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A review of advanced and practical lithium battery materialsRotem Marom,*S.Francis Amalraj,Nicole Leifer,David Jacob and Doron AurbachReceived 3rd December 2010,Accepted 31st January 2011DOI:10.1039/c0jm04225kPresented herein is a discussion of the forefront in research and development of advanced electrode materials and electrolyte solutions for the next generation of lithium ion batteries.The main challenge of the ﬁeld today is in meeting the demands necessary to make the electric vehicle fully commercially viable.This requires high energy and power densities with no compromise in safety.Three families of advanced cathode materials (the limiting factor for energy density in the Li battery systems)are discussed in detail:LiMn 1.5Ni 0.5O 4high voltage spinel compounds,Li 2MnO 3–LiMO 2high capacity composite layered compounds,and LiMPO 4,where M ¼Fe,Mn.Graphite,Si,Li x TO y ,and MO (conversion reactions)are discussed as anode materials.The electrolyte is a key component that determines the ability to use high voltage cathodes and low voltage anodes in the same system.Electrode–solution interactions and passivation phenomena on both electrodes in Li-ion batteries also play signiﬁcant roles in determining stability,cycle life and safety features.This presentation is aimed at providing an overall picture of the road map necessary for the future development of advanced high energy density Li-ion batteries for EV applications.IntroductionOne of the greatest challenges of modern society is to stabilize a consistent energy supply that will meet our growing energy demands.A consideration of the facts at hand related to the energy sources on earth reveals that we are not encountering an energy crisis related to a shortage in total resources.For instancethe earth’s crust contains enough coal for the production of electricity for hundreds of years.1However the continued unbridled usage of this resource as it is currently employed may potentially bring about catastrophic climatological effects.As far as the availability of crude oil,however,it in fact appears that we are already beyond ‘peak’production.2As a result,increasing oil shortages in the near future seem inevitable.Therefore it is of critical importance to considerably decrease our use of oil for propulsion by developing effective electric vehicles (EVs).EV applications require high energy density energy storage devices that can enable a reasonable driving range betweenDepartment of Chemistry,Bar-Ilan University,Ramat-Gan,52900,Israel;Web:http://www.ch.biu.ac.il/people/aurbach.E-mail:rotem.marom@live.biu.ac.il;aurbach@mail.biu.ac.ilRotem MaromRotem Marom received her BS degree in organic chemistry (2005)and MS degree in poly-mer chemistry (2007)from Bar-Ilan University,Ramat Gan,Israel.She started a PhD in electrochemistry under the supervision of Prof.D.Aurbach in 2010.She is currently con-ducting research on a variety of lithium ion battery materials for electric vehicles,with a focus on electrolyte solutions,salts andadditives.S :Francis AmalrajFrancis Amalraj hails from Tamil Nadu,India.He received his MSc in Applied Chemistry from Anna University.He then carried out his doctoral studies at National Chemical Laboratory,Pune and obtained his PhD in Chemistry from Pune University (2008).He is currently a postdoctoral fellow in Prof.Doron Aurbach’s group at Bar-Ilan University,Israel.His current research interest focuses on the synthesis,electrochemical and transport properties of high ener-getic electrode materials for energy conversion and storage systems.Dynamic Article Links CJournal ofMaterials ChemistryCite this:DOI:10.1039/c0jm04225k /materialsFEATURE ARTICLED o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225KView Onlinecharges and maintain acceptable speeds.3Other important requirements are high power density and acceptable safety features.The energy storage ﬁeld faces a second critical chal-lenge:namely,the development of rechargeable systems for load leveling applications (e.g.storing solar and wind energy,and reducing the massive wasted electricity from conventional fossil fuel combustion plants).4Here the main requirements are a very prolonged cycle life,components (i.e.,relevant elements)abun-dant in high quantities in the earth’s crust,and environmentally friendly systems.Since it is not clear whether Li-ion battery technology can contribute signiﬁcantly to this application,battery-centered solutions for this application are not discussedherein.In fact,even for electrical propulsion,the non-petroleum power source with the highest energy density is the H 2/O 2fuel cell (FC).5However,despite impressive developments in recent years in the ﬁeld,there are intrinsic problems related to electrocatalysis in the FCs and the storage of hydrogen 6that will need many years of R&D to solve.Hence,for the foreseeable future,rechargeable batteries appear to be the most practically viable power source for EVs.Among the available battery technologies to date,only Li-ion batteries may possess the power and energy densities necessary for EV applications.The commonly used Li-ion batteries that power almost all portable electronic equipment today are comprised of a graphite anode and a LiCoO 2cathode (3.6V system)and can reach a practical energy density of 150W h kg À1in single cells.This battery technology is not very useful for EV application due to its limited cycle life (especially at elevated temperatures)and prob-lematic safety features (especially for large,multi-cell modules).7While there are ongoing developments in the hybrid EV ﬁeld,including practical ones in which only part of the propulsion of the car is driven by an electrical motor and batteries,8the main goal of the battery community is to be able to develop full EV applications.This necessitates the development of Li-ion batteries with much higher energy densities compared to the practical state-of-the-art.The biggest challenge is that Li-ion batteries are complicated devices whose components never reach thermodynamic stability.The surface chemistry that occurs within these systems is very complicated,as described brieﬂy below,and continues to be the main factor that determines their performance.9Nicole Leifer Nicole Leifer received a BS degree in chemistry from MIT in 1998.After teaching high school chemistry and physics for several years at Stuyvesant High School in New York City,she began work towards her PhD in solid state physics from the City University of New York Grad-uate Center.Her research con-sisted primarily of employing solid state NMR in the study of lithium ion electrode materialsand electrode surfacephenomena with Prof.Green-baum at Hunter College andProf.Grey at Stony Brook University.After completing her PhD she joined Prof.Doron Aurbach for a postdoctorate at Bar-Ilan University to continue work in lithium ion battery research.There she continues her work in using NMR to study lithium materials in addition to new forays into carbon materials’research for super-capacitor applications with a focus on enhancement of electro-chemical performance through the incorporation of carbonnanotubes.David Jacob David Jacob earned a BSc from Amravati University in 1998,an MSc from Pune University in 2000,and completed his PhD at Bar-Ilan University in 2007under the tutelage of Professor Aharon Gedanken.As part of his PhD research,he developed novel methods of synthesizing metal ﬂuoride nano-material structures in ionic liquids.Upon ﬁnishing his PhD he joined Prof.Doron Aurbach’s lithium ionbattery group at Bar-Ilan in2007as a post-doctorate and during that time developed newformulations of electrolyte solutions for Li-ion batteries.He has a great interest in nanotechnology and as of 2011,has become the CEO of IsraZion Ltd.,a company dedicated to the manufacturing of novelnano-materials.Doron Aurbach Dr Doron Aurbach is a full Professor in the Department of Chemistry at Bar-Ilan Univer-sity (BIU)in Ramat Gan,Israel and a senate member at BIU since 1996.He chaired the chemistry department there during the years 2001–2005.He is also the chairman of the Israeli Labs Accreditation Authority.He founded the elec-trochemistry group at BIU at the end of 1985.His groupconducts research in thefollowing ﬁelds:Li ion batteries for electric vehicles and for otherportable uses (new cathodes,anodes,electrolyte solutions,elec-trodes–solution interactions,practical systems),rechargeable magnesium batteries,electronically conducting polymers,super-capacitors,engineering of new carbonaceous materials,develop-ment of devices for storage and conversion of sustainable energy (solar,wind)sensors and water desalination.The group currently collaborates with several prominent research groups in Europe and the US and with several commercial companies in Israel and abroad.He is also a fellow of the ECS and ISE as well as an associate editor of Electrochemical and Solid State Letters and the Journal of Solid State Electrochemistry.Prof.Aurbach has more than 350journals publications.D o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225KAll electrodes,excluding 1.5V systems such as LiTiO x anodes,are surface-ﬁlm controlled (SFC)systems.At the anode side,all conventional electrolyte systems can be reduced in the presence of Li ions below 1.5V,thus forming insoluble Li-ion salts that comprise a passivating surface layer of particles referred to as the solid electrolyte interphase (SEI).10The cathode side is less trivial.Alkyl carbonates can be oxidized at potentials below 4V.11These reactions are inhibited on the passivated aluminium current collectors (Al CC)and on the composite cathodes.There is a rich surface chemistry on the cathode surface as well.In their lithiated state,nucleophilic oxygen anions in the surface layer of the cathode particles attack electrophilic RO(CO)OR solvents,forming different combinations of surface components (e.g.ROCO 2Li,ROCO 2M,ROLi,ROM etc.)depending on the electrolytes used.12The polymerization of solvent molecules such as EC by cationic stimulation results in the formation of poly-carbonates.13The dissolution of transition metal cations forms surface inactive Li x MO y phases.14Their precipitation on the anode side destroys the passivation of the negative electrodes.15Red-ox reactions with solution species form inactive LiMO y with the transition metal M at a lower oxidation state.14LiMO y compounds are spontaneously delithiated in air due to reactions with CO 2.16Acid–base reactions occur in the LiPF 6solutions (trace HF,water)that are commonly used in Li-ion batteries.Finally,LiCoO 2itself has a rich surface chemistry that inﬂuences its performance:4LiCo III O 2 !Co IV O 2þCo II Co III 2O 4þ2Li 2O !4HF4LiF þ2H 2O Co III compounds oxidize alkyl carbonates;CO 2is one of the products,Co III /Co II /Co 2+dissolution.14Interestingly,this process seems to be self-limiting,as the presence of Co 2+ions in solution itself stabilizes the LiCoO 2electrodes,17However,Co metal in turn appears to deposit on the negative electrodes,destroying their passivation.Hence the performance of many types of electrodes depends on their surface chemistry.Unfortunately surface studies provide more ambiguous results than bulk studies,therefore there are still many open questions related to the surface chemistry of Li-ion battery systems.It is for these reasons that proper R&D of advanced materials for Li-ion batteries has to include bulk structural and perfor-mance studies,electrode–solution interactions,and possible reﬂections between the anode and cathode.These studies require the use of the most advanced electrochemical,18structural (XRD,HR microscopy),spectroscopic and surface sensitive analytical techniques (SS NMR,19FTIR,20XPS,21Raman,22X-ray based spectroscopies 23).This presentation provides a review of the forefront of the study of advanced materials—electrolyte systems,current collectors,anode materials,and ﬁnally advanced cathodes materials used in Li-ion batteries,with the emphasis on contributions from the authors’group.ExperimentalMany of the materials reviewed were studied in this laboratory,therefore the experimental details have been provided as follows.The LiMO 2compounds studied were prepared via self-combus-tion reactions (SCRs).24Li[MnNiCo]O 2and Li 2MnO 3$Li/MnNiCo]O 2materials were produced in nano-andsubmicrometric particles both produced by SCR with different annealing stages (700 C for 1hour in air,900 C or 1000 C for 22hours in air,respectively).LiMn 1.5Ni 0.5O 4spinel particles were also synthesized using SCR.Li 4T 5O 12nanoparticles were obtained from NEI Inc.,USA.Graphitic material was obtained from Superior Graphite (USA),Timcal (Switzerland),and Conoco-Philips.LiMn 0.8Fe 0.2PO 4was obtained from HPL Switzerland.Standard electrolyte solutions (alkyl carbonates/LiPF 6),ready to use,were obtained from UBE,Japan.Ionic liquids were obtained from Merck KGaA (Germany and Toyo Gosie Ltd.,(Japan)).The surface chemistry of the various electrodes was charac-terized by the following techniques:Fourier transform infrared (FTIR)spectroscopy using a Magna 860Spectrometer from Nicolet Inc.,placed in a homemade glove box purged with H 2O and CO 2(Balson Inc.air puriﬁcation system)and carried out in diffuse reﬂectance mode;high-resolution transmission electron microscopy (HR-TEM)and scanning electron microscopy (SEM),using a JEOL-JEM-2011(200kV)and JEOL-JSM-7000F electron microscopes,respectively,both equipped with an energy dispersive X-ray microanalysis system from Oxford Inc.;X-ray photoelectron spectroscopy (XPS)using an HX Axis spectrom-eter from Kratos,Inc.(England)with monochromic Al K a (1486.6eV)X-ray beam radiation;solid state 7Li magic angle spinning (MAS)NMR performed at 194.34MHz on a Bruker Avance 500MHz spectrometer in 3.2mm rotors at spinning speeds of 18–22kHz;single pulse and rotor synchronized Hahn echo sequences were used,and the spectra were referenced to 1M LiCl at 0ppm;MicroRaman spectroscopy with a spectrometerfrom Jobin-Yvon Inc.,France.We also used M €ossbauer spec-troscopy for studying the stability of LiMPO 4compounds (conventional constant-acceleration spectrometer,room temperature,50mC:57Co:Rh source,the absorbers were put in Perspex holders.In situ AFM measurements were carried out using the system described in ref.25.The following electrochemical measurements were posite electrodes were prepared by spreading slurries comprising the active mass,carbon powder and poly-vinylidene diﬂuoride (PVdF)binder (ratio of 75%:15%:10%by weight,mixed into N -methyl pyrrolidone (NMP),and deposited onto aluminium foil current collectors,followed by drying in a vacuum oven.The average load was around 2.5mg active mass per cm 2.These electrodes were tested in two-electrode,coin-type cells (Model 2032from NRC Canada)with Li foil serving as the counter electrode,and various electrolyte puter-ized multi-channel battery analyzers from Maccor Inc.(USA)and Arbin Inc.were used for galvanostatic measurements (voltage vs.time/capacity,measured at constant currents).Results and discussionOur road map for materials developmentFig.1indicates a suggested road map for the direction of Li-ion research.The axes are voltage and capacity,and a variety of electrode materials are marked therein according to their respective values.As is clear,the main limiting factor is the cathode material (in voltage and capacity).The electrode mate-rials currently used in today’s practical batteries allow forD o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225Ka nominal voltage of below 4V.The lower limit of the electro-chemical window of the currently used electrolyte solutions (alkyl carbonates/LiPF 6)is approximately 1.5V vs.Li 26(see later discussion about the passivation phenomena that allow for the operation of lower voltage electrodes,such as Li and Li–graphite).The anodic limit of the electrochemical window of the alkyl carbonate/LiPF 6solutions has not been speciﬁcally determined but practical accepted values are between 4.2and 5V vs.Li 26(see further discussion).With some systems which will be discussed later,meta-stability up to 4.9V can be achieved in these standard electrolyte solutions.Electrolyte solutionsThe anodic stability limits of electrolyte solutions for Li-ion batteries (and those of polar aprotic solutions in general)demand ongoing research in this subﬁeld as well.It is hard to deﬁne the onset of oxidation reactions of nonaqueous electrolyte solutions because these strongly depend on the level of purity,the presence of contaminants,and the types of electrodes used.Alkyl carbonates are still the solutions of choice with little competition (except by ionic liquids,as discussed below)because of the high oxidation state of their central carbon (+4).Within this class of compounds EC and DMC have the highest anodic stability,due to their small alkyl groups.An additional beneﬁt is that,as discussed above,all kinds of negative electrodes,Li,Li–graphite,Li–Si,etc.,develop excellent passivation in these solutions at low potentials.The potentiodynamic behavior of polar aprotic solutions based on alkyl carbonates and inert electrodes (Pt,glassy carbon,Au)shows an impressive anodic stability and an irreversible cathodic wave whose onset is $1.5vs.Li,which does not appear in consequent cycles due to passivation of the anode surface bythe SEI.The onset of these oxidation reactions is not well deﬁned (>4/5V vs.Li).An important discovery was the fact that in the presence of Li salts,EC,one of the most reactive alkyl carbonates (in terms of reduction),forms a variety of semi-organic Li-con-taining salts that serve as passivation agents on Li,Li–carbon,Li–Si,and inert metal electrodes polarized to low potentials.Fig.2and Scheme 1indicates the most signiﬁcant reduction schemes for EC,as elucidated through spectroscopic measure-ments (FTIR,XPS,NMR,Raman).27–29It is important to note (as reﬂected in Scheme 1)that the nature of the Li salts present greatly affects the electrode surface chemistry.When the pres-ence of the salt does not induce the formation of acidic species in solutions (e.g.,LiClO 4,LiN(SO 2CF 3)2),alkyl carbonates are reduced to ROCO 2Li and ROLi compounds,as presented in Fig. 2.In LiPF 6solutions acidic species are formed:LiPF 6decomposes thermally to LiF and PF 5.The latter moiety is a Lewis acid which further reacts with any protic contaminants (e.g.unavoidably present traces of water)to form HF.The presence of such acidic species in solution strongly affects the surface chemistry in two ways.One way is that PF 5interactswithFig.1The road map for R&D of new electrode materials,compared to today’s state-of-the-art.The y and x axes are voltage and speciﬁc capacity,respectively.Fig.2A schematic presentation of the CV behavior of inert (Pt)elec-trodes in various families of polar aprotic solvents with Li salts.26D o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225Kthe carbonyl group and channels the reduction process of EC to form ethylene di-alkoxide species along with more complicated alkoxy compounds such as binary and tertiary ethers,rather than Li-ethylene dicarbonates (see schemes in Fig.2);the other way is that HF reacts with ROLi and ROCO 2Li to form ROH,ROCO 2H (which further decomposes to ROH and CO 2),and surface LiF.Other species formed from the reduction of EC are Li-oxalate and moieties with Li–C and C–F bonds (see Scheme 1).27–31Efforts have been made to enhance the formation of the passivation layer (on graphite electrodes in particular)in the presence of these solutions through the use of surface-active additives such as vinylene carbonate (VC)and lithium bi-oxalato borate (LiBOB).27At this point there are hundreds of publica-tions and patents on various passivating agents,particularly for graphite electrodes;their further discussion is beyond the scope of this paper.Readers may instead be referred to the excellent review by Xu 32on this subject.Ionic liquids (ILs)have excellent qualities that could render them very relevant for use in advanced Li-ion batteries,including high anodic stability,low volatility and low ﬂammability.Their main drawbacks are their high viscosities,problems in wetting particle pores in composite structures,and low ionic conductivity at low temperatures.Recent years have seen increasing efforts to test ILs as solvents or additives in Li-ion battery systems.33Fig.3shows the cyclic voltammetric response (Pt working electrodes)of imidazolium-,piperidinium-,and pyrrolidinium-based ILs with N(SO 2CF 3)2Àanions containing LiN(SO 2CF 3)2salt.34This ﬁgure reﬂects the very wide electrochemical window and impressive anodic stability (>5V)of piperidium-and pyr-rolidium-based ILs.Imidazolium-based IL solutions have a much lower cathodic stability than the above cyclic quaternary ammonium cation-based IL solutions,as demonstrated in Fig.3.The cyclic voltammograms of several common electrode mate-rials measured in IL-based solutions are also included in the ﬁgure.It is clearly demonstrated that the Li,Li–Si,LiCoO 2,andLiMn 1.5Ni 0.5O 4electrodes behave reversibly in piperidium-and pyrrolidium-based ILs with N(SO 2CF 3)2Àand LiN(SO 2CF 3)2salts.This ﬁgure demonstrates the main advantage of the above IL systems:namely,the wide electrochemical window with exceptionally high anodic stability.It was demonstrated that aluminium electrodes are fully passivated in solutions based on derivatives of pyrrolidium with a N(SO 2CF 3)2Àanion and LiN(SO 2CF 3)2.35Hence,in contrast to alkyl carbonate-based solutions in which LiN(SO 2CF 3)2has limited usefulness as a salt due to the poor passivation of aluminium in its solutions in the above IL-based systems,the use of N(SO 2CF 3)2Àas the anion doesn’t limit their anodic stability at all.In fact it was possible to demonstrate prototype graphite/LiMn 1.5Ni 0.5O 4and Li/L-iMn 1.5Ni 0.5O 4cells operating even at 60 C insolutionsScheme 1A reaction scheme for all possible reduction paths of EC that form passivating surface species (detected by FTIR,XPS,Raman,and SSNMR 28–31,49).Fig.3Steady-state CV response of a Pt electrode in three IL solutions,as indicated.(See structure formulae presented therein.)The CV presentations include insets of steady-state CVs of four electrodes,as indicated:Li,Li–Si,LiCoO 2,and LiMn 1.5Ni 0.5O 4.34D o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225Kcomprising alkyl piperidium-N(SO2CF3)2as the IL solvent and Li(SO2CF3)2as the electrolyte.34Challenges remain in as far as the use of these IL-based solutions with graphite electrodes.22Fig.4shows the typical steady state of the CV of graphite electrodes in the IL without Li salts.The response in this graph reﬂects the reversible behavior of these electrodes which involves the insertion of the IL cations into the graphite lattice and their subsequent reduction at very low potentials.However when the IL contains Li salt,the nature of the reduction processes drastically changes.It was recently found that in the presence of Li ions the N(SO2CF3)2Àanion is reduced to insoluble ionic compounds such as LiF,LiCF3, LiSO2CF3,Li2S2O4etc.,which passivate graphite electrodes to different extents,depending on their morphology(Fig.4).22 Fig.4b shows a typical SEM image of a natural graphite(NG) particle with a schematic view of its edge planes.Fig.4c shows theﬁrst CVs of composite electrodes comprising NG particles in the Li(SO2CF3)2/IL solution.These voltammograms reﬂect an irreversible cathodic wave at theﬁrst cycle that belongs to the reduction and passivation processes and their highly reversible repeated Li insertion into the electrodes comprising NG. Reversible capacities close to the theoretical ones have been measured.Fig.4d and e reﬂect the structure and behavior of synthetic graphiteﬂakes.The edge planes of these particles are assumed to be much rougher than those of the NG particles,and so their passivation in the same IL solutions is not reached easily. Their voltammetric response reﬂects the co-insertion of the IL cations(peaks at0.5V vs.Li)together with Li insertion at the lower potentials(<0.3V vs.Li).Passivation of this type of graphite is obtained gradually upon repeated cycling(Fig.4e), and the steady-state capacity that can be obtained is much lower than the theoretical one(372mA h gÀ1).Hence it seems that using graphite particles with suitable morphologies can enable their highly reversible and stable operation in cyclic ammonium-based ILs.This would make it possible to operate high voltage Li-ion batteries even at elevated temperatures(e.g. 4.7–4.8V graphite/LiMn1.5Ni0.5O4cells).34 The main challenge in thisﬁeld is to demonstrate the reasonable performance of cells with IL-based electrolytes at high rates and low temperatures.To this end,the use of different blends of ILs may lead to future breakthroughs.Current collectorsThe current collectors used in Li-ion systems for the cathodes can also affect the anodic stability of the electrolyte solutions.Many common metals will dissolve in aprotic solutions in the potential ranges used with advanced cathode materials(up to5V vs.Li). Inert metals such as Pt and Au are also irrelevant due to cost considerations.Aluminium,however,is both abundantand Fig.4A collection of data related to the behavior of graphite electrodes in butyl,methyl piperidinium IL solutions.22(a)The behavior of natural graphite electrodes in pure IL without Li salt(steady-state CV is presented).(b)The schematic morphology and a SEM image of natural graphite(NG)ﬂakes.(c)The CV response(3ﬁrst consecutive cycles)of NG electrodes in IL/0.5lithium triﬂuoromethanesulfonimide(LiTFSI)solution.(d and e)Same as(b and c)but for synthetic graphiteﬂakes.DownloadedbyBeijingUniversityofChemicalTechnologyon24February211Publishedon23February211onhttp://pubs.rsc.org|doi:1.139/CJM4225Kcheap and functions very well as a current collector due to its excellent passivation properties which allow it a high anodic stability.The question remains as to what extent Al surfaces can maintain the stability required for advanced cathode materials (up to 5V vs.Li),especially at elevated temperatures.Fig.5presents the potentiodynamic response of Al electrodes in various EC–DMC solutions,considered the alkyl carbonate solvent mixture with the highest anodic stability,at 30and 60 C.37The inset to this picture shows several images in which it is demonstrated that Al surfaces are indeed active and develop unique morphologies in the various solutions due to their obvious anodic processes in solutions,some of which lead to their effective passivation.The electrolyte used has a critical impact on the anodic stability of the Al.In general,LiPF 6solutions demonstrate the highest stability even at elevated temperatures due to the formation of surface AlF 3and even Al(PF 6)3.Al CCs in EC–DMC/LiPF 6solutions provide the highest anodic stability possible for conventional electrode/solution systems.This was demonstrated for Li/LiMn 1.5Ni 0.5O 4spinel (4.8V)cells,even at 60 C.36This was also conﬁrmed using bare Al electrodes polarized up to 5V at 60 C;the anodic currents were seen to decay to negligible values due to passivation,mostly by surface AlF 3.37Passivation can also be reached in Li(SO 2CF 3),LiClO 4and LiBOB solutions (Fig.5).Above 4V (vs.Li),the formation of a successful passivation layer on Al CCs is highly dependent on the electrolyte formula used.The anodic stability of EC–DMC/LiPF 6solutions and Al current collectors may be further enhanced by the use of additives,but a review of additives in itself deserves an article of its own and for this readers are again referred to the review by Xu.32When discussing the topic of current collectors for Li ion battery electrodes,it is important to note the highly innovative work on (particularly anodic)current collectors by Taberna et al.on nano-architectured Cu CCs 47and Hu et al.who assembled CCs based on carbon nano-tubes for ﬂexible paper-like batteries,38both of whom demonstrated suberb rate capabilities.39AnodesThe anode section in Fig.1indicates four of the most promising groups of materials whose Li-ion chemistry is elaborated as follows:1.Carbonaceous materials/graphite:Li ++e À+C 6#LiC 62.Sn and Si-based alloys and composites:40,41Si(Sn)+x Li ++x e À#Li x Si(Sn),X max ¼4.4.3.Metal oxides (i.e.conversion reactions):nano-MO +2Li ++2e À#nano-MO +Li 2O(in a composite structure).424.Li x TiO y electrodes (most importantly,the Li 4Ti 5O 12spinel structure).43Li 4Ti 5O 12+x Li ++x e À#Li 4+x Ti 5O 12(where x is between 2and 3).Conversion reactions,while they demonstrate capacities much higher than that of graphite,are,practically speaking,not very well-suited for use as anodes in Li-ion batteries as they generally take place below the thermodynamic limit of most developed electrolyte solutions.42In addition,as the reactions require a nanostructuring of the materials,their stability at elevated temperatures will necessarily be an issue because of the higher reactivity (due to the 1000-fold increase in surface area).As per the published research on this topic,only a limited meta-stability has been demonstrated.Practically speaking,it does not seem likely that Li batteries comprising nano-MO anodes will ever reach the prolonged cycle life and stability required for EV applications.Tin and silicon behave similarly upon alloying with Li,with similar stoichiometries and >300%volume changes upon lith-iation,44but the latter remain more popular,as Si is much more abundant than Sn,and Li–Si electrodes indicate a 4-fold higher capacity.The main approaches for attaining a workable revers-ibility in the Si(Sn)–Li alloying reactions have been through the use of both nanoparticles (e.g.,a Si–C nanocomposites 45)and composite structures (Si/Sn–M1–M2inter-metalliccompounds 44),both of which can better accommodate these huge volume changes.The type of binder used in composite electrodes containing Si particles is very important.Extensive work has been conducted to determine suitable binders for these systems that can improve the stability and cycle life of composite silicon electrodes.46As the practical usage of these systems for EV applications is far from maturity,these electrodes are not dis-cussed in depth in this paper.However it is important to note that there have been several recent demonstrations of how silica wires and carpets of Si nano-rods can act as much improved anode materials for Li battery systems in that they can serveasFig.5The potentiodynamic behavior of Al electrodes (current density measured vs.E during linear potential scanning)in various solutions at 30and 60 C,as indicated.The inset shows SEM micrographs of passivated Al surfaces by the anodic polarization to 5V in the solutions indicated therein.37D o w n l o a d e d b y B e i j i n g U n i v e r s i t y o f C h e m i c a l T e c h n o l o g y o n 24 F e b r u a r y 2011P u b l i s h e d o n 23 F e b r u a r y 2011 o n h t t p ://p u b s .r s c .o r g | d o i :10.1039/C 0J M 04225K。

动物蛋白源免疫调节肽的研究进展

梁泳仪，王宏，白卫东，等. 动物蛋白源免疫调节肽的研究进展[J]. 食品工业科技，2023，44（18）：492−501. doi: 10.13386/j.issn1002-0306.2022120041LIANG Yongyi, WANG Hong, BAI Weidong, et al. Advances in Immunomodulatory Peptides of Animal Protein Origin[J]. Science and Technology of Food Industry, 2023, 44(18): 492−501. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2022120041· 专题综述 ·动物蛋白源免疫调节肽的研究进展梁泳仪，王　宏*，白卫东，肖更生，曾晓房*（仲恺农业工程学院，广东省岭南特色食品科学与技术重点实验室，农业农村部岭南特色食品绿色加工与智能制造重点实验室，轻工食品学院，广东广州 510225）摘　要：动物界中蕴藏着丰富且宝贵的活性肽资源，其中动物蛋白源免疫调节肽具有高安全性、低过敏性、成本低等优势，在人类营养健康和疾病防治中发挥着不可替代的作用。

其免疫调节活性作用与氨基酸组成、序列及肽链长度等多种因素有关。

近年来，围绕动物蛋白源相关的免疫活性成分及功能研究已取得了较多新的进展，但鲜有团队对其免疫调节肽进行详细介绍并总结。

本文综述了近年来动物蛋白源免疫调节肽的构效关系和作用机制，总结了不同动物蛋白来源的免疫调节肽的特点，并对动物蛋白源免疫调节肽的未来研究和发展趋势进行展望，以期为动物蛋白源免疫调节肽的进一步研究与开发提供参考。

关键词：免疫调节肽，动物蛋白，构效关系，分子机制本文网刊:中图分类号：TS201.4 文献标识码：A 文章编号：1002−0306（2023）18−0492−10DOI: 10.13386/j.issn1002-0306.2022120041Advances in Immunomodulatory Peptides of Animal Protein OriginLIANG Yongyi ，WANG Hong *，BAI Weidong ，XIAO Gengsheng ，ZENG Xiaofang *（Zhongkai University of Agriculture and Engineering, Guangdong Provincial Key Laboratory of Lingnan Specialty Food Science and Technology, Key Laboratory of Green Processing and Intelligent Manufacturing of Lingnan Specialty Food,Ministry of Agriculture and Rural Affairs, School of Light Industry and Food Technology, Guangzhou 510225, China ）Abstract ：Animals have long been a rich and invaluable source of bioactive peptides, of which animal protein-derived immunomodulatory peptides have the advantages of high safety, low allergenicity and low cost, and play an irreplaceable role in human health and disease prevention. The immunomodulatory activities of peptides are related to amino acid composition, sequence and peptide chain length. In recent years, many new advances have been made around the study of immunomodulatory components and bioactivities related to animal protein sources, but few teams have introduced and summarized the immunomodulatory peptides in detail. In this review, the structure-effect relationships and mechanism of action of animal protein-derived immunomodulatory peptides in recent years are reviewed, the characteristics of immunomodulatory peptides from different animal protein sources are summarized, and the future research and development trend of animal protein-derived immunomodulatory peptides are prospected, which might contribute to further research and development of animal protein-derived immunomodulatory peptides.Key words ：immunomodulatory peptide ；animal protein ；structure-effect relationship ；molecular mechanisms免疫调节肽是一类具有免疫调节作用的生物活性肽，其作用包括但不限于促进/抑制淋巴细胞分化成熟、调节巨噬细胞的吞噬功能、转移免疫信息、调节细胞分泌因子等[1−2]。

基于深度学习的雷达降雨临近预报及洪水预报

第34卷第5期2023年9月㊀㊀水科学进展ADVANCES IN WATER SCIENCEVol.34,No.5Sep.2023DOI:10.14042/ki.32.1309.2023.05.003基于深度学习的雷达降雨临近预报及洪水预报李建柱,李磊菁,冯㊀平,唐若宜(天津大学水利工程仿真与安全国家重点实验室,天津㊀300350)摘要:为探究深度学习的雷达降雨临近预报在流域洪水预报中的适用性,采用U-Net㊁嵌入注意力门的Attention-Unet 和添加转换器的多级注意力TransAtt-Unet 开展雷达降雨临近预报,将预报降雨作为HEC-HMS 水文模型的输入,对柳林实验流域进行洪水预报㊂结果表明:1h 预见期时,Attention-Unet 对短时强降雨预报结果较好,TransAtt-Unet 预报降雨模拟的洪峰流量和径流量相对误差小于20%,各深度学习模型对量级较大的降雨和洪水预报精度较高;2h 预见期的预报降雨强度㊁降雨总量㊁洪峰流量和径流量存在显著低估,U-Net 能取得相对较好的降雨预报结果㊂基于深度学习的1h 预见期雷达降雨临近预报及洪水预报可为流域防洪减灾提供科学依据㊂关键词:雷达降雨临近预报;降雨定量估计;深度学习;洪水预报;柳林实验流域中图分类号:P333㊀㊀㊀文献标志码:A㊀㊀㊀文章编号:1001-6791(2023)05-0673-12收稿日期:2023-05-19;网络出版日期:2023-09-19网络出版地址:https :ʊ /urlid /32.1309.P.20230918.1718.002基金项目:国家自然科学基金资助项目(52279022)作者简介:李建柱(1981 ),男,河北沧州人,教授,博士,主要从事水文水资源方面研究㊂E-mail:lijianzhu@近年来,极端降雨事件导致洪涝灾害频发,对洪水预报精度和时效性的要求越来越高[1]㊂准确的降雨预报是洪水预报的关键,可为防洪减灾工作提供重要的科学依据[2]㊂传统的洪水预报主要以地面雨量站实测降雨输入水文模型,导致洪水预报的有效预见期短,且雨量站实测降雨无法反映其空间分布特性[3]㊂天气雷达具有高时空分辨率㊁高精度和可靠性等特点[4]㊂将雷达降雨临近预报结果作为水文模型的输入进行洪水预报,能在一定程度上延长洪水预见期[5],是水文预报领域的主要发展趋势,但降雨临近预报是尚未解决的重要科学难题[6]㊂以光流法㊁质心跟踪法㊁交叉相关法为主的传统雷达回波外推方法[7],能在较短预见期内对缓慢变化的回波过程取得较好的外推效果,但无法准确描述迅速变化的回波过程[8]㊂近年来大量研究将深度学习的方法引入到水文气象领域,并取得显著成效[9-10]㊂Zhang 等[6]提出一种具有预测误差优化的神经网络模型NowcastNet,基于中国和美国的雷达资料开展降雨预报,显著提高了极端强降雨的预报精度㊂Ritvanen 等[11]提出一种基于卷积神经网络U-Net 的拉格朗日模型,改善了强降雨的临近预报效果㊂作为一种应用广泛的基础模型,U-Net 在临近预报领域得到推广[12]㊂Han 等[13]将U-Net 模型用于雷达回波外推,并与循环神经网络的TrajGRU 和交叉相关法的预报结果进行对比,表明U-Net 模型在时空序列预测问题的适用性㊂预报降雨的重要用途之一是作为水文模型的输入进行洪水预报[14-15]㊂Heuvelink 等[16]使用确定性和概率性方法进行降雨预报,并将结果作为WALRUS 水文模型的输入进行流量预报,在小流域取得较好的预报效果;Nguyen 等[17]将雷达回波外推和数值模式天气预报结合,提高了降雨预报精度,并指出降雨预报与分布式水文模型结合使用的优势;包红军等[18]构建了临近降雨集合预报的中小河流洪水预报模型,延长了洪水预报的预见期㊂但目前使用深度学习的方式开展雷达降雨临近预报,从而进行洪水预报的精度还有待提高,尤其是在半干旱半湿润地区的小流域㊂U-Net 结构简单,可根据目标灵活调整和添加模块,为实现更加精确的雷达降雨临近预报和洪水预报提供了更多可能㊂因此,本研究采用深度学习的U-Net,并尝试使用嵌入注意力门的Attention-Unet(简写为Att-674㊀水科学进展第34卷㊀Unet)和添加转换器的多级注意力TransAtt-Unet进行柳林实验流域典型降雨过程的1h和2h预见期雷达回波外推,利用动态雷达反射率因子和降雨强度关系计算外推回波对应的逐小时降雨,作为半分布式水文模型HEC-HMS的输入进行洪水预报,对比分析预报降雨与雨量站实测降雨模拟的洪水精度差异,探讨基于深度学习的雷达降雨临近预报在小流域洪水预报中的适用性㊂1㊀研究区域与数据1.1㊀流域概况选择河北省邢台市内丘县柳林实验流域为研究区㊂如图1所示,流域出口位于114ʎ21ᶄE㊁37ʎ17ᶄN,布设有柳林水文站进行水位和流量观测㊂流域面积为57.4km2,主河道长13.2km,流域坡度为30.9ɢ㊂地处半干旱半湿润气候区,季节变化分明,径流的年内和年际分配不均,降雨多发生在6 9月,多年平均降水量为594.5mm,多年平均径流深为80.7mm㊂雷达资料来源于中国新一代多普勒天气雷达监测网河北省石家庄市的Z9311站㊂雷达位于114ʎ42ᶄ50ᵡE㊁38ʎ21ᶄ00ᵡN,采用VP21体扫模式,扫描半径为230km,时间分辨率为6min,能够完成9个不同仰角的扫描㊂柳林实验流域在距离雷达120km范围内,可保证雷达回波数据的质量㊂图1㊀柳林实验流域位置和雷达监测范围Fig.1Location of Liulin experimental watershed and radar monitoring range1.2㊀雷达数据预处理将2018 2020年降雨时段的雷达基数据,经过编码转换㊁杂波抑制㊁衰减订正㊁地物遮挡订正㊁坐标转换后,形成反射率混合扫描数据图,用于深度学习模型的训练㊂由于柳林实验流域面积较小,将回波图裁剪至流域周围128行128列的范围(113ʎ36ᶄ36ᵡE㊁37ʎ30ᶄ36ᵡN到114ʎ53ᶄ24ᵡE㊁36ʎ47ᶄ24ᵡN)㊂以训练集中20180521场次降雨为例,图2为经过预处理与未处理回波对比图,经过质量控制后的回波剔除了杂波干扰并显著减少波束遮挡,具有较高的可靠性㊂训练集和验证集共包含20000帧回波图,按照8ʒ2的比例划分进行模型训练和验证㊂测试集选取2012年㊁2016年和2021年的4场典型降雨过程对应的雷达数据㊂1.3㊀典型降雨洪水过程降雨洪水资料来源于河北省邢台水文勘测研究中心㊂洪水资料为柳林水文站汛期实测逐小时流量数据,㊀第5期李建柱,等:基于深度学习的雷达降雨临近预报及洪水预报675㊀图2㊀20180521场次降雨未处理与预处理后回波对比Fig.2Comparison of unprocessed and preprocessed echoes of20180521case暴雨资料为流域内菩萨岭㊁神头㊁任庄㊁安上和柳林5个雨量站汛期逐小时雨量,筛选出与雷达回波时段对应的典型降雨洪水过程对降雨和洪水预报精度进行评价㊂降雨洪水信息如表1所示㊂由于20211006场次降雨过程在汛期后发生,柳林水文站未对其洪水过程进行观测㊂表1㊀典型降雨洪水过程信息Table1Information of typical rainfall and flood processes降水场次降水量/mm最大小时雨量/mm降雨时长/h洪水径流深/mm洪峰流量/(m3㊃s-1) 2012072675.958.45 5.147.020160719251.942.718129.2368.020210721149.426.92929.993.32021100625.58.25//2㊀研究方法2.1㊀雷达回波外推的深度学习模型2.1.1㊀U-NetU-Net网络由4层编码器-解码器组成,是一种卷积神经网络㊂如图3(a)所示,网络的左边是编码器,应用最大池化和双重卷积来减小图像大小和加倍特征映射的数量㊂编码器之后的右侧为解码器,通过双线性插值进行上采样操作,使特征图大小增加1倍㊂每层编码器和解码器之间通过1个跳跃连接保存来自较浅层的细尺度信息㊂完成上述采样操作之后,模型通过一个1ˑ1的卷积,输出代表网络预测值的单个特征图㊂2.1.2㊀Att-UnetAtt-Unet(图3(a))在U-Net的解码器前添加注意力门,以此过滤跳跃连接传播的特征,再将编码器的特征与解码器中相应的特征进行拼接,有效抑制无关区域的激活,减少编码器中无关信息的跳跃连接,达到改善预测效果的目的[19]㊂本研究将Att-Unet模型调整为时间序列预测模型进行回波外推㊂676㊀水科学进展第34卷㊀图3㊀U-Net㊁Att-Unet㊁TransAtt-Unet和TSA㊁GSA模块结构Fig.3Structure of U-Net,Attention-Unet,TransAtt-Unet,TSA and GSA modules2.1.3㊀TransAtt-UnetTransAtt-Unet将多层次引导注意和多尺度跳跃连接联合嵌入U-Net,如图3(b)㊂将变换器自注意力(TSA)和全局空间注意力(GSA)嵌入到网络中,同时在解码器中使用多尺度跳跃连接来聚合不同语义尺度的特征,从而有效减少卷积层叠加和连续采样操作造成的细节损失㊂如图3(c)和图3(d)所示,TSA将特征嵌入到Q㊁K㊁V3个矩阵中,在Q和K的转置之间采用Softmax函数进行归一化运算,形成注意力图,再与V 矩阵相乘得到注意力权重㊂GSA对特征进行卷积转置映射为W㊁M㊁N,对M㊁N采用Softmax函数进行归一化运算得到位置注意力信息,再与W相乘得到位置特征㊂在解码器部分采用残差多尺度跳跃连接的方式[20],输入特征图通过双线性插值向上采样到输出的分辨率,然后与输出特征图进行级联,作为后续块的输入㊂2.2㊀深度学习模型训练1h外推数据集取前1h间隔6min共10帧回波图(反射率因子),预测后1h共10帧回波图(2h外推为前20帧预测后20帧)㊂深度学习模型基于Pytorch环境,初始学习率设置为0.001,批处理大小设置为8,损失函数采用均方根误差(E MS)[13],在NVIDIA Geforce RTX3050上采用Adam优化器训练200个轮次㊂当损失函数在4个周期内没有增加时,学习率调节器将学习率自动减小10%㊂采用二元评价指标命中率(Proba-bility of detection,D PO)㊁虚警率(False alarm ratio,R FA)㊁临界成功指数(Critical success index,I CS)和准确率(Accuracy,A)进行雷达回波外推精度的评价[21]㊂2.3㊀雷达降雨临近预报多普勒天气雷达采用Z R关系描述雷达反射率因子(Z)和降雨强度(R)的幂指数关系[22]㊂中国的多普勒雷达普遍采用Z=aR b(a=300,b=1.4)进行降雨定量估计,但仅适用于平均情况㊂基于实测资料动态调整的Z R关系,可以实现更加精确的降雨估计[23]㊂殷志远等[24]采用4种不同的Z R关系开展雷达降雨定量估计,并将结果用于水文模拟,表明动态Z R关系的降雨定量估计精度最高,洪水模拟效果最好㊂动态Z R关系建立在逐小时快速更新资料的基础上,通过动态调节参数a和b,使逐小时雷达估测降雨与对应㊀第5期李建柱,等:基于深度学习的雷达降雨临近预报及洪水预报677㊀的雨量站观测降雨的最优判别函数δ达到最小[23],从而确定适用于逐小时雷达定量降雨估计的多组Z R关系参数㊂为保证参数a和b的取值合理,限定a和b数值调节范围分别为[150.00,400.00]㊁[0.80, 2.40],调整间隔分别为10和0.05㊂经过上述步骤最终确定出每场降雨过程的动态Z R关系参数如图4所示㊂采用相关系数(Correlation coefficient,C C)㊁平均偏差(Mean bias,B M)和平均绝对误差(Mean absolute error,E MA)进行降雨预报精度评价[14]㊂图4㊀动态Z R关系参数Fig.4Parameters of dynamic Z R relationship2.4㊀水文模型李建柱等[25]研究了地形数据源和分辨率对柳林实验流域洪水模拟精度的影响,结果表明,基于无人机三维倾斜摄影构建的1m分辨率DEM能反映流域真实地形的变化,在此基础上构建的HEC-HMS模型能较好地模拟流域洪水过程㊂本研究采用作者基于无人机三维倾斜摄影构建的1m分辨率HEC-HMS模型,将雷达降雨临近预报结果作为HEC-HMS水文模型的输入,进行柳林实验流域洪水预报㊂采用洪峰流量相对误差(E RP)㊁径流量相对误差(E RV)㊁峰现时差(ΔT)和纳什效率系数(E NS)进行洪水预报精度评价[25]㊂3㊀结果及分析3.1㊀回波外推结果分析以反射率20dBZ和30dBZ为阈值计算二元评价指标㊂1h回波外推评价结果见表2,Att-Unet对20120726场次降雨的回波外推效果相对较好,注意力门加强了Att-Unet对强回波的识别和外推效果,同时抑制弱回波或杂波产生的干扰,但对弱回波或中等回波的外推效果较差;TransAtt-Unet采用的多尺度跳跃连接和注意力机制使模型能综合不同尺度的图像特征,提高模型精度和稳定性,因此,该模型对于持续时间较长㊁降雨过程变化丰富的20160719场次回波过程取得了较好的外推效果;20210721和20211006场次降雨的过程回波总体偏弱,各模型的1h预见期回波外推精度差异并不显著㊂2h回波外推评价结果见表3,U-Net 模型对30dBZ阈值的回波外推效果优于其他模型,其原因是雷达回波外推需要预测每个像素的精确值;Att-Unet和TransAtt-Unet所采用的注意力门或者多尺度跳跃连接结构仅增强局部特征的学习,而忽略随时间动态变化的信息,因此导致预测时效性的不足㊂U-Net模型尽管结构简单,但以往研究表明其在时间序列预测中具有一定适用性[26],对不同等级回波信息具有一定的泛化能力[27],因此,尽管U-Net的1h预见期回波外推效果略差于添加注意力机制的模型,但能在更长预见期的回波外推中保持相对较好的效果㊂总体来看, 3种模型对中等强度回波外推效果均好于强回波,1h预见期回波外推效果好于2h预见期㊂国内外研究主要依靠天气雷达外推实现1h预见期降雨预报[5]㊂与传统的雷达外推方法相比,深度学习678㊀水科学进展第34卷㊀对回波和降水的演变趋势具有更好的预报效果,更适用于剧烈变化的降雨过程[28]㊂曹伟华等[29]使用基于U-Net网络搭建的RainNet模型开展雷达降雨临近预报,并与交叉相关的外推结果进行对比,指出了深度学习模型对降雨消亡过程的时空演变趋势和强度变化范围具有更好的预报效果,而交叉相关法更适合于稳定降雨的预报㊂本研究预报的4场典型降雨过程,除20211006场次持续时间短㊁降雨强度较小外,其余场次降雨过程变化较为剧烈,回波过程变化较为迅速,因此,采用深度学习的方法进行雷达降雨临近预报更为合适㊂表2㊀1h回波外推结果评价指标值Table2Evaluation index value of1h echo extrapolation results降雨场次模型D PO R FA I CS A20dBZ30dBZ20dBZ30dBZ20dBZ30dBZ20dBZ30dBZ20120726U-Net0.830.370.070.190.780.330.820.56 Att-Unet0.820.520.120.170.760.440.800.65 TransAtt-Unet0.750.350.060.170.720.340.770.5820160719U-Net0.710.370.140.440.610.210.610.31 Att-Unet0.790.460.150.450.680.240.690.33 TransAtt-Unet0.870.470.140.490.750.240.750.3120210721U-Net0.740.420.140.210.670.360.810.71 Att-Unet0.700.490.260.440.540.280.640.51 TransAtt-Unet0.720.520.260.460.550.290.650.5320211006U-Net0.450.240.560.760.190.090.740.64 Att-Unet0.440.210.550.790.240.080.750.61 TransAtt-Unet0.430.280.560.720.210.090.690.63表3㊀2h回波外推结果评价指标值Table3Evaluation index value of2h echo extrapolation results降雨场次模型D PO R FA I CS A20dBZ30dBZ20dBZ30dBZ20dBZ30dBZ20dBZ30dBZ20120726U-Net0.660.370.140.160.600.350.640.63 Att-Unet0.620.180.140.170.590.180.650.48 TransAtt-Unet0.660.200.110.130.590.200.630.5120160719U-Net0.590.200.420.630.380.120.430.47 Att-Unet0.480.120.440.640.310.070.370.47 TransAtt-Unet0.570.150.360.600.410.100.420.4820210721U-Net0.690.480.140.330.620.330.770.62 Att-Unet0.600.360.250.390.460.220.590.51 TransAtt-Unet0.650.380.290.460.480.220.570.4820211006U-Net0.500.170.480.770.320.080.670.58 Att-Unet0.420.180.670.810.210.020.600.54 TransAtt-Unet0.410.170.610.800.200.040.640.52㊀第5期李建柱,等:基于深度学习的雷达降雨临近预报及洪水预报679㊀3.2㊀降雨预报精度分析利用动态Z R关系计算各降雨场次真实回波和外推回波的逐小时降雨,精度和相关性评价指标见表4㊂20160719㊁20210721和20211006场次真实回波的反演降雨与实际降雨有较高的相关性,但20120726场次真实回波反演降雨与实际降雨的相关性较弱,但该场次回波外推取得较高的技能评分,其原因可能是2012年Z9311雷达为单偏振雷达,所采集的原始回波数据存在一定的数值和发生时间的系统误差,且该场降雨过程变化迅速,导致预报降雨与实际产生误差㊂TransAtt-Unet对20160719和20210721场次降雨在1h预见期内具有较小的误差,Att-Unet在20160719场次降雨的预报中具有最高的相关性㊂3种模型对20211006场次降雨预报效果差别并不显著,其原因是该场降雨强度较小,深度学习模型对此类降雨预报性能较接近㊂在2h 预见期降雨预报中,U-Net模型的降雨预报效果优于其他模型,这与雷达回波外推结果相对应,表明了U-Net在较长预见期降雨预报中的适用性㊂表4㊀降雨相关性评价指标值Table4Rainfall correlation evaluation index value降雨场次模型E MA/mm C C B M/mm1h2h1h2h1h2h20120726U-Net22.5722.49-0.28-0.41-1.96-2.32 Att-Unet23.9921.28-0.22-0.32-0.66-3.08 TransAtt-Unet24.2022.66-0.28-0.32-1.76-2.66真实回波14.780.31 2.9320160719U-Net8.868.840.480.420.22-6.21 Att-Unet8.7010.710.590.170.25-7.05 TransAtt-Unet7.8810.520.580.13-0.74-6.77真实回波 6.020.77-0.0620210721U-Net 4.57 4.780.520.380.31-1.90 Att-Unet 4.85 5.580.320.19-0.93-1.31 TransAtt-Unet 4.40 5.650.470.21-0.22-1.29真实回波 3.090.67-0.4120211006U-Net 2.81 2.650.840.61-2.81-2.39 Att-Unet 2.61 2.790.790.63-2.61-2.79 TransAtt-Unet 2.48 2.620.820.65-2.48-2.62真实回波 1.670.88-1.67㊀㊀预报降雨过程如图5所示㊂3种模型在1h预见期时,预报的20120726场次降雨峰值与实际较为一致,但出现1h时差;对20160719和20210721场次降雨过程预报结果出现部分异常值,这与回波外推过程较大的虚警率有关,但总体上能反映降雨过程变化和雨强峰值;20211006场次降雨则存在少量低估,但能预报出该场降雨峰值出现的时间,这与动态Z R算法对较弱降雨的系统性低估有关㊂2h预见期降雨可以一定程度预报降雨过程的变化,但对各场降雨的峰值存在显著低估㊂目前,小流域降雨临近预报效果普遍较差㊂Heuvelink等[16]采用拉格朗日持续性方法在一个40km2的680㊀水科学进展第34卷㊀流域上对一场强降雨进行预报,产生了50%相对误差,发现面积越小的流域对过程变化迅速的降雨越容易产生误报;石毅[30]采用Farneback光流法和ConvLSTM在柳林实验流域进行降雨预报,结果表明光流法对回波演变的敏感性相对较低,ConvLSTM对强回波存在显著的均化趋势,导致1h预见期强降雨存在严重的低估㊂本研究采用的深度学习方法,在1h预见期内对不同类型的降雨均取得相对较好的回波外推效果,且能较准确的预报出强降雨峰值和变化过程,尽管2h预见期的预报精度相对较差,但能预报出降雨变化过程㊂预报结果存在的误差与定量降雨估计方法的系统误差和小流域上有限的雷达回波信息相关㊂动态Z R关系在定量降雨估计中具有相对较高的精度,但在降雨预报的业务化应用中仍然具有优化的空间,如Mihulet等[31]使用机器学习的方法改善了定量降雨估计的效果㊂另外,由于流域面积较小,随着预见期的延长降雨发生的实际位置也许出现在雷达图之外,使得深度学习的方法对剧烈变化的降雨产生较大的误差,Heuvelink等[16]也指出面积越小的流域对降雨发生的位置敏感性越高㊂图5㊀预报逐小时降雨过程Fig.5Forecasted hourly rainfall process3.3㊀洪水预报精度分析表5为洪水预报精度评价结果㊂3场实测降雨模拟的洪峰流量均小于实测洪峰流量,但E NS均达到了0.7以上㊂预报降雨模拟的20120726和20210721场次峰量较小的洪水,E NS均小于0.3,但20120726场次洪水1h预见期径流量相对误差小于20%,20210721场次洪水的洪峰流量预报效果也好于实测降雨模拟结果㊂对于20160719场次峰量较大的洪水,1h预见期预报的洪水E NS均能达到0.7以上且预报洪峰流量相对误差均小于20%,满足预报的精度要求㊂2h预见期洪水预报效果显著变差,洪峰流量和径流量的预报也存在较大误差㊂1h预见期时,TransAtt-Unet对于3场洪水的预报洪峰流量和径流量相对误差均小于20%,且20160719场次洪水E NS达0.78;Att-Unet则较准确地预报出20210721场次洪水的洪峰流量,相对误差仅为-0.9%㊂由于2h预见期预报的降水量存在显著低估,使得预报洪峰流量显著小于实测值,但U-Net模型对3场洪水预报的E NS为3个深度学习模型的最优值,且预报的20160719场次洪水E NS达0.52㊂㊀第5期李建柱,等:基于深度学习的雷达降雨临近预报及洪水预报681㊀表5㊀洪水预报精度评价结果Table5Accuracy evaluation of forecasted floods洪水场次模型预见期Q S/(m3㊃s-1)E RP/%V S/mm E RV/%ΔT/h E NS20120726U-Net1h31.3-33.4 4.4-13.610.23 2h19.2-59.2 4.7-8.010.16Att-Unet1h40.3-24.5 5.68.810.06 2h17.8-62.1 3.9-43.630.08TransAtt-Unet1h38.0-19.2 5.3 2.210.23 2h19.0-59.6 4.3-17.110.15实测降雨模拟36.7-21.97.0537.200.7220160719U-Net1h372.4 1.2162.525.810.76 2h198.4-46.189.3-30.930.52Att-Unet1h407.310.7165.928.410.77 2h185.3-49.779.3-38.640.34TransAtt-Unet1h354.9-3.6154.819.910.78 2h191.3-48.183.9-35.030.37实测降雨模拟343.3-6.7167.729.810.8320210721U-Net1h123.232.033.010.400.25 2h32.3-65.47.7-74.300.14Att-Unet1h92.5-0.917.9-40.110.04 2h41.6-55.411.6-61.31-0.09TransAtt-Unet1h101.08.325.7-14.000.19 2h57.0-38.912.8-57.210.02实测降雨模拟76.2-18.327.7-7.300.79㊀㊀预报洪水过程线如图6所示㊂3种模型1h预见期洪水变化过程与实际较为一致,预报的20120726场次洪水峰现时间和洪水涨落时间较实际滞后1h;20160719场次预报洪水与实测降雨模拟的峰现时间均较实际滞后1h,预报洪峰与实际较为接近,但径流量存在一定的高估;对于20210721场次洪水预报,U-Net预报的洪峰流量较实际偏大,Att-Unet预报的峰现时间较实际滞后1h,TransAtt-Unet的预报结果与实际更为接近,3种模型均能预报出该场洪水的涨落过程㊂深度学习的方法对于剧烈变化的降雨引发的洪水,1h预见期的预报洪水E NS较低,但能较好地预报出洪水的变化过程和洪峰流量,对量级较大的洪水能取得较高的E NS,且能在准确预报洪水变化过程的基础上,较准确地预报出洪峰流量㊁径流量和峰现时间㊂2h预见期降雨虽然可以预报出洪峰形成过程,但对洪峰流量和径流量存在显著低估㊂糜佳伟等[32]在梅溪流域(面积约956km2)进行降雨预报和洪水预报,指出1h预见期降雨预报结果能满足中小流域洪水预报需求㊂本研究在降雨径流响应时间更快的柳林实验流域进行洪水预报,尽管预报洪水E NS较小,但能在1h预见期对不同类型降雨引发的洪水取得较为准确的洪峰流量和径流量预报效果,预报的20160719场次大洪水的洪峰流量和径流量相对误差小于实测降雨模拟洪水结果,因此,1h预见期洪水预报效果具有一定的准确性,为流域的防洪减灾工作争取了更长的时间㊂未来可在更多流域开展雷达降雨临近预报和洪水预报研究,以验证本文采用的深度学习方法在其他流域的适用性㊂682㊀水科学进展第34卷㊀图6㊀模拟和预报洪水过程线Fig.6Simulated and forecasted flood hydrographs4㊀结㊀㊀论采用深度学习的U-Net㊁Att-Unet和TransAtt-Unet进行雷达回波外推,通过动态雷达反射率因子和降雨强度关系实现雷达降雨临近预报,将降雨预报的结果输入HEC-HMS水文模型对柳林实验流域典型洪水过程进行预报,得到以下主要结论:(1)1h预见期时Att-Unet对强回波过程外推效果较好,TransAtt-Unet对变化更丰富的回波过程外推效果较好;2h预见期时U-Net外推效果更稳定㊂(2)深度学习模型在1h预见期对短时强降雨存在时间上的误差,对持续时间较长的降雨存在少量预报异常值,但均能较准确地预报降雨强度和过程;2h预见期降雨存在显著低估和较大误差㊂(3)3种模型的1h预见期预报的洪水能反映实际变化过程,TransAtt-Unet预报的洪峰流量和径流量误差更小,Att-Unet能对部分场次洪水取得较准确的洪峰预报效果㊂U-Net在2h预见期洪水预报效果精度最高㊂参考文献:[1]雍斌,张建云,王国庆.黄河源区水文预报的关键科学问题[J].水科学进展,2023,34(2):159-171.(YONG B, ZHANG J Y,WANG G Q.Key scientific issues of hydrological forecast in the headwater area of Yellow River[J].Advances in Water Science,2023,34(2):159-171.(in Chinese))[2]金君良,舒章康,陈敏,等.基于数值天气预报产品的气象水文耦合径流预报[J].水科学进展,2019,30(3):316-325.(JIN J L,SHU Z K,CHEN M,et al.Meteo-hydrological coupled runoff forecasting based on numerical weather prediction products[J].Advances in Water Science,2019,30(3):316-325.(in Chinese))[3]IMHOFF R O,BRAUER C C,van HEERINGEN K J,et rge-sample evaluation of radar rainfall nowcasting for flood early warning[J].Water Resources Research,2022,58(3):e2021WR031591.[4]IMHOFF R O,de CRUZ L,DEWETTINCK W,et al.Scale-dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open-source pysteps library[J].Quarterly Journal of the Royal Meteorological Society,2023,149(753):㊀第5期李建柱,等:基于深度学习的雷达降雨临近预报及洪水预报683㊀1335-1364.[5]刘佳,邱庆泰,李传哲,等.降水临近预报及其在水文预报中的应用研究进展[J].水科学进展,2020,31(1):129-142.(LIU J,QIU Q T,LI C Z,et al.Advances of precipitation nowcasting and its application in hydrological forecasting[J]. Advances in Water Science,2020,31(1):129-142.(in Chinese))[6]ZHANG Y C,LONG M S,CHEN K Y,et al.Skilful nowcasting of extreme precipitation with NowcastNet[J].Nature,2023, 619(7970):526-532.[7]SOKOL Z,SZTURC J,ORELLANA-ALVEAR J,et al.The role of weather radar in rainfall estimation and its application in mete-orological and hydrological modelling:a review[J].Remote Sensing,2021,13(3):351.[8]HAN L,ZHAO Y Y,CHEN H N,et al.Advancing radar nowcasting through deep transfer learning[J].IEEE Transactions on Geoscience and Remote Sensing,2022,60:1-9.[9]BI K F,XIE L X,ZHANG H H,et al.Accurate medium-range global weather forecasting with3D neural networks[J].Nature, 2023,619(7970):533-538.[10]李步,田富强,李钰坤,等.融合气象要素时空特征的深度学习水文模型[J].水科学进展,2022,33(6):904-913.(LI B,TIAN F Q,LI Y K,et al.Development of a spatiotemporal deep-learning-based hydrological model[J].Advances in Water Science,2022,33(6):904-913.(in Chinese))[11]RITVANEN J,HARNIST B,ALDANA M,et al.Advection-free convolutional neural network for convective rainfall nowcasting[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2023,16:1654-1667. [12]AYZEL G,SCHEFFER T,HEISTERMANN M.RainNet v1.0:a convolutional neural network for radar-based precipitation now-casting[J].Geoscientific Model Development,2020,13(6):2631-2644.[13]HAN L,LIANG H,CHEN H N,et al.Convective precipitation nowcasting using U-net model[J].IEEE Transactions on Geo-science and Remote Sensing,2022,60:1-8.[14]熊立华,刘成凯,陈石磊,等.遥感降水资料后处理研究综述[J].水科学进展,2021,32(4):627-637.(XIONG LH,LIU C K,CHEN S L,et al.Review of post-processing research for remote-sensing precipitation products[J].Advances in Water Science,2021,32(4):627-637.(in Chinese))[15]刘家宏,梅超,刘宏伟,等.特大城市外洪内涝灾害链联防联控关键科学技术问题[J].水科学进展,2023,34(2):172-181.(LIU J H,MEI C,LIU H W,et al.Key scientific and technological issues of joint prevention and control of river flood and urban waterlogging disaster chain in megacities[J].Advances in Water Science,2023,34(2):172-181.(in Chi-nese))[16]HEUVELINK D,BERENGUER M,BRAUER C C,et al.Hydrological application of radar rainfall nowcasting in the Netherlands[J].Environment International,2020,136:105431.[17]NGUYEN H M,BAE D H.An approach for improving the capability of a coupled meteorological and hydrological model for rain-fall and flood forecasts[J].Journal of Hydrology,2019,577:124014.[18]包红军,曹勇,曹爽,等.基于短时临近降水集合预报的中小河流洪水预报研究[J].河海大学学报(自然科学版),2021,49(3):197-203.(BAO H J,CAO Y,CAO S,et al.Flood forecasting of small and medium-sized rivers based on short-term nowcasting and ensemble precipitation forecasts[J].Journal of Hohai University(Natural Sciences),2021,49(3): 197-203.(in Chinese))[19]GAO Y B,GUAN J P,ZHANG F H,et al.Attention-unet-based near-real-time precipitation estimation from Fengyun-4A satel-lite imageries[J].Remote Sensing,2022,14(12):2925.[20]FANG J,YANG C,SHI Y T,et al.External attention based TransUNet and label expansion strategy for crack detection[J].IEEE Transactions on Intelligent Transportation Systems,2022,23(10):19054-19063.[21]TREBING K,STA CZYK T,MEHRKANOON S.SmaAt-UNet:precipitation nowcasting using a small attention-UNet architec-ture[J].Pattern Recognition Letters,2021,145:178-186.[22]ZOU H B,WU S S,TIAN M X.Radar quantitative precipitation estimation based on the gated recurrent unit neural network andecho-top data[J].Advances in Atmospheric Sciences,2023,40(6):1043-1057.[23]GOU Y B,CHEN H N,CHANDRASEKAR V.A dynamic approach to quantitative precipitation estimation using multiradar mul-tigauge network[J].IEEE Transactions on Geoscience and Remote Sensing,2020,58(9):6376-6390.。

general structure analysis system

general structure analysis systemGeneral Structure Analysis System（GSAS）是一款用于结构分析和晶体学研究的计算机软件。

它最初由Robert B. Von Dreele和Brian H. Toby于1976年首次开发，并由Argonne National Laboratory继续维护和更新。

GSAS的主要功能是通过处理粉末XRD，单晶衍射，中子衍射等类型数据，进行结构精修。

随着Windows的普及，DOS控制对一般用户而言变得不友好。

因此2001年，B.H. Toby在GSAS基础上推出了用户交互界面的EXPGUI软件。

EXPGUI通过鼠标和键盘即可控制参数，使用起来非常方便，此外，软件所提供的画图功能也可实时追踪精修进度，因此受到学者们广泛好评。

如需更多关于General Structure Analysis System（GSAS）的详细信息，可以访问Argonne National Laboratory官网获取。

GSAS（General Structure Analysis System）是一款广泛使用的晶体结构分析软件，主要用于处理粉末X射线衍射（XRD）和中子衍射等类型的数据。

GSAS具有以下主要功能和特点：1.精修晶体结构：GSAS通过最小化实验观测数据与理论模拟数据的差异，可以对晶体结构进行精修和优化。

这包括晶胞参数、原子位置、占位等参数的调整。

2.数据处理：GSAS可以处理各种类型的数据，包括粉末XRD、中子衍射、单晶X射线衍射等。

它还可以进行数据的平滑处理、背景扣除、指标化等操作。

3.模型构建：GSAS提供了多种模型构建工具，可以根据已知的晶体结构信息手动构建模型，也可以通过程序自动生成模型。

4.图形界面：GSAS提供了直观的用户界面，使用户可以方便地进行数据导入、处理和精修。

此外，GSAS还提供了实时图形显示功能，可以在精修过程中观察数据的差异和变化。

GSA词条注释

GSA词条注释Version 2.1, 2018数据递交 (2)实验 (2)实验基本信息 (2)文库信息 (4)测序反应 (6)测序反应基本信息 (6)测序反应数据信息 (7)GSA Submission 数据递交*Alias 别名最终系统搜索或显示的GSA名称* Data Released选择在指定日期发布数据，日期格式为（yyyy-mm-dd）----------------------------------------------------------------------------------------------------------------------Experiments 实验Meta Information 实验基本信息* Platform测序平台测序平台以及测序仪型号*Alias 实验别名最终系统搜索或显示的Experiment名称*Title 标题名称可以用来在搜索或显示中调用实验记录的短文本*Project accession 所属项目序列号用于建立与BioProject间的关联关系* Sample accession 所属样本序列号用于建立与Bio Sample间的关联关系* Library Construction/Experiment design实验设计和策略用于填写您的实验设计和策略的详细信息，可包括杂交和亲和捕获试剂选择等细节Library 文库信息用于描述文库正在进行测序的材料的来源和材料可能对测序结果产生影响的任何处理Library name 文库名文库的名称*Strategy 策略文库的测序技术和策略* Source样本来源文库的实验材料来源类型*Selection 实验方式选择是否使用了任何方法来选择和/或富集被测序的材料*Layout 文库布局测序片段读取配置相关信息*Insert size (bp)插入片段长度Nominal size (bp)接头长度Nominal standard deviation (bp)接头标准偏差----------------------------------------------------------------------------------------------------------------------Run 测序反应General Information 测序反应基本信息* Alias 测序反应别名最终系统搜索或显示的Run名称* Run data file type 数据类型关于提交序列数据的支持格式，我们建议提交格式列表如下：Data Blocks 测序反应数据信息Fastq format (as an example)FASTQ是一种存储了生物序列（通常是核酸序列）以及相应的质量评价的文本格式。

3D 生物打印负载转化生长因子 β3 的软骨复合支架说明书

Chinese Journal of Tissue Engineering Research ｜Vol 25｜No.34｜December 2021｜54453D 生物打印负载转化生长因子β3的软骨复合支架杨振1，2，李浩1，2，付力伟1，2，高仓健1，2，姜双鹏2，王福鑫2，苑志国2，孙志强1，2，查康康1，2，1，22222文题释义：3D 生物打印：通过精准控制生物材料、种子细胞、生长因子在整体3D 结构中的位置、组合与互相作用，使之具有生物活性，并能实现与目标组织或生物器官接近相同，甚至更优越的功能。

转化生长因子β3：作为关节软骨组织形成的重要调节因子，可以促进干细胞迁移和成软骨分化，增强软骨损伤的修复，是一种理想的干细胞招募和促分化因子。

摘要背景：通过募集内源性干细胞原位再生软骨损伤的治疗策略，是未来软骨组织工程研究的新方向。

目的：构建既能募集干细胞又能促进其黏附和增殖，且有利于新生组织成熟的组织工程软骨复合支架。

方法：将脱细胞软骨细胞外基质(extracellular matrix ，ECM)与甲基丙烯酸酯化明胶(methacrylated gelatin ，GelMA)混合配制光敏性生物墨水，利用3D 生物打印技术分别制备单纯聚己内酯[poly(Ɛ-caprolactone)，PCL]支架、PCL/GelMA/ECM 支架。

将转化生长因子β3(transforming growth factor β3，TGF-β3)负载于生物墨水中制备PCL/GelMA/ECM/TGF-β3支架，检测其缓释性能。

从形态学、组织学、生物化学、生物力学等角度评价PCL/GelMA/ECM 支架的物理化学性质。

利用CCK-8法检测PCL/GelMA/ECM 支架的细胞毒性。

将脂肪间充质干细胞接种于PCL/GelMA/ECM 支架上，1，4，7 d 后，共聚焦显微镜下观察细胞活性，扫描电镜观察细胞黏附。

输电线路杆塔空气间隙三维可视化管理系统

输电线路杆塔空气间隙三维可视化管理系统许焱1，郭宁1，张辉1，苗堃1，李超1，刘亚文2*（1.国网河南省电力公司济源供电公司，河南济源459000；2.武汉大学遥感信息工程学院，湖北武汉430079）摘要：在Web GIS 框架下构建了真三维场景的防风偏参数杆塔空气间隙管理系统，提出了兼顾数据量和表现力的无人机摄影测量输电线路建模方案，保证了三维场景的精细度与可量测性，并设计了合理的系统多源数据组织方式及数据浏览、查询、分析等功能。

实践表明，该系统能够实现在真实三维场景下，对杆塔空气间隙的查看、浏览与分析，为输电线路防风偏提供有效的分析平台。

关键词：杆塔空气间隙；可视化管理系统；输电线路点云模型中图分类号：P208文献标志码：B文章编号：1672-4623（2022）04-0163-05doi:10.3969/j.issn.1672-4623.2022.04.035Transmission Line Tower-line Air Gap Management SystemBased on 3D Visualization SceneXU Yan 1,GUO Ning 1,ZHANG Hui 1,MIAO Kun 1,LI Chao 1,LIU Yawen 2(1.State Grid Henan Jiyuan Electric Power Supply Company,Jiyuan 459000,China;2.School of Remote Sensingand Information Engineering,Wuhan University,Wuhan 430079,China)Abstract:The tower-line air gap management system with real 3D scene based on Web GIS was constructed.This paper presented a transmis-sion line modeling scheme on UA V photogrammetry that ensures 3D scene precision and measurability.A reasonable multi-source data organiza-tion and data browsing,query and analysis functions were designed for this management system.The practice shows that this management sys-tem can achieve tower-line air gap query,browse and analysis in real 3D scene,and provide a reliable analysis platform for transmission line windage yaw prevention.Key words:tower-line air gap,management system on 3D visualization scene,transmission line point model随着通信技术、网络技术的广泛应用，结合Web GIS 和虚拟建模技术的输电线路管理系统成为主流，如文献[1]将三维仿真场景同日常输电线路管理结合起来，实现电网企业智能化的运行和管理。

asa芯片测序原理

asa芯片测序原理
SASA测序是一种新兴的测序技术，它可以通过产生可以用于遗传分析的数据来实现基因组分析。

它利用可编程芯片技术进行介导的聚合酶链式反应(PCR)的测序。

SASA测序的基本原理是将特定的基因序列特异性聚合酶(例如，Taq聚合酶)放到特定的位置(i.e.,位点)上，然后聚合酶根据基因序列特异性催化该序列特定部分上的核苷酸合成活性，形成可以被电流检测器检测到的产物。

SASA测序技术利用可编程芯片技术，使每个位点都有唯一的 DNA 序列，使PCR更加可控，同时，该技术可以同时测序多种DNA多聚体来实现高通量的测序。

在以芯片作为基础的SASA测序中，首先，芯片上的每个位置，即每个点位上有一个特定的基因序列。

然后，将需要进行测序的DNA引物按照芯片上基因序列的特异性进行灌注，并与加入的现代DNA模板和Taq DNA 聚合解聚分子共同结合反应，形成一系列特定位点上的PCR反应成品，通过电流检测器逐个测序，实现基因组分析。

通过芯片技术实现高通量、高精度的基因组分析，SASA测序受到广泛关注。

相比于传统的测序技术，SASA测序拥有更高的灵敏度、更低的错误率、更低的试剂消耗等优点，可以实现更加快速、经济、准确的测序，从而在基因组研究和临床检测等方面产生广泛的应用。

论文的参考文献标准模版

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Near-optimal sparse Fourier representations via sampling[P]. Proceedings of the Annual ACM Symposium on Theory of Computing.Montreal，Que.，Canada: Association for Computing Machinery，2002:152-161.[107] A.C.Gilbert，S.Muthukrishnan，M.J.Strauss. Improved time bounds for neat-optimal sparse Fourier representation[P]. Proceedings of SPIE，Waveles XI，Belingham WA: International Society for Optical Engineering，2005，5914:1-15.[108] A.C.Gilbert，M.J.Strauss，J.Tropp. Algorithmic linear dimension reduction in thel1 norm for sparse vectors[N]. /files/cs/allerton2006GSTV.pdf. [109] A.C.Gilbert，M.J.Strauss，J.Tropp.One sketch for all:Fast algorithms for compressed sensing. Proceedings of the 39th Annual ACM Symposium on Theory of Computing，New York:Association for Computing Machiner，2007:237-246.[110] Takigawa I，Kudo M，Toyama J. Performance analysis of minimuml-norm1 solutions for underdetermined source separation[J]. IEEE Transactions on Signal Processing，2004，52(3): 582-591.。

动态最佳位点校准[发明专利]

专利名称：动态最佳位点校准
专利类型：发明专利
发明人：P.萨哈,S.K.S.赛伊,A.达斯古普塔,P.查克拉博蒂,D.马吉姆德
申请号：CN201910588434.0
申请日：20190702
公开号：CN110677803A
公开日：
20200110
专利内容由知识产权出版社提供
摘要：一种用于动态最佳位点校准的技术。

所述技术包括：接收收听环境的图像，所述图像可能已经在不良照明条件下捕获；以及基于所述图像而生成人群密度图。

所述技术还包括基于所述人群密度图而设置与音频系统相关联的至少一个音频参数。

可以基于所述至少一个音频参数而生成至少一个音频输出信号。

申请人：哈曼国际工业有限公司
地址：美国康涅狄格州
国籍：US
代理机构：北京市柳沈律师事务所
代理人：高巍
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国内外科技成果转化模式的比较与研究

研究与探讨Academic Research科学技术是第一生产力。

科技成果转化是将科学技术转变为现实生产力的关键环节。

党中央高度重视科技成果转化工作，习近平总书记在党的十九大报告中指出要深化科技体制改革，建立技术创新体系，促进科技成果转化。

李克强总理在政府工作报告中强调，要支持科研院校与企业融通创新，加快创新成果转化应用。

为促进科技成果转移转化，2015年全国人大常委会修订了《促进科技成果转化法》，2016年国务院印发《实施<中华人民共国内外科技成果转化模式的比较与研究丁帅1 许强2（1.中关村发展集团股份有限公司博士后科研工作站，北京 100081；2.北京市科学技术委员会，北京 100744）概要：总结国内外科技成果转化的典型案例，系统地分析其技术转移模式、转化平台搭建和运营管理机制等方面的做法及特点，归纳与总结其在科技成果转化体制机制上的创新之处，并探索从政府监督引导、产学研介合作、成立专业机构、注重长远效益等方面给出进一步推动科技成果转化的思考和建议。

关键词：科技成果转化；技术转移；转化平台；转移模式中图分类号：G301；G311；G321 文献标识码：AAbstract: Summarize the typical cases of the transformation of scientific and technological achievements at home and abroad, systematically analyze the practices and characteristics of its technology transfer mode, transformation platform construction and operation management mechanism, summarize its innovations in the transformation mechanism of scientific and technological achievements, and explore thoughts and suggestions for further promoting the transformation of scientific and technological achievements from the aspects of government supervision and guidance, industry-university research and cooperation, establishment of professional institutions and focusing on long-term beneﬁts.Key words: Scientific and technological achievements transformation; technology transfer; transformationplatform; transfer mode和国促进科技成果转化法>若干规定》和国务院办公厅印发《促进科技成果转移转化行动方案》，形成了科技成果转移转化工作的“三部曲”。

组学原始数据归档库（GSA）使用说明书

组学原始数据归档库（GSA）使用说明系统简介 (2)用户注册 (2)GSA数据集创建 (3)GSA数据集修改、删除和追加 (12)GSA数据集发布 (14)GSA数据集分享链接生成 (15)数据文件上传 (16)Aspera命令行上传（推荐） (16)FTP上传 (18)协助上传 (25)数据触发机制说明 (26)提交状态与操作说明 (27)系统简介组学原始数据归档库（Genome Sequence Archive, GSA）是组学原始数据汇交、存储、管理与共享系统。

GSA遵循INSDC数据库系统的数据标准和数据结构，主要汇交实验信息（Experiment Metadata）、测序反应信息（Run Metadata）信息以及归档测序文件数据（Sequence Data file）。

GSA用户可通过大数据中心生物数据统一汇交入口——生物数据递交系统（BIG Submission，BIG Sub）完成一站式数据递交。

用户注册请您进入生物数据递交系统（BIG Submission，BIG Sub，https:///gsub/）完成账号注册，建议使用实验室公共邮箱进行注册。

如果您在账号注册和使用过程中遇到任何问题，请联系*****************.cn。

GSA数据集创建为保证元数据信息与测序数据文件的一致性与完整性，便于后续数据使用者检索与使用，通过BIG Sub统一入口递交GSA数据信息时，用户需要为GSA数据集的研究任务创建BioProject，并为数据集的实验样本创建相应的BioSample(s)。

GSA各类数据信息间是线性的、一对多的关联关系，数据结构如下图。

本系统支持中英文双语言模式，可随时自由切换⚫提交者信息（Submitter）—用于收集数据提交者信息，系统会帮您自动填入用户注册时的姓名和电子邮件信息，如部分信息需要调整，可直接修改并通过“保存并进入下一项（Save and forward）”键完成修改。

gsa原理 -回复

gsa原理-回复什么是GSA原理？GSA，即基金分配市场（Generalized Second Price Auction），是一种常用的在线广告的拍卖模式。

在这种拍卖模式中，广告主通过投标方式来争取在广告位中展示他们的广告。

然后，广告位拍卖的赢家将支付给广告平台相应的费用，此费用通常是次高出价。

GSA拍卖的基本原理是什么？GSA拍卖通过以下几个步骤来进行：第一步是广告主的投标。

广告主会对广告位进行报价，报价通常以每一次广告展示的费用为单位。

广告主可以根据预算和广告效果对每个广告位进行投标。

第二步是确定赢家。

广告平台根据广告主的投标情况来决定哪个广告主将成为广告位的赢家。

赢家一般是出价最高的广告主。

第三步是确定广告主需要支付的费用。

GSA拍卖中的特点是次高出价支付原则，也就是说，广告主需要支付的费用是第二高的报价。

这是为了避免广告主通过故意报价低于其真实出价来降低自己的成本。

第四步是展示广告。

广告平台将向赢家展示其广告，赢家需要支付给广告平台之前确定的费用。

为什么GSA拍卖采用次高出价支付原则？GSA拍卖采用次高出价支付原则的主要目的是为了促使广告主提供真实的并与其真实期望值相符的报价。

如果拍卖采用最高出价支付原则，广告主可能会故意报价较低以降低自己的成本，导致广告平台无法获得真实的报价信息。

通过次高出价支付原则，广告平台可以更准确地了解市场价格和广告主的真实期望值。

这样，广告平台能够更好地预测投放广告的效果，并根据投放效果对广告主进行更准确的定价。

次高出价支付原则还可以促使广告主更加谨慎地估计他们的报价，从而降低了竞争过度的风险。

如果采用最高出价支付原则，广告主可能会报出过高的价位，以确保赢得广告位，从而导致广告费用的不合理增加。

GSA拍卖的优势及适用范围是什么？GSA拍卖具有如下的优势：1. 高度透明：GSA拍卖过程公开透明，所有广告主都可以根据竞争对手的报价来制定自己的报价策略。

这样能够有效地促使广告主提供真实的报价信息。

gsa算法流程-概述说明以及解释

gsa算法流程-概述说明以及解释1.引言1.1 概述GSA算法，即Gravitational Search Algorithm（引力搜索算法），是一种基于引力的全局优化算法。

它模拟了物理引力的作用机制，通过引力和质量的概念来进行搜索优化。

该算法最初由Rashedi等人于2009年提出，并且在许多领域得到了广泛的应用。

GSA算法的核心思想是模拟粒子间的引力相互作用，其中每个粒子代表一个候选解，并由其质量和位置确定。

粒子之间通过计算引力来更新其位置，并逐步进行全局搜索以找到最优解。

在整个搜索过程中，算法通过对所有粒子进行迭代调整来提高全局搜索的效果，以尽可能快地达到最优解。

不同于其他优化算法，GSA算法以一种高度并行的方式工作，这是由于粒子之间的引力作用是根据它们之间的距离和质量来计算的。

如果两个粒子之间距离较近并且质量较大，它们之间的引力将会比较强，从而导致这两个粒子相互靠近并进行信息交流。

这种并行性使得GSA算法在处理大规模和高维度问题时表现出色。

总体而言，GSA算法在全局优化问题中具有一定的优势。

通过模拟物体之间的引力相互作用，它能够在问题的解空间中进行全面且高效的搜索。

本文将详细介绍GSA算法的流程，并通过具体案例来展示其实际应用和性能。

通过深入理解和掌握GSA算法的流程，我们可以更好地利用这一算法来解决实际问题。

1.2 文章结构本文将围绕二进制格雷独立散列（GSA）算法展开讨论，旨在介绍该算法的原理、应用场景以及其核心流程。

文章分为引言、正文和结论三个部分，具体结构如下：引言部分（Chapter 1）：在本部分中，我们将首先对本文的研究背景进行概述，介绍GSA算法的基本概念和发展历程。

随后，我们将给出本文的主要目标和研究内容，以及相关研究的研究方法和数据来源。

正文部分（Chapter 2）：本部分是本文的核心部分，将详细介绍GSA 算法的原理和流程。

首先，我们将对GSA算法的基本概念进行介绍，包括二进制格雷独立散列的定义和特点。

《2024年二维过渡金属硫族化合物薄膜的制备及性能研究》范文

《二维过渡金属硫族化合物薄膜的制备及性能研究》篇一一、引言随着纳米科技和材料科学的飞速发展，二维材料因其独特的物理和化学性质在诸多领域中展现出了巨大的应用潜力。

其中，二维过渡金属硫族化合物（TMDs）薄膜因其优异的电子、光学和催化性能，近年来受到了广泛关注。

本文将详细介绍二维TMDs薄膜的制备方法、性能特点及其潜在应用。

二、二维TMDs薄膜的制备方法1. 化学气相沉积法（CVD）化学气相沉积法是一种常用的制备二维TMDs薄膜的方法。

该方法通过在高温环境下将前驱体气体引入反应室，使其在基底上发生化学反应，生成目标TMDs薄膜。

此方法具有薄膜厚度可控、均匀性好等优点。

2. 机械剥离法机械剥离法是一种简单易行的制备二维TMDs薄膜的方法。

通过机械剥离或撕拉的方式，将TMDs块材分离成薄片，然后将其转移到目标基底上。

该方法制备的薄膜质量较高，但产量较低。

3. 液相剥离法液相剥离法是一种利用溶剂剥离TMDs块材，制备二维TMDs薄膜的方法。

通过将TMDs块材置于有机溶剂中，利用超声波处理，使块材剥离成薄片，并悬浮在溶液中。

随后，通过离心、过滤等方法将薄膜转移到目标基底上。

三、二维TMDs薄膜的性能特点1. 优异的电子性能：二维TMDs薄膜具有较高的电子迁移率和导电性能，使其在电子器件、光电器件等领域具有广泛应用。

2. 独特的光学性能：TMDs薄膜在光吸收、发光、光催化等方面表现出独特的性能，为其在光电子领域的应用提供了可能。

3. 良好的催化性能：TMDs薄膜在电催化、光催化等领域展现出良好的性能，为其在能源、环境等领域的应用提供了广阔的前景。

四、二维TMDs薄膜的潜在应用1. 电子器件：利用TMDs薄膜优异的电子性能，可制备高性能的晶体管、场效应管等电子器件。

2. 光电器件：TMDs薄膜独特的光学性能使其在光电器件领域具有广泛应用，如光探测器、LED等。

3. 能源领域：TMDs薄膜良好的催化性能使其在太阳能电池、氢能等领域具有潜在应用价值。

用于在数字处理系统中调度矩阵运算的方法和设备[发明专利]

专利名称：用于在数字处理系统中调度矩阵运算的方法和设备专利类型：发明专利
发明人：尚哲·庄,沙拉德·瓦桑特劳·蔻依,西亚德·玛
申请号：CN202080049870.1
申请日：20200507
公开号：CN114072780A
公开日：
20220218
专利内容由知识产权出版社提供
摘要：人工智能是计算机行业中越来越重要的领域。

然而，人工智能是计算极其密集的领域，使得执行人工智能计算可能是昂贵、耗时且耗费精力的。

幸运的是，人工智能应用程序所需的许多计算可以并行执行，使得专用的线性代数矩阵处理器可以大大提高计算性能。

但即使利用线性代数矩阵处理器，性能也可能会由于复杂的数据依赖性而受到限制。

如果没有适当的协调，线性代数矩阵处理器可能会最终处于空闲状态或花费大量时间四处移动数据。

因此，本文件公开了用于高效地调度线性代数矩阵处理器的方法。

申请人：艾克斯派得拉有限责任公司
地址：美国加州帕洛阿尔托市3468号考珀法院
国籍：US
代理机构：上海汇诚合一知识产权代理有限公司
代理人：翟国建
更多信息请下载全文后查看。

《2024年碳基全无机CsPbBr3钙钛矿太阳能电池的制备及其性能研究》范文

《碳基全无机CsPbBr3钙钛矿太阳能电池的制备及其性能研究》篇一一、引言随着对可再生能源的日益重视和科技的发展，太阳能电池的效率及其稳定性的提高显得尤为重要。

近年来，碳基全无机钙钛矿太阳能电池（PSC）凭借其独特的光电性质及较低的成本在太阳能研究领域内迅速崛起。

特别是基于CsPbBr3钙钛矿结构的太阳能电池，因其优异的光电性能及环境稳定性受到了广泛的关注。

本文旨在详细探讨碳基全无机CsPbBr3钙钛矿太阳能电池的制备工艺，以及对其性能的深入研究。

二、碳基全无机CsPbBr3钙钛矿太阳能电池的制备1. 材料选择与预处理制备碳基全无机CsPbBr3钙钛矿太阳能电池，首先需要选择高质量的CsPbBr3钙钛矿材料和导电碳基底。

材料经过清洗、干燥后，进行预处理以提高其表面活性和附着性。

2. 电池制备工艺电池的制备主要包括钙钛矿层的制备、碳电极的制备以及电池的封装等步骤。

首先，在预处理后的碳基底上制备钙钛矿层，通过溶液法或气相沉积法将CsPbBr3钙钛矿材料均匀地涂覆在基底上。

然后，制备碳电极，通过印刷或喷涂等方式将导电碳材料覆盖在钙钛矿层上。

最后，对电池进行封装，以提高其环境稳定性。

三、性能研究1. 光电性能分析通过光电性能测试，对碳基全无机CsPbBr3钙钛矿太阳能电池的光电转换效率、开路电压、短路电流等性能参数进行评估。

实验结果表明，该类太阳能电池具有较高的光电转换效率和较好的稳定性。

2. 环境稳定性测试为评估电池在实际环境中的性能表现，对电池进行了长时间的环境稳定性测试。

测试结果表明，碳基全无机CsPbBr3钙钛矿太阳能电池在湿度、温度等环境因素影响下表现出较好的稳定性。

四、讨论与展望碳基全无机CsPbBr3钙钛矿太阳能电池的制备工艺简单、成本低廉，且具有优异的光电性能和稳定性。

然而，其在实际应用中仍面临一些挑战，如制备过程中的均匀性控制、电池寿命的进一步提高等。

未来研究可关注以下几个方面：1. 优化制备工艺：通过改进制备方法，提高钙钛矿层的均匀性和致密性，进一步提高太阳能电池的光电性能。

GSAS软件操作简介

GSAS软件操作简介2008-11-17 21:32:55| 分类：学术研究| 标签：|字号大中小订阅GENERAL STRUCTURE ANALYSIS SYSTEM目前常用的Rietveld结构精修软件有GSAS, Fullprof, Rietan, BGMN, DBWS, WinPLOTR等等，其实他们的核心算法都是一样的。

DBWS是最早的精修软件，但由于其是DOS 操作界面，目前用户越来越少。

而GSAS由于操作方便、界面友好、更新迅速而得到广泛使用。

GSAS有两个版本的软件，一个叫PC-GSAS，另外一个叫EXPGUI。

PC-GSAS是Los Alamos National Laboratory的Allen C. Larson和Robert B. Von Dreele编写的，联系方式Bob von Dreele - *****************，文章引用应标明：A.C. Larson and R.B. Von Dreele, "General Structure Analysis System (GSAS)", Los Alamos National Laboratory Report LAUR 86-748 (1994).PC-GSAS是基于人机对话的方式，操作起来稍显复杂。

在这儿我们主要介绍EXPGUI。

EXPGUI是B. H. Toby在GSAS的基础上编写的图形用户界面（Graphical User Interface）程序，可以说EXPGUI囊括了我们所经常用到的大部分GSAS的功能，但不是全部。

文章引用应标明：B. H. Toby, EXPGUI, a graphical user interface for GSAS, J. Appl. Cryst. (2001). 34, 210-213.联系方式: Brian Toby - ******************本文主要包括以下几个部分：1．软件下载与安装2．数据导入与模型建立3．结构精修过程过程（背景函数，晶格参数，峰形参数，原子位置，温度因子，择优取向）4．数据导出与处理1．软件下载与安装主页/solution/gsas/下载地址：ftp:///public/gsas//ccp/ccp14/ftp-mirror/gsas/public/gsas/ftp:///ccp14/ftp-mirror/gsas/public/gsas/http://ccp14.sims.nrc.ca/ccp/ccp14/ftp-mirror/gsas/public/gsas/作者编写了非常详细的使用说明文件：GSASManual.pdf，可以从网上下载：ftp:///public/gsas/manual/GSASManual.pdf./ccp/ccp14/ftp-mirror/gsas/public/gsas/manual/GSASManual.pdfEXPGUI可以运行在多种平台：Windows，Mac，UNIX，Linux，SGI。

GSA2.0 使用流程.ver3

Gsub系统数据信息填写及数据上传说明组学原始数据归档库（Genome Sequence Archive, GSA）是组学原始数据汇交、存储、管理与共享系统，是国内首个被国际期刊认可的组学数据发布平台。

面向全球接收不同测序平台产生的组学原始数据，提供免费的数据长期存储、管理与共享服务，旨在形成国家生物大数据战略发展资源，服务于国家公益性科学研究与产业创新项目。

注：GSA2.0已正式上线，GSA元数据录入系统迁移到Genome Sequence Submission (Gsub), Gsub。

数据集合的单位改为GSA即CRAxxxxxx, 每一批次上传数据都放在同一个GSA下，也就是通常状况下，一个GSA有且只对应一个BioProject。

用户注册：Genome Sequence Submission (Gsub), Gsub主页：/gsub。

注意事项：1.不建议使用Win10系统操作，推荐使用Firefox浏览器，其他浏览器可能有bug；2.每一层级信息的Release Date的设置时间可尽量往后填写，但最长不要超过2年。

这点很重要，保证数据不能够被他人下载；3.GSA充分考虑到大体量数据上传用户的需求，开启了硬盘寄送&协助上传的绿色通道。

用户只需填写批量上传表格，并将把数据硬盘寄送给GSA，我们会协助您完成信息录入和数据上传；4.如在系统使用过程中遇到任何问题，请您联系GSA工作组，邮箱: gsa@；QQ工作群:548170081；通信地址：北京市朝阳区北辰西路1号院104号楼；联系电话：+86（01）84097340。

按照注册用户信息Login 后，系统会自动跳回到GSA 主页，填写前先了解GSA 创建总的概览和思考一个问题。

◆ GSA 元信息创建过程总的概览，创建GSA 完整的元信息需要3个步骤。

①BioProject 中创建Project ；②在BioSample 中创建Sample ；③在GSA 中创建experiment 和Run 信息。

在规范下前行——安捷伦科技有限公司（中国）专访

在规范下前行——安捷伦科技有限公司（中国）专访
王成玥
【期刊名称】《流程工业》
【年(卷),期】2003(000)003
【摘要】2003年1月24日，安捷伦科技有限公司(中国)在北京国贸饭店B1层
举行了题为“遵循国际制药行业法规标准”的研讨会。

在会上，安捷伦科技生命科学事业部全球产品市场经理Ludwig Huber博士和生命科学与化学分析事业部亚
太地区销售拓展经理Yoko Gemba女士分别就“制药工业的国际标准”“实验室计算机系统认证”“电子文件／签名和21CFR Partll规范”和“安捷伦全程服务”进行了专题演讲，并回答了与会听众提出的问题。

本刊记者获邀前往，并在研讨会间隙采访了安捷伦生命科学事业，生命科学与化学分析事业部东北亚区经理曾雅才先生。

【总页数】3页(P18-20)
【作者】王成玥
【作者单位】无
【正文语种】中文
【中图分类】F270
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