10 papers
Spinel nitride solid solutions: charting properties in the configurational space with explainable machine learning
Pablo Sánchez-Palencia, Said Hamad, Pablo Palacios +2
Ab initio prediction of the variation of properties in the configurational space of solid solutions is computationally very demanding. We present an approach to accelerate these pr…
Distributed Representations of Atoms and Materials for Machine Learning
Luis M. Antunes, Ricardo Grau-Crespo, Keith T. Butler
The use of machine learning is becoming increasingly common in computational materials science. To build effective models of the chemistry of materials, useful machine-based repres…
Engineering the electronic and optical properties of 2D porphyrin paddlewheel metal-organic frameworks
Victor Posligua, Dimpy Pandya, Alex Aziz +4
Metal organic frameworks (MOFs) are promising photocatalytic materials due to their high surface area and tuneability of their electronic structure. We discuss here how to engineer…
Mixing thermodynamics and photocatalytic properties of GaP-ZnS solid solutions
Joel Shenoy, Judy N. Hart, Ricardo Grau-Crespo +2
Preparation of solid solutions represents an effective means to improve the photocatalytic properties of semiconductor-based materials. Nevertheless, the effects of site-occupancy…
Electron and phonon interactions and transport in ultra-high-temperature ceramic ZrC
Thomas A. Mellan, Alex Aziz, Yi Xia +2
We have simulated the ultra-high-temperature ceramic zirconium carbide (ZrC) in order to predict electron and phonon scattering properties, including lifetimes and transport. Our p…
The origin of the vanadium dioxide transition entropy
Thomas Ambrose Mellan, Hao Wang, Udo Schwingenschlögl +1
The reversible metal-insulator transition in VO at K has been closely scrutinized yet its thermodynamic origin remains ambiguous. We discuss the origin…