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Defect formation in CsSnI <sub>3</sub> from density functional theory and machine learning

Chadawan Khamdang, Mengen Wang

2025Journal of Materials Chemistry C11 citationsDOIOpen Access PDF

Abstract

This study used density functional theory calculations to identify dopants that suppress the p-type self-doping of CsSnI 3 . Machine learning algorithms are used to predict the defect formation energetics from elemental features of the dopants.

Topics & Concepts

Density functional theoryMaterials scienceCondensed matter physicsPhysicsQuantum mechanicsPerovskite Materials and ApplicationsMachine Learning in Materials ScienceAdvanced Semiconductor Detectors and Materials
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