Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim +8 more
wiley +1 more source
Global solar energy potential forecasting through machine learning and deep learning models. [PDF]
Raza MA +6 more
europepmc +1 more source
Assessing Photovoltaic Recycling Capacities and Policy Gaps in the European Union
This study maps photovoltaic recycling capacity in the EU and key global regions, highlighting gaps between growing waste volumes and available infrastructure. It combines survey insights and policy analysis to identify recycling bottlenecks and offers recommendations to boost circularity in the solar sector.
Nieves Espinosa +3 more
wiley +1 more source
Machine Learning for Designing Perovskites and Perovskite-Inspired Solar Materials: Emerging Opportunities and Challenges. [PDF]
Zhang Y +6 more
europepmc +1 more source
Challenges and enablers in fluidization technology
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley +1 more source
Smart home energy management for sustainable socioeconomic development in Egyptian households. [PDF]
Saif O, Elazab R, Daowd M.
europepmc +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
A hybrid statistical-machine learning framework for evaluating geomagnetic storm effects on MisrSat2 satellite power subsystems. [PDF]
Mostafa MS +5 more
europepmc +1 more source
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
Correlation between active regions' spectra at high radio frequencies and solar flare occurrences. [PDF]
Mulas S +33 more
europepmc +1 more source

