Machine learning for 2D material–based devices

Yuan Yan

doi:10.1016/j.mser.2025.101085

Machine learning for 2D material–based devices

2025-08-20

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DOI：10.1016/j.mser.2025.101085

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Abstract

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• Machine learning significantly enhances the efficiency and quality of 2D material synthesis. • Integrating machine learning with characterization techniques improves accuracy in defect and property analysis. • Data-driven models optimize fabrication parameters and predict the performance of 2D devices. • Machine learning drives interdisciplinary advancements from fundamental research to applications in 2D materials.

Keywords:

machine learning

2D materials

synthesis

characterization

data-driven models

Machine learning for 2D material–based devices

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