Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide

By Vinod K. Sangwan, Hong-Sub Lee, Hadallia Bergeron, Itamar Balla, M. Beck, K. Chen, Mark C. Hersam. Nature, 2018

877 citations recorded by the source corpus.

Memristors are two-terminal passive circuit elements that have been developed for use in non-volatile resistive random-access memory and may also be useful in neuromorphic computing. Memristors have higher endurance and faster read/write times than flash memory and can provide multi-bit data storage. However, although two-terminal memristors have demonstrated capacity for basic neural functions, synapses in the human brain outnumber neurons by more than a thousandfold, which implies that multi-terminal memristors are needed to perform complex functions such as heterosynaptic plasticity. Previous attempts to move beyond two-terminal memristors, such as the three-terminal Widrow–Hoff memristor and field-effect transistors with nanoionic gates or floating gates, did not achieve memristive switching in the transistor. Here we report the experimental realization of a multi-terminal hybrid memristor and transistor (that is, a memtransistor) using polycrystalline monolayer molybdenum disulfide (MoS2) in a scalable fabrication process. The two-dimensional MoS2 memtransistors show gate tunability in individual resistance states by four orders of magnitude, as well as large switching ratios, high cycling endurance and long-term retention of states. In addition to conventional neural learning behaviour of long-term potentiation/depression, six-terminal MoS2 memtransistors have gate-tunable heterosynaptic functionality, which is not achievable using two-terminal memristors. For example, the conductance between a pair of floating electrodes (pre- and post-synaptic neurons) is varied by a factor of about ten by applying voltage pulses to modulatory terminals. In situ scanning probe microscopy, cryogenic charge transport measurements and device modelling reveal that the bias-induced motion of MoS2 defects drives resistive switching by dynamically varying Schottky barrier heights. Overall, the seamless integration of a memristor and transistor into one multi-terminal device could enable complex neuromorphic learning and the study of the physics of defect kinetics in two-dimensional materials.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/20230912b9ad9c4d923c89045898c7e6f96936c7

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In Biomedical Engineering

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In Electrical and Electronic Engineering

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In Materials Chemistry

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6. Yongsheng Chen
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Citations in the corpus

• Three-dimensional memristor circuits as complex neural networks (2020, background): “Emerging non-volatile devices 4,5 , such as memris-tors 6–8 , can directly implement synaptic weights and efficiently carry out resource-hungry matrix operations inside ensemble arrays 9–17 .”