aceMachine learning insights into band gap properties in halide-based perovskites
Halide perovskites show great promise for applications in optoelectronic devices. The lead-free perovskites are attracting increasing interest due to their low toxicity and motivate the exploration of alternative compositions and structures, including A 2 BX 6 , A 2 BB'X 6 , A 3 B 2 X 9 , and A 4 BX 6 . Accurate predictions of a wide range of band gap energies are important for designing new materials. It is also important to generate a direct relationship between the structural and elemental descriptors and the…
Ensemble tree-based machine learning models predicted band gap energies across multiple halide perovskite families with strong accuracy and identified B-site and X-site properties as key descriptors to guide design of new low-toxicity materials for optoelectronics.
Evidence
- Peer-reviewedPhysical Chemistry Chemical Physics2026-09-08
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Truvace Impact Record TRV-2026-1028, v1: “Machine learning insights into band gap properties in halide-based perovskites.” Truvace, 2026-09-09. /record/TRV-2026-1028 (accessed at citation time). sha256 2918ed37739b9e4d…
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