Results 101 to 110 of about 2,062,209 (334)

Cosmology without time: What to do with a possible signature change from quantum gravitational origin?

open access: yes, 2016
Within some approaches to loop quantum cosmology, the existence of an Euclidean phase at high density has been suggested. In this article, we try to explain clearly what are the observable consequences of this possible disappearance of time. Depending on
Barrau, Aurélien, Grain, Julien
core   +1 more source

Primordial scalar power spectrum from the Euclidean Big Bounce

open access: yes, 2016
In effective models of loop quantum cosmology, the holonomy corrections are associated with deformations of space-time symmetries. The most evident manifestation of the deformations is the emergence of an Euclidean phase accompanying the non-singular ...
Barrau, Aurélien   +5 more
core   +3 more sources

Powder Metallurgy and Additive Manufacturing of High‐Nitrogen Alloyed FeCr(Si)N Stainless Steel

open access: yesAdvanced Engineering Materials, EarlyView.
The alloying element Nitrogen enhances stainless steel strength, corrosion resistance, and stabilizes austenite. This study develops austenitic FeCr(Si)N steel production via powder metallurgy. Fe20Cr and Si3N4 are hot isostatically pressed, creating an austenitic microstructure.
Louis Becker   +5 more
wiley   +1 more source

Corrigendum: A survey of Fusarium species and ADON genotype on Canadian wheat grain

open access: yesFrontiers in Fungal Biology, 2023
Janice Bamforth   +15 more
doaj   +1 more source

Phenomenology of black hole evaporation with a cosmological constant

open access: yes, 2005
In this brief note, we investigate some possible experimental consequences of the de-Sitter or Anti-de-Sitter background spacetime structure for d-dimensional evaporating black holes.
Barrau, A., Grain, J., Labbe, J.
core   +2 more sources

Nanoparticle‐Coated X2CrNiMo17‐12‐2 Powder for Additive Manufacturing—Part II: Processability by Powder Bed Fusion of Metals Using a Laser Beam

open access: yesAdvanced Engineering Materials, EarlyView.
In this manuscript, the processability of X2CrNiMo17‐12‐2 powder coated with silicon carbide, silicon, and silicon nitride nanoparticles is investigated. The amount of nanoparticles varies from 0.25 to 1 vol%. By coating the powder feedstock material with nanoparticles, an enlargement of the process window and an increase in the build rate are achieved.
Nick Hantke   +5 more
wiley   +1 more source

Research Progress on the Influence of Coagulants and Processing Conditions on the Formation and Quality of Tofu Gel

open access: yesShipin gongye ke-ji
Tofu is a widely consumed protein gel, which is the denaturation of soybean protein (specifically the 7S and 11S globulin), under heat treatment, and the aggregation by salt ions, hydrogen ions or enzymes, forming a dense and uniform protein gel with a ...
Bingyu SUN   +8 more
doaj   +1 more source

Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes

open access: yesAdvanced Engineering Materials, Volume 27, Issue 13, July 2025.
Fog harvesting using mesh designs offers a sustainable solution to water scarcity. This study highlights key considerations for fog harvesting research and develops a methodology for a standardized protocol reflecting fog characteristics and environmental conditions.
Pegah Sartipizadeh   +3 more
wiley   +1 more source

Deformation Behavior of La2O3‐Doped Copper during Equal Channel Angular Pressing

open access: yesAdvanced Engineering Materials, EarlyView.
By additions of strengthening elements and/or structure optimization, the mechanical properties of copper can be increased while keeping favorable electric conductivity. By combining addition of La2O3 and processing by equal channel angular pressing, substructure development is achieved, leading to increase in microhardness to more than double the ...
Lenka Kunčická   +2 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

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