Results 161 to 170 of about 14,142 (285)
Reconfigurable Selector‐Only Memory (SOM) for Scalable Neuromorphic Computing
ABSTRACT Highly scalable reconfigurable neuromorphic devices are critical for addressing continual‐learning challenges in artificial intelligence. However, the scalability of existing reconfigurable devices is severely constrained by limited operating margins and insufficient process maturity.
Jin‐Yu Wen +7 more
wiley +1 more source
Confined-hydrogel fluidic memristor crossbar array for neuromorphic computing. [PDF]
Guo G +12 more
europepmc +1 more source
A nanoporous SiO2 memristor enabling reconfigurable volatile and non‐volatile switching within a single device is demonstrated. The dual‐mode functionality supports both physical reservoir dynamics and synaptic weight storage, allowing unified hardware implementation of reservoir computing for temporal information processing, including image and ...
Bohao Ding +5 more
wiley +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source
Engineering and Exploiting Self-Driven Domain Wall Motion in Ferrimagnets for Neuromorphic Computing Applications. [PDF]
Brock JA +4 more
europepmc +1 more source
Rational engineering of terminal substituents in symmetric azobenzene‐based molecules enables precise control over conformationally coupled charge‐transfer processes. This design yields tunable nonvolatile resistive memory behaviors, ranging from write‐once‐read‐many‐times (WORM) to rewritable switching.
Yanze Liu +11 more
wiley +1 more source
Leveraging Electrochemical Diversity in Engineering Liquid-State Ionic Devices for Neuromorphic Computing. [PDF]
Noh Y, Smolyanitsky A.
europepmc +1 more source
2D materials and van der Waals heterojunctions for neuromorphic computing
Yang, D +6 more
core +1 more source

