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Anuj Goyal
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Anuj Goyal

Assistant Professor

anujgoyal@msme.iith.ac.in
PhD: University of Florida
Office: MSME 204

Research Interests

First principles electronic structure methods.Thermodynamic modeling of defects in materials.Multiscale Materials Modeling Methods.Machine Learning Approaches to Accelerate Materials Property Prediction.

Selected Publications

A. Goyal, Michael D. Sanders, Ryan P. O’Hayre, and Stephan Lany, “Predicting thermochemical equilibria with interacting defects: Sr1−xCexMnO3−δ alloys for water splitting”, Physical Review X Energy 3, 013008 2024. DOI: 10.1103/PRXEnergy.3.013008.

M. Witman∗ , A. Goyal∗, T. Ogitsu, A. H. McDaniel, and S. Lany, “Defect graph neural networks for materials discovery in high-temperature clean-energy applications”, Nature Computational Science 3, 675-686 2023. DOI:10.1038/s43588-023-00495-2. (∗authors contributed equally.)

A. Goyal, A. Zakutayev, V. Stevanovi´c and S. Lany, “Computational Fermi level engineering and doping-type conversion of Mg:Ga2O3 via three-step synthesis processing”, Journal of Applied Physics 129, 245704 2021. DOI: 10.1063/5.0051788.

A. Goyal, A. Zakutayev, V. Stevanovi´c and S. Lany, “Computational Fermi level engineering and doping-type conversion of Mg:Ga2O3 via three-step synthesis processing”, Journal of Applied Physics 129, 245704 2021. DOI: 10.1063/5.0051788.

A. Goyal, P. Gorai, H. Peng, S. Lany, and V. Stevanovi´c, “A computational framework for au- tomation of point defect calculations”, Computational Materials Science 130, 1-9 2017. DOI: 10.1016/j.commatsci.2016.12.040.

Recent Courses Taught

Electronic Structure and Atomistic Modeling of Materials.
Computational Methods in Materials Science.