Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-26T03:17:42.415Z Has data issue: false hasContentIssue false
  • English
  • Français

Three-Dimensional (3D) Nanometrology Based on Scanning Electron Microscope (SEM) Stereophotogrammetry†

Published online by Cambridge University Press:  18 September 2017

Vipin N. Tondare ,
John S. Villarrubia  and
András E. Vladár
Vipin N. Tondare
Affiliation:
Engineering Physics Division, Physical Measurement Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8212, Gaithersburg, MD 20899, USA Theiss Research, La Jolla, CA 92037, USA
John S. Villarrubia
Affiliation:
Engineering Physics Division, Physical Measurement Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8212, Gaithersburg, MD 20899, USA
András E. Vladár*
Affiliation:
Engineering Physics Division, Physical Measurement Laboratory, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Stop 8212, Gaithersburg, MD 20899, USA
*
*Corresponding author. [email protected]
Get access

Abstract

Three-dimensional (3D) reconstruction of a sample surface from scanning electron microscope (SEM) images taken at two perspectives has been known for decades. Nowadays, there exist several commercially available stereophotogrammetry software packages. For testing these software packages, in this study we used Monte Carlo simulated SEM images of virtual samples. A virtual sample is a model in a computer, and its true dimensions are known exactly, which is impossible for real SEM samples due to measurement uncertainty. The simulated SEM images can be used for algorithm testing, development, and validation. We tested two stereophotogrammetry software packages and compared their reconstructed 3D models with the known geometry of the virtual samples used to create the simulated SEM images. Both packages performed relatively well with simulated SEM images of a sample with a rough surface. However, in a sample containing nearly uniform and therefore low-contrast zones, the height reconstruction error was ≈46%. The present stereophotogrammetry software packages need further improvement before they can be used reliably with SEM images with uniform zones.

Keywords

JMONSELscanning electron microscopythree-dimensionalphotogrammetrynanometrology
Type
Instrumentation and Software
Information
Microscopy and Microanalysis , Volume 23 , Issue 5 , October 2017 , pp. 967 - 977
Copyright
© Microscopy Society of America 2017 

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.)

Footnotes

†

Contributions of the National Institute of Standards and Technology are not subject to copyright in the United States.

References

Bunday, B., Cepler, A., Cordes, A. & Arceo, A. (2014). CD-SEM metrology for sub-10 nm width features. In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XXVIII, vol. 9050, Cain, J.P. & Sanchez, M.I. (Eds.), pp. 1–20, 90500T. San Jose, CA: International Society for Optical Engineering.Google Scholar
Bunday, B., Germer, T.A., Vartanian, V., Cordes, A., Cepler, A. & Settens, C. (2013). Gaps analysis for CD metrology beyond the 22 nm node. In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XXVII, vol. 8681, Starikov, A. & Cain, J.P. (Eds.), pp. 1–29, 86813B. San Jose, CA: International Society for Optical Engineering.Google Scholar
Drzazga, W., Paluszynski, J. & Slowko, W. (2006). Three-dimensional characterization of microstructures in a SEM. Meas Sci Technol 17, 28–31.Google Scholar
Eulitz, M. & Reiss, G. (2015). 3D reconstruction of SEM images by use of optical photogrammetry software. J Struct Biol 191, 190–196.Google Scholar
Gontard, L.C., López-Castro, J.D., González-Rovira, L., Vázquez-Martínez, J.M., Varela-Feria, F.M., Marcos, M. & Calvino, J.J. (2017). Assessment of engineered surfaces roughness by high-resolution 3D SEM photogrammetry. Ultramicroscopy 177, 106–114.Google Scholar
Gontard, L.C., Schierholz, R., Yu, S., Cintas, J. & Dunin-Borkowski, R.E. (2016). Photogrammetry of the three-dimensional shape and texture of a nanoscale particle using scanning electron microscopy and free software. Ultramicroscopy 169, 80–88.CrossRefGoogle ScholarPubMed
The International Technology Roadmap for Semiconductors (ITRS) (2013). International Technology Roadmap for Semiconductors, 2013 edition: Process integration, devices, and structures. San Jose, CA: Semiconductor Industry Association. Available online at https://www.semiconductors.org/clientuploads/Research_Technology/ITRS/2013/2013PIDS.pdf. Google Scholar
Marinello, F., Bariani, P., Savio, E., Horsewell, A. & De Chiffre, L. (2008). Critical factors in SEM 3D stereo microscopy. Meas Sci Technol 19, 065705 (12pp).CrossRefGoogle Scholar
Piazzesi, G. (1973). Photogrammetry with the scanning electron microscope. J Phys E Sci Instrum 6, 392–396.Google Scholar
Su, B., Oshana, R., Menaker, M., Barak, Y. & Shi, X. (2000). Shape control using sidewall imaging. In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XIV, vol. 3998, Sullivan, N.T. (Ed.), pp. 232–238. San Jose, CA: International Society for Optical Engineering.Google Scholar
Tafti, A.P., Kirkpatrick, A.B., Alavi, Z., Owen, H.A. & Yu, Z. (2015). Recent advances in 3D SEM surface reconstruction. Micron 78, 54–66.Google Scholar
Vanderlinde, W.E. (2008). 3-D image reconstruction in the scanning electron microscope. ISTFA 2008: Proceedings from the 34th International Symposium for Testing and Failure Analysis, November 2–6, 2008, Portland, OR, pp. 515–523.Google Scholar
Villarrubia, J.S., Tondare, V.N. & Vladár, A.E. (2016). Virtual rough samples to test 3D nanometer-scale SEM stereo photogrammetry. In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XXX, vol. 9778, Sanchez, M.I. & Ukrainstev, V.A. (Eds.), 977809, pp. 1–9. San Jose, CA: International Society for Optical Engineering.Google Scholar
Villarrubia, J.S., Vladár, A.E., Ming, B., Kline, R.J., Sunday, D.F., Chawla, J.S. & List, S. (2015). Scanning electron microscope measurement of width and shape of 10 nm patterned lines using a JMONSEL-modeled library. Ultramicroscopy 154, 15–28.Google Scholar
Villarrubia, J.S., Vladár, A.E. & Postek, M.T. (2005). Scanning electron microscope dimensional metrology using a model-based library. Surf Interface Anal 37, 951–958.Google Scholar
Vladár, A.E., Cizmar, P., Villarrubia, J.S. & Postek, M.T. (2012). Can we get 3D-CD metrology right? In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XXVI, vol. 8324, Starikov, A. (Ed.), 832402, pp. 1–13. San Jose, CA: International Society for Optical Engineering.Google Scholar
Vladár, A.E., Villarrubia, J.S., Chawla, J., Ming, B., Kline, R.J., List, S. & Postek, M.T. (2014). 10 nm three-dimensional CD-SEM metrology. In Proceedings of SPIE, Metrology, Inspection, and Process Control for Microlithography XXVIII, vol. 9050, Cain, J.P. & Sanchez, M.I. (Eds.), 90500A, pp. 1–11. San Jose, CA: International Society for Optical Engineering.Google Scholar
Xie, J. (2011). Stereomicroscopy: 3D imaging and the third dimension measurement. 5990–9127EN. Application note from Agilent Technologies. Palo Alto, CA: Keysight Technologies, Inc.Google Scholar
Zhang, X., Zhou, H., Ge, Z., Vaid, A., Konduparthi, D., Osorio, C., Ventola, S., Meir, R., Shoval, O., Kris, R., Adan, O. & Bar-Zvi, M. (2014). Addressing FinFET metrology challenges in 1× node using tilt-beam critical dimension scanning electron microscope. J Micro/Nanolith MEMS MOEMS 13(4), 1–7.Google Scholar