Research Highlights

Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations

Comput. Phys. Commun. 314, 109654 (2025)

Probing Iron in Earth’s Core with Molecular-Spin Dynamics

Proc. Natl. Acad. Sci. 121, e2408897121 (2024)

Bridging the Gap in Electronic Structure Calculations via Machine Learning

Nat. Comput. Sci. 4, 729 (2024)

Inverting the Kohn–Sham Equations with Physics-Informed Machine Learning

Mach. Learn. Sci. Technol. 5 015050 (2024)

Predicting Electronic Structures at Any Length Scale with Machine Learning

npj Comput. Mater. 9, 115 (2023)

Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry

Phys. Rev. Mater. 6, 040301 (2022)

Data-Driven Magneto-Elastic Predictions with Scalable Classical Spin-Lattice Dynamics

npj Comput. Mater. 7, 153 (2021)