Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

Silviu Rei; Dan Chicea

doi:10.1515/aucts-2017-0020

.blurhash-client-img { display: none !important; }

Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

Acta Universitatis Cibiniensis. Technical Series

Volume 69 (2017): Issue 1 (December 2017)

By: Silviu Rei and Dan Chicea

Open Access

|Jan 2018

Abstract

Using a Lorentzian function fit as reference, a basic experiment was designed for processing Dynamic Light Scattering time series, allowing to estimate the average particle size of a suspension. For fitting the averaged power spectrum of the time series, several neural network configurations were tested in order to compare the results with the reference. The results of this comparison revealed a good match, serving as a proof of concept for using neural networks as an alternative for DLS time series processing.

References

1. O.V. Salata, “Applications of nanoparticles in biology and medicine. Journal of Nanobiotechnology, vol. 2, no. 3, pp. 3-8, (2004), doi:10.1186/1477-3155-2-3.
Open DOI Search in Google Scholar Back to article
2. G.G. Leppard, “ Nanoparticles in the environment as revealed by transmission electron microscopy: detection, characterisation and activities”, Current Nanoscience vol. 4, no. 2, pp. 278-301, (2008).
Search in Google Scholar Back to article
3. W. Hull, “A new method of chemical analysis”, J. Am. Chem. Soc., vol. 41, no. 8, pp 1168-1175, (1919), doi: 10.1021/ja02229a003
Open DOI Search in Google Scholar Back to article
4. A.L. Patterson, “The Scherrer Formula for X-Ray Particle Size Determination”, Phys. Rev. vol. 56, no. 10, pp. 978-982, (1939), doi:10.1103/PhysRev.56.978
Open DOI Search in Google Scholar Back to article
5. F. Zhang, S.W. Chan, J. E. Spanier, E. Apak, Q. Jin, R. D. Robinson, I. P. Herman, “Cerium oxide nanoparticles: Size-selective formation and structure analysis”, Appl. Phys. Lett. Vol. 80, no. 1, pp. 127-129 (2002); doi:10.1063/1.1430502.
Open DOI Search in Google Scholar Back to article
6. D. Chicea, “Nanoparticles and nanoparticle aggregates sizing by DLS and AFM”, Optoelectronics and Advanced Materials - Rapid Communications vol. 4, no. 9, pp. 1310 - 1315, (2010).
Search in Google Scholar Back to article
7. L. M. Lacava, B. M. Lacava, R. B. Azevedo, Z. G. M. Lacava, N. Buske, A. L. Tronconi and P. C. Morais, “Nanoparticle sizing: a comparative study using atomic force microscopy, transmission electron microscopy, and ferromagnetic resonance”, Journal of Magnetism and Magnetic Materials, vol. 225, no. 1-2, pp. 79-83, (2001).
Search in Google Scholar Back to article
8. JitKang Lim, Swee Pin Yeap, Hui Xin Che and Siew Chun Low, “Characterization of magnetic nanoparticle by dynamic light scattering”, Nanoscale Research Letters, vol. 8, no. 1, pp: 381, (2013), http://www.nanoscalereslett.com/content/8/1/381
Search in Google Scholar Back to article
9. D. Chicea, “Coherent light scattering on nanofluids: computer simulation results”, Applied Optics, vol. 47, no. 10, pp. 1434-1442, DOI: 10.1364/AO.47.001434.10.1364/AO.47.001434
Open DOI Search in Google Scholar Back to article
10. S.A. Prahl, M. Keijer, S.L. Jacques, A.J. Welch, “A Monte Carlo Model of light propagation in tissue”, SPIE Proc. Ser. vol. 5, pp. 102-111, (1989).10.1117/12.2283590
Search in Google Scholar Back to article
11. D. Chicea, I. Turcu, “RWMCS - an alternative random walk Monte Carlo code to simulate light scattering in biological suspensions, OPTIK-International Journal for Light and Electron Optics, Vol 118 no. 5, pp 232-236, (2007), DOI:10.1016/j.ijleo.2006.02.00810.1016/j.ijleo.2006.02.008
Open DOI Search in Google Scholar Back to article
12. L. Wang, S.L. Jacques, L. Zheng, “MCML - Monte Carlo modeling of light transport in multi-layered tissues”, Comput. Methods Programs Biomed., Vol. 47, pp. 131-146, (1995).10.1016/0169-2607(95)01640-F
Search in Google Scholar Back to article
13. J.D. Briers, “Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging”, Physiol. Meas. Vol. 22, R35-R66, (2001).10.1088/0967-3334/22/4/20111761081
Search in Google Scholar Back to article
14. Y. Piederrière, J. Cariou, Y. Guern, B. Le Jeune, G. Le Brun, J. Lotrian, “Scattering through fluids: speckle size measurement and Monte Carlo simulations close to and into the multiple scattering”, Optics Express vol. 12, pp. 176-188, (2004).10.1364/OPEX.12.00017619471524
Open DOI Search in Google Scholar Back to article
15. Y. Piederriere, J. Le Meur, J. Cariou, J.F. Abgrall, M.T. Blouch, “Particle aggregation monitoring by speckle size measurement; application to blood platelets aggregation”, Optics Express, Vol. 12, pp. 4596-4601, (2004).10.1364/OPEX.12.004596
Open DOI Search in Google Scholar Back to article
16. D. Chicea, “Speckle size, intensity and contrast measurement application in micron-size particle concentration assessment”, European Physical Journal Applied Physics, Vol. 40, pp. 305-310, DOI: 10.1051/epjap:2007163 (2007).10.1051/epjap:2007163(2007)
Open DOI Search in Google Scholar Back to article
17. J.W. Goodman, “Laser speckle and related phenomena”, Topics in Applied Physics, Vol.9 , J.C. Dainty, Ed., Springer-Verlag, Berlin, Heidelberg, New York, Tokyo, (1984).
Search in Google Scholar Back to article
18. M. Giglio, M. Carpineti, A. Vailati and D. Brogioli, “Near-field intensity correlations of scattered light“, Applied Optics, Vol. 40,pp. 4036-4040, (2001).10.1364/AO.40.004036
Open DOI Search in Google Scholar Back to article
19. K. Gurney, “An Introduction to Neural Networks”,London: Routledge, ISBN 1-85728-673-1, (1997)10.4324/9780203451519
Search in Google Scholar Back to article
20. Haykin, S. Neural Networks: “A Comprehensive Foundation”, Prentice Hall, ISBN 0-13-273350-1, (1999)
Search in Google Scholar Back to article
21. V. V. Berdnik, R.D. Mukhamedjarov, V.A. Loiko, “Characterization of optically soft spheroidal particles by
Search in Google Scholar Back to article
multiangle light-scattering data by use of the neural-networks method”, Optics Letters, Vol. 29, No. 9, pp. 1019-1021, (2004).10.1364/OL.29.00101915143660
Search in Google Scholar Back to article
22. P. Kaye, E. Hirst, Z. Wang-Thomas, “Neural-network-based spatial light-scattering instrument for hazardous airborne fiber detection”, Applied Optics, Vol. 36, No. 24, pp. 6149-6156, (1997).10.1364/AO.36.00614918259463
Open DOI Search in Google Scholar Back to article
23. Z. Ulanowski, Z. Wang, P. Kaye, I.K. Ludlow, “Application of neural networks to the inverse light scattering problem for spheres”, Applied Optics, Vol. 37, No. 18, pp. 4027-4033, (1998).10.1364/AO.37.00402718273375
Search in Google Scholar Back to article
24. V.V. Berdnik, V.A. Loiko, “Retrieval of size and refractive index of spherical particles by multiangle light scattering: neural network method application”, Applied Optics, vol. 48, no. 32, pp. 6178-6187, (2009).10.1364/AO.48.00617819904314
Open DOI Search in Google Scholar Back to article
25. A.H. Carrieri, “Neural network pattern recognition by means of differential absorption Mueller matrix spectroscopy”, Applied Optics, vol. 38, no. 17, pp. 3759-3766, (1999).10.1364/AO.38.00375918319983
Search in Google Scholar Back to article
26. D. Chicea, “Probing magnetic fluid nanoparticle aggregation in aqueous suspensions by coherent light scattering anisotropy measurement”, Journal of Optoelectronics and Advanced Materials, vol. 12, no. 4, pp. 858-863, (2010).
Search in Google Scholar Back to article
27. D. Chicea, “A Study of Nanoparticle Aggregation by Coherent Light Scattering“, Current Nanoscience, vol. 8, no. 2, pp. 259-265, (2012).10.2174/157341312800167704
Search in Google Scholar Back to article
28. N.A. Clark, J.H. Lunacek, G.B. Benedek, “A study of Brownian motion using light scattering”, American Journal of Physics, vol. 38, no. 5, pp. 575-585, (1970).10.1119/1.1976408
Open DOI Search in Google Scholar Back to article
29. B. J. Berne, R. Pecora, Dynamic Light Scattering: With Applications to Chemistry, Biology, and Physics, John Willey, New York, (1976).
Search in Google Scholar Back to article
30. B. J. Berne, R. Pecora, Dynamic Light Scattering: With Applications to Chemistry, Biology, and Physics, Dover Publications, (2000).
Search in Google Scholar Back to article
31. D. Chicea, “Revealing Fe3O4 nanoparticles aggregation dynamics using dynamic light scattering, Optoelectronics and Advanced Materials-Rapid Communications, vol. 3, no. 12, pp. 1299-1305, (2009).
Search in Google Scholar Back to article
32. K. Levenberg, "A Method for the Solution of Certain Problems in Least Squares," Quart. Appl. Math., vol.2, pp. 164-168, (1944).10.1090/qam/10666
Open DOI Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.1515/aucts-2017-0020 | Journal eISSN: 2668-6449 | Journal ISSN: 1583-7149

Journal RSS Feed

Language: English

Page range: 155 - 161

Published on: Jan 11, 2018

Published by: Lucian Blaga University of Sibiu

In partnership with: Paradigm Publishing Services

Publication frequency: 1 issue per year

Keywords:

Dynamic Light Scattering,

Related subjects:

Electrical engineering,

Automation,

Mechanical engineering,

Production technology,

Process engineering and industrial engineering

© 2018 Silviu Rei, Dan Chicea, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 69 (2017): Issue 1 (December 2017)