Accelerating defect analysis of solar cells via machine learning of the modulated transient photovoltage

Fast and non-destructive analysis of material defect is a crucial demand for semiconductor devices. Herein, we are devoted to exploring a solar-cell defect analysis method based on machine learning of the modulated transient photovoltage (m-TPV) measurement. The perturbation photovoltage generation...

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Bibliographic Details
Main Authors:	Yusheng Li, Yiming Li, Jiangjian Shi, Licheng Lou, Xiao Xu, Yuqi Cui, Jionghua Wu, Dongmei Li, Yanhong Luo, Huijue Wu, Qing Shen, Qingbo Meng
Format:	Article
Language:	English
Published:	KeAi Communications Co. Ltd. 2024-11-01
Series:	Fundamental Research
Subjects:	Defect analysis Modulated transient photovoltage Machine learning Solar cell Charge recombination Neural network
Online Access:	http://www.sciencedirect.com/science/article/pii/S2667325823000304
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http://www.sciencedirect.com/science/article/pii/S2667325823000304

Accelerating defect analysis of solar cells via machine learning of the modulated transient photovoltage

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