Results 171 to 180 of about 13,303,652 (245)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

open access: yesAdvanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali   +3 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

Predictable and Scalable Analog Matrix–Vector Multiplication in Memristor Crossbars via Closed‐Form Wire‐Resistance Compensation

open access: yesAdvanced Electronic Materials, EarlyView.
Wire resistance and sneak paths severely compromise the performance of large memristor crossbars. A predictive closed‐form distributed line‐resistance model, combined with a fourmatrix geometry‐averaging algorithm, eliminates these parasitic limitations.
Davide Rossetti   +5 more
wiley   +1 more source

Harnessing the VO2 Phase Transition for Automatic Gain Control in Transimpedance Amplifiers

open access: yesAdvanced Electronic Materials, EarlyView.
A nanoscale VO2‐based volatile switch integrated into a transimpedance‐amplifier feedback loop dynamically lowers gain when input current rises, preventing saturation and extending dynamic range. Rapid self‐recovery restores high sensitivity without external reset circuitry.
Amir Gildor   +3 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

open access: yesAdvanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan   +12 more
wiley   +1 more source

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