journal article·2025-05-13

Unintended Soft Breakdown Mechanism Limiting Ultrathin Ferroelectric HZO Films Scaling

Wonwoo Kho, Hyunjoo Hwang, Hyo-Bae Kim, Gunho Kim, Ji-Hoon Ahn, Seung-Eon Ahn

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Abstract

In the memory semiconductor industry, the primary focus is on enhancing integration and scaling down devices. Both DRAM and flash memory have achieved substantial advancements in integration by adopting vertical structures. However, the need for further scaling persists due to the increasing volume of data generated and utilized. Consequently, there is a growing demand for next-generation memory devices that combine the benefits of both DRAM and flash memory while supporting the continued scaling. Hafnium oxide (HfO 2 )-based ferroelectric materials, discovered in 2011, have emerged as promising candidates to meet these scaling requirements, as they retain ferroelectricity even at thicknesses below 10 nm. Unlike perovskite ferroelectrics, which suffer polarization loss as scaling progresses, few-nanometer HfO 2 -based fluorite structure ferroelectrics have addressed this limitation, drawing significant attention within the memory field. To enable the application of these HfO 2 -based ferroelectrics in memory devices, it is crucial to understand the scaling limits and their underlying causes by examining the interface effects that intensify with scaling and the emerging phenomena observed in ultrathin films. In this work, we analyze sub-5 nm ultrathin ferroelectric HZO (hafnium zirconium oxide) films to investigate the soft breakdown phenomenon, which constrains scaling. Through an examination of various established electron transport models, we demonstrate that an unintended conduction path, facilitated by oxygen-vacancy (V O )-rich regions within the HZO layer and the TiO x N y layer, plays a dominant role in the conduction mechanism of ultrathin films, suggesting the cause of the scaling limitations of HZO devices.
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Research context

OpenAlex topics: Ferroelectric and Negative Capacitance Devices · Semiconductor materials and devices · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of IT Semiconductor Convergence Engineering

Tech University of Korea

Department of Materials Science and Chemical Engineering

Hanyang University

Department of Nano & Semiconductor Engineering

Funding

National Research Foundation of Korea

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