Prediction of metastable energy level distribution of D 3+ (D = Cr and Fe) doped phosphors based on machine learning
Source abstract
Abstract
This paper employs regression models based on machine learning to propose a method for predicting the energy level distribution rules of Cr 3+ and Fe 3+ in various doped crystals.
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Molecular Sensors and Ion Detection · Machine Learning in Materials Science · Advanced Chemical Sensor Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing, 210023, China
State Key Laboratory of Luminescent Materials and Devices, South China University of Technology, Guangzhou 510641, China
Funding
South China University of Technology
References (100+)
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