Results 141 to 150 of about 106,796 (274)
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
Bistable Mechanisms 3D Printing for Mechanically Programmable Vibration Control
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
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Powder Metallurgy and Additive Manufacturing of High‐Nitrogen Alloyed FeCr(Si)N Stainless Steel
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
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
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
Low‐Activation Compositionally Complex Alloys for Advanced Nuclear Applications—A Review
Low‐activation compositionally complex alloys (LACCAs) are advanced metallic materials primarily composed of low‐activation elements, offering advantages such as rapid compliance with operational standards and safe recyclability. This review highlights their potential for extreme high‐temperature irradiation environments as structural materials for ...
Yangfan Wang+8 more
wiley +1 more source
Ground state solutions for Choquard type equations with a singular potential
This article concerns the Choquard type equation $$ -\Delta u+V(x)u=\Big(\int_{\mathbb{R}^N}\frac{|u(y)|^p}{|x-y|^{N-\alpha}}dy\Big) |u|^{p-2}u,\quad x\in \mathbb{R}^N, $$ where $N\geq3$, $\alpha\in ((N-4)_+,N)$, $2\leq p
Tao Wang
doaj
A remark on the concentration compactness principle in critical dimension
Fengbo Hang
openalex +2 more sources
What happens when 32 labs join forces to study nanoparticle‐modified powders? A data‐driven journey through laser powder bed fusion—now openly accessible for the entire additive manufacturing community—is studied. Laser powder bed fusion is a cornerstone technology for additive manufacturing (AM) of metals and polymers, yet challenges in achieving ...
Ihsan Murat Kuşoğlu+73 more
wiley +1 more source