Mapping causal pathways with structural modes fingerprint for perovskite oxides

Ghosh, Ayana; Ghosh, Saurabh

doi:10.1088/2632-2153/ad7d5e

Title: Mapping causal pathways with structural modes fingerprint for perovskite oxides

Journal Article · 11 October 2024 · Machine Learning: Science and Technology

DOI: https://doi.org/10.1088/2632-2153/ad7d5e · OSTI ID:2462830

; Ghosh, Saurabh

Abstract Causality is innate to the determination of the fundamental mechanism controlling any physical phenomena. However, combining causality within the standard practices of computational modelling to understand structure-functionality connections is extremely rare. This work proposes a fingerprint based on key structural modes for ABO ₃ -type perovskite oxides and its derivatives, combined with causal models, for predicting Kohn–Sham energies. Our study of causal models captures the inherent coupling between structural modes such as rotation, tilt and antiferroelectric displacements, responsible for phase transition, polarization, magnetization and metal–insulator transition, exhibited by these materials. Although developed for modelling specific functionality, this method is universally applicable to derive other functionalities and even different material classes while tracking hidden causal mechanisms via structural distortions.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2462830

Journal Information:: Machine Learning: Science and Technology, Journal Name: Machine Learning: Science and Technology Journal Issue: 4 Vol. 5; ISSN 2632-2153

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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