Results 191 to 200 of about 355,365 (355)
Welding and brazing fumes and lung cancer risk: a systematic review and meta-analysis. [PDF]
J Occup Med ToxicolKim Y, Kim EM, Kim I.
europepmc +1 more source
Effect of heat input on the Fe-based nanostructured weld overlay
, 2015 A. Gualco +2 more
openalex +2 more sources
Advanced Energy Materials, EarlyView.This study investigates the feasibility of scaling up Prussian White (PW)‐based cathode manufacturing at a pilot scale. Through careful PW dehydration combined with optimized aqueous processing, we report the stepwise development of industrially relevant 1 Ah pouch cells and evaluate their performance under various conditions.
Faduma M. Maddar +7 more
wiley +1 more source
Effect of Welding Heat Input on the Microstructure and Mechanical Properties of MIG-Welded Dissimilar Magnesium Alloy Joints. [PDF]
Materials (Basel)Jin L +5 more
europepmc +1 more source
Flash Welding and Upset Welding.
Journal of the Japan Welding Society, 1995 Shigeru Suzuki, Kazuyoshi Hasegawa
openaire +2 more sources
Production of welding consumables by enterprises of corporation «Plazmatek» [PDF]
, 2017 V.P. Slobodyanyuk +1 more
openalex +1 more source
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Hybrid Weld-Bonded Joints: A Critical Comparative Review of Welding Processes, Adhesive Interaction and Joint Performance. [PDF]
Materials (Basel)Krawczuk A.
europepmc +1 more source
Breakdown of residual stress in highly restrained thick section steel welds.
, 2009 S.V. Pearce
openalex +1 more source
Advanced Intelligent Systems, EarlyView.This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley +1 more source