Actions for Electron Microscopic and Spectroscopic Characterization for Soot Source Differentiation by Laser Derivatization

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Electron Microscopic and Spectroscopic Characterization for Soot Source Differentiation by Laser Derivatization

Author
Gaddam, Chethan K.
Published
[University Park, Pennsylvania] : Pennsylvania State University, 2015.
Physical Description
1 electronic document
Additional Creators
Vander Wal, R. (Randy L.)
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Open Access.
Summary
Combustion produced soot is highly variable with nanostructure and chemistry dependent upon combustion conditions and fuel. Previous studies have shown soot nanostructure to be dependent upon the source via quantification of high-resolution transmission electron microscopy (HRTEM) images for nanostructural parameters. In principle this permits identification of the soot source and its contribution to any particular receptor site. Yet many structural aspects are subtle, and the chemistry of lamellae is unaddressed for reasons of poorly resolved or differentiated nanostructure and insufficient sample quantity for traditional analytical methods. This characterization gap then leads to the formative question prompting this study: how best to bring out small differences in nanostructure and other seemingly subtle differences in chemistry? A process of pulsed laser annealing is proposed to highlight compositional and structural differences thereby distinctively and uniquely identifying the source of the soot. The operative premise being that small variations in nanostructure and unresolved differences in chemistry exist and are specific to the particular combustion process. The overall goal is then to develop the laser-based heating as an analytical tool by identifying the process conditions and operational parameters for optimal derivatization. Specific objectives directed towards achieving this goal include: 1)Identifying optimal laser operational parameters for derivatization. 2)Defining the dependence upon nanostructure and molecular composition using model soots while also identifying variability and range of outcomes. 3)Demonstrating differentiation upon combustion derived soots from real engines, e.g. diesel, gasoline, gas-turbines, combustors, etc.4)Applying image processing algorithms to the laser heated soots to quantify and differentiate the transformed carbon nanostructures.For laser derivatization, a sample-housing chamber was custom built using a commercial optical grade quartz tube. Depending on the sample quantity, two different sample support systems were designed. Soot was laser-heated while in an inert (Ar) atmosphere using a pulsed Nd:YAG laser operating at 1064 nm. A laser beam dimension of ca 9 mm in diameter ensured that the entire sample area received uniform irradiation. To identify the optimal laser fluence, pulsed laser heating was applied at three different laser fluences to three carbon samples. Laser heating at these short timescales produced partially graphitized structures comprised of extended graphitic layers (>1 nm), and voids as material is rearranged. While laser heating the material with additional pulses did further graphitize the material, multiple pulses were not particularly beneficial for laser derivatization as this repetitive exposure decreased the degree of differentiation between the test samples. Based on visual HRTEM observations and quantified fringe analysis, a single pulse laser fluence of 250 mJ/cm2 (~2800 K, determined from multi-wavelength pyrommetry) produced the best derivatization without causing fragmentation or material ablation. For demonstrating the uniqueness of the laser-derivatized (nano)structure as dependent upon source and combustion conditions, the laser derivatization technique was validated by comparing different synthetic carbons, selected soots from transportation and residential combustion sources, and laboratory flames, each with recognizable nanostructure. After laser heating, the direction of nanostructure evolution of the synthetic carbons (possessing C:H > 10:1) appeared to be governed by their initial nanostructure as shown by HRTEM images. As illustration of chemistry's role, though nascent R250 carbon black showed structural similarity across multiple particles, laser heating led to either hollow shells or particles with internal structures. These differences were attributed to the chemistry of construction, i.e., the sp2/sp3 bonding as quantified by electron energy loss spectroscopy (EELS), showing significant differences between particles as large as 60%. The nanostructure of soots from different transportation sources (such as diesel, jet and gasoline engines) evolved distinctively upon laser annealing. Laser derivatization of soot collected from same platform (engine-type) revealed that fuel commonality leads to similar nanostructure for the same class of combustion source, whereas, fuel dependence and ensuing chemistry differences were prominently illustrated by comparison of laser-annealed soots originating from ultra-low sulfur diesel (ULSD) and an oxygenated fuel blend. The origin for this dependence was identified by X-ray photoelectron spectroscopy (XPS), revealing a significantly lower sp2/sp3 carbon bonding for the oxygenated fuels compared to their pure hydrocarbon fuels. As another example, laser annealing of residential boiler soot produced highly intertwined lamellae; this was attributed to inherent chemistry differences relative to the biodiesel (B100) soot that similarly lacked recognizable nanostructure. These observations suggest that the initial soot nanostructure in conjunction with the chemistry of construction governs the material transformation under pulsed laser annealing. Image processing algorithms were applied to quantify and differentiate the carbon nanostructural changes after laser annealing. A "recognition key" approach using a combination of present quantification algorithms: 1) fringe analysis, 2) stacking distribution, and 3) void dimension was reported for two laser-heated carbons, as examples. A second, method, using the radial intensity profile generated from the Fourier-Transformed bright field image was implemented to identify soot source upon laser derivatization against a reference set of values in a database. This semi-automated analytical method involves conversion of HRTEM images into the frequency domain, band-pass filtering, radial intensity profiling, and identification by least squares comparison with an empirically set limit for the sum of residuals. To illustrate the analytical methodology for source identification, a mixture of three soots was analyzed by laser derivatization. Laser heating led to visual differences; further quantification and comparison to the database identified the respective sources.
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Dissertation Note
Ph.D. Pennsylvania State University 2015.
Reproduction Note
Microfilm (positive). 1 reel ; 35 mm. (University Microfilms 10-666493)
Technical Details
The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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