Applying machine learning to boost the development of high-performance membrane electrode assembly for proton exchange membrane fuel cells-Reference-Cited by-同舟云学术

Applying machine learning to boost the development of high-performance membrane electrode assembly for proton exchange membrane fuel cells

Published:2021 Issue:11 Volume:9 Page:6841-6850
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Ding Rui¹²³⁴⁵,Ding Yiqin¹²³⁴⁵,Zhang Hongyu¹²³⁴⁵,Wang Ran¹²³⁴⁵,Xu Zihan¹²³⁴⁵,Liu Yide¹²³⁴⁵,Yin Wenjuan¹²³⁴⁵,Wang Jiankang¹²³⁴⁵,Li Jia¹²³⁴⁵,Liu Jianguo¹²³⁴⁵^ORCID

Affiliation:

1. National Laboratory of Solid State Microstructures

2. College of Engineering and Applied Sciences

3. Collaborative Innovation Center of Advanced Microstructures

4. Nanjing University

5. Nanjing 210093

Abstract

A comprehensive machine learning workflow consisting of feature selection, decision modeling, regression modeling, and extremum optimization was set up to give predictions based on big-data, bringing revolutionary changes to labor-intensive fields.

Funder

National Natural Science Foundation of China

National Basic Research Program of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/TA/D0TA12571G

Reference45 articles.

1. Ternary heterogeneous Pt–Ni–Au nanowires with enhanced activity and stability for PEMFCs

2. The effects of Nafion® ionomer content in PEMFC MEAs prepared by a catalyst-coated membrane (CCM) spraying method