背景(考古学)
锂(药物)
动力学蒙特卡罗方法
蒙特卡罗方法
离子
比例(比率)
纳米技术
统计物理学
材料科学
化学
物理
内分泌学
有机化学
古生物学
统计
生物
医学
量子力学
数学
作者
E. M. Gavilán-Arriazu,Michael P. Mercer,Daniel E. Barraco,Harry E. Hoster,E.P.M. Leiva
出处
期刊:Progress in energy
[IOP Publishing]
日期:2021-08-03
卷期号:3 (4): 042001-042001
被引量:39
标识
DOI:10.1088/2516-1083/ac1a65
摘要
Since 1994, Kinetic Monte Carlo (kMC) has been applied to the study of Li-ion batteries and has demonstrated to be a remarkable simulation tool to properly describe the physicochemical processes involved, on the atomistic scale and over long time scales. With the growth of computing power and the widespread use of lithium-based storage systems, more contributions from theoretical studies have been requested. This has led to a remarkable growth of theoretical publications on Li-ion batteries; kMC has been one of the preferred techniques to study these systems. Despite the advantages it presents, kMC has not yet been fully exploited in the field of lithium-ion batteries (LIBs) and its impact in this field is increasing exponentially. In this review, we summarize the most important applications of kMC to the study of LIBs and then comment on the state-of-the-art and prospects for the future of this technique, in the context of multi-scale modeling. We also briefly discuss the prospects for applying kMC to post lithium-ion chemistries such as lithium-sulfur and lithium-air.
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