AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
The Effect of Sampler Design on Nanoparticle Sizing
EIRINI GOUDELI, Arto Groehn, Sotiris E. Pratsinis, ETH Zurich
Abstract Number: 116 Working Group: Combustion
Abstract The properties (e.g. transport, optical) and final product performance of nanoparticles made by gas-phase processes depend strongly on their composition, size and morphology. The size and structure of such particles that typically have fractal-like nature need to be closely controlled as they do not only find a score of applications (catalysts, sensors, biomaterials) that require well-defined characteristics but are also found in the atmosphere impacting health and climate. Measurements of aerosol characteristics, however, depend on the design of the sampling system as they change by deposition, coagulation and/or fragmentation in the sampling lines.
Here the effect of different sampler configurations (straight-tube and pinhole samplers of varying hole diameter and orientation) on real-time flame-made ZrO$_2 particle characterization (mobility size distribution and morphology-structure) is elucidated at fuel-rich and -lean flame conditions at 10 – 60 cm above the burner. The sampling system affects little the shape and spread of the mobility size distributions, but most importantly it affects the mean mobility size. All samplers in downstream orientation result in larger mobility diameters than in upstream or sidestream orientation, especially at fuel-lean spray flames.
In addition, the structure (fractal dimension, mass-mobility exponent) and size (radius of gyration, mobility and volume-equivalent radius) evolution from spherical to fractal-like particles formed by agglomeration in the absence of coalescence, sintering or surface growth is investigated by discrete element modeling simulations and is compared to the above online experimental results and literature data. The evolution of structure and quasi self-preserving number-based geometric standard deviation is quantified by simple relationships that can be readily used in detailed particle dynamics simulations coupled to fluid mechanics for industrial process design, air pollution, meteorology and climate dynamics.