Results 111 to 120 of about 4,904 (261)

Neuromorphic Devices and Computing for Sensing, Memory, and Control

open access: yesAdvanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu   +2 more
wiley   +1 more source

Analog Synaptic Plasticity in 2D Layered Material Iontronic Memtransistors for Brain‐Inspired Computing

open access: yesAdvanced Science, EarlyView.
In this work, we demonstrated a robust 2D MoS2 based iontronic memtransistor of planar architecture operated under the influence of an electrical double layer with versatile performance and applications, including pinched hysteresis nature of transfer curve, analogue channel conductance tuning, low‐voltage operation, logic‐gate operation, classical ...
Puranjay Saha   +2 more
wiley   +1 more source

Supramolecular Protection–Deprotection for Switching Pore‐Surface Functionality in a Crystalline Porous Organic Salt

open access: yesAngewandte Chemie, EarlyView.
A supramolecular protection–deprotection strategy temporally separates the framework construction from pore‐surface activation in a porous organic salt. In Form I, phenolic OH groups are protected by DMSO, enabling framework formation. Stepwise single‐crystal‐to‐single‐crystal phase transformation (SCSC) affords a dormant intermediate (Form II ...
Kazuki Shiga   +4 more
wiley   +2 more sources

Millisecond‐Scale Relaxation in Metastable HZO Ferroelectric Capacitors for Bio‐Inspired Temporal Computing

open access: yesAdvanced Electronic Materials, EarlyView.
Through the introduction of a niobium oxide layer into a hafnia ferroelectric capacitor stack, we build a memory device with a strong imprint effect. This imprint leads to a millisecond retention loss that can be tuned by the programming conditions that can be utilized as a scalable, analog hardware time constant for bio‐inspired temporal computing ...
Luca Fehlings   +3 more
wiley   +1 more source

Experimental Study on Seismic Performance of Fire-Damaged Concrete-Filled Steel Tubular Column-Steel Beam Joints Under Low-Cycle Reversed Loading

open access: yesBuildings
As a typical steel-concrete composite structure, Concrete-Filled Steel Tubular (CFST) structures utilize the synergistic mechanical advantages of steel and concrete, showing good performance in bearing capacity, ductility and fire resistance, and ...
Fang Liu   +5 more
doaj   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

open access: yesAdvanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel   +6 more
wiley   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

open access: yesAdvanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj   +4 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

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

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