Multi-scale computation methods: Their applications in lithium-ion battery research and development

Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database,enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps,as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales.     

基于材料基因组方法的锂电池新材料开发

近年来,在锂二次电池新材料的研发过程中逐渐建立了基于材料基因组思想的高通量计算理论工具与研究平台.在该平台上,通过将不同精度的计算方法组合,实现了基于离子输运性质的材料筛选;通过将信息学中数据挖掘算法引入高通量计算数据的分析,证实了材料大数据解读的可行性.上述平台实现了在锂电池固体电解质的高通量筛选、优化和设计上进行新材料研发的示范应用,通过高通量计算筛选获得了两种可用于富锂正极包覆材料的化合物Li_2SiO_3和Li2SnO_3,有效改善了富锂正极的循环稳定性;通过对掺杂策略的高通量筛选,获得了提高固体电解质β-Li_3PS_4离子电导率和稳定性的方案;通过高通量结构预测设计了全新的氧硫化物固体电解质LiAlSO;并在零应变电极材料结构与性能的构效关系研究中进行了大数据分析的尝试,分析了零应变电极材料的设计依据.上述材料基因组方法在锂电池材料研发中的应用为在其他类型材料研发中推广这种新的研发模式提供了可能.