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February 19, 2026Advanced Functional Materials4 citations

Brain‐Inspired Two‐Dimensional CuInP 2 S 6 Ferroelectric Materials for Neuromorphic Computing

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XWXiyao WenQYQian YuTWTianyu Wang

Key Points

  • The study aims to explore the potential of copper indium thiophosphate (CIPS) ferroelectric materials in neuromorphic computing.
  • Reviewed classification of CIPS materials and their device structures.
  • Discussed evaluation parameters for memory capacity and synaptic features.
  • Outlined hardware and software strategies for neuromorphic applications with CIPS devices.
  • CIPS materials exhibit room-temperature ultrathin ferroelectricity.
  • Devices show strong retention, low power needs, and multifunctionality.
  • Considerable potential applications in artificial vision, image processing, and logic gates.

Abstract

ABSTRACT 2D van der Waals (vdW) ferroelectric materials have emerged as transformative components in advancing neuromorphic computing and artificial intelligence applications. Among these novel vdW materials, copper indium thiophosphate (CIPS) has attracted significant attention due to its van der Waals layered structure and room‐temperature ultrathin ferroelectricity. It demonstrates great potential for fabricating novel CIPS‐based ferroelectric devices with unique crystalline structures and multifunctional characteristics, thereby promoting developments in non‐volatile multilevel memory, artificial synapses, and neuromorphic computing. Leveraging the interplay between robust ferroelectricity and ionic conductivity, CIPS‐based ferroelectric devices offer advantages such as ultra‐thinness, high endurance, strong retention, low power consumption, and multifunctionality. They show considerable application potential in artificial vision/auditory systems, image processing, bio‐sensory simulation, true random number generator, and logic gates. This review summarizes the classification of CIPS materials, device structures, and underlying mechanisms, while also discussing evaluation parameters for memory capability and synaptic plasticity in novel CIPS ferroelectric devices to enable efficient neuromorphic computing. It systematically outlines both hardware and software approaches for neuromorphic computing based on advanced CIPS devices, providing insights for future applications. Furthermore, the prospects and challenges in cutting‐edge application scenarios are thoroughly discussed, offering valuable guidance for the development of next‐generation neuromorphic computing devices.

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Cite This Study

Wen et al. (2026) studied this question.

synapsesocial.com/papers/6996a7d3ecb39a600b3edd6ehttps://doi.org/10.1002/adfm.202530852
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