Sudarshan Vijay

VASP Software (Austria) — Austria

Energy · Physical Sciences

16h-index2.1kcitations67works6.72yr avg
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Research Topics

Electrocatalysts for Energy Conversion(26), Machine Learning in Materials Science(20), CO2 Reduction Techniques and Catalysts(17), Advanced Chemical Physics Studies(13), Catalytic Processes in Materials Science(12)

Publications67 total

Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation
Physical review. B./Physical review. B·2025· 2 citedOpen Access
Efficient periodic density functional theory calculations of charged molecules and surfaces using Coulomb kernel truncation
arXiv (Cornell University)·2025· 2 citedOpen Access
Ethylene Carbonate Oxidation Due to Reactive Oxygen Species Near the Cathode: Insights from High-Throughput DFT Calculations and Monte Carlo Simulations
ECS Meeting Abstracts·2024
Decomposition of Electrolyte Solutions at Positive Electrodes
ECS Meeting Abstracts·2024
Benchmarking water adsorption on metal surfaces with <i>ab initio</i> molecular dynamics
The Journal of Chemical Physics·2024· 16 cited
On the Thermodynamic Equivalence of Grand Canonical, Infinite‐Size, and Capacitor‐Based Models in First‐Principle Electrochemistry
ChemPhysChem·2024· 18 citedOpen Access
Benchmarking water adsorption on metal surfaces with ab-initio molecular dynamics
2024· 2 citedOpen Access
A Critical Analysis of Chemical and Electrochemical Oxidation Mechanisms in Li-Ion Batteries
The Journal of Physical Chemistry Letters·2024· 21 citedOpen Access
Author response for "&lt;i&gt;CoeffNet&lt;/i&gt;: predicting activation barriers through a chemically-interpretable, equivariant and physically constrained graph neural network"
2024
Author response for "&lt;i&gt;CoeffNet&lt;/i&gt;: predicting activation barriers through a chemically-interpretable, equivariant and physically constrained graph neural network"
2024
Characterization of adsorption sites on IrO<sub>2</sub><i>via</i> temperature programmed O<sub>2</sub> desorption simulations
Physical Chemistry Chemical Physics·2024· 8 cited
<i>CoeffNet</i> : predicting activation barriers through a chemically-interpretable, equivariant and physically constrained graph neural network
Chemical Science·2024· 11 citedOpen Access
A critical analysis of chemical and electrochemical oxidation mechanisms in Li-ion batteries
2023Open Access
On the equivalence of grand-canonical and capacitor-based models in first-principle electrochemistry
2023Open Access
Author response for "&lt;i&gt;CoeffNet&lt;/i&gt;: predicting activation barriers through a chemically-interpretable, equivariant and physically constrained graph neural network"
2023
Number of sites‐based solver for determining coverages from steady‐state mean‐field micro‐kinetic models
Journal of Computational Chemistry·2023· 4 citedOpen Access
A critical analysis of chemical and electrochemical oxidation mechanisms in Li-ion batteries
2023Open Access
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
Nature Reviews Physics·2023· 64 citedOpen Access
A database of molecular properties integrated in the Materials Project
2023Open Access
Author response for "A database of molecular properties integrated in the Materials Project"
2023
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Frequent Co-authors

Karen Chan(26), Georg Kastlunger(14), Kristin A. Persson(11), Henrik H. Kristoffersen(10), Evan Walter Clark Spotte‐Smith(9), Hendrik H. Heenen(7), Yu Katayama(7), Yang Shao‐Horn(7), Ib Chorkendorff(7), Brian Seger(7), Sven Brückner(5), Peter Strasser(5), Jens K. Nørskov(5), Wen Ju(4), Joseph A. Gauthier(4), Georg Kresse(4), Martijn Marsman(4), Orion Cohen(4), Samuel M. Blau(4), Jason M. Munro(4)