In this paper,we report a method through the combination of ab-initio calculations and partial least squares(PLS)analysis to develop the Quantitative Structure eActivity Relationship(QSAR)formulations of cathode volume changes in lithium ion batteries.The PLS analysis is based on ab-initio calculation data of 14 oxide cathodes with spinel structure LiX2O4 and 14 oxide cathodes with layered-structure LiXO_(2)(X=Ti,V,Cr,Mn,Fe,Co,Ni,Nb,Mo,Ru,Rh,Pd,Ta,Ir).Five types of descriptors,describing the characteristics of each compound from crystal structure,element,composition,local distortion and electronic level,with 34 factors in total,are adopted to obtain the QSAR formulation.According to the variable importance in projection analysis,the radius of X4t ion,and the X octahedron descriptors make major contributions to the volume change of cathode during delithiation.The analysis is hopefully applied to the virtual screening and combinatorial design of low-strain cathode materials for lithium ion batteries.
The physics of ionic and electrical conduction at electrode materials of lithium-ion batteries （LIBs） are briefly sum marized here, besides, we review the current research on ionic and electrical conduction in electrode material incorporating experimental and simulation studies. Commercial LIBs have been widely used in portable electronic devices and are now developed for large-scale applications in hybrid electric vehicles （HEV） and stationary distributed power stations. However, due to the physical limits of the materials, the overall performance of today＇s LIBs does not meet all the requirements for future applications, and the transport problem has been one of the main barriers to further improvement. The electron and Li-ion transport behaviors are important in determining the rate capacity of LIBs.
The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is re- viewed, including fiigh-capacity cathodes, low-strain cathodes, anodes, solid state eleclrolytes, and electrolyte additives. With tfie development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new malerials. With the help of automatic simnlation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve perlbmmnce, and some representative criteria are： higher energy density, better safety, and faster charge/discharge speed.
The physics that associated with the performance of lithium secondary batteries(LSB)are reviewed.The key physical problems in LSB include the electronic conduction mechanism,kinetics and thermodynamics of lithium ion migration,electrode/electrolyte surface/interface,structural(phase)and thermodynamics stability of the electrode materials,physics of intercalation and deintercalation.The relationship between the physical/chemical nature of the LSB materials and the batteries performance is summarized and discussed.A general thread of computational materials design for LSB materials is emphasized concerning all the discussed physics problems.In order to fasten the progress of the new materials discovery and design for the next generation LSB,the Materials Genome Initiative(MGI)for LSB materials is a promising strategy and the related requirements are highlighted.
From first principle calculations, we demonstrate that LiXS_2（X = Ga, In） compounds have potential applications as cathode materials for Li ion batteries. It is shown that Li can be extracted from the LiXS_2 lattice with relatively small volume change and the XS_4 tetrahedron structure framework remains stable upon delithiation. The theoretical capacity and average intercalation potential of the LiGaS_2（LiInS_2） cathode are 190.4（144._2） m Ah/g and 3.50 V（3.53 V）. The electronic structures of the LiXS_2 are insulating with band gaps of _2.88 eV and 1.99 eV for X = Ga and In, respectively.However, Li vacancies, which are formed through delithiation, change the electronic structure substantially from insulating to metallic structure, indicating that the electrical conductivities of the LiXS_2 compounds should be good during cycling.Li ion migration energy barriers are also calculated, and the results show that Li ion diffusions in the LiXS_2 compounds can be as good as those in the currently widely used electrode materials.
Inorganic solid electrolytes have distinguished advantages in terms of safety and stability, and are promising to substitute for conventional organic liquid electrolytes. However, low ionic conductivity of typical candidates is the key problem. As connective diffusion path is the prerequisite for high performance, we screen for possible solid electrolytes from the 2004 International Centre for Diffraction Data （ICDD） database by calculating conduction pathways using Bond Valence （BV） method. There are 109846 inorganic crystals in the 2004 ICDD database, and 5295 of them contain lithium. Except for those with toxic, radioactive, rare, or variable valence elements, 1380 materials are candidates for solid electrolytes. The rationality of the BV method is approved by comparing the existing solid electrolytes＇ conduction pathways we had calculated with those from ex- periments or first principle calculations. The implication for doping and substitution, two important ways to improve the conductivity, is also discussed. Among them LizCO3 is selected for a detailed comparison, and the pathway is reproduced well with that based on the density functional studies. To reveal the correlation between connectivity of pathways and conductivity, a/γ-LiAlO2 and Li2CO3 are investigated by the impedance spectrum as an example, and many experimental and theoretical studies are in process to indicate the relationship between property and structure. The BV method can calculate one material within a few minutes, providing an efficient way to lock onto targets from abundant data, and to investigate the struc- ture-property relationship systematically.
