Results 111 to 120 of about 7,115,593 (223)

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

From Ternary Modeling to Predictive PROTAC Design: A Computational Perspective. [PDF]

J Chem Inf Model
Schulz JM, Reynolds RC, Schürer SC.
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Simultaneous nanoscale imaging of local conductivity and chemical potential in a quantum Hall isospin ferromagnet. [PDF]

Nat Commun
Hu J, Zhu S, Li B, Wang Y, Xu S, Cheng Z, Shen C, Geim AK, Wu F, Gao HJ.   +9 more
europepmc   +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

Activated carbon for multicomponent heavy-metal removal: bridging macroscopic adsorption performance and microscopic statistical-physics modeling. [PDF]

RSC Adv
Aouaini F, Ben Yahia M, Aljaiussy BK, Alyousef H, Ben Lamine A.   +4 more
europepmc   +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

Volumetric Ablation of Phenolic Resin in Extreme Environments: A Variable-Property Physics-Informed Neural Network Framework. [PDF]

Polymers (Basel)
Du W, Ma T, Song H.
europepmc   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Correction: Almessiere et al. Correlation Between Composition and Electrodynamics Properties in Nanocomposites Based on Hard/Soft Ferrimagnetics with Strong Exchange Coupling. <i>Nanomaterials</i> 2019, <i>9</i>, 202. [PDF]

Nanomaterials (Basel)
Almessiere MA, Trukhanov AV, Slimani Y, You KY, Trukhanov SV, Trukhanova EL, Esa F, Sadaqat A, Chaudhary K, Zdorovets M, Baykal A.   +10 more
europepmc   +1 more source