To overcome the von Neumann bottleneck and increase power efficiency in computation, neuromorphic computing has been considered which has the capability for parallel computing, long-term potentiation, and adaptive learning for developing energy efficient neural networks.1 Electric double layer (EDL) gated transistor uses ions within an electrolyte to induce high carrier density (1014 cm-2) in the channel, and its short term and long term ionic responses resemble a biological synapse, making it a promising platform for synaptic applications such as artificial synapses and neurons.2 The accuracy, computational demands, and simplicity of training neural networks depend significantly on a linear synaptic weight response (or plasticity), i.e. a proportionate synaptic weight update in response to input signals.3-6 However, achieving linear weight update in EDLT based synaptic devices have proven to be challenging with fixed magnitude input pulses.7-9 In this study, we first discussed the fundamental cause for nonlinear synaptic weight update in the aforementioned EDLT synaptic devices. With fixed magnitude input voltage pulses, while the amount of EDL build up during each pulse is constant, the amount of EDL dissipation in between pulses is dependent on the instantaneous EDL concentration and follows an exponential decay with respect to time. This leads to increasing amount of dissipation as pulses progress and EDL builds up nonlinearly. This behavior was confirmed with finite element modeling using modified Nernst-Poisson-Planck equations.10,11 A train of 10 pulses with frequencies ranging from 10 – 100 Hz (VG = 1 V) was applied to a parallel plate capacitor geometry consisting of PEO:LiClO4 as the electrolyte, and the ion concentration was calculated. As expected, the linear input pulses resulted in a non-linear response, where the maximum EDL concentration at 100 Hz eventually saturated at 9 x 1013 ions/cm2, more than 2 times smaller than the maximum EDL concentration at a steady 1 V (1.9 x 1014 ions/cm2). Then, we demonstrated that linear weight update can be achieved with varying input pulse widths and/or magnitudes (i.e., nonlinear inputs). A challenge for this approach is that the EDL concentration at the end of each pulse needs to be evaluated to predict the input voltage or width of the subsequent pulse. Based on the instantaneous change in EDL concentration with respect to time (dc/dt), we obtained an empirical relationship relating dc/dt, voltage, concentration, and time. Coupling this relation with the original COMSOL model, the input signals for a linear synaptic response can be predicted in a single computation. For a series of pulses with magnitude between 0.25 V and 3 V at a fixed frequency of 100 Hz, a linear synaptic weight update was obtained with R2 = 0.996. After 10 pulses the improved model resulted with a 13% increase in EDL concentration (to 1.02 x 1014 ions/cm2) and can continue to increase with subsequent pulses. These preliminary results provide insights into extending this model for an FET and developing an EDL gated synaptic network. As part of ongoing work, the group is currently working on experimentally demonstrating the model using parallel plate capacitors (metal-electrolyte-metal) and Graphene-based EDL transistors. 1. Schuman et al. arXiv abs/1705.06963, 2017; 2. Zhu et al. Adv. Mat., 2018, 30 (21); 3. Sung et al. Nanotech., 2018, 29 (11); 4. Lee at al. Adv. Fun. Mat., 2020, 30 (45); 5. Yang et al. Small Science, 2022, 2 (1); 6. Jacobs-Gedrim et al. IEEE (ICRC), 2017; 7. Jiang et al. Nanoscale, 2019, 11 (3); 8. Wan et al. Adv. Mat., 2016, 28; 9. Wen et al. ACS App. Mat. & Int., 2017, 9 (42); 10. Woeppel et al. ACS App. Mat. & Int., 2020, 12 (36); 11. Kilic et al. Phy. Rev., 2007, 75 (2)

Realizing a Linear Synaptic Weight Update in Electric-Double-Layer Gated Transistors for Achieving Spike-Timing-Dependent Plasticity in Neuromorphic Computing

Z: Emergent Materials and Devices for Microelectronics

technical paper

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The Electronic Materials Conference (EMC) is the premier annual forum on the preparation, characterization and use of electronic materials. 

Nithil Harris Manimaran

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Realizing a Linear Synaptic Weight Update in Electric-Double-Layer Gated Transistors for Achieving Spike-Timing-Dependent Plasticity in Neuromorphic Computing

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