Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels

Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels

Abstract This study has focused on modeling and predicting the electrical properties and parameters of CdZnO interlayered Al/p-Si Schottky Diodes (SDs) using the Long Short-Term Memory (LSTM) algorithm. The primary aim of this study was to develop a robust predictive model that accurately captures h...

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Bibliographic Details
Main Authors: Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
CdZnO thin films
Long Short-Term memory (LSTM) algorithm
Schottky photodiode
Illumination effects on I–V characteristics
Cheung’s and norde’s method
Online Access:https://doi.org/10.1038/s41598-025-06809-w
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