Results 111 to 120 of about 24,617 (263)

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

open access: yesAdvanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith   +4 more
wiley   +1 more source

用随机无网格点插值法分析齿轮弯曲疲劳强度的可靠性

open access: yesJixie chuandong, 2005
The bending fatigue reliability of gear teeth has been analyzed by perturbation stochastic meshless point interpolation method(PSMPIM).In the meshless point interpolation method the problem domain is represented by properly scattered points.A technique ...
游世辉   +3 more
doaj  

Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays

open access: yesAdvanced Electronic Materials, EarlyView.
A novel model‐based time‐modulated write algorithm efficiently programs analog 1R memristive crossbar arrays by varying pulse duration at a fixed voltage. By leveraging a physics‐based compact model and a dynamic gain mechanism, this approach overcomes device nonlinearities and parasitic effects.
Richard Schroedter   +7 more
wiley   +1 more source

Synchronization of Analog Neuron Circuits With Digital Memristive Synapses: An Hybrid Approach

open access: yesAdvanced Electronic Materials, EarlyView.
An hybrid circuit mimicking neural units coupled using memristive synapses is introduced. The analog neurons provide flexibility and robustness, and the digital memristive coupling guarantees the full reconfigurability of the interconnection. The onset of a synchronized spiking behavior in two circuits mimicking the Izhikevich neuron is discussed from ...
Lamberto Carnazza   +3 more
wiley   +1 more source

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

open access: yesAdvanced Electronic Materials, EarlyView.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci   +6 more
wiley   +1 more source

Scan‐Path‐ and Initial‐State‐Dependent Superdomain Switching in (111)‐Oriented PZT

open access: yesAdvanced Electronic Materials, EarlyView.
Scan trajectory and initial superdomain topology govern polarization switching in (111)‐oriented PZT. Automated AFM writing, pulsing experiments, and interferometric 3D‐PFM show that raster scans reproducibly stabilize ordered Type‐I stripe superdomains with constrained variant selection, whereas spiral trajectories generate frustrated mixed‐variant ...
Rama Vasudevan   +11 more
wiley   +1 more source

A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration

open access: yesAdvanced Electronic Materials, EarlyView.
Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti   +6 more
wiley   +1 more source

Wetting‐Driven Transfer of Flexible Ultra‐Thin Temperature Sensors

open access: yesAdvanced Electronic Materials, EarlyView.
A wetting‐driven transfer approach enables ultra‐thin temperature sensors to be transferred from a super‐hydrophilic donor substrate onto rigid, curved, and biological receiver substrates. By combining controlled wetting with a conformal Parylene carrier layer, the method preserves stable thermal sensing performance while expanding the integration of ...
Hafiza Faiqa Maqsood   +5 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

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