Machine-learning Driven Synthesis of TiZrNbHfTaC5 High-Entropy Carbide

Synthesis of high-entropy carbides (HEC) requires high temperatures that can be provided by electric arc plasma method. However, the formation temperature of a single-phase sample remains unknown. Moreover, under some temperatures multi-phase structures can emerge. In this work we developed an approach for a controllable synthesis of HEC TiZrNbHfTaC5 based on theoretical and experimental techniques. We used canonical Monte Carlo (CMC) simulations with the machine learning interatomic potentials to determine the temperature conditions for the formation of single-phase and multi-phase samples. In full agreement with the theory, the single-phase sample, produced with electric arc discharge, was observed at 2000 K. Below 1200 K the sample decomposed into (Ti-Nb-Ta)C and a mixture of (Zr-Hf-Ta)C, (Zr-Nb-Hf)C, (Zr-Nb)C, and (Zr-Ta)C. Our results demonstrate the conditions for the formation of HEC and we anticipate that our approach can pave the way towards targeted synthesis of multicomponent materials.Comment: 16 pages, 8 figure

Influence of anionic surfactant on stability of nanoparticles in aqueous solutions

Dispersion and aggregation of nanoparticles in aqueous solutions are important factors for safe and effective application of nanoparticles, for instance, in the oil industry. As conventional oil reserves are depleted, it is necessary to advance chemical enhanced oil recovery (cEOR) techniques to develop unconventional oil reservoirs. Nanoparticles modified by surfactants can be a promising reagent in cEOR. These nanomaterials can reduce interfacial tension and change the wettability of reservoir rock, which leads to an increase in oil recovery. However, the application of nanoparticles is limited by their substantial aggregation in aqueous solutions. The purpose of this work is to select nanoparticles for obtaining stable sols in water in the presence of an anionic surfactant and to optimize the conditions (pH) for further modifying the nanoparticles with the anionic surfactant. Sodium dodecyl sulfate (SDS) is used as an anionic surfactant. The aggregation of oxide and carbon nanoparticles in water and anionic surfactant solutions was studied by laser diffraction, dynamic and electrophoretic light scattering methods. Most of the studied nanoparticles in water form aggregates with bi-, three- and polymodal particle size distributions. TiO2 nanoparticles obtained by plasma dynamic synthesis form the most stable sols in anionic surfactant solutions. The range of 5–7 pH is defined as optimal for their modification with surfactants. The stability of carbon nanoparticles in aqueous solutions increases significantly in the presence of a surfactant. The obtained results form the basis for further research on the modification of marked nanoparticles in surfactant solutions

Influence of non-vacuum electric arc synthesis energy on the product of tungsten ore concentrate processing

Relevance. Caused by the problem of developing methods for obtaining tungsten carbide, especially from tungsten-containing waste. As a solution, a non-vacuum electric arc method is proposed. It is easy to operate and cheap compared to a direct analogue (arc discharge method in inert gas atmosphere). The resulting product can be used as a catalyst carrier in hydrogen production reactions. Aim. To determine the current and the energy entered in the system, necessary to obtain a product with a largest proportion of the hexagonal phase of tungsten carbide WC from tungsten ore concentrate by a non-vacuum electric arc method and investigate a sample with the largest proportion of tungsten carbide phase. Object. Electric arc synthesis in open air from tungsten ore concentrate. Methods. Grinding in a SAMPLE SPEX 8000M ball mill, magnetic separation, non-vacuum electric arc method of synthesis, X-ray phase analysis on a Shimadzu XRD 7000s X-ray diffractometer (λ=1.54060 Å), scanning electron microscopy combined with X-ray fluorescence energy-dispersive analysis based on a TESCAN VEGA 3 microscope SBU with OXFORD X-Max prefix, transmission electron microscopy combined with energy dispersive spectroscopy and selected area electron diffraction based on the JEM-2100F microscope, scanning electron-ion microscopy based on the QUANTA 200 3D microscope. Results. The authors have built the dependence of the phase composition of the product of non-vacuum electric arc synthesis at current strengths from 50 to 220 A. Mass fraction of each of the identified phases in the synthesis product was determined using the reference intensity ratio. The current and the energy entered in the system, which provide the largest proportion of tungsten carbide WC in the synthesis product, are determined. The authors studied the product containing the largest proportion of tungsten carbide WC using scanning and transmission electron microscopy methods

Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide

Abstract Synthesis of high-entropy carbides (HEC) requires high temperatures that can be provided by electric arc plasma method. However, the formation temperature of a single-phase sample remains unknown. Moreover, under some temperatures multi-phase structures can emerge. In this work, we developed an approach for a controllable synthesis of HEC TiZrNbHfTaC5 based on theoretical and experimental techniques. We used Canonical Monte Carlo (CMC) simulations with the machine learning interatomic potentials to determine the temperature conditions for the formation of single-phase and multi-phase samples. In full agreement with the theory, the single-phase sample, produced with electric arc discharge, was observed at 2000 K. Below 1200 K, the sample decomposed into (Ti-Nb-Ta)C, and a mixture of (Zr-Hf-Ta)C, (Zr-Nb-Hf)C, (Zr-Nb)C, and (Zr-Ta)C. Our results demonstrate the conditions for the formation of HEC and we anticipate that our approach can pave the way towards targeted synthesis of multicomponent materials

CMS : the TriDAS Project Technical Design Report; v.1, the Trigger Systems

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Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

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