Results 171 to 180 of about 7,749 (260)

Investigation of the Effects of Surface and Heat Treatment on the Corrosion Behavior of Additively Manufactured AlSi10Mg

open access: yesMaterials and Corrosion, EarlyView.
Surface finish and heat treatment strongly affect the corrosion behavior of AM AlSi10Mg. Polished samples show the highest corrosion resistance, while as‐built ones suffer from surface roughness and weak oxide layers. Stress relief (SR300) improves the corrosion potential but lowers pitting resistance due to Si network dissolution.
Manel Ellouz   +4 more
wiley   +1 more source

The Effect of Heat Treatment on the Localized Corrosion Susceptibility of Extruded AA6063 Alloys With High Amount of Tramp Elements

open access: yesMaterials and Corrosion, EarlyView.
In AA6063 variants with increased Cu and Zn contents, T6 heat treatment increased local electrochemical contrast, promoting earlier trenching and more frequent intergranular corrosion initiation. Non‐heat‐treated variants developed fewer but larger intergranularly corroded regions, showing that T6 shifts localized corrosion from propagation toward ...
Salil Sainis, Dominique Thierry
wiley   +1 more source

Computational Thermodynamic Design of Nb–Mo‐Based Refractory Multi‐Principal Element Alloy for Hydrogen Energy Storage

open access: yesMetalMat, EarlyView.
Through the use of thermophysical parameter analysis, CALPHAD‐based thermodynamic modeling, and open‐source pressure–composition–temperature (PCT) simulations, Al3Nb60Mo20V16Cr1 was discovered to be a BCC refractory multi‐principal element alloy (RMPEA) with ideal stability for solid‐state hydrogen storage.
Abidemi Adeyoye   +4 more
wiley   +1 more source

Novel Ensemble Prediction Framework for Fast and Accurate Phase Prediction in FeNiCoCrAlCu High‐Entropy Alloys by Integrating Data Augmentation and Interpretable Methods

open access: yesMaterials Genome Engineering Advances, EarlyView.
A physics‐informed machine learning framework is established for phase prediction in FeNiCoCrAlCu HEA. Limited experimental data are expanded through GMM‐based augmentation, followed by descriptor calculation, Pearson‐PCA feature optimization, stacking ensemble classification, and SHAP interpretation, enabling accurate phase identification and ...
Ruixiao Zhang   +5 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

open access: yesResponsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen   +8 more
wiley   +1 more source

Effect of Metal–Metal Distance on the Performance of Dual‐Atom Catalysts for the Oxygen Reduction Reaction: A Density Functional Theory and Micro‐kinetics Study

open access: yesSmall, EarlyView.
Density functional theory calculations and microkinetic modeling were carried out on 108 dual‐atom catalysts with varied metalmetal distances ranging from 2.2 to 3.5 Å. The results reveal that moderate spacing of around 3.0 Å promotes bridging oxygen adsorption and dissociative reduction pathways, weakens the hydroxylhydroperoxyl scaling relationship ...
Yu Mao   +7 more
wiley   +1 more source

Home - About - Disclaimer - Privacy