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
Fundamentals and Applications of Fluid Mechanics and Acoustics in Biomedical Engineering. [PDF]
Little I, Gutmark E.
europepmc +1 more source
A fluid mechanics explanation of the effectiveness of common materials for respiratory masks. [PDF]
Maher B+4 more
europepmc +1 more source
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
Fluid mechanics of luminal transport in actively contracting endoplasmic reticulum. [PDF]
Htet PH, Avezov E, Lauga E.
europepmc +1 more source
Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes
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-resolution stereolithography: Negative spaces enabled by control of fluid mechanics. [PDF]
Coates IA+9 more
europepmc +1 more source
Multiple Grid Methods for Equations of the Second Kind with Applications in Fluid Mechanics. [PDF]
H. J. S., H. Schippers
openalex +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
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
Exergy Flow as a Unifying Physical Quantity in Applying Dissipative Lagrangian Fluid Mechanics to Integrated Energy Systems. [PDF]
Xu K+7 more
europepmc +1 more source