Role of strain reversal in microstructure and texture of pure al during non-monotonic simple shear straining

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Dyestuff is one of the most widely released pollutants into the environment. Many approaches have been considered to deal with the dye removal from polluted water such as adsorption, ultrafiltration, osmosis, solvent extraction and photocatalytic degradation. The photocatalytic degradation process is one of the most beneficial, economical and environmentally friendly ways to degrade the organic pollutants from wastewater. In this study, an efficient ferrite-based photocatalyst, AgFeO2/rGO/TiO2 was successfully developed using simple deposition and reflux method. Physical, chemical and structural properties were analyzed by using XRD, FTIR Raman and PL spectroscopy. The efficiency of photocatalyst was investigated for the decolorization of methyl blue (MB) dye and activity was measured through UV-vis spectroscopy. The effect of parameters like pH, concentrations of MB dye, and loading of silver ferrite (AgFeO2) was investigated. The study depicted that the properties of TiO2 were improved due to addition of silver ferrite and reduced graphene oxide (rGO). The 2.5% AgFeO2/rGO/TiO2 exhibited the highest efficiency and completely degraded the 50 ppm of MB dye in 30 min. The parametric study revealed that dye decolorization is faster in a neutral solution than in basic and acidic medium. The higher performance of the photocatalyst was attributed to the reduced charge recombination and improved optical properties. Thus, AgFeO2/rGO/TiO2 can be a potential composite for photocatalytic dye degradation and other photocatalytic applications under UV-Visible light irradiations

Improving strength-ductility synergy of nano/ultrafine-structured Al/Brass composite by cross accumulative roll bonding process

Copyright © 2023 The Author(s). Increasing the strength of metallic multilayered composites fabricated through accumulative roll bonding (ARB) is typically accompanied by a sacrifice in ductility. In the current work, we propose a strategy to achieve microstructural refinement and outstanding strength-ductility synergy in Al/Brass composites. Here, the aluminum matrix exhibits a bimodal grain distribution, consisting of fine equiaxed grains with an average size of ∼100 nm and ultrafine-elongated grains, in which the brass fragments were distributed uniformly. These microstructural features, introduced through cross accumulative roll bonding (CARB), provide synergistic strengthening effects. The CARB processed composite exhibits a mean misorientation angle of 43.16° and a fraction of high angle grain boundaries of 87%, compared to values of 38.02° and 79% for ARB processed specimen. The CARB processed composite demonstrates a major texture characterized by prominent Rotated Brass {110}, Rotated Goss {011}, and Rotated Cube {001} components. In contrast, the ARB processed specimen revealed strong Goss {011}, Rotated Goss {011}, Brass {011}, and S {123} components. The Copper {112} and S {123} components were nearly absent in the CARB processed composite, because both of them were unstable under the CARB regime. The CARB processed composite shows a tensile strength of 405 MPa and a remarkable elongation of 12.4% at ambient temperature, outperforming ARB processed specimen with a tensile strength of 335 MPa and elongation of 9.5%. These unique mechanical properties in the CARB processed composite are ascribed to the dislocation strengthening, bimodal grain size distribution, uniformity of the brass fragments, and quality of bonding at the interfaces.Ministry of Science and Higher Education of the Russian Federation (FENU-2023-0013).; Seoul National University, Seoul, South Korea (Brain Korea 21 (BK21) Postdoctoral Fellowship to MN).

Multi-dimension Tensor Factorization Collaborative Filtering Recommendation for Academic Profiles

The choice of academic itineraries and/or optional subjects to attend is not usually an easy decision since, in most cases, students lack the information, maturity, and knowledge required to make right decisions. This paper evaluates the support of Collaborative Systems for helping and guiding students in this decision-making process, considering the behavior and impact of these systems on the use of data different from the formal information the students usually use. For this purpose, the research applied the clustering based Multi-dimension Tensor Factorization approach to build a recommendation system and confirm that the increment in tensors improves the recommendation accuracy. As a result, this approach permits the user to take advantage of the contextual information to reduce the sparsity issue and increase the recommendation accuracy