Recent advances in ferroelectric materials, devices, and in-memory computing applicationsopen access
- Authors
- Hwang, Hwiho; Youn, Sangwook; Kim, Hyungjin
- Issue Date
- Nov-2025
- Publisher
- SPRINGER
- Keywords
- Ferroelectric thin films; Non-volatile memory devices; In-memory computing; Neuromorphic computing; Hardware security
- Citation
- NANO CONVERGENCE, v.12, no.1, pp 1 - 31
- Pages
- 31
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- NANO CONVERGENCE
- Volume
- 12
- Number
- 1
- Start Page
- 1
- End Page
- 31
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/210746
- DOI
- 10.1186/s40580-025-00520-2
- ISSN
- 2196-5404
- Abstract
- Ferroelectric memories have undergone a transformative evolution from conventional perovskite-based materials to modern fluorite-structured ferroelectrics, driven by the pursuit of scalable, low-power, and CMOS-compatible non-volatile memory solutions. The observation of ferroelectricity in nanoscale HfO2-based films has enabled integration with CMOS-compatible processes, providing advantages such as potential scalability, low power consumption, and non-volatility, while facilitating continued scaling and high-density integration. Leveraging established materials infrastructure in the semiconductor industry, hafnia-based ferroelectrics have been incorporated in various memory architectures, including ferroelectric random-access memory (FeRAM), ferroelectric tunnel junctions (FTJs), ferroelectric field-effect transistors (FeFETs), and ferroelectric memcapacitors (FeCAPs). Beyond conventional non-volatile storage, these devices have also emerged as promising building blocks for in-memory computing applications, including neuromorphic systems, hardware security primitives, and associative memory. In this review, we explore the historical development of ferroelectric memories from a materials-device co-design perspective, examine recent advances in device architectures and in-memory computing applications, and discuss the remaining challenges in endurance, retention, variability, and scaling. Finally, we propose future research directions that integrating material innovation, interface engineering, and circuit-level optimization to realize the full potential of ferroelectric memories in next-generation computing platforms.
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