Results 101 to 110 of about 1,221,835 (366)
Advanced Engineering Materials, EarlyView.This study explores the energy conversion in powder bed fusion of polymers using laser beam for polyamide 12 and polypropylene powders. It combines material and process data, using dimensionless parameters and numerical models, to enable the prediction of suitable printing parameters.
Christian Schlör +9 more
wiley +1 more source
Imaging modalities in keratoconus
Indian Journal of Ophthalmology, 2013 Diagnosis of keratoconus has greatly improved from simple clinical diagnosis with the advent of better diagnostic devices like corneal topographers based on placido disc, elevation based topographers and lately optical coherence tomography (OCT).
Himanshu Matalia, Rishi Swarup
doaj +1 more source
A possible testbed for warped extra dimension from the angle of Buchdahl's limit
, 2018 We consider a five dimensional AdS warped spacetime in presence of a massive scalar field in the bulk. The scalar field potential fulfills the requirement of modulus stabilization even when the effect of backreaction of the stabilizing field is taken ...
Paul, Tanmoy
core +1 more source
Substrate modulus directs neural stem cell behavior.
Biophysical Journal, 2008 Although biochemical signals that modulate stem cell self-renewal and differentiation were extensively studied, only recently were the mechanical properties of a stem cell's microenvironment shown to regulate its behavior.
Krishanu Saha +6 more
semanticscholar +1 more source
Bistable Mechanisms 3D Printing for Mechanically Programmable Vibration Control
Advanced Engineering Materials, EarlyView.This work introduces a 3D‐printed bistable mechanism integrated into tuned mass dampers (TMDs) for mechanically adaptive passive vibration suppression. Through optimized geometry, the bistable design provides adaptable vibration reduction across a broad range of scenarios, achieving effective vibration mitigation without complex controls or external ...
Ali Zolfagharian +4 more
wiley +1 more source
Advanced 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
Shear modulus of neutron star crust
, 2011 Shear modulus of solid neutron star crust is calculated by thermodynamic perturbation theory taking into account ion motion. At given density the crust is modelled as a body-centered cubic Coulomb crystal of fully ionized atomic nuclei of one type with ...
Albers +30 more
core +1 more source
MODULUS OF ELASTICITY AND MODULUS OF RUPTURE OF ELECTRICAL PORCELAIN
Journal of the Ceramic Association, Japan, 1937 Measuring the modulus of elasticity and that of rupture for electrical porcelain with the small cross sectional area, the following results have been obtained.1. When the grain size of green body is reduced, the modules of rupture and the modulus of elasticity become larger, but the increase of the latter is smaller when compared with that of the ...
openaire +2 more sources
Deformation Behavior of La2O3‐Doped Copper during Equal Channel Angular Pressing
Advanced 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
Advanced 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