Statistical Mixture Design Research Articles

Statistical mixture design—Varimax factor optimization for selective compound extraction from plant material

Varimax-transformed chromatograms of compounds extracted from Erythrina speciosa Andrews leaves by simplex centroid design mixtures of dichloromethane, hexane, ethanol and acetone are reported and compared with principal component results. Six varimax factors were investigated focusing on the three main groups of extracted compounds with retention times of 1.7, 3.1 and 6.6 min. Varimax models provide chromatographic loading profiles that are simpler than their principal component counterparts. Furthermore varimax score models in terms of extraction medium compositions are simpler to interpret. The first varimax model results in an optimum extraction mixture of 71% dichloromethane–29% acetone although substitution of acetone by ethanol results in an almost identical extraction profile. The second varimax score model predicts optimum extraction binary mixtures with hexane proportions ranging from 50 to 100% for complementary proportions of either acetone or ethanol. The third varimax factor provides a response surface that is very similar to the one found for the third PC. Confirmatory experiments were performed to validate the model predictions.

Statistical mixture design – principal component optimization for selective compound extraction from plant material

A simplex centroid design is used to optimize solvent mixtures for selective extraction of compounds from Erythrina speciosa Andrews leaves. Three main groups of compounds characterized by chromatographic retention times of 1.7, 3.1, and 6.6 min were extracted. The chromatographic peak heights registered at 1407 equally spaced times for each design extract were converted into principal components (PCs). Three PCs account for 89.1% of the data variance and have important loading values at the above retention times. Quadratic mixture models were found to adequately describe the response surfaces of their PC score values. Maximizing the first PC scores while minimizing the second and third ones results in an optimum 83% dichloromethane-17% acetone mixture that selectively extracts the group of compounds with retention times around 3.1 min. Maximizing the second PC scores and minimizing the third PC scores leads to a 78% hexane-22% acetone mixture adequate for extracting the 6.6 min retention time compounds as well as other compounds with high retention times. The 1.7 min group of compounds is most efficiently extracted on maximizing the third PC that results in a 50% ethanol-50% acetone mixture. The Derringer-Suich algorithm confirmed the determination of these optimized mixtures.

Multivariate chromatographic fingerprint preparation and authentication of plant material from the genus Bauhinia

Multivariate analysis and statistical mixture designs were used for chromatographic fingerprint preparation and authentication of the plant material of three species of the genus Bauhinia. The extracts were analysed by reversed-phase high-performance liquid chromatography. Mixture design gave an optimum solvent composition for extracting components from the plants of 36% dichloromethane, 17% ethanol and 47% ethyl acetate (by volume), while an optimum mobile phase for chromatographic analyses was found to be 27% methanol, 27% acetonitrile and 46% of water (by volume). Results from principal component analysis, hierarchical analysis and soft independent modelling by class analogy showed that Bauhinia candicans cannot be synonymous with B. forficata Link. It was also possible to trace the metabolic profile without identifying its chemical constituents and to determine a chromatographic discriminating region. The characteristics responsible for discrimination between B. candicans and B. forficata were more polar substances that presented peaks with retention times around 1.65 and 1.81 min.

Optimisation of Natural Ingredient Based Lipstick Formulation by Using Mixture Design

The cosmetic industry in Malaysia is proven to be one of the important economy sources. Lipstick is one of the decorative cosmetic products that command a unique market. The quality of lipstick is directly linked to the basic material used in the formulation. The ratio of the ingredients used determines the final product characteristics. In previous researches, statistical mixture design has been proved to be effective tool to investigate the relationship between variables in formulation work. Contour graphics were formed to assess the change in the response surface in order to understand the relationship between the product cost and consumer acceptance of the lipsticks. In this work, natural waxes, solvents and colorant were used to prepare lipstick formulation. Statistical mixture design has been applied for experimental setting for the components system. The effects of the mixture components on the physical properties and consumer acceptance of the lipstick have been investigated. The results indicate that the physical properties of the lipstick can be manipulated by changing the composition of the base ingredient used in the formulation. It was found that the variation of the mixture component affected the consumer acceptance on lipstick's rub-off characteristic. © 2007 Asian Network for Scientific Information.

Statistical mixture design optimization of extraction media and mobile phase compositions for the characterization of green tea

The influence of different solvents on the extraction medium and the RP-HPLC mobile phase composition were investigated by statistical mixture designs to optimize solvent proportions to prepare the fingerprint of a medicinal herbal extract. For modeling, the number of peaks was used as a measure of fingerprint information. The optimum compositions of solvent to extract chemical substances from green tea and for mobile phase chromatographic analysis were ethyl acetate/ ethanol/dichloromethane (20:5:75 v/v/v) and MeOH/ACN/water (7.5:57.5:35 v/v/v), respectively. This system results in 26 peaks in the chromatographic fingerprint. These results show that an incorrect choice of modifiers for mobile phase composition and solvent extraction hampers the detection of a maximum number of peaks and produces a poor chromatographic fingerprint.

Feedstock Optimization of In-Vessel Food Waste Composting Systems for Inactivation of Pathogenic Microorganisms

An optimum composting recipe was investigated to reduce pathogenic microorganisms in a forced-aerated in-vessel system (55 liters). The feedstocks used for in-vessel composting were food waste, cow manure, and bulking materials (wood shavings and mulch hay). A statistical extreme vertices mixture design method was used to design the composting experiments and analyze the collected data. Each mixture (nine total) was replicated randomly three times. Temperature was monitored as an indicator of the efficiency of the composting experiments. The maximum temperature values of the mixtures were used as a response for both extreme vertices mixture design and statistical analyses. Chemical changes (moisture content, carbon/nitrogen ratio, volatile solids, and pH) and reductions of indicator (fecal coliforms and fecal streptococci) and pathogenic microorganisms (Salmonella and Escherichia coli O157:H7) were measured by the most-probable-number method before and after a 12-day composting period. Maximum temperatures for the tested compost mixtures were in the range of 37.0 to 54.7°C. Extreme vertices mixture design analysis of the surface plot suggested an optimum mixture containing 50% food waste, 40% manure, and 10% bulking agents. This optimum mixture achieved maximum temperatures of 54.7 to 56.6°C for about 3.3 days. The total reduction of Salmonella and E. coli O157:H7 were 92.3%, whereas fecal coliforms and fecal streptococci reductions were lower (59.3 and 27.1%, respectively). Future study is needed to evaluate the extreme vertices mixture design method for optimization of large-scale composting.

Halogenated aromatics from steel production: results of a pilot-scale investigation

The potential environmental impact of emissions of halogenated aromatics from the steel industry is of growing concern. It has been suggested that electric arc furnaces are the only industrial source with constant or increasing emissions of dioxins to air. Here the results are reported from a pilot plant study on how scrap composition and various treatment alternatives affect the formation and release of chlorinated and brominated aromatics. The experiments were conducted with a statistical mixture design, and it is shown that scrap composition has a significant impact on the outcome. In contrast, the various treatment schemes examined––shredding, disassembly, and briquetting––did not affect the formation and release of halogenated aromatics. Parallel experiments with injection of adsorbents showed that it is possible to reduce emissions without substantial investments, and this option is recommended as a low-cost solution.

Prediction of submerged arc weld‐metal composition from flux ingredients with the help of statistical design of mixture experiment

A prediction model has been developed for submerged arc weld‐metal chemical composition in terms of flux ingredients with the help of statistical experiments for mixture (extreme vertices design). Bead‐on‐plate weld deposits as per statistical mixture design experiments were performed at the following welding parameters: current (400 A), voltage (26 V), speed (4.65 mm/s) and electrode extension (30 mm) using CaO–MgO–CaF2–Al2O3 flux system. The results show that some of the individual flux ingredients and their binary mixtures have a predominant effect on weld‐metal oxygen, manganese, silicon, sulphur, nickel and carbon content. The predicted results show a reasonably good agreement with the experimental results, which were obtained by performing the actual experiments based on a randomly designed flux. Analysis of the experimental data indicate that several mechanisms such as basicity index, oxygen potential, oxide stability, viscosity, electrode chemical reaction, kinetics of slag–metal reaction, etc. are operating simultaneously to yield the final weld‐metal composition.

Partitioning and speciation of chromium, copper, and arsenic in CCA-contaminated soils: influence of soil composition

This study focused on the influence of soil composition and physicochemical characteristics on the retention and partitioning of Cu, Cr and As in nine chromated copper arsenate (CCA) artificially contaminated soils. A statistical mixture design was used to set up the number of soils and their respective composition. Sequential extraction and modified solvent extraction were used to assess Cu and Cr partitioning and As speciation [As(III) or As(V)]. It was found that peat had a strong influence on CEC (232 meq/100 g), on buffer capacity and on Cu and Cr retention, whereas kaolinite's contribution to the CEC was minor (38 meq/100 g). Average metal retention in mineral soils was low (58% for Cu and 23% for Cr) but increased dramatically in highly organic soils (96% for Cu and 78% for Cr). However, both organic and mineral soils demonstrated a very high sorption of added As (71–81%). Levels of Cu and Cr in a soluble or exchangeable form (F1) in highly organic soils were very low, whereas the levels strongly bound to organic matter were much higher. Conversely, in mineral soils, 47% of Cu and 18% of Cr were found in F1. As a result, Cr and Cu in moderately and highly organic contaminated soils were present in less mobile and less bioavailable forms, whereas in mineral soils, the labile fraction was higher. The modified method used for selective determination of mineral As species in CCA-contaminated soils was found to be quantitative and reliable. Results revealed that arsenic was principally in the pentavalent state. Nevertheless, in organic soils, arsenite was found in significant proportions (average value of 29% in highly organic soils). This indicates that some reduction of arsenate to arsenite occurred since the original species in CCA is As(V).

Study of the Separation of Dianin's Compound Formed in the Bisphenol-A Synthesis

A method of separating Dianin'scompound from a complex mixture of by-productsobtained from the bisphenol-A industrial processis described using compounds which formcrystalline clathrate structures with Dianin'scompound. Under the conditions used the clathratestructure obtained could be crystallized with highpurity (above 99.5%). The described statistical modelof mixture design shows that the highest yield ofcrystallization was found by using a single solvent(ethyl alcohol) for separation of Dianin's compound.

HPLC Method Development for Duloxetine Hydrochloride Using a Combination of Computer-Based Solvent Strength Optimization and Solvent Selectivity Mixture Design

Abstract Computer simulation software for solvent strength optimization and statistical mixture design based on the solvent | selectivity triangle were useful tools employed for the development of a reversed-phase HPLC method to separate duloxetine, a new anti-depressant compound, and structurally-related impurities. Solvent strength optimization was used to show that adequate separation for all impurities could not be obtained with a single organic modifier and to aid in choosing appropriate boundary conditions for a mixture design study. The mixture design was used to obtain resolution maps for organic modifier mixtures consisting of acetonitrile, methanol, and tetrahydrofuran. Overlapping resolution maps for the peak pairs of interest revealed the solvent composition that would provide the maximum resolution. Finally, solvent strength was optimized at the best solvent composition and information about method robustness obtained.

Statistical Mixture Design Applied to RP-HPTLC Chromatographic Separations of Amino Acid Hydroxamates

Abstract Mixture Design and a Chromatographic Response Function were used to study the effect of different organic solvents as modifiers on the Reversed Phase (C-18) High Performance Thin Layer Chromatographic separation of three amino acid hydroxamates (Arginine hydroxamate, Threonine hydroxamate, and Histidine hydroxamate). Both 3 solvent (methanol, acetonitrile and tetrahydrofuran) and 4 solvent (methanol, acetonitrite, tetrahydrofuran and acetone) systems were studied.

The Use of a 3-Factor Statistical Mixiure Design and a 2-Factor Chromatograhic Response Function to the RP-HPLC Separation of Several Free α-Amino Acids

Abstract A 3-factor statistical mixture design and a 2-factor chromatographic response function were used in the solvent optimization of the RP-HPLC separation of a mixture containing free histidine, methionine, tyrosine, phenylalanine and tryptophan. The influences of phosphoric acid, methanol and acetonitrile on the separation were compared. A solvent condition resulting in a satisfactory separation of the amino acid mixture was predicted.

Development and optimisation of a high-performance liquid chromatographic assay for tioconazole and its potential impurities : I. Selection of separation conditions

Statistical mixture design techiques have been utilized to develop an isocratic high-performance liquid chromatographic separation of 1-{2-(chloro-3-thienyl)-methoxy]-2-(2,4-dichlorophenyl)ethyl}-1H-imidazole (tioconazole) and its potential impurities. By using suitable quality criteria such as reduced plate height, peak asymmetry and selectivity for the interrogation of chromatograms the variables producing best column efficiency and greatest selectivity have been identified. The optimum separation for these variables has been located by the sequential simplex approach and confirmed by response surface mapping.

Use of Statistical Mixture Designs to Evaluate Ternary Mixtures of Organics as Corrosion Inhibitors

Abstract Corrosion inhibitors are often mixtures of compounds which may or may not behave as a linear comination of the pure components in the mixture. Evaluation of the effect of the composition of the mixture on its inhibitory properties are often done on fragmentary data and there is an incomplete knowledge of the system being studied. Mixture Designs can be used to plan experiments which provide equations to model the system being studied.