Advancements in ruthenium-based sensitizers for dye-sensitized solar cells-from structural tailoring to AI-ML

S Mahalakshmi - Coordination Chemistry Reviews, 2025 - Elsevier
The global focus on sustainable energy sources has intensified amidst concerns over
environmental degradation caused by fossil fuel consumption. Solar energy stands out as a …

Data‐Driven Tunnel Oxide Passivated Contact Solar Cell Performance Analysis Using Machine Learning

J Zhou, TJ Jacobsson, Z Wang, Q Huang… - Advanced …, 2024 - Wiley Online Library
Tunnel oxide passivated contacts (TOPCon) have gained interest as a way to increase the
energy conversion efficiency of silicon solar cells, and the International Technology …

Stokes shift prediction of fluorescent organic dyes using machine learning based hybrid cascade models

KD Mahato, SSGK Das, C Azad, U Kumar - Dyes and Pigments, 2024 - Elsevier
Fluorescent organic dyes are widely used in various fields, including science and
technology, research and development, medicine, and drug delivery. Multitudinous attempts …

[HTML][HTML] Artificial neural networks for predicting optical conversion efficiency in luminescent solar concentrators

PS André, LMS Dias, SFH Correia, ANC Neto… - Solar Energy, 2024 - Elsevier
Develo** light-harvesting materials able to shape the sunlight to cope with the absorption
region of photovoltaic (PV) cells presents an opportunity for the utilization of spectral …

Optimized machine learning techniques enable prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum …

KD Mahato, U Kumar - Spectrochimica Acta Part A: Molecular and …, 2024 - Elsevier
Applications of organic dyes, ranging from basic research to industry, are functions of their
photophysical properties. Two important aspects—(1) knowledge of the photophysical …

Advanced High‐Throughput Rational Design of Porphyrin‐Sensitized Solar Cells Using Interpretable Machine Learning

JM Liao, YH Chen, HW Lee, BC Guo, PC Su… - Advanced …, 2024 - Wiley Online Library
Accurately predicting the power conversion efficiency (PCE) in dye‐sensitized solar cells
(DSSCs) represents a crucial challenge, one that is pivotal for the high throughput rational …

Predictive Modeling and SHAP (SHapley Additive ExPlanations) Analysis for Enhancing Natural Dye‐Sensitized Solar Cell Performance

B Oral, HA Maddah, R Yildirim - Solar RRL, 2024 - Wiley Online Library
Achieving high power conversion efficiency (PCE) in natural dye‐sensitized solar cells
remains a challenge. To better understand such challenges and explore potential solutions …

Numerical modeling of charge transfer and recombination kinetics in the dye-sensitized solar cell: Conceptual integration of optics, electricity, and electrochemistry

N Dehghani, A Jamekhorshid, T Jalali, S Osfouri - Renewable Energy, 2025 - Elsevier
Enhancing the performance of dye-sensitized solar cells (DSSCs) requires thoroughly
examining their operational dynamics. Modeling is a cost-effective and flexible method for in …

Testing the performance of dye sensitized solar cells under various temperature and humidity environments

N Tomar, VS Dhaka, PK Surolia - Journal of Applied Electrochemistry, 2024 - Springer
Temperature and humidity are the two vital outdoor factors that significantly affect the dye
sensitized solar cells (DSSCs) efficiency. The complete performance of DSSCs depends on …

[HTML][HTML] Machine learning based hybrid ensemble models for prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths …

KD Mahato, SS Kumar Das, C Azad, U Kumar - APL Machine Learning, 2024 - pubs.aip.org
Fluorescent organic dyes are extensively used in the design and discovery of new materials,
photovoltaic cells, light sensors, imaging applications, medicinal chemistry, drug design …