Results 291 to 300 of about 11,568,694 (339)

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani   +2 more
wiley   +1 more source

The Method of Types for the AWGN Channel. [PDF]

open access: yesEntropy (Basel)
Tridenski S, Somekh-Baruch A.
europepmc   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

open access: yesAdvanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez   +5 more
wiley   +1 more source

Comparative Wear and Friction Analysis of Sliding Surface Materials for Hydrostatic Bearing under Oil Supply Failure Conditions

open access: yesAdvanced Engineering Materials, EarlyView.
Hydrostatic bearings excel in high‐precision applications, but their performance hinges on a continuous external supply. This study evaluates various material combinations for sliding surfaces to mitigate damage during supply failures or misalignment and to discover the most effective materials identified for enhancing the reliability and efficiency of
Michal Michalec   +6 more
wiley   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Cusp Universality for Correlated Random Matrices. [PDF]

open access: yesCommun Math Phys
Erdős L, Henheik J, Riabov V.
europepmc   +1 more source

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