Adaptive iterative regularization schemes for two‐dimensional integral‐algebraic systems

The main idea of this paper is to utilize the adaptive iterative schemes based on regularization techniques for moderately ill‐posed problems that are obtained by a system of linear two‐dimensional Volterra integral equations with a singular matrix in the leading part. These problems may arise in the modeling of certain heat conduction processes as well as in the dynamic simulation packages such as compressible flow through a plant piping network. Owing to the ill‐posed nature of the first kind Volterra equation that appears in the system, we will focus on the two families of regularization algorithms, ie, the Landweber and Lavrentiev type methods, where we treat both the exact and perturbed data. Our aim is to work directly with the original Volterra equations without any kind of reduction. Two fast iterative algorithms with reasonable computational complexity are developed. Numerical experiments on a few test problems are used to illustrate the validity and efficiency of the proposed iterative methods in comparison with the classical regularization methods.     

Plasma Assisted Synthesis and Physicochemical Characterizations of Ni–Co/Al2O3 Nanocatalyst Used in Dry Reforming of Methane

To assess the effects of plasma treatment a Ni–Co/Al₂O₃ nanocatalyst (10 % Ni and 3 % Co) was prepared via impregnation method followed by treatment with a non-thermal plasma to be investigated in a catalytic dry reforming of methane. The impregnated and plasma-treated nanocatalysts were characterized using XRD, FESEM, EDX, TEM, BET, FTIR, and XPS techniques. The XRD patterns confirmed the presence of nickel as NiO and NiAl₂O₄ and cobalt as Co₃O₄ on alumina support. Small NiO, NiAl₂O₄, and Co₃O₄ crystals observed in plasma-treated nanocatalyst, exhibited a good dispersion of active phase in this catalyst. The average particles size in plasma-treated sample obtain by FESEM micrograph were shown to be smaller than that of impregnated sample and the morphology was more homogenous and relatively agglomeration-free in plasma-treated Ni–Co/Al₂O₃ nanocatalyst. According to BET analysis, specific surface area of plasma-treated sample was 58 % higher than the non-treated catalyst. TEM analysis showed that particles of active phase were fairly small and well-dispersed on Al₂O₃ as a result of the plasma treatment. Better dispersion of active metal on the surface of plasma-treated sample was confirmed by XPS analysis. The plasma-treated sample showed higher yield and conversion at all temperature ranges investigated and was more resistant to coke formation compared to the non-treated sample. The results from the characterization and reaction studies suggests that plasma treatment may be a promising method for obtaining more active and stable nanocatalysts for dry reforming of methane.     

Corrosion Inhibition of Mild Steel by Safflower (Carthamus tinctorius) Extract: Polarization,EIS, AFM,SEM, EDS,and Artificial Neural Network Modeling

Inhibitory action of safflower (Carthamus tinctorius) extract (SE) was investigated in hydrochloric acid solution through electrochemical (polarization, EIS), and surface analysis (optical microscopy/atomic force microscopy (AFM)/scanning electron microscopy (SEM)/energy dispersive spectroscopy (EDS)) techniques. In addition, Inhibition efficiency was predicted by neural network (NN) modeling in elevated temperatures and different acid concentrations. The thermodynamic adsorption parameters propose that this inhibitor retard both cathodic and anodic processes through physical adsorption and blocking the active corrosion sites. Surface analysis techniques confirm the inhibitor adsorption on the metal surface, which is in accordance with the variation of apparent activation energy of corrosion. Finally, inhibition efficiency is discussed in terms of protective film formation.     

Synthesis of Functionalized Pyrido[1,2-f]phenanthridines from Phenanthridine,Activated Acetylenes,and Arylidenemalononitriles

The zwitterions generated from phenanthiridine and dialkyl acetylenedicarboxylates (DAADs) react with a variety of arylidenemalononitriles, affording substituted pyrido[1,2-f]phenanthridines.     

Kinetic Study of Radical Polymerization VI. Copolymer Composition and Kinetic Parameters for Coplymerization of Styrene‐Itaconic Acid by On‐Line 1H‐NMR

Free radical solution copolymerization of styrene (St) and itaconic acid (IA) in dimethylsulfoxide‐d₆ (DMSO‐d₆) as the solvent and the use of 2,2′‐azobisisobutyronitrile (AIBN) as the initiator at 78°C was investigated by an on‐line ¹H‐NMR spectroscopy technique. Individual monomer conversion vs. reaction time, which was calculated from the ¹H‐NMR spectra data, was used to study the drift in monomer mixture composition vs. conversion. It was found that in general, both monomers were incorporated almost equally into the copolymer. However, when the mole fraction of IA was low, the tendency of IA toward incorporation into the copolymer chain was somewhat higher than St and by increasing the mole fraction of IA in the reaction mixture, the inverse tendency was observed. Overall monomer conversion as a function of time was calculated from individual monomer conversion data and used for the estimation of k_p /k_t ^0.5 for various monomer mixture compositions. This ratio was decreased with increasing the amount of IA in the initial feed, indicating a decrease in the rate of copolymerization. Changes in the copolymer composition vs. overall monomer conversion were investigated experimentally from the NMR spectra. This was in good agreement with the changes in monomer mixture composition vs. reaction progress. Plotting the copolymer composition vs. initial monomer feed showed tendency of the system toward alternating copolymerization.     

Removal of thorium from aqueous solutions by sodium clinoptilolite

Adsorptive behavior of natural clinoptilolite was assessed for removal of thorium from aqueous solutions. Natural zeolite was characterized by X-ray diffraction and X-ray fluorescence. The zeolite sample composed mainly of clinoptilolite. Na-exchanged form of zeolite was prepared and its sorption capacity for removal of thorium from aqueous solutions was examined. The effects of relevant parameters, including initial concentration, contact time, solid to liquid ratio, temperature and initial pH on the removal efficiency were investigated in batch studies. The pH strongly influenced thorium adsorption capacity and maximal capacity was obtained at pH 4.0. Kinetics and isotherm of adsorption were also studied. The pseudo-first-order, pseudo-second-order, Elovich and intra-particle diffusion models were used to describe the kinetic data. The pseudo-second-order kinetic model provided excellent kinetic data fitting (R ² > 0.999) with rate constant of 1.25, 1.37 and 1.44 g mmol⁻¹ min⁻¹ respectively for 25, 40 and 55 °C. The Langmuir and Freundlich models were applied to describe the equilibrium isotherms for thorium uptake and the Langmuir model agrees very well with experimental data. Thermodynamic parameters were determined and are discussed.     

Development of a novel flow injection liquid-liquid microextraction method for the on-line separation and preconcentration for determination of zinc(II) using 5-(8-hydroxy-2-quinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane as a sensitive and selective fluorescent chemosensor

A novel flow injection analysis (FIA) system based on liquid-liquid microextraction and fluorimetric determination was developed for the determination of traces of the Zn²⁺ ion using 5-(8-hydroxy-2-quinolinylmethyl)-2,8-dithia-5-aza-2,6-pyridinophane (L) as a sensitive and selective fluorimetric sensor, with λ_ex = 373 nm and λ_em = 530 nm, and hexanol as the extracting organic solvent. In the designed FIA system, the phase separation takes place via gravitation forces in the absence of any segmenter. The influence of pH and ionic strength of the solution, amount of ligand, nature of counter ion, volume of organic solvent, extraction time and coil length was investigated. Under optimized experimental conditions, the calibration curve found to be liner over a concentration range of 0.025-4.53 μg mL⁻¹ (R² = 0.9951) with a limit of detection of 2.3 ng mL⁻¹. The enrichment factor was 45 and relative standard deviation for 7 replicate determinations was 2.43%. The method is very fast and uses low levels of organic solvents. The proposed method was applied successfully to the determination of zinc(II) in human hair, human serum and two inorganic sludge samples.     

Calcium manganese oxides as oxygen evolution catalysts: O2 formation pathways indicated by 18O-labelling studies

Oxygen evolution catalysed by calcium manganese and manganese-only oxides was studied in (18)O-enriched water. Using membrane-inlet mass spectrometry, we monitored the formation of the different O(2) isotopologues (16)O(2), (16)O(18)O and (18)O(2) in such reactions simultaneously with good time resolution. From the analysis of the data, we conclude that entirely different pathways of dioxygen formation catalysis exist for reactions involving hydrogen peroxide (H(2)O(2)), hydrogen persulfate (HSO(5)(-)) or single-electron oxidants such as Ce(IV) and [Ru(III) (bipy)(3)](3+) . Like the studied oxide catalysts, the active sites of manganese catalase and the oxygen-evolving complex (OEC) of photosystem II (PSII) consist of μ-oxido manganese or μ-oxido calcium manganese sites. The studied processes show very similar (18)O-labelling behaviour to the natural enzymes and are therefore interesting model systems for in vivo oxygen formation by manganese metalloenzymes such as PSII.     

Failure tolerance of spike phase synchronization in coupled neural networks

Neuronal synchronization plays an important role in the various functionality of nervous system such as binding, cognition, information processing, and computation. In this paper, we investigated how random and intentional failures in the nodes of a network influence its phase synchronization properties. We considered both artificially constructed networks using models such as preferential attachment, Watts-Strogatz, and Erdo?s-Re?nyi as well as a number of real neuronal networks. The failure strategy was either random or intentional based on properties of the nodes such as degree, clustering coefficient, betweenness centrality, and vulnerability. Hindmarsh-Rose model was considered as the mathematical model for the individual neurons, and the phase synchronization of the spike trains was monitored as a function of the percentage∕number of removed nodes. The numerical simulations were supplemented by considering coupled non-identical Kuramoto oscillators. Failures based on the clustering coefficient, i.e., removing the nodes with high values of the clustering coefficient, had the least effect on the spike synchrony in all of the networks. This was followed by errors where the nodes were removed randomly. However, the behavior of the other three attack strategies was not uniform across the networks, and different strategies were the most influential in different network structure.