Genome mining in glass chemistry using linear component analysis of ion conductivity data

06 March 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Understanding the multivariate origin of physical properties is particularly complex for polyionic glasses. As a concept, the term genome has been used to describe the entirety of structure-property relations in solid materials, based on functional genes acting as descriptors for a particular property, for example, for input in regression analysis or other machine-learning tools. Here, we present the genes of ionic conductivity in polyionic sodium-conducting glasses as fictive chemical entities with a characteristic stoichiometry, derived from strong linear component analysis (SLCA) of a uniquely consistent dataset. SLCA is based on a twofold optimization problem that maximizes the quality of linear regression between a property (here: ionic conductivity) and champion candidates from all possible combinations of elements. Family trees and matrix rotation analysis are subsequently used to filter for essential elemental combinations, and from their characteristic mean composition, the essential genes. These genes reveal the intrinsic relationships within the multivariate input data. While they do not require a structural representation in real space, we finally demonstrate how possible structural interpretations agree with intuitive understanding of structural entities known from spectroscopic experiments.


genome mining
sodium-ion conduction

Supplementary materials

Supplementary Data
Chemical composition data, ion conductivity data, SLCA parameters


Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.