Results 151 to 160 of about 327,410 (288)

Lead‐Free Bismuth Halide Perovskite Memristors: Low‐Voltage Switching and Physical Modeling of Resistive Hysteresis

open access: yesAdvanced Materials Technologies, EarlyView.
Lead‐free bismuth halide perovskite memristors exhibit stable low‐voltage resistive switching behavior. The conductance‐activated quasi‐linear memristor model quantitatively reproduces the experimental hysteresis, confirming ion migration‐driven filament dynamics.
So‐Yeon Kim   +4 more
wiley   +1 more source

Enhanced Trapping with an Optimized Graphene‐Based Bowtie Plasmonic Nanotweezer: Design, Analysis, and Bioanalytical Applications

open access: yesAdvanced Photonics Research, EarlyView.
A graphene‐based bowtie plasmonic nanotweezer is designed and optimized using particle swarm optimization and transfer matrix analysis. The structure achieves strong field confinement, delivering trapping forces up to 6 nN W−1 for 10 nm bioparticles with sixfold lower power requirements than conventional designs.
Saba Ebrahimpanah   +2 more
wiley   +1 more source

Information Transmission Strategies for Self‐Organized Robotic Aggregation

open access: yesAdvanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng   +5 more
wiley   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

open access: yesAdvanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek   +3 more
wiley   +1 more source

Data‐Driven Multi‐Objective Optimization of Large‐Diameter Si Floating‐Zone Crystal Growth

open access: yesAdvanced Theory and Simulations, EarlyView.
This study presents a surrogate‐based Multi‐Objective Optimization framework for Floating Zone silicon crystal growth. An ensemble of Neural Networks is trained on simulation data and combined with Genetic Algorithms to explore trade‐offs in process parameters.
Lucas Vieira   +3 more
wiley   +1 more source

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