Results 81 to 90 of about 206,551 (266)

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Rafting of Ni‐Based Superalloys Under Multiaxial Load as Understood by Phase‐Field Simulations and Critical Experiments

Advanced Engineering Materials, EarlyView.
Phase‐field simulations coupled with dislocation‐density‐based crystal plasticity modeling reproduce γ′ rafting behavior in single‐crystal Ni‐based superalloys under varied loading conditions. The model captures both macroscopic creep and microscopic morphology evolution, with results matching high‐temperature creep experiments.
Micheal Younan, David Bürger, Gunther Eggeler, Oleg Shchyglo, Ingo Steinbach, Muhammad Adil Ali   +5 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

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Augmented Reality for Art, Design and Cultural Heritage—System Design and Evaluation

EURASIP Journal on Image and Video Processing, 2009
This paper describes the design of an optical see-through head-mounted display (HMD) system for Augmented Reality (AR). Our goals were to make virtual objects "perfectly" indistinguishable from real objects, wherever the user roams, and to find out to ...
Rotteveel Joachim, Kolstee Yolande, van Eck Wim, Caarls Jurjen, Jonker Pieter   +4 more
doaj  

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

Applying cognitive theory of multimedia learning principles to augmented reality and its effects on cognitive load and learning outcomes

Computers in Human Behavior Reports
In the last decade, the use of augmented reality as a learning support tool has been extensively researched, largely due to the proliferation of augmented reality-compatible smartphones.
Vito Candido, Alberto Cattaneo
doaj   +1 more source