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利用MGI方法寻找锂离子扩散激活能的材料基因
引用本文:陈宁,王裕晓,雷承辉,刘洋,李阳,王丽君,李福燊.利用MGI方法寻找锂离子扩散激活能的材料基因[J].化学通报,2020,83(1):50-57.
作者姓名:陈宁  王裕晓  雷承辉  刘洋  李阳  王丽君  李福燊
作者单位:北京科技大学材料科学与工程学院 北京 100083;北京科技大学材料科学与工程学院 北京 100083;Department of Engineering Science and Materials,University of Puerto Rico,Mayaguez,Puerto Rico 00681-9044,USA
基金项目:科技部重点专项计划项目(2016YFB0700503-7)资助
摘    要:锂离子电池的应用涉及了正负极和电解质等关键材料,材料中的锂离子扩散属于最核心的微观过程。通过实验测量和理论计算可以找到锂离子扩散激活能小的优秀材料,但是通过一个好的激活能参数,我们不能明确它的影响因素是什么,也无法实现优化现有材料和发现新的锂电材料的目的。本文利用材料基因组计划(MGI)的研究思路,利用第一性原理计算得到的40多种典型体系的激活能参数,结合能带结构特征的计算结果,并通过数据分析,明确了晶格结构中影响锂离子扩散激活能的因素,确定出价带宽度和价带中d电子轨道比例数等基因参数影响激活能的规律。这些结果反映了锂离子材料能带整体特征研究的必要性,也体现了MGI研究方法的优势和特点。

关 键 词:锂离子电池  扩散激活能  固体电解质  大数据
收稿时间:2019/6/9 0:00:00
修稿时间:2019/10/3 0:00:00

Identifying the Material Gene of Lithium Ion Diffusion Activation Energy by MGI Method
Chen Ning,Wang Yuxiao,Lei Chenghui,Liu Yang,Li Yang,Wang Lijun and Li Fushen.Identifying the Material Gene of Lithium Ion Diffusion Activation Energy by MGI Method[J].Chemistry,2020,83(1):50-57.
Authors:Chen Ning  Wang Yuxiao  Lei Chenghui  Liu Yang  Li Yang  Wang Lijun and Li Fushen
Institution:School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083,School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083,School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083,School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083,School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083;Department of Engineering Science and Materials, University of Puerto Rico, Mayaguez, Puerto Rico 00681-9044, USA,School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083 and School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083
Abstract:The application of lithium-ion batteries involves key materials such as cathode and anode, electrolytes. The diffusion of lithium ions in materials is the core microscopic process. Through experimental measurements and theoretical calculations, excellent materials with small diffusion activation energy of lithium ions can be found, but with a good activation energy parameter, we cannot clarify what the influencing factors are, nor can we optimize existing materials and discover new lithium batteries material. In this paper, using materials genome initiative (MGI) research ideas, using the first-principles calculation of the activation energy parameters of more than 40 typical systems, combined with the calculation results of the energy band structure characteristics, and through data analysis, we have identified the influence of lithium-ion diffusion in the lattice structure. The law of activation energy influenced by gene parameters such as valence band width and d orbital proportion in valence band was determined. These results reflect the necessity of the study of the overall characteristics of the lithium ion material band, and also reflect the advantages and characteristics of the MGI research method.
Keywords:Lithium ion battery  Diffusion activation energy  Solid electrolyte  Big Data
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