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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.
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.
Machine Learning Guided Design of Single–Phase Hybrid Lead Halide White Phosphors
Yuan, Hailong (Autor:in) / Qi, Luyuan (Autor:in) / Paris, Michael (Autor:in) / Chen, Fei (Autor:in) / Shen, Qiang (Autor:in) / Faulques, Eric (Autor:in) / Massuyeau, Florian (Autor:in) / Gautier, Romain (Autor:in)
Advanced Science ; 8
01.10.2021
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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