Switching Dynamics in Ferroelectric Hf₀.₅Zr₀.₅O₂ Devices: Experiments and Models

Ferroelectric Hf₀.₅Zr₀.₅O₂ (FE-HZO) has breathed new life into the field of ferroelectric research, boasting exceptional physical properties, such as compatibility with existing semiconductor processes, highly scalable thickness, and prominent FE properties. As a result, this intriguing material has gathered extensive attention for applications in ultra-scaled Si MOSFETs, memory devices, energy-efficient hardware for convolutional computation, and RF devices. However, despite intense research, there is still controversy about the FE switching dynamics, a crucial factor in designing ferroelectric device applications. This thesis pursues fundamental understanding of the switching dynamics in FE-HZO structures founded on accurate dynamic measurements with meticulous experimental design considerations. Towards this, low-parasitic FE-HZO structures have been fabricated and characterized over a broad range of frequencies using large-signal and small-signal analysis. In large-signal analysis, a Finite-Difference implementation of the Nucleation Limited Switching model (FD-NLS) is introduced, which accurately predicts the FE circuit dynamics across a wide range of time scales. Additionally, a thorough analysis of the imprint effect, a critical reliability issue in FE devices is provided. In small-signal analysis, a physically meaningful small-signal equivalent circuit model is developed that describes impedance measurements well over a full bias range and 7 orders of magnitude of frequency all the way into the GHz regime. Moreover, this work sheds light on the underlying physics of the circuit elements. The findings in this thesis will contribute to the design and modeling of diverse FE-HZO devices for a wide range of applications, adding valuable knowledge to the field of FE-HZO research.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Kim, Taekyong

Advisors dc:contributor.advisor

• del Alamo, Jesús A.
• Antoniadis, Dimitri A.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/152658

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/152658