Machine Learning for Materials Design
(Cangi Lab)
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Research Highlights
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
Comput. Phys. Commun. 314, 109654 (2025)
May, 2025
Probing Iron in Earth’s Core with Molecular-Spin Dynamics
Proc. Natl. Acad. Sci. 121, e2408897121 (2024)
Dec, 2024
Bridging the Gap in Electronic Structure Calculations via Machine Learning
Nat. Comput. Sci. 4, 729 (2024)
Oct, 2024
Inverting the Kohn–Sham Equations with Physics-Informed Machine Learning
Mach. Learn. Sci. Technol. 5 015050 (2024)
Mar, 2024
Predicting Electronic Structures at Any Length Scale with Machine Learning
npj Comput. Mater. 9, 115 (2023)
Jun, 2023
Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry
Phys. Rev. Mater. 6, 040301 (2022)
Apr, 2022
Data-Driven Magneto-Elastic Predictions with Scalable Classical Spin-Lattice Dynamics
npj Comput. Mater. 7, 153 (2021)
Sep, 2021
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