A droplet memristor with ionic liquid-electrolyte meniscus

Artikel i vetenskaplig tidskrift, 2025

Recent advances in fluidic memristors have revolutionized the field of iontronics, enabling unprecedented control over ionic transport and presenting new opportunities for breakthroughs in neuromorphic computing and artificial intelligence. Unlike traditional long-channel-based fluidic memristors, we introduce an innovative droplet memristor that leverages an ionic liquid-electrolyte interface within a custom pore-microwell architecture. We developed a robust physical model to simulate and predict the memristor's conductance states, which guided the fabrication of a specialized memristor device. In this model, the dynamic expansion and contraction of the charged droplet under an electric field leads to variable conductance, thereby inducing memory effects. Our experimental results demonstrate the successful implementation of neuromorphic functions and responses using the droplet memristor, including pulse signal processing and mechanical stimulus–response. Both theoretical and experimental findings demonstrate the remarkable neuromorphic behaviors of droplet memristors, paving the way for the development of advanced neuromorphic devices.