Deep machine learning interatomic potential for liquid silica.

The use of machine learning to develop neural network potentials (NNP) representing the interatomic potential energy surface allows us to achieve an optimal balance between accuracy and efficiency in computer simulation of materials. A key point in developing such potentials is the preparation of a training dataset of ab initio trajectories. Here we apply a deep potential molecular dynamics (DeePMD) approach to develop NNP for silica, which is the representative glassformer widely used as a model system for simulating network-forming liquids and glasses. We show that the use of a relatively small training dataset of high-temperature ab initio configurations is enough to fabricate NNP, which describes well both structural and dynamical properties of liquid silica. In particular, we calculate the pair correlation functions, angular distribution function, velocity autocorrelation functions, vibrational density of states, and mean-square displacement and reveal a close agreement with ab initio data. We show that NNP allows us to expand significantly the time-space scales achievable in simulations and thus calculating dynamical and transport properties with more accuracy than that for ab initio methods. We find that developed NNP allows us to describe the structure of the glassy silica with satisfactory accuracy even though no low-temperature configurations were included in the training procedure. The results obtained open up prospects for simulating structural and dynamical properties of liquids and glasses via NNP.

Low-temperature decomposition and segregation on a surface in carbide-containing solid solutions of the zirconium-niobium-carbon system and in related ternary systems.

The crystal structure and microstructure of pseudobinary (ZrC0.96)1-x(NbC0.97)x carbide solid solutions has been studied. It was found that monocrystalline grains of zirconium carbide are spontaneously isolated on the surface of diluted solid solutions of the pseudobinary system ZrCy-NbCy' containing less than 2.0 mol% of zirconium carbide. It is shown that the appearance of zirconium carbide is a consequence of the solid-phase decomposition of these solid solutions and anisotropy of elastic properties of monocrystalline ZrC carbide grains. The model of subregular solutions was used in the temperature interval from 300 to 3900 K to calculate and plot an equilibrium phase diagram of the ternary Zr-Nb-C system. It is shown that at temperatures above 1210 K in the Zr-Nb-C ternary system, nonstoichiometric carbides ZrCy and NbCy' have unlimited mutual solubility and form a continuous series of (ZrCy)1-x(NbCy')x solid solutions with 0.6 ≤ y ≤ 0.98, 0.7 ≤ y' ≤ 1.0, and 0 ≤ x ≤ 1.0. At temperatures below 1200 K, under equilibrium conditions, a discontinuity of the miscibility of the solid solutions ZrCy-NbCy' is observed and there appears a region of solid phase decomposition. The anisotropy of elastic properties of monocrystalline grains of ZrC was considered. It is predicted that solid-phase decomposition and surface segregation can be observed in such related carbide systems as HfCy-NbCy', HfCy-TaCy', ZrCy-TaCy', VCy-TaCy' and VCy-NbCy'.