.The value for the carbon number dependence exponential constant c (0.38)is in agreement of the value given by Van der Laan and Beenackers (1999b)(0.29)and Schulz and Claeys (1999a)(0.38,at 523K),which suggests the strong influence on the secondary reactions by the olefins chain length dependent solubility.In addition,ethene is more active than other olefins with a factor 17.49,which is in agreement of the literature values (Paskas and Hurlbut,2003).As shown in Fig.5,the resultant model also can well de-scribe the product distribution in entire experimental condition range.It indicates that the modification based on accounting for the olefin readsorption and its secondary hydrogenation is reasonable.That is,heavier olefin has more marked tendencyto stick on catalyst surface,which leads to higher extent to initiate new chain growth.While when 1-olefins readsorbed on the catalytic sites surrounding by carbon pools like “islands”(site ),where there is not enough monomer to propaga-tion the chain,the hydrogenation became another dominating pathway.6.ConclusionDetailed kinetic study is conducted on an industrial Fe .Cu .K .SiO 2catalyst in stirred slurry phase tank reactor over a wide range of industrial relevant reaction conditions.With the assumption of that the primary olefins can re-enter the4990J.Chang et al./Chemical Engineering Science62(2007)4983–4991carbon chain growth and directly hydrogenate in paraffins on separated active sites,the comprehensive kinetic model based on alkylidene mechanism for FTS and the formate intermedi-ate mechanism for WGS can well predict the CO consumption rate and products selectivity self-consistently.This accurate kinetic model based on LHHW approach can be used in future reactor modeling and scaling-up.Notationc exponential factor of carbon number dependenceE active energy of corresponding elementary stepF obj objective function for regressionk pre-exponential factor of corresponding elemen-tary stepsK equilibrium constantM i,inflow rate of component i at inlet,mol s−1M i,outflow rate of component i at outlet,mol s−1N maximum carbon number of the hydrocarbons in-volvedN exp number of experimentsN R total number of reaction concernedN resp total number of responses for parameter evaluation R gas constant,J mol−1K−1R j reaction rate of the j th reaction,mol g−1s−1w j weight of j th responseW cat the weight of catalyst used,gGreek letters1chain growth factor for carbonnumber1i,j stoichiometric coefficient for i th component in j th reactionn chain growth factor for carbon number n,n>1 n readsorption factor of1-olefin with carbon number nthe active site for primary FT reaction and sec-ondary reaction of the participation into the chaingrowth of1-olefinsactive coefficient of ethene comparing to other olefinsthe active site for the secondary hydrogenation reaction of1-olefinsthe active site for the WGS reaction Subscriptscalc calculated valueexp experimental valueh hydrogenation reactioni index indicating reactionsj index indicating componentsm methanen carbon numbero olefinsp chain propagation stept termination step AcknowledgmentsThe work was supported by Synfuels China.Financial sup-ports from National Natural Science Foundation of China (Grant no.20590361)and National Outstanding Young Sci-entists Foundation of China(Grant no.20625620)are also gratefully acknowledged.ReferencesBai,L.,Xiang,H.W.,Li,Y.W.,et al.,2002.Slurry phase Fischer–Tropsch synthesis over manganese-promoted iron ultrafine particle catalyst.Fuel 81,1577–1581.Breman, B.B.,Beenackers, A.A.C.M.,Rietjens, E.W.J.,et al.,1994.Gas–liquid solubilities of carbon monoxide,carbon dioxide,hydrogen, water,1-alcohols,and n-paraffins in hexadecane,octacosane,1-hexadecanol,phenanthrene,and tetraethylene glycol at pressures up to5.5MPa and temperatures from293to553K.Journal of ChemicalEngineering Data39,647–666.Box,G.E.P.,Hunter,W.G.,Hunter,J.S.,1978.Statistics for Experiments:An Introduction to Design,Data Analysis,and Model Building.Wiley,New York,p.631.Chang,J.,Teng,B.T.,Bai,L.,et al.,2005.Detailed kinetic study of FTS on Co/ZrO2/SiO2catalyst.Chinese Journal of Catalysis26(10),859–868. Donohue,M.C.,Shah,D.S.,Connally,K.G.,et al.,1985.Henry’s constants for C5to C9hydrocarbons in C10and larger hydrocarbons.Industrial Engineering Chemical Fundamentals24,241–246.Huff,G.A.,Satterfield,C.N.,1984.Intrinsic kinetics of the Fischer–Tropsch on a reduced fused-magnetite catalyst.Industrial Engineering Chemical Process Design and Development23,696–705.Iglesia, E.,Reyes,S.C.,Madon,R.J.,1991.Transport-enhanced -olefin readsorption pathways Ru-catalyzed hydrocarbon synthesis.Journal of Catalysis129,238–256.Keyser,M.J.,Everson,R.C.,Espinozat,R.L.,2000.Fischer–Tropsch kinetics studies with cobalt-manganese oxide catalysts.Industrial Engineering Chemical Research39,48–54.Lox,E.S.,Froment,G.F.,1993a.Kinetic of the Fischer–Tropsch reaction on a precipitated promoted iron catalyst1.Experimental procedure and results.Industrial Engineering Chemical Research32,61–70.Lox,E.S.,Froment,G.F.,1993b.Kinetic of the Fischer–Tropsch reaction on a precipitated promoted iron catalyst2.Kinetic modeling.Industrial Engineering Chemical Research32,71–81.Nowicki,L.,Ledakowicz,S.,Bukur,D.B.,2001.Hydrocarbon selectivity model for the slurry phase Fischer–Tropsch synthesis on precipitated iron catalysts.Chemical Engineering Science56,1175–1180.Paskas,I.,Hurlbut,R.S.,ments about the cause of deviations from the Anderson–Schulz–Flory distribution of the Fischer–Tropsch reaction products.Catalysis Today84,99–109.Schulz,H.,Claeys,M.,1999a.Kinetic modeling of Fischer–Tropsch product distributions.Applied Catalysis A186,91–107.Schulz,H.,Claeys,M.,1999b.Reaction of -olefin of different chain length added during Fischer–Tropsch synthesis on a cobalt catalyst in a slurry reactor.Applied Catalysis A186,71–90.Van der Laan,G.P.,Beenackers,A.A.C.M.,1999a.Kinetics and selectivity of the Fischer–Tropsch synthesis:a literature review.Catalysis Review-Science Engineering41,255–315.Van der Laan,G.P.,Beenackers,A.A.C.M.,1999b.Hydrocarbon selectivity model for the gas–solid Fischer–Tropsch synthesis on precipitated iron catalysts.Industrial Engineering Chemical Research38,1277–1290. Van der Laan,G.P.,Beenackers,A.A.C.M.,2000.Intrinsic kinetics of the gas–solid Fischer–Tropsch and water gas shift reaction over a precipitated iron catalyst.Applied Catalysis A193,39–53.Vannice,M.A.,1975.The catalytic synthesis of hydrocarbons from H2/CO mixtures over the group VIII metals II.The kinetics of the methanation reaction over supported metals.Journal of Catalysis37,462–473.Van Steen, E.,Schulz,H.,1999.Polymerisation kinetics of the Fischer–Tropsch CO hydrogenation using iron and cobalt based catalysts.Applied Catalysis A186,309–320.。

地层剥蚀量恢复方法浅述

地层剥蚀量恢复方法浅述

地层剥蚀是多期沉积盆地中普遍存在的现象[1-2],它对沉积盆地中油气的生成、运移和聚集等产生重要的影响。

恢复地层剥蚀厚度是进行地质构造演化史研究的一项很重要的内容,也是进行油气资源定量评价的重要基础工作[2]。

很多地质工作者进行了深入的研究,先后出现了近20种地层剥蚀厚度恢复的方法,比较常用的方法归纳起来有以下5类(图1)。

1 以Wyllie公式为模型计算的方法1.1 测井曲线法基本原理是,正常压实下碎屑岩孔隙度随深度的变化是连续的。

如果我们利用场波测井、密度测井资料或综合解释出的孔隙度曲线观察其变化趋势即可做出有无剥蚀的判断。

目前,人们最常用的是声波时差测井曲线(Magara,1976),一般用于测井曲线质量较高、剥蚀量较大且埋藏较浅时。

在正常压实情况下,页岩压实与上覆的负荷或埋深有关,孔隙度是页岩压实程度的度量,而声波测井资料直接反映了页岩压实程度的大小。

因此,根据正常的压实趋势,应用声波测井资料推算沉积层的压实程度,就可以估算被剥蚀地层的厚度。

它的应用依赖于正确确定地下沉积层的孔隙度-深度和声波传播时间-深度关系。

该方法的缺点是,当剥蚀面再度下沉至大于剥蚀厚度的深度以下时,因压实趋势改变,则无法计算出剥蚀量的大小。

2 地层对比的方法2.1 地层对比法地层对比法是比较传统的恢复剥蚀厚度的方法,即将要恢复剥蚀厚度的地层与邻区未被剥蚀的相同地层进行对比,求出其沉积厚度,除去该地层的残余厚度即可得到地层剥蚀量。

运用地层对比法求剥蚀厚度的原理如图2所示,图中Ⅰ,Ⅱ分别代表地层的深凹处(假设没有剥蚀的地层)和斜坡处(假设有剥蚀的地层)的钻井位,以C组地层为参考地层,即假设C地层在斜坡处没有剥蚀,则深凹处的地层厚度比为:λA=HA/HC其中,HA,HC分别为A地层和C地层在深凹处的厚度。

由地层对比法的原理可以计算斜坡处A地层在斜坡处的剥蚀厚度ΔHA:ΔHA=λA×HC’-HA’其中,HA’、HC’分别为A地层和C地层在斜坡处的厚度。

人体行走过程中上肢运动仿真及生物力学特征分析

人体行走过程中上肢运动仿真及生物力学特征分析

第43卷第8期 2009年8月上海交通大学学报JOU RN AL O F SH AN G HA I JIA OT O N G U N IV ERSIT YVol.43No.8 Aug.2009收稿日期:2008 09 02基金项目:国家自然科学基金重点项目资助(30530230,30470455);上海市体育局科研攻关与科技服务项目资助(07J T018)作者简介:王洪生(1986 ),男,江西上饶人,硕士生.主要研究方向为人体生物力学、人体运动学.王成焘(联系人),男,教授,博士生导师,电话(T el.):021 ********;E m ail:trib@s .文章编号:1006 2467(2009)08 1302 05人体行走过程中上肢运动仿真及生物力学特征分析王洪生, 白雪岭, 张希安, 张琳琳, 王成焘(上海交通大学机械与动力工程学院,上海200240)摘 要:为了分析人体行走过程中上肢运动状态的影响因素,对正常步态下人体上肢运动仿真模型与理想单摆模型进行了对比分析.以7名(4男,3女)步态无异常的志愿者为研究对象,采集人体测量学参数,建立上肢理想单摆模型.采用运动捕捉系统及肌电测量系统,对志愿者常速(1.2m/s)步行下的上肢运动以及肩关节周围6组肌肉的肌电信号进行同步测量,并基于所测运动学参数对人体行走中上肢运动进行仿真,计算实际肩关节角位移和角速度,分析相关肌肉的肌电信号特征.理想模型与实际测量结果比较表明,不同志愿者在同速行走过程中上肢的摆动周期相近,各相关肌肉肌电信号随摆臂而周期性变化,上肢实际最大摆动角速度均大于理想单摆角速度.证明摆臂过程中肩关节周围相关肌群驱动力大于肩关节阻尼.关键词:上肢;肌电信号;步态;运动捕捉中图分类号:R 318.01 文献标识码:AKinematics Simulation and Biomechanics Characteristic Analysis of U pper Extremity during Human WalkingWA N G H ong sheng , BA I X ue ling , ZH A N G X i an, ZH AN G L in lin, WAN G Cheng tao (School of M echanical Eng ineer ing ,Shanghai Jiaotong U niv er sity,Shanghai 200240,China)Abstract:In order to investig ate the factors that influence the mo vem ent condition o f upper extremity dur ing hum an walking,a co mparative study betw een the ex perimental conditio n and the ideal pendulum mo del condition w as co nducted.Firstly,sev en health participants (4males and 3females)w ere inv olved in the ex periment and the pendulum m odels w ere built according to their anthro pom etric parameters.Secondly,the markers coordinatio n and the EM G of related m uscles w ere simultaneously m easured w hen the partici pant w as w alking on a tr eadm ill w ith a daily v elo city of 1.2m/s.Based on the captured signals,the angle and angular velocity of the sho ulder joint w as calculated and the actual angular velocity w as co mpared w ith the v elo city of the upper extremity pendulum mo del.Also an analy sis w as undertaken for the recorded EM G.The study sho ws that the actual maxim um angular velocity of shoulder joint ex ceeds those of the virtual pendulum s and the EM G of the related m uscles w as cycling according to the periods of sw ing.The ex periment also indicates that the actual periods o f upper limb swing represent a level of similarity amo ng different participants;the related muscular forces contribute larg er motivity than the damp of the shoulder joint during human w alking in a no rmal speed.Key words:upper ex trem ity ;electro myo graphy (EM G)sig nals;g ait;mo tion capture正常人体步行过程中,上肢伴随下肢的运动而做周期摆动.Wagenaar等[1]认为,人体在低速运动过程中上肢的习惯摆动周期与上肢的固有频率(质量与质心到肩关节的长度的函数)有关;而在高速过程中上肢摆动频率主要与下肢的频率有关.Webb 等[2]在对人体上肢运动特性的研究中引入了虚拟单摆理论,分析了步频与人体上肢单摆频率的关系,并认为单摆假设将在上肢运动研究中扮演重要角色. Bertram等[3]对人体上肢单摆模型进行了进一步研究,并从能量角度对模型仿真性能加以探讨.而基于上肢单摆模型的研究表明[4],人体肌肉能量消耗主要用来改变人体的质心位置.Neptune等[5]提出肌肉的能量输出不仅用于双脚支撑阶段时人体质心位置的改变,还用于单脚支撑阶段质心位置抬高. Gutnik等[6]把步态过程中人体上肢运动与虚拟单摆运动进行了比较,认为肌肉对上肢运动具有一定的影响.然而,以上研究没有在人体步态测量过程中同步进行主要肌肉群的肌电信号测量.本文在步态试验中对肌电信号进行同步测量,与理想单摆模型进行对比,分析上肢肌肉群对人体行走过程中上肢摆臂运动的影响.1 试验方法1.1 试验对象在上海交通大学机械与动力工程学院师生中挑选7名身体健康并步态无异常的志愿者(4男3女)作为研究对象(试验之前他们均不知道本试验的直接目的).测量志愿者的人体测量学参数(见表1),包括:身高、体重、前臂长度、上臂长度以及手长;前臂长度为桡骨茎突到外上髁距离、上臂为肩峰到外上髁,手为桡骨茎突到中指指尖距离,臂长取为肩峰到桡骨茎突.表1 志愿者人体测量学基本参数Tab.1 Anthropom etric parameters of participants试验对象(编号)身高/m体重/kg上臂长/m前臂长/m手长/m#1 1.76363.20.3150.2450.195男性#2 1.63350.20.3000.2180.177#3 1.73563.50.3120.2550.190#4 1.81780.10.3250.2620.200#5 1.65455.20.2820.2250.178女性#6 1.58746.50.2850.2100.175 #7 1.72153.40.3170.2450.1801.2 试验设备及方案本试验采用Optotrak Certus运动捕捉系统对人体行走过程中上肢运动进行运动捕捉.如图1所示,2个Marker刚体(每个刚体至少由3个Marker 点组成)通过自黏性纱布分别固结在前臂、上臂的外侧,另一个刚体贴附于胸骨,以参考计算上臂摆动角度.由于手腕关节在行走过程中运动幅度微小,故可把手与前臂视为同一个刚体.对于不易采集的各关键解剖特性点,采用Optotrak Certus运动捕捉系统的虚拟工具进行虚拟M arker设置(虚拟M arker所对应刚体的位置不变),分别对上肢运动相关的6个解剖特征点(肩峰、外上髁、内上髁、桡骨茎突、尺骨茎突、中节指关节)设置虚拟Marker点,并测量贴附于试验对象上肢主动发光Marker点的三维运动轨迹.上肢的运动的捕捉频率为30H z,测量误差在0.1m m以内.图1 前臂/上臂刚体及创建的虚拟M arker(白色的亮点示意)F ig.1 T he attached M arker cluster s of for earm/upper arm&the anat omical land mar ker s(w hite highlig hts)采用8 通道肌电测试系统对摆臂过程中肩关节周围6块主要肌肉(三角肌前部、胸大肌锁骨部、肱二头肌、背阔肌、大圆肌、三角肌后部)的肌电信号进行同步测量,试验过程详见文献[7].1.3 试验过程首先对试验对象进行人体学参数测量,然后按以上制定的M ar ker点和肌电电极方案依次对其进行贴附.志愿者上身穿短T恤或背心.在捕捉试验开始之前调节跑步机速度至1.2m/s,每位试验者都将进行至少4次适应性练习,以适应试验室的光线、温度、跑步机及其他仪器设备.要求试验者以自然放松的状态走,然后开始捕捉测量;每位试验者同样动作循环20次.2 结果及数据分析2.1 上肢单摆模型的运动分析上肢运动过程中单摆的质量为上肢的总质量,1303第8期王洪生,等:人体行走过程中上肢运动仿真及生物力学特征分析单摆长度为上肢质心到肩关节距离.如图2所示,前屈/后伸过程中质心落在上肢体以外,具体位置确定如下[8]:x = (m ix i )m iy = (mi y i )mil =(x 2+y 2)(1)式中:m i 为各部位的质量;x i 为m i 质心到支点(肩关节)的水平距离;y i 为m i 质心到支点(肩关节)的垂直距离;l 为单摆的长度.得到最大前屈位置或最大后伸位置的等效单摆的质量与长度,则在最低点的转速:I max =m l 2maxE potential =mg (L -l max )max =2E potential /I max(2)式中:l max 为平衡位置单摆最大臂长;L 为平衡位置单摆臂长;E potential 为上臂最高点(最大前屈)势能,g 为重力加速度;I max 为平衡位置转动惯量; max 为单摆最大角速度.根据人体惯性参数的国际标准[9],把已测得的人体参数代入如下的二元回归方程:y =B 0+B 1X 1+B 2X 2(3)图2 上肢摆动前屈/后伸过程F ig.2 T he fo rw ard flex io n/backwar d ex tensiono f upper limb式中:X 1、X 2分别为试验对象的体重与身高;B 0、B 1、B 2为方程系数(与性别有关).由式(3)计算出试验者上肢各部位的质量、质心位置.将上肢各部位的质量、质心位置代入式(1)可得各位试验者上肢的l max 、L 和I max (见表2).最大前屈/后伸垂直位置可由三维捕捉系统(NDI)测量得到;理想单摆模型的最大前屈势能全部转化为摆动最低点的动能,把所得数据分别代入式(2)可得单摆平均最大角速度 max ,结果如表2所示.表中质心测量起点为:上臂,即桡骨点;前臂,即桡骨茎突点;手,即中指指尖点.表2 志愿者上肢基本惯性参数及计算所得单摆模型参数Tab.2 The inertial parameters of upper limb and the calculated parameters of virtual pendulum试验对象(编号)质心位置(m)/质量(k g)上臂前臂手l ma x /m I ma x /(k g !m 2) max /(rad !s -1)#10.167/1.750.137/0.910.116/0.470.2810.2477 1.024男性#20.154/1.350.124/0.690.110/0.380.2470.1995 1.457#30.164/1.760.135/0.910.116/0.460.2750.2454 1.214#40.174/2.260.147/1.200.122/0.540.3020.2832 1.078#50.158/1.450.122/0.650.116/0.270.2540.2024 1.201女性#60.150/1.190.116/0.520.112/0.250.2420.1878 1.054#70.161/1.310.123/0.630.116/0.280.2650.21841.1652.2 实际运动测量数据分析利用NDI 将测得的各解剖特性点的运动学参数以及肌电测量仪(Bo rtec)同步采集的目标肌肉的肌电信号保存为*.c3d 格式的文件.然后,将该文件导入Visual3D 中建立对象的三维骨架模型,并进行运动计算,计算正常行走过程中上肢摆动的角位移、角速度.其中,典型运动阶段如图3所示.图4所示为正常行走过程中上肢摆动状态下的肩关节角位移和角速度曲线.其中,#1为所测4名男性试验者运动学参数平均值,#2为3名女性试图3 V isual3D 上肢模型摆动的典型阶段F ig.3 T he mo del of ty pical perio ds dur ing upperlimb swing1304上 海 交 通 大 学 学 报第43卷(a)#1试验者步行时手部解剖特性点垂直位置变化(b)#2试验者步行时手部解剖特性点垂直位置变化(c)#1试验者步行时肩关节矢状面角度(d)#2试验者步行时肩关节矢状面角度(e)#1试验者步行时肩关节矢状面角速度(f)#2试验者步行时肩关节矢状面角速度图4 试验对象的中节指关节点垂直位移、肩关节角位移与角速度曲线F ig.4 T he vert ical displacement o f PM,ang ular displacement and velocity of shoulder joint fo r participants验者的平均值,采样频率为30H z.可见:正常速度(1.2m/s)下不同对象同速步行时,摆臂周期具有一定统一性[(1.1∀0.08)s],但摆臂幅度以及角速度有较大差异.#1步行过程中肩关节最大转角为(0.17∀0.01)rad与(-0.12∀0.01)rad(后伸);最大角速度为(0.64∀0.11)rad/s与(-0.88∀0.07)rad/s(后伸).#2肩关节最大转角为(0.20∀0.02)rad与(-0.13∀0.01)rad(后伸);最大角速度为(0.84∀0.12)rad/s与(1.00∀0.05)rad/s(后伸).将实测结果与理想单摆模型计算结果进行比较发现,人体上肢理想单摆模型计算得到的矢状面上肢运动学参数与实际结果偏差较大.2.3 肌电信号分析本文对志愿者正常行走过程中上肢主要肌肉的肌电信号进行了同步采集,采集频率为900H z.结果表明,在步态过程中,肌电信号呈现出周期性变化特征.图5所示为一个步态周期下,志愿者正常行走过程中肩关节主要肌肉的肌电信号,其中,高频信号已经过整流与低通滤波处理.由图可见,1个周期内各肌电信号的变化趋势:前屈阶段(0~0.75s)三角肌前头、三角肌后头受到较大刺激,肌电信号分别从0.02mV增至(0.103∀0.007)mV(三角肌前头)、(0.081∀0.006)mV(三角肌后头);大圆肌有平均1305 第8期王洪生,等:人体行走过程中上肢运动仿真及生物力学特征分析0.37mV 的肌电信号;后伸阶段(0.75~1.17s)大圆肌肌电信号从0.037m V 增大到0.105mV,三角肌前/后头也分别受到0.03mV 水平的肌电刺激;在整个周期中,背阔肌、肱二头肌及胸大肌的肌电信号较小.图5 上肢摆动中肩关节主要肌肉的肌电信号Fig.5 EM G o f the main muscles related to upperlimb s movement3 讨 论男性试验者上肢单摆模型的平均最大角速度为0.51rad/s,而实际所测最大前屈角速度为(0.64∀0.11)r ad/s;女性试验者上肢单摆模型最大角速度为0.73rad/s,而实际所测最大前屈角速度为(0.84∀0.12)r ad/s.比较上述数据,即人体实际最大摆臂速度大于无阻尼下的单摆速度.所测肌电信号反映了上肢肌肉对摆臂的作用情况,即前屈阶段三角肌前/后头发出较大的肌肉力、而后伸阶段大圆肌对上肢施加了较大的驱动力.肱二头肌肌电信号较小,说明在摆臂过程中肘关节屈伸幅度较小;胸大肌肌电信号较小,说明摆臂过程中上肢外展、外旋(即冠状面、横截面运动)幅度较小.背阔肌对上臂的作用主要为使臂内收、内旋和后伸,其信号微弱,说明摆臂过程中内收、内旋的阻力较小.同时,由于前屈时较大的势能转化为后伸的动能,使得在正常行走中需要背阔肌作为后伸原动力较小.上肢摆动状态受重力、相关肌肉力和肩关节关节阻尼的综合影响,由实际与理想模型的比较结果可知,肌肉力驱动作用大于关节阻尼,则实际速度大于理想模型速度.4 结 语本文基于运动捕捉系统和肌电测量系统,以7名无步态异常的高校师生为试验对象,对其进行了正常步态过程中上肢运动的运动学测量,并同步测量了相关肌肉的肌电信号,避免了运动与肌电分开测量时所带来的误差.将实际运动与上肢理想单摆模型运动进行比较,得出正常步态(1.2m/s)三角肌、大圆肌对肩关节驱动力作用大于关节阻尼,且实际摆臂角速度大于无阻尼状态的理想单摆模型角速度.文中建立的一整套试验方案对以后人体上肢运动测量试验有一定的指导作用,对人体上肢运动状态的深入研究、人体运动机制研究、脑偏瘫诊断、康复治疗等领域具有深远意义.参考文献:[1] Wag enaar R C,v an Emmer ik R E.R eso nant fr equencies of arms and legs identify different w alking patterns [J].Journal of Biomechanical ,2000,33(7):853 861.[2] Webb D,T uttle R H,Baksh M .Pendular activ ity o fhuman upper limbs during slo w and no rmal w alking [J].American Journal of Physical Anthropology ,1994,93(4):477 489.[3] Bert ram J E,Chang Y H.M echanical energ y oscillations o f tw o brachiatio n g aits:M easurement and simu latio n [J].Am erican Journal of Physical Anthropology ,2001,115(4):319 326.[4] Kuo A D.Ener getics o f actively pow ered lo co motionusing the simplest w alking mo del [J].Journal of Bio mechanical Engineering ,2002,124(2):113 120.[5] Neptune R R,Zajac F E,Kautz S A.M uscle mechanical w or k r equir ements during no rmal w alking :T he en er getic cost of r aising the bo dy s center of mass is sig nificant [J].Journal of Biomechanics ,2004,37(6):817 825.[6] Gutnik B,M ackie H ,H udson G,et al .H ow clo se toa pendulum is human upper limb mov ement during walking ?[J].Journal of Comparative Human Biology ,2005,56(1):35 49.[7] Luttg ens K ,Hamilto n N.Kinesio lo gy :Scientif ic basisof human motio n [M ].Bosto n:W CB M cGr aw H ill,1997.[8] T imo shenko S,Y oung D H.Eng ineer ing mechanics[M ].4th edition .N ew Y or k:M cGr aw H ill,1956.[9] 刘静民.GB/T 17245 2004成年人人体惯性参数[M ].北京:中国标准出版社,2004.1306上 海 交 通 大 学 学 报第43卷。

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以下是lw54小编为您整理的金融专业参考文献,希望能提供帮助。

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淮南采煤塌陷湖泊浮游植物优势种的营养动力学

淮南采煤塌陷湖泊浮游植物优势种的营养动力学

!#$%'((湖泊科学),2018,!0(%):713-722D O I10. 18307/2018.031%©2018b y Journal o f Lake Sciences淮南采煤塌陷湖泊浮游植物优势种的营养动力学!张鑫、易齐涛1,3!!,谢凯2,张思亮、佘艳霞、张银1(1:安徽理工大学地球与环境学院,淮南232001"(2$安徽理工大学数学与大数据学院,淮南232001)(3:中国科学院生态环境研究中心,北京100085"摘要:在淮南潘谢矿区选取3个营养盐结构差异较大的塌陷湖泊,于2014—2015年4个季度分别对浮游植物群落结构组成进行调查,选取3个湖泊中的优势种(属)具尾蓝隐藻(<?r o r n f a s c a u2a3)、链形小环藻(<7.31catena3)和伪鱼腥藻(9s u2a n a:a e a SP.)作为研究对象,设置不同的氮(N)、磷(P)浓度梯度进行营养动力学培养实验,并结合M a A方程,获得3个藻种在不同营养盐限制下的营养动力学参数.N限制下具尾蓝隐藻、小环藻和伪鱼腥藻的最大生长速率(%腿)和半饱和常数([0分别为:0.66扣、1.66瓜§/;0.37^1、1.06瓜§/;0.71扣、2.26瓜§/;4限制下它们的%歷和[0则分别为:061d'0.023m g/L;0.31d'0.035m g/L;0.90d'0.015m g/L•综上所述,在N充足时,伪鱼腥藻能够在竞争中形成优势,同时在P限制情况下易成为优势种,从营养动力学的角度揭示了其在塌陷湖泊中占据优势的营养盐动力学机制.研究结果可以为沉陷区水域开发利用和营养盐管理提供科学依据.关键词:采煤塌陷区;塌陷湖泊;浮游植物;营养动力学;营养限制Nutrient kinetics of dominant species of phytoplankton in the artificial lakes formed fromland subsidence by mining activities in the Huainan coalmine subsidence areasZHANG X in1,Y I Qitao1,3**,XIE Kai^,ZHANG Siliang1,YU Yanxia1&ZHANG Yin1(1:School of Earth and Environment,Anhui University of Science and Technology,Huainan232001,P.R.China)(2: School of Mathematics and B.Data,Anhui University of Science and Technology,Huainan 232001,P.R.China)(3:Research Center for Eco-environmental Sciences,Chinese Academy of Sciences,Beijing100085,P.R.China)A b s tr c ic t:T hree lakes in the H u a in a n P a n xie c o a lm in e a re a s,w itli d?fe re n t n u trie n t r a tio,were in ve stig a te d fo r th e ir p h y to p la n k­ton co m m u n itie s in fo u r seasons fro m2014to 2015. T h re e d o m in a n t species ( g e n e ra) o f p h y to p l caudata,Cydotella catenata and Pseudanabaena s p.,w ere selected to o b ta in th e ir n u trie n t k in e tic s b y a n u m b e r o f in c u b a ti pe rim e n ts withi lim ita tio n fo r in d iv id u a l n itro g e n(N) and phosphorus ( P )•U n d e r N lim it a t io n c o n d itio n s,the grow th and half-satiarated constant fo r the thre e species o f Chroormnas caudate,Cydotella catenata 0.66 d 1and 1.66m g/L,0.37 d 1and 1.06m g/L,0.71 d 1and 266m g/L,re s p e c tiv e ly; w ith respectthey w ere 0.51 d 1and 0.023m g/L,0.31 d 1and 0.035m g/L,0.90 d 1and 0.015m g/L,resp e ctive ly. E s p e c ia lly,the P s u d a n-abaena sp. takes d o m in a n t ro le due to its n u trie n t co m p e titio n a b ility u n d e r P lim ita tio n in th is typefo r its grow th. T h is research has im p o rta n t im p lic a tio n on lo c a l n u trie n t m anagem ent o f w a te r resources in theK e y w o r d s: C o alm ine subsidence a re a s; sub sid e n cc la k e s; p h y to p la n k to n; n u tritio n k in e tic s; n u trie n t lim ita tio n淮南煤矿近几十年来由于煤炭的大量开采,导致了大面积的土地沉陷和积水,形成了许多小型塌陷湖泊组成的水生态景观.研究资料表明2010年淮南矿区土地沉陷面积达140k m2,至2020年将进一步扩展至200k m2,其中水域面积占30%〜50%,在矿区社会经济发展和生态环境保护中具有十分重要的作用[1],因而!国家自然科学基金项目(51579001,51504012)和中国博士后科学基金项目(2014M560127)联合资助.2017-07-04收稿;2017-08-13收修改稿•张鑫(1994 〜),女,硕士研究生&E-m a il:418849804@q q x o m.!!通信作者;E-m a il:y iq ita o@163.c o m.714!#$%'((湖泊科学),2018,!0(%)对其生态系统结构和功能的研究具有十分重要的意义.游植物是生态系统的主要初级生产者和食物网的起点,也是生物与环境因子相互作用的第一个重要界面,其群构组成和演对区域生态环境特征具有重要的指用,同时对生态系统构和功着性的调控作用[2]..前,涉及采煤塌陷湖泊中浮游植物群构与环境因子关系的研究较多,研究表淮南采煤塌陷湖泊浮游植物群构的主要环境因子为光照、水[%],淮北采煤塌陷湖泊浮游植物群构演替的主要环境因子浓度度等[4].本研究在分析淮南采煤塌陷湖泊浮游植物群构的上,选择其中的优,在(Y)、(P)浓度梯度行限制培养实验,并用M〇n〇d方确定动力学参数.本研究拟游植物群构野外调查结室动力学实验,深入分类型湖泊优势物种形成和演的动力学机制,以获得更加准确可靠的,研究区的理提供科学依据.1材料与方法1.1研究区域与站点淮南潘谢矿区(32°42'23X32°55'38"Y,116°18'32"〜116°57'05"E)是淮南煤矿基地中沉陷积水最为集中的区域,安黴省淮河北岸冲积平原,西长近58k m,南北宽6〜25k m,面积约865k m2..道西淝河、、、、架,人工河道有,均由西北向东南流入淮河[5],自西向东分为西淝河、永幸河、架4个小流域.在潘谢的潘集矿区、中的顾桥西部的谢桥选1个采煤塌陷湖泊进行研究(图1),分别命名为潘谢潘集(P X P)、潘谢顾桥(P X G Q)和潘谢谢桥(P X X Q).这3个湖泊水较大,其中4X4〗站点潘集西北侧,与流的泥河常通,小流域;P X G Q站点桥西北侧(永幸小流域),但水体相对&P X X Q站点则谢桥矿的西北侧,在汛期通过节制闸接纳南边的性引水.3个湖泊用于渔业:地,有苗投入,但一无施加,湖泊的形成、容积、水深和面积等具体信献[6].图1潘谢采煤沉陷区研究湖泊站点分布F i g. 1 D istri b u tio n o f t h e s u b si d e n c e are as a n d locatio n o f t h re e st u d ie d la k e s i n t h1.2水质、浮游植物样品采集与分析2014 — 2015年分4个季度对P X P R P X G Q和P X X Q3个湖泊的水质特征和浮游植物群落结构进行调张鑫等:淮南采煤塌陷湖泊浮游植物优势种的营养动力学715查和分析.在各湖泊中心附近设置3个水质采样点,用有机玻璃采水器采集表层水样.水质调查和分析指标 包括:水温(Tem)、PH、透明度(SD)、电导率(EC)、溶解氧(DO)、总悬浮颗粒物(TSP)、碱度(A ik)、溶解性反 应磷(P〇2—-P)、硝态氮(YO\-Y)、化学需氧量(COD&)、总氮(TY)、总磷(TP)和叶绿素a(Chl.a).其中分别 使用p H计(YSI pH100)、JPB-607A便携式溶解氧测定仪、塞氏盘和DDS-11A电导率仪对pH、D O浓度、SD 和E C进行现场测定.参照相关国家标准,TSP采用重量法测定,碱度采用酸碱指示剂滴定法测定,PO:T-P浓 度采用钼兰分光光度法测定,NO\-N浓度采用紫外分光光度法测定,T N浓度采用碱性过硫酸钾消解一紫外 分光光度法测定,T P浓度采用过硫酸钾消解一钼酸铵分光光度法测定,COD&采用重铬酸钾法测定[7].Chl.a 浓度采用分子荧光法测定[8].选取SD、TN、T P和Chl.a共4个指标计算湖泊营养状态综合指数(G/),具体 计算公式参见文献[(].浮游植物采样点和水质采样点一致,定性样品用25#(网孔直径64 #h)浮游生物网在水面下0.5 h处以 “”字型来回捞取,加鲁哥试剂固定,部分样品作活体观察,用于鉴定种类.定量样品用5.0 L采水器根据水 深采集上、中、下层水样混合后装入1000 m l采集瓶,现场加入15 m l鲁哥试剂固定,带回实验室静置沉淀48 h并浓缩至50 ml.计数前摇匀后取0.1 m l在20 mmx20 m m的计数框内鉴定和计数,计数方法采用视野法,对于群体性藻类如铜绿微囊藻(=)*y0) ae™g)*a)等,以细胞数计数,具体参照文献[10].1.3营养动力学实验在对4个季节浮游植物群落结构分析的基础上,选取不同门类的浮游植物优势种进行营养动力学实 验,分别为具尾蓝隐藻()、链形小环藻()和伪鱼醒藻(Pseudanabaena 5.),在不同Y、P浓度的培养基进行营养限制培养.藻种均购于中国科学院水生生物研究所,培养基具体配 方参见中国淡水藻种库官网,其中具尾蓝隐藻采用BBM培养基,链形小环藻采用CSI培养基,伪鱼腥藻采用 BG-11培养基.实验前将各藻种扩大培养1周,再饥饿培养2 d后取一定体积的藻种以4000转/m in离心8 min,去掉上 清液,用15 mg/L的NaHCO%洗涤后离心,去上清液,此过程重复3次,然后用无菌水稀释至一定的密度用于 接种和实验.实验中所有玻璃器皿均用稀盐酸浸泡过夜并用去离子水洗涤,培养基均用高压灭菌锅在1211 下灭菌0.5 h[11].采用动力学“分批培养实验”,每组设置3个平行.以各藻种培养基为基础配制成无Y或无P培养基,然 后分别加入系列浓度的营养盐(YaYO%或WHPO4),具体Y、P浓度在范围内倍比梯度设置见表1,最高浓度 一般设置为实际水体的2〜3倍,其中P高浓度添加不超过PXGQ站点水体P的浓度范围.取配置好的各组 培养基100 m l置于250 m l三角瓶中,接种对应藻种后置于光照培养箱(GZX-400BS-I I I)中静置培养,温度设 置为251,光照强度为4000 l,光暗比为12 h:12 h,每天定时晃瓶3〜4次,并定时取少量样品在显微镜下进 行藻细胞计数,其中伪鱼腥藻为丝状蓝藻并容易聚团,在计数前稀释并用超声波震荡离散后再进行计数.在 培养后期,3组平行实验中至少两组藻类增长率低于5%时认为藻类达到最大生物量并终止培养.表1 3种优势种藻类培养实验添加的氮、磷浓度Tab.1Added nitro/en and phosf)horus concentrations for phytoplankton nutrient kinetics experiment培养藻种营养盐添加浓度/(m/L)具尾蓝隐藻P00.010.020.040.080.160.320.64N00.200.400.80 1.60 3.20 6.4012.8链形小环藻P00.010.020.040.080.160.320.64N00.200.400.80 1.60 3.20 6.4012.8伪鱼腥藻P00.010.020.040.080.160.320.64N00.200.400.80 1.60 3.20 6.4012.81.4数据分析方法用浮游植物优势种的优势度指数(M)来确定浮游植物优势种,其计算公式为:716! #$% '((湖泊科学),2018,30(3)式中,F为优势度指数,-,为各站点i物种的个数,#为各站点浮游植物总个数,/,为i物种在各站位中出现的 频率.当F>0.02时,该物种为群落中的优势种.生物量测定采用血球计数板计数法进行,特定增长率(M)指在某一时间间隔内藻类生长速率[11],计算 公式为$[2/^1)/(t2~t#)(2)式中,[为某一时间间隔终结时的藻类现存量,[为某一时间间隔开始时的藻类现存量,3\i为时间间隔. 将M a A方程式;%=%_•(((&)变成以下形式进行动力学参数计算[12]$1Z11…M M m a x C M m a x式中为比生长速率为最大比生长速率,(为限制性基质浓度(mg/L),Z为半饱和常数(mg/L).以1/和1/C做图,通过线性回归求得%>…和&值.2研究结果2.1湖泊水质特征调查期间,PXPJ站点水体TP、T N和Chl.a浓度变化范围分别为0.05~0.10 m//L、1.4~4.1 m/L和6.5~ 43.0m//m3;PXGQ站点这 3 个指标变化范围分别为 0.14~0.63 m//L、1.4~4.7 m/L和 3.2~63.7 m//m3; PXXQ站点则分别为0.03~0.08 m//L、1.2~4.5 m/L和10.5~40.8 m/m%(表2).总体来看,3个湖泊水体 Y、P和Chl.a浓度均较高,体现了富营养化湖泊的典型特征.表2调查期间淮南潘谢采煤沉陷区内3个塌陷湖泊的水质指标T a b.2S e a s o n a l w a te r q u a lit y o f t lie th r e e la k e s i n th e H u a in a n P a n x ie c o a lm in e a re aP X P J P X G Q P X X Q水质指标---------------------------------------------------------------------春季夏季秋季冬季春季夏季秋季冬季春季夏季秋季冬季T e m/l18.529.318.6 4.621.533.717.5 5.320.030.317.9 3.3E C/(#S/c m)757580585524427620506429977723617540S D/m 1.20.7 1.0—0.70.60.6— 1.10.70.9 1.3p H9.388.237.467.649.218.848.367.679.208.367.577.66D0/(m g/L)8.0811.10 5.3311.507.8814.83 6.9011.17.6815.36 5.8610.83T S S/(m g/L) 5.77.0 4.38.010.312.7 3.79.0 3.312.7 6.8 3.0C0D c r/(m g/L)21.719.722.224.736.926.629.824.720.516.723.021.7A l k/(m g/L)248134189189151111130143266142194217T P/( m g/L)0.080.100.070.050.260.630.520.140.060.080.060.03T N/( m g/L) 4.1 1.6 1.4 2.3 4.7 1.4 2.1 2.0 4.5 1.2 1.2 1.5N0\-N/( m g/L) 1.040.350.49 1.420.640.170.80 1.34 1.750.090.190.93P〇4_-P/(m g/L)0.00600.0310.0010.1170.4810.4280.0900.00700.0100C h i.a/( m g/m3 )21.843.07.3 6.563.730.930.8 3.210.540.816.611.22.2湖泊浮游植物群落结构特征调查期间,3个湖泊共观察到浮游植物7门51属88种,其中绿藻门种类最多,共43种,占浮游植物总 种数的48.8%;其次是蓝藻,共21种,占浮游植物总种数的23.9%;桂藻17种,占总种数的19.3%;甲藻4种,占总种数的4.5%;裸藻2种,占总种数的2.3%(图2).P X P站点春季的第1优势种(属)为尖针杆藻,优势度为0.199,第2优势种(属)为伪鱼腥藻(优势度为0.180);夏、秋和冬季第1优势种(属)分别为具尾蓝隐藻、小环藻和具尾蓝隐藻,优势度分别为0.215、0.224和0.372.P X G Q站点春、冬季第1优势种(属)为具尾蓝隐藻,优势度分别为0.559和0.250;夏、秋季第1优张鑫等:淮南采煤塌陷湖泊浮游植物优势种的营养动力学717势种(属)为伪鱼腥藻,优势度分别为0.412和0.528.P X X Q站点春季第1优势种(属)为具尾蓝隐藻,优势度为0.244;夏、秋季为伪鱼腥藻,优势度分别为0.510和0.473;冬季为卵型隐藻,优势度为0.375(表3).表 3 P X P J、P X G Q和P X X Q湖泊水体中浮游植物优势种(属)名录及优势度分布!T a b. 3 D o m in a n t s p e c ie s o f p h y t o p la n k t o n i n th e th r e e la k e s a t s ite s P X P J,P X G Q a n d P X X Q季节 PXPJ PXGQ PXXQ春季尖针杆藻'7&ra ac+(0.199)伪鱼腥藻属 9e+2a-a:e-a(0.180)具尾蓝隐藻 ca+2ato(〇_164)卵形隐藻 <736*$Ehr_(0_121)衣藻属 0.064)曲壳藻属 &(0.053)螺旋纤维藻 &6+0ra.(0.051)链形小环藻 ca3-ato(0.040)小球藻属 <?.,&$(0.032)夏季具尾蓝隐藻<w*m*a0a+2ato(0_215) 伪鱼腥藻属 9e+2a-a:e-a(0.183)链形小环藻 (3-a3(0_166)卵形隐藻 <736*$*$3(0.089)螺旋藻属'>,.-$(0.079)小球藻属 C?.re&a(0.058)尖针杆藻'7&ra $c+(0.023)简单罗马藻 Jom&$0m>e30.021)秋季小环藻属Cy(o3&$(0.224)卵形隐藻 <7360-$*$3(0.192)变异直链靈=&0$ ;,$—(0.087)具尾蓝隐藻 <w*6*$0$+2$3(0_050)伪鱼腥藻属 9e+2$-$:e-$(0.050)衣藻:属Chl$m ydonw n$s(0_Q37)財状针杆藻'7&,+-$(0.037)双对珊藻'ce-ed&6+ :+8$(0.031)四尾珊藻'(-&&6+g+$d,$+d$(0_031)微小四角藻 G&raedro- 6)6+6(0.031)小球藻属 Chlre&$(0.031)嗤蚀隐藻 <736*$0,0(0.031)具尾蓝隐藻 <ro〇6〇-$0$+d$3 (0.559)卵形隐藻 <,>〇6〇-$5 〇;3(0_105)衣藻属 <1.6;7〇6〇-$0 0.081)链形小环藻 <7.&$ c$3-$3 (0.073)伪鱼腥藻属 9e+d$-$:e-$(0.038)小球藻属 Chlr&$(0.027)伪鱼腥藻属 90+d$-$:&$(0_412)弯形小尖头藻 J$phidi*0c+,$to(0.123)色球藻属 Chr*c*c+(0.106)链形小环藻 <7.&$ c$3-$3(0.081)螺旋藻属'>,.-$(0.041)细小平裂藻 M e,r n*edi$ 6)6$(0.028)尖针杆藻'7&ra $c+(0.025)小球藻属 Chlr&$(0.024)具尾蓝隐藻 <ro〇6〇-$0$+d$3(0.021)卵形隐藻 <,>〇6〇〇$ 〇;3(0.021)伪鱼腥藻属 90+d$-$:e-$(0_528)小环藻属 <7.3&$(0.100)螺旋藻属'>,.-$(0.080)卵形隐藻 <,>〇6〇〇$ 〇;3(0.040)点形平裂藻=&)r n*edi$ >-($3(0.027)具尾蓝隐藻 C^hr*mm$0$+d$to(O•244)链形小环藻 <7.&$c$3-$3(0.175)尖针杆藻'7&,$c+(0.101)伪鱼腥藻属 9e+d$-$:e-$(0.077)小球藻属 Chlre&$(0.070)螺旋纤维藻 1-%0*&6+0)$l(0.057)卵形隐藻 <73rn o-$*$3(0.047)四尾珊藻'(-&&6+g+$dr)$+d$(0_043)梅尼小环藻 <r l&$rn-&hini$-$(0_020)小型月牙藻'&-$0+6 6)+36(0.020)伪鱼腥藻属 9&d$-$:e-$(0_510)弯形小尖头藻J$ph)*0(,$3(0.081)具尾蓝隐藻 C^hroom m$0$+d$to(O•O69)束丝藻属 1>$-)〇6-*(0_057)链形小环藻 <7.3&$ c$3-$3 (0.039)衣藻:属Chl$6ydonw n$s(0_Q32)卵形隐藻 <73rn*$s*$3(0.031)尖针杆藻'7&, $c+(0.027)小球藻属 Chlre&$(0.020)伪鱼腥藻属 9e+d$-$:e-$(0.473)链形小环藻 <7.&$ c$3-$3 (0.089)颗粒首链蕩=&0$ 8$-+$3(0.048)束丝藻属 1>$-)〇6-*( 0.041)卵形隐藻 <73rn*$s*$3(0.034)尖针杆藻'7&, $c+(0.034)拟浮丝藻属 9$-%o3r)o)e00.034)螺旋藻属'>,.-$(0.034)直角十字藻 <+)&),($-8+$,(0.027)新月藻属<*&+6(0.021)裸甲藻属 E?rawd))6(0.021)冬季具尾蓝隐藻C^h room m$0$+d$to(O•372)具尾蓝隐藻 <ro〇6〇-$0$+d$3 (0.250)卵形隐藻 <73rnm$s*$3(0.375)小环藻属 <7.&$(0.128) 小环藻属 C y d&$(0.150) 具尾蓝隐藻 C hro〇™*$s c$+d$to(0.291)微芒藻=),(-)6sp_(0_128) 卵形隐藻 <736〇-$s〇;3(0• 125)钟形裸甲藻 Ey6-od))66),36(0.128)小球藻属 <1,&$(0.100)颗粒首链藻=&0$ 8$-+$3(0.047) 韦斯藻属 N&e&$ :3*de00.100)小球藻属<1,&$(0.047) 针杆藻属'7&,(0.075)尖针杆藻'7&, $c+(0.023) 舟形藻属 C$;+$(0.075)桥弯藻属 0^6:&$(0.023) 四尾珊藻'(&d&6+g+$dr)$+d$(0.050)拟浮丝藻属 9$-%o3r)o)e00.167)小环藻属〔7.3&$(0.125)螺旋纤维藻 1-%3*&6+0)$l(0.042)!括号里数据为优势度.2.3浮游植物优势种的营养动力学2.3.1Y添加的藻类生长动力学具尾蓝隐藻培养周期为12d,在Y添加浓度为0.2m g/L时,开始对藻生长有促进作用,在Y添加浓度为3.2m g/L以上时达到最大生物量;链形小环藻培养周期为10d,Y添加浓度在1.6m/L时只生长到第6d便持续减少,在Y添加浓度为3.2m/L以上时达到最大生物量;伪鱼腥藻培养周期为8 d,其生长周期比其他两种藻要短,在前3 d处于适应期,Y浓度在0.8m<L时开始对生长有促进作用,随着[ID 金藻门□甲藻门 □裸藻门 H 隐藻门 H 绿藻门 H 硅藻门H 蓝藻门718((湖泊科学),2018,!0(%)春季夏季秋季冬季 春季夏季秋季冬季 春季夏季秋季冬季图2%个湖泊不同季节浮游植物的种类分布Fig .2 Seasonal distributions of phytoplankton taxa in the three lakesN 浓度的增加生物量呈非常快速的趋势,N 浓度为12.8 m g /L 时,其生物量达到最大,2 d 便达到稳定期(图3).0 mg/L -口- 0.2 mg/L 0.4 mg/L -a -0.8 mg/L 1.6 mg/L -x -3.2 mg/L -*-6.4 mg/L -^-12.8 mg/Lm铂驾思图3不同N 浓度下具尾蓝隐藻、链形小环藻和伪鱼腥藻的生长曲线F i g.!^G rowt l i of Chroomonas caudate,Cyclotella catenata a n d Pseudanabaena s p. w it l i d i fere n t N co n ce n tratio n s3种藻类比生长速率对N 营养添加有很好的响应,1/(与1/线性回归方程及根据其确定的%m a 和Z 如图4所示,其中伪鱼腥藻和具尾蓝隐藻%a 较大,分别为061和0.66 d _#,而链形小环藻较小,为0.37 d _#. 伪鱼腥藻Z 最大,为2.26 mg /L ,链形小环藻Z 最小,为1.06 mg /L .茗2.40.8尸3.2(k +1.42 及2=〇.998 "腦=0.71 d _1 K s ^2.26 m g f L.伪鱼腥藻l /c /(L /mg )l /c /(L /mg )0.20.4l /c /(L /m g )0.6图4 3类生 与N 浓度的线性回归(由于伪鱼腥藻在N 浓度高于0.8 mg /L 时才开始对N 添加有较好的 ,故在N 浓度为1.6 mg /L 以上时与比生 行线性回归)Fig .4 The linear regression between specific growth rate and Nconcentration forthe three studied species (The /rowtli of Pseudanabaena sp . started to resjD onse to N addition aband the linear regression was conducted withi N concentrations above 1.6 m /L )__i _i_-oooo4321鵪f i 蠢2.3.2 P 添加的藻类生长动力学3种藻类对P 添加均有很好的响应,即培养期间藻类生物量随着P 浓度的 添增.其中具尾蓝隐藻在第12 d 达到最大 度;链形小环藻在第10 d最大度;伪腥藻在第8d最大度(图5).张鑫等:淮南采煤塌陷湖泊浮游植物优势种的营养动力学71904 m g /L —0.08 m g/L链形小环藻0.32 m g /L -〇- 0.64 m g/L_ 伪鱼腥藻246 81012时间/d246 810时间/d2 4 6时间/d图5不同P 浓度下具尾蓝隐藻、链形小环藻和伪鱼腥藻的生长曲线F i g .^G rowt I i of Chroomonas caudata # Cyclotella catenata a n d Pseudanabaena s p. wit l i d ?fere n t P co n ce n tratio n s1U 与1/u 线性回归方程及根据其确定的%B 和Z 如图6所示,其中伪鱼腥藻的%B 最大,为0.90 d \#而链形小环藻较小,为0.31 d _#.伪鱼腥藻的Z 最小,为0.015 mg /L ,链形小环藻的Z 最大,为0.035 mg /L .n y =0.050x +2.000 及2=0,986=0.51 d -1 沿=0.023 n6会42具尾蓝隐藻0 20 40 60 80 100l /c /(L /mg ) 1.50.5n y =0.017r +1.108 R 2=0.9S 6,=0.90 d "1 尤5=0.015 m g/L 伪鱼腥藻12182430l /c /(L /mg )l /c /(L /mg )图6 3种藻类比生长速率与P 浓度的线性回归Fig . 6 The linear regression between specific growthrateand P concentration forthethreestudi3讨论游植物群构的有物理、化学和生物等因子,即通常“上行效应”和“行效应”两种机制调控,在具体水环境中, 子在 生态系统中都有可能成为控制浮游植物生长、群 构组成与演替的关键因素[13—14(.本文研究4个季节3个湖泊的营养状态指数分别为52~61、56~70和49〜59,总体处 轻度一中度富 状态,在富湖泊中,游物粒径较大,特别是群体聚集性藻的生物可食性较弱,从而可致“下行效应”不足而“上行效应”更为突出[15],、光照和温度等对浮游植物群落构组成有更突出的 .调 ,3个塌陷湖泊除PXXQ 站点冬季T P 浓度外,其余各站点各季度的氮、磷浓度均超出)类水质标准,特是PXGQ 站点 有肥料的投入,特别是P 浓度大幅上升,春、、、浓度甚至超过V 类水标准.在富湖泊中,浮游物生物量的上升通常会引起光因子限制,造成光环境的浮游植物类群占据优势地位,3个湖泊的优(属)如具尾蓝隐藻、伪腥藻、小环藻以及小 等物具有对弱光环境的耐受特征[6,16—7].但由于各湖泊生态水文条件、营养盐比率、渔业活动方式与程度的不同,游植物群 构存在较大.塌陷湖泊在冬、水较隐藻、类群占据优势地位,特是对牧食较为敏感的隐藻类群,可能是由于水温偏食者未大量发育而导致其占据第1优地位(表3)[6].】、水温升高,浮游物生物 增加,适高 光环境( 游物自遮光效应所产生)的丝状 在PXGQ 和PXXQ 站点中 占据绝对优势地位.但PXPJ 站点中仍然以隐 主要优类群,该湖泊 通,对的个湖泊可能存在一定的,从而导致浮游植物群落结构现.o oC2.1.(U 01X M雲思16.6.2.8.4C 1X1X (I s /s n s fe l x )/^铂驾思720! #$% '((湖泊科学),2018,30(3)从浮游植物营养动力学角度来看,%_为当限制性底物浓度趋向无穷大时生物的生长速率,Z通常用来衡量生物物种对营养物质的亲和性,Z值越小亲和性越高,二者综合起来可以分析不同藻类在营养盐竞争中的优势地位.如果%b1=%b2,Z i<Z,那么两种藻在营养较丰富的时候可以共同生长,互不占优势,但是在营养短缺时,藻1可以迅速占优势;当%^i b^h Z i b Z,那么在营养丰富的时候藻1占优势,而营养短缺时藻2将占优势,这就是确定最大比增长率和半饱和常数的意义[1819].塌陷湖泊3个优势浮游植物种类中,Y限制下具尾蓝隐藻、链形小环藻和伪鱼腥藻的%^和Z分别为0.66d—m g/L;0.37d'L O)m g/L;0.71d'2.26m g/L;P限制下它们的%…和Z分别为0.51d—\0.023m g/L;0.31d—^O.O%,m g/L;0.90d'0.015m g/L.从中可以看出,链形小环藻比具尾蓝隐藻和伪鱼腥藻具有更强的Y亲和性,因此在Y营养相对缺乏情况下,链形小环藻对资源竞争能力更强,而在Y营养丰富的情况下,伪鱼腥藻能够形成优势,有研究表明丝状蓝藻对高浓度Y的适应性[20].同时伪鱼腥藻比具尾蓝隐藻和链形小环藻具有更强的P亲和性,因此在P营养相对缺乏的情况下,伪鱼腥藻更容易在P竞争中取得优势地位.此前相关研究表明,由于农业非点源的大量输入,淮南塌陷湖泊Y相对丰富,水体初级生产主要受P限制[$],结合实际水环境调查结果(表2)、浮游植物群落结构(表3)和各优势种营养动力学参数可知,在3个湖泊Y浓度相差不大、但存在P限制的环境条件下,伪鱼腥藻%…最大而Z值最低,对P亲和性最强,形成优势,同时耐受高温并适应低光环境[21],因而夏、秋季在PXUQ和PXXQ站点中占据优势地位.在水温相对较低的春、冬季,浮游生物生长缓慢,特别是丝状蓝藻对温度较为敏感,而隐藻对P的Z值低于链形小环藻,%h b大于链形小环藻,且水体中的Y浓度与隐藻的Z值最为接近,这些综合因素使得隐藻容易成为优势种.P X P站点与其他两个站点相比,桂藻和隐藻类群常年占优势,原因可能在于P X P站点与河流相通,有硅的输入,同时还可能与水环境条件、浮游动物和滤食性鱼类有关,具体原因需要进一步深入研究.此外,后续研究还需要综合营养、光照、温度及生物等多重因子的影响,建立相关的生态动力学模型,进一步确认并量化浮游植物群落结构演替的主要因素和动力学机制[22 23].从塌陷湖泊生态系统和营养盐管理角度上看,具尾蓝隐藻和链形小环藻蛋白质含量高,是鱼类和水产养殖动物的天然饵料,而伪鱼腥藻则是易暴发水华的典型藻种,特别是塌陷湖泊氮浓度较高,在P浓度进一步升高,加上夏季温度光照适宜的情况下,可能会导致丝状蓝藻浮游植物密度的急剧攀升引起水华,事实上在夏季P XX S和PXGQ塌陷湖泊的部分避风区,已经能见到部分丝状蓝藻的聚集,值得重点关注.湖泊的初级生产力主要受水体中Y、P浓度及二者比率的影响,此前相关研究表明,两淮塌陷湖泊初级生产主要受P限制并与湖泊水体P浓度呈良好的正相关关系[8,M],因而,要控制湖泊水华的发生,首要应控制水中P的浓度,同时Y浓度降低也可以减少丝状蓝藻的生物量,因为其对Y的亲和性也较弱.综合来看,控制水体中TY浓度在2.0 m//L、P浓度在0.1 m<L(I V类水质标准)能维持水生态环境的健康,进一步可以优化渔业活动,保持控制丝状蓝藻的同时促进渔业生产.4结论1)2014—2015年对淮南潘谢矿区3个塌陷湖泊的调查期间,观察到浮游植物共7门51属88种,其中 PXPR站点春季的第1优势种(属)为尖针杆藻,夏、秋、冬季分别为具尾蓝隐藻、小环藻和具尾蓝隐藻;PXGQ站点春、冬季第1优势种(属)为具尾蓝隐藻,夏、秋季为伪鱼腥藻;PXXQ站点春季第1优势种(属)为具尾蓝隐藻,夏、秋季为伪鱼腥藻,冬季为卵型隐藻.2)从浮游植物营养动力学角度上看,链形小环藻比具尾蓝隐藻和伪鱼腥藻具有更强的Y亲和性,因此 在Y营养相对缺乏情况下更容易在竞争中取得优势;在塌陷湖泊现阶段Y营养丰富P相对缺乏的环境条件下,伪鱼腥藻具有比具尾蓝隐藻和链形小环藻更强的P亲和性,加上丝状蓝藻的其他生态学特征,使得其易于在夏、秋季形成优势类群.结合区域营养状况和初级生产限制条件,在塌陷湖泊营养管理中P的控制和调分重要.5参考文献[ 1 ] Y i Q T, Sun P F, X ie K et al.Im p a c t o f re g io n a l w a te r c h e m istry o;the phosphorus iso th e rm a l adso rptio n o f the sedim ents张鑫等:淮南采煤塌陷湖泊浮游植物优势种的营养动力学721?three subsidence w aters o f th e H u a in a; m in e areas. 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Code fo r in v e s tig a tio n o f la ke e u tro p h ic a tio n. B e ijin g: C h in a E n v iro n m e n ta l ScienceP r e s,1990.全国富营养化调查组•湖泊富营养化调查规范•北京:中国环境科学出版社,1990.][12]Z hang ZJ ed. A c tiv a te d sliadge b io lo g and re a ctio n k in e tic s. B e ijin g: C h in a E n v iro n m e n ta l Science P re s s,1989: 355-356.[张自杰•活性污泥生物学与反应动力学•北京:中国环境科学出版社,1989: 355-356.][13]L itc h m a n E,P in to P D T,K la u s m e ie r C A ei a l. L in k in g tra its to species d iv e rs ity and c o m m u n ity stru ctu re in p h y to p la n k­ton. Hydrobiolo^yia,2010,653( 1) :15-28.[14]C e lla m are M,P in to P D T,L e ita o M et al.U sin g fu n c tio n a l approaches to stiady p h yto p la n k to n co m m u n itie s in a tem perateregio n exposed to tro p ic a l species disp e rsa l. H y d r f i f),2013,702(1):267-282.[15]K a lf f J ed. L im n o lo g y: In la n d w a te r ecosystem. B e ijin g: H ig h e r E d u c a tio n P re s s,2011: 334-335. 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关键链识别的数理方法

关键链识别的数理方法

关键链识别的数理方法Keychain recognition is an important task in computer vision and image processing, as it can be used for a variety of applications such as object recognition, tracking, and security systems. There are various mathematical methods and algorithms that can be used to recognize keychains in images and videos, and these methods have their own advantages and disadvantages.关键链识别是计算机视觉和图像处理中的重要任务,因为它可以用于各种应用,如对象识别、跟踪和安全系统。

有各种数学方法和算法可用于识别图像和视频中的关键链,这些方法各有优缺点。

One commonly used method for keychain recognition is feature-based matching, which involves identifying distinctive features of the keychain, such as its shape, color, and texture, and then matching these features to a database of known keychain features. This method can be effective for recognizing keychains in images with low to moderate levels of noise and distortion, but it may not perform well in images with high levels of noise or in videos with rapid motion.关键链识别的一种常用方法是基于特征的匹配,这涉及识别关键链的独特特征,如形状、颜色和纹理,然后将这些特征与已知关键链特征的数据库进行匹配。

《2024年垂直影像_媒介考古、银幕动力学与新媒体的语言》范文

《2024年垂直影像_媒介考古、银幕动力学与新媒体的语言》范文

《垂直影像_媒介考古、银幕动力学与新媒体的语言》篇一垂直影像_媒介考古、银幕动力学与新媒体的语言一、引言在当代社会,垂直影像已经成为一种重要的媒介形式,它不仅承载着历史的记忆,还引领着未来的趋势。

本文将从媒介考古、银幕动力学与新媒体语言三个方面进行深入探讨,试图理解垂直影像在媒介生态中的地位与价值。

二、媒介考古:垂直影像的历史溯源垂直影像,作为媒介的呈现形式,可以追溯到远古时期的壁画、雕刻以及洞穴壁画等。

这些早期的垂直影像不仅为人们提供了信息的传播途径,更记录了人类文明的历程。

随着时代的进步,摄影技术的出现为垂直影像带来了新的表达方式,而电影和电视的普及更是推动了垂直影像的广泛传播。

进入21世纪,数字技术的发展使得垂直影像的制作和传播更加便捷,同时也不断影响着人们的生活方式与观念。

三、银幕动力学:垂直影像的表现方式与功能银幕作为垂直影像的重要载体,具有独特的表现方式和功能。

银幕动力学强调了时间与空间的相互作用,为观众带来了更加立体的视觉体验。

在电影中,银幕通过叙事技巧、色彩、音乐等元素来塑造场景和情感氛围,从而传达特定的信息和意义。

垂直影像的独特表现方式使电影得以记录并反映现实世界的变迁和人们的精神世界。

此外,在影视创作中,垂直影像还能传递信息、激发思考和产生共鸣,从而达到引导公众意识和塑造社会价值观的目的。

四、新媒体语言:垂直影像的传播与互动随着新媒体的崛起,垂直影像的传播方式和互动性也发生了巨大变化。

新媒体语言强调了信息的即时性、互动性和多样性,为垂直影像的传播提供了新的途径。

在社交媒体、短视频平台等新媒体平台上,垂直影像以更加灵活的方式传播着信息,同时也为观众提供了更多的互动机会。

观众可以通过点赞、评论等方式参与到内容的创作和传播过程中,从而形成了一种新的媒介生态。

五、结论垂直影像作为媒介的一种重要形式,承载着历史的记忆和未来的趋势。

通过对媒介考古的探究,我们可以看到垂直影像的历史渊源;从银幕动力学的角度来看,其独特的表现方式和功能使得观众能够获得更加立体的视觉体验;而新媒体语言则为垂直影像的传播和互动提供了新的途径。

锆石辐射损伤定年方法研究现状

锆石辐射损伤定年方法研究现状

锆石辐射损伤定年方法研究现状徐杰【摘要】锆石辐射损伤定年作为一种新的低温定年方法,有着良好的应用前景.该方法基于锆石中U、Th元素衰变使锆石晶体结构受到放射性破坏,利用拉曼光谱法测得半高宽(FWHM)定量其结构损伤程度,同时利用锆石中U、Th元素含量获得α剂量,通过两者之间的关系去确定年龄的一种低温年代学方法.相较于其他低温年代学有着高效的优势.本文将阐述锆石拉曼光谱特征、辐射损伤退火作用以及该方法目前的应用.【期刊名称】《四川建材》【年(卷),期】2017(043)003【总页数】3页(P166-168)【关键词】锆石;低温年代学;拉曼光谱法【作者】徐杰【作者单位】西北大学地质学系,陕西西安 710069【正文语种】中文【中图分类】P575.4锆石损伤定年方法在20世纪50年代便被提出。

由于微量的U和Th放射性衰变导致锆石密度、折射率、双折射逐渐降低以及锆石晶胞的膨胀。

使得锆石的原子尺度结构逐渐破坏。

通过XRD测定的密度和晶胞属性与测定的斯里兰卡锆石测量的铀和钍含量和α剂量(当时已知年龄为570 Ma)之间系统的相关性。

观察到的两者系统关系的校准曲线可以作为用于确定辐射损伤年龄[1-4]。

原本的技术中,辐射损伤是由XRD测定,然而这并不适合在现代年代学中小样本分析。

现在可以使用拉曼光谱和SIMS质谱测量锆石抛光表面微米大小区域的辐射损伤和U和Th含量[5-8]。

本文通过目前研究以及资料总结对锆石损伤定年现状进行了分析探讨。

天然锆石放射性破坏主要是来源于锆石中U和Th自发衰变产生的α粒子事件,导致锆石晶格产生大量的点缺陷 [6-7,9]。

在对锆石拉曼图谱研究中,V3(SiO4)1008 cm-1峰最为标志(见图1),最能反映锆石结构损伤程度。

随着锆石蜕晶质化程度的增加,其特征峰的峰形变宽,而且峰位向低频偏移,尤其是V3(SiO4)峰最为敏感,能直接反映晶体结构短程有序度的降低或SiO4四面体畸变程度的增加[5]。

杨维桢铁崖体名词解释

杨维桢铁崖体名词解释

杨维桢铁崖体名词解释杨维桢铁崖体名词解释一、引言在地质学领域,杨维桢铁崖体是一种普遍存在于中国东部地区的地质构造单元。

本文将对杨维桢铁崖体进行全面评估和解释,并提供深入的理解。

二、定义与起源1. 杨维桢铁崖体的定义杨维桢铁崖体(Yangweizhen Iron Cliff)是中国东部地区一种特殊的地质结构单元,主要由夏一矿组成,是由古生代沉积岩和火山岩等多种岩石组成的。

其名称来源于中国著名地质学家杨维桢之名,他是首次发现和研究这种地质单元的学者。

2. 杨维桢铁崖体的形成和起源杨维桢铁崖体形成于古生代的构造运动和火山活动期间。

在这个过程中,岩石经历了多次变质和改造,形成了富含铁矿石和其他矿物资源的地质单元。

这一过程中,火山岩的喷发和沉积沉积产生了厚厚的岩层,随后经历了强烈的构造变形作用,从而形成了今天的杨维桢铁崖体。

三、特征和分布1. 杨维桢铁崖体的特征杨维桢铁崖体具有以下显著特征:a. 构造复杂:杨维桢铁崖体的构造非常复杂,包含了多种岩石和矿物的组合,形成了独特的地形和地貌。

b. 矿产资源丰富:杨维桢铁崖体富含大量的铁矿石和其他有价值的矿产资源,对当地经济发展具有重要意义。

c. 多样的地质现象:在杨维桢铁崖体中,可以观察到多种地质现象,如断裂、褶皱、岩层倾角等,为研究和认识地质学提供了宝贵的实例。

2. 杨维桢铁崖体的分布杨维桢铁崖体分布广泛,主要分布在中国东部的山地和丘陵地区。

其中,以杨维桢的研究地区为中心,包括山东、安徽、江苏等地,这些地区的岩石和矿产资源丰富,对于中国的工业和经济发展具有重要意义。

四、意义和应用1. 学术意义杨维桢铁崖体的发现和研究为地质学家提供了研究地质构造和岩石组成的重要案例,对于理解地球演化和构造运动具有重要意义。

杨维桢铁崖体的研究也为矿产资源的勘探和开发提供了重要的参考。

2. 经济意义杨维桢铁崖体富含大量的铁矿石和其他有价值的矿产资源,对于当地经济的发展具有重要的意义。

徐凤敏:行走在稀疏金融优化领域的先行者

徐凤敏:行走在稀疏金融优化领域的先行者

徐凤敏:行走在稀疏金融优化领域的先行者发布时间:2021-07-26T04:48:01.543Z 来源:《中国经济评论》2021年第3期作者:严迪[导读]小云文化咨询有限公司北京 100000人物介绍:徐凤敏,计算机数学博士,现任西安交通大学经济与金融学院教授、博士生导师,西安交通大学经济与金融学院金融工程系系主任;加拿大西蒙弗雷泽大学访问学者、香港理工大学访问学者、韩国首尔大学高级交换学者和客座研究员。

长期致力于大数据所涉及的统计与稀疏优化理论算法的研究和典型金融问题微观研究,主持并承担了十余项国家自然科学基金,是我国稀疏金融优化领域成就突出的知名专家。

她,传道授业,课堂上神采飞扬,书写出知识的卷轴;她,脚踏实地,潜心治学,怀着赤诚之心筑造科研之路;她,只问耕耘,但求无愧于心,孕育出桃李满园芬芳。

她,就是西安交通大学经济与金融学院的徐凤敏教授。

徐凤敏教授是稀疏金融优化领域知名专家,主要研究数据驱动的优化,包括建模和算法设计,以及如何在宏观和微观层面的实际分析中应用于经济和金融问题。

她所提出的一些原创性理论在国际会议上多次被学者提及并被广泛引用,其中一些研究成果已成功应用于金融实际问题,为推动稀疏金融优化领域的发展作出了突出贡献。

2001年,徐凤敏进入西安交通大学经济与金融学院任教,为本科生、硕士生讲授有关数学系列及金融工程系列的课程。

二十年来,她为祖国的金融行业培养和输送了一大批宝贵人才。

徐凤敏教授认为,关于稀疏金融优化的教学工作,仅仅停留在课堂教育是远远不够的,学生应该积极走出课堂,到更广阔的外部天地中,用所学理论指导实践、理论与实践相结合,才能真正做到学以致用。

为此,她作为指导老师带领学生参加了多届“美国大学生数学建模竞赛”,在竞赛中,学生们不仅能够熟练运用所学的专业知识解决实际问题,同时锻炼了研究问题、解决方案的能力及团队合作精神,可谓一举夺得。

在徐凤敏教授的悉心指导下,西安交通大学多支参赛队伍顺利完成了从建立模型、求解、验证到全英文论文撰写的全部工作,并取得了理想成绩,先后获得了2011-2012年两届数学建模竞赛荣誉奖、2013年数学建模竞赛优异奖和2013跨学科建模竞赛荣誉奖等殊荣。

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1. Introduction Latent fission tracks ( F-F' s) in minerals are annealed with increasing temperature, and the analysis of fossil FT's accumulated for geologic periods provides useful information on a rock's thermal history. Quantitative analysis of track facling on the geological time scale enables us to reliably estimate thermal histories. The fading of F T ' s is chza'acterized by the reduction of both track density and length; especially the lengths of horizontal confined tracks ( H C T ' s ; Laslett et al., 1982)
Received 5 April 1994; accepted after revision 12 January 1995
Abstract A series of laboratory annealing experiments on zircon fission tracks has been carded out under heating conditions of 3507500(2 for 10- t-103 hr (i.e. 4.5 min- ~ 40 days). Variation in the confined lengths of spontaneous fission tracks was determined using zircon grains fn)m Nisatai Dacite. The fading contours of normalized mean track length (r) on the Arrhenius diagram showed as sets of straight lines. We performed a series of model fittings, called the parallel and fanning models, in order to describe the decrease in r with increasing temperature or heating time. The lowest temperature limit of the zircon partial annealing zone (ZPAZ) was defined as r = 0.95, and the highest as r-- 0.4, which approximately corresponded to the total fading of surface tracks. Extrapolation of the results of the laboratory experiments to the geological timescale gives, for a heating duration of 106 yr, estimated values of the ZPAZ of ~ 210-320°C ( + 60°C, 2tr) with the parallel model; ~ 190-350°C ( + 50°C, 2~') with the fanning model (critical temperature, To= ~); and ~ 170-390°(2 ( _ 50°C, 2tr) with the fanning model (TO~ oo). The temperatures of the ZPAZ decrease by ~ 20°C for an annealing duration that is an order of magnitude longer. Because the estimated closure temperature of zircon fission-track analysis approximately corresponds to the middle of the ZPAZ, these results support the previously estimated closure temperature of ~ 240°C. By varying the etching time it was revealed that significant removal of a-radiation damage occurs at r ~--0 et al. / Chemical Geology (Isotope Geoscience Section) 122 (1995) 249-258
observed track density during annealing with measuring angular distribution of etched tracks. Additionally, the effect of overetching is anisotropic and variable for different crystallographic directions according to highly anisotropic etching characteristics. Yamada et al. (1993) precisely assessed this effect for reliable track length analysis. A reference framework of HCT length measurement in zircon was established, focusing on the angular distribution of length and number of HCT's (Hasebe et al., 1993). It is known that various factors control the observed and measured lengths of annealed FT' s (Laslett et al., 1982, and Gleadow, 1984; Tagami et al., 1990). Yamada et al. (1995) assessed the factors affecting the paleotemperature estimate, and recommended realistic experimental criteria for routine HCT length measurements. In order to estimate quantitatively the thermal histories using zircon FT length analysis, we here report data sets of Arrhenius plot experiments in the laboratory. Based on the experimental criteria proposed by Yamada et al. (1995), track annealing experiments were carried out at 350-750°C for 10-L103 hr (i.e. 4.5 m i n - ~ 40 days). The data were fitted by mathematical models that describe the reduction of etched length as a function of time and temperature. We used both parallel and fanning models (e.g., Laslett et al., 1987) for calculation, and estimated the temperatures of the zircon partial annealing zone (ZPAZ) for the geological time scale on the order of 106-108 yr.
Ryuji Yamada a,., Takahiro Tagami a, Susumu Nishimura a, Hisatoshi Ito b
a Department of Geology and Mineralogy, Faculty of Science, Kyoto University, Kyoto 606-01, Japan b Central Research Institute of Electric Power Industry, 1646 Abiko 270-11, Japan
* Corresponding author.
[PD]
0009-2541/95/$09.50 ~ 1995 Elsevier Science B.V. All rights reserved SSD10009 -254 ! ( 95 ) 0 0 0 0 6 - 2
offer an accurate parameter with minimum experimental biases. On the basis of both laboratory and geological annealing data, quantitative analysis of the thermal history has been achieved using observed apatite FT parameters (e.g., Green et al., 1989). In the case of zircon, however, potential difficulties have been recognized on laboratory FT annealing experiments. Gleadow (1978) found that accumulated a-radiation damage in the mineral is reduced during annealing. This annealing process accordingly increases the anisotropy in the procedure of track etching and can result in an apparent reduction of track etching efficiency. Tagami et al. (1990) successfully corrected the effects of varying etching anisotropy on
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