Design and implementation of novel piezoelectric memristors

As an emerging nonlinear device, the piezoelectric memristor demonstrates significant potential in neuromorphic hardware and adaptive systems due to its unique electromechanical coupling and memory properties. However, its design and fabrication remain highly challenging, placing stringent demands on material selection and micro-nano processing techniques. Moreover, experimental studies based on physical devices are often costly, time-consuming, and inefficient for rapidly validating circuit-level application concepts.This paper proposes a novel circuit-based modeling approach that leverages the high sensitivity of piezoelectric sensors to mechanical stimuli, efficiently converting ambient mechanical energy into electrical signals. By integrating a Microcontroller Unit (MCU) with robust computational and real-time control capabilities, the circuit parameters can be dynamically adjusted to achieve precise modulation of memristance. This modeling strategy significantly reduces reliance on complex physical fabrication processes and offers researchers an efficient and low-cost platform for design and validation.