Selective Recovery of Gold from Electronic Waste by New Efficient Type of Sorbent. [PDF]
Wójcik G +3 more
europepmc +1 more source
Machine Learning for Green Solvents: Assessment, Selection and Substitution
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
Fundamental insights into gallium leaching for sustainable electronic waste recovery. [PDF]
Erkmen AN +3 more
europepmc +1 more source
Simulation of Electronic Waste Reverse Chains for the Sao Paulo Circular Economy: An Artificial Intelligence-Based Approach for Economic and Environmental Optimizations. [PDF]
Oliveira Neto GC +5 more
europepmc +1 more source
Perspective: Hollow Core Optical Fibres for Ultraviolet and Visible Wavelengths
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
Neurocognitive consequences of occupational heavy metal exposure among electronic waste sorting workers in Thailand. [PDF]
Harasarn K, Keawkaen P, Thetkathuek A.
europepmc +1 more source
Performance evaluation of a novel multi-metal catalyst solution obtained from electronic waste bioleaching on upgrading and enhancing oil recovery. [PDF]
Faryadi K, Jafari A, Mousavi SM.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
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
Review and Analyze the Sources, Characteristics and Composition of Electronic Waste
The objective of this paper was to review and analyze the sources, characteristics and composition of electronic wastes by collecting the studies related to the research problem from various databases. The results of the evaluation of articles show that
N. H. T. Ly, N. T. Giao
doaj
Leachability and Chemical Profiles of Per- and Polyfluoroalkyl Substances in Electronic Waste Components: Targeted and Non-Targeted Analysis. [PDF]
Ocheje JO +4 more
europepmc +1 more source

