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S. Radel, J. Schnöller, A. Dominguez, B. Lendl, M. Gröschl, E. Benes:
"Ultrasonic particle separation for improving SNR of RAMAN spectra from particles in suspension";
Poster: 2nd Europ. Conf. on Filtration and Separation, Compiègne /F; 12.10.2006 - 13.10.2006; in: "Proceedings of the 2nd Europ. Conf. on Filtration and Separation", (2006), ISBN 10: 2-913923-25-9, ISBN 13:978-2-913923-25-6; S. 449 - 454.

Ultrasonic separation techniques are based on the so-called acoustic radiation forces exerted on suspended particles within an ultrasonic standing wave in the megahertz frequency range. Among the systems employing the aggregation effects caused by sonication, acoustic cell filters are successfully applied in biotechnology.

In this work, an ultrasonic standing wave field of 2 MHz was used to concentrate particles in the light path of a confocal Raman microscope. Due to the increased spatial concentration of matter in the focus of the laser beam, an increase of the signal-to-noise ratio of the recorded Raman spectra of the particles was achieved.

The utilized biomodel suspensions of yeast cells are important, e.g., for on-line monitoring of bioprocesses. Spectra are presented taken by the Raman microscope pointing at cell aggregates induced by ultrasound. As an indication of feasibility, this data are compared to measurements taken when no means of concentration were at work and to measurements of dried yeast cells, respectively.

A further field of application was identified in the control of crystallisation processes with emphasis to discriminate polymorphs. Therefore, suspensions of theophylline crystals were investigated following a similar
protocol as with the yeast cells. Here, the data show significant differences in the spectroscopic feature structure between dried matter and crystals in contact with water. In addition, SNR is increased by several orders of magnitude.

Key words: ultrasound, Raman spectroscopy, optical measurement, ultrasonic particle separation

http://aleph.ub.tuwien.ac.at/F?base=tuw01&func=find-c&ccl_term=AC06588037