2 papers
cond-mat.mtrl-sci2026
Dynamically training machine-learning-based force fields for strongly anharmonic materials
Martin Callsen, Tai-Ting Lee, Mei-Yin Chou
Machine learning (ML) force fields have emerged as a powerful tool for computing materials properties at finite temperatures, particularly in regimes where traditional phonon-based…
cond-mat.mes-hall2025
Competing interlayer interactions in twisted monolayer-bilayer graphene: From spontaneous electric polarization to quasi-magic angle
Wei-En Tseng, Mei-Yin Chou
The family of moiré materials provides a powerful platform for tuning interlayer couplings via the twist angle in systems with large spatial periodicity. In trilayer graphene syst…