Machine learning surrogates trained on 1,221 DFT compounds identify five DFT-validated stable lead-free double perovskites from 13,088 candidates using genome-guided descriptors.
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A backward-mapping framework with chemical-genome descriptors and ML reduces 13,088 compositions to seven DFT-validated lead-free double perovskite candidates with phase stability and functional electronic properties.
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Genome-Guided Interpretable Screening of Phase-Stable, Lead-Free Double Perovskite Absorbers for All-Inorganic Semiconductors, Sensors, and Photovoltaics with DFT-Validated Design Rules
Machine learning surrogates trained on 1,221 DFT compounds identify five DFT-validated stable lead-free double perovskites from 13,088 candidates using genome-guided descriptors.
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Backward Mapping from Device Targets to Chemical Genomes for Interpretable Discovery of Phase-Stable Lead-Free Double Perovskites with DFT-Validated Design Rules
A backward-mapping framework with chemical-genome descriptors and ML reduces 13,088 compositions to seven DFT-validated lead-free double perovskite candidates with phase stability and functional electronic properties.