23 citations · 80 across the 12 of their papers we have counts for
13 papers
Four-phonon scattering and coherent heat transport in ultrawide-bandgap SrSnO3
Xuejie Li, Xiaoying Wang, Shengying Yue +4
SrSnO3 is a promising ultrawide-bandgap perovskite oxide whose thermal transport is governed by structural distortions and anharmonic lattice dynamics. Here, we investigate the lat…
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 int…
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…
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…
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 are…
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…
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…
An interpretable formula for lattice thermal conductivity of crystals
Xiaoying Wang, Guoyu Shu, Guimei Zhu +5
Lattice thermal conductivity (kL) is a crucial physical property of crystals with applications in thermal management, such as heat dissipation, insulation, and thermoelectric energ…
Bonding Hierarchy and Coordination Interaction Leading to High Thermoelectricity in Wide Bandgap TlAgI2
Xiaoying Wang, Mengyang Li, Minxuan Feng +6
High thermoelectric properties are associated with the phonon-glass electron-crystal paradigm. Conventional wisdom suggests that the optimal bandgap of semiconductor to achieve the…
Machine learning for predicting ultralow thermal conductivity and high ZT in complex thermoelectric materials
Yuzhou Hao, Yuting Zuo, Jiongzhi Zheng +7
Efficient and precise calculations of thermal transport properties and figure of merit, alongside a deep comprehension of thermal transport mechanisms, are essential for the practi…
Anomalous thermal conductivity in 2D silica nanocages of immobilizing noble gas atom
Yang Wang, Zhibin Gao, Xiaoying Wang +6
Noble gas atoms such as Kr and Xe are byproducts of nuclear fission in nuclear plants. How to trap and confine these volatile even radioactive gases is particularly challenging. Re…