Results 131 to 140 of about 862,343 (216)

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks. [PDF]

HGG Adv
Tsai YT, Hrytsenko Y, Elgart M, Tahir UA, Chen ZZ, Wilson JG, Gerszten RE, Sofer T.   +7 more
europepmc   +1 more source

A Novel Approach on Rapid Alloy Development of Tool Steels for Laser Powder Bed Fusion by In Situ Alloying

Advanced Engineering Materials, EarlyView.
A novel approach for alloy development in laser powder bed fusion is introduced. Instead of producing massive samples of one composition at a time, prepressed powder bed samples produced from powder mixtures are processed. Guidelines for the selection of precursor powders are developed.
Felix Großwendt, Anna Strauch, Jonathan Lentz, Arne Röttger, Rainer Fechte‐Heinen, Sebastian Weber, Werner Theisen   +6 more
wiley   +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

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

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

Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes

Advanced Engineering Materials, EarlyView.
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, Mohammad Reza Mohammadizadeh, Carlo Antonini, Raziyeh Akbari   +3 more
wiley   +1 more source

A pseudo-response approach to constructing confidence intervals for the subset of patients expected to benefit from a new treatment. [PDF]

J R Stat Soc Ser C Appl Stat
Liu W, Zhang Z, Hu Z, Xu P, Cohen CJ.
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

Confidence intervals.

BMJ, 1988
openaire   +3 more sources

Static Recrystallization Simulation of Interstitial Free‐Steel by Coupling Multi‐Phase‐Field and Crystal Plasticity Model Considering Dislocation Density Distribution

Advanced Engineering Materials, EarlyView.
This study models static recrystallization in interstitial free‐steel using coupled crystal plasticity and phase‐field simulations. The method directly links heterogeneous dislocation density to nucleation site prediction, eliminating reliance on empirical assumptions.
Alireza Rezvani, Ramin Ebrahimi, Ebad Bagherpour   +2 more
wiley   +1 more source

A Simulative Approach for the Prediction of Mesoscale Residual Stress Fields in Solution‐Strengthened Ferritic Ductile Iron

Advanced Engineering Materials, EarlyView.
This study presents a 3D representative volume element‐based simulation approach to predict mesoscopic residual stress and strain fields in silicon solid solution‐strengthened ductile cast iron. By modeling phase transformation kinetics with an enhanced Johnson–Mehl–Avrami–Kolmogorov model, the effects of varying cooling rates on residual stresses are ...
Lutz Horbach, Oliver Schenk, Valérian Iss, Ali Rajaei, Jiali Zhang, Felix Weber, Christoph Broeckmann   +6 more
wiley   +1 more source