Retrieval of kinetic rates in reactions with semi batch liquid phase using ill-posed inverse problem theory

A neural network procedure to solve inverse chemical kinetic problems is discussed in this work. Rate constants are calculated from the product concentration of an irreversible consecutive reaction: the hydrogenation of Citral molecule, a process with industrial interest. Simulated and experimental data are considered. Errors in the simulated data, up to 7% in the concentrations, were assumed to investigate the robustness of the inverse procedure. Also, the proposed method is compared with two common methods in nonlinear analysis; the Simplex and Levenberg-Marquardt approaches. In all situations investigated, the neural network approach was numerically stable and robust with respect to deviations in the initial conditions or experimental noises.

A fluorescence-based assay for octreotide in kinetic release from depot formulations

Here we report the validation of a derivatization method that makes use of fluorescamine as a selective reactant for the quantitative analysis of peptide and protein drugs in the dissolution profile from depot formulations. Typical current methods require separation of the nano/microparticles and time-consuming chromatographic runs. In this study we report a method which can be conducted without the need for complete physical separation of the particles or removal of the unreacted probe. This method was used here for the analysis of the release profile of octreotide in a depot formulation, with results in excellent agreement with reported chromatographic assays.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.

Kinetic modeling of the biosorption of Cd2+ ions from aqueous solutions onto Eichhornia crassipes roots using potentiometry: low-cost alternative to conventional methods

This work presents the use of potentiometric measurements for kinetic studies of biosorption of Cd2+ ions from aqueous solutions on Eichhornia crassipes roots. The open circuit potential of the Cd/Cd2+ electrode of the first kind was measured during the bioadsorption process. The amount of Cd2+ ions accumulated was determined in real time. The data were fit to different models, with the pseudo-second-order model proving to be the best in describing the data. The advantages and limitations of the methodology proposed relative to the traditional method are discussed.

Delineamentos experimentais eficientes para estudos de cinética química

In this paper we show how to obtain efficient designs of experiments for fitting Michaelis-Menten and Hill equations useful in chemical studies. The search of exact D-optimal designs by using local and pseudo-Bayesian approaches is considered. Optimal designs were compared to those commonly used in practice using an efficiency measure and theoretical standard errors of the kinetic parameter estimates. In conclusion, the D-optimal designs based on the Hill equation proved efficient for estimating the parameters of both models. Furthermore, these are promising with respect to practical issues, allowing efficient estimation as well as goodness-of-fit tests and comparisons between some kinetic models.

A new approach to evaluate immobilization of β-galactosidase on Eupergit® C: structural, kinetic, and thermal characterization

This study aimed to evaluate β-galactosidase immobilization. For this purpose, the ionic strength of the buffer, reaction time, amount of the immobilization support, and pH were evaluated by a central composite design. Assay 8, which consisted of 1.5 mol L-1 phosphate buffer (pH 7.5) and a reaction time of 2 h, produced the maximum yield. Eupergit® C (400 mg) was subsequently used as an immobilization support. Immobilization kinetics wereinvestigated, and a significant increase in the yield was obtained after immobilization compared with that obtained from assay 8 (22.0 U mL-1 vs. 15.6 U mL-1). The enzyme efficiency of actuation was evaluated using o-nitrophenyl-β-D-galactopyranoside and lactose, with lactose providing better results. The reuse of β-galactosidase was evaluated, and more than 50% of the initial enzyme activity was maintained after five cycles of use. Enzyme characterization revealed that immobilization improved some aspects of the thermostability of β-galactosidase.

Preparation and evaluation of magnetic chitosan particles modified with ethylenediamine and Fe(III) for the removal of Cr(VI) from aqueous solutions

The adsorption of Cr(VI) in aqueous solution by magnetic particles of crosslinked chitosan-ethylenediamine-Fe(III) (MPCh-EDA-FeCL) was studied in a batch system. Fe3+ in the MPCh-EDA-FeCL permitted that adsorption of Cr(VI) occurred with maximum efficiency between pH 3 and 11. The maximum adsorption capacity at pH 7.0 was 81.04 mg g-1 at 25 ºC. The adsorption kinetic process was described by the pseudo-second-order model. Thermodynamic parameters indicated spontaneous, exothermic and chemical adsorption nature. The adsorbent was successively regenerated using a 0.1 mol L-1 NaOH solution. Results were satisfactory for treatment of wastewater from the electroplating industry.