Machine Learning Guided Design of Single-Phase Hybrid Lead Halide White Phosphors

Designing new single-phase white phosphors for solid-state lighting is a challenging trial-error process as it requires to navigate in a multidimensional space (composition of the host matrix/dopants, experimental conditions, etc.). Thus, no single-phase white phosphor has ever been reported to exhibit both a high color rendering index (CRI - degree to which objects appear natural under the white illumination) and a tunable correlated color temperature (CCT). In this article, a novel strategy consisting in iterating syntheses, characterizations, and machine learning (ML) models to design such white phosphors is demonstrated. With the guidance of ML models, a series of luminescent hybrid lead halides with ultra-high color rendering (above 92) mimicking the light of the sunrise/sunset (CCT = 3200 K), morning/afternoon (CCT = 4200 K), midday (CCT = 5500 K), full sun (CCT = 6500K), as well as an overcast sky (CCT = 7000 K) are precisely designed.

Automated summary

Designing new single-phase white phosphors for solid-state lighting is a challenging trial-error process that requires navigation in a multidimensional space. With the guidance of machine learning models, a series of luminescent hybrid lead halides with ultra-high color rendering have been precisely designed.