Efficiency of Various Devices and Theories to Collect Nanoparticles Directly onto

Colorado State University, Fort Collins CO

Investigators

Abstract

DESCRIPTION (provided by applicant): Transmission electron microscope (TEM) is a very useful technique for evaluating nanoparticle morphology, for elemental analysis, and for particle counting and sizing. This technique has recently become a required tool to characterize exposure to airborne nanoparticles. The specific aim of this proposed research is to compare the available methods using TEM diffusive sampler (TDS), electrostatic precipitation sampler (EPS) and thermophoretic sampler (TPS) for directly depositing airborne engineered nanoparticles (ENPs) onto grids for material characterization. Research objectives include: comparison of size distributions, deposition uniformity and the ease of use. Test nanoparticle aerosols will be generated and samples will be collected side-by-side with three devices using each method, along with the NanoScan SMPS (TSI Model 3910, 10-420 nm) and Optical Particle Counter (OPC) (TSI Model 3330, 300 nm- 10 ?m) to record the particle concentration. Experiments will be performed in the Birck Nanotechnology cleanroom laboratory at Purdue University. This research will test the following hypotheses: (1) Basic aerosol theory can be used to predict particle collection onto TEM grids; (2)TPS is more efficient than TDS and EPS for collecting particles less than 200 nm directly onto a TEM grid, EPS is more efficient than TPS and TDS for collecting particles from 200 nm - 10 ?m, and none of the techniques are efficient at collecting particles larger than 1 ?m; and (3) Nanoparticles collected by all three mechanisms are randomly distributed across a grid surface. The results from this research will provide informative technical results to develop the adequate use of samplers for collecting nanoparticles. In addition, the results will provide the input for further modifications to existin samplers or the development of a newly-designed sampler which can provide better performance for future research.