A unifying picture of gas-phase formation and growth of PAH (Polycyclic Aromatic Hydrocarbons), soot, diamond and graphite

A variety of seemingly different carbon formation processes -- polycyclic aromatic hydrocarbons and diamond in the interstellar medium, soot in hydrocarbon flames, graphite and diamond in plasma-assisted-chemical vapor deposition reactors -- may all have closely related underlying chemical reaction mechanisms. Two distinct mechanisms for gas-phase carbon growth are discussed. At high temperatures it proceeds via the formation of carbon clusters. At lower temperatures it follows a polymerization-type kinetic sequence of chemical reactions of acetylene addition to a radical, and reactivation of the resultant species through H-abstraction by a hydrogen atom

PAH formation in carbon-rich circumstellar envelopes

While there is growing observational evidence that some fraction of interstellar carbon is in polycyclic aromatic hydrocarbons (PAH's), the mechanisms by which these molecules might be formed have not been extensively studied. A detailed investigation of PAH production in the outflowing molecular envelopes of carbon-rich red giant star is presented. The gasphase kinetics of a chemical reaction mechanism developed to study soot production in hydrocarbon flames is modified to apply in circumstellar environments. It was found that astrophysically significant quantities of PAH's can be formed in carbon star envelopes provided the gas is sufficiently dense and resides for a long time in the temperature range of 900 to 1100 k. The precise yield of PAH's is very sensitive to astronomical parameters of the envelope (e.g., mass loss rate, outflow velocity, and acetylene abundance) and certain poorly determined chemical reaction rates

Diagnostics of Data-Driven Models: Uncertainty Quantification of PM7 Semi-Empirical Quantum Chemical Method.

We report an evaluation of a semi-empirical quantum chemical method PM7 from the perspective of uncertainty quantification. Specifically, we apply Bound-to-Bound Data Collaboration, an uncertainty quantification framework, to characterize (a) variability of PM7 model parameter values consistent with the uncertainty in the training data and (b) uncertainty propagation from the training data to the model predictions. Experimental heats of formation of a homologous series of linear alkanes are used as the property of interest. The training data are chemically accurate, i.e., they have very low uncertainty by the standards of computational chemistry. The analysis does not find evidence of PM7 consistency with the entire data set considered as no single set of parameter values is found that captures the experimental uncertainties of all training data. A set of parameter values for PM7 was able to capture the training data within ±1 kcal/mol, but not to the smaller level of uncertainty in the reported data. Nevertheless, PM7 was found to be consistent for subsets of the training data. In such cases, uncertainty propagation from the chemically accurate training data to the predicted values preserves error within bounds of chemical accuracy if predictions are made for the molecules of comparable size. Otherwise, the error grows linearly with the relative size of the molecules

Particle aggregation with simultaneous surface growth

Particle aggregation with simultaneous surface growth was modeled using a dynamic Monte Carlo method. The Monte Carlo algorithm begins in the particle inception zone and constructs aggregates via ensemble-averaged collisions between spheres and deposition of gaseous species on the sphere surfaces. Simulations were conducted using four scenarios. The first, referred to as scenario 0, is used as a benchmark and simulates aggregation in the absence of surface growth. Scenario 1 forces all balls to grow at a uniform rate while scenario 2 only permits them to grow once they have collided and stuck to each other. The last one is a test scenario constructed to confirm conclusions drawn from scenarios 0-2. The transition between the coalescent and the fully-developed fractal aggregation regimes is investigated using shape descriptors to quantify particle geometry. They are used to define the transition between the coalescent and fractal growth regimes. The simulations demonstrate that the morphology of aggregating particles is intimately related to both the surface deposition and particle nucleation rates