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Brain-inspired computation that mimics the coordinated functioning of neural networks through multitudes of synaptic connections is deemed to be the future of computation to overcome the classical von Neumann bottleneck. The future artificial intelligence circuits require scalable electronic synapse (e-synapses) with very high bit densities and operational speeds. in this respect, nanostructures of two-dimensional materials serve the purpose and offer the scalability of the devices in lateral and vertical dimensions. in this work, we report the nonvolatile bipolar resistive switching and neuromorphic behavior of molybdenum disulfide (MoS 2) quantum dots (QD) synthesized using liquid-phase exfoliation method. The ReRAM devices exhibit good resistive switching with an On-Off ratio of 10 4 , with excellent endurance and data retention at a smaller read voltage as compared to the existing MoS 2 based memory devices. Besides, we have demonstrated the e-synapse based on MoS 2 QD. Similar to our biological synapse, paired pulse facilitation / Depression of short-term memory has been observed in these MoS 2 QD based e-synapse devices. this work suggests that MoS 2 QD has potential applications in ultra-high-density storage as well as artificial intelligence circuitry in a costeffective way.

Hybrid perovskites have emerged as an excellent class of materials for resistive random access memory (ReRAM) devices and neuromorphic computing applications. Among numerous perovskites, formamidinium lead triiodide (α-FAPbI3) is an...

The biggest challenge in the resistive random access memory (ReRAM) technology is that the basic operational parameters, such as the set and reset voltages, the current on-off ratios (hence the power), and their operational speeds, strongly depend on the active and electrode materials and their processing methods. Therefore, for its actual technological implementations, the unification of the operational parameters of the ReRAM devices appears to be a difficult task. In this letter, we show that by fabricating a resistive memory device in a thin film transistor configuration and thus applying an external gate bias, we can control the switching voltage very accurately. Taking partially reduced graphene oxide, the gate controllable switching is demonstrated, and the possible mechanisms are discussed.

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