Results 111 to 120 of about 13,297 (272)
Photoresponsive Rotaxanes Switch Lipid Bilayer Neuromorphic Behavior with Light
A rotaxane consisting of a macrocycle ring with two azobenzene units mechanically interlocked onto an amphiphilic axle was incorporated into droplet interface bilayers (DIBs). Photoswitching between the azobenzene configurations on the ring resulted in cycling between memristive and memcapacitive behaviors in lipid bilayers, enabling programmable ...
P.T. Podar +4 more
wiley +1 more source
Tunable stochastic memristors for energy-efficient encryption and computing
Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements – security (encryption) requires a source of unpredictability, while computing generally requires predictability.
Kyung Seok Woo +6 more
doaj +1 more source
Model‐Based Time‐Modulated Write Algorithm for 1R Analog Memristive Crossbar Arrays
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
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa +6 more
wiley +1 more source
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
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
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
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
Memristors are recognized as crucial devices for the hardware implementation of neuromorphic computing. The conductance training process of memristors has a direct impact on the performance of neuromorphic computing.
Qin Xie +8 more
doaj +1 more source
Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol +7 more
wiley +1 more source

