Unimolecular Dissociation of C6H6-C6Cl6 Complex and Effect of Mode-Mode Coupling

On the intramolecular vibrational energy redistribution dynamics of aromatic complexes: A comparative study on C6H6-C6H5Cl, C6H6-C6H3Cl3, C6H6-C6Cl6 and C6H6-C6H5F, C6H6-C6H3F3, C6H6-C6F6

Chemical dynamics Simulation studies on benzene dimer (Bz2) and benzene-hexachlorobenzene (Bz-HCB) as performed in the past suggest that the coupling between the monomeric (intramolecular) vibrational modes and modes generated due to the association of two monomers (intermolecular) has to be neither strong nor weak for a fast dissociation of the complex. To find the optimum coupling, four complexes are taken into consideration in this work, namely, benzene-monofluorobenzene, benzene-monochlorobenzene, benzene-trifluorobenzene (Bz-TFB), and benzene-trichlorobenzene. Bz-TFB has the highest rate of dissociation among all seven complexes, including Bz2, Bz-HCB, and Bz-HFB (HFB stands for hexafluorobenzene). The set of vibrational frequencies of Bz-TFB is mainly the reason for this fast dissociation. The mass of chlorine in Bz-HCB is optimized to match its vibrational frequencies similar to those of Bz-TFB, and the dissociation of Bz-HCB becomes faster. The power spectrum of Bz-TFB, Bz-HCB, and Bz-HCB with the modified mass of chlorine is also computed to understand the extent of the said coupling in these complexes.

Unimolecular dissociation of C6H6-C6H5Cl, C6H6-C6H3Cl3, and C6H6-C6Cl6 complexes using machine learning approach

The application of Machine Learning (ML) algorithms in chemical sciences, particularly computational chemistry, is a vastly emerging area of modern research. While many applications of ML techniques have already been in place to use ML based potential energies in various dynamical simulation studies, specific applications are also being successfully tested. In this work, the ML algorithms are tested to calculate the unimolecular dissociation time of benzene-hexachlorobenzene, benzene-trichlorobenzene, and benzene-monochlorobenzene complexes. Three ML algorithms, namely, Decision-Tree-Regression (DTR), Multi-Layer Perceptron, and Support Vector Regression are considered. The algorithms are trained with simulated dissociation times as functions (attributes) of complexes' intramolecular and intermolecular vibrational energies. The simulation data are used for an excitation temperature of 1500 K. Considering that the converged result is obtained with 1500 trajectories, an ML algorithm trained with 700 simulation points provides the same dissociation rate constant within statistical uncertainty as obtained from the converged 1500 trajectory result. The DTR algorithm is also used to predict 1000 K simulation results using 1500 K simulation data.

An advanced bath model to simulate association followed by ensuing dissociation dynamics of benzene + benzene system: a comparative study of gas and condensed phase results

The role of the environment (N₂ molecules) on the association followed by the ensuing dissociation reaction of benzene + benzene system is studied here with the help of a new code setup. Chemical dynamics simulations are performed to investigate this reaction in vacuum as well as in a bath of 1000 N₂ molecules, equilibrated at 300 K. Bath densities of 20 and 324 kg m^-3 are considered with a few results from the latter density. The simulations are performed at three different excitation temperatures of benzene, namely, 1000, 1500, and 2000 K, with an impact parameter range of 0-12 Å for both vacuum and bath models. Higher association probabilities and hence, higher temperature dependent association rate constants are obtained in the condensed phase. In the condensed phase, when a trajectory takes a longer time for the monomers to associate, the associated complex is formed with a longer lifetime and provides a lower rate of ensuing dissociation. Higher association rate and lower dissociation rate in condensed phase dynamics are due to the energy transfer process. Hence, the energy transfer phenomenon plays a decisive role in the association/dissociation dynamics, which is completely ignored in the same reaction when studied in vacuum.

Dynamical Behavior of Aromatic Trimer Complexes in Unimolecular Dissociation Reaction at High Temperatures. Case Studies on C6H6-C6F6-C6H6 and C6H6 Trimer Complexes

The intramolecular vibrational energy redistribution (IVR) dynamics during unimolecular dissociation of aromatic trimers at high temperatures is the primary interest of this study. Chemical dynamics simulations are performed for the unimolecular dissociation of benzene-hexafluorobenzene-benzene (Bz-HFB-Bz) and benzene trimer (Bz-trimer) complexes at a temperature range of 1000-2000 K. Partial dissociation of both the complexes is observed, which leads to a dimer and a monomer in the dynamics. However, the probability of such dissociation was found much lower in the case of the Bz-trimer, which further decreases with the increase of temperature. The rate of partial dissociation of Bz-HFB-Bz is faster at 1500, 1800, and 2000 K, whereas the rate of complete dissociation of the Bz-trimer is significantly faster than Bz-HFB-Bz at all temperatures. This is just the opposite of the corresponding dimer's dissociation, where benzene-hexafluorobenzene (Bz-HFB) dissociates at a faster rate than the benzene dimer (Bz-dimer). Thus, the dissociation dynamics of the trimer is different than that of the dimer. Simulations with excited intramolecular and intermolecular modes of the trimer complexes reveal that energy flows from intermolecular to intramolecular modes of Bz-HFB-Bz more freely than the Bz-trimer, and the dissociation process becomes slower for the former. Calculated activation energies for both types of dynamics are much lower than the corresponding binding energies, which may be due to the anharmonicity. The Arrhenius equation with an anharmonic correction factor is considered to recalculate the activation energy and pre-exponential factor.