Vaidish Sumaria

University of California, Los Angeles — United States

Materials Science · Physical Sciences

8h-index375citations16works16.02yr avg
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Research Topics

Machine Learning in Materials Science(9), Catalytic Processes in Materials Science(6), Electrocatalysts for Energy Conversion(5), CO2 Reduction Techniques and Catalysts(5), Electrochemical Analysis and Applications(4)

Publications16 total

Structure Sensitivity and Catalyst Restructuring for CO2 Electro-reduction on Copper
Nature Communications·2025· 55 citedOpen Access
Structure Sensitivity and Catalyst Restructuring for CO2 Electro-reduction on Copper
2024· 2 cited
Machine Learning, Density Functional Theory, and Experiments to Understand the Photocatalytic Reduction of CO<sub>2</sub> on CuPt/TiO<sub>2</sub>
The Journal of Physical Chemistry C·2024· 16 cited
Structure Sensitivity and Catalyst Restructuring for CO2 Electro-reduction on Copper
2024· 4 citedOpen Access
Machine Learning, Density Functional Theory, and Experiments to Understand the Photocatalytic Reduction of CO$_2$ by CuPt/TiO$_2$
arXiv (Cornell University)·2024· 3 citedOpen Access
Generation of Thermodynamically Favorable Crystal Structures of Pb_{10-x}Cu_x(PO4)6O using Atom Combinatorics Approach
2023Open Access
Atomic-Scale Mechanism of Platinum Catalyst Restructuring under a Pressure of Reactant Gas
Journal of the American Chemical Society·2022· 49 citedOpen Access
Atomic scale mechanism of platinum catalystrestructuring under a pressure of reactant gas
2022· 1 citedOpen Access
Atomic scale mechanism of Pt catalyst restructuring under a pressure of gas
2022Open Access
CO organization at ambient pressure on stepped Pt surfaces: first principles modeling accelerated by neural networks
Chemical Science·2021· 29 citedOpen Access
Optimal Packing of CO at High Coverage on Pt(100) and Pt(111) Surfaces
eScholarship (California Digital Library)·2020Open Access
Optimal Packing of CO at a High Coverage on Pt(100) and Pt(111) Surfaces
ACS Catalysis·2020· 37 cited
Quantifying robustness of DFT predicted pathways and activity determining elementary steps for electrochemical reactions
The Journal of Chemical Physics·2018· 21 cited
Quantifying Confidence in DFT Predicted Surface Pourbaix Diagrams and Associated Reaction Pathways for Chlorine Evolution
ACS Catalysis·2018· 100 citedOpen Access
Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions
The Journal of Physical Chemistry Letters·2018· 58 citedOpen Access
Self-Formed Catalysts Using Electrochemical (de)Lithiation for Oxygen Evolution Reaction 
ECS Meeting Abstracts·2017

Frequent Co-authors

Philippe Sautet(8), Dilip Krishnamurthy(4), Venkatasubramanian Viswanathan(4), Franklin Tao(4), Dongfang Cheng(3), Khanh‐Ly C. Nguyen(3), Ziyang Wei(3), Zisheng Zhang(3), Winston Gee(3), Yichen Li(3), Carlos G. Morales‐Guio(3), Markus Heyde(3), Beatriz Roldán Cuenya(3), Anastassia N. Alexandrova(3), Takat B. Rawal(3), Young Feng Li(3), David E. Sommer(3), Jake Vikoren(3), Deeptanshu Prasad(3), Luan Nguyen(2)