Optimization of xylitol recovery by crystallization from synthetic solutions using response surface methodology

Continuous Generation of Millimeter-Sized Glycine Crystals in Non-Seeded Millifluidic Slug Flow

Millimeter-sized α-glycine crystals were generated from continuous non-seeded cooling crystallization in slug flow. The crystallization process is composed of three steps in sequence: slug formation, crash-cooling nucleation, and growth. Stable uniform slugs of three different aspect ratios (slug length/tubing inner diameter) were formed, by adjusting the flow rates of both the solution and air streams. Besides supersaturation, the slug aspect ratio can also affect primary nucleation outcome. Stable slug flow can accommodate a relative supersaturation (C/C*) of up to 1.5 without secondary nucleation. Large glycine crystals can grow to millimeter size within 10 min, inside millimeter-sized slugs without reducing the slug quality.

Surfactant-bound monolithic columns for CEC

A novel anionic surfactant bound monolithic stationary phase based on 11-acrylaminoundecanoic acid is designed for CEC. The monolith possessing bonded undecanoyl groups (hydrophobic sites) and carboxyl groups (weak cationic ion-exchange sites) were evaluated as a mixed-mode stationary phase in CEC for the separation of neutral and polar solutes. Using a multivariate D-optimal design the composition of the polymerization mixture was modeled and optimized with five alkylbenzenes and seven alkyl phenyl ketones as test solutes. The D-optimal design indicates a strong dependence of electrochromatographic parameters on the concentration of 11-acrylaminoundecanoic acid monomer and porogen (water) in the polymerization mixture. A difference of 6, 8 and 13% RSD between the predicted and the experimental values in terms of efficiency, resolution and retention time, respectively, indeed confirmed that the proposed approach is practical. The physical (i.e. morphology, porosity and permeability) and chromatographic properties of the monolithic columns were thoroughly investigated. With the optimized monolithic column, high efficiency separation of N-methylcarbamates pesticides and positional isomers was successfully achieved. It appears that this type of mixed-mode monolith (containing both chargeable and hydrophobic sites) may have a great potential as a new generation of CEC stationary phase.

Surfactant-bound monolithic columns for separation of proteins in capillary high performance liquid chromatography

A surfactant-bound monolithic stationary phase based on the co-polymerization of 11-acrylamino-undecanoic acid (AAUA) is designed for capillary high performance liquid chromatography (HPLC). Using D-optimal design, the effect of the polymerization mixture (concentrations of monomer, crosslinker and porogens) on the chromatographic performance (resolution and analysis time) of the AAUA-EDMA monolithic column was evaluated. The polymerization mixture was optimized using three proteins as model test solutes. The D-optimal design indicates a strong dependence of chromatographic parameters on the concentration of porogens (1,4-butanediol and water) in the polymerization mixture. Optimized solutions for fast separation and high resolution separation, respectively, were obtained using the proposed multivariate optimization. Differences less than 6.8% between the predicted and the experimental values in terms of resolution and retention time indeed confirmed that the proposed approach is practical. Using the optimized column, fast separation of proteins could be obtained in 2.5 min, and a tryptic digest of myoglobin was successfully separated on the high resolution column. The physical properties (i.e., morphology, porosity and permeability) of the optimized monolithic column were thoroughly investigated. It appears that this surfactant-bound monolith may have a great potential as a new generation of capillary HPLC stationary phase.

Improvement of trypanocidal metabolites production by Aspergillus fumigatus using neural networks

An optimization procedure using artificial neural networks was developed to determine the optimal combination of parameters, such as medium culture, initial pH, temperature and time of fermentation for maximal trypanocidal metabolites production by Aspergillus fumigatus. A data set of 81 experiments was carried out and an artificial neural network was trained to identify the optimal conditions for this process. Good correlation was obtained between the experimental and predicted values of lysis of the trypomastigote forms of Trypanosoma cruzi (r2 = 0.9990). The simulations of fermentation performance were undertaken on combinations of input variables and the highest level of activity against T. cruzi was obtained from the chloroform extract of the modified Jackson medium culture, initial pH of 6.0, incubated at 40 degrees C for 144 h. It displayed lysis of 95% of the trypomastigote forms of T. cruzi and the red blood cells remained normal.