Nanocomposites TiO2/SiO2 with photocatalytic and adsorptive properties were prepared by codispersing of η-modification and anatase (commercial Hombifine N) and SiO2 (opal, granules, ultrafine) in ethanol (or ethanol–water mixture in the presence of chlorophylls or porphyrins) with ultrasonic treatments of the mixture (method 1) and an aqueous solution of KOH with a microwave treatment (method 2), as well as the introduction of SiO2 in the reaction mixture during the synthesis of TiO2 by brief hydrolysis of sulfate titanyl (method 3). It was found that the state of titania in the sample (X-ray amorphous or nanocrystalline) and its deposition on SiO2 nanocomposites depend on the method and the conditions of obtaining. It was established that the photocatalytic activity of nanocomposite TiO2/SiO2 (granules) (method 1) photosensitized by coproporphyrin I in the visible range and the photocatalytic activity of nanocomposite TiO2/SiO2 (opal) (method 3) in the near UV range exceed activity of the commercial sample of TiSiO4 by more than 20-fold and ~7-fold, respectively. It was shown that the nanocomposite TiO2/SiO2 (opal) significantly reduces the concentration of cations (in particular, Be, Ni, Bi) in the model water systems.
A number of MK-40 cation-exchange membrane samples modified with ceria have been obtained. The membranes have been studied using a set physicochemical methods, including impedance spectroscopy, scanning electron microscopy, microanalysis, transmission electron microscopy, and XRD phase analysis. Ithas been shown that the embedding of cerium oxide reduces the humidity content and ionic conduction of membranes. It is accompanied by a marked increase in the membrane selectivity expressed by a decrease in transfer numbers with respect to anions
Science and technology are seen globally as key drivers of economic growth. At the same time, international and Russian experiences show that balanced and harmonised development of all components in the S&T sphere is crucially important, including research facilities and equipment. Government policy should be supported by holistic and as comprehensive as possible datasets that describe the state and quality of R&D facilities and equipment. Such statistical and empirical data must meet certain specific requirements regarding their completeness and objectivity. The facilities and equipment that R&D organisations have access to are currently represented by a limited set of generalised value indicators. These indicators are usually insufficient to provide adequate information about the structure and technological level of specific facilities. In particular, research equipment is not covered by regular and detailed statistical monitoring. This is due to the wide range of instruments, devices, and installations used, many of which are highly specialised; to methodological problems; and the high costs associated with describing or classifying research equipment. Extending the statistical coverage of R&D equipment and facilities is only possibly by systematising and structuring their numerous and diverse units and by applying a specialised classification. This paper presents the main approaches to classifying R&D equipment and facilities and proposes a novel classification scheme for research equipment designed by the authors.