Stochastic Simulation of Carbonaceous Nanoparticle Precursor Formation in Combustion.
dc.contributor.author | Lai, Jason Yue Wai | en_US |
dc.date.accessioned | 2014-06-02T18:14:45Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2014-06-02T18:14:45Z | |
dc.date.issued | 2014 | en_US |
dc.date.submitted | 2014 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/107094 | |
dc.description.abstract | Combustion-generated nanoparticles (diameter less than or equal to 100 nm) are prevalent in modern society. Carbonaceous nanoparticles (CNPs) are especially important, finding applications as pigments in ink, in composite materials, or as catalysts. Despite such useful applications, CNPs have attracted the most attention as hazardous emissions from combustion sources like automotive engines, especially as aggregate particles known as soot, as their primary constituents are carcinogenic polycyclic aromatic hydrocarbons (PAHs). Critically, the formation of CNPs in combustion environments remains an area of considerable uncertainty, particularly the growth from gas phase precursors through the nucleation of solid phase particles. Towards elucidating PAH formation via chemical reactions, a significant element of the growth process, a novel simulation software was developed, named the Stochastic Nanoparticle Simulator (SNAPS), along with a corresponding PAH chemical reaction mechanism. This software was then applied to investigate the chemical and physical properties of PAHs formed in combustion. SNAPS simulations were corroborated through comparisons with existing experimental measurements in flames utilizing a variety of fuels. Furthermore, simulations provided molecular-level detail that revealed key aspects of a complex chemical growth process. Importantly, these simulations provided insights into chemical reaction and composition details beyond those typically inaccessible by experiment. For all studied flames, analysis of the major chemical reactions and PAH species involved in simulations contrasted with conventional theories. Simulations showed that PAH growth is characterized by complex sequences of highly reversible reactions, leading to a variety of species that far exceeds the relatively narrow range that has traditionally been the focus of investigations. SNAPS therefore represents an important tool for synthesizing experimental observations and theoretical predictions, towards building a comprehensive and accurate description of CNP growth. Most importantly, the current work is only one application of the software. The extensibility of SNAPS will enable modeling of many different systems involving heterogeneous nucleation and growth of nanoparticles, which illustrates its potential for wide impact. Altogether, this work represents a strong framework that will support and drive future investigations of nanoparticle growth and contribute to the development of novel combustion technologies that will positively impact society. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Stochastic Simulation | en_US |
dc.subject | Carbonaceous Nanoparticles | en_US |
dc.subject | Chemical Kinetics | en_US |
dc.subject | Soot | en_US |
dc.subject | Polycyclic Aromatic Hydrocarbons | en_US |
dc.subject | Nucleation | en_US |
dc.title | Stochastic Simulation of Carbonaceous Nanoparticle Precursor Formation in Combustion. | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Mechanical Engineering | en_US |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | en_US |
dc.contributor.committeemember | Violi, Angela | en_US |
dc.contributor.committeemember | Barker, John R. | en_US |
dc.contributor.committeemember | Atreya, Arvind | en_US |
dc.contributor.committeemember | Boehman, Andre L. | en_US |
dc.contributor.committeemember | Elvati, Paolo | en_US |
dc.subject.hlbsecondlevel | Chemical Engineering | en_US |
dc.subject.hlbsecondlevel | Mechanical Engineering | en_US |
dc.subject.hlbsecondlevel | Chemistry | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/107094/1/jasonlai_1.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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