Results 281 to 290 of about 1,958,447 (346)

A Framework for Applying Data Integration and Curation Pipelines to Support Integration of Migrants and Refugees in Europe

, 2016
Oya Beyan, Siegfried Handschuh, Adamantios Koumpis, Garyfallos Fragidis, Stefan Decker   +4 more
openalex   +2 more sources

Development of a Novel Processing Route for Dispersoid/Precipitation‐Strengthened High Conductive Copper Alloys by Using Metalized Nanoceramics in Additive Manufacturing

Advanced Engineering Materials, EarlyView.
This study explores a process chain to produce dispersoid‐strengthened CuCr1Zr for applications requiring high strength and conductivity. Using gas‐atomized powder and copper‐plated alumina nanoparticles, additive manufacturing is performed via powder bed based additive manufacturing with green and red lasers, followed by heat treatment.
Heinrich von Lintel, Abdelrahman Elsayed, Lukas Mielewczyk, Katja Eichmann, Julia Grothe, Ulrich Krupp, Avinash Hariharan, Katrin Jahns   +7 more
wiley   +1 more source

Site-based data curation based on hot spring geobiology. [PDF]

PLoS One, 2017
Palmer CL, Thomer AK, Baker KS, Wickett KM, Hendrix CL, Rodman A, Sigler S, Fouke BW.   +7 more
europepmc   +1 more source

Trans‐Conductive Melt Pool Scaling and its Implications for Parameter Transfer in Laser Powder Bed Fusion for Metals with High Thermal Diffusivity

Advanced Engineering Materials, EarlyView.
Developing process parameters for the laser‐based Powder Bed Fusion of metals can be a tedious task. Based on melt pool depth, the process parameters are transferable to different laser scan speeds. For this, understanding the melt pool scaling behavior is essential, particularly for materials with high thermal diffusivity, as a change in scaling ...
Markus Döring, Matthias Gehring, Michael Schmidt   +2 more
wiley   +1 more source

Scaling up data curation using deep learning: An application to literature triage in genomic variation resources. [PDF]

PLoS Comput Biol, 2018
Lee K, Famiglietti ML, McMahon A, Wei CH, MacArthur JAL, Poux S, Breuza L, Bridge A, Cunningham F, Xenarios I, Lu Z.   +10 more
europepmc   +1 more source

Analysis of Temperature and Stress Distribution on the Bond Properties of Hybrid Tailored Formed Components

Advanced Engineering Materials, EarlyView.
Hybrid materials enable high‐performance components but are challenging to process. This study explores an inductive heating concept with spray cooling for steel–aluminum specimens in a two‐step process including friction welding and cup backward extrusion.
Armin Piwek, Eduard Ortlieb, Caner‐Veli Ince, Julius Peddinghaus, Hendrik Wester, Johanna Uhe, Annika Raatz, Kai Brunotte   +7 more
wiley   +1 more source

Value, but high costs in post-deposition data curation. [PDF]

Database (Oxford), 2016
ten Hoopen P, Amid C, Buttigieg PL, Pafilis E, Bravakos P, Cerdeño-Tárraga AM, Gibson R, Kahlke T, Legaki A, Narayana Murthy K, Papastefanou G, Pereira E, Rossello M, Luisa Toribio A, Cochrane G.   +14 more
europepmc   +1 more source

Faculty Opinions recommendation of Trust, but verify II: A practical guide to chemogenomics data curation.

, 2016
John Lowe
openalex   +1 more source

A Perspective on Powder Metallurgy and Additive Manufacturing of High‐Nitrogen Alloyed Stainless Steels

Advanced Engineering Materials, EarlyView.
This perspective article explores an innovative powder metallurgical approach to producing high‐nitrogen steels by utilizing a mixture of stainless steel and Si3N4. This mixture undergoes hot isostatic pressing followed by direct quenching. The article also examines adapting this method to laser powder bed fusion (PBF‐LB/M) to overcome nitrogen ...
Louis Becker, Felix Radtke, Jonathan Lentz, Simone Herzog, Christoph Broeckmann, Sebastian Weber   +5 more
wiley   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

Advanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, Saeed Saber‐Samandari, Jung‐il Song   +4 more
wiley   +1 more source