Difference between Metal-S and Metal-O Bond Orders: A Descriptor of Oxygen Evolution Activity for Isolated Metal Atom-Doped MoS2 Nanosheets
Exploration of predictive descriptors for the performance of electrocatalytic oxygen evolution reaction (OER) is significant for material development in many energy conversion processes. In this work, we used high-throughput density functional theory (DFT) calculations to systematically investigate...
Saved in:
Published in | iScience Vol. 20; pp. 481 - 488 |
---|---|
Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Inc
25.10.2019
Elsevier |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Exploration of predictive descriptors for the performance of electrocatalytic oxygen evolution reaction (OER) is significant for material development in many energy conversion processes. In this work, we used high-throughput density functional theory (DFT) calculations to systematically investigate the OER performance of thirty kinds of isolated transition metal atoms-doped ultrathin MoS2 nanosheets (M-UMONs). The results showed that the OER activity could be a function of the decorated transition metal-sulfur (M-S) bond orders with a volcanic-shaped correlation, and a strong correlation could be found when the difference of the M-S bond orders and corresponding metal-oxygen (M-O) bond orders were taken into consideration, implying that the difference in M-S and M-O bond orders could be a predictive descriptor of OER activity for M-UMON system. This successful result also implies this calculation-based method for the exploring of descriptors would also provide a new promising avenue for the discovery of high-performance OER catalysts.
[Display omitted]
•A predictive descriptor of OER activity for M-UMONs was proposed•Calculation and experiments were combined to explore the descriptor•A series of monatomic catalyst was prepared via a universal method•High-throughput calculation was applied to shorten the development cycle
Computational Chemistry; Nanomaterials; Energy Materials |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Lead Contact These authors contributed equally |
ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2019.10.001 |