Oxidative Aromatization of 4,7-Dihydro-6-nitroazolo[1,5-a]pyrimidines: Synthetic Possibilities and Limitations, Mechanism of Destruction, and the Theoretical and Experimental Substantiation.

The reaction tolerance of the multicomponent process between 3-aminoazoles, 1-morpholino-2-nitroalkenes, and aldehydes was studied. The main patterns of this reaction have been established. Conditions for the oxidation of 4,7-dihydro-6-nitroazolo[1,5-a]pyrimidines were selected.

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.

Ab initio molecular dynamics and high-dimensional neural network potential study of VZrNbHfTa melt.

The structural and dynamics properties of melts are directly related to their solidification processes, and consequently to the properties of as-cast solid alloys. Ab initio molecular dynamics (AIMD) is a powerful tool that can study both of these factors. However, the main disadvantage of this method is its low performance which is critical for simulation of the multicomponent liquids.