@PhdThesis{duepublico_mods_00074931,
  author = 	{Janbazi, Hossein},
  title = 	{Development of a chemical kinetics reaction mechanism for tetramethylsilane-doped flames and comprehensive thermochemistry of silanes and siloxanes},
  year = 	{2021},
  month = 	{Nov},
  day = 	{11},
  keywords = 	{Reaction mechanism development; Silica nanoparticle synthesis; Thermochemistry of organosilanes},
  abstract = 	{In this work, a comprehensive database for the thermodynamic properties of a large group of silicon-organic compounds is provided. A reaction mechanism is also developed for tetramethylsilane (TMS) as a precursor in the flame synthesis of silica nanoparticles. In the first part of this work, a combinatorial consideration is applied to derive group additivity values (GAVs) required to describe the thermochemistry of a large group of silicon-organic compounds. Due to a lack of experimental data for Si--C--H--O species, the thermochemistry of species is calculated by quantum chemical calculations. The theoretically calculated compounds are considered as a training set for the regression of GAVs. Based on the group additivity method, a multivariate linear regression analysis is performed. The regressed group additivity values serve as an alternative for the estimation of thermodynamic data of new silicon-organic compounds. The uncertainty of quantum chemical calculations, as well as the uncertainty of GAVs are discussed in this work. The final results are provided as databases. For the second part of this work, a kinetics model is developed for the decomposition and oxidation of TMS as a promising precursor for the flame synthesis of silica nanoparticles. The reaction mechanism is developed and validated based on the experimental data. The reaction pathways analysis and the sensitivity analysis are performed to the developed kinetics model. The sources of uncertainty and the possibility to improve the kinetics model are discussed. In this mechanism, reaction rate coefficients are either estimated via an algorithmic optimization procedure or are assumed based on analogies to similar reactions in the literature or calculated using Rice--Ramsperger--Kassel--Marcus theory (RRKM) theory. The genetic algorithm-based optimizer is also extended in this work.},
  doi = 	{10.17185/duepublico/74931},
  url = 	{https://duepublico2.uni-due.de/receive/duepublico_mods_00074931},
  url = 	{https://doi.org/10.17185/duepublico/74931},
  file = 	{:https://duepublico2.uni-due.de/servlets/MCRFileNodeServlet/duepublico_derivate_00074668/Diss_Janbazi.pdf:PDF},
  language = 	{en}
}