journal article·2023-11-28

Nonvolatile Bioresistive Random Access Memory Based on Glycine max and Graphene Oxide

Lu Wang, Jiazhuang Li, Wantao Su, Dianzhong Wen

ACS Applied Electronic Materials· Volume 5· Issue 11
Publisher page

Abstract

Devices that realize memory functions and simulate synaptic characteristics are an important part of realizing artificial neural networks. In this article, a bioresistive random access memory based on Glycine max and graphene oxide (GO) is proposed. The devices can simulate the potentiation and depression of synapses under pulsed voltage stimulation. The device has different low resistance values under different compliance currents, which can realize multilevel data storage (4 levels, 2 bits) on the same cell. With the change in GO concentration, the ON/OFF current ratio of the devices can be adjusted in the range of 10–10 4 . Since the minimum operating voltage is ±1 V, the power consumption of the devices is low. Multilevel tunable nonvolatile resistive random access memory has great potential in data storage and artificial synapses in the future.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Electronic Engineering, Heilongjiang University, Harbin 150080, China

Funding

Natural Science Foundation of Heilongjiang Province · National Natural Science Foundation of China · Basic Research Business Funding for Provincial Universities in Heilongjiang Province

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