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  • 标题:Machine learning assisted optimization of electrochemical properties for Ni-rich cathode materials
  • 本地全文:下载
  • 作者:Kyoungmin Min ; Byungjin Choi ; Kwangjin Park
  • 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.
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