Results 181 to 190 of about 274,856 (260)

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, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Recycling of Rare Earth Elements: From E-Waste to Stereoselective Catalytic Reactions. [PDF]

ChemSusChem
Donato E, Medici F, Chiroli V, Puglisi A, Rogoli C, Fröhlich P, Bertau M, Zanoni G, Benaglia M.   +8 more
europepmc   +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, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Assessing the Health Effects of Informal E-Waste Processing

Journal of Health and Pollution, 2013
Anne M. Riederer, ScD, Stephanie Adrian, MPH, Ruediger Kuehr, PhD   +2 more
doaj   +1 more source

Editorial: E-waste and heavy metals: health hazards and environmental impact. [PDF]

Front Public Health
Tabassum B.
europepmc   +1 more source

Insights Into CO2 Loss, pH Effects, and Tafel Kinetics in Ni Single Atom‐Driven Bicarbonate Electroreduction

Advanced Science, EarlyView.
Selective CO formation in bicarbonate electrolysis is achieved by retaining reactive CO2 and tuning pH, while the competing hydrogen evolution reaction occurs at the interface. The rate‐determining step couples the chemical equilibrium of bicarbonate/CO2 with electrochemical charge transfer, offering insight into optimizing reaction conditions for ...
Lin Li, Yi‐Jie Kong, Ting Zhang, Xu Han, Kristine Aalestrup, Steen Uttrup Pedersen, Xin‐Ming Hu, Kim Daasbjerg   +7 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Comprehensive Blood Metabolome and Exposome Analysis, Annotation, and Interpretation in E-Waste Workers. [PDF]

Metabolites
Pang Z, Viau C, Fobil JN, Basu N, Xia J.
europepmc   +1 more source

Engineering Microbial Particles for Next‐Generation Biomedical Platforms

Advanced Science, EarlyView.
Microbe‐derived particles (MDPs), which include extracellular vesicles, outer membrane vesicles, inclusion bodies, polysaccharide particles, and virus‐like particles, represent a rapidly expanding category of bioinspired nanomaterials. With their natural origin, intrinsic biocompatibility, and highly programmable functionality, MDPs serve as a ...
Yuting Li, Yunjie Lu, Ziyan Huang, Jianjiang Chen, Yanbin Liu, Lei Qin, Chao Wang, Yumin Wu   +7 more
wiley   +1 more source

Post-Synthetic Modification of a MOF via Continuous Flow Methods for Gold E-Waste Recycling. [PDF]

ChemSusChem
Roth J, Trukhina O, Allouss D, Stoian D, Schertenleib T, Felder T, Queen WL.   +6 more
europepmc   +1 more source