Progress in Computational and Machine‐Learning Methods for Heterogeneous Small‐Molecule Activation-Reference-Cited by-同舟云学术

Progress in Computational and Machine‐Learning Methods for Heterogeneous Small‐Molecule Activation

Published:2020-03-20 Issue:35 Volume:32 Page:1907865
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Adv. Mater.

Author:

Gu Geun Ho¹,Choi Changhyeok¹,Lee Yeunhee²,Situmorang Andres B.²,Noh Juhwan¹^ORCID,Kim Yong‐Hyun²,Jung Yousung¹^ORCID

Affiliation:

1. Department of Chemical and Biomolecular EngineeringKorea Advanced Institute of Science and Technology (KAIST) 291 Daehak‐ro, Yuseong‐gu Daejeon 34141 Republic of Korea

2. Department of Physics and Graduate School of Nanoscience and TechnologyKorea Advanced Institute of Science and Technology (KAIST) 291 Daehak‐ro, Yuseong‐gu Daejeon 34141 Republic of Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.201907865

Reference252 articles.

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

2. Review of electrochemical ammonia production technologies and materials

3. Ammonia and related chemicals as potential indirect hydrogen storage materials