Predicting Photodetector Responsivity through Machine Learning
Amir‐Mohammad Arjmandi‐Tash,
Amir Mansourian,
Fatemeh Rahnemaye Rahsepar
et al.
Abstract:This study introduces a novel methodology for predicting photodetector responsivity, specifically targeting challenging materials like borophene. The synthesis of these materials faces substantial experimental complexities, necessitating reliable performance predictions before fabrication. To address this, a comprehensive approach leveraging advanced machine learning techniques, specifically artificial neural networks (ANN), is developed. Integration of X‐ray diffraction (XRD) and Raman spectra data into AI mo… Show more
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