An ensemble learning classifier to discover arsenene catalysts with implanted heteroatoms for hydrogen evolution reaction-Reference-Cited by-同舟云学术

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An ensemble learning classifier to discover arsenene catalysts with implanted heteroatoms for hydrogen evolution reaction

Published:2023-03 Issue: Volume:78 Page:268-276
ISSN:2095-4956
Container-title:Journal of Energy Chemistry
language:en
Short-container-title:Journal of Energy Chemistry

Author:

Chen An,Cai Junfei,Wang Zhilong,Han Yanqiang,Ye Simin,Li Jinjin

Funder

Shantou Science and Technology Project

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Electrochemistry,Energy (miscellaneous),Energy Engineering and Power Technology,Fuel Technology

Reference52 articles.

1. ENERGY Production, Conversion, Storage, Conservation, and Coupling;Demirel,2016

2. Advancing the Electrochemistry of the Hydrogen‐Evolution Reaction through Combining Experiment and Theory

3. Combining theory and experiment in electrocatalysis: Insights into materials design

4. Cleaning the Air and Improving Health with Hydrogen Fuel-Cell Vehicles

5. Ultrafast self-heating synthesis of robust heterogeneous nanocarbides for high current density hydrogen evolution reaction

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3. Grouping Hydrogen Storage Materials Based on Their Characteristics;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

4. Beyond the horizons of graphene: xenes for energy applications;RSC Sustainability;2024

5. Ensemble Classification of Hydrogen Storage Materials Using Its Properties;Algorithms for Intelligent Systems;2024

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