ScholarWorks@경상국립대학교

초록

Halide perovskites have emerged as multifunctional materials for next-generation computing, owing to their coupled ionic-electronic conduction, structural tunability, and optoelectronic responsiveness. Although halide perovskites have been extensively investigated in electronic and optoelectronic devices, their role as a unified materials platform for both in-memory computing (IMC) and neuromorphic computing (NC), and the connections between their material properties, device architectures, and system-level computing functionalities, remain insufficiently clarified in the current literature. This review presents a comprehensive overview of halide perovskite-based IMC and NC devices, highlighting how their unique material characteristics can be leveraged to address key challenges in emerging computing paradigms. In the context of IMC, we discuss resistive switching phenomena in halide perovskite memristors and their integration into logic in-memory arrays for analog computation. For NC applications, both two-terminal and three-terminal devices are examined in terms of synaptic plasticity, spatiotemporal learning, and multimodal stimulus processing. We further highlight how low-dimensional perovskite structures, defect-mediated dynamics, and coupled ionic-electronic transport enable adaptive synaptic functionalities, while also introducing critical limitations related to stability, defect control, and reproducibility. By explicitly linking material properties to device operation and system performance, this review clarifies both the opportunities and remaining challenges of halide perovskites for practical and scalable IMC and NC implementations, providing a problem-driven perspective on their potential in compact, energy-efficient, and adaptive computing technologies.

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