Results 161 to 170 of about 1,257,183 (296)

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

Expression of Concern: An Efficient Hybrid Job Scheduling Optimization (EHJSO) approach to enhance resource search using Cuckoo and Grey Wolf Job Optimization for cloud environment. [PDF]

PLoS One
PLOS One Editors.
europepmc   +1 more source

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems. [PDF]

PLoS One, 2017
Idris H, Ezugwu AE, Junaidu SB, Adewumi AO.   +3 more
europepmc   +1 more source

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

Advanced Engineering Materials, EarlyView.
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

An intelligent job scheduling and real-time resource optimization for edge-cloud continuum in next generation networks. [PDF]

Sci Rep
Naeem AB, Senapati B, Rasheed J, Baili J, Osman O.   +4 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

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

Optimization of the Production of Rubber Compounds Using Mathematical Models

Advanced Engineering Materials, EarlyView.
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann   +7 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