A Flexible Inkjet-Printed Memristive Sensor: Modeling and Simulation

The exploration of neuromorphic computing, driven by the demand for efficient data-intensive operations, relies on memristive devices for versatile information storage. In this study, a low-cost, nonlinear, current-controlled memristor using hexagonal boron nitride (hBN) and graphene inkjet-printed materials is proposed for neuromorphic computing applications. The memristor device, designed with a standard office piezoelectric printer, demonstrates the feasibility of inkjet printing technology for flexible and cost-effective computing solutions. The research investigates the use of nanoparticle-based inks and explores the potential of inkjet-printed circuits as an eco-friendly and power-efficient alternative. An empirical model is developed using MATLAB to analyze the behavior of the inkjet-printed memristor device, with insights complemented by a physical Simscape model. This work contributes to the advancement of flexible and low-cost memristor devices, facilitating their integration into neuromorphic computing architectures and other applications requiring versatile information storage.