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Aerosol classification by dielectrophoresis: a theoretical study on spherical particles.
Lorenz, Malte; Weber, Alfred P; Baune, Michael; Thöming, Jorg; Pesch, Georg R.
Afiliação
  • Lorenz M; Faculty of Production Engineering, Chemical Process Engineering (CVT), University of Bremen, Bremen, Germany.
  • Weber AP; Institute of Particle Technology, Clausthal University of Technology, Clausthal-Zellerfeld, Germany.
  • Baune M; Faculty of Production Engineering, Chemical Process Engineering (CVT), University of Bremen, Bremen, Germany.
  • Thöming J; Faculty of Production Engineering, Chemical Process Engineering (CVT), University of Bremen, Bremen, Germany.
  • Pesch GR; MAPEX Center for Materials and Processes, University of Bremen, Bremen, Germany.
Sci Rep ; 10(1): 10617, 2020 Jun 30.
Article em En | MEDLINE | ID: mdl-32606445
ABSTRACT
The possibilities and limitations using dielectrophoresis (DEP) for the dry classification of spherical aerosol particles was evaluated at low concentrations in a theoretical study. For an instrument with the geometry of concentric cylinders (similar to cylindrical DMA), the dependencies of target particle diameter [Formula see text], resolution, and yield of the DEP classification on residence time, applied electric field strength, and pressure of the carrier gas were investigated. Further, the diffusion influence on the classification was considered. It was found that [Formula see text] scales with the mean gas flow velocity [Formula see text], classifier length L, and electric field strength E as [Formula see text]. The resolution of the classification depends on the particle diameter and scales proportionally to [Formula see text]. It is constrained by the flow ratio [Formula see text] (i.e., sheath gas to aerosol flow), electrode diameters, and applied electric field strength. The classification yield increases with the ratio of the width of the extended outlet slit [Formula see text] to the diffusion induced broadening [Formula see text]. As expected, resolution and yield exhibit opposite dependencies on [Formula see text]. Our simulations show that DEP classification can principally cover a highly interesting particle size range from 100 nm to [Formula see text] while being directly particle size-selective and particle charge independent.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article