Issue 6, 2019

Predicting the capacitance of carbon-based electric double layer capacitors by machine learning

Abstract

Machine learning (ML) methods were applied to predict the capacitance of carbon-based supercapacitors. Hundreds of published experimental datasets are collected for training ML models to identify the relative importance of seven electrode features. This present method could be used to predict and screen better carbon electrode materials.

Graphical abstract: Predicting the capacitance of carbon-based electric double layer capacitors by machine learning

Supplementary files

Article information

Article type
Communication
Submitted
20 fev 2019
Accepted
25 apr 2019
First published
25 apr 2019
This article is Open Access
Creative Commons BY-NC license

Nanoscale Adv., 2019,1, 2162-2166

Predicting the capacitance of carbon-based electric double layer capacitors by machine learning

H. Su, S. Lin, S. Deng, C. Lian, Y. Shang and H. Liu, Nanoscale Adv., 2019, 1, 2162 DOI: 10.1039/C9NA00105K

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