Thickness-Dependence of the Coercive Field in Ferroelectrics
P. Chandra, M. Dawber, P.B. Littlewood, J.F. Scott

TL;DR
This paper extends the understanding of the thickness dependence of coercive fields in ferroelectrics by applying a generalized nucleation and growth model, incorporating screening effects, and successfully matching experimental data across various materials and thicknesses.
Contribution
It introduces a more general Kolmogorov-Avrami model with screening corrections to accurately describe coercive fields in ferroelectrics over a wide thickness range.
Findings
Quantitative agreement with experimental data for PZT, potassium nitrate, and PVDF.
Switching kinetics in PVDF are domain-wall limited down to 1 nanometer.
The model explains the thickness dependence without invoking new effects.
Abstract
For forty years researchers on ferroelectric switching have used the Kay-Dunn theory to model the thickness-dependence of the coercive field; it works surprisingly well, despite the fact that it is based upon homogeneous nucleation and a small-field expansion, neither of which is realized in thin films. Here we demonstrate that this result can be obtained from a more general Kolmogorov-Avrami model of (inhomogeneous) nucleation and growth. By including a correction to the switching field across the dielectric that includes Thomas-Fermi screening in the metal electrode, we show that our theory quantitatively describes the coercive fields versus thickness in several different families of ferroelectric (lead zirconate-titanate [PZT], potassium nitrate, and polyvinylidenefluoride [PVDF]) over a wide range of thickness (5 decades). This agreement is particularly satisfying in the case of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFerroelectric and Piezoelectric Materials · Acoustic Wave Resonator Technologies · Advanced Memory and Neural Computing
