Self-rectifying organic memristor based on PAA/PEDOT:PSS heterojunction for neuromorphic computing

Neuromorphic computing has emerged as a promising strategy to overcome the intrinsic limitations of the von Neumann architecture, where memristive devices that emulate biological synapses are of particular interest. Among them, organic memristors offer unique advantages in mechanical flexibility, biocompatibility, and solution processability. Here, we report a flexible, self-rectifying organic memristor fabricated on an ITO/PAA(Ca2+)/PEDOT:PSS/ITO architecture. The device operates through directional Ca2+ migration within the poly(acrylic acid) (PAA) electrolyte layer, enabling stable resistive switching. Importantly, the integration of PEDOT:PSS with ITO forms an intrinsic p–n junction, imparting pronounced self-rectifying behavior with a rectification ratio of approximately 103, effectively suppressing sneak-path currents in crossbar arrays. The device is able to simultaneously maintain stable resistive switching and robust rectification, avoiding the mutual interference commonly observed in conventional designs. The memristor reliably reproduces key synaptic functions, including transitions from short-term to long-term potentiation and depression, as well as spike-timing-dependent plasticity. Artificial neural networks constructed using experimentally extracted device characteristics achieve image and digit recognition accuracies exceeding 90%. This work demonstrates that flexible organic memristors with built-in p–n junction rectification can simultaneously address mechanical compliance, energy efficiency, and integration density, thereby establishing a viable materials and device platform for biocompatible neuromorphic hardware and scalable pattern-recognition systems.