10 citations · 19 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…