Results 211 to 220 of about 473,413 (369)

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

open access: yesAdvanced 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   +17 more
wiley   +1 more source

Sustainable Geopolymer Mortars from Ceramic Sanitaryware Waste: Impact of Curing Methods on Mechanical and Thermal Behavior. [PDF]

open access: yesMaterials (Basel)
Benkabou R   +8 more
europepmc   +1 more source

Parameter Variation in Planetary Ball Milling of Titanium Aluminide Powder in XHV‐Adequate Atmosphere

open access: yesAdvanced Engineering Materials, EarlyView.
This study investigates the effects of milling parameters, including rotational speed, milling duration, and ball‐to‐powder ratio, on TiAl particle size and morphology in an XHV‐equivalent atmosphere. The creation of oxide‐free surfaces enhances the mechanical properties of green bodies.
Jytte Möckelmann   +4 more
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced 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   +4 more
wiley   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

open access: yesAdvanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang   +2 more
wiley   +1 more source

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