Machine‐Learning‐Assisted Understanding of Depth‐Dependent Thermal Conductivity in Lithium Niobate Induced by Point Defects

Machine‐Learning‐Assisted Understanding of Depth‐Dependent Thermal Conductivity in Lithium Niobate Induced by Point Defects

Abstract Lithium niobate (LiNbO3, LN) has unique electro‐optic and piezoelectric properties, making it widely used in optical devices, telecommunications, sensors, and acoustic systems. Thermal conductivity κ is a critical property influencing the performance and reliability of these applications. P...

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Bibliographic Details
Main Authors: Yunjia Bao, Tao Chen, Zhuo Miao, Weidong Zheng, Puqing Jiang, Kunfeng Chen, Ruiqiang Guo, Dongfeng Xue
Format: Article
Language:English
Published: Wiley-VCH 2025-07-01
Series:Advanced Electronic Materials
Subjects:
lithium niobate
machine learning
point defects
pump‐probe thermoreflectance
thermal conductivity gradient
Online Access:https://doi.org/10.1002/aelm.202400944
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https://doi.org/10.1002/aelm.202400944

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