Predicting Photodetector Responsivity through Machine Learning

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 addres...

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Veröffentlicht in:	Advanced theory and simulations 2024-06, Vol.7 (6), p.n/a
Hauptverfasser:	Arjmandi‐Tash, Amir‐Mohammad, Mansourian, Amir, Rahsepar, Fatemeh Rahnemaye, Abdi, Yaser
Format:	Artikel
Sprache:	eng
Schlagworte:	artificial neural networks (ANN) generative adversarial networks (GANs) materials science optoelectronics photodetector X‐ray diffraction (XRD)
Online-Zugang:	Volltext
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