Accelerating Atomic Catalyst Discovery by Theoretical Calculations‐Machine Learning Strategy-Reference-Cited by-全球学者库

Accelerating Atomic Catalyst Discovery by Theoretical Calculations‐Machine Learning Strategy

Published:2020-03 Issue:12 Volume:10 Page:1903949
ISSN:1614-6832
Container-title:Advanced Energy Materials
language:en
Short-container-title:Adv. Energy Mater.

Author:

Sun Mingzi¹,Dougherty Alan William¹,Huang Bolong¹^ORCID,Li Yuliang²,Yan Chun‐Hua³

Affiliation:

1. Department of Applied Biology and Chemical TechnologyThe Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong SAR 999077 China

2. Key Laboratory of Organic SolidsInstitute of ChemistryChinese Academy of Sciences Beijing 100190 P. R. China

3. Key Laboratory of Nonferrous Metal Chemistry and Resources Utilization of Gansu ProvinceState Key Laboratory of Applied Organic Chemistry and College of Chemistry and Chemical EngineeringResearch Center of Biomedical NanotechnologyLanzhou University Lanzhou 730000 P. R. China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aenm.201903949

Reference64 articles.

1. Earth-abundant catalysts for electrochemical and photoelectrochemical water splitting

3. Support and Interface Effects in Water‐Splitting Electrocatalysts

4. Recent progress made in the mechanism comprehension and design of electrocatalysts for alkaline water splitting

5. A Perovskite Nanorod as Bifunctional Electrocatalyst for Overall Water Splitting

Cited by 93 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Interaction of metal ions in high efficiency seawater hydrogen peroxide production by a carbon-based photocatalyst;Applied Catalysis B: Environmental;2024-04

2. Challenges and opportunities of atomic-scales reactive sites in thriving electrochemical CO2 reduction reaction;Nano Today;2024-04

3. Hybrid scheme of DFT and machine learning to accelerate the design of graphyne nanoribbons as electrocatalysts for the ORR and HER;Fuel;2024-02

4. Deciphering orbital hybridization in heterogeneous catalysis;Electron;2024-01-24

5. Linking stability with molecular geometries of perovskites and lanthanide richness using machine learning methods;Computational Materials Science;2024-01