Practical Models for Predicting the Emission Peak Wavelengths of Inorganic Phosphors Based on Stoichiometric Information

Nakano, Hiroshi; Tanaka, Kenichi; Miyao, Tomoyuki; Funatsu, Kimito; Shirasawa, Raku; Tomiya, Shigetaka

doi:10.1246/cl.170611

Cited by 5 publications

(15 citation statements)

References 15 publications

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“…The final material features were constructed by mathematical operators (Max., Min., Avg., and Std.) as formulae – based on the above elemental features. , where P i is the property of the i th element in the compound and x i is the corresponding stoichiometry coefficient. In addition, the tolerance factor of the garnet structure proposed by Liu was added for describing the structural information.…”

Section: Strategymentioning

confidence: 99%

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Jiang

Zhang

et al. 2022

ACS Appl. Mater. Interfaces

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Ce-doped garnet phosphors play an important role in the white light-emitting diode (LED) family. In the past years, a lot of trial-and-error experiments guided by experience to discover phosphors suitable for white LEDs have been presented. The working temperature of phosphors may reach 200 °C in white LEDs, and so, the exploration of phosphors with excellent thermal stability at the desired wavelength continues to be a challenge. In the present study, to discover novel cyan−green garnet:Ce phosphors, wavelength and thermal stability machine learning models were built by constructing reasonable features. Among the 171,636 compounds with garnet structures predicted by our models, 25 samples were selected for preparation and characterization by multiobjective optimization based on active learning.

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Section: Strategymentioning

confidence: 99%

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Jiang

Zhang

et al. 2022

ACS Appl. Mater. Interfaces

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“…Recently, data-driven approaches have been reported for the rapid discovery and development of new phosphors using screening of materials databases, high-throughput density functional theory (DFT) calculations, and machine learning on luminescence properties. [5][6][7][8][9][10] The emission spectrum is one of the most important characteristics of phosphors because it determines their luminescence color. The emission spectrum is often characterized by its peak top and full width at half maximum (FWHM).…”

Section: Introductionmentioning

confidence: 99%

Rapid discovery of new Eu²⁺-activated phosphors with a designed luminescence color using a data-driven approach

Koyama

Ikeno²,

Harada

et al. 2023

Mater. Adv.

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“…PersL materials. [119][120][121] For such a single system, the constructed prediction model of the lifetime using ML techniques seems reliable. [118] However, in terms of other PersL materials, very little information is available.…”

Section: Introduction Of Materials Designing Toolsmentioning

confidence: 99%

Emerging Ultraviolet Persistent Luminescent Materials

Wang

Mao

2022

Advanced Optical Materials

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Ultraviolet (UV, 200–400 nm) persistent luminescence (PersL) is an emerging topic of luminescent materials due to their “self‐sustainable” high‐photon‐energy characteristics. Although the family of UV PersL materials is fast‐growing, especially in the past few years, an overview on the current status in terms of material development, mechanism investigation, promising applications, research challenges, future directions, and the correlations of these aspects is absent. Many potential applications of UV PersL have recently been demonstrated and proposed depending on where UV PersL falls in the UVA (315–400 nm), UVB (280–315 nm), or UVC (200–280 nm) range. Hence, here the state‐of‐the‐art UV PersL materials, the theoretical and experimental attempts and explanations of UV PersL mechanisms, and strategies utilized to improve UV PersL performance are summarized. Also their unprecedented application promises spanning “solar‐blind” tagging (“glow‐in‐the‐bright” tagging), persistent disinfection, persistent photocatalysis, and “device‐free” skin phototherapy that are beyond the capabilities of the “glow‐in‐the‐dark” visible and infrared PersL are discussed. Facing challenges in understanding their complicated mechanisms, meeting their high charging requirement, and easing the public concerns, a bright future for UV PersL materials from lab to market is envisaged.

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Practical Models for Predicting the Emission Peak Wavelengths of Inorganic Phosphors Based on Stoichiometric Information

Cited by 5 publications

References 15 publications

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Rapid discovery of new Eu²⁺-activated phosphors with a designed luminescence color using a data-driven approach

Emerging Ultraviolet Persistent Luminescent Materials

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Practical Models for Predicting the Emission Peak Wavelengths of Inorganic Phosphors Based on Stoichiometric Information

Cited by 5 publications

References 15 publications

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Multiobjective Machine Learning-Assisted Discovery of a Novel Cyan–Green Garnet: Ce Phosphors with Excellent Thermal Stability

Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color using a data-driven approach

Emerging Ultraviolet Persistent Luminescent Materials

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Rapid discovery of new Eu²⁺-activated phosphors with a designed luminescence color using a data-driven approach