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Suppression or reduction of soot emissions is an important goal in the development of automotive engines for environmental and human health purposes. A better understanding at the molecular level of the formation process of soot particles resulting from collision and aggregation of smaller particles made of Polycyclic Aromatic Hydrocarbon (PAH) is needed. In addition to experiments, computational methods are efficient and valuable tools for this purpose. As a first step in our detailed computational chemistry study, we applied Ultra-Accelerated Molecular Dynamics (UAQCMD) and Canonical Monte-Carlo (CMC) methods to investigate the nucleation process. The UA-QCMD can calculate chemical reaction dynamics 107 times faster than conventional first principle molecular dynamics methods, while CMC can calculate equilibrium properties at various temperatures, pressures, and chemical compositions.

Effects of measurement method, coolant temperature and fuel composition on soot emissions were examined by engine experiments. By reducing the pressure fluctuation in the sampling line, the measured soot emissions with better stability and reproducibility could be obtained. With lower coolant temperatures, larger soot emissions were yielded at much advanced fuel injection timings. Compared to gasoline, soot emissions with a blend fuel of normal heptane, isooctane and toluene were significantly decreased, suggesting the amounts of aromatic components (toluene or others) should be increased to obtain a representative fuel for the predictive model of particulate matter in SIDI engines.