Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-03T01:05:25.115Z Has data issue: false hasContentIssue false
  • English
  • Français

A New Methodology to Analyze Instabilities in SEM Imaging

Published online by Cambridge University Press:  20 October 2014

Catalina Mansilla ,
Václav Ocelík  and
Jeff T. M. De Hosson
Catalina Mansilla*
Affiliation:
Department of Applied Physics, Materials innovation institute M2i, University of Groningen, Nijenborgh 4, Groningen, 9474 AG, The Netherlands
Václav Ocelík
Affiliation:
Department of Applied Physics, Materials innovation institute M2i, University of Groningen, Nijenborgh 4, Groningen, 9474 AG, The Netherlands
Jeff T. M. De Hosson
Affiliation:
Department of Applied Physics, Materials innovation institute M2i, University of Groningen, Nijenborgh 4, Groningen, 9474 AG, The Netherlands
*
*Corresponding author. [email protected]; [email protected]; [email protected]
Get access

Abstract

This paper presents a statistical method to analyze instabilities that can be introduced during imaging in scanning electron microscopy (SEM). The method is based on the correlation of digital images and it can be used at different length scales. It consists of the evaluation of three different approaches with four parameters in total. The methodology is exemplified with a specific case of internal stress measurements where ion milling and SEM imaging are combined with digital image correlation. It is concluded that before these measurements it is important to test the SEM column to ensure the minimization and randomization of the imaging instabilities. The method has been applied onto three different field emission gun SEMs (Philips XL30, Tescan Lyra, FEI Helios 650) that represent three successive generations of SEMs. Important to note that the imaging instability can be quantified and its source can be identified.

Keywords

scanning electron microscopydigital image correlationself-correlation imageresidual stressfocused ion beam
Type
Technology and Software Development
Information
Microscopy and Microanalysis , Volume 20 , Issue 6 , December 2014 , pp. 1625 - 1637
Copyright
© Microscopy Society of America 2014 

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

Aramis v5.3.0 User Manual, GOM mbH, D-38106 Braunschweig, Germany, Rev A, 20.8.2004.Google Scholar
Bouzakis, K.-D., Skordaris, G., Hadjiyiannis, S., Asimakopoulos, A., Mirisidis, J., Michailidis, N., Erkens, G., Cremer, R., Klocke, F. & Kleinjans, M. (2004). A nanoindentation based determination of internal stress alterations in PVD films and their cemented carbides substrates induced by recoating procedures and their effect on the cutting performance. Thin Solid Films 447–448, 264–271.Google Scholar
Kahn-Jetter, Z.L. & Chu, T.C. (1990). Three-dimensional displacement measurements using digital image correlation and photogrammic analysis. Exp Mech 30, 10–16.Google Scholar
Kang, K.J., Yao, N., He, M.Y. & Evans, A. G. (2003). A method for in situ measurement of the residual stress in thin films by using the focused ion beam. Thin Solid Films 443, 71–77.CrossRefGoogle Scholar
Korsunsky, A.M., Sebastiani, M. & Bemporad, E. (2010). Residual stress evaluation at the micrometer scale: Analysis of thin coatings by FIB milling and digital image correlation. Surf Coat Technol 205, 2393–2403.CrossRefGoogle Scholar
Krottenthaler, M., Schmid, C., Schaufler, J., Durst, K. & Göken, M. (2013). A simple method for residual stress measurements in thin films by means of focused ion beam milling and digital image correlation. Surf Coat Technol 215, 247–252.Google Scholar
Lagattu, F., Bridier, F., Villechaise, P. & Brillaud, J. (2006). In-plane strain measurements on a microscopic scale by coupling digital image correlation and an in situ SEM technique. Mater Charact 56, 10–18.CrossRefGoogle Scholar
Mansilla, C., Ocelik, O. & De Hosson, J.Th.M. (2013). Statistical analysis of SEM image noise. In: 11th International Conference on Surface Effects and Contact Mechanics: Computational Methods and Experiments, J.Th.M. De Hosson & C.A. Brebbia(Eds), pp. 13–24. vol. 78, 2013. WIT Transactions on Engineering Sciences. Siena, Italy: WIT Press.Google Scholar
Nelson, D.V. (2010). Residual stress determination by hole drilling combined with optical methods. Expl Mech 50, 145–158.CrossRefGoogle Scholar
Nelson, D.V., Makino, A. & Schmidt, T. (2006). Residual stress determination using hole drilling and 3D image correlation. Expl Mech 46, 31–38.CrossRefGoogle Scholar
Orfanidis, S.J. (1996). Optimum Signal Processing. An Introduction, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Pawley, J. (1985). Strategy for locating and eliminating sources of mains frequency stray magnetic-fileds. Scanning 7, 43–46.Google Scholar
Pawley, J.B. (1987). Use of pseudo-stereo techniques to detect magnetic stray field in the SEM. Scanning 9, 134–136.CrossRefGoogle Scholar
Prummer, R. & Pfeiffervollmar, H. (1983). A method for X-ray stress-analysis of thermochemically treated materials. Adv X-Ray Anal 26, 225–231.Google Scholar
Sabaté, N., Vogel, D., Gollhardt, A., Keller, J., Cané, C., Gràcia, I., Morante, J.R. & Michel, B. (2007). Residual stress measurement on a MEMS structure with high-spatial resolution. J Microelectromech Syst 16, 365–372.Google Scholar
Sabaté, N., Vogel, D., Gollhardt, A., Marcos, J., Gràcia, I., Cané, C. & Michel, B. (2006). Digital image correlation of nanoscale deformation fields for local stress measurement in thin films. Nanotechnology 17, 5264–5270.Google Scholar
Sebastiani, M., Eberl, C., Bemporad, E. & Pharr, G.M. (2011). Depth-resolved residual stress analysis of thin coatings by a new FIB-DIC method. Mat Sci Eng A 528, 7901–7908.Google Scholar
Shen, B. & Paulino, G.H. (2011). Direct extraction of cohesive fracture properties from digital image correlation: A hybrid inverse technique. Exp Mech 53, 143–163.CrossRefGoogle Scholar
Shull, A.L. & Spaepen, F. (1996). Measurements of stress during vapor deposition of copper and silver thin films and multilayers. J Appl Phys 80, 6243–6256.CrossRefGoogle Scholar
Song, X., Yeap, K.B., Zhu, J., Belnoue, J., Sebastiani, M., Bemporad, E., Zeng, K. & Korsunsky, A.M. (2012). Residual stress measurement in thin films at sub-micron scale using focused ion beam milling and imaging. Thin Solid Films 520, 2073–2076.Google Scholar
Sutton, M.A., Li, N., Joy, D.C., Reynolds, A.P. & Li, X. (2007). Scanning electron microscopy for quantitative small and large deformation measurements part I: SEM imaging at magnifications from 200 to 10,000. Exp Mech 47, 775–787.Google Scholar
Sutton, M.A., Orteu, J.J. & Schreier, H.W. (2009). Image Correlation for Shape, Motion and Deformation Measurements—Basic Concepts, Theory and Applications. New York, NY: Springer.Google Scholar
Tada, H., Paris, P. & Irwin, G. (2000). The Stress Analysis of Cracks Handbook . 3rd edition, ASME Press, New York.Google Scholar
Wang, H., Xie, H., Ju, Y. & Duan, Q. (2006). Error analysis of digital speckle correlation method under scanning electron microscope. Exp Tech 30, 42–45.Google Scholar
Winiarski, B., Gholinia, A., Tian, J., Yokoyama, Y., Liaw, P.K. & Withers, P.J. (2012). Submicron-scale depth profiling of residual stress in amorphous materials by incremental focused ion beam slotting. Acta Mater 60, 2337–2349.CrossRefGoogle Scholar
Winiarski, B., Langford, R.M., Tian, J., Yokoyama, Y., Liaw, P.K. & Withers, P.J. (2010). Mapping residual stress distributions at the micron scale in amorphous materials. Metall Mater Trans A 41, 1743–1751.CrossRefGoogle Scholar
Winiarski, B., Schajer, G.S. & Withers, P.J. (2012). Surface decoration for improving the accuracy of displacement measurements by digital image correlation in SEM. Exp Mech 52, 793–804.Google Scholar
Withers, P.J. & Bhadeshia, H.K.D.H. (2001). Residual stress part 2—Nature and origins. Mater Sci Technol 17, 366–375.CrossRefGoogle Scholar