Special Issue "Recent Advances in Thin-Film Solar Cells"

A special issue of Crystals (ISSN 2073-4352). This special issue belongs to the section "Materials for Energy Applications".

Deadline for manuscript submissions: closed (10 November 2023) | Viewed by 1123

Special Issue Editors

Energy Materials and Devices, Korea Institute of Energy Technology (KENTECH), Naju 58217, Republic of Korea
Interests: kesterite; compound semiconductors; interface engineering; optoelectronics; photovoltaics
Solar Energy Department, Korea Institute of Energy Technology (KENTECH), Naju 58217, Republic of Korea
Interests: material science; thin film solar cells; tandem solar cells; kesterits; CZTSSe
Korea Institute of Energy Technology (KENTECH), 72, Ujeong-ro, Naju-si, Jeollanam-do, Republic of Korea
Interests: thin film solar cells; integrated PV modules and systems (BIPV, VIPV, RIPV)
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Special Issue Information

Dear Colleagues,

Society is shifting towards renewable energy generation to minimize greenhouse gas emissions for better environmental conditions. Among all the renewable energy sources (wind, water, solar, etc.), photovoltaic (PV) technology is a promising approach to harvesting solar energy into electricity. Various types of photovoltaic technologies have been developed, among which thin-film solar cells (TFSCs) have achieved significant success among all other photovoltaic technologies because of their low processing cost, flexibility, and eco-friendly nature. This Special Issue will cover recent advancements in thin-film solar cells based on various absorber materials, associated issues, and their prospects.

Photovoltaics are a nearly unlimited and ultimate resource of natural and green power for the Earth. Thus, the effort towards developing highly efficient thin-film solar cells, which is a probable solution to the most demanding environmental and economic concerns, is of extreme importance. The recent progress in thin-film solar cell (TFSC) technologies has broadened the possibility to employ eco-friendly photovoltaic (PV) technology for solar energy harvesting. Various types of photovoltaic technologies have been developed, among which thin-film solar cells have gained a significant place among other photovoltaic technologies. This Special Issue will cover new topics that have arisen with the recent development of thin-film solar cell technologies. We welcome research and review papers, both experimental and theoretical, in areas concerning the development of highly efficient thin-film photovoltaics, as well as in associated fields.

Dr. Kuldeep Singh Gour
Dr. Vijay Chandrakant Karade
Prof. Dr. Jaeho Yun
Guest Editors

Manuscript Submission Information

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Keywords

  • thin-film solar cells
  • bifacial solar cells
  • perovskite solar cells
  • indoor photovoltaics (IPVs)
  • optical/electrical properties
  • defects and stability of photovoltaics
  • chalcogenide-based absorber materials
  • building-integrated photovoltaic (BIPV)
  • emerging photovoltaic absorber materials
  • tandem/multijunction thin-film solar cells
  • colloidal quantum dot-based photovoltaics
  • CIS, CIGS, CZTS, Sb2Se3, SnS, SnSe, Cu2SnS3
  • transparent conductive oxides, protective, and anti-reflective coatings

Published Papers (1 paper)

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Research

10 pages, 3118 KiB  
Article
Unraveling the Effect of Compositional Ratios on the Kesterite Thin-Film Solar Cells Using Machine Learning Techniques
Crystals 2023, 13(11), 1581; https://doi.org/10.3390/cryst13111581 - 12 Nov 2023
Viewed by 481
Abstract
In the Kesterite family, the Cu2ZnSn(S,Se)4 (CZTSSe) thin-film solar cells (TFSCs) have demonstrated the highest device efficiency with non-stoichiometric cation composition ratios. These composition ratios have a strong influence on the structural, optical, and electrical properties of the CZTSSe absorber [...] Read more.
In the Kesterite family, the Cu2ZnSn(S,Se)4 (CZTSSe) thin-film solar cells (TFSCs) have demonstrated the highest device efficiency with non-stoichiometric cation composition ratios. These composition ratios have a strong influence on the structural, optical, and electrical properties of the CZTSSe absorber layer. So, in this work, a machine learning (ML) approach is employed to evaluate effect composition ratio on the device parameters of CZTSSe TFSCs. In particular, the bi-metallic ratios like Cu/Sn, Zn/Sn, Cu/Zn, and overall Cu/(Zn+Sn) cation composition ratio are investigated. To achieve this, different machine learning algorithms, such as decision trees (DTs) and classification and regression trees (CARTs), are used. In addition, the output performance parameters of CZTSSe TFSCs are predicted by both continuous and categorical approaches. Artificial neural networks (ANN) and XGBoost (XGB) algorithms are employed for the continuous approach. On the other hand, support vector machine and k-nearest neighbor’s algorithms are also used for the categorical approach. Through the analysis, it is observed that the DT and CART algorithms provided a critical composition range well suited for the fabrication of highly efficient CZTSSe TFSCs, while the XGB and ANN showed better prediction accuracy among the tested algorithms. The present work offers valuable guidance towards the integration of the ML approach with experimental studies in the field of TFSCs. Full article
(This article belongs to the Special Issue Recent Advances in Thin-Film Solar Cells)
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