• English
  • Deutsch
  • Log In
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Optical fiber based light scattering detection in microfluidic droplets
 
  • Details
  • Full
Options
2019
  • Konferenzbeitrag

Titel

Optical fiber based light scattering detection in microfluidic droplets

Abstract
Droplet based microfluidic technology is a miniaturized platform for microbial analysis on picoliter scale. With its costefficiency, high-throughput and feasibility of complex handling protocols, droplet microfluidics is a favorable platform for applications such as microorganism screening or synthetic biology. Scattered-light-based microbial detection, in comparison to the widely used fluorescent-label-based approach, provides a contact-free and label-free, yet sensitive measuring solution. The angular dependency of scattered light delivers an elaborate information about the morphology and the physical properties, e.g. size and refractive index, of microbial samples. Due to the complexity and ambiguity of the droplet contents, an angle resolved scattered light detection system could provide powerful method for a label-free identification and quantification of the microbes in droplets. In this paper, a novel approach of light scattering measurement in Polydimethylsiloxane (PDMS) microfluidic chips is presented, engaging optical fibers for a light-scattering-based on-chip microbial detection. Optical fibers, with their fast readout and compact size, are very suitable for easier system integration towards flexible and versatile lab-on-a-chip applications.
Author(s)
Wohlfeil, S.
Hengoju, S.
Munser, A.S.
Tovar, M.
Shvydkiv, O.
Roth, M.
Schröder, S.
Beckert, E.
Eberhardt, R.
Tünnerman, A.
Hauptwerk
Microfluidics, BioMEMS, and Medical Microsystems XVII
Konferenz
Biophotonics, Biomedical Optics, and Imaging Conference (BIOS) 2019
Photonics West Conference 2019
Thumbnail Image
DOI
10.1117/12.2509248
Language
Englisch
google-scholar
IOF
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022