Unveiling degradation patterns in dye-sensitized solar cells: a machine learning perspective

Unveiling degradation patterns in dye-sensitized solar cells: a machine learning perspective

Abstract This study examines the time-dependent degradation of dye-sensitized solar cells (DSSCs) by systematically investigating several critical parameters, including TiO2 thickness, porosity, dye concentration, and iodine-based electrolyte concentration. We developed a novel figure of merit (FOM)...

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Bibliographic Details
Main Authors: Ahmet Sait Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Dye-sensitized solar cells
Degradation
Finite element model
Long short-term memory
Predictive modeling
Online Access:https://doi.org/10.1038/s41598-025-05536-6
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https://doi.org/10.1038/s41598-025-05536-6

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