In this work, an activated electric arc furnace slag (A-EAFS) was investigated as an effective Fenton catalyst for the photodegradation of methylene blue (MB) and acid blue 29 (AB29). Fourier transform infrared spectroscopy and UV-visible absorption analyses indicated that A-EAFS offers additional Fe3O4 because of the changes in the iron oxide phase and the favorable response to visible light. It has been found that the highest degradation efficiency can reach up to 94% for MB under optimal conditions of 1 g L-1 of A-EAFS, 20 mM H2O2, and pH 3. The optimal conditions for AB29 were 0.1 g L-1 A-EAFS, 4 mM H2O2, and pH 3 to reach 98% degradation efficiency. Visible light enhanced the degradation of both dyes. In addition, A-EAFS, could be easily separated magnetically, exhibited good chemical stability after seven successive photodegradation cycles.
The adsorption of methylene blue (MB) from aqueous solution using a low-cost adsorbent, rejected tea (RT), has been studied by batch adsorption technique. The adsorption experiments were carried out under different conditions of initial concentration (50-500 mg/L), solution pH 3-12, RT dose (0.05-1g) and temperature (30-50 degrees C). The equilibrium data were fitted to Langmuir and Freundlich isotherms and the equilibrium adsorption was best described by the Langmuir isotherm model with maximum monolayer adsorption capacities found to be 147, 154 and 156 mg/g at 30, 40 and 50 degrees C, respectively. Three kinetic models, pseudo-first-order, pseudo-second-order and intraparticle diffusion were employed to describe the adsorption mechanism. The experimental results showed that the pseudo-second-order equation is the best model that describes the adsorption behavior with the coefficient of correlation R(2)>or=0.99. The results suggested that RT has high potential to be used as effective adsorbent for MB removal.
Recently, the plant polyphenols have attracted much attention for membrane modification, especially in surface coating application. In this study, the synthesis of catechol-amine coating solutions was evaluated at different pH conditions and with different concentrations of tannic acid and tetraethylenepentamine in order to determine the relationship between chemical structure and mechanism in the oxidation reaction. The reactivity of catechol and amine groups in the formulation was measured using UV-Vis spectroscopy and observation of the change in colour of the coating solutions. Then, the deposition of catechol-amine coating solutions was applied onto the hydrophobic polyvinylidene fluoride (PVDF) membrane. The formulation results show significant differences in alkaline conditions, revealing the role of catechol groups in the oxidation of polyphenolics. The reactions of quinone and amines to form crosslinks by Michael addition and Schiff base reactions were observed at different concentrations of each compound in coating solution. In addition, the negative charge of hydrophilic and underwater oleophobic-coated PVDF membrane was confirmed by surface zeta potential analysis. The morphological surface of modified membrane is rougher due to that coating deposition was also examined using scanning electron microscopy (SEM). Furthermore, the performance of modified membrane is comparable with the commercial hydrophilic membrane in terms of fluxes and separation efficiency of emulsion solution.
Hadoop MapReduce reactively detects and recovers faults after they occur based on the static heartbeat detection and the re-execution from scratch techniques. However, these techniques lead to excessive response time penalties and inefficient resource consumption during detection and recovery. Existing fault-tolerance solutions intend to mitigate the limitations without considering critical conditions such as fail-slow faults, the impact of faults at various infrastructure levels and the relationship between the detection and recovery stages. This paper analyses the response time under two main conditions: fail-stop and fail-slow, when they manifest with node, service, and the task at runtime. In addition, we focus on the relationship between the time for detecting and recovering faults. The experimental analysis is conducted on a real Hadoop cluster comprising MapReduce, YARN and HDFS frameworks. Our analysis shows that the recovery of a single fault leads to an average of 67.6% response time penalty. Even though the detection and recovery times are well-turned, data locality and resource availability must also be considered to obtain the optimum tolerance time and the lowest penalties.