Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session D02: Ferroelectrics and Relaxors
3:00 PM–6:00 PM,
Monday, March 4, 2024
Room: L100B
Sponsoring
Unit:
DMP
Chair: Mahmoud Asmar, Kennesaw State University
Abstract: D02.00013 : Understanding and Controlling the Energy Landscape of Hf0.5Zr0.5O2*
5:24 PM–5:36 PM
Presenter:
Jack Broad
(University of California, Berkeley)
Authors:
Jack Broad
(University of California, Berkeley)
Pratik Brahma
(University of California, Berkeley)
Sinéad M Griffin
(Lawrence Berkeley National Lab)
Zhi (Jackie) Yao
(Lawrence Berkeley National Laboratory)
Prabhat Kumar
(Lawrence Berkeley National Laboratory)
Jorge A Munoz
(University of Texas at El Paso)
Sayeef Salahuddin
(University of California, Berkeley)
However, the energy landscape of HZO is a complex triple well potential, which features an energy barrier for the non-polar to polar transition, and stable ferroelectric and antiferroelectric structures that are energetically similar. The coexistence of these two structures leads to the equivalent oxide thickness (EOT) of a gate oxide stack with HZO being lower than the interfacial SiO2 thickness, which usually determines the lower limit of the EOT. This is indicative of a higher capacitance and, consequently, a more effective FET.
This talk will explore the energy landscape of HZO, which is fundamental to its effectiveness in FETs. Multi-scale data will be used to elucidate this landscape, from machine learning and Landau potentials fitted to density functional theory calculations, to the results of phase-field simulations. These data will be employed to explain the effects of oxygen defects and strain on the HZO energy landscape, and ascertain how such conditions can be used to control it.
*This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, using NERSC award BES-ERCAP m3349.This research used the Lawrencium computational cluster resource provided by the IT Division at the Lawrence Berkeley National Laboratory.This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.This work was supported by the Defense Advanced Research Projects Agency.
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