Synaptic Plasticity and Visual Memory in a Neuromorphic 2D Memitter Based on WS2 Monolayers
Source abstract
Abstract
Abstract Neuromorphic computing aims to leverage physical phenomena of adaptive materials for emulating information processing capabilities and effectiveness of biological neuronal circuits. In this framework, memristors (resistors with memory) based on 2D materials are demonstrated for the hardware implementation of highly integrated artificial neural networks. All the works reported thus far exploited electrical properties of 2D materials to emulate neuromorphic functionalities. Here, a 2D memitter (emitter with memory) is reported on that exploits the stimuli‐responsive photoluminescence of a monolayer WS2 for neuromorphic‐type of data processing. A combined experimental and modeling approach reveals that photoluminescent dynamics triggered by optical stimulation emulates Short‐Term synaptic Plasticity and Visual Short‐Term Memory typical of biological systems. While spatio‐temporal processing capabilities of input signals can be used for information processing in the context of reservoir computing, the capability of the 2D memitter of sensing, processing, and memorizing‐forgetting optical inputs in the same physical substrate can be utilized for in‐sensor computing.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Ferroelectric and Negative Capacitance Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Advanced Materials Metrology and Life Science Division INRiM (Istituto Nazionale di Ricerca Metrologica) Strada delle Cacce 91 Torino 10135 Italy
Department of Applied Science and Technology Politecnico di Torino C.so Duca degli Abruzzi 24 Torino 10129 Italy
CNR‐SCITEC via A. Corti 12 Milano 20133 Italy
CNR‐IMM Agrate Brianza Unit via C. Olivetti 2 Agrate Brianza 20864 Italy
Funding
Ministero dell'Università e della Ricerca
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