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  4. Sub-2 nm Equivalent-Oxide-Thickness Ferroelectric Transistors for Cryogenic Memory and Computing
 
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2026
Journal Article
Title

Sub-2 nm Equivalent-Oxide-Thickness Ferroelectric Transistors for Cryogenic Memory and Computing

Abstract
Ferroelectric hafnia-based field-effect transistors are promising candidates for nonvolatile memory and in-memory computing. However, their operation principle under deep-cryogenic conditions at aggressively scaled gate stacks remains underexplored, especially for bulk silicon technology. This work presents an experimental demonstration of front-end-of-line bulk silicon-channel ferroelectric field-effect transistors featuring sub-2 nm equivalent-oxide-thickness gate stacks with ≃5 nm hafnium–zirconium oxide, exhibiting robust switching at 10 K. Key metrics include memory windows exceeding 1 V, tightly distributed threshold voltages (standard deviation ≲ 40 mV), endurance surpassing 10<sup>7</sup> cycles, and retention projections consistent with decade-scale stability. Correlative four-dimensional scanning transmission electron microscopy phase mapping reveals an increased orthorhombic ferroelectric fraction following electrical wake-up at cryogenic temperatures, correlated with enhanced polarization stability and strengthened oxygen–metal coordination. We hypothesize that suppressed trapping-related instability, along with a higher orthorhombic phase, jointly contribute to this effect. Current–voltage sweeps define an operational design window, with memory-window saturation beyond ±5 V programming voltages and ≳900 ns pulse widths, consistent with nucleation-limited reversal kinetics in ultrathin films. A spiking neural network implemented at 10 K achieves >92% classification accuracy on MNIST and 73.8% accuracy on NMNIST data sets, demonstrating practical utility. These findings provide materials- and device-level insights into scaled hafnia FeFETs for energy-efficient cryogenic applications, including potential integration in quantum–classical systems.
Author(s)
Das, Apu
National Tsing Hua University
Senapati, Asim
National Tsing Hua University
Kumar, Gautham
National Tsing Hua University
Lou, Zhaofeng
National Taiwan University
Müller, Jonas
Université de Toulouse
Maskeen, Jaskirat Singh
Indian Institute of Technology Gandhinagar
Chang, Yii Tay
National Taiwan University
Tewari, Mohit
Indian Institute of Technology Gandhinagar
Agarwal, A.
National Cheng Kung University
Paul, Agniva
National Tsing Hua University
Raffel, Yannick
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Maikap, Siddheswar
Chang Gung University
Kao, Kuo-Hsing Hsing
National Cheng Kung University
Agarwal, Tarun Kumar
Indian Institute of Technology Gandhinagar
Lashkare, Sandip
Indian Institute of Technology Gandhinagar
Lu, Darsen Duane
National Cheng Kung University
Larrieu, Guilhem
Université de Toulouse
Lee, Minhung
National Taiwan University
De, Sourav
National Tsing Hua University
Journal
ACS nano  
Open Access
File(s)
Download (7.13 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.1021/acsnano.5c16255
10.24406/publica-8482
Additional link
Full text
Language
English
Fraunhofer Institute for Photonic Microsystems IPMS  
Keyword(s)
  • 4D-STEM

  • cryogenic electronics

  • FeFETs

  • HZO

  • neuromorphic computing

  • nonvolatile memory

  • XPS

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