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ESM Cloud Toolkit:A Copilot for Energy Storage Material Research

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Searching and designing new materials play crucial roles in the development of energy storage devices.In today's world where machine learning technology has shown strong predictive ability for various tasks,the combi-nation with machine learning technology will accelerate the process of material development.Herein,we develop ESM Cloud Toolkit for energy storage materials based on MatElab platform,which is designed as a convenient and accurate way to automatically record and save the raw data of scientific research.The ESM Cloud Toolkit includes multiple features such as automatic archiving of computational simulation data,post-processing of ex-perimental data,and machine learning applications.It makes the entire research workflow more automated and reduces the entry barrier for the application of machine learning technology in the domain of energy storage materials.It integrates data archive,traceability,processing,and reutilization,and allows individual research data to play a greater role in the era of AI.

许晶、肖睿娟、李泓

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Institute of Physics,Chinese Academy of Sciences,Beijing 100190,China

School of Physical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China

国家自然科学基金国家自然科学基金Informatization Plan of Chinese Academy of Sciences

5202210652172258CAS-WX2021SF-0102

2024

中国物理快报(英文版)
中国科学院物理研究所,中国物理学会

中国物理快报(英文版)

CSTPCDEI
影响因子:0.515
ISSN:0256-307X
年,卷(期):2024.41(5)
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