Memcapacitive to Memristive Transition in Al/Y<sub>2</sub>O<sub>3</sub>/GZO Crossbar Array

Kumar, Sanjay; Gautam, Mohit Kumar; Yadav, Saurabh; Mukherjee, Shaibal

doi:10.1109/ted.2023.3265622

Cited by 2 publications

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2D MoS2 monolayers integration with metal oxide-based artificial synapses

Gautam,

Kumar,

Rani

et al. 2024

Front. Nanotechnol.

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In this study, we report on a memristive device structure wherein monolayers of two-dimensional (2D) molybdenum disulfide (MoS2) are integrated with an ultrathin yttrium oxide (Y2O3) layer to simulate artificial synapses functionality. The proposed physical simulation methodology is implemented in COMSOL Multiphysics tool and is based on the minimization of free energy of the used materials at the applied input voltage. The simulated device exhibits a stable bipolar resistive switching and the switching voltages is significantly reduced by increasing the number of MoS2 layers, which is key to conventional low-power computing and neuromorphic applications. The device is shown to perform synaptic functionalities under various applied bias conditions. The resulting synaptic weight decreases almost linearly with the increasing number of MoS2 layers due to the increase in the device thickness. The simulation outcomes pave the way for the development of optimised metal oxide-based memristive devices through their integration with semiconducting 2D materials. Also, the 2D MoS2 integration can enable the optoelectronic operation of this memory device.

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2D MoS2 monolayers integration with metal oxide-based artificial synapses

Gautam,

Kumar,

Rani

et al. 2024

Front. Nanotechnol.

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Non-Idealities in Memristor Devices and Methods of Mitigating Them

Ahsan Kaleem,

Cai,

Chang

et al. 2024

Memristors - The Fourth Fundamental Circuit Element - Theory, Device, and Applications

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One of the main issues that memristors face, like other hardware components, is non-idealities (that can arise from long-term usage, low-quality hardware, etc.). In this chapter, we discuss some ways of mitigating the effects of such non-idealities. We consider both hardware-based solutions and universal solutions that do not depend on hardware or specific types of non-idealities, specifically in the context of memristive neural networks. We compare such solutions both theoretically and empirically using simulations. We also explore the different non-idealities in depth, such as device faults, endurance, retention, and finite conductance states, considering what causes them and how they can be avoided, and present ways of simulating these non-idealities in software.

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Memcapacitive to Memristive Transition in Al/Y₂O₃/GZO Crossbar Array

Cited by 2 publications

References 50 publications

2D MoS2 monolayers integration with metal oxide-based artificial synapses

2D MoS2 monolayers integration with metal oxide-based artificial synapses

Non-Idealities in Memristor Devices and Methods of Mitigating Them

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Memcapacitive to Memristive Transition in Al/Y2O3/GZO Crossbar Array

Cited by 2 publications

References 50 publications

2D MoS2 monolayers integration with metal oxide-based artificial synapses

2D MoS2 monolayers integration with metal oxide-based artificial synapses

Non-Idealities in Memristor Devices and Methods of Mitigating Them

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Memcapacitive to Memristive Transition in Al/Y₂O₃/GZO Crossbar Array