Results 111 to 120 of about 1,304,632 (243)
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 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
Global Optimization by Particle Swarm Method:A Fortran Program [PDF]
Programs that work very well in optimizing convex functions very often perform poorly when the problem has multiple local minima or maxima. They are often caught or trapped in the local minima/maxima.
Mishra, SK
core
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
Sustainability assessment requires methodologies that appropriately distinguish between additive and non‐additive material properties. A toxicity‐weighted scoring system is developed and applied that accounts for the disproportionate influence of highly toxic constituents through nonlinear weighting functions, providing more realistic estimates than ...
Seth Mehalic +2 more
wiley +1 more source
Fabrication Routes for Ionic Conducting Fiber Strain Sensors
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw +3 more
wiley +1 more source
RFID Network Planning of Smart Factory Based on Swarm Intelligent Optimization Algorithm: A Review
With the development of intelligent manufacturing in China, Radio Frequency Identification (RFID), a key technology for smart factories, has received widespread attention. As RFID applications expand, so does the size of their networks.
Wang Yejiao +4 more
doaj +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
There is an established idea – found in science fiction, architectural studios, and scientific papers alike – of stainable buildings crafted from bio-based materials, colonized by plant and animal life, and blending seamlessly into the natural ...
Jordan H Boyle
doaj +1 more source

