Effect of Al Concentration on Ferroelectric Properties in HfAlOx‐Based Ferroelectric Tunnel Junction Devices for Neuroinspired Applications

Author:

Kim Jihyung1,Kim Dahye12,Min Kyung Kyu3,Kraatz Matthias2,Han Taeyoung4,Kim Sungjun1ORCID

Affiliation:

1. Division of Electronics and Electrical Engineering Dongguk University Seoul 04620 South Korea

2. Nanomechanics and Reliability for Microelectronics Fraunhofer IKTS 01109 Dresden Germany

3. Department of Electrical and Computer Engineering and Inter-university Semiconductor Research Center Seoul National University Seoul 08826 Republic of Korea

4. Biodegradation and Nanofunctionalization Fraunhofer IKTS Maria-Reiche-Str.2 01109 Dresden Germany

Abstract

Since HfOx‐based ferroelectric tunnel junctions (FTJs) are attractive compared to perovskite‐based FTJs and other emerging memory devices, they are being actively studied recently. They have advantages such as a simple metal–insulator–metal structure, complementary metal oxide semiconductor (CMOS) compatibility, non‐destructive operation, and low power consumption. Moreover, doped HfOx‐based FTJs are in the spotlight in terms of neuromorphic engineering as a way of advancing from the von Neumann structure. In particular, Al dopant is effective for inducing ferroelectric properties due to its smaller radius than that of Hf. The optimal concentration of Al varies depending on the device materials and the annealing conditions during deposition. Therefore, in‐depth research is required for neuromorphic applications. Herein, the properties of FTJ devices according to Al doping concentrations are analyzed. Subsequently, using the device with the highest remanent polarization, neuromorphic applications are implemented, including spike‐timing‐dependent plasticity (STDP), paired‐pulse facilitation (PPF), long‐term potentiation, and depression. The characteristics in different frequency regions are also studied to satisfy the demand for fast switching. Finally, the FTJ device is used as a physical reservoir in reservoir computing for efficient processing of time‐dependent inputs.

Funder

National Research Foundation of Korea

Korea Institute of Energy Technology Evaluation and Planning

Publisher

Wiley

Subject

General Medicine

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