A high-performance MoS2 synaptic device with floating gate engineering for neuromorphic computing

As one of the most important members of the two dimensional chalcogenide family, molybdenum disulphide (MoS2) has played a fundamental role in the advancement of low dimensional electronic, optoelectronic and piezoelectric designs. Here, we demonstrate a new approach to solid state synaptic transistors using two dimensional MoS2 floating gate memories. By using an extended floating gate architecture which allows the device to be operated at near-ideal subthreshold swing of 77 mV/decade over four decades of drain current, we have realised a charge tunneling based synaptic memory with performance comparable to the state of the art in neuromorphic designs. The device successfully demonstrates various features of a biological synapse, including pulsed potentiation and relaxation of channel conductance, as well as spike time dependent plasticity (STDP). Our device returns excellent energy efficiency figures and provides a robust platform based on ultrathin two dimensional nanosheets for future neuromorphic applications.

[1]  Wei Lu,et al.  Short-term Memory to Long-term Memory Transition in a Nanoscale Memristor , 2022 .

[2]  Arindam Ghosh,et al.  2D van der Waals Hybrid: Structures, Properties and Devices , 2017 .

[3]  Ajay Joshi,et al.  Performance and energy models for memristor-based 1T1R RRAM cell , 2012, GLSVLSI '12.

[4]  Byung-Gook Park,et al.  Silicon-Based Floating-Body Synaptic Transistor With Frequency-Dependent Short- and Long-Term Memories , 2016, IEEE Electron Device Letters.

[5]  Wang Yao,et al.  Valley polarization in MoS2 monolayers by optical pumping. , 2012, Nature nanotechnology.

[6]  Young-Jun Yu,et al.  Controlled charge trapping by molybdenum disulphide and graphene in ultrathin heterostructured memory devices , 2013, Nature Communications.

[7]  M. Hersam,et al.  Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide , 2018, Nature.

[8]  A. R. Newton,et al.  Alpha-power law MOSFET model and its applications to CMOS inverter delay and other formulas , 1990 .

[9]  Arindam Ghosh,et al.  Current crowding mediated large contact noise in graphene field-effect transistors , 2016, Nature Communications.

[10]  Byung-Gook Park,et al.  Spiking Neural Network Using Synaptic Transistors and Neuron Circuits for Pattern Recognition With Noisy Images , 2018, IEEE Electron Device Letters.

[11]  David A. Patterson,et al.  Computer Architecture: A Quantitative Approach , 1969 .

[12]  Hyunsang Hwang,et al.  Organic core-sheath nanowire artificial synapses with femtojoule energy consumption , 2016, Science Advances.

[13]  Arindam Ghosh,et al.  Percolative switching in transition metal dichalcogenide field-effect transistors at room temperature , 2015, Nanotechnology.

[14]  Kazushi Ikeda,et al.  Effects of kernel function on Nu support vector machines in extreme cases , 2006, IEEE Transactions on Neural Networks.

[15]  F. Xia,et al.  Anisotropic Black Phosphorus Synaptic Device for Neuromorphic Applications , 2016, Advanced materials.

[16]  K. Shepard,et al.  Boron nitride substrates for high-quality graphene electronics. , 2010, Nature nanotechnology.

[17]  Carver A. Mead,et al.  A single-transistor silicon synapse , 1996 .

[18]  Yuchao Yang,et al.  Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics , 2018, Advanced materials.

[19]  Farnood Merrikh-Bayat,et al.  High-Performance Mixed-Signal Neurocomputing With Nanoscale Floating-Gate Memory Cell Arrays , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[20]  Arindam Ghosh,et al.  Graphene-MoS2 hybrid structures for multifunctional photoresponsive memory devices. , 2013, Nature nanotechnology.

[21]  Ralph Etienne-Cummings,et al.  An Analogue Neuromorphic Co-Processor That Utilizes Device Mismatch for Learning Applications , 2018, IEEE Transactions on Circuits and Systems I: Regular Papers.

[22]  G. Malliaras,et al.  Neuromorphic Functions in PEDOT:PSS Organic Electrochemical Transistors , 2015, Advanced materials.

[23]  A. Radenović,et al.  Single-layer MoS2 transistors. , 2011, Nature nanotechnology.

[24]  Qing Wan,et al.  Artificial synapse network on inorganic proton conductor for neuromorphic systems. , 2014, Nature communications.

[25]  Gert Cauwenberghs,et al.  Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain , 2018, Front. Neurosci..

[26]  Arindam Ghosh,et al.  Seebeck Coefficient of a Single van der Waals Junction in Twisted Bilayer Graphene. , 2017, Nano letters.

[27]  G. Cerullo,et al.  Out-of-plane heat transfer in van der Waals stacks through electron–hyperbolic phonon coupling , 2017, Nature Nanotechnology.

[28]  Y. Dan,et al.  Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.

[29]  Kenneth L. Shepard,et al.  Electron tunneling through atomically flat and ultrathin hexagonal boron nitride , 2011 .

[30]  Young Sun,et al.  All‐Solid‐State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing , 2018, Advanced Functional Materials.

[31]  Shihab A. Shamma,et al.  Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time , 2015, Front. Neurosci..

[32]  K. Miller,et al.  Synaptic Economics: Competition and Cooperation in Synaptic Plasticity , 1996, Neuron.

[33]  Arindam Ghosh,et al.  1 / f noise in van der Waals materials and hybrids , 2017 .

[34]  Seongjun Park,et al.  Two-terminal floating-gate memory with van der Waals heterostructures for ultrahigh on/off ratio , 2016, Nature Communications.

[35]  SUPARNA DUTTASINHA,et al.  Van der Waals heterostructures , 2013, Nature.

[36]  Arindam Ghosh,et al.  Nature of electronic states in atomically thin MoS₂ field-effect transistors. , 2011, ACS nano.

[37]  L. Abbott,et al.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.

[38]  Ji Feng,et al.  Valley carrier dynamics in monolayer molybdenum disulfide from helicity-resolved ultrafast pump-probe spectroscopy. , 2013, ACS nano.

[39]  Junhwan Choi,et al.  Low‐Power Nonvolatile Charge Storage Memory Based on MoS2 and an Ultrathin Polymer Tunneling Dielectric , 2017 .

[40]  B. M. Gordon,et al.  Supply and threshold voltage scaling for low power CMOS , 1997, IEEE J. Solid State Circuits.

[41]  Moon J. Kim,et al.  MoS2 transistors with 1-nanometer gate lengths , 2016, Science.

[42]  Huaqiang Wu,et al.  Graphene Oxide Quantum Dots Based Memristors with Progressive Conduction Tuning for Artificial Synaptic Learning , 2018, Advanced Functional Materials.

[43]  Carver A. Mead,et al.  Neuromorphic electronic systems , 1990, Proc. IEEE.

[44]  Arindam Ghosh,et al.  Microscopic origin of low frequency noise in MoS2 field-effect transistors , 2014 .

[45]  Herman H. Goldstine,et al.  Preliminary discussion of the logical design of an electronic computing instrument (1946) , 1989 .

[46]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[47]  R. Guillery.  Binocular competition in the control of geniculate cell growth , 1972, The Journal of comparative neurology.

[48]  P. Ye,et al.  Channel length scaling of MoS2 MOSFETs. , 2012, ACS nano.

[49]  Qing Hua Wang,et al.  Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. , 2012, Nature nanotechnology.

[50]  F. Merrikh Bayat,et al.  Spike-timing-dependent plasticity learning of coincidence detection with passively integrated memristive circuits , 2018, Nature Communications.

[51]  Keliang He,et al.  Control of valley polarization in monolayer MoS2 by optical helicity. , 2012, Nature nanotechnology.

[52]  P. B. Pillai,et al.  Nanoionics-Based Three-Terminal Synaptic Device Using Zinc Oxide , 2017 .

[53]  A. Kis,et al.  Nonvolatile memory cells based on MoS2/graphene heterostructures. , 2013, ACS nano.

[54]  M. Marinella,et al.  A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. , 2017, Nature materials.

[55]  Alex Ming Shen,et al.  A Carbon Nanotube Synapse with Dynamic Logic and Learning , 2013, Advanced materials.

[56]  Arindam Ghosh,et al.  Microscopic mechanism of 1/f noise in graphene: role of energy band dispersion. , 2011, ACS nano.

[57]  D. Ielmini,et al.  Demonstration of hybrid CMOS/RRAM neural networks with spike time/rate-dependent plasticity , 2016, 2016 IEEE International Electron Devices Meeting (IEDM).

[58]  Pierre-Emmanuel Gaillardon,et al.  Low-power multiplexer designs using three-independent-gate field effect transistors , 2017, 2017 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH).

[59]  Wang Yao,et al.  Coupled spin and valley physics in monolayers of MoS2 and other group-VI dichalcogenides. , 2011, Physical review letters.

[60]  Lei Liao,et al.  Floating gate memory-based monolayer MoS2 transistor with metal nanocrystals embedded in the gate dielectrics. , 2015, Small.

[61]  David Money Harris,et al.  A Compact Transregional Model for Digital CMOS Circuits Operating Near Threshold , 2014, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[62]  Young Sun,et al.  A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide , 2017, Advanced materials.

[63]  P. Jeon,et al.  MoS2 nanosheets for top-gate nonvolatile memory transistor channel. , 2012, Small.

[64]  Jian Shi,et al.  A correlated nickelate synaptic transistor , 2013, Nature Communications.

[65]  Zhiyong Li,et al.  Ionic/Electronic Hybrid Materials Integrated in a Synaptic Transistor with Signal Processing and Learning Functions , 2010, Advanced materials.

[66]  David Baltimore,et al.  Neurotransmitters, Synapses, and Impulse Transmission , 2000 .

[67]  K. K. Young.  Short-channel effect in fully depleted SOI MOSFETs , 1989 .

[68]  Takashi Taniguchi,et al.  Direct-bandgap properties and evidence for ultraviolet lasing of hexagonal boron nitride single crystal , 2004, Nature materials.

[69]  Alessandro Calderoni,et al.  Neuromorphic Learning and Recognition With One-Transistor-One-Resistor Synapses and Bistable Metal Oxide RRAM , 2016, IEEE Transactions on Electron Devices.

[70]  L. Lauhon,et al.  Emerging device applications for semiconducting two-dimensional transition metal dichalcogenides. , 2014, ACS nano.

[71]  Sungho Kim,et al.  Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity. , 2015, Nano letters.

[72]  Wei Yang Lu,et al.  Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.

[73]  Ji Feng,et al.  Valley-selective circular dichroism of monolayer molybdenum disulphide , 2012, Nature Communications.

[74]  F. Attneave,et al.  The Organization of Behavior: A Neuropsychological Theory , 1949 .