959 resultados para kinetic dissolution
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Intact cells from Pseudomonas aeruginosa strain L10 containing amidase were used as biocatalysts both free and immobilized in a reverse micellar system. The apparent kinetic constants for the transamidation reaction in hydroxamic acids synthesis, were determined using substrates such as aliphatic, amino acid and aromatic amides and esters, in both media. In reverse micelles, K-m values decreased 2-7 fold relatively to the free biocatalyst using as substrates acetamide, acrylamide, propionamide and glycinamide ethyl ester. We have concluded that overall the affinity of the biocatalyst to each substrate increases when reactions are performed in the reversed micellar system as opposed to the buffer system. The immobilized biocatalyst in general, exhibits higher stability and faster rates of reactions at lower substrates concentration relatively to the free form, which is advantageous. Additionally, the immobilization revealed to be suitable for obtaining the highest yields of hydroxamic acids derivatives, in some cases higher than 80%. (C) 2013 Elsevier B.V. All rights reserved.
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This research work has been focused in the study of gallinaceous feathers, a waste that may be valorised as sorbent, to remove the Dark Blue Astrazon 2RN (DBA) from Dystar. This study was focused on the following aspects: optimization of experimental conditions through factorial design methodology, kinetic studies into a continuous stirred tank adsorber (at pH 7 and 20ºC), equilibrium isotherms (at pH 5, 7 and 9 at 20 and 45ºC) and column studies (at 20ºC, at pH 5, 7 and 9). In order to evaluate the influence of the presence of other components in the sorption of the dyestuff, all experiments were performed both for the dyestuff in aqueous solution and in real textile effluent. The pseudo-first and pseudo-second order kinetic models were fitted to the experimental data, being the latter the best fit for the aqueous solution of dyestuff. For the real effluent both models fit the experimental results and there is no statistical difference between them. The Central Composite Design (CCD) was used to evaluate the effects of temperature (15 - 45ºC) and pH (5 - 9) over the sorption in aqueous solution. The influence of pH was more significant than temperature. The optimal conditions selected were 45ºC and pH 9. Both Langmuir and Freundlich models could fit the equilibrium data. In the concentration range studied, the highest sorbent capacity was obtained for the optimal conditions in aqueous solution, which corresponds to a maximum capacity of 47± 4 mg g-1. The Yoon-Nelson, Thomas and Yan’s models fitted well the column experimental data. The highest breakthrough time for 50% removal, 170 min, was obtained at pH 9 in aqueous solution. The presence of the dyeing agents in the real wastewater decreased the sorption of the dyestuff mostly for pH 9, which is the optimal pH. The effect of pH is less pronounced in the real effluent than in aqueous solution. This work shows that feathers can be used as sorbent in the treatment of textile wastewaters containing DBA.
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Specific marine macro algae species abundant at the Portuguese coast (Laminaria hyperborea, Bifurcaria bifurcata, Sargassum muticum and Fucus spiralis) were shown to be effective for removing toxic metals (Cd(II), Zn(II) and Pb(II)) from aqueous solutions. The initial metal concentrations in solution were about 75–100 mg L−1. The observed biosorption capacities for cadmium, zinc and lead ions were in the ranges of 23.9–39.5, 18.6–32.0 and 32.3–50.4 mg g−1, respectively. Kinetic studies revealed that the metal uptake rate was rather fast, with 75% of the total amount occurring in the first 10 min for all algal species. Experimental data were well fitted by a pseudo-second order rate equation. The contribution of internal diffusion mechanism was significant only to the initial biosorption stage. Results indicate that all the studied macro algae species can provide an efficient and cost-effective technology for eliminating heavy metals from industrial effluents.
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This research work aims to study the use of peanut hulls, an agricultural and food industry waste, for copper and lead removal through equilibrium and kinetic parameters evaluation. Equilibrium batch studies were performed in a batch adsorber. The influence of initial pH was evaluated (3–5) and it was selected between 4.0 and 4.5. The maximum sorption capacities obtained for the Langmuir model were 0.21 ± 0.03 and 0.18 ± 0.02 mmol/g, respectively for copper and lead. In bi-component systems, competitive sorption of copper and lead was verified, the total amount adsorbed being around 0.21 mmol of metal per gram of material in both mono and bi-component systems. In the kinetic studies equilibrium was reached after 200 min contact time using a 400 rpm stirring rate, achieving 78% and 58% removal, in mono-component system, for copper and lead respectively. Their removal follows a pseudo-second-order kinetics. These studies show that most of the metals removal occurred in the first 20 min of contact, which shows a good uptake rate in all systems.
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Biochemical and Biophysical Research Communications 308 (2003) 73–78
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Quimica Nova, Vol. 32, Nº2
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Dissertação apresentada para obtenção do grau de Doutor em Bioquímica,especialidade Bioquímica-Física, pela Universidade Nova de Lisboa, Faculdade de Cincias e Tecnologia
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Thesis for the master degree in Structural and Functional Biochemistry
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J. Am. Chem. Soc., 2009, 131 (23), pp 7990–7998 DOI: 10.1021/ja809448r
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Biochemistry. 2008 Oct 14;47(41):10852-62. doi: 10.1021/bi801375q
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J Biol Inorg Chem (2004) 9: 839–849 DOI 10.1007/s00775-004-0584-6
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The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.
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This study aimed to develop appropriate changes in a pair of shoes in order to improve the gait of an individual selected for this case study. This analysis took into account ergonomic aspects, namely those relating to the individual’s anthropometrics. Gait analysis was done with the adapted footwear both before and after intervention.A conventional X-ray was performed, which revealed a 29-mm left lower limb shortening and possible foot adduction. The anthropometric assessment confirmed a 27-mm asymmetry between the left knee and foot.Corrective changes were implemented in the left boot, with a 20-mm increase in the plantar aspect and approximately 30-mm in the calcaneus area.The pressure-mapping system WalkinSense was used for the kinetic gait analysis. Results showed some improvement in plantar pressure distribution after corrective changes in footwear. Peak pressure in the left foot decreased from 2.8kg/cm2 to 1.6kg/cm2. The second peak also showed a marked decrease. The right foot presented with a reduction in peak plantar pressure from 2.7kg/cm2 to 2.3kg/cm2.After identifying asymmetries, the associated pathologies and modifyingthe footwear, a kinetic analysis of gait before and after altering the footwear was undertaken, which showed improvements in the gait. According to the obtained results, it was possible to demonstrate that the initially proposed objectives were achieved, i.e., the changes in footwear resulted in an improvement of the analyzed individual.
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To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.