Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-29T08:33:04.910Z Has data issue: false hasContentIssue false
  • English
  • Français

An approach to the three-dimensional simulations of the Bosch process

Published online by Cambridge University Press:  20 December 2011

Branislav Radjenović  and
Marija Radmilović-Radjenović
Branislav Radjenović
Affiliation:
Institute of Physics, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
Marija Radmilović-Radjenović*
Affiliation:
Institute of Physics, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
*
a)Address all correspondence to this author. e-mail: marija@ipb.ac.rs
Get access

Abstract

The Bosch process is a high-speed, deep reactive ion etching technology for silicon, which has both excellent flexibility and selectivity. For better understanding and control of the time evolution of the feature profile during the Bosch process, an accurate, predictive, and fast simulation tool would be useful. In this article, a simplified model for three-dimensional simulation of the Bosch process is proposed. Etching is modeled by an isotropic etching rate superposed by an anisotropic term. For the passivation cycle, a perfect conformal deposition is assumed corresponding to a constant deposition rate. Level set method was used for tracking the surface evolution. Since the etching and deposition rates are the model input parameters which are not computed, the computational time is significantly reduced. Calculation results presented here illustrate some typical applications of the Bosch process.

Keywords

PassivationPlasma depositionSi
Type
Articles
Information
Journal of Materials Research , Volume 27 , Issue 5: Focus Issue: Plasma and Ion-Beam Assisted Materials Processing , 14 March 2012 , pp. 793 - 798
Copyright
Copyright © Materials Research Society 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Elwenspoek, M. and Jansen, H.V.: Silicon Micromachining (Cambridge University Press, UK, 2004).Google Scholar
2.Ostrikov, K.: Colloquium: Reactive plasmas as a versatile nanofabrication tool. Rev. Mod. Phys. 77, 489 (2005).CrossRefGoogle Scholar
3.Petit-Etienne, C., Darnon, M., Vallier, L., Pargon, E., Cunge, G., Boulard, F., Joubert, O., Banna, S., and Lill, T.: Reducing damage in Si substrates during gate etching processes by synchronous plasma pulsing. J. Vac. Sci. Technol. B 28, 926 (2010).CrossRefGoogle Scholar
4.Radjenović, B. and Radmilović-Radjenović, M.: Top down nano technologies in surface modification of materials. Cent. Eur. J. Phys. 9, 265 (2011).Google Scholar
5.Mariotti, D. and Sankaran, R.M.: Perspectives on atmospheric-pressure plasmas for nanofabrication. J. Phys. D: Appl. Phys. 44, 174023 (2011).CrossRefGoogle Scholar
6.Akbulut, H. and Inal, O.T.: Plasma-assisted deposition of metal and metal oxide coatings. J. Mater. Sci. 33, 1189 (1998).CrossRefGoogle Scholar
7.Zhang, Q., Yoon, S.F., and Yu, M.B.: Synthesis of carbon tubes using microwave plasma-assisted chemical vapor deposition. J. Mater. Res. 15, 1749 (2000).CrossRefGoogle Scholar
8.Lieberman, M.A. and Lichtenberg, A.J.: Principles of Plasma Discharges and Materials Processing (John Wiley and Sons, New York, 1994).Google Scholar
9.Chen, F.F. and Chang, J.P.: Lecture Notes on Principles of Plasma Processing (Plenum/Kluwer Publishers, New York, 2002).Google Scholar
10.Campos, L.C., Manfrinato, V.R., Sanchez-Yamagishi, J.D., Kong, J., and Jarillo-Herrero, P.: Anisotropic etching and nanoribbon formation in single-layer graphene. Nano Lett. 9, 2600 (2009).CrossRefGoogle ScholarPubMed
11.Ehiasarian, A.P., Andersson, J., and Anders, A.: Distance-dependent plasma composition and ion energy in high power impulse magnetron sputtering. J. Phys. D: Appl. Phys. 43, 275204 (2010).CrossRefGoogle Scholar
12.Kiihamaki, J.: Deceleration of silicon etch rate at high aspect ratios. J. Vac. Sci. Technol. A 18, 1385 (2000).CrossRefGoogle Scholar
13.Wang, X., Zeng, W., Lu, G., Russo, O.L., and Eisenbraun, E.: High aspect ratio Bosch etching of sub-0.25 μm trenches for hyperintegration applications. J. Vac. Sci. Technol. B 25, 1376 (2007).CrossRefGoogle Scholar
14.Yunkin, V.A., Fischer, D., and Voges, E.: Reactive ion etching of silicon submicron-sized trenches in SF6/C2Cl3F3 plasma. Microelectron. Eng. 27, 463 (1995).CrossRefGoogle Scholar
15.Fu, Y.Q., Colli, A., Fasoli, A., Luo, J.K., Flewitt, A.J., Ferrari, A.C., and Milne, W.I.: Deep reactive ion etching as a tool for nanostructure fabrication. J. Vac. Sci. Technol. B 27, 1520 (2009).CrossRefGoogle Scholar
16.Cherukov, N., Grigoras, K., Peltonen, A., Franssila, S., and Tottonen, I.: The fabrication of silicon nanostructures by local gallium implantation and cryogenic deep reactive ion etching. Nanotechnology 20, 065307 (2009).Google Scholar
17.Bakhtazad, A., Huo, X., and Sabarinathan, J.: Cryogenic shallow reactive ion etch process for profile control on silicon on insulator platform. J. Vac. Sci. Technol. B 29, 041001 (2011).CrossRefGoogle Scholar
18.Roxhed, N., Griss, P., and Stemme, G.: A method for tapered deep reactive ion etching using a modified Bosch process. J. Micromech. Microeng. 17, 1087 (2007).CrossRefGoogle Scholar
19.Abdolvand, R. and Ayazi, F.: An advanced reactive ion etching process for very-high aspect-ratio sub-micron wide tranches in silicon. Sens. Actuators, A 144, 109 (2008).CrossRefGoogle Scholar
20.Lindroos, V., Tilli, M., Lehto, A., and Matooka, T. (editors): Handbook of Silicon Based MEMS Materials and Technologies (Elsevier, Boston, 2010).Google Scholar
21.Zhou, R., Zhang, H., Hao, Y., and Wang, Y.: Simulation of the Bosch process with a string-cell hybrid method. J. Micromech. Microeng. 14, 851 (2004).CrossRefGoogle Scholar
22.Hössinger, A., Djurić, Z., and Babayan, A.: Modeling of deep reactive ion etching in a three-dimensional simulation environment, in Proceedings of the International Conference on Simulation of Semiconductor Processes and Devices (SISPAD), September 25–27, 2007, p. 53.Google Scholar
23.Kokkoris, G., Tserepi, A., Boidouvis, A.G., and Gogolides, E.: Simulation of SiO2 and Si feature etching for microelectronics and microelectromechanical systems fabrication: A combined simulator coupling modules of surface etching, local flux calculation, and profile evolution. J. Vac. Sci. Technol. A 22, 1896 (2004).CrossRefGoogle Scholar
24.Ertl, O. and Selberherr, S.: Three-dimensional level set based Bosch process simulations using ray tracing for flux calculation. Microelectron. Eng. 87, 20 (2010).CrossRefGoogle Scholar
25.Sethian, J.A.: Evolution, implementation, and application of level set and fast marching methods for advancing fronts. J. Comput. Phys. 169, 503 (2001).CrossRefGoogle Scholar
26.Sethian, J.A. and Adalsteinsson, D.: An overview of level set methods for etching, deposition and lithography development. IEEE Trans. Semicond. Manuf. 10, 167 (1997).CrossRefGoogle Scholar
27.Sethian, J.A.: Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (Cambridge University Press, Cambridge, UK, 1999).Google Scholar
28.Whitaker, R.: A level-set approach to 3D reconstruction from range data. Int. J. Comput. Vision 29, 203 (1999).CrossRefGoogle Scholar
29.NLM Insight Segmentation and Registration Toolkit, Available at: http://www.itk.org.Google Scholar
30.Radjenović, B., Lee, J.K., and Radmilović-Radjenović, M.: Sparse field level set method for non-convex Hamiltonians in 3D plasma etching profile simulations. Comput. Phys. Commun. 174, 127 (2006).CrossRefGoogle Scholar