249 citations · 291 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
A Quantum-Chemical Bonding Database for Solid-State Materials
Aakash Ashok Naik, Christina Ertural, Nidal Dhamrait +2
An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important…
"Ultima Ratio": Simulating wide-range X-ray scattering and diffraction
Brian R. Pauw, Sofya Laskina, Aakash Naik +4
We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for…