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Abstract The rapid growth toward digitization and artificial intelligence for high-performance storage technologies has spurred the development of brain-inspired neuromorphic electronics. In the post-Moore era, the conventional von Neumann computing architecture, characterized by physically separated processing and memory units, faces significant challenges including excessive power consumption and limited data processing capabilities. As a novel nano electronic device paradigm, memristor has emerged with integrated data storage and computing technology, which is promising for breaking through the von Neumann bottleneck. Perovskite semiconductors possess structural tunability, exceptional electronic and optical properties. When combined with mechanically robust substrates, perovskite-based memristors pave the way for the development of flexible and lightweight neuromorphic systems, suitable for wearable electronics and the internet of things. In this review, we provide a comprehensive overview of recent progress in flexible perovskite memristor technologies, with special focus on the optimization engineering for improving the resistive switching characteristics of memory devices. We then review the role of perovskite-based flexible memories in neuromorphic applications from artificial synapses to image recognition. We outline the importance of clarifying the resistance-switching mechanism in perovskite memristors. Finally, we highlight the challenges that researchers face upon fabricating operationally stable perovskite-based flexible memristors and what is still missing to unlock their full potential in next-generation neuromorphic electronics.
Wang et al. (Wed,) studied this question.