journal article·2024-03Open access

Organic-2D composite material-based RRAM with high reliability for mimicking synaptic behavior

Tangyou Sun, Fantao Yu, Xiaosheng Tang, Haiou Li, Fabi Zhang, Zhimou Xu, Qing Liao, Zhiqiang Yu, Xingpeng Liu, Peihua Wangyang, Hezhang Li, Ying Peng

Journal of Materiomics· Volume 10· Issue 2

Abstract

The field of artificial intelligence and neural computing has been rapidly expanding due to the implementation of resistive random-access memory (RRAM) based artificial synaptic. However, the low flexibility of conventional RRAM materials hinders their ability to mimic synaptic behavior accurately. To overcome such limitation, organic-2D composites with high mechanical properties are proposed as the active layer of RRAM. Moreover, we enhance the reliability of the device by ZrO2 insertion layer, resulting in stable synaptic performance. The Ag/PVA:h-BN/ZrO2/ITO devices show stable bipolar resistive switching behavior with an ON/OFF ratio of over 5 × 102, a ∼2400 cycles endurance and a long retention time (>6 × 103s), which are essential for the development of high-performance RRAMs. We also study the possible synaptic mechanism and dynamic plasticity of the memory device, observing the transition from short-term potentiation (STP) to long-term potentiation (LTP) under the effect of continuous voltage pulses. Moreover, the device exhibits both long-term depression (LTD) and paired-pulse facilitation (PPF) properties, which have significant implications for the design of organic-2D composite material RRAMs that aim to mimic biological synapses, representing promising avenues for the development of advanced neuromorphic computing systems.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · Conducting polymers and applications

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

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