Response Surface Methodology (RSM) in Fabrication of Nanostructured Silicon

Article Preview

Abstract:

In this paper, a respond surface methodology (RSM) model has been developed using three levels Box-Benkhen experimental design (BBD) technique to study the influence of several metal-assisted chemical etching (MACE) process variables on the properties of nanostructured silicon (Si) wafer. Five process variables are examined i.e. concentrations of silver (Ag), hydrofluoric acid (HF), deposition time, H2O2 concentration and etching time as a function of etching rate. Design-Expert® software (version 7.1) is used in formulating the RSM model of five factors with 46 experiments. A regression quadratic model is developed to correlate the process variables where the most significant factors are identified and validated using analysis of variance (ANOVA). The model for etching rate is found to be significant with R2 of 0.8, where both Ag concentrations and etching time are the major influence.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

151-155

Citation:

Online since:

May 2016

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2016 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] S. Chong, C. Dee, N. Yahya and S. Rahman. Journal of Nanoparticle Research. 15. 4. (2013), p.1.

Google Scholar

[2] S. Barth, F. Hernandez-Ramirez, J.D. Holmes and A. Romano-Rodriguez. Progress in Materials Science. 55. 6. (2010), p.563.

Google Scholar

[3] K.W. Kolasinski. Current Opinion in Solid State and Materials Science. 10. 3–4. (2006), p.182.

Google Scholar

[4] K.H. Ploog. Journal of Crystal Growth. 301–302. 0. (2007), p.10.

Google Scholar

[5] N. Galiana, P. -P. Martin, C. Munuera, M. Varela, F. Soria, C. Ocal, A. Ruiz and M. Alonso. Surface Science. 600. 18. (2006), p.3956.

DOI: 10.1016/j.susc.2006.01.107

Google Scholar

[6] Z. Yue, H. Shen and Y. Jiang. Applied Surface Science. 271. (2013), p.402.

Google Scholar

[7] a. colli, s. hofmann, a. fasoli, a. c. ferrari, c. ducati, r. e. dunin-borkowski and j. robertson. Applied Physics A – Materials Science & Processing. 85. (2006), p.247.

DOI: 10.1007/s00339-006-3708-8

Google Scholar

[8] Z.R. Smith, R.L. Smith and S.D. Collins. Electrochimica Acta. 92. (2013), p.139.

Google Scholar

[9] K. Peng, H. Fang, J. Hu, Y. Wu, J. Zhu, Y. Yan and S. Lee. Chemistry. 12. 30. (2006), p.7942.

Google Scholar

[10] X. Li. Current Opinion in Solid State and Materials Science. 16. 2. (2012), p.71.

Google Scholar

[11] K. Tsujino and M. Matsumura. Electrochimica Acta. 53. 1. (2007), p.28.

Google Scholar

[12] Y. Kato and S. Adachi. Applied Surface Science. 258. 15. (2012), p.5689.

Google Scholar

[13] F. Zhao, G. -a. Cheng, R. -t. Zheng and L. -y. Xia. Journal of the Korean Physical Society. 52. (2008), p.104.

Google Scholar

[14] C. Yuangyai and H.B. Nembhard. Emerging Nanotechnologies for Manufacturing. W. Ahmed and M. Jackson. Academic Press. Inc., (2009 ).

Google Scholar

[15] J.W. Lee, J.F. Donohue, K.D. Mackenzie, R. Westerman, D. Johnson and S.J. Pearton. Solid-State Electronics 43 (1999), p.1769.

DOI: 10.1016/s0038-1101(99)00129-x

Google Scholar

[16] S. Chattopadhyay, X. Li and P.W. Bohn. Journal of Applied Physics. 91. 9. (2002), p.6134.

Google Scholar

[17] X. Sun, L. Lin, Z. Li, Z. Zhang and J. Feng. Applied Surface Science. 256. 3. (2009), p.916.

Google Scholar

[18] W.Q. Xie, J.I. Oh and W.Z. Shen. Nanotechnology. 22. 6. (2011), p.065704.

Google Scholar

[19] C. Chartier, S. Bastide and C. Lévy-Clément. Electrochimica Acta. 53. 17. (2008), p.5509.

DOI: 10.1016/j.electacta.2008.03.009

Google Scholar