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A Combined DFT and Machine Learning to Predict Bond Lengths in Rare Earth-doped Inorganic Crystals
Editor's Choice | 更新时间：2026-01-30

    • A Combined DFT and Machine Learning to Predict Bond Lengths in Rare Earth-doped Inorganic Crystals

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    • “The research progress in the field of inorganic crystal materials was introduced, and relevant experts combined first principles calculations and machine learning to accurately predict the local structural bond lengths of rare earth ions, providing an important approach for the structural and performance design of rare earth doped inorganic crystal materials.”
    • Chinese Journal of Luminescence   Vol. 47, Issue 1, Pages: 22-32(2026)

    • DOI：10.37188/CJL.20250215    

      CLC： O482.31
    • CSTR：32170.14.CJL.20250215    

    • Received：18 September 2025，

      Revised：2025-10-09，

      Published：25 January 2026

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  • CHEN Bingrong,HE Fengting,TAM YU Puy Mang,et al.A Combined DFT and Machine Learning to Predict Bond Lengths in Rare Earth-doped Inorganic Crystals[J].Chinese Journal of Luminescence,2026,47(01):22-32. DOI： 10.37188/CJL.20250215. CSTR： 32170.14.CJL.20250215.

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Guangdong Provincial Engineering Research Center of Crystal and Laser Technology， Department of Optoelectronic Engineering， Jinan University
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