New Publication in Physical Review Letters

02.06.2025

We’re excited to share our latest breakthrough published in Physical Review Letters! Researchers from the University of Vienna, led by Cesare Franchini, have developed a cutting-edge AI-driven approach to simulate polaron dynamics with unprecedented accuracy and scale.

By combining first-principles quantum simulations with a custom machine learning framework—Leopold (Learning of polaron dynamics)—the team has captured how polarons form and move through materials over nanosecond timescales. This work, co-authored with the University of Bologna, unlocks new insights into materials for solar energy, batteries, and next-gen electronics.

“Machine learning isn’t just speeding things up—it’s reshaping how we study quantum systems,” says co-first author Luca Leoni.

Read more:
Birschitzky, V.C., Leoni, L., Reticcioli, M., Franchini, C. Machine Learning Small Polaron Dynamics, Phys. Rev. Lett. 134, 216301 (2025).
DOI: 10.1103/PhysRevLett.134.216301

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