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cond-mat.mtrl-sci2026
Machine-learning octet -type binary compounds across chemical space with domain knowledge of the interatomic bond
Rohan Kumar, Mariano D. Forti, Aakash A. Naik +2
The prediction of the structural stability of octet -type binary compounds is a classical materials informatics problem. The challenge is to capture the relative stability of 4…
cond-mat.mtrl-sci2026
A critical assessment of bonding descriptors for predicting materials properties
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen +4
Most machine learning models for materials science rely on descriptors based on materials compositions and structures, even though the chemical bond has been proven to be a valuabl…
cond-mat.mtrl-sci2025
Thermal Transport in Ag8TS6 (T= Si, Ge, Sn) Argyrodites: An Integrated Experimental, Quantum-Chemical, and Computational Modelling Study
Joana Bustamante, Anupama Ghata, Aakash A. Naik +4
Argyrodite-type Ag-based sulfides combine exceptionally low lattice thermal and high ionic conductivity, making them promising candidates for thermoelectric and solid-state energy…