Perovskite Solar Cell: Chemical Composition and Bandgap Energy via Machine Learning

Perovskite Solar Cell: Chemical Composition and Bandgap Energy via Machine Learning

The exponential growth in publications and applications of perovskite photovoltaic cells highlights their significance in energy conversion and carbon emissions mitigation. From 2009 to 2023, the efficiency of these cells has significantly increased from 3.9% to 25.7%. The adaptive capacity of pero...

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Bibliographic Details
Main Authors: Filipi França dos Santos, Kelly Cristine Da Silveira, Gesiane Mendonça Ferreira, Daniella Herdi Cariello, Mônica Calixto de Andrade
Format: Article
Language:English
Published: Universidade Federal de Viçosa (UFV) 2023-12-01
Series:The Journal of Engineering and Exact Sciences
Subjects:
Perovskite
Photovoltaic cells
Bandgap
Support Vector Machines (SVM)
Random Forest (RF)
Floresta Aleatória (RF)
Online Access:https://periodicos.ufv.br/jcec/article/view/17804
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