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September 12, 2025International Journal of Extreme Manufacturing7 citationsOpen Access

Memristor devices for next-generation computing: from performance optimization to application-specific co-design

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ZLZhaorui LiuCGCaifang GaoJYJingbo Yang

Key Points

  • Memristors offer fast switching speeds and low power consumption, transforming computing capabilities.
  • Recent advancements include strategies for performance enhancement in non-volatile memory, neuromorphic computing, and hardware security.
  • Analyzing key performance metrics enables tailored applications to optimize device functionality and usability.
  • The proposed co-design framework aims to integrate device optimizations with operational improvements, bridging theoretical and practical applications.

Abstract

Abstract Memristors have emerged as a transformative technology in the realm of electronic devices, offering unique advantages such as fast switching speeds, low power consumption, and the ability to sensor-memory-compute. The applications span across non-volatile memory, neuromorphic computing, hardware security, and beyond, prompt memristors becoming a versatile solution for next-generation computing and data storage systems. Despite enormous potentials of memristors, the transition from laboratory prototypes to large-scale applications was challenging in terms of material stability, device reproducibility, and array scalability. This review systematically explores recent advancements in high-performance memristor technologies, focusing on performance enhancement strategies through material engineering, structural design, pulse protocol optimization, and algorithm control. We provide an in-depth analysis of key performance metrics tailored to specific applications, including non-volatile memory, neuromorphic computing, and hardware security. Furthermore, we propose a co-design framework that integrates device-level optimizations with operational-level improvements, aiming to bridge the gap between theoretical models and practical implementations.

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Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/68d44c3431b076d99fa5521ahttps://doi.org/10.1088/2631-7990/ae053a
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