The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Chemical Pressure-Driven Enhancement of the Hydrogen Evolving Activity of Ni2P from Nonmetal Surface Doping Interpreted via Machine Learning
Open accessAbstract
The activity of Ni 2 P catalysts for the hydrogen evolution reaction (HER) is currently limited by strong H adsorption at the Ni 3 -hollow site. We investigate the effect of surface nonmetal doping on the HER activity of the Ni 3 P 2 termination of Ni 2 P(0001), which is stable at modest electrochemical conditions. Using density functional theory (DFT) calculations, we find that both 2 p nonmetals and heavier chalcogens provide nearly thermoneutral H adsorption at moderate surface doping concentrations. We also find, however, that only chalcogen substitution for surface P is exergonic. For intermediate surface concentrations of S, the free energy of H adsorption at the Ni 3 -hollow site is −0.11 eV, which is significantly more thermoneutral than the undoped surface (−0.45 eV). We use the regularized random forest machine learning algorithm to discover the relative importance of structure and charge descriptors, extracted from the DFT calculations, in determining the HER activity of Ni 2 P(0001) under different doping concentrations. We discover that the Ni–Ni bond length is the most important descriptor of HER activity, which suggests that the nonmetal dopants induce a chemical pressure-like effect on the Ni 3 -hollow site, changing its reactivity through compression and expansion.
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Identification of Active Edge Sites for Electrochemical H 2 Evolution from MoS 2 Nanocatalysts
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Nanostructured Nickel Phosphide as an Electrocatalyst for the Hydrogen Evolution Reaction
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Plasma-Assisted Synthesis of NiCoP for Efficient Overall Water Splitting
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A Critical Review of Machine Learning of Energy Materials
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Metadata
- Authors
- Wexler, R. B., Martirez, J. M. P., & Rappe, A. M.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-03-19
- Volume
- 140
- Issue
- 13
- Pages
- 4678-4683
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2791210137
- Cited by
- 207
- References
- 7
- FWCI
- 4.58
- Type
- journal article
- Language
- en
- Open access
- green
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