Theoretical modeling of dendrite growth from conductive wire electro-polymerization

Abstract

Electropolymerization is a bottom-up materials engineering process of micro/nano-scale that utilizes electrical signals to deposit conducting dendrites morphologies by a redox reaction in the liquid phase. It resembles synaptogenesis in the brain, in which the electrical stimulation in the brain causes the formation of synapses from the cellular neural composites. The strategy has been recently explored for neuromorphic engineering by establishing link between the electrical signals and the dendrites’ shapes. Since the geometry of these structures determines their electrochemical properties, understanding the mechanisms that regulate polymer assembly under electrically programmed conditions is an important aspect. In this manuscript, we simulate this phenomenon using mesoscale simulations, taking into account the important features of spatial–temporal potential mapping based on the time-varying signal, the motion of charged particles in the liquid due to the electric field, and the attachment of particles on the electrode. The study helps in visualizing the motion of the charged particles in different electrical conditions, which is not possible to probe experimentally. Consistent with the experiments, the higher AC frequency of electrical activities favors linear wire-like growth, while lower frequency leads to more dense and fractal dendrites’ growth, and voltage offset leads to asymmetrical growth. We find that dendrites' shape and growth process systematically depend on particle concentration and random scattering. We discover that the different dendrites’ architectures are associated with different Laplace and diffusion fields, which govern the monomers’ trajectory and subsequent dendrites’ growth. Such unconventional engineering routes could have a variety of applications from neuromorphic engineering to bottom-up computing strategies.

Dendritic Organic Electrochemical Transistors Grown by Electropolymerization for 3D Neuromorphic Engineering

“…While for long time period (low frequency) the particles can transport over longer distances from the center of the electrodes, enabling fractal‐like growth with multiple branches. [ 16 ] This effect can also be explained by the monomer permeation through the anodic double layer that forms partially depending on the applied frequency responsible for different dendrites’ growth. For high frequencies and short time durations, the double layer can form only near the tip, while at low frequency, the double layer is capable to be formed isotropically, leading to high dendrite growth.…”

Structural plasticity for neuromorphic networks with electropolymerized dendritic PEDOT connections

“…Such electropolymerization process has been reported to depend strongly on electrical parameters of the AC input signals such as peak-to-peak amplitude and frequency 23 . These dependencies were correlated to the voltage potential oxidation threshold of EDOT monomers into polymers and to the dynamics of charged species in the electrolyte through the influence of drift and diffusion 27 . The structural aspect and growth dynamics of dendritric fibers are reminiscent of neurons genesis during development of biological neural networks (see Supplementary Video 1) .…”