Reductive removal of hexavalent chromium from aqueous solution using sepiolite-stabilized zero-valent iron nanoparticles: Process optimization and kinetic studies

We studied the optimization of hexavalent chromium (Cr(VI)) removal from aqueous solution using the synthesized zero-valent iron nanoparticles stabilized with sepiolite clay (S-ZVIN), under various parameters such as reaction time (min), initial solution pH and concentration of S-ZVIN (g·L^?1) using response surface methodology (RSM). The kinetic study of Cr(VI) was conducted using three types of the most commonly used kinetic models including pseudo zero-order, pseudo first-order, and pseudo second-order models. The rate of reduction reaction showed the best fit with the pseudo first-order kinetic model. The process optimization results revealed a high agreement between the experimental and the predicted data (R²=0.945, Adj-R²=0.890). The results of statistical analyses showed that reaction time was the most impressive factor influencing the efficiency of removal process. The optimum conditions for maximum response (98.15%) were achieved at the initial pH of 4.7, S-ZVIN concentration of 1.3 g·L^?1 and the reaction time of 75 min.     

Performance analysis of three advanced controllers for polymerization batch reactor: An experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC.     

A thermodynamically consistent framework for non-isothermal modelling of local heat generation and electromotive force in SOFC single electrodes

Mathematical models for single electrode reversible heat and non-isothermal electromotive force (EMF) of a solid oxide fuel cell (SOFC) are developed. These models estimate the volumetric reversible heat generation and EMF of electrochemical reactions, within each electrode at local conditions of temperature and pressure, based on entropy change of half reactions. The resulting equations are thermodynamically consistent. They inherently obey the conservation of energy law as the electrochemical energy released added to the heat of reactions at each electrode equate the enthalpy change of the reacted species. The equations are implemented to model electrodes in a tubular micro- solid oxide fuel cell (TμSOFC). The thermodynamic consistency of the model is numerically confirmed as the enthalpy of the reactants equates the electric energy released by the cell plus the sum of electrode heats plus electrolyte Ohmic heat. The effect of thermal gradients on the cell's overall EMF is found to be negligible. The reversible and irreversible heat generation of each electrode are distinguished. Overall, the anode is found to be endothermic, and the cathode exothermic.     

Modelling qualitative and quantitative parameters of groundwater using a new wavelet conjunction heuristic method: wavelet extreme learning machine versus wavelet neural networks

In recent years, as a result of climate change as well as rainfall reduction in arid and semi‐arid regions, modelling qualitative and quantitative parameters belonging to aquifers has become crucially important. In Iran, as aquifers are treated as the most commonly used drinking water resources, modelling their qualitative and quantitative parameters is enormously important. In this paper, for the first time, values of salinity, total dissolved solids (TDS), groundwater level (GWL) and electrical conductivity (EC) of the Arak Plain, located in Markazi Province, Iran, are simulated by means of four modern artificial intelligence models including extreme learning machine (ELM), wavelet extreme learning machine (WELM), online sequential extreme learning machine (OSELM) and wavelet online sequential extreme learning machine (WOSELM) as well as the MODFLOW software for a 15‐year period monthly. To develop the hybrid artificial intelligence models, the wavelet is employed. First, the effective lags in estimating the qualitative and quantitative parameters of the groundwater are identified using the autocorrelation function (ACF) and the partial autocorrelation function (PACF) analysis. After that, four different models are developed by the selected input combinations and also the ACF and the PACF in the form of different lags for each of ELM, WAELM, OSELM and WOSELM methods. Then, the superior models in simulating the groundwater qualitative and qualitative parameters are detected by conducting a sensitivity analysis. To forecast the electrical conductivity (EC) by the best WOSELM model, the values of the Nash–Sutcliffe efficiency coefficient (NSC), Mean Absolute Error (MAE) and the scatter index (SI) are obtained to be 0.991, 18.005 and 4.28E‐03, respectively. In addition, the most effective lags in estimating these parameters are introduced. Subsequently, the results found by the MODFLOW model are compared with those of the artificial intelligence models and it is concluded that the latter are more accurate. For instance, the scatter index and Nash–Sutcliffe efficiency coefficient values calculated by WOSELM for TDS, respectively, are 5.34E‐03 and 0.991. Finally, an uncertainty analysis is conducted to evaluate the performance of different numerical models. For example, MODFLOW has an underestimated performance in simulating the salinity parameter.     

Sweet lemon mechanical damage detection using image processing technique and UV radiation

Non-destructive measurement of qualitative parameters of agricultural produce is quite beneficial in the postharvest operations. The consequential effect of mechanical damage in citrus fruits is rarely visible in their appearance compared to other commodities. The purpose of this study was to propose a fast, non-destructive method for sweet lemon mechanical damage detection using image processing technique and UV radiation. For this purpose, 135 sweet lemons were tested based on a completely randomized factorial design. In order to examine mechanical damage, the independent variables included drop height, fruit diameter and tempering period (holding time at room temperature after treatment). Fruits were dropped from heights of 2, 2.5 and 3 m onto the ground. Then images were captured under UV light having a wavelength of 365 nm, 1, 3 and 6 days after treatment. The images were sent to a PC and analyzed using MATLAB software. “Green Spot Index” or GSI was defined to show the extent of mechanical damage. Results of the analysis of variance showed that the percentage of green spots on fruit skin is significant at the 1% level considering the main and double interaction effects of drop height and fruit diameter. Green spot index significantly increases with the level of mechanical damage. Accuracy of the developed method in differentiating the bruised and undamaged fruits was found to be 100%.     

A novel proposal for all optical 3 to 8 decoder based on nonlinear ring resonators

In this paper, a 3 to 8 optical decoder was proposed using nonlinear photonic crystal ring resonators. For realizing the 3 to 8 decoder, we combined seven 1 to 2 optical decoders. In the proposed structure, X, Y and Z serve as input ports. By combination of these ports, one can control which output port to be ON. The maximum time delay of the proposed structure is about 6?ps.     

A Novel Approach for Prediction of Monthly Ground Water Level Using a Hybrid Wavelet and Non-Tuned Self-Adaptive Machine Learning Model

Water Resources Management - In recent decades, due to groundwater withdrawal in the Kabodarahang region, Iran, Hamadan, hazardous events such as sinkholes, droughts, water scarcity, etc., have...     

Solid-phase electrochemical reduction of graphene oxide films in alkaline solution

Graphene oxide (GO) film was evaporated onto graphite and used as an electrode to produce electrochemically reduced graphene oxide (ERGO) films by electrochemical reduction in 6 M KOH solution through voltammetric cycling. Fourier transformed infrared and Raman spectroscopy confirmed the presence of ERGO. Electrochemical impedance spectroscopy characterization of ERGO and GO films in ferrocyanide/ferricyanide redox couple with 0.1 M KCl supporting electrolyte gave results that are in accordance with previous reports. Based on the EIS results, ERGO shows higher capacitance and lower charge transfer resistance compared to GO.     

Graft Copolymerization of Styrene‐Maleic Anhydride Onto Poly(Vinyl Chloride) and Its Cross‐linking by Toluene Diisocyanate: Characterization,Thermal, and Mechanical Properties

In this work, styrene‐maleic anhydride (St‐MA) copolymer was successfully grafted onto poly(vinyl chloride) (PVC) by means of chemical method in cyclohexanone medium. In this manner, the effects of various parameters such as total monomer content, monomers ratio, and initiator concentration on the grafting percentage (GP) and acid value (AV) were examined. The graft copolymers were characterized by Fourier‐transform infrared and nuclear magnetic resonance spectroscopy methods. Afterward, the cross‐linking reaction was carried out through MA hydrolysis and condensation reaction between maleic acid and produced diamines, by toluene diisocyanate (TDI) at the presence of hot water. The results showed that the GP and AV of PVC‐g‐(St‐MA) copolymers were considerably higher than those of PVC‐g‐MA and PVC‐g‐St with significant molecular weight. A gel content of 56% was attained with 1 phr TDI in PVC‐g‐(St‐MA) copolymer. The glass transition temperatures and mechanical properties of PVC‐g‐(St‐MA) samples were increased compared to pure PVC. Cross‐linked PVC‐g‐(St‐MA) showed improved mechanical properties than other samples, but the glass transition temperature of PVC backbone in this cross‐linked copolymer was disappeared due to its heavily dense structure. J. VINYL ADDIT. TECHNOL., 25:377–384, 2019. © 2019 Society of Plastics Engineers