Results 171 to 180 of about 14,306 (300)
Advanced Electronic Materials, EarlyView.A non‐destructive, quantitative approach has been developed to explore the nanoscale dynamics of TaOx‐based memristive devices. The utilization of nano‐X‐ray fluorescence analysis enables the direct probing of spatially resolved elemental distributions, including those present in buried layers, that are critical for the resistive switching.
André Wählisch +9 more
wiley +1 more source
Ultra-low-power probabilistic graphical computing based on memristors enabling communications signal processing. [PDF]
Nat CommunJiang C +7 more
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.ABSTRACT With the continuous development of computer image processing, developing efficient and low‐power computing devices has become a key challenge. Memristors have integrated in‐situ storage and computing capabilities, making them an ideal choice for low‐power image processing computing architectures. However, current memristors are confronted with
Tengyu Li +4 more
wiley +1 more source
Citation: 'memristor' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.08840 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms.
openaire +1 more source
Synchronization of Analog Neuron Circuits With Digital Memristive Synapses: An Hybrid Approach
Advanced 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
Deterministic Switching-Path Engineering of CMOS-Integrated 2D Memristors for Neuromorphic Computing. [PDF]
SmallYang J +12 more
europepmc +1 more source
SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range
Advanced 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
Advanced Electronic Materials, EarlyView.ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez +10 more
wiley +1 more source
PLANT SUCCESS: The consequence of the hysteretic responses of leaves to ambient water vapor, carbon dioxide, light intensity, and temperature. [PDF]
J Biol PhysPeak D, Frame M.
europepmc +1 more source