Results 81 to 90 of about 89,907 (213)
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
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 +3 more
wiley +1 more source
An Outlier Detection Algorithm Based on Multimodal Granular Distances
Outlier detection is pivotal in data mining and machine learning, as it focuses on discovering unusual behaviors that deviate substantially from the majority of data samples.
Tiancai Huang +5 more
doaj +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
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 +8 more
wiley +1 more source
The identification of anomalous data objects within massive datasets is a critical technique in financial auditing. Most existing methods, however, focus on global outlier anomalies detection with less effective in contexts such as Chinese financial ...
Xiuguo Wu
doaj +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
A novel workflow for investigating hydride vapor phase epitaxy for GaN bulk crystal growth is proposed. It combines Design of experiments (DoE) with physical simulations of mass transport and crystal growth kinetics, serving as an intermediate step between DoE and experiments.
J. Tomkovič +7 more
wiley +1 more source
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 +6 more
wiley +1 more source
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji +3 more
wiley +1 more source
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source

