Computer-assisted optimization for the selection of mobile phase in semi-preparative HPLC

A computer-assisted method is presented for optimization for the selection of mobile phasecomposition in semi-preparative HPLC.The optimization for the expected separation is based ona polynomial estimation from five preliminary runs.Statistical scanning technique was used foroptimization.Double criteria simulation system (DCSS) is established for chromatographic perfor-mance measurement in this method.The validity of the optimization strategy is confirmed by applyingit to a technical Cypermethrin separation.Excellent agreement is obtained between the predictedand experimental results.     

Computer-assisted optimization of temperature programming and flow rate in capillary gas chromatography

A computer-assisted method is presented for simultaneous optimization of three-factor of temperature programming (initial temperature, temperature rising rate and carrier gas flow rate) for the separation of eleven compounds in capillary gas chromatography. The optimization of the separation over the experimental region is based on a special polynomial from fifteen preliminary experiments using the resolution as the selection criterion. Computer scanning technique was used for optimum selection on three dimensions. Excellent agreement was found between the predicted data and the experimental results.     

Optimization of the separation of a mixture of unknown composition by reversed-phase HPLC

A method is presented for the computer-assisted optimization of mobile phaseselection for the separation of a synthetic intermediate of unknown composition by reversed-phase HPLC.The method is based on recognition of the order of the peaks by comparisonof peak area ratio and followed by the BSOS-L(Binary Solvent Optimization System forHPLC)method.Excellent agreement was obtained between predicted data and experimentalresults.     

Optimization separation of five phosphoamidothioate enantiomers using a series of silica and chiral column by high-performance liquid chromatography

A computer-assisted method is described for optimization of multi-component,mobile phase selection for separation of five phosphoamidothioate enantiomers with a series of silica and chiral columns in normal phase HPLC.The method is based on the triangular solvent selection concept using a statistical scanning method.The optimization of the separation over the experimental region is based on a special polynomial estimation from seven experimental runs,and resolution (Rs) is used as the selection criterion.Excellent agreement was obtained between predicted and experimental data.     

Computer-assisted optimization of mobile phase compositions and development distance selectivity in gradient two-step development high-performance thin-layer chromatography

A computer-assisted method is presented for optimization of mobile phase compositions and development distance in gradient two-step development HPTLC. The method is based on a system which can predict the final Rf values for gradient two-step development from values measured using five preliminary runs. The statistical scanning method is then used for optimization, using Rf difference as the selection criterion. The method was evaluated using a mixture of eight components. Excellent agreement was obtained between predicted and experimental results. Gradient two-step development HPTLC, mobile phase composition optimization, velopment distance optimizationde-     

A Hybrid Ant Colony Optimization for the Prediction of Protein Secondary Structure

Based on the concept of ant colony optimization and the idea of population in genetic algorithm, a novel global optimization algorithm, called the hybrid ant colony optimization （HACO）, is proposed in this paper to tackle continuous-space optimization problems. It was compared with other well-known stochastic methods in the optimization of the benchmark functions and was also used to solve the problem of selecting appropriate dilation efficiently by optimizing the wavelet power spectrum of the hydrophobic sequence of protein, which is the key step on using continuous wavelet transform （CWT） to predict a-helices and connecting peptides.