Impact of HfO2 Dielectric Layer Placement in Hf0.5Zr0.5O2-Based Ferroelectric Tunnel Junctions for Neuromorphic Applications

  • Kim, Juri
  • Park, Yongjin
  • Lee, Jungwoo
  • Lim, Eunjin
  • Lee, Jung-Kyu
  • ... Kim, Sungjun
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초록

The use of Hf0.5Zr0.5O2 (HZO) films within hafnia-based ferroelectric tunnel junctions (FTJ) presents a promising avenue for next-generation non-volatile memory devices. HZO exhibits excellent ferroelectric properties, ultra-thinness, low power consumption, nondestructive readout, and compatibility with silicon devices. In this study, Mo/HZO/n(+) Si devices are investigated, incorporating a 1 nm HfO2 dielectric layer at the top and bottom of the HZO ferroelectric layer. Comparing the FTJ device configurations, it is observed that the metal-ferroelectric-dielectric-semiconductor (MFIS) outperforms the metal-dielectric-ferroelectric-semiconductor (MIFS) in terms of ferroelectricity, displaying a high 2P(r) value of approximate to 69 mu C cm(-2). Additionally, MFIS exhibits lower leakage current, higher tunneling electro-resistance ratio, and a thin dead layer during short pulse switching, as confirmed through DC double sweeping of I-V characteristics. The modified half-bias scheme demonstrates a maximum array size of 191 for MFIS, showcasing its superior performance over MIFS. Synaptic characteristics, including potentiation, depression, paired-pulse facilitation, spike-rate-dependent plasticity, and excitatory postsynaptic current, are measured using MFIS, highlighting its outstanding ferroelectric properties. As a physical reservoir, the FTJ device implements 16 states of 4 bits in reservoir computing. Finally, pattern recognition using a deep learning neural network achieves high accuracy with using the Modified National Institute of Standards and Technology dataset.

키워드

ferroelectric tunnel junctionHf0.5Zr0.5O2HfO2 dielectric layerreservoir computingsneak currentARTIFICIAL SYNAPSESMEMORYOXIDEFILMS
제목
Impact of HfO2 Dielectric Layer Placement in Hf0.5Zr0.5O2-Based Ferroelectric Tunnel Junctions for Neuromorphic Applications
저자
Kim, JuriPark, YongjinLee, JungwooLim, EunjinLee, Jung-KyuKim, Sungjun
DOI
10.1002/admt.202400050
발행일
2024-05
유형
Article
저널명
Advanced Materials Technologies
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