Analysis of Soot Nanoparticles in a Laminar Premixed Ethylene Flame by Scanning Mobility Particle Sizer

Zhao, Bin; Yang, Zhiwei; Wang, Jinjin; Johnston, Murray V.; Wang, Hai

doi:10.1080/02786820300908

Cited by 184 publications

(136 citation statements)

References 16 publications

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“…The more recent studies of turbulent flames by Koylu and colleagues (Hu et al 2003(Hu et al , 2004Yang et al 2005) show the coexistence of the singlet spheroids and the carbonaceous aggregates and suggest that distributed particle nucleation occurs in these fuel-rich flames even in the presence of the larger soot aggregates. In this event, the particle size distribution (PSD) is clearly bimodal as has been found by the direct observations of laminar premixed flames (Zhao et al 2003;Öktem et al 2005).…”

Section: Precursor Nanoparticlesmentioning

confidence: 70%

“…However, micrographs from turbulent diffusion flames (Hu et al 2003(Hu et al , 2004Yang et al 2005) clearly show precursor nanoparticles in coexistence with mature aggregates. These images represent concrete evidence of a bimodal PSD that has been observed (Zhao et al 2003) in the premixed laminar flame using a scanning mobility particle sizer.…”

Section: Transformation Of Precursor Particles To Aggregatesmentioning

confidence: 99%

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Hydrocarbon Nanoparticles Formed in Flames and Diesel Engines

Dobbins

2007

Aerosol Science and Technology

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The formation of nanoparticles in laboratory hydrocarbon flames is reviewed in terms of particle morphology, chemical composition, and health hazards. The nascent nanoparticles in the nucleation mode have been widely reported in diverse laboratory flames, and are distinguished by their occurrence as singlet particles that form translucent images in transmission electron microscopy (TEM). Their sizes range from about 10 nm or more down to 2 to 3 nm, the limit of resolution of the TEM, and they possess a liquid-like quality. These particles are widely considered to be the precursor stage to the more readily observed carbonaceous aggregates consisting of chained primary particles that are opaque to the electron beam of the TEM. Nanoparticles sampled from the inverse diffusion flame and the particle effluent from diesel engines show a strong resemblance by GCMS analysis, and they contain many of the stabilomer PAHs and their isomers in the 200 to 302 atomic mass range. Many of these chemical species have high relative mutagenicities. Distinctive bimodal particle size distributions can be observed in both flame and engine samples. Recent TEM micrographs of diesel particulates show images of precursor-like nanoparticles, of as yet unknown chemical composition, that are formed in a diesel engine at many operating conditions.

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Section: Precursor Nanoparticlesmentioning

confidence: 70%

Section: Transformation Of Precursor Particles To Aggregatesmentioning

confidence: 99%

Hydrocarbon Nanoparticles Formed in Flames and Diesel Engines

Dobbins

2007

Aerosol Science and Technology

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“…2) over a range of flame temperature and C/O ratios, using previously established experimental methods and procedures [44,49,50]. A schematic of the experimental arrangement for performing particle sampling and analysis by either SMPS or thermal desorption mass spectrometry is shown in Fig.…”

Section: Flat Flame Measurementsmentioning

confidence: 99%

Understanding and predicting soot generation in turbulent non-premixed jet flames.

Wang

Kook²,

Doom³

et al. 2010

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This report documents the results of a project funded by DoD's Strategic Environmental Research and Development Program (SERDP) on the science behind development of predictive models for soot emission from gas turbine engines. Measurements of soot formation were performed in laminar flat premixed flames and turbulent non-premixed jet flames at 1 atm pressure and in turbulent liquid spray flames under representative conditions for takeoff in a gas turbine engine. The laminar flames and open jet flames used both ethylene and a prevaporized JP-8 surrogate fuel composed of n-dodecane and m-xylene. The pressurized turbulent jet flame measurements used the JP-8 surrogate fuel and compared its combustion and sooting characteristics to a world-average JP-8 fuel sample. The pressurized jet flame measurements demonstrated that the surrogate was representative of JP-8, with a somewhat higher tendency to soot formation. The premixed flame measurements revealed that flame temperature has a strong impact on the rate of soot nucleation and particle coagulation, but little sensitivity in the overall trends was found with different fuels. An extensive array of non-intrusive optical and laser-based measurements was performed in turbulent non-premixed jet flames established on specially designed piloted burners. Soot concentration data was collected throughout the flames, together with instantaneous images showing the relationship between soot and the OH radical and soot and PAH. A detailed chemical kinetic mechanism for ethylene combustion, including fuel-rich chemistry and benzene formation steps, was compiled, validated, and reduced. The reduced ethylene mechanism was incorporated into a high-fidelity LES code, together with a momentbased soot model and models for thermal radiation, to evaluate the ability of the chemistry and soot models to predict soot formation in the jet diffusion flame. The LES results highlight the importance of including an optically-thick radiation model to accurately predict gas temperatures and thus soot formation rates. When including such a radiation model, the LES model predicts mean soot concentrations within 30% in the ethylene jet flame. 3This page left intentionally blank.

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“…Nevertheless, the determination of primary particle size distribution by using these techniques implies to record many images and the postprocessing is essentially controlled and consequently long and fastidious. For various soot origins and statistics levels, some authors found that size distributions of D p follows a normal distribution (Equation (1a)) (K€ oyl€ u and Faeth 1992;Wentzel et al 2003;Lapuerta et al 2007;Ouf et al 2008) and others found lognormal distributions (Equation (1b)) (Maricq et al 2003;Zhao et al 2003b;Mitchell et al 2006;Zhao et al 2007).…”

Section: Introductionmentioning

confidence: 99%