3 papers
cond-mat.supr-con2026
Machine learning reveals common features of unconventional superconductors with high transition temperatures
Haosheng Xu, Dongheng Qian, Yijun Yu +1
Superconductors with high critical temperatures that emerges beyond the phonon-mediated regime are usually considered unconventional in nature, yet unlike conventional superconduct…
cond-mat.mtrl-sci2025
Design Topological Materials by Reinforcement Fine-Tuned Generative Model
Haosheng Xu, Dongheng Qian, Zhixuan Liu +2
Topological insulators (TIs) and topological crystalline insulators (TCIs) are materials with unconventional electronic properties, making their discovery highly valuable for pract…
cond-mat.mtrl-sci2024
Predicting Many Crystal Properties via an Adaptive Transformer-based Framework
Haosheng Xu, Dongheng Qian, Jing Wang
Machine learning has revolutionized many fields, including materials science. However, predicting properties of crystalline materials using machine learning faces challenges in inp…