Enabling nondestructive readout in ferroelectric capacitors for computing-in-memory through interface engineering

Ferroelectric capacitors based on hafnium materials hold significant potential in nonvolatile memory and compute-in-memory computing, yet their on/off ratio and endurance under nondestructive readout remain critical challenges. This paper proposes an interface engineering strategy that effectively modulates the capacitive memory window at zero bias by inserting an ultrathin tungsten metal interlayer at the ferroelectric–dielectric interface. Experiments have demonstrated that devices with a 5 nm tungsten interlayer achieve a capacitive on/off ratio of 1.18 and exhibit exceptional endurance exceeding 108 cycles. This enhancement in performance is primarily attributable to the synergistic effects of charge modulation and localized field enhancement at the interface. A LeNet-5 neural network constructed using this device achieved a recognition accuracy of 95.16% in the MNIST handwritten digit recognition task. This research provides a viable device solution for developing high-performance, highly reliable edge computing hardware.

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Publication Details

Journal
Applied Physics Letters
Published
2026-10-26
DOI
https://doi.org/10.1063/5.0327479
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
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article

Enabling nondestructive readout in ferroelectric capacitors for computing-in-memory through interface engineering

Jingwen Hou, Zongliang Huo, Xin Gong, Bao Zhang et al.
Applied Physics Letters
Ferroelectric and Negative Capacitance Devices
article

Enabling nondestructive readout in ferroelectric capacitors for computing-in-memory through interface engineering

Jingwen Hou, Zongliang Huo, Xin Gong, Bao Zhang, Qi Wang, Jing Zhou
article en

Abstract

Ferroelectric capacitors based on hafnium materials hold significant potential in nonvolatile memory and compute-in-memory computing, yet their on/off ratio and endurance under nondestructive readout remain critical challenges. This paper proposes an interface engineering strategy that effectively modulates the capacitive memory window at zero bias by inserting an ultrathin tungsten metal interlayer at the ferroelectric–dielectric interface. Experiments have demonstrated that devices with a 5 nm tungsten interlayer achieve a capacitive on/off ratio of 1.18 and exhibit exceptional endurance exceeding 108 cycles. This enhancement in performance is primarily attributable to the synergistic effects of charge modulation and localized field enhancement at the interface. A LeNet-5 neural network constructed using this device achieved a recognition accuracy of 95.16% in the MNIST handwritten digit recognition task. This research provides a viable device solution for developing high-performance, highly reliable edge computing hardware.

Applied Physics LettersVol. 129(17)
Chinese Academy of Sciences (CN), Institute of Microelectronics (CN)
Openalex Percentile: Top 24%
Ferroelectric and Negative Capacitance Devices
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