Predicting the capacitance of carbon-based electric double layer capacitors by machine learning. Issue 6 (8th May 2019)

• Record Type: Journal Article
• Authors: Su, Haiping; Lin, Sen; Deng, Shengwei; Lian, Cheng; Shang, Yazhuo; Liu, Honglai
• Is Part Of: Nanoscale advances. Volume 1:Issue 6(2019)
• Page Start: 2162
• Page End: 2166
• Publication Date: 2019-05-08
• Subjects: 620.5
• DOI: 10.1039/c9na00105k
• Languages: English
• ISSNs: 2516-0230

Abstract

Abstract : Machine learning (ML) methods were applied to predict the capacitance of carbon-based supercapacitors. 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.