Modelling diffusion and adsorption of As species in Fe/GAC adsorbent beds

BACKGROUND: Arsenic decontamination of drinking water by adsorption is a simple and robust operation. When designing packed bed adsorbers for arsenic, the main problems are the slow diffusion kinetics of As in microporous media and the lack of simple equations for predicting the performance of the equipment. Commercial iron‐doped granular activated carbon adsorbents (Fe/GAC) for groundwater arsenic abatement were studied in this work. Basic parameters for arsenate (As^V) adsorption were measured and their performance at larger scale was simulated with an approximate analytical model. RESULTS: In the 0–300 µg_As L^?1 range, the As^V adsorption isotherm on Fe/GAC was found to be approximately linear. Assuming Henry's law for adsorption and homogeneous surface diffusion with constant diffusivity for intrapellet mass transfer, an approximate model for flow and adsorption of arsenate inside packed bed adsorbers was developed, and reduced to an analytic compact solution using the quasi‐lognormal distribution (Q‐LND) approximation. The use of this model with fitted and reported parameters enabled the approximate simulation of industrial adsorbers and home point‐of‐use filters. Results show that industrial adsorbers meet the breakthrough condition with incomplete utilization of the adsorbent unless convenient process configurations are used. In point‐of‐use systems with short residence times intraparticle diffusion would drastically reduce the adsorbent performance. CONCLUSION: Assuming linear adsorption of As^V over Fe/GAC, an analytical approximate solution for flow and adsorption in packed beds can be obtained. The model seems to represent correctly the main features of industrial and home filters, however, more experimental data is necessary for scale‐up purposes. Copyright © 2011 Society of Chemical Industry     

Selective Binding of Cyclodextrins with Leflunomide and Its Pharmacologically Active Metabolite Teriflunomide

The selectivity of encapsulation of leflunomide and teriflunomide by native α-, β- and γ-cyclodextrins was investigated through ¹H NMR and molecular modeling. Thermodynamic analysis revealed the main driving forces involved in the binding. For α-cyclodextrin, the partial encapsulation was obtained while deep penetration was characterized for the other two cyclodextrins, where the remaining polar fragment of the molecule is located outside the macrocyclic cavity. The interactions via hydrogen bonding are responsible for high negative enthalpy and entropy changes accompanying the complexation of cyclodextrins with teriflunomide. These results were in agreement with the molecular modeling calculations, which provide a clearer picture of the involved interactions at the atomic level.     

Molecular differentiation of the species of two squid families (Loliginidae and Ommastrephidae) based on a PCR study of the 5S rDNA gene

The present study aimed to demonstrate the effectiveness of the 5s rDNA gene for the identification of commercially-valuable species of cephalopod belonging to the families Loliginidae and Ommastrephidae. Our results demonstrate distinct banding patterns in each of the six species sampled (Loligo surinamensis; Loligo sanpaulensis; Lolliguncula brevis; Sepiotheuthis sepioidea; Ornithoteuthis antillarum; Illex argentinus), as well as diagnostic traits at the genus and probably family levels. The results emphasize the efficiency of the 5s rDNA marker as a low-cost and rapid forensic technique, which not only permits the identification of species, but also differentiation of members of the Loliginidae and Ommastrephidae.     

Conversion and hydroconversion of hydrocarbons on zeolite-based catalysts: an FT-IR study

The interaction of HZSM5 and Mo-ZSM5 with benzene, naphthalene, toluene, ortho-xylene, para-xylene, n-butane, isobutane, n-heptane, and methylcyclohexane, in the range 100–773 K has been investigated using FT-IR spectroscopy. Hydrogen bonded species with the internal bridging and the external terminal OHs has been detected. The reactivity at high temperature has also been studied. The access to the internal cavities and to the strongly acidic OHs is at least partly hindered in the case of Mo-ZSM5. The catalytic activity of ZSM5 was moderated by the addition of molybdenum, with lower cracking and higher liquid yields.     

Comparison of the Ewald and Wolf methods for modeling electrostatic interactions in nanowires

Ionic compounds pose extra challenges with the appropriate modeling of long‐range coulombic interactions. Here, we study the mechanical properties of zinc oxide (ZnO) nanowires using molecular dynamic simulations with Buckingham potential and determine the suitability of the Ewald (Ann. Phys. 1921; 19) and Wolf (J. Chem. Phys. 1999; 110 (17):8254–8282) summation methods to account for the long‐range Coulombic forces. A comparative study shows that both the summation methods are suitable for modeling bulk structures with periodic boundary conditions imposed on all sides; however, significant differences are observed when nanowires with free surfaces are modeled. As opposed to Wolf's prediction of a linear stress–strain response in the elastic regime, Ewald's method predicts an erroneous behavior. This is attributed to the Ewald method's inability to account for surface effects properly. Additionally, Wolf's method offers highly improved computational performance as the model size is increased. This gain in computational time allows for modeling realistic nanowires, which can be directly compared with the existing experimental results. We conclude that the Wolf summation is a superior technique when modeling non‐periodic structures in terms of both accuracy of the results and computational performance. Copyright © 2010 John Wiley & Sons, Ltd.     

Effect of additive distribution in H2 absorption and desorption kinetics in MgH2 milled with NbH0.9 or NbF5

This paper presents a comparative study of H₂ absorption and desorption in MgH₂ milled with NbF₅ or NbH_0.9. The addition of NbF₅ or NbH_0.9 greatly improves hydriding and dehydriding kinetics. After 80 h of milling the mixture of MgH₂ with 7 mol.% of NbF₅ absorbs 60% of its hydrogen capacity at 250 °C in 30 s, whereas the mixture with 7 mol.% of NbH_0.9 takes up 48%, and MgH₂ milled without additive only absorbs 2%. At the same temperature, hydrogen desorption in the mixture with NbF₅ finishes in 10 min, whereas the mixture with NbH_0.9 only desorbs 50% of its hydrogen content, and MgH₂ without additive practically does not releases hydrogen. The kinetic improvement is attributed to NbH_0.9, a phase observed in the hydrogen cycled MgH₂ + NbF₅ and MgH₂ + NbH_0.9 materials, either hydrided or dehydrided. The better kinetic performance of the NbF₅-added material is attributed to the combination of smaller size and enhanced distribution of NbH_0.9 with more favorable microstructural characteristics. The addition of NbF₅ also produces the formation of Mg(H_xF_1-x)₂ solid solutions that limit the practically achievable hydrogen storage capacity of the material. These undesired effects are discussed.     

Supervisory control design based on hybrid systems and fuzzy events detection. Application to an oxichlorination reactor

This paper presents a supervisory control scheme based on hybrid systems theory and fuzzy events detection. The fuzzy event detector is a linguistic model, which synthesizes complex relations between process variables and process events incorporating experts' knowledge about the process operation. This kind of detection allows the anticipation of appropriate control actions, which depend upon the selected membership functions used to characterize the process under scrutiny. The proposed supervisory control scheme was successfully implemented for an oxichlorination reactor in a vinyl monomer plant. This implementation has allowed improvement of reactor stability and reduction of raw material consumption.     

Knowledge representation of the software architecture design process based on situation calculus

Software architecture design is an interactive, complex, decision‐making process. Such a design process involves the exploration, evaluation, and composition of design alternatives. Increasingly, new computer‐aided tools are available to help designers in these complex activities. However, these tools do not know how design is actually done, in other words, by means of which design activities the final artefact was obtained. In fact, the architectural design knowledge exclusively rests in the mind of designers, and there is an urgent need to move it, as much as possible, to a computer‐supported environment that enables the capture of this type of knowledge. This contribution addresses this need by introducing a model for capturing how products under development are generated and transformed along the software architecture design process. The proposed model follows an operational perspective, where architectural design decisions are modelled by means of sequences of operations that are applied on the design products. Situation calculus is used to formally express the existence of an object in a given state of a design process. In addition, this formalism allows us expressing without ambiguities when an operation can be performed in a specific state of the design process.     

A numerical tool to predict ice growth in lakes

Oil and gas exploration activities on the North of Slope of Alaska rely on ice roads to provide access to the exploration sites, with negligible effects on the tundra. The construction of ice roads requires a large volume of water which, in turn, poses challenges to water resource managers. A tool capable of predicting ice thickness in a given lake could certainly benefit the oil industry. This study focuses on the development and use of such a predictive tool. Using a simplified Stefan equation, the tool is based on a combination of three weather scenarios (warm, average and cold winters), current winter condition and ice thickness measurements. It was applied to four lakes located on the Arctic Coastal Plain and one lake in the foothill area. The study results indicate the model predictions are relatively accurate (7% average percentage error) for monthly time spans. The study results also reveal a temporal variation in a coefficient used in the calculations, although previous literature utilized a constant coefficient to estimate the ice thickness.