Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction

Published 2017 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction
Authors
Keywords
-
Journal
ACS Catalysis
Volume 7, Issue 10, Pages 6600-6608
Publisher
American Chemical Society (ACS)
Online
2017-07-28
DOI
10.1021/acscatal.7b01648

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started

Ask a Question. Answer a Question.

Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.

Get Started
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.