Determination of Thickness of PZO<sub> </sub>Films Deposited on ITO Glass Substrates-Reference-Cited by-同舟云学术

Determination of Thickness of PZOFilms Deposited on ITO Glass Substrates

Published:2013-01 Issue: Volume:537 Page:161-164
ISSN:1662-9795
Container-title:Key Engineering Materials
language:
Short-container-title:KEM

Author:

Li Xue Jiao¹,Zhang Cheng²,Zhang Na²

Affiliation:

1. Shanghai Institute of Thecnology

2. Shanghai Institute of Technology

Abstract

PZO (PbZrO3) coatings with different thicknesses were deposited onto Indium Tin Oxide ITO glass substrates at room temperature by magnetron sputtering technique. UV-Vis absorption spectra method and microhardness testing method were used to measure the thickness of coating. It was proved that the measuring results of film thickness by two kinds of methods were equivalent, and either one method can be alternatively used to determine the thickness of deposited films.

Publisher

Trans Tech Publications, Ltd.

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://www.scientific.net/KEM.537.161.pdf

Reference5 articles.

1. F. Mitsugi, A. Matsuoka, Y. Umeda, Development of thickness measurement program for transparent conducting oxide, Thin Solid Films. 518 (2010) 6330–6333.

2. J. Pei, F.L. Degertekin, B.V. Honein, B.T. Khuri-Yakub, K.C. Saraswa, In-situ thin film thickness measurement using ultrasonics waves, Proc. Int. Ultrasonic Symp. (1994) 1237–1240.

3. J. Lhotka, R. Kuzel, G. Cappuccio, V. Valvod, Thickness determination of thin polycrystalline film by grazing incidence X-ray diffraction, Surf. Coat. Technol. 148 (2001) 96–101.

4. K.H. Chen, C.C. Hsu, D.C. Su, Appl. Phys. B 77 (2003) 839.

5. G. Cox, C.J.R. Sheppard, et al. Measurement of thin coatings in the confocal microscope, Micron 32 (2001) 701–705.

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