Results 41 to 50 of about 45,232 (180)

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

Advanced Engineering Materials, EarlyView.
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

Affecting the Properties of Copper–Graphene Electroconductive Composite by Severe Plastic Deformation

Advanced Engineering Materials, EarlyView.
Copper‐based composites enhanced with carbon feature convenient mechanical properties and favorable electric conductivity. Processing via deformation and thermomechanical treatments can introduce advantageous microstructures further enhancing their performance. Herein, copper–graphene powder‐based composites are directly consolidated via rotary swaging
Radim Kocich, Lenka Kunčická, Pavel Czernek, Zifan Wang   +3 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Microstructure, Thermal Transport, and Dry‐Sliding Tribology of Powder‐Metallurgy Al7075 Composites Reinforced With Sol–Gel‐Derived ZnO–rGO Hybrid Nanoparticles

Advanced Engineering Materials, EarlyView.
Sol–gel‐derived ZnO–rGO hybrid nanoparticles enable Al7075 powder‐metallurgy composites to achieve concurrent gains in hardness and thermal conductivity while markedly lowering friction and wear. The hybrid architecture couples ZnO‐based load support with rGO‐assisted lamellar sliding and heat spreading, revealing a promising route toward lightweight ...
Bunyamin Aksakal, Cevher Kursat Macit, Merve Ayık, Hakan Tutumlu   +3 more
wiley   +1 more source

Active Corrosion Protection of Sintered AA7075 Aluminum Alloy via Mn Powder Addition

Advanced Engineering Materials, EarlyView.
AA7075 containing Mn‐rich particles is fabricated via spark plasma sintering using AA7075 and Mn powders. Corrosion resistance is evaluated through dip‐and‐dry tests using 0.1 M NaCl (pH 6.0), and mass loss decreases with increasing Mn addition. Mn‐rich particles function as a source of Mn ions, and formation of Mn‐accumulation films on Cu‐containing ...
Ko Ebina, Masashi Nishimoto, Izumi Muto
wiley   +1 more source