Principal component analysis and cluster analysis for the characterisation of marbles by capillary electrophoresis

Chemical characterisation has been carried out on 25 quarry marbles collected from Marmara, Aegean and Thrace regions of Turkey. Ten elements were determined by capillary electrophoresis (CE). Principal component analysis and cluster analysis techniques were utilised to define grouping of different marble samples. These techniques showed that the analysed marbles were differentiable mainly by provenance. Experimental conditions such as pH, applied voltage and concentration of α-hydroxyisobutyric acid (HIBA) were optimised to achieve the best separation of metal ions using central composite design. The optimum pH 3.7, applied voltage 15 kV and concentration of HIBA 10 mM were found to provide the best separation for all metal ions investigated.     

Principal component and cluster analyses as supporting tools for co-crystals detection

The effects of super absorbent polymer (SAP) on the early hydration evolution of Portland cement within 72 h were investigated by isothermal calorimetry, thermal analysis and X-ray diffraction analysis. The results show that the SAP definitely affects the early hydration process of Portland cement, increases the hydration heat evolution rate during the acceleration period and during the main exothermic peak, promotes the earlier appearance of the main exothermic peak, but does not affect the lengths of the initial reaction period and the induction period and the onset of the acceleration period. The SAP can accelerate cement hydration to increase the hydration degree within 72 h. But the dosage variation of SAP has minor influence on the hydration heat evolution and hydration degree. The SAP enhances the formation of Ca(OH)₂ after 12 h to keep higher content than that in the reference paste. The SAP does not affect the maximum content of ettringite, but delays the conversion of ettringite to monosulphate to remain ettringite content higher at later hydration time. Besides, no new phases are found to have formed in cement paste with SAP.     

Principal component analysis and hierarchical cluster analysis for homogeneity evaluation during the preparation of a wheat flour laboratory reference material for inorganic analysis

The development of a homogeneity study during the preparation of a wheat flour laboratory reference material (LRM) for use in the quantification of metals and metalloids is reported. Inductively coupled plasma optical emission spectrometry (ICP OES) was used with validation performed using a certified reference material of wheat flour furnished by the National Institute of Standards and Technology (NIST). Copper, iron, manganese, phosphor, strontium and zinc were studied in a within-bottle homogeneity test whereas barium, copper, iron, zinc, manganese, strontium, phosphor and calcium were included in a between batch homogeneity study. Standard univariate analysis of variance (ANOVA) was performed for all analytes. Furthermore an alternative multivariate analysis for homogeneity is proposed by performing ANOVA of principal component scores and by inspection of principal component score graphs and hierarchical cluster analysis dendrograms. The ANOVA F-tests performed on both, the univariate and multivariate parameters, were not significant at the 95% confidence level and indicated homogeneous wheat flour samples. A 10 kg amount of material was processed, which was distributed in 100 bottles, each containing 100 g. For the between-bottle homogeneity test, three replicates were taken from each of 10 bottles selected of the 100 bottles obtained. The results were evaluated using an F-test, which demonstrated no significant difference for the between-bottle results. It is indicative that this material is homogeneous. Afterwards, the influence of the sample mass on the homogeneity of the material was also evaluated by quantification of the elements for 100, 300, 500, 700 and 1000 mg sample masses with all the experiments being performed in triplicate. The F-test was also used for evaluation of these results and demonstrated that the material is homogeneous for masses taken in the 100 to 1000 mg range. All these results were further evaluated employing the principal component analysis (PCA) and hierarchical cluster analysis (HCA) multivariate techniques. Both techniques also demonstrated that the material is perfectly homogeneous for use as laboratory reference material.     

Principal component analysis of dipeptides

Principal component analysis applied to a set of dipeptides illustrates how changes in families of parameters act in concert to produce overall molecular structural changes. Principal component analysis is an eigenvalue–eigenvector analysis whereby the parametric sensitivity coefficient matrix is manipulated to produce weighted principal components, which reveal the variant and invariant directions in the parameter space. This analysis summarizes the sensitivity results by revealing interdependence among the parameter values with regard to their role in controlling the molecular structure. An analysis of the principal components reveals hidden relationships among the parameters. Thus, those parameters, which were thought to be of controlling significance with respect to the molecular structure, may, in fact, not be (or vice versa) due to cooperative parametric interactions; as a result, the parameters of significance in a sequence of dipeptides are identified. In general, for the dipeptides studied, there is mutual exclusion of dominant parameters between the sets of invariant and variant eigenvectors. © 1994 by John Wiley & Sons, Inc.     

Principal component analysis of kinetic models

An eigenvalue–eigenvector analysis is used to extract meaningful kinetic information from linear sensitivity coefficients computed for several species of a reacting system at several time points. The main advantage of this method lies in its ability to reveal those parts of the mechanism which consist of strongly interacting reactions, and to indicate their importance within the mechanism. Results can be used to solve three general kinetic problems. Firstly, an objective condition for constructing a minimal reaction set is presented. Secondly, the uncovered dependencies among the parameters are shown to confirm or deny validity of quasi-steady-state assumptions under the considered experimental conditions. Thirdly, taking into account only sensitivities of observed species, the analysis is used to yield error estimates on unknown parameters determined from the experimental observations, and to suggest the parameters that should be kept fixed in the estimation procedure. To illustrate we chose the well-known hydrogen–bromine reaction and the kinetics of formaldehyde oxidation in the presence of CO.     

Principal component analysis with boundary constraints

Observed data often belong to some specific intervals of values (for instance in case of percentages or proportions) or are higher (lower) than pre‐specified values (for instance, chemical concentrations are higher than zero). The use of classical principal component analysis (PCA) may lead to extract components such that the reconstructed data take unfeasible values. In order to cope with this problem, a constrained generalization of PCA is proposed. The new technique, called bounded principal component analysis (B‐PCA), detects components such that the reconstructed data are constrained to belong to some pre‐specified bounds. This is done by implementing a row‐wise alternating least squares (ALS) algorithm, which exploits the potentialities of the least squares with inequality (LSI) algorithm. The results of a simulation study and two applications to bounded data are discussed for evaluating how the method and the algorithm for solving it work in practice. Copyright © 2007 John Wiley & Sons, Ltd.     

Principal component analysis of the infrared spectra of mixtures

Principal component analysis of the infrared spectra of a series of related mixtures is used to determine the number of compounds present. The use of empirical error estimates makes it possible to determine correctly the number of components even when the spectra of the individual compounds are very similar.     

Principal component analysis and multicomponent surface free energy theories

The same underlying mathematical structure characterizes some of the most popular multicomponent models for the prediction of surface free energies and adhesion works. After a brief illustration of the general methods for the computation of liquid and solid components in typical multicomponent theories, it is shown that both model definition and component estimate may take great advantage from application of Principal Component Analysis techniques, owing to the very peculiar structure of adhesion work equations. It is also put into evidence that a problem of scale multiplicity arises as a consequence of the symmetries involved in the model equations for adhesion work and surface free energy. A special discussion is devoted to the specific cases of van Oss–Chaudhury–Good acid–base theory, Qin–Chang model and extended Drago theory, which constitute the most common multicomponent models usually applied in the analysis of adhesion phenomena.      

Principal component and decomposition analysis of multicomponent mixtures of carcinogenic fluorophores

A series of binary and tertiary mixtures of polycyclic aromatic hydrocarbons is analyzed by using principal component and decomposition analysis of molecular fluorescence spectra. The results demonstrate the ability to determine the number and identity of species that are present. Failures caused by high correlation among spectra are considered.     

Thermal characterization of dental composites by TG/DTG and DSC

Dental composites can be improved by heat treatment, as a possible way to increase mechanical properties due to additional cure (post-cure). Direct dental composites are essentially similar to the indirect ones, supposing they have the same indication. Therefore, to establish a heat treatment protocol for direct composites, using as indirect (photoactivated by continuous and pulse-delay techniques), a characterization (TG/DTG and DSC) is necessary to determine parameters, such as mass loss by thermal decomposition, heat of reaction and glass transition temperature (T _g). By the results of this study, a heat treatment could be carried out above 160 °C (above T _g, and even higher than the endset exothermic event) and under 180 °C (temperature of significant initial mass loss).     

Principal component analysis: a chemometric aid for classification of polluted and unpolluted mussels

Ten trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb) were determined in the dissolved ash of the edible part of wild mussels (28 samples) from a polluted site by electrothermal atomic absorption spectrometry. The distribution of the concentration of each element in the mussels was first investigated by means of a test of normality. The correlation matrix around the mean was used as a starting matrix for principal component analysis (PCA). Ten variables were reduced to two principal components, accounting for 77% of the total variance; Al, Cr, Mn, Fe, Zn, Cd and Pb are all positively associated with the first principal component and form a cluster of variables, indicating a common terrigenous origin. Comparison with 43 samples of unpolluted mussels from a nearby hatchery, on the basis of eight common variables (concentration of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb; 71 samples) by using a two-dimensional plot of PC scores, allows the mussels from the two sites to be differentiated.     

Principal component analysis of dipole moment derivative signs of chloroform

The use of principal components as a basis for a graphical procedure to analyze polar tensor data is proposed. Molecular orbital and experimental polar tensor data for all possible sign combinations of the ? p /?Q_j of CHCl₃ and CDCl₃ are represented graphically as principal component scores facilitating sign selection for the ? p /?Q_j. The graphs are particularly useful in analyzing an apparent conflict in ? p /?Q_j sign choices based on the isotopic invariance criterion and molecular orbital results for the A₁ symmetry species of these molecules. The numerical impacts of individual sign ambiguities for the ? p /?Q_j on the polar tensor data are measured by the variances associated with the principal components. Assuming the ? p /?Q_j sign sets with indeterminate signs provide replicated results for the polar tensor elements, their errors are estimated and compared with errors obtained previously by propagating intensity uncertainties through the polar tensor equations.     

Principal component analysis of the 13C NMR spectra of enamino ketones

The ¹³C NMR spectra of eleven 3-N,N-dialkylamino-5,5-dimethylcyclohex-2-en-1-ones have been determined. The chemical shifts of the three sp² carbons and of the two methylene carbons on the cyclohexenone moiety have been subjected to factor analysis. Two factors are necessary and sufficient to account for more than 93% of the total variance. The more important axis (79%) corresponds to a factor closely related to the inductive and steric effects of the alkyl nitrogen substituents. The second parameter is more difficult to interpret and could correspond to the ‘ipso effects’ of amino groups.     

Principal component analysis applied to collisionally-activated-decomposition mass spectra of alkylbenzenes

Pattern recognition of the level-1 type is applied to collisionally-activated-decomposition (c.a.d.) mass spectra of eight isomeric C₉H₁₂ alkylbenzenes. Principal component analysis is used for data compression. Only masses with a relative intensity above a variable threshold are selected; no autoscaling is used. Various criteria for deducing the number of factors are compared; because of the error structure, the 3s-misfit and chi-squared criteria are most suitable. The principal components technique produces three factors describing four different groups of c.a.d. mass spectra, those corresponding to n-propyl-, isopropyl-, ethylmethyl- and trimethyl-benzene molecular ions.     

Principal component analysis of polarity and interaction parameters in inverse gas chromatography

Inverse gas chromatography is used in the characterization of aliphatic-aromatic and aromatic ketones, their oximes, and ketone-oxime or oxime-oxime mixtures. All these organic materials are used as liquid stationary phases in gas chromatographic columns. A series of polarity and Flory-Huggins interaction parameters are determined and used to describe the physicochemical properties of examined materials, metal extractants, and products of their degradation. Principal component analysis (PCA) is performed on a data matrix consisting of polarity and interaction parameters for ketones, their oximes, and mixtures. The calculations are carried out on the correlation matrix. It is found that seven principal components account for more than 95% of the total variance in the data, indicating that the polarity (interaction) parameters are not correlating well. Physical meanings are attributed to the principal components, the most influential ones being that the first and the second principal components account for several Flory-Huggins interaction parameters, whereas the fifth is correlated with criterion "A". The plots of component loadings show characteristic groupings of polarity indicators, whereas that of component scores show several groupings of stationary phases. Cluster analysis provides mainly the same groupings. PCA allows for the grouping of polarity and solubility parameters based on the information carried within those parameters. There is no need to use more than one parameter from each cluster. McReynolds polarity and the partial molar excess Gibbs free energy of solution per methylene group carry the same information. The groups of ketones, oximes, and their mixtures can be distinguished with the use of PCA on the basis of the measured polarity, solubility parameters, or both.     

Principal component analysis of the absorption and resonance Raman spectra of the metallochromic indicator antipyrylazo III

Metallochromic indicators, whose spectral properties are changed in the presence of metal cations, are used mainly in biological studies to monitor Ca2+ and Mg2+ ions. Antipyrylazo III is such indicator, employed for mid-range Ca2+ concentrations (10-1000 microM). The stoichiometry of the interactions of antipyrylazo III with Ca2+, Mg2+, Ba2+, Sr2+ and Zn2+ ions and the relevant binding constants were studied by principal component analysis (PCA) of the absorption spectral changes. The resonance Raman spectra of the above systems were measured as well, and the resolved Raman spectra of the various species were calculated and assigned. The vibrational spectra are more featured, more characteristic of the binding ions and exhibit stronger relative spectral changes upon binding the cations. The basis sets of Raman spectra could thus be used as an analytical tool for these divalent metallic cations.     

Synthesis,characterization and evaluation of new fluorene‐based dimethacrylates for formulating dental composites

This study focused on the preparation and evaluation of several new fluorene‐based dimethacrylates, as possible intermediates to formulate improved dental composites. As the first step towards modification of the composite formulation, the new monomers and unfilled resin matrix were prepared. The formulated and visible light‐cured materials were found to be more hydrophobic, along with having higher wet (water saturated) glass transition temperatures (T_g) than the commonly used matrix resins based on 2,2‐bis(4(2‐hydroxy‐3‐methacryloxy‐propyloxy))‐phenylpropane (Bis GMA). In addition, the new matrix resins exhibited greater compressive strength, along with greater resistant to creep and fracture. Finally, the results suggested a correlation may exist between creep and the homologous temperature (T/T_g) of the light‐cured neat resins, where the T/T_g may be used to compare the mechanical properties of different materials at various temperature. Copyright © 1999 John Wiley & Sons, Ltd.     

Principal component analysis for the selection of variables in the application of the H-point and generalised H-point standard addition method

The present paper deals with the selection of variables for the H-point and generalised H-point standard additions methods (HPSAM and GHPSAM, respectively). Both methods are applied for the resolution of spectroscopic interfered signals in the UV-vis range. The HPSAM is a suitable method for the resolution of binary and ternary mixtures when the interferent is known. The GHPSAM is applied for the resolution of samples that contain unknown interferents. In this paper, a method based on the study of a principal components analysis (PCA) for the selection of variables for the HPSAM and GHPSAM is proposed. The PCA results show the isolation of the analyte signal from the sample signal, achieved by the application of the HPSAM and GHPSAM. It is showed that by means of the score and loading plots, it is possible to select the most appropriate variables without a priori establishing any condition.     

Principal component analysis of thermal decomposition of magnesium salts used as drugs

Thermal decomposition of magnesium salts of organic acids used in medicine (Mg acetate, Mg valproate, Mg lactate, Mg citrate, Mg hydrogen aspartate, Zn hydrogen aspartate) was analyzed by thermoanalytical, calorimetrical, and computational methods. Thermoanalytical studies were performed with aid of a derivatograph. 50-, 100-, and 200-mg samples were heated in a static air atmosphere at a heating rate of 3, 5, 10, and 15 °C min⁻¹ up to the final temperature of 700–900 °C. By differential thermal analysis (DTA), thermogravimetry (TG), and derivative thermogravimetry (DTG) methods, it has been established that thermal decomposition of the salts under study occurs via two stages. The first stage (dehydratation) was distinctly marked on the thermoanalytical curves. Calorimetrical studies were carried out by using of a heat-flux Mettler Toledo differential scanning calorimetry (DSC) system. Ten milligram samples of compounds under study were heated in the temperature range from 20 to 400 °C at a heating rate of 10 and 20 °C min⁻¹ under an air stream. The studies showed that the values of transitions heats and enthalpies of dehydration for investigated salts varied with the increasing of heating rate. For chemometric evaluation of thermoanalytical results, the principal component analysis (PCA) was applied. This method revealed that points on PC1 versus PC2 diagrams corresponding to the compounds of similar chemical constitution are localized in the similar ranges of the first two PC’s values. This proves that thermal decomposition reflects similarity in the structure of magnesium salts of organic acids.