Targeting high performance of perovskite solar cells by combining electronic, manufacturing and environmental features in machine learning techniques-Reference-Cited by-同舟云学术

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Targeting high performance of perovskite solar cells by combining electronic, manufacturing and environmental features in machine learning techniques

Published:2023-11 Issue:11 Volume:9 Page:e21498
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Mammeri M.,Dehimi L.,Bencherif H.,Amami Mongi,Ezzine Safa,Pandey Rahul,Hossain M. Khalid^ORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference29 articles.

1. Quantum machine learning;Biamonte;Nature,2017

2. Machine learning algorithms-a review;Mahesh;Int. J. Sci. Res.,2020

3. Design and numerical investigation of efficient (FAPbI3) 1− x (CsSnI3) x perovskite solar cell with optimized performances;Bencherif;Sol. Energy,2022

4. An extensive study on multiple ETL and HTL layers to design and simulation of high-performance lead-free CsSnCl3-based perovskite solar cells;Hossain;Sci. Rep.,2023

5. A comprehensive study of the optimization and comparison of cesium halide perovskite solar cells using ZnO and Cu 2 FeSnS 4 as charge transport layers;Hossain;New J. Chem.,2023

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ZnO/SrTiO₃, ZnO/WO₃, and ZnO/Zn₂SnO₄ Bilayer as Electron Transport Layers for Lead Sulfide Colloidal Quantum Dots Solar Cells;Small;2024-09-09

2. Numerical interface optimization of lead-free perovskite solar cells (CH3NH3SnI3) for 30% photo-conversion efficiency using SCAPS-1D;Next Materials;2024-07

3. Machine Learning for Perovskite Solar Cells: An Open‐Source Pipeline;Advanced Physics Research;2024-06-20

4. Stability forecasting of perovskite solar cells utilizing various machine learning and deep learning techniques;Journal of Optics;2024-04-16

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