Identifying the Activity Origin of a Cobalt Single‐Atom Catalyst for Hydrogen Evolution Using Supervised Learning. (23rd February 2021)
- Record Type:
- Journal Article
- Title:
- Identifying the Activity Origin of a Cobalt Single‐Atom Catalyst for Hydrogen Evolution Using Supervised Learning. (23rd February 2021)
- Main Title:
- Identifying the Activity Origin of a Cobalt Single‐Atom Catalyst for Hydrogen Evolution Using Supervised Learning
- Authors:
- Liu, Xinghui
Zheng, Lirong
Han, Chenxu
Zong, Hongxiang
Yang, Guang
Lin, Shiru
Kumar, Ashwani
Jadhav, Amol R.
Tran, Ngoc Quang
Hwang, Yosep
Lee, Jinsun
Vasimalla, Suresh
Chen, Zhongfang
Kim, Seong‐Gon
Lee, Hyoyoung - Abstract:
- Abstract: Single‐atom catalysts (SACs) have become the forefront of energy conversion studies, but unfortunately, the origin of their activity and the interpretation of the synchrotron spectrograms of these materials remain ambiguous. Here, systematic density functional theory computations reveal that the edge sites—zigzag and armchair—are responsible for the activity of the graphene‐based Co (cobalt) SACs toward hydrogen evolution reaction (HER). Then, edge‐rich (E)‐Co single atoms (SAs) were rationally synthesized guided by theoretical results. Supervised learning techniques are applied to interpret the measured synchrotron spectrum of E‐Co SAs. The obtained local environments of Co SAs, 65.49% of Co‐4N‐plane, 13.64% in Co‐2N‐armchair, and 20.86% in Co‐2N‐zigzag, are consistent with Athena fitting. Remarkably, E‐Co SAs show even better HER electrocatalytic performance than commercial Pt/C at high current density. Using the joint effort of theoretical modeling, thorough characterization of the catalysts aided by supervised learning, and catalytic performance evaluations, this study not only uncovers the activity origin of Co SACs for HER but also lays the cornerstone for the rational design and structural analysis of nanocatalysts. Abstract : Single‐atom‐catalysts (SACs) are at the forefront of energy conversion research. Unfortunately, the origin of their activity and interpretation of these materials' synchrotron spectrograms remain ambiguous. By theoretical modeling,Abstract: Single‐atom catalysts (SACs) have become the forefront of energy conversion studies, but unfortunately, the origin of their activity and the interpretation of the synchrotron spectrograms of these materials remain ambiguous. Here, systematic density functional theory computations reveal that the edge sites—zigzag and armchair—are responsible for the activity of the graphene‐based Co (cobalt) SACs toward hydrogen evolution reaction (HER). Then, edge‐rich (E)‐Co single atoms (SAs) were rationally synthesized guided by theoretical results. Supervised learning techniques are applied to interpret the measured synchrotron spectrum of E‐Co SAs. The obtained local environments of Co SAs, 65.49% of Co‐4N‐plane, 13.64% in Co‐2N‐armchair, and 20.86% in Co‐2N‐zigzag, are consistent with Athena fitting. Remarkably, E‐Co SAs show even better HER electrocatalytic performance than commercial Pt/C at high current density. Using the joint effort of theoretical modeling, thorough characterization of the catalysts aided by supervised learning, and catalytic performance evaluations, this study not only uncovers the activity origin of Co SACs for HER but also lays the cornerstone for the rational design and structural analysis of nanocatalysts. Abstract : Single‐atom‐catalysts (SACs) are at the forefront of energy conversion research. Unfortunately, the origin of their activity and interpretation of these materials' synchrotron spectrograms remain ambiguous. By theoretical modeling, catalytic characterization aided by supervised learning, and catalytic performance evaluations, this study uncovers the Co SACs' activity origin of hydrogen evolution. It lays the cornerstone for the design and structural analysis of nanocatalysts. … (more)
- Is Part Of:
- Advanced functional materials. Volume 31:Number 18(2021)
- Journal:
- Advanced functional materials
- Issue:
- Volume 31:Number 18(2021)
- Issue Display:
- Volume 31, Issue 18 (2021)
- Year:
- 2021
- Volume:
- 31
- Issue:
- 18
- Issue Sort Value:
- 2021-0031-0018-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-02-23
- Subjects:
- density functional theory -- electrocatalysts -- hydrogen evolution reaction -- machine learning -- single‐atom catalysts
Materials -- Periodicals
Chemical vapor deposition -- Periodicals
620.11 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1616-3028 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adfm.202100547 ↗
- Languages:
- English
- ISSNs:
- 1616-301X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.853900
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24151.xml