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Machine learning empowers efficient design of ternary organic solar cells with PM6 donor
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 …
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 …
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**
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 …
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
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 …
becoming more pronounced with ongoing advancements in material science and device …
Facile Approach for Metallic Precursor Engineering for Efficient Kesterite Thin-Film Solar Cells
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 …
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
Thin film photovoltaic (TFPV) materials and devices present a high complexity with
multiscale, multilayer, and multielement structures and with complex fabrication procedures …
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 …
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
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 …
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
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 …
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 …
rational allocation of time and resources while enhancing the practical application of …