Accelerating the development of thin film photovoltaic technologies: An artificial intelligence assisted methodology using spectroscopic and optoelectronic techniques

E Grau‐Luque, I Becerril‐Romero, F Atlan… - Small …, 2024 - Wiley Online Library
Thin film photovoltaic (TFPV) materials and devices present a high complexity with
multiscale, multilayer, and multielement structures and with complex fabrication procedures …

Machine learning-assisted SCAPS device simulation for photovoltaic parameters prediction of CsSnI3 perovskite solar cells

I Chabri, M Said, E El-Allaly, A Oubelkacem - Materials Today …, 2024 - Elsevier
Perovskite solar cells (PSCs) have garnered significant research attention because of their
remarkable surge in power conversion efficiency (PCE) surpassing 26% within a short …

Effect of oxide diffusion barrier and substrate on the reliability of stainless-steel-based CIGS solar cells

H Kim, SP Cias - Solar Energy Materials and Solar Cells, 2024 - Elsevier
This paper investigates the effect of the oxide diffusion barrier and substrate on the residual
stress and the delamination at the CIGS/Molybdenum (Mo) interface when stainless-steel …

Efficient SnS Solar Cells via Plasmonic Light Trapping and Alternative Buffer Layers: A Combined Machine Learning and FDTD Analysis

H Ferhati, T Berghout, F Djeffal - Plasmonics, 2024 - Springer
In this work, we propose a novel design framework based on combined finite-difference time-
domain (FDTD) simulations and machine learning (ML) analysis, aiming to improve the light …

Machine Learning DFT-Based Approach to Predict the Electrical Properties of Tin Oxide Materials

H Ferhati, T Berghout, A Benyahia, F Djeffal - Engineering Proceedings, 2023 - mdpi.com
The effects of oxygen concentration and growth technique during the deposition process on
the electrical properties of tin oxide alloy (SnOx) should be investigated for developing new …