Results 211 to 220 of about 2,571,381 (260)

Consumer Behavior Toward Andean Grains Among Young Peruvian Adults: Purchase Patterns, Motivations, and Barriers Across Cultural Contexts. [PDF]

open access: yesFoods
Millones-Liza DY   +5 more
europepmc   +1 more source

Enhancement of the Through‐Thickness Electrical Conductivity of Carbon‐Fiber‐Reinforced Plastics Using Large Graphite Particles

open access: yesAdvanced Engineering Materials, EarlyView.
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe   +6 more
wiley   +1 more source

Rotary 3D Printing With Integrated Electroplating

open access: yesAdvanced Engineering Materials, EarlyView.
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria   +5 more
wiley   +1 more source

Consumer choice between common generic and brand medicines in a country with a small generic market. [PDF]

open access: yesJ Manag Care Spec Pharm, 2015
Fraeyman J   +5 more
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose   +7 more
wiley   +1 more source

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