7 citations · 7 across the 1 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025★ 7 cited
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al-Fahdi +3
The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces. Whil…
cond-mat.mtrl-sci2024
Accelerating Discovery of Extreme Lattice Thermal Conductivity by Crystal Attention Graph Neural Network (CATGNN) Using Chemical Bonding Intuitive Descriptors
Mohammed Al-Fahdi, Riccardo Rurali, Jianjun Hu +2
Designing materials with targeted lattice thermal conductivity (LTC) demands electronic-level insight into chemical bonding. We introduce two bonding descriptors, namely normalized…