Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions. Bilayer 2D material stacking is essential for exploring new materials with novel functions and inherent phenomena, enabling the creation of new 2D bilayers for diverse real-world applications. Research on bilayer vdWs materials has made significant progress from experimental and computational perspectives. Various bilayer materials have been successfully synthe sized experimentally and the increasing utilization of high-throughput computing technology has con structed several computational two-dimensional materials databases. However, the ...
| Authors | An Vuong, Minh-Hao Van, Chen Zhao et al. |
|---|---|
| Primary category | cs.AI |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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