Machine learning for continuous innovation in battery technologies

Muratahan Aykol

doi:10.1038/s41578-020-0216-y

2020-06-15

145

PRE

Muratahan Aykol *

Patrick K. Herring

Abraham Anapolsky

DOI：10.1038/s41578-020-0216-y

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摘要

En 中文

Batteries, as complex materials systems, pose unique challenges for the application of machine learning. Although a shift to data-driven, machine learning-based battery research has started, new initiatives in academia and industry are needed to fully exploit its potential.

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Nature Reviews Materials

IF:

86.2

论文数:

1.2K

被引数:

4.3W

机构

toyota motor corporation

学者数:

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论文数: 1.3K

被引数: 2

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