Study On Ion Conduction Of Inorganic Solid Electrolytes Based On Material Genome

Materials genome is a kind of new ideas and new methods to efficiently promote the research and development of new materials by integrating three elements of high-throughput computing,high-throughput experiment and material database.The data-driven mode based on the materials genome represents a new paradigm for material research and development.In the field of lithium-ion battery,inorganic solid electrolyte has been widely concerned due to its high safety,while the lower ionic conductivity limits its development and application.Understanding the ion conduction mechanism and extracting the cause and rule of ion conduction speed is helpful to reasonably and effectively find and design inorganic solid electrolyte materials with high ionic conductivity.Inspired by this,this thesis,based on the idea of the material genome and adopting the methods of statistical analysis and machine learning,mainly conducts a systematic qualitative and quantitative research on the basic problem of ion conduction.It mainly focuses on the generation of data such as descriptors for ion condction and the analysis of the relationship between descriptors and ion conduction performance.The main contents and results of this thesis are as follows:1.The factors influencing the ionic conductivity are systematically analyzed by combining static and dynamic lattice.By integrating the theory,experience knowledge and desigh rules of ion conduction in inorganic solid electrolyte,the factors related to ionic conduction are systemcatically analyzed from the point of the static and dynamic.It mainly involves three dimensions（crystal structure,energy,and conduction dynamics）and six aspects（ionic properties,ionic spatial arrangement characteristics,defects and ionic conduction mechanisms,the ionic potential energy changes,lattice dynamics and rotational dynamics）.The case studies are carried out by taking volume effect and paddle-wheel effect as the representations of static and dynamic factors respectively.From the experimental and calculated results on the phase structure evolution and ionic conductivities ofα-Li₂SO₄ andα-Na₃PO₄based inorganic plastic crystal electrolytes and Li₁₀MP₂S₁₂（M=Si,Ge,Se）electrolytes,it reveals the the suppression of rotational motion effect of polyanion,i.e.paddle-wheel is the reason of that the substitution of the bigger-size polyanion expands the skeleton lattice but ultimately increases activation energy and lowers the ionic conductivity.These results show that,in order to develop inorganic solid electrolyte materials with high ionic conductivity,it is necessary to enhance the volume effect and impove the paddle-wheel effect of polyanion at the same time,which verifies the importance and necessity of analyzing factors associated with ionic conduction by combing static and dynamic effect.2.A generic hierarchically encoding crystal structure-based descriptor is proposed.Based on the anlaysis on factor assiated with ion conduction,by integrating the global and local effects of Li⁺conduction environment,we develop the generic hierarchically encoding crystal structure-based（HECS）descriptors encompassing composition,structure,conduction pathway,ion distribution,and special ions derived from the unit cell information.The case study is carried out by taking cubic Li-argyrodite as the model system.32 HECS-descriptors are constructed and their causalities with Li⁺conduction are inferred via partial correlation analysis.It’s found that the smaller anion size plays a significant role in achieving lower activation energy,which results from the competing effects between the lattice space and bottleneck size controlled by framework site disorder.Based on this rule,the promising candidates are suggested,such as Li_6-xPS_5-xCl_1+x（0<x<1）,Li_6+xPS_5+xBr_1-x（0<x<1）,Li₆PS₅Cl_0.5+xBr_0.5-x（0<x<0.5）,Li_6+xPS_5+xBr_0.75I_0.25-x（0<x<0.25）and Li₆PS₅Br_0.75+xI_0.25-x（0<x<0.25）,in which Li_5.5PS_4.5Cl_1.5(Li_6-xPS_5-xCl_1+x,x=0.5)have been experimentally evaluated as excellent candidates for practical SSEs.Its room temperature ionicconductivity can reach 9.4 m S/cm,which is about 4 times higher than that of Li₆PS₅Cl prepared under the same processing conditions.And its activation energy is only 0.29 e V.Besides,sintering leads to a higher conductivity（12±0.2 m S/cm）of Li_5.5PS_4.5Cl_1.5,which is comparable to Li₁₀Ge P₂S₁₂,However,the raw materials of Li_5.5PS_4.5Cl_1.5 are cheaper than that of Li₁₀Ge P₂S₁₂.3.A generic framework of ML prediction for E_a in SSEs with hierarchically encoding crystal structure-based（HECS）descriptors is constructed.Under this framework,the case study is carried out by taking cubic Li-argyrodite as the model system.The E_a prediction model is developed to the coefficient of determination（R²）and root-mean-square error（RMSE）values of 0.887 and 0.02 e V for training dataset,and 0.820 and 0.02 e V for test dataset,respectively by partial least-squares regression analysis.The variable importance in projection（VIP）scores demonstrate the combined effects from global and local Li⁺conduction environments,especially the anion size and the resultant structural changes associated with anion site disorder make the significant contributions to the variation of E_a values.This analysis helps to further guide the discovery and design of new potential SSEs.Meantime,knowledge extracted from the ML model leads us to optimize and design new SSEs with low E_a,such as Li_6-xPS_5-xCl_1+x（E_a<0.322 e V）,Li_6+xPS_5+xBr_1-x（E_a<0.273 e V）,Li_6+xPS_5+xBr_0.25I_0.75-x（E_a<0.352 e V）;Li_6+（5-n）yP_1-yN_yS₅I（E_a<0.420 e V）,Li_6+（5-n）yAs_1-yN_yS₅I（E_a<0.371 e V）,Li_6+（5-n）yAs_1-yN_ySe₅I（E_a<0.450 e V）by broadening the bottleneck size,invoking anion site disorder and activating concerted conduction.