Wang Youwei, Zhang Wenqing, Chen Lidong, Shi Siqi, Liu Jianjun
State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, PR China.
Materials Genome Institute, Shanghai University, Shanghai, PR China.
Sci Technol Adv Mater. 2017 Feb 14;18(1):134-146. doi: 10.1080/14686996.2016.1277503. eCollection 2017.
Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.
锂离子电池是应对全球清洁可再生能源和环境污染挑战的关键技术。它们在便携式电子设备、电动汽车和大规模电网中的当代应用，推动了具有高能量密度、高功率、良好安全性和长寿命的高性能电池材料的发展。高通量计算为发现新型电池材料和优化现有材料性能提供了一种实用策略。以往高通量计算筛选出的大多数阴极材料无法满足实际应用的要求，因为仅考虑了体相的容量、电压和体积变化。在高通量计算中纳入更多结构-性能关系，如点缺陷、表面和界面、掺杂和金属混合以及纳米尺寸效应，非常重要。在本综述中，我们通过本征体相参数建立了锂离子电池材料结构-性能关系的定量描述，可应用于未来高通量计算以筛选锂离子电池材料。基于这些参数化的结构-性能关系，提出了一种可能的高通量计算筛选流程路径，以获得高性能电池材料。
