Results 121 to 130 of about 7,060,757 (314)

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

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

PEMBELAJARAN KIMIA TEMATIK PADA MATA KULIAH KIMIA DASAR SEBAGAI MODEL PEMBELAJARAN BERBASIS MASALAH

Cakrawala Pendidikan: Jurnal Ilmiah Pendidikan, 2010
: Thematic Chemistry Learning in the General Chemistry Course as a Problem-Based Learning Model. This study aims to investigate how thematic chemistry learning can be implemented and how the learning quality can be improved through thematic chemistry ...
Rr. Lis Permanasari & Sukisman Purtadi
doaj   +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

Exploring the interplay of innovation competence and chemistry mastery: insights from educational practices and factors of influence

Eclética Química
Innovation competence is a critical skill today, enabling individuals to generate and apply innovative ideas. Its influence on students’ mastery of chemical concepts and the factors shaping this relationship remain underexplored.
Norliyana binti Md. Aris, Nor Hasniza binti Ibrahim, Noor Dayana Binti Abd Halim, Johari bin Surif   +3 more
doaj   +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

Machine Learning in Chemistry

, 2022
Machine learning (ML) approaches are widely used to analyze and model various types of problems, including those related to chemistry. The basic premise is to have a large enough and reliable dataset that is used for training and testing a predictive model.
openaire   +2 more sources

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

Microstructure Evolution of a VMnFeCoNi High‐Entropy Alloy After Synthesis, Swaging, and Annealing

Advanced Engineering Materials, EarlyView.
The synthesis and processing (rotary swaging and annealing) of the novel VMnFeCoNi alloy is investigated, alongside the estimation of the grain size effect on hardness. Analysis of a wide grain size range of recrystallized microstructures (12–210 µm) reveals a low annealing twin density.
Aditya Srinivasan Tirunilai, Zeki Ayrildi, Buse Şen, Maik Rajkowski, Mathias Redondo Garcia, Markus Stricker, Guillaume Laplanche   +6 more
wiley   +1 more source