Machine learning empowers efficient design of ternary organic solar cells with PM6 donor

KA Nirmal, TD Dongale, SS Sutar, AC Khot… - Journal of Energy …, 2025 - Elsevier
Organic solar cells (OSCs) hold great potential as a photovoltaic technology for practical
applications. However, the traditional experimental trial-and-error method for designing and …

Surface modification of SnO2 electron transporting layer by graphene quantum dots for performance and stability improvement of perovskite solar cells

R Panyathip, S Sucharitakul, K Hongsith… - Ceramics …, 2024 - Elsevier
The surface modification of SnO 2 electron transporting layer (ETL) is investigated for the
performance and stability improvement of perovskite solar cells by adding citric acid (SnO 2 …

Improving the device performance of CZTSSe thin-film solar cells via indium do**

SD Korade, KS Gour, VC Karade, JS Jang… - … Applied Materials & …, 2023 - ACS Publications
Cation incorporation emerges as a promising approach for improving the performance of the
kesterite Cu2ZnSn (S, Se) 4 (CZTSSe) device. Herein, we report indium (In) do** using …

Machine learning-guided analysis of CIGS solar cell efficiency: Deep learning classification and feature importance evaluation

A Maoucha, T Berghout, F Djeffal, H Ferhati - Solar Energy, 2025 - Elsevier
The increasing sensitivity of thin-film solar cells to variations in design parameters is
becoming more pronounced with ongoing advancements in material science and device …

Facile Approach for Metallic Precursor Engineering for Efficient Kesterite Thin-Film Solar Cells

SW Park, M He, JS Jang, GU Kamble… - … Applied Materials & …, 2024 - ACS Publications
Kesterite-based Cu2ZnSn (S, Se) 4 (CZTSSe) thin-film solar cells (TFSCs) are a promising
candidate for low-cost, clean energy production owing to their environmental friendliness …

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 …

Regulating SnZn defects and optimizing bandgap in the Cu2ZnSn (S, Se) 4 absorption layer by Ge gradient do** for efficient kesterite solar cells

R Guo, X Li, Y Jiang, T Zhou, Y **a, P Wang… - Ceramics …, 2024 - Elsevier
In recent years, the primary reasons for low efficiency Cu 2 ZnSn (S, Se) 4 (CZTSSe) solar
cells have been attributed to Sn Zn defects and related defect clusters, as well as the …

Machine Learning Aided Optimization of P1 Laser Scribing Process on Indium Tin Oxide Substrates

VC Karade, S Kim, I Jeong, MJ Ko… - Advanced Intelligent …, 2024 - Wiley Online Library
Present study employes a picosecond laser (532 nm) for selective P1 laser scribing on the
indium tin oxide (ITO) layer and subsequent fine‐tuning of P1 scribing conditions with …

[HTML][HTML] Unraveling the effect of compositional ratios on the kesterite thin-film solar cells using machine learning techniques

VC Karade, SS Sutar, JS Jang, KS Gour, SW Shin… - Crystals, 2023 - mdpi.com
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 …

Employing machine learning algorithm for properties of wood ceramics prediction: A case study of ammonia nitrogen adsorption capacity, apparent porosity, surface …

W Jiang, X Guo, Q Guan, Y Zhang, D Du - Ceramics International, 2024 - Elsevier
The estimation of material performance plays a crucial role in practical life, enabling the
rational allocation of time and resources while enhancing the practical application of …