Abstract:Developing inorganic phosphor with desired properties for light-emitting diode application has traditionally relied on time-consuming and labor-intensive material development processes. Moreover, the results of material development research depend significantly on individual researchers’ intuition and experience. Thus, to improve the efficiency and reliability of materials discovery, machine learning has been widely applied to various materials science applications in recent years. However, the prediction capa… Show more
This paper employs regression models based on machine learning to propose a method for predicting the energy level distribution rules of Cr3+ and Fe3+ in various doped crystals.
This paper employs regression models based on machine learning to propose a method for predicting the energy level distribution rules of Cr3+ and Fe3+ in various doped crystals.
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