2 papers
cond-mat.mtrl-sci2026
Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates
Zeyu Wang, Shuya Yamazaki, Martin Hoffmann Petersen +11
The appearance of generative models has opened vast chemical spaces in the design of functional materials. Although machine learning interatomic potentials (MLIPs) have substantial…
cond-mat.mtrl-sci2026
SWORD: Symmetry and Wyckoff-sequence of Ordered and Disordered crystals
Yuyao Huang, Wei Nong, Shuya Yamazaki +4
Novelty in materials discovery requires candidates to be distinct, non-redundant, and thermodynamically plausible. While crystallographic databases continue to expand in both size…