Hydrophobically gated memristive nanopores for neuromorphic applications

TL;DR

This paper introduces a bioinspired hydrophobically gated memristive nanopore that mimics neural signal transmission, demonstrating potential for energy-efficient, nanoscale neuromorphic devices through simulations and experiments.

Contribution

It proposes and experimentally realizes a novel hydrophobic gating mechanism in nanopores that functions as a memristor, advancing bioinspired neuromorphic hardware.

Findings

Hydrophobic gating enables memristive behavior via electrowetting.

Engineered nanopores replicate memristor hysteresis cycles.

Device demonstrates learning and forgetting capabilities.

Abstract

Brain-inspired computing has the potential to revolutionise the current von Neumann architecture, advancing machine learning applications. Signal transmission in the brain relies on voltage-gated ion channels, which exhibit the electrical behaviour of memristors, resistors with memory. State-of-the-art technologies currently employ semiconductor-based neuromorphic approaches, which have already demonstrated their efficacy in machine learning systems. However, these approaches still cannot match performance achieved by biological neurons in terms of energy efficiency and size. In this study, we utilise molecular dynamics simulations, continuum models, and electrophysiological experiments to propose and realise a bioinspired hydrophobically gated memristive nanopore. Our findings indicate that hydrophobic gating enables memory through an electrowetting mechanism, and we establish simple design rules accordingly. Through the engineering of a biological nanopore, we successfully replicate the characteristic hysteresis cycles of a memristor \tr{and construct a synaptic device capable of learning and forgetting}. This advancement offers a promising pathway for the realization of nanoscale, cost- and energy-effective, and adaptable bioinspired memristors.