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LLM-driven discovery for carbon allotropes with bond-network entropy
Yuzhou Hao, Yujie Liu, Xuejie Li +4
The discovery of novel carbon allotropes with tailored thermal and mechanical properties is critical for advanced thermal management. However, exploring the vast configurational sp…
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…
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…
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…
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…
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…