Machine Learning for Green Solvents: Assessment, Selection and Substitution
Advanced Science, EarlyView.Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta +4 more
wiley +1 more source
An in-depth analysis and review of management strategies for E-waste in the south Asian region: A way forward towards waste to energy conversion and sustainability. [PDF]
HeliyonIslam MK, Khatun MS, Mourshed M.
europepmc +1 more source
Perspective: Hollow Core Optical Fibres for Ultraviolet and Visible Wavelengths
Advanced Science, EarlyView.Hollow core optical fibres bypass material constraints that limit optical fibres at ultraviolet and visible wavelengths. However, their challenging fabrication has limited their development, and significant gains in performance remain possible. In this perspective we outline approaches to enable the next generation of fibres for shorter wavelengths ...
Robbie Mears +5 more
wiley +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
Advanced Science, EarlyView.FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Techno-economic and environmental assessments of optimal planning of waste-to-energy based CHP-DG considering load growth on a power distribution network. [PDF]
HeliyonAkanni Alao M, Mohammed Popoola O.
europepmc +1 more source
Waste to Energy in Denmark: Danish legal pathway to a clean Waste to Energy
, 2020 openaire +1 more source
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Circular economy and waste to energy
AIP Conference Proceedings, 2018Waste management in European Union has long being regulated by the 4Rs principle, i.e. reduction, reuse, recycling, recovery, with landfill disposal as the last option. This vision recently led the European Union (especially since 2015) to the introduction of virtuous goals based on the rejection of linear economy in favour of circular economy strongly
E. C. Rada +5 more
openaire +3 more sources
Many conversion technologies and processes for bioenergy generation from wastes have been reported and discussed in the previous chapters. These conversion technologies are being selected and applied depending on the type of wastes, chemical composition of the available waste and the desired energy vector.
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