collaborators

6 papers

cond-mat.mtrl-sci2026

Role of octahedral tilting induced acoustic softening on limiting thermal transport in SrSnO3

Yuzhou Hao, Turab Lookman, Xiangdong Ding +2

Octahedral tilting is a fundamental structural distortion in perovskites, governing key phenomena such as lattice stabilizing, soft phonon dynamics, group-theoretical analysis, pha…

cond-mat.mtrl-sci2025

Metavalent Bonding-Induced Phonon Hardening and Giant Anharmonicity in BeO

Xuejie Li, Yuzhou Hao, Yujie Liu +6

The search for materials with intrinsically low thermal conductivity () is critical for energy applications, yet conventional descriptors often fail to capture the complex in…

cond-mat.mtrl-sci2025

Machine learning-driven elasticity prediction in advanced inorganic materials via convolutional neural networks

Yujie Liu, Zhenyu Wang, Hang Lei +6

Inorganic crystal materials have broad application potential due to excellent physical and chemical properties, with elastic properties (shear modulus, bulk modulus) crucial for pr…

cond-mat.supr-con2025

Same-group element replacement enhances superconductivity in clathrate-like YH4

Xuejie Li, Yuzhou Hao, Yujie Liu +5

H3S, LaH10, and hydrogen-based compounds have garnered significant interest due to their high-temperature superconducting properties. However, the requirement for extremely high pr…

cond-mat.mtrl-sci2025

Copper delocalization leads to ultralow thermal conductivity in chalcohalide CuBiSeCl2

Yuzhou Hao, Junwei Che, Xiaoying Wang +5

Mixed anion halide-chalcogenide materials have attracted considerable attention due to their exceptional optoelectronic properties, making them promising candidates for various app…

cond-mat.mtrl-sci2025

PINK: physical-informed machine learning for lattice thermal conductivity

Yujie Liu, Xiaoying Wang, Yuzhou Hao +5

Lattice thermal conductivity () is crucial for efficient thermal management in electronics and energy conversion technologies. Traditional methods for predicting \k{appa}L ar…