Identifying Active Sites for CO2 Reduction on Dealloyed Gold Surfaces by Combining Machine Learning with Multiscale Simulations-Reference-Cited by-同舟云学术

Identifying Active Sites for CO2 Reduction on Dealloyed Gold Surfaces by Combining Machine Learning with Multiscale Simulations

Published:2019-06-18 Issue:29 Volume:141 Page:11651-11657
ISSN:0002-7863
Container-title:Journal of the American Chemical Society
language:en
Short-container-title:J. Am. Chem. Soc.

Author:

Chen Yalu¹^ORCID,Huang Yufeng¹^ORCID,Cheng Tao¹²,Goddard William A.¹^ORCID

Affiliation:

1. Materials and Process Simulation Center (MSC) and Joint Center for Artificial Photosynthesis (JCAP), California Institute of Technology, Pasadena, California 91125, United States

2. Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, 199 Renai Road, Suzhou, 215123 Jiangsu, P.R. China

Funder

Office of Science

Publisher

American Chemical Society (ACS)

Subject

Colloid and Surface Chemistry,Biochemistry,General Chemistry,Catalysis

Link

https://pubs.acs.org/doi/pdf/10.1021/jacs.9b04956

Reference42 articles.

1. Recycling of carbon dioxide to methanol and derived products – closing the loop

2. Prospects of CO2 Utilization via Direct Heterogeneous Electrochemical Reduction

3. Alloys of platinum and early transition metals as oxygen reduction electrocatalysts