Ferroelectric transistors: operating principles, materials, applications

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Abstract

Applications related to the use of artificial intelligence (AI) and the Internet of Things require high-performance computing systems. Modern digital neuromorphic coprocessors, which are manufactured using CMOS technology, are ineffective in executing neural network algorithms due to the limitations of the von Neumann architecture. A promising direction for research in this area is integrated circuits based on non-volatile ferroelectric transistors. The paper provides an overview of studies devoted to ferroelectric materials, characteristics of ferroelectric transistors and methods for their study.

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About the authors

А. Yu. Reznyukov

Kurchatov Institute; Moscow Power Engineering Institute

Author for correspondence.
Email: RezniukovAY@mpei.ru
Russian Federation, Moscow; Moscow

K. A. Fetisenkova

Kurchatov Institute; Moscow Institute of Physics and Technology

Email: fetisenkova@ftian.ru
Russian Federation, Moscow; Moscow

A. E. Rogozhin

Kurchatov Institute; Moscow Power Engineering Institute; Moscow Institute of Physics and Technology

Email: rogozhin@ftian.ru
Russian Federation, Moscow; Moscow; Moscow

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Supplementary files

Supplementary Files
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2. Fig. 1. Schematic diagram of (a) FeFET structure with reverse gate, (b) FeFET structure with direct gate

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3. Fig. 2. Hysteresis of the transfer curve in FeFET [16]

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4. Fig. 3. Domain structure of FeFET gate stack

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5. Fig. 4. (a) Schematic of FeFET using PZT as a segment dielectric; (b) PZT perovskite structure

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6. Fig. 5. Schematic of HZO-based FeFET with TiN layer as a gate

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7. Fig. 6. FeS-FET structure using α-In2Se3 as a segmentoelectric semiconductor layer

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8. Fig. 7. FeFET-based three-terminal synaptic cell [46]

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9. Fig. 8. Structure of Fe-FinFET

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10. Fig. 9. Schematic representation of the test structure for the study of segmentoelectrics

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11. Fig. 10. Principle of PSM operation on the inverse piezoelectric effect [72]

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12. Fig. 11. Distribution of segmentoelectric domains at switching polarisation obtained by PSM [73]

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13. Fig. 12. Schematic representation of the pulse shape of the PUND method, tinc - rise time, tdec - fall time, trelax - relaxation time [75]

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