Mechanisms of strength, thermal stability, and doping effects in metal-doped bilayer borophene for energy storage applications using a DFT-trained deep-learning potential
DFT-trained deep-learning potentials are used to uncover how Al and Ru dopants tune strength and structural transition temperatures in bilayer borophene, guiding design for robust 2D devices.
Authors
- Chen Hsing-Yin
- Hsin‐Tsung Chen (ORCID: https://orcid.org/0000-0002-1419-8324)
- Sheng Ju
- Hui-Lung Chen
- An-Zhi Lin
- Shan-Han Lo
Institutions
- National Sun Yat-sen University (TW)
- Chung Yuan Christian University (TW)
- Kaohsiung Medical University (TW)
- Chinese Culture University (TW)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1039/d5ta08592f
- Primary Topic
- Boron and Carbon Nanomaterials Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00