Anuj Goyal

National Renewable Energy Laboratory — United States

Materials Science · Physical Sciences

16h-index1.5kcitations52works1.52yr avg
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Research Topics

Machine Learning in Materials Science(16), Electronic and Structural Properties of Oxides(8), Chalcogenide Semiconductor Thin Films(7), Chemical Looping and Thermochemical Processes(7), Perovskite Materials and Applications(6)

Publications52 total

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks
Materials Horizons·2025· 1 cited
Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks
2025Open Access
(<i>Invited) </i>Development of Machine Learned Compounds and Evaluation Protocols for Solar Thermochemical Hydrogen Production
ECS Meeting Abstracts·2025
(<i>Invited) </i>Structure-Property Defect Models for Materials Discovery in Clean Energy Applications
ECS Meeting Abstracts·2025
Interlayer Ions Control Spin Canting in Low-Dimensional Manganese Trimers in 12R-Ba<sub>4</sub><i>M</i>Mn<sub>3</sub>O<sub>12</sub> (<i>M</i> = Ce, Pr) Layered Perovskites
Inorganic Chemistry·2024· 1 citedOpen Access
Evaluation of Ba(Al,Fe)2O4, a Machine Learned Compound, for Solar Thermochemical Hydrogen Production
2024Open Access
Materials discovery for high-temperature clean-energy applications via defect graph neural networks
2024Open Access
Predicting Thermochemical Equilibria with Interacting Defects: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi>Sr</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mi>Ce</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:msub><mml:mrow><mml:mi>Mn</mml:mi><mml:mi mathvariant="normal">O</mml:mi></mml:mrow><mml:mrow><mml:mn>3</mml:mn><mml:mo>−</mml:mo><mml:mi>δ</mml:mi></mml:mrow></mml:msub></mml:math> Alloys for Water Splitting
PRX Energy·2024· 10 citedOpen Access
LaMnO<sub>3</sub> Dopants for Efficient Thermochemical Water Splitting Identified by Density Functional Theory Calculations
The Journal of Physical Chemistry C·2023· 8 citedOpen Access
Defect graph neural networks for materials discovery in high-temperature clean-energy applications
Nature Computational Science·2023· 59 citedOpen Access
From data-driven modeling to systems level co-design: progress in materials discovery and optimization for hydrogen storage and generation
2023Open Access
A database of vacancy formation enthalpies for materials discovery
Zenodo (CERN European Organization for Nuclear Research)·2023Open Access
A database of vacancy formation enthalpies for materials discovery
2023· 3 citedOpen Access
Investigating the Electronic Structure of Prospective Water-Splitting Oxide BaCe<sub>0.25</sub>Mn<sub>0.75</sub>O<sub>3−δ</sub> before and after Thermal Reduction
Chemistry of Materials·2023· 3 citedOpen Access
Materials discovery for high-temperature, clean-energy applications using graph neural network models of vacancy defects and free-energy calculations
2023· 2 citedOpen Access
Sampling and screening approaches for imperfect materials: Defects and incommensurate interfaces
2023Open Access
Graph Neural Network Modeling of Vacancy Formation for Materials Discovery in Solar Thermochemical Water Splitting.
2022Open Access
Graph neural network modeling of vacancy formation enthalpy for materials discovery and its application in solar thermochemical water splitting
2022· 3 citedOpen Access
A database of vacancy formation enthalpies for materials discovery
Zenodo (CERN European Organization for Nuclear Research)·2022· 1 citedOpen Access
CSD 2144499: Experimental Crystal Structure Determination
The Cambridge Structural Database·2022Open Access
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Frequent Co-authors

Stephan Lany(25), Vladan Stevanović(16), Matthew Witman(16), Anthony H. McDaniel(16), Tadashi Ogitsu(15), Simon R. Phillpot(8), Prashun Gorai(7), Eric S. Toberer(6), Aleksandr Chernatynskiy(6), Nicholas A. Strange(6), Robert Bell(6), Eric N. Coker(6), Blas P. Uberuaga(5), James Eujin Park(5), Sarah Shulda(5), David S. Ginley(5), Andrew J. E. Rowberg(5), Sean R. Bishop(5), Kevin H. Stone(4), Shijing Sun(4)