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Hydrogen Coupling on Platinum Using Artificial Neural Network Potentials and DFT
Peter S Rice, Zhi-Pan Liu, P Hu
School of Chemistry and Chemical Engineering
Research output
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Contribution to journal
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Article
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peer-review
Overview
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Dive into the research topics of 'Hydrogen Coupling on Platinum Using Artificial Neural Network Potentials and DFT'. Together they form a unique fingerprint.
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Engineering & Materials Science
Adsorbates
100%
Platinum
77%
Discrete Fourier transforms
72%
Free energy
52%
Hydrogen
52%
Neural networks
40%
Solvation
35%
Energy barriers
33%
Ions
20%
Catalysts
18%
Substrates
15%
Sampling
15%
Liquids
14%
Chemical Compounds
Gibbs Free Energy
50%
Platinum
48%
Simulation
41%
Liquid-Solid Interface
38%
Hydrogen
33%
Energy Barrier
31%
Solvation
28%
Sampling
27%
Surface
21%
Catalyst
13%
Ion
13%
Time
11%
Physics & Astronomy
platinum
64%
free energy
53%
hydrogen
40%
liquid-solid interfaces
37%
solvation
36%
catalysts
30%
sampling
27%
interactions
26%
simulation
25%
ions
15%