Predicted Optimal Bifunctional Electrocatalysts for the Hydrogen Evolution Reaction and the Oxygen Evolution Reaction Using Chalcogenide Heterostructures Based on Machine Learning Analysis of in Silico Quantum Mechanics Based High Throughput Screening
- Award ID(s):
- 1805022
- NSF-PAR ID:
- 10275132
- Date Published:
- Journal Name:
- The Journal of Physical Chemistry Letters
- Volume:
- 11
- Issue:
- 3
- ISSN:
- 1948-7185
- Page Range / eLocation ID:
- 869 to 876
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1021/acs.jpclett.9b03875
