Results 31 to 40 of about 22,044 (198)
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
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ +19 more
wiley +1 more source
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 +15 more
wiley +1 more source
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn +5 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
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Structure‐Guided Dynamical Mechanics in Bioinspired Double Twisted Laminated Thin Films
This work explores a dynamic mechanistic study of crack propagation and puncture testing via real‐time monitoring of crack initiation, propagation, and termination through nature‐inspired single and double twisted architectures fabricated from cellulose nanocrystals.
Justin Brackenridge +4 more
wiley +1 more source
The optimal layout of football players: A case study for AC Milan [PDF]
This paper attempts to find the optimal formation of three midfielders and three forward football players on ground, using the classic Quadratic Assignment Problem or Facility Layout problem.
Papahristodoulou, Christos
core
Ionic Precursors Transformed Into Vinyl Acetate Synthesis Catalyst via Reaction‐Driven Restructuring
This work demonstrates that a simple physical mixture of Pd and Au ionic precursors, KOAc promoter, and SiO2 support can transform into a highly active vinyl acetate synthesis catalyst through reaction‐driven restructuring. The results highlight reaction‐induced restructuring as an innovative and sustainable catalyst design strategy.
Byeong Jun Cha +11 more
wiley +1 more source

