文章基本信息

标题：Machine learning assisted optimization of electrochemical properties for Ni-rich cathode materials
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作者：Kyoungmin Min ; Byungjin Choi ; Kwangjin Park 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2018
卷号：8
期号：1
页码：15778
DOI：10.1038/s41598-018-34201-4
语种：English
出版社：Springer Nature
摘要：= 0.833, from the extremely randomized tree with adaptive boosting algorithm. Furthermore, we propose a reverse engineering framework to search for experimental parameters that satisfy the target electrochemical specification. The proposed results were validated by experiments. The current results demonstrate that machine learning has great potential to accelerate the optimization process for the commercialization of cathode materials.