Results 241 to 250 of about 818,829 (307)

Nanoparticle‐Coated X2CrNiMo17‐12‐2 Powder for Additive Manufacturing – Part I: Surface, Flowability, and Optical Properties of SiC, Si, and Si3N4 Coated Metal Powders

open access: yesAdvanced Engineering Materials, EarlyView.
Herein, silicon‐based nanoparticle coatings on X2CrNiMo17‐12‐2 metal powder are presented. The coating process scale, process parameters, nanoparticle size (65–200 nm) as well as the coating amount are discussed regarding powder properties. The surface roughness affects the flowability, while reflectance depends on the coating material and surface ...
Arne Lüddecke   +4 more
wiley   +1 more source

Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes

open access: yesAdvanced Engineering Materials, EarlyView.
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

High Repetition Rate Laser‐Induced Printing of Bioink with Picosecond Pulse Durations: Optimization of the Printing Process

open access: yesAdvanced Engineering Materials, EarlyView.
This study explores the use of laser‐induced forward transfer in the picosecond regime to create in vitro biomodels. Focusing on hydrodynamics and rheology, it investigates jet dynamics through time‐resolved imaging, optimizing laser fluence, biological ink viscosity, and printing distance to precisely control the volume and location of bioink ...
Lucas Duvert   +5 more
wiley   +1 more source

Machine Learning‐Guided Discovery of Factors Governing Deformation Twinning in Mg–Y Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
This study uses interpretable machine learning to identify key microstructural and processing parameters related to twinning in magnesium‐yttrium (Mg–Y) alloys. It is identified that using only grain size, grain orientation, and total applied strain, grains can be classified with 84% accuracy based on whether the grain contains a twin.
Peter Mastracco   +8 more
wiley   +1 more source

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