Results 141 to 150 of about 72,066 (264)

Electrode‐Engineered Dual‐Mode Multifunctional Lead‐Free Perovskite Optoelectronic Memristors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos, Konstantinos Rogdakis, Konstantinos Chatzimanolis, Katerina Anagnostou, Emmanuel Kymakis   +4 more
wiley   +1 more source

Photoresponsive Rotaxanes Switch Lipid Bilayer Neuromorphic Behavior with Light

Advanced Electronic Materials, EarlyView.
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, U.N.K. Conthagamage, J. Katsaras, V. García‐López, C. P. Collier   +4 more
wiley   +1 more source

Agar-Based Resistive Switching Memory for Neuromorphic Applications. [PDF]

ACS Omega
Chen HC, Kao IC, Lai KJ, Chen CY, Chang YC.   +4 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, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Synaptic plasticity in Hippocampus. Long-term depression and its relation to long-term potentiation

, 1998
Synaptic plasticity has long been considered as a cellular basis for learning and memory. The most prominent forms of such plasticity are the homosynaptic long-term potentiation (LTP) and long-term depression (LTD) in the hippocampus. The aim of the present study has been to advance the understanding of the mechanisms involved in the expression of ...
openaire  

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Addictive drug abuse and depression-a focus on epigenetics. [PDF]

Commun Biol
Zhang W, Xu M, Wang C, Liang H, Zhu X, Pan Y, Guo F.   +6 more
europepmc   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Molecular Mechanisms of Emerging Antidepressant Strategies: From Ketamine to Neuromodulation. [PDF]

Int J Mol Sci
Kowalczyk M, Aebisher D, Szpara J, Czech S, Bartusik-Aebisher D, Henrykowska G.   +5 more
europepmc   +1 more source

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source