Coupled electro-opto-mechanical oscillations in neuristors

Abstract

Action potentials (AP) in biological neurons, measured through electrophysiological techniques, are electrical signals that emerge and propagate along the axonal membrane. It has been shown that close to the temperatures of physiological interest, a chain melting phase transition in the neuronal membrane accompanied by a change in density and heat capacity, is responsible for creating and propagating mechanical displacements. Correlated electronic systems such as VO2 exhibit temperature dependent first-order phase transitions, analogous to lipid membranes. This is an insulator-to-metal transition (IMT), accompanied by a structural change from monoclinic to rutile phase, signified by substantial contrast in electrical resistance, density and refractive index between the two phases. In a device setting, this transition occurs through current-induced Joule heating, resulting in a negative differential resistance (NDR) region in current-controlled measurement. Yi et al. have shown 23 different types of electrical signals in this neuristor system, emulating a complex portfolio of electrical activity exhibited by biological neurons. In particular, three types of neuronal signals i.e. tonic spiking, tonic bursting and phasic spiking are of interest to the current work. In the first part of this thesis, the dynamics of voltage-driven self-sustained oscillations in NdNiO₃ neuristors are presented. These oscillations result from negative differential resistance (NDR). This part is focused on addressing gaps in electro-thermal modeling that have not been previously covered in the literature. In the subsequent part, we explore whether VO₂ neuristors, which have been compared to biological neurons primarily in the electrical domain, can also be considered coupled electromechanical and electro-optical systems. This is motivated by the significant volume change during IMT and the associated refractive index changes. Specifically, this study investigates: a) whether VO₂ neuristors exhibit coupled electro-mechanical behavior, b) whether they function as coupled electro-optical systems, and c) how they compare with conventional piezoelectric and electro-optic materials. To address these questions, experiments were designed and conducted. Building on the findings from VO2 film, we also explored whether this mechanical motion propagates along the material as it does in neurons. To investigate this, we utilized VO2 microwires equipped with multiple electrodes along the same wire. By actuating one electrode, we examined whether the mechanical motion would travel to other regions of the wire. Our preliminary check indicated the presence of mechanical motion propagation. Finally, we present a method for encoding information within the waveforms of coupled oscillators, utilizing one-shot learning inspired by Hebb’s law, which emphasizes the weighted relationship between coupled neurons. Additionally, a hardware implementation using relaxation oscillators is presented for pattern extraction, demonstrating the capability of oscillatory neural networks for pattern recognition tasks and advancing the field of neuromorphic computing