Results 131 to 140 of about 1,347,640 (177)

Nanoparticle‐Coated X2CrNiMo17‐12‐2 Powder for Additive Manufacturing—Part II: Processability by Powder Bed Fusion of Metals Using a Laser Beam

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, Tim R. Brocksieper, Arne Lüddecke, Tobias Grimm, Arno Kwade, Jan T. Sehrt   +5 more
wiley   +1 more source

Spatially multiplexed single-photon sources based on binary-tree multiplexers with optimized structure. [PDF]

Sci Rep
Mechler M, Adam P.
europepmc   +1 more source

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

Advanced 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, Nick Hantke, Harald Zetzener, Jan T. Sehrt, Arno Kwade   +4 more
wiley   +1 more source

Big data show idiosyncratic patterns and rates of geomorphic river mobility. [PDF]

Nat Commun
Boothroyd RJ, Williams RD, Hoey TB, Brierley GJ, Tolentino PLM, Guardian EL, Reyes JCMO, Sabillo CJ, Quick L, Perez JEG, David CPC.   +10 more
europepmc   +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, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Standardizing a microbiome pipeline for body fluid identification from complex crime scene stains. [PDF]

Appl Environ Microbiol
Swayambhu M, Gysi M, Haas C, Schuh L, Walser L, Javanmard F, Flury T, Ahannach S, Lebeer S, Hanssen E, Snipen L, Bokulich NA, Kümmerli R, Arora N.   +13 more
europepmc   +1 more source

Low‐Activation Compositionally Complex Alloys for Advanced Nuclear Applications—A Review

Advanced Engineering Materials, EarlyView.
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, Hanliang Zhu, Zhiyang Wang, Zhijun Qiu, Xiao Wang, Zengxi Pan, Hongtao Zhu, Mingxing Zhang, Huijun Li   +8 more
wiley   +1 more source

Analysis of rare events in healthcare intervention using department of defense data: intravenous immune globulin therapy for bullous pemphigoid. [PDF]

BMC Med Res Methodol
Baser O, Yuce H, Samayoa G.
europepmc   +1 more source

An Examination of Aerosol Jet‐Printed Surface Roughness and its Impact on the Performance of High‐Frequency Electronics

Advanced Engineering Materials, EarlyView.
This study explores aerosol jet‐printed (AJP) surface roughness, its effects on the performance of microwave electronics, and its process contributors. First, an electromagnetic model is vetted for AJP's unique roughness signature. Simulations are built which show process‐induced roughness is as significant as conductor resistivity in driving microwave
Christopher Areias, Alkim Akyurtlu
wiley   +1 more source