Results 101 to 110 of about 5,876,040 (331)

Evaluating Dielectric Properties for Semicrystalline Thermoplastics to Analyze the Thermal and Rheological Properties in Laser‐Based Powder Bed Fusion of Plastics

open access: yesAdvanced Engineering Materials, EarlyView.
This study aims to establish a link between the dielectric properties of polyamide 12 (PA12) and its thermal and rheological properties using dielectric analysis (DEA). A standardized methodology is introduced to determine melting and crystallization temperatures.
Benedikt Burchard   +2 more
wiley   +1 more source

New Developments in the Field of Production and Application of Multi‐Material Wire Arc Additive Manufacturing Components: A Review

open access: yesAdvanced Engineering Materials, EarlyView.
The utilization of direct energy deposition (DED)‐arc additive manufacturing processes in industrial applications is increasing, and these processes have the potential for multi‐material applications. This work provides a overview of the state of research in DED‐arc made functional graded structures, to establish a link to potential industrial ...
Kai Treutler, Volker Wesling
wiley   +1 more source

Stratum Corneum‐Inspired Zwitterionic Hydrogels with Intrinsic Water Retention and Anti‐Freezing Properties for Intelligent Flexible Sensors

open access: yesAdvanced Functional Materials, EarlyView.
A novel stratum corneum‐inspired zwitterionic hydrogel is developed for intelligent, flexible sensors, featuring intrinsic water retention and anti‐freezing properties. The quasi‐gel, composed of hygroscopic polymers and bound water, maintains its softness across a wide range of humidity.
Meng Wu   +8 more
wiley   +1 more source

Heat Conduction Modulation in Incommensurate Twisted Stacking of Transition‐Metal Dichalcogenide

open access: yesAdvanced Functional Materials, EarlyView.
The interlayer thermal conductance in twisted bilayer TMDs is initially investigated experimentally by the thermoreflectance method. The overlap of lattice vibrations within individual layers and the interlayer interactions, as elucidated through both Raman spectroscopy and molecular dynamics simulations, are demonstrated to be critical factors in ...
Bin Xu   +6 more
wiley   +1 more source

Munchausen Reinforcement Learning

open access: yes, 2020
NeurIPS 2020.
Vieillard, Nino   +2 more
openaire   +3 more sources

Self‐organized Criticality in Neuromorphic Nanowire Networks With Tunable and Local Dynamics

open access: yesAdvanced Functional Materials, EarlyView.
Memristive nanowire networks (NWNs) are shown to be electrically tunable to a critical state where specific local dynamics evaluated by multiterminal characterization are exploited as feature selection in nonlinear transformation (NLT) tasks.
Fabio Michieletti   +3 more
wiley   +1 more source

Autonomous Control of Extrusion Bioprinting Using Convolutional Neural Networks

open access: yesAdvanced Functional Materials, EarlyView.
This work presents a novel computer vision system for high‐fidelity monitoring of extrusion‐based bioprinting and a correction system utilizing convolutional neural networks for error mitigation. This system has demonstrated high detection accuracy and extrusion correction abilities that advance the state of the art toward accelerated printing ...
Daniel Kelly   +4 more
wiley   +1 more source

How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review

open access: yesMayo Clinic Proceedings: Digital Health
To assess the current real-world applications of machine learning (ML) and artificial intelligence (AI) as functionality of digital behavior change interventions (DBCIs) that influence patient or consumer health behaviors.
Amy Bucher, PhD   +2 more
doaj  

Differential effects of reward and punishment in decision making under uncertainty: a computational study.

open access: yesFrontiers in Neuroscience, 2014
Computational models of learning have proved largely successful in characterising potentialmechanisms which allow humans to make decisions in uncertain and volatile contexts.
Elaine eDuffin   +3 more
doaj   +1 more source

Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting

open access: yesAdvanced Functional Materials, EarlyView.
High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal   +5 more
wiley   +1 more source

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