Molecular dynamics investigations of the dissociation of SiO2 on an ab initio potential energy surface obtained using neural network methods

Abstract

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.

Oxidative Reactions of Silicon Atoms and Clusters at Ultralow Temperature in Helium Droplets

“…The dissociation of the SiO 2 molecule to SiO and O requires an energy of about 94.3 kcal mol -1 . 19 Thus, in the case of a fast dissipation of the reaction energy, the dissociation will not occur. In this case, the liquid helium environment stabilizes the intermediate reaction product, SiOO, and prevents this molecule from fragmentation.…”

“…19 Even the smaller reaction energy (52.9 kcal mol -1 ) would result in the evaporation of approximately 3500 He atoms. Thus, the reaction energy is capable of completely evaporating a small He droplet.…”

Molecular dynamics investigations of chlorine peroxide dissociation on a neural network ab initio potential energy surface

“…Malshe et al [55] have demonstrated a typical study of the vinyl bromide system, in which nearly 72,000 data points were sampled, and a two-layer NN was employed to fit the PES. This approach has been further employed to investigate the reaction dynamics of SiO 2 [56], HONO [57], HOOH [58], BeH 3 [59], and O 3 [60] systems. The fitting algorithm has been improved by allowing both energies and forces (energy gradient) to be fitted, and this new application was performed in an illustrative study of H ?…”

“…The PES construction requires an efficient sampling procedure [55][56][57]65] to sufficiently select data points from the multi-dimensional hyperspace. A particular construction of the NN PES perhaps requires more configurations to be selected than the other PES fitting methods.…”

A Full-Dimensional Neural Network Potential-Energy Surface for Water Clusters up to the Hexamer

“…NNs have been used for about two decades to construct PESs for a number of different systems and several reviews have been published [22][23][24][25]. Most of these NN potentials, however, are restricted to small molecules [26][27][28][29][30][31][32] or small molecules interacting with frozen metal surfaces [33][34][35][36][37][38]. Only a few potentials for higher-dimensional systems exist, which aim to describe the properties of solids [39,40].…”