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Modeling of velocities and temperatures processes distribution in the plasma-forming channel determining the design features and optimal parameters of the plasma torch nozzle is one of promising directions in development of plasma technologies. The aim of this work was to simulate the processes of velocities and temperature distribution in the plasma-forming channel and to determine the design features and optimal geometric parameters of the plasmatron nozzle  which  ensures  the  formation  of  necessary  direction  of  plasma  flows for generation of surface waves on the surface of a liquid metal droplet under the influence of the investigated instabilities.One of the main tasks is to consider the process of plasma jet formation and the flow of electric arc plasma. For obtaining small-sized particles one of the main parameters is the plasma flow  velocity.  It  is necessary that the plasma outflow velocity be close to supersonic. An increase of  the  supersonic  speed  is possible due to design of the plasmatron nozzle especially the design feature and dimensions of the gas channel in which the plasma is formed. Also the modeling took into account dimensions of the plasma torch nozzle, i. e. the device should provide a supersonic plasma flow with the smallest possible geometric dimensions.As a result models of velocities and temperatures distribution in the plasma-forming channel at the minimum and maximum diameters of the channel were obtained. The design features and optimal geometric parameters of the plasmatron have been determined: the inlet diameter is 3 mm, the outlet diameter is 2 mm.The design of the executive equipment has been developed and designed which implements the investigated process of generating droplets of the micro- and nanoscale range. A plasmatron nozzle was manufactured which forms the necessary directions of plasma flows for the formation of surface waves on the metal droplet surface under the influence of instabilities. An algorithm has been developed for controlling of executive equipment that implements the process of generating drops of micro- and nanoscale range.

Addition of nanopowders of tungsten and aluminum oxyhydroxide to the weld pool has shown positive effect on the structure of metal during arc gas welding with a consumable electrode. It has been shown that introducing the powders decreases dendrite size and leads to the formation of a more equilibrium micrоstructure.

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We propose a hierarchical normalizing flow model for generating molecular graphs. The model produces new molecular structures from a single-node graph by recursively splitting every node into two. All operations are invertible and can be used as plug-and-play modules. The hierarchical nature of the latent codes allows for precise changes in the resulting graph: perturbations in the top layer cause global structural changes, while perturbations in the consequent layers change the resulting molecule marginally. The proposed model outperforms existing generative graph models on the distribution learning task. We also show successful experiments on global and constrained optimization of chemical properties using latent codes of the model.

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