Measuring multiple nano-textured areas simultaneously with imaging scatterometry
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Measuring multiple nano-textured areas simultaneously with imaging scatterometry. / Madsen, Jonas Skovlund; Hansen, Poul Erik; Bilenberg, Brian; Nygård, Jesper; Madsen, Morten Hannibal.
Proceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016. ed. / P. Bointon; R. Leach; N. Southon. Nottingham, UK : euspen, 2017.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Measuring multiple nano-textured areas simultaneously with imaging scatterometry
AU - Madsen, Jonas Skovlund
AU - Hansen, Poul Erik
AU - Bilenberg, Brian
AU - Nygård, Jesper
AU - Madsen, Morten Hannibal
N1 - Conference code: 16
PY - 2017
Y1 - 2017
N2 - Periodic nano- Textured surfaces have been characterised using the new optical imaging scatterometry technique. A major benefit of imaging scatterometry compared to traditional scatterometry is that an area much smaller than the illuminated area can be analysed. That is, instead of averaging over the full illumination spot, scatterometry analysis can be made pixel by pixel. An area of interest much smaller than the spot size can therefore be characterized and the user first has to select the area of interest in the post-processing. Furthermore, a specific area on the sample can easily be found and areas with defects can be avoided. These advantages make imaging scatterometry a very effective and user-friendly characterization method and allow us to determine the homogeneity of a nano- Textured surface by performing pixel-wise analyses. In the analysis an inverse modelling approach is used, where measured diffraction efficiencies are compared to simulated diffraction efficiencies using a least-square fitting approach. We demonstrate an imaging scatterometry setup built into an optical microscope. The setup is capable of measuring multiple 2D gratings with pitches of 200 nm simultaneously. It is demonstrated that the imaging scatterometer can measure 2D nano- Textured surfaces with an accuracy of a few nm for the depth and width of the structures on areas down to 3 x 3 μm2.
AB - Periodic nano- Textured surfaces have been characterised using the new optical imaging scatterometry technique. A major benefit of imaging scatterometry compared to traditional scatterometry is that an area much smaller than the illuminated area can be analysed. That is, instead of averaging over the full illumination spot, scatterometry analysis can be made pixel by pixel. An area of interest much smaller than the spot size can therefore be characterized and the user first has to select the area of interest in the post-processing. Furthermore, a specific area on the sample can easily be found and areas with defects can be avoided. These advantages make imaging scatterometry a very effective and user-friendly characterization method and allow us to determine the homogeneity of a nano- Textured surface by performing pixel-wise analyses. In the analysis an inverse modelling approach is used, where measured diffraction efficiencies are compared to simulated diffraction efficiencies using a least-square fitting approach. We demonstrate an imaging scatterometry setup built into an optical microscope. The setup is capable of measuring multiple 2D gratings with pitches of 200 nm simultaneously. It is demonstrated that the imaging scatterometer can measure 2D nano- Textured surfaces with an accuracy of a few nm for the depth and width of the structures on areas down to 3 x 3 μm2.
KW - Instrumentation
KW - Nanometrology
KW - Nanostructures
KW - Scatterometry
UR - http://www.scopus.com/inward/record.url?scp=84984598934&partnerID=8YFLogxK
M3 - Article in proceedings
AN - SCOPUS:84984598934
BT - Proceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
A2 - Bointon, P.
A2 - Leach, R.
A2 - Southon, N.
PB - euspen
CY - Nottingham, UK
Y2 - 30 May 2016 through 3 June 2016
ER -
ID: 179324816