Results 261 to 270 of about 3,573,253 (377)
TOWARDS AN ABM-BASED FRAMEWORK FOR INVESTIGATING CONSUMER BEHAVIOUR IN THE INSURANCE INDUSTRY
Aurelija Ulbinaitė, Yannick Le Moullec
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Consumers behaviour of students when shopping for organic food in the Czech Republic [PDF]
Martina Zámková, Martin Prokop
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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
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
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The fabrication and post‐treatment via solvent annealing of poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate‐based electrodes using spray deposition in a roll‐to‐roll setup are presented. The decrease in sheet resistance and its correlation with nanostructure and molecular structure in the electrodes as a function of the processing parameters is ...
Marie Betker+10 more
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Motivation and consumer behaviour in the context of loyalty programs [PDF]
Klára Mrkosová+2 more
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Enhanced Fog Water Harvesting on Superhydrophobic Steel Meshes
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+3 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
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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
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