Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published February 2020 | Supplemental Material
Journal Article Open

The Spider DMA: A miniature radial differential mobility analyzer


The Spider differential mobility analyzer (DMA) is a novel, miniaturized radial DMA developed to provide size classification in the 10–500 nm range for applications requiring high portability and time resolution. Its external dimensions are ∼12 cm in diameter by 6 cm in height (excluding tubing); it weighs ∼350 g, and is designed to operate at 0.6–1.5 L/min sheath and 0.3 L/min sample flowrates. It features a new sample inlet geometry that is designed to produce a uniform azimuthal particle distribution at the entrance of the classifier, optimized sample/sheath flow streams introduction in the classifier to minimize particle delays, and extension of the electric field interaction volume for ∼30% enhanced dynamic range. Based on three-dimensional finite element simulations of flows, electric fields, and particle trajectories, we demonstrate that the Spider DMA transfer functions can be predicted with high fidelity using a parameterized fit based on the Stolzenburg semi-analytical model. Experimental characterization of the instrument response with size-selected particles confirmed close agreement with model prediction; mobility size response is linear over three orders of magnitude in mobility span. Electrical ground shielding of the external surfaces of the DMA has been found to be necessary to avoid particle losses associated with field effects as the high voltage operating limit is approached. The mean deviation between the reference size of polystyrene latex spheres and the Spider DMA measurement is less than 2%, corroborating its high sizing precision and potential for high quality size distribution measurements.

Additional Information

© 2019 American Association for Aerosol Research. Received 02 Mar 2019, Accepted 26 May 2019, Accepted author version posted online: 07 Jun 2019, Published online: 19 Jun 2019. The authors would like to thank Dr. Huajun Mai for helpful discussions and assistance in preparation of the experimental data acquisition software. This research was supported by the Small Business Innovative Research and Small Business Technology Transfer Department of Energy Research Grant No. DE-SC0013152.

Attached Files

Supplemental Material - uast_a_1626974_sm7768.pdf


Files (1.4 MB)
Name Size Download all
1.4 MB Preview Download

Additional details

August 19, 2023
October 20, 2023