65 citations · 65 across the 3 of their papers we have counts for
6 papers
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…
Modelling the dielectric constants of crystals using machine learning
Kazuki Morita, Daniel W. Davies, Keith T. Butler +1
The relative permittivity of a crystal is a fundamental property that links microscopic chemical bonding to macroscopic electromagnetic response. Multiple models, including analyti…
Metal-free perovskites for non-linear optical materials
Thomas W. Kasel, Zeyu Deng, Austin M. Mroz +3
We identify the existence of nonlinear optical (NLO) activity in a number of novel -type metal-free perovskites, where is a highly tuneable organic cation, is a NH$_…
Finding a junction partner for candidate solar cell absorbers enargite and bournonite from electronic band and lattice matching
Suzanne K. Wallace, Keith T. Butler, Yoyo Hinuma +1
An essential step in the development of a new photovoltaic (PV) technology is choosing appropriate electron and hole extraction layers to make an efficient device. We recently prop…
Quick-start guide for first-principles modelling of semiconductor interfaces
Ji-Sang Park, Young-Kwang Jung, Keith T. Butler +1
Interfaces between dissimilar materials control the transport of energy in a range of technologies including solar cells (electron transport), batteries (ion transport), and thermo…
Band Engineering of Carbon Nitride Monolayers by N-type, P-type, and Isoelectronic Doping for Photocatalytic Applications
Meysam Makaremi, Sean Grixti, Keith T. Butler +2
Since hydrogen fuel involves the highest energy density among all fuels, production of this gas through the solar water splitting approach has been suggested as a green remedy for…