Morphology and Raman Spectra of Engine-Emitted Particulates

Author: Soewono Arka   Rogak Steven  

Publisher: Taylor & Francis Ltd

ISSN: 1521-7388

Source: Aerosol Science and Technology, Vol.45, Iss.10, 2011-10, pp. : 1206-1216

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Abstract

The morphology and nanostructure of soot from different engines were studied. The soot samples were collected from a 1.9 L Volkswagen light-duty diesel (LDD) engine for two different fuel types [ultralow sulfur diesel (ULSD) and B20] and six speed/load combinations, as well as from a heavy-duty engine using a pilot-ignited high-pressure direct-injection (HPDI) natural-gas combustion system for three different speed/load combinations. Transmission electron microscopy (TEM) was employed to investigate the soot morphology by using alternative fractal measurement methods. The fractal dimensions (Df) were computed from the scaling of the projected aggregate dimensions with the number of primary particles (“LW” method) and two-dimensional pair correlation functions. For the soot collected from the LDD, it was found that the fractal dimensions are independent of fuel type, while a higher engine load slightly decreased Df. The soot produced by the HPDI exhibited a similar correlation between Df and engine load. The fractal dimension of the engine-emitted soot was measured in a range of 1.70-1.85 and the fractal prefactor kfLW of 1.08-1.39. Raman spectroscopy was used to characterize the soot nanostructure based on the degree of microstructural disorder. The Raman spectral analysis was done using two-band (“G” at ∼1578 and “D” at ∼1340 cm-1) and five-band (G, D1, D2, D3, and D4 at about 1580, 1350, 1500, 1620, and 1200 cm-1 respectively) combinations. For the soot sampled from the LDD, the results from both methods showed that B20 soot exhibited a greater structural disorder. Likewise, the Raman analysis of the soot from both engines also showed that the increase in engine load condition caused increases in the degree of the structural order of soot. The use of either D/G ratio or D1 width cannot distinguish between the HPDI and the LDD soot. However, on a plot of D/G versus D1, the data fall into distinct clusters. This may indicate the importance of using more than two spectral parameters to characterize the soot samples.

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