Automatic estimation of pressure-dependent rate coefficients

A general framework is presented for accurately and efficiently estimating the phenomenological pressure-dependent rate coefficients for reaction networks of arbitrary size and complexity using only high-pressure-limit information. Two aspects of this framework are discussed in detail. First, two methods of estimating the density of states of the species in the network are presented, including a new method based on characteristic functional group frequencies. Second, three methods of simplifying the full master equation model of the network to a single set of phenomenological rates are discussed, including a new method based on the reservoir state and pseudo-steady state approximations. Both sets of methods are evaluated in the context of the chemically-activated reaction of acetyl with oxygen. All three simplifications of the master equation are usually accurate, but each fails in certain situations, which are discussed. The new methods usually provide good accuracy at a computational cost appropriate for automated reaction mechanism generation.