2D Drift-Diffusion-Reaction Model of Organic Electrochemical Transistors for Biosensing and Neuromorphic Hardware Simulations

Organic electronics, and in particular electrolyte-gated transistors, witnessed an exponential growth in the last decades, enabling a collection of different applications, ranging from biosensing to flexible digital circuits¹.<br/>In particular, PEDOT:PSS-based organic electrochemical transistors (OECTs), have come to play an important role for their natural ionic-to-electronic signal transduction and biocompatibility².<br/>In addition, thanks to the development of inexpensive, tuneable and energy efficient devices, organic neuromorphic engineering emerged as a promising approach to overcome conventional silicon technology limitations³. Notably, neuromorphic OECTs were shown to exhibit non-volatile and reproducible memory⁴, and the first biohybrid synapse was demonstrated, in which an artificial neuron could communicate with dopaminergic cells⁵.<br/>As complex electrochemical mechanisms take place during doping/de-doping processes of OECT, several models were developed over the years^6,7, in order to guide device design of such complex devices. Still, while correctly describing several featured of such devices, these modelling approaches rely on a 1D approximation of the transistor channel, neglecting import dynamics of ions and holes. Furthermore, a clear model of a neuromorphic OECT is still missing.<br/>Here, starting from a newly developed 2D drift-diffusion model of an OECT⁸, we present a numerical model of a PEDOT:PSS-based neuromorphic OECT, working at the border with biology.<br/>First, drift-diffusion-reaction equations are solved, to describe redox reactions happening at the gate/electrolyte interface, and the subsequent faradic charge transfer that dopes/de-doped the OECT.<br/>In particular, dopamine oxidation, and the subsequent hydrogen release in the electrolyte of the OECT, were simulated.<br/>Notably, the model predicts a dependence of the faradic reaction on the composition of the electrolyte, as it directly affects the voltage drop at gate/electrolyte interface, that drives the whole faradic reaction. In addition, experimental data are provided, validating the model.<br/>Lastly, charge trapping is implemented in the model, enabling the simulation of a biohybrid synapse, in which PEDOT:PSS is de-doped by hydrogen ions in a non-volatile manner.<br/>The proposed model aims to provide a tool to guide the design of the novel generation of organic sensors and neuromorphic hardware, enabling the modelling of the devices working at the interface with biological systems.<br/><br/>1. Rashid, R. B., Ji, X. & Rivnay, J. Organic electrochemical transistors in bioelectronic circuits. <i>Biosens. Bioelectron.</i> <b>190</b>, 113461 (2021).<br/>2. Mariano, A. <i>et al.</i> Advances in Cell-Conductive Polymer Biointerfaces and Role of the Plasma Membrane. <i>Chem. Rev.</i> <b>122</b>, 4552–4580 (2022).<br/>3. van de Burgt, Y., Melianas, A., Keene, S. T., Malliaras, G. & Salleo, A. Organic electronics for neuromorphic computing. <i>Nat. Electron.</i> <b>1</b>, 386–397 (2018).<br/>4. van de Burgt, Y. <i>et al.</i> A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. <i>Nat. Mater.</i> <b>16</b>, 414–418 (2017).<br/>5. Keene, S. T. <i>et al.</i> A biohybrid synapse with neurotransmitter-mediated plasticity. <i>Nat. Mater.</i> <b>19</b>, 969–973 (2020).<br/>6. Friedlein, J. T., McLeod, R. R. & Rivnay, J. Device physics of organic electrochemical transistors. <i>Org. Electron.</i> <b>63</b>, 398–414 (2018).<br/>7. Bernards, D. A. & Malliaras, G. G. Steady-State and Transient Behavior of Organic Electrochemical Transistors. <i>Adv. Funct. Mater.</i> <b>17</b>, 3538–3544 (2007).<br/>8. Paudel, P. R., Skowrons, M., Dahal, D., Radha Krishnan, R. K. & Lüssem, B. The Transient Response of Organic Electrochemical Transistors. <i>Adv. Theory Simul.</i> <b>5</b>, 2100563 (2022).