Funding for this research was provided by:
Engineering and Physical Sciences Research Council (EP/L015862/1)
Science and Engineering Research Council (A1898b0043)
Article Title: Machine learning-assisted cross-domain prediction of ionic conductivity in sodium and lithium-based superionic conductors using facile descriptors
Journal Title: Journal of Physics Communications
Article Type: paper
Copyright Information: © 2020 The Author(s). Published by IOP Publishing Ltd
Publication dates
Date Received: 2019-12-25
Date Accepted: 2020-05-13
Online publication date: 2020-05-25