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The Determination and Application of the Point Spread Function in the Scanning Electron Microscope

Published online by Cambridge University Press:  03 September 2018

Matthew D. Zotta ,
Mandy C. Nevins Open the ORCID record for Mandy C. Nevins [Opens in a new window] ,
Richard K. Hailstone  and
Eric Lifshin
Matthew D. Zotta
Affiliation:
Nanoscience Constellation of the Colleges of Nanoscience and Engineering, SUNY Polytechnic Institute, Albany, NY 12203, USA
Mandy C. Nevins
Affiliation:
Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA
Richard K. Hailstone
Affiliation:
Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA
Eric Lifshin*
Affiliation:
Nanoscience Constellation of the Colleges of Nanoscience and Engineering, SUNY Polytechnic Institute, Albany, NY 12203, USA
*
*Author for correspondence: Eric Lifshin, E-mail: ericlifshin@gmail.com
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Abstract

A method is presented to determine the spatial distribution of electrons in the focused beam of a scanning electron microscope (SEM). Knowledge of the electron distribution is valuable for characterizing and monitoring SEM performance, as well as for modeling and simulation in computational scanning electron microscopy. Specifically, it can be used to characterize astigmatism as well as study the relationship between beam energy, beam current, working distance, and beam shape and size. In addition, knowledge of the distribution of electrons in the beam can be utilized with deconvolution methods to improve the resolution and quality of backscattered, secondary, and transmitted electron images obtained with thermionic, FEG, or Schottky source instruments. The proposed method represents an improvement over previous methods for determining the spatial distribution of electrons in an SEM beam. Several practical applications are presented.

Keywords

point spread functionscanning electron microscopyelectron distributionastigmatism correctionimage restoration
Type
Software and Instrumentation
Information
Microscopy and Microanalysis , Volume 24 , Issue 4 , August 2018 , pp. 396 - 405
Copyright
© Microscopy Society of America 2018 

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Footnotes

†

These authors contributed equally to this work.

References

Babin, S, Gaevski, M, Joy, D, Machin, M Martynov, A (2008) Automatic measurement of electron-beam diameter and astigmatism: BEAMETR. Phys Procedia 1, 113–118.Google Scholar
Goldstein, J, Newbury, D, Michael, J, Ritchie, N, Scott, JH Joy, D (2018) Scanning Electron Microscopy and X-Ray Microanalysis, 4th ed. New York: Springer.Google Scholar
Gonzalez, RC Woods, RE (Eds.) (2008) Image restoration and reconstruction. In: Digital Image Processing, 3rd ed., pp. 311–393. Upper Saddle River, NJ: Pearson Prentice Hall.Google Scholar
International Organization for Standardization (ISO) (2011) ISO/TS 24597:2011(E) – Microbeam Analysis – Scanning Electron Microscopy – Methods of Evaluating Image Sharpness.Google Scholar
Kandel, YP, Zotta, MD, Caferra, A, Moore, R Lifshin, E (2015) Measurement of the electron beam point spread function (PSF) in a scanning electron microscope (SEM). Microsc Microanal 21(Suppl 3), 699–700.Google Scholar
Klemperer, O Barnett, ME (2011) Electron Optics, 3rd ed. Cambridge, UK: Cambridge University Press.Google Scholar
Kološová, J, Hrnčíř, T, Jiruše, J, Rudolf, M Zlámal, J (2015) On the calculation of SEM and FIB beam profiles. Microsc Microanal 21(Suppl 4), 206–211.Google Scholar
Khursheed, A (2011) Scanning Electron Microscope Optics and Spectrometers. Hackensack, NJ: World Scientific.Google Scholar
Liddle, JA, Naulleau, P Schmid, G (2004) Probe shape measurement in an electron beam lithography system. J Vac Sci Technol B 22(6), 2897–2901.Google Scholar
Lifshin, E, Kandel, YP Moore, RL (2014) Improving scanning electron microscope resolution for near planar samples through the use of image restoration. Microsc Microanal 20, 78–89.Google Scholar
Michael, JR Williams, DB (1987) A consistent definition of probe size and spatial resolution in the analytical electron microscope. J Microsc 147, 289–303.Google Scholar
Orloff, J (1997) Handbook of Charged Particle Optics, 1st ed. Boca Raton, FL: CRC Press.Google Scholar
Reimer, L (1998) Scanning Electron Microscopy: Physics of Image Formation and Microanalysis, 2nd ed. Berlin, Heidelberg: Springer-Verlag.Google Scholar
Sato, M (2009) Resolution. In: Handbook of Charged Particle Optics, 2nd ed., Orloff J (Ed.), pp. 391–435. Boca Raton, FL: CRC Press.Google Scholar
Schneider, CA, Rasband, WS Eliceiri, KW (2012) NIH Image to ImageJ: 25 years of image analysis. Nature Methods 9(7), 671–675.Google Scholar
Watanabe, M (2011) X-ray energy-dispersive spectrometry in scanning transmission electron microscopes. In: Scanning Transmission Electron Microscopy, Pennycook SJ and Nellist PD (Eds.), pp. 291–351. New York, NY: Springer.Google Scholar
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