Skip to main content

Open Access Performance Evaluation of a Fiber Length Classifier

Download Article:
A performance evaluation was conducted on a differential mobility classifier that separates fibers according to length using dielectrophoresis. The classifier had been constructed and used for several applications in previous studies. The performance of the classifier was predicted using a two-dimensional axisymmetric model of the flow field and then calculating particle trajectories for a variety of conditions. Based on the flow calculations, several regions of the classifier were improved to reduce likelihood of turbulent losses. For a given total flow through the classifier and a maximum voltage across the electrodes, the performance of the classifier was found to depend on the ratios of the aerosol flow to the inner and the outer sheath flows. It was found that the minimum classifiable length, the minimum length distribution width, and the throughput of classified fibers can each be optimized, but not independently. Several approaches to testing the resolution of the classifier were tried. The first was to measure the length distribution of fibers passing through the classifier under different conditions using electron microscopy. However, this was a slow and imprecise measure of performance. Two approaches using monodisperse latex spheres were used; one operated the instrument as an electrical mobility (electrophoresis) analyzer and the other evaluated only the flow system accuracy. All measures indicate that the classifier operates close to theoretical performance, but improvements are still possible. Suggested improvements require redesign of the flow system and improved electrode alignment.

13 References.

No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Publication date: 1999-05-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more