196 citations · 198 across the 5 of their papers we have counts for
5 papers
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…
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 syste…
BN-embedded monolayer graphene with tunable electronic and topological properties
Chih-Piao Chuu, Wei-En Tseng, Kuan-Hung Liu +2
Finding an effective and controllable way to create a sizable energy gap in graphene-based systems has been a challenging topic of intensive research. We propose that the hybrid of…
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…
Stability and electronic properties of two-dimensional silicene and germanene on graphene
Yongmao Cai, Chih-Piao Chuu, C. M. Wei +1
We present first-principles calculations of silicene/graphene and germanene/graphene bilayers. Various supercell models are constructed in the calculations in order to reduce the s…