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International Journal of Big Data Intelligent Technology, 2020, 1(2); doi: 10.38007/IJBDIT.2020.010206.

Sem Image Based on Denoising Algorithm Shows the Effect of PTO Seed Layer on the Crystallization Temperature and Electrical Properties of PZT Ferroelectric Thin Films


Romanya Vijue

Corresponding Author:
Romanya Vijue

New Valley University, Egypt


Lead zirconate titanate (PZT) materials have been widely studied because of their excellent dielectric, ferroelectric, piezoelectric and electro-optic effects.The electrical properties of ferroelectric thin films indicate that the temperature of ferroelectric thin films changes under the action of external light field under adiabatic conditions. Previous studies have shown that the crystal orientation of ferroelectric films is an important factor affecting the local structure of ferroelectric films. Therefore, starting from the micro domain structure, the effects of denoising algorithm on the crystallization temperature and electrical properties of PZT ferroelectric thin films shown in SEM were studied. At the same time, the crystalline layers in the microstructure of PZT and PZT / PTO films were analyzed by SEM images, and the electrical properties of PZT films were compared with ferroelectric and stable dielectric properties. The experimental results show that the residual polarization intensity obtained by annealing at 550C after adding PTO seed layer is about 20uC/CM2, which is basically the same as that obtained by annealing PZT ferroelectric film at 650C . Therefore, the ferroelectric properties of PZT film are enhanced after adding PTO seed layer. Moreover, the dielectric loss of PZT / PTO film is smaller than that of PZT film.


Denoising Algorithm, Sem Image, PTO Seed Layer, PZT Ferroelectric Film Crystallization Temperature, Electrical Properties

Cite This Paper

Romanya Vijue. Sem Image Based on Denoising Algorithm Shows the Effect of PTO Seed Layer on the Crystallization Temperature and Electrical Properties of PZT Ferroelectric Thin Films. International Journal of Big Data Intelligent Technology (2020), Vol. 1, Issue 2: 74-90. https://doi.org/10.38007/IJBDIT.2020.010206.


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