Highly Efficient Solar-Light-Active Ag-Decorated g-C3N4 Composite Photocatalysts for the Degradation of Methyl Orange Dye

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).In this study, we utilized calcination and simple impregnation methods to successfully fabricate bare g-C3N4 (GCN) and x% Ag/g-C3N4 (x% AgGCN) composite photocatalysts with various weight percentages (x = 1, 3, 5, and 7 wt.%). The synthesized bare and composite photocatalysts were analyzed to illustrate their phase formation, functional group, morphology, and optical properties utilizing XRD, FT-IR, UV-Vis DRS, PL, FE-SEM, and the EDS. The photodegradation rate of MO under solar light irradiation was measured, and the 5% AgGCN composite photocatalyst showed higher photocatalytic activity (99%), which is very high compared to other bare and composite photocatalysts. The MO dye degradation rate constant with the 5% AgGCN photocatalyst exhibits 14.83 times better photocatalytic activity compared to the bare GCN catalyst. This photocatalyst showed good efficiency in the degradation of MO dye and demonstrated cycling stability even in the 5th successive photocatalytic reaction cycle. The higher photocatalytic activity of the 5% AgGCN composite catalyst for the degradation of MO dye is due to the interaction of Ag with GCN and the localized surface plasmon resonance (SPR) effect of Ag. The scavenger study results indicate that O2 •− radicals play a major role in MO dye degradation. A possible charge-transfer mechanism is proposed to explain the solar-light-driven photocatalyst of GCN

Ru Nanoparticles Supported on Mesoporous Al-SBA-15 Catalysts for Highly Selective Hydrogenation of Furfural to Furfuryl Alcohol

This is an open access article under the terms of the Creative Commons Attribution Non-Commercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Furfuryl alcohol, which is the hydrogenated product of furfural, has been identified as a very promising platform chemical with high potential for applications in the manufacture of key chemicals, lubricants, fragrances, and pharmaceuticals. In this work, bare SB, and x % Ru/Al-SB (x=1.5, 2.5, 3.5, and 4.5 wt. %) samples were fabricated by a hydrothermal method. Bare and most active catalysts were characterized by different techniques, such as BET, FE-SEM, TEM, FT-IR, and XRD, to understand their physical and chemical properties. An evaluation of the effects of various reaction parameters, such as catalyst loading, reaction temperature, and reaction time, on the catalytic performance, showed higher catalytic conversion of furfural and selectivity for the desired products. The most active RuS3 catalyst showed 100 % conversion of furfural and 99 % selectivity for furfuryl alcohol. It could be reused for five consecutive reaction cycles without significant loss of performance. In addition, Ru leaching and loss of conversion or selectivity were not noticed during the five-run recycling test. The EDS elemental mapping analysis of the used catalyst established the preservation of the mesoporous structure, suggesting a strong interaction between the hexagonal porous silicate and the Ru nanoparticles

Analysis of electrochemical noise data by use of recurrence quantification analysis and machine learning methods

© 2017 By use of recurrence quantification analysis (RQA), twelve features were extracted from the electrochemical noise signals generated by three types of corrosion: uniform, pitting and passivation. Machine learning methods, i.e. linear discriminant analysis (LDA) and random forests (RF), were used to identify the different corrosion types from those features. Both models gave satisfactory performance, but the RF model showed better prediction accuracy of 93% than the LDA model (88%). Furthermore, an estimation of the importance of the variables by use of the RF model suggested the RQA variables laminarity (LAM) and determinism (DET) played the most significant role with regard to identification of corrosion types. In addition, the comparison of noise resistance with the resistance obtained from EIS measurement showed that the noise resistance can be used for monitoring corrosion rate variations not only for uniform corrosion and passivation, but also for pitting