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 computing1,2,3,4,5,6. Memristors have higher endurance and faster read/write times than flash memory4,7,8 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 plasticity3,9,10,11,12,13. Previous attempts to move beyond two-terminal memristors, such as the three-terminal Widrow–Hoff memristor14 and field-effect transistors with nanoionic gates15 or floating gates16, did not achieve memristive switching in the transistor17. 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 materials18,19,20,21,22.
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This research was supported by the Materials Research Science and Engineering Center (MRSEC) of Northwestern University (NSF DMR-1720139) and the 2-DARE programme (NSF EFRI-1433510). The CVD growth of MoS2 was supported by the National Institute of Standards and Technology (NIST CHiMaD 70NANB14H012). Charge transport instrumentation was funded by an ONR DURIP grant (ONR N00014-16-1-3179). H.-S.L. acknowledges the Basic Science Research Program of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Education (2017R1A6A3A03008332). H.B. acknowledges support from the NSERC Postgraduate Scholarship–Doctoral Program. H.B. and M.E.B. acknowledge support from the National Science Foundation through a Graduate Research Fellowship. For this work, we used the Northwestern University NUANCE Center and the Northwestern University Micro/Nano Fabrication Facility (NUFAB), which are partially supported by the Soft and Hybrid Nanotechnology Experimental (SHyNE) Resource (NSF ECCS-1542205), the Materials Research Science and Engineering Center (NSF DMR-1720139), the State of Illinois and Northwestern University. We thank J. J. McMorrow for assistance with photolithography, X. Liu for assistance with lateral force microscopy and S. Mohseni for assistance with atomic force microscopy.
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Nature Reviews Materials (2018)