3 papers
cond-mat.mtrl-sci2026
Equivariant Electronic Hamiltonian Prediction with Many-Body Message Passing
Chen Qian, Valdas Vitartas, James Kermode +1
Machine learning surrogate models of Kohn-Sham Density Functional Theory Hamiltonians provide a powerful tool for accelerating the prediction of electronic properties of materials,…
cond-mat.mtrl-sci2026
Hydrostatic Pressure-enhanced correlated magnetism and Chern insulator in moir'e WSe2
Pengfei Jiao, Chenghao Qian, Ning Mao +24
Moiré semiconductors offer flat bands where Coulomb interactions and band topology intertwine, while interlayer coupling plays a central role in forming the moiré potential. Howe…
cond-mat.mtrl-sci2026
Turning Insulators into Accelerators: Deciphering the Interfacial Conductivity Boost in ZrO2-Li2ZrCl6 Composites through Machine Learning Molecular Dynamics Simulations
Boyuan Xu, Chen Qian, Liyi Bai +3
Halide solid-state electrolytes have emerged as promising candidates for all-solid-state lithium batteries due to their high oxidative stability and deformability, yet their modera…