collaborators

8 papers

cs.CL2026

Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery

Yunze Jia, Yuehui Xian, Yangyang Xu +5

We present a framework for generating universal semantic embeddings of chemical elements to advance materials inference and discovery. This framework leverages ElementBERT, a domai…

cond-mat.mtrl-sci2026

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…

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…