Issue

Vol. 18 (2026)

Hafnium-Based Ferroelectric Post-Moore Electronics: Device Physics, Integration Architectures, and Neuromorphic System Implementation

https://doi.org/10.1007/s40820-026-02158-z
Xiangwei Chen
Shandong Key Laboratory of Next‑Generation Semiconductor Technology and Systems, School of Integrated Circuits, Shandong University, Jinan 250100, People’s Republic of China
Zheng Wang
Shandong Key Laboratory of Next‑Generation Semiconductor Technology and Systems, School of Integrated Circuits, Shandong University, Jinan 250100, People’s Republic of China
Jialin Meng
Shandong Key Laboratory of Next‑Generation Semiconductor Technology and Systems, School of Integrated Circuits, Shandong University, Jinan 250100, People’s Republic of China
Tianyu Wang
Shandong Key Laboratory of Next‑Generation Semiconductor Technology and Systems, School of Integrated Circuits, Shandong University, Jinan 250100, People’s Republic of China

Corresponding Author: Tianyu Wang

tywang@sdu.edu.cn

Nano-Micro Letters, Vol. 18 (2026), Article Number: 326

Abstract

Hafnium-based ferroelectric (Hf-FEs) materials overcome the limitations of perovskite ferroelectric materials. Owing to their compatibility with the complementary metal–oxide–semiconductor process and high scalability, Hf-FEs devices have driven the development of non-volatile memory and neuromorphic computing, demonstrating significant potential for application in image processing and in-memory logic operations. First of all, this paper summarizes the material systems, device structure, and physical mechanisms relevant to Hf-FEs devices. Then, for the purpose of achieving efficient neuromorphic computing, the evaluation parameters related to Hf-FEs devices, specifically concerning storage performance and synaptic plasticity, are discussed. Furthermore, the progress of Hf-FEs devices in arrays and hardware integration is systematically reviewed, offering insights for future applications. Finally, this study explores in depth the prospects and challenges of these devices in advanced applications, providing valuable guidance for the development of high-performance neuromorphic computing devices.


Highlights:
1 Comprehensively review the material systems, device physics, and performance metrics of complementary metal-oxide-semiconductor-compatible hafnium-based ferroelectric (Hf-FEs), highlighting their potential for next-generation non-volatile memory.
2 The review summarized the synaptic plasticity and neuromorphic computing functions implemented by Hf-FEs, emphasizing their advantages in parallelism, energy efficiency, and system-level integration.
3 Valuable insights into the development of Hf-FEs toward advanced applications in post-Moore electronics.

Keywords

Hafnium oxide Ferroelectric materials Neuromorphic computing Non-volatile memory
Chen, Xiangwei, Zheng Wang, Jialin Meng, and Tianyu Wang. 2026. “Hafnium-Based Ferroelectric Post-Moore Electronics: Device Physics, Integration Architectures, and Neuromorphic System Implementation”. Nano-Micro Letters 18 (April):326. https://doi.org/10.1007/s40820-026-02158-z.
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