Experiments in Fluids

, 59:61 | Cite as

Investigation of the flow structure in thin polymer films using 3D µPTV enhanced by GPU

  • Philipp Cavadini
  • Hannes Weinhold
  • Max Tönsmann
  • Suren Chilingaryan
  • Andreas Kopmann
  • Alexander Lewkowicz
  • Chuan Miao
  • Philip Scharfer
  • Wilhelm Schabel
Research Article

Abstract

To understand the effects of inhomogeneous drying on the quality of polymer coatings, an experimental setup to resolve the occurring flow field throughout the drying film has been developed. Deconvolution microscopy is used to analyze the flow field in 3D and time. Since the dimension of the spatial component in the direction of the line-of-sight is limited compared to the lateral components, a multi-focal approach is used. Here, the beam of light is equally distributed on up to five cameras using cubic beam splitters. Adding a meniscus lens between each pair of camera and beam splitter and setting different distances between each camera and its meniscus lens creates multi-focality and allows one to increase the depth of the observed volume. Resolving the spatial component in the line-of-sight direction is based on analyzing the point spread function. The analysis of the PSF is computational expensive and introduces a high complexity compared to traditional particle image velocimetry approaches. A new algorithm tailored to the parallel computing architecture of recent graphics processing units has been developed. The algorithm is able to process typical images in less than a second and has further potential to realize online analysis in the future. As a prove of principle, the flow fields occurring in thin polymer solutions drying at ambient conditions and at boundary conditions that force inhomogeneous drying are presented.

References

  1. Born MAX, Wolf E (1980) Chapter VIII—elements of the theory of diffraction. In: Wolf MB (ed) Principles of optics (Sixth (Corrected) Edition). Pergamon, ‎Oxford, pp 370–458Google Scholar
  2. Brokmann X et al (2005) Orientational imaging and tracking of single CdSe nanocrystals by defocused microscopy. Chem Phys Lett 406(1–3):210–214CrossRefGoogle Scholar
  3. Cavadini P et al (2013) Investigation of surface deformation during drying of thin polymer films due to Marangoni convection. Chem Eng Process 64(0):24–30CrossRefGoogle Scholar
  4. Cavadini P et al (2015) Investigation of the flow field in thin polymer films due to inhomogeneous drying. J Coat Technol Res 12(5):921–926CrossRefGoogle Scholar
  5. Cierpka C, Kähler CJ (2012) Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics. J Vis 15(1):1–31CrossRefGoogle Scholar
  6. Davies ER (1985) Radial histograms as an aid in the inspection of circular objects. IEE Proc D Control Theory Appl 132(4):158–163CrossRefGoogle Scholar
  7. Elsinga GE (2008) Tomographic particle image velocimetry and its application to turbulent boundary layers. Institute of Aerospace Engineering, TU DelftGoogle Scholar
  8. Elsinga GE et al (2006) Tomographic particle image velocimetry. Exp Fluids 41(6):933–947CrossRefGoogle Scholar
  9. Frisken Gibson S, Lanni F (1992) Experimental test of an analytical model of aberration in an oil-immersion objective lens used in three-dimensional light microscopy. J Opt Soc Am A 9(1):154–166CrossRefGoogle Scholar
  10. Harris DJ, Lewis JA (2008) Marangoni effects on evaporative lithographic patterning of colloidal films. Langmuir 24(8):3681–3685CrossRefGoogle Scholar
  11. Harris DJ et al (2007) Patterning colloidal films via evaporative lithography. Phys Rev Lett 98(14):148301CrossRefGoogle Scholar
  12. Hollitt C (2013) A convolution approach to the circle Hough transform for arbitrary radius. Mach Vis Appl 24(4):683–694CrossRefGoogle Scholar
  13. Jonas M et al (2006) Detecting single quantum dot motion with nanometer resolution for applications in cell biology. IEEE Trans Nanobiosci 5(4):246–50CrossRefGoogle Scholar
  14. Kinoshita H et al (2007) Three-dimensional measurement and visualization of internal flow of a moving droplet using confocal micro-PIV. Lab Chip 7(3):338–346CrossRefGoogle Scholar
  15. Kirchartz T et al (2012) Understanding the thickness-dependent performance of organic bulk heterojunction solar cells: the influence of mobility, lifetime, and space charge. J Phys Chem Lett 3(23):3470–3475CrossRefGoogle Scholar
  16. Lindken R, Westerweel J, Wieneke B (2006) Stereoscopic micro particle image velocimetry. Exp Fluids 41(2):161–171CrossRefGoogle Scholar
  17. Lindken R et al (2009) Micro-particle image velocimetry ([small micro]PIV): recent developments, applications, and guidelines. Lab Chip 9(17):2551–2567CrossRefGoogle Scholar
  18. McNally JG et al (1994) Artifacts in computational optical-sectioning microscopy. J Opt Soc Am A 11(3):1056–1067CrossRefGoogle Scholar
  19. Memmolo P et al (2015) Recent advances in holographic 3D particle tracking. Adv Opt Photon 7(4):713–755CrossRefGoogle Scholar
  20. Moule AJ, Bonekamp JB, Meerholz K (2006) The effect of active layer thickness and composition on the performance of bulk-heterojunction solar cells. J Appl Phys 100(9):094503CrossRefGoogle Scholar
  21. Nasse MJ, Woehl JC (2010) Realistic modeling of the illumination point spread function in confocal scanning optical microscopy. J Opt Soc Am A 27(2):295–302CrossRefGoogle Scholar
  22. Ober R et al (1983) Study of the surface tension of polymer solutions: theory and experiments. Good solvent conditions. Macromolecules 16(1):50–55CrossRefGoogle Scholar
  23. Olsen MG, Adrian RJ (2000) Out-of-focus effects on particle image visibility and correlation in microscopic particle image velocimetry. Exp Fluids 29:S166-S174CrossRefGoogle Scholar
  24. Park JS, Kihm KD (2006) Three-dimensional micro-PTV using deconvolution microscopy. Exp Fluids 40(3):491–499CrossRefGoogle Scholar
  25. Park J, Choi C, Kihm K (2004) Optically sliced micro-PIV using confocal laser scanning microscopy (CLSM). Exp Fluids 37(1):105–119CrossRefGoogle Scholar
  26. Park JS, Choi CK, Kihm KD (2005) Temperature measurement for a nanoparticle suspension by detecting the Brownian motion using optical serial sectioning microscopy (OSSM). Meas Sci Technol 16(7):1418CrossRefGoogle Scholar
  27. Pedersen SJK (2007) Circular Hough transform, in vision, graphics, and interactive systems. Aalborg University, AalborgGoogle Scholar
  28. Rui L, Yan-Fei S (2011) Pattern matching for three-dimensional tracking of sub-micron fluorescent particles. Meas Sci Technol 22(4):045402CrossRefGoogle Scholar
  29. Speidel M, Joná A, Florin E-L (2003) Three-dimensional tracking of fluorescent nanoparticles with subnanometer precision by use of off-focus imaging. Opt Lett 28(2):69–71CrossRefGoogle Scholar
  30. Vieyra Salas JA et al (2012) Active control of evaporative solution deposition by modulated infrared illumination. J Phys Chem C 116(22):12038–12047CrossRefGoogle Scholar
  31. Vogelgesang M et al (2012) UFO: a scalable GPU-based image processing framework for on-line monitoring. In: High performance computing and communication and 2012 IEEE 9th international conference on embedded software and systems (HPCC-ICESS), 2012 IEEE 14th international conference onGoogle Scholar
  32. Wereley ST, Meinhart CD (2010) Recent advances in micro-particle image velocimetry. In: Annual review of fluid mechanics, annual reviews: Palo Alto, pp 557–576Google Scholar
  33. Wu M, Roberts JW, Buckley M (2005) Three-dimensional fluorescent particle tracking at micron-scale using a single camera. Exp Fluids 38(4):461–465CrossRefGoogle Scholar
  34. Yuen HK et al (1990) Comparative study of Hough transform methods for circle finding. Image Vis Comput 8(1):71–77CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Philipp Cavadini
    • 1
  • Hannes Weinhold
    • 1
  • Max Tönsmann
    • 1
  • Suren Chilingaryan
    • 2
  • Andreas Kopmann
    • 2
  • Alexander Lewkowicz
    • 2
  • Chuan Miao
    • 2
  • Philip Scharfer
    • 1
  • Wilhelm Schabel
    • 1
  1. 1.Institute of Thermal Process Engineering, Thin Film TechnologyKarlsruhe Institute of TechnologyKarlsruheGermany
  2. 2.Institute of Data Processing and ElectronicsKarlsruhe Institute of TechnologyKarlsruheGermany

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