Molecular dynamic studies of melting of nitromethane have been carried out using two methods: (1) void-nucleated melting with the gradual heating of the lattice and (2) equilibration of coexisting liquid and solid phases. The results are in near agreement with each other; the small difference is attributed to the hysteresis effect associated with the direct heating process. The values of the melting temperature Tm computed by using the intermolecular interaction potential of Sorescu et al. [J. Phys. Chem. B 104, 8406 (2000)] are found to be in good agreement with the experimental data at various values of pressure ranging from 1 atm to 30 kbar. The computed values of the melting temperature satisfy the Simon–Glatzel equation P(kbar)=aTmb+c, where a=1.597×10−5, b=2.322, c=−6.74, and Tm is in kelvin. A comparison of computed Tm with and without the presence of molecular vibrations reveals that Tm is insensitive to the intramolecular interaction term of the potential energy function, but depends strongly on the intermolecular interactions, particularly the Coulombic term (i.e., the partial charges on atoms).

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The defect-nucleated melting of Ar has been simulated by the gradual heating of lattices that contain voids using isobaric molecular dynamics. The criterion given by Solca et al. [Chem. Phys. 224, 253 (1997)] has been used to determine the melting point from the transition temperature versus void size curve. A crystal containing a single void created by the removal of an atom and its nearest (n−1) neighboring atoms was found to give almost the same melting temperature as a crystal containing n randomly distributed single-atom voids. The melting temperature is insensitive to the shape of the void. The critical void size, beyond which there is a sudden drop in the melting temperature, decreases with pressure. At various values of pressures ranging from 0.094 to 531.6 kbar the melting points are found to be in good agreement with the experimental results and with thermodynamic results using the same exp-6 potential. The results are consistent with the Lindemann criterion of melting and in better agreement with the Lindemann criterion than are the thermodynamic results.

The neural network (NN) procedure to interpolate ab initio data for the purpose of molecular dynamics (MD) simulations has been tested on the SiO(2) system. Unlike other similar NN studies, here, we studied the dissociation of SiO(2) without the initial use of any empirical potential. During the dissociation of SiO(2) into Si+O or Si+O(2), the spin multiplicity of the system changes from singlet to triplet in the first reaction and from singlet to pentet in the second. This paper employs four potential surfaces. The first is a NN fit [NN(STP)] to a database comprising the lowest of the singlet, triplet, and pentet energies obtained from density functional calculations in 6673 nuclear configurations. The other three potential surfaces are obtained from NN fits to the singlet, triplet, and pentet-state energies. The dissociation dynamics on the singlet-state and NN(STP) surfaces are reported. The results obtained using the singlet surface correspond to those expected if the reaction were to occur adiabatically. The dynamics on the NN(STP) surface represent those expected if the reaction follows a minimum-energy pathway. This study on a small system demonstrates the application of NNs for MD studies using ab initio data when the spin multiplicity of the system changes during the dissociation process.

A previously reported method for conducting molecular dynamics simulations of gas-phase chemical dynamics on ab initio potential-energy surfaces using modified novelty sampling and feedforward neural networks is applied to the investigation of the unimolecular dissociation of vinyl bromide. The neural network is fitted to a database comprising the MP4(SDQ) energies computed for 71 969 nuclear configurations using an extended basis set. Dissociation rate coefficients and branching ratios at an internal excitation energy of 6.44 eV for all six open reaction channels are reported. The distribution of vibrational energy in HBr formed in three-center dissociation is computed and found to be in excellent accord with experimental measurements. Computational requirements for the electronic structure calculations, neural network training, and trajectory calculations are given. The weight and bias matrices required for implementation of the neural network potential are made available through the Supplementary Material.