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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.mtrl-sci2022
Creating a Nanoscale Lateral Heterojunction in a Semiconductor Monolayer with a Large Built-in Potential
Madisen Holbrook, Yuxuan Chen, Hyunsue Kim +6
The ability to engineer atomically thin nanoscale lateral heterojunctions (HJs) is critical to lay the foundation for future two-dimensional (2D) device technology. However, the tr…