Three-Dimensional Simulations of the Anisotropic Etching Profile Evolution for Producing Nanoscale Devices

• Authors: B. Radjenović , M. Radmilović-Radjenović
• Languages of publication: EN

Abstracts

EN

Refined control of etched profiles is one of the most important tasks of micro (nano) electro mechanical systems manufacturing process. In spite of its wide use, the simulation of etching for micro (nano) electro mechanical systems applications has been so far a partial success only, although a great number of commercial and academic research tools dedicated to this problem are developed. In this paper we describe an application of the sparse field method for solving level set equations in 3D anisotropic wet etching of silicon with potassium hydroxide (KOH). Angular dependence of the silicon etching rate is determined on the basis of the silicon crystal symmetry properties. Some examples illustrating developed methodology are given.

Keywords

EN

81.65.Cf

Discipline

• 81.65.Cf: Surface cleaning, etching, patterning(see also 52.77.Bn Etching and cleaning in physics of plasmas)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2011
• Volume: 119
• Issue: 3
• Pages: 447-450

Dates

published

2011-03

received

2010-02-27

(unknown)

2010-11-18

Contributors

author

B. Radjenović

• Institute of Physics, Pregrevica 118, 11080 Belgrade, Serbia

author

M. Radmilović-Radjenović

• Institute of Physics, Pregrevica 118, 11080 Belgrade, Serbia

References

• 1. M. Elwenspoek, H.V. Jansen, Silicon Micromachining, Cambridge University Press, Cambridge, UK 1998
• 2. J. Sethian, Level Set Methods and Fastmarching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision and Materials Sciences, Cambridge University Press, Cambridge, UK 1998
• 3. S. Osher, R. Fedkiw, Level Set Method and Dynamic Implicit Surfaces, Springer-Verlag, New York, NY 2003
• 4. R. Whitaker, Int. J. Comp. Vision 29, 203 (1998)
• 5. L. Evans, Partial Differential Eqautions, American Mathematical Society, Providence, RI 1998
• 6. B. Radjenović, J.K. Lee, M. Radmilović-Radjenović, Computer Phys. Commun. 174, 127 (2006)
• 7. J.A. Sethian, D. Adalsteinsson, IEEE Trans. Semicond. Dev. 10, 167 (1996)
• 8. T.J. Hubbard, Ph.D. Thesis, California Institute of Technology, 1994
• 9. K. Sato, M. Shikida, Y. Matsushima, T. Yamashiro, Sensors Actuators A 64, 87 (1988)
• 10. NLM Insight Segmentation and Registration Toolkit, http://www.itk.org
• 11. M. Buerger, Elementary Crystallography, Wiley, New York, Chapman & Hall, London 1956
• 12. M. Shikida, K. Sato, K. Tokoro, D. Uchikawa, Sensors Actuators A 80, 179 (2000)
• 13. B. Radjenović, M. Radmilović-Radjenović, M. Mitrić, Appl. Phys. Lett. 89, 213102 (2006)

Identifiers

DOI

10.12693/APhysPolA.119.447