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Stress-induced surface characterization by wavelet and fractal analysis in Ga-doped ZnO thin films

Published online by Cambridge University Press:  09 May 2017

Chenlei Jing
Affiliation:
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China
Yang Hu
Affiliation:
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China
Wu Tang*
Affiliation:
State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China
*
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Abstract

The Ga-doped ZnO (GZO) were deposited by magnetron reactive sputtering on glass substrates at room temperature with different deposited times to obtain various thickness. The root-mean-square (RMS) roughness obtained from the atomic force microscopy (AFM) images is observed to shift linearly with the deposited time, the fractal geometry and multi-resolution signal decomposition (MRSD) based on wavelet transform were applied on the surface profiles and the results does not synchronously changes as the thickness, which is related to the profile’s frequency. The calculated compressive in-plane stress of highly c-axis oriented GZO films also shows an irregular variation as the increase of film thickness, what’s more, the in-plane stress and fractal dimension exhibit a polynomial relationship and the two parameters can be used for describing the surface morphology.

Type
Articles
Copyright
Copyright © Materials Research Society 2017 

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References

REFERENCES

Ng, Z.-N., Chan, K.-Y., Low, C.-Y., Kamaruddin, S. A. and Sahdan, M. Z., Ceram. Int. 41, S254S258 (2015).CrossRefGoogle Scholar
Jing, C. and Tang, W., Appl. Surf. Sci. 364, 843849 (2016).Google Scholar
Ikegami, K., Yoshiyama, T., Maejima, K., Shibata, H., Tampo, H. and Niki, S., J. Appl. Phys. 105(9), 093713 (2009).Google Scholar
Park, Y. J., Kim, H. N. and Shin, H. H., Appl. Surf. Sci. 255(17), 75327536 (2009).CrossRefGoogle Scholar
Nasehnejad, M., Gholipour Shahraki, M. and Nabiyouni, G., Appl. Surf. Sci. 389, 735741 (2016).CrossRefGoogle Scholar
Mohanty, B. C., Jo, Y. H., Yeon, D. H., Choi, I. J. and Cho, Y. S., Appl. Phys. Lett. 95(6), 062103 (2009).Google Scholar
Wang, Y., Tang, W., Liu, J. and Zhang, L., Appl. Phys. Lett. 106(16), 162101 (2015).Google Scholar
Hung-Chun Lai, H., Basheer, T., Kuznetsov, V. L., Egdell, R. G., Jacobs, R. M. J., Pepper, M. and Edwards, P. P., J. Appl. Phys. 112(8), 083708 (2012).Google Scholar
Sharma, B. K. and Khare, N., J. Phys. D: Appl. Phys. 43(46), 465402 (2010).CrossRefGoogle Scholar
Alipour, R., Hosseinnejad, M. T., Salar Elahi, A. and Ghoranneviss, M., J. Alloys Compd. 687, 7278 (2016).Google Scholar
Mallat, S. G., IEEE Transactions on Pattern Analysis & Machine Intelligence 11(7), 674693 (1989).Google Scholar
Raoufi, D. and Kalali, Z., Phys. B: Condens. Matter 407(21), 43694374 (2012).CrossRefGoogle Scholar
Ai, T., Zhang, R., Zhou, H. W. and Pei, J. L., Appl. Surf. Sci. 314, 610621 (2014).CrossRefGoogle Scholar
Sarkar, N. and Chaudhuri, B. B., IEEE Transactions on Systems, Man, and Cybernetics 24(1), 115120 (1994).CrossRefGoogle Scholar
Bao, D., Gu, H. and Kuang, A., Thin Solid Films 312 (1-2), 3739 (1998).CrossRefGoogle Scholar
Raoufi, D. and Raoufi, T., Appl. Surf. Sci. 255(11), 58125817 (2009).CrossRefGoogle Scholar