Results 181 to 190 of about 4,199,345 (361)

Dimensionless Investigations on Energy Conversion and Analysis of Interlayer Time in Laser‐Based Powder Bed Fusion of Polymers for Polyamide 12 with Nanoadditives and Polypropylene

open access: yesAdvanced 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

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

Parallel computing and molecular dynamics of biological membranes [PDF]

open access: green, 1998
Giovanni La Penna   +5 more
openalex   +1 more source

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

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

An Integrated MATLAB Code for Homogenization‐Based Topology Optimization and Generating Functionally Graded Surface Lattices for Additive Manufacturing

open access: yesAdvanced Engineering Materials, EarlyView.
Unlocking structural efficiency, this work integrates homogenization‐based topology optimization with functionally graded triply periodic minimal surface lattices to create highly efficient, customizable lattice structures. Key achievements include the development of a versatile MATLAB framework, optimization of mechanical properties for additive ...
Mirhan Ozdemir   +4 more
wiley   +1 more source

Enhancing Corrosion Resistance and Mechanical Strength of 3D‐Printed Iron Polylactic Acid for Marine Applications via Laser Surface Texturing

open access: yesAdvanced Engineering Materials, EarlyView.
Laser surface texturing significantly improves the corrosion resistance and mechanical strength of 3D‐printed iron polylactic acid (Ir‐PLA) for marine applications. Optimal laser parameters reduce corrosion by 80% and enhance tensile strength by 25% and ductility by 15%.
Mohammad Rezayat   +6 more
wiley   +1 more source

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