Sample optimization, chemometric

Affinity capillary electrophoresis (ACE) constitutes a versatile microana-lytical technique that allows the estimation of affinity constants of analytes through the study of interactions such as protein-hgand, protein-antibody, and antibody-antigen. In ACE, PF techniques (whose optimization is not an easy task) can also be used to minimize the amount of sample needed. Chemometric methodology has also been applied for the optimization of the PF technique in ACE. 

The aim of this work is the optimization of distillation process using H SO for fluoride separation and potentiometric determination in anhydrite samples by means of chemometric tools. 

Key words in the definition are optimal and material systems . These express the fact that chemical analysis is related to a problem and not to a sample and that economical aspects of chemical analysis prevail. The result of chemometric research is chemometric software, which enable a large scale implementation and application of chemometric tools in practical chemical analysis. 

Exploration of a data set before resolution is a golden rule fully applicable to image analysis. In this context, there are two important domains of information in the data set the spectral domain and the spatial domain. Using a method for the selection of pure variables like SIMPLISMA [53], we can select the pixels with the most dissimilar spectra. As in the resolution of other types of data sets, these spectra are good initial estimates to start the constrained optimization of matrices C and ST. The spatial dimension of an image is what makes these types of measurement different from other chemical data sets, since it provides local information about the sample through pixel-to-pixel spectral variations. This local character can be exploited with chemometric tools based on local-rank analysis, like FSMW-EFA [30, 31], explained in Section 11.3. 

An efficient slurry health monitoring tool should be able to provide both chemical as well as abrasive particle information on a continuous basis. There have been some efforts in this direction using an NIR absorption spectrum based analyzer [19]. This unit can provide oxidizer concentration and abrasive particle information in CMP slurry and operates on the principles of chemometrics, which is a two-phase process. In the first calibration phase, samples with known property values are measured by the system. A mathematical procedure then determines the correlation between the measured spectra and the true property values. The output of this phase is a model that optimally calculates the parameter values from the measured spectra of the calibration samples. In the second measurement phase, unknown samples are measured by the system, employing a model to produce estimates of the property values. 

Chemometrics provides a means of contemporaneously analyzing sample data to optimize processes. Data sources may be spectral, wet chemistry or a combination. 

Several studies have employed chemometric designs in CZE method development. In most cases, central composite designs were selected with background electrolyte pH and concentration as well as buffer additives such as methanol as experimental factors and separation selectivity or peak resolution of one or more critical analyte pairs as responses. For example, method development and optimization employing a three-factor central composite design was performed for the analysis of related compounds of the tetracychne antibiotics doxycycline (17) and metacychne (18). The separation selectivity between three critical pairs of analytes were selected as responses in the case of doxycycline while four critical pairs served as responses in the case of metacychne. In both studies, the data were htted to a partial least square (PLS) model. The factors buffer pH and methanol concentration proved to affect the separation selectivity of the respective critical pairs differently so that the overall optimized methods represented a compromise for each individual response. Both methods were subsequently validated and applied to commercial samples. 

Chemometries has played two major roles in MEKC for analysis of the data collected from the separation and detection of analytes, and for efficient optimization of the separation conditions. Regarding data analysis, chemometrics can allow deconvolution of poorly resolved peaks (15,16) and quantification of the corresponding analytes. Chemometrics can also be employed for multivariate calibration (17), characterization of complex samples, and to study peak purity. Sentellas and Saurina have recently reviewed the role of chemometrics applied to data analysis in CE (18). For MEKC in particular, chemometrics has been used more widely as a tool for optimization of separation conditions. The focus of this chapter is to exemplify the utility of chemometric methods for the optimization of separation conditions in MEKC. 

TABLE 5.1. A summary of factors, responses, chemometric designs and methods, and validation criteria nsed by different gronps for the optimization of the separation of varions samples by MEKC... 

One of the current trends in separation science is the development of comprehensive or multidimensional separation systems, in which CE and CE-MS are also achieving relative importance. Chemometric approaches like the ones described in this chapter will surely be of great help for the optimization of these more complicated separation systems. Current trends toward miniaturization in separation science are also well known. Ultrafast separations, extremely low sample requirements, and automation of the arrangement are some of these goals. Chemometrics will surely provide an interesting and challenging approach for the optimization of separation conditions in these miniaturized systems, including microchips for years to come. 

Optimization of sample preparation using chemometric approaches 230... 

OPTIMIZATION OF SAMPLE PREPARATION USING CHEMOMETRIC APPROACHES... 

Advances in herbal medicines have hastened the need for high-throughput CE methods that can effectively screen and resolve numerous compounds in a short period of time. Chemometric experimental design and optimization techniques will continue to increase as new developments in sample preparation, method optimization, and data processing in (3E analysis of herbal medicines occur. 

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