Results 191 to 200 of about 3,037,320 (289)

Autonomous Molecular Sensing with a Chemically Stateful Solid-State Nanopore. [PDF]

open access: yesACS Nano
Tsutsui M   +9 more
europepmc   +1 more source

Oxygen‐Scavenging‐Driven Interlayer Engineering for Balancing Linearity and Retention in IGZO Synaptic Memristors

open access: yesAdvanced Electronic Materials, EarlyView.
Oxygen‐scavenging‐induced self‐formed interlayers regulate Schottky‐barrier modulation in IGZO memristors, producing a fundamental trade‐off between synaptic update linearity and retention. A preserved AlOx interlayer moderates voltage distribution and enables gradual, nearly linear conductance updates, whereas a soft‐broken SiO2 interlayer provides a ...
Jae Woo Lee   +11 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

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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