Cement classification and characterization using Non-Invasive techniques.

Cement is one of the most widely used materials in the global construction industry, serving as an adhesive and binder in projects that require strength and durability. Additionally, cement production indicates a country's development and economic activity, with global production reaching approximately 4 billion tons annually. It is a fine powder composed mainly of lime, silica, iron oxide, and alumina.

A new constraint to model background signals when processing chromatographic-spectral second-order data with multivariate curve resolution.

Background: the chemometric processing of second-order chromatographic-spectral data is usually carried out with the aid of multivariate curve resolution-alternating least-squares (MCR-ALS). When baseline contributions occur in the data, the background profile retrieved with MCR-ALS may show abnormal lumps or negative dips at the position of the remaining component peaks.

Results: The phenomenon is shown to be due to remaining rotational ambiguity in the obtained profiles, as confirmed by the estimation of the boundaries of the range of feasible bilinear profiles.

Interpretation of matrix chromatographic-spectral data modeling with parallel factor analysis 2 and multivariate curve resolution.

Parallel factor analysis 2 (PARAFAC2) is still being advocated for the processing of second-order chromatographic-spectral data, both for qualitative and quantitative applications. However, neither classical PARAFAC2 nor the newly developed flexible non-negative NN-PARAFAC2 version can adequately model these data in a general situation. In quantitative analysis, considerable bias may result in the estimation of analyte concentrations, due to the fact that both PARAFAC2 models apply an artificial constraint to the retrieved profiles, requiring constant cross-product, i.

Excitation-emission fluorescence-kinetic third-order/four-way data: Determination of bisphenol A and nonylphenol in food-contact plastics.

The endocrine disrupting chemicals bisphenol A (BPA) and 4-nonylphenol (NP) were simultaneously quantified through third-order/four-way calibration. Excitation-emission fluorescence matrix-kinetic (EEFM-K) third-order data were generated by measuring the EEFMs of these priority xenoestrogens as a function of reaction time during their Fenton degradation. Third-order/four-way calibration notably improves the sensitivity of the method and provides the required selectivity for quantifying analytes with critically overlapped fluorescence signals.

Multivariate curve resolution strategy for non-quadrilinear type 4 third-order/four way liquid chromatography-excitation-emission fluorescence matrix data.

For the first time, a third-order/four-way system having instrumental modes depending on each other was experimentally generated and it was successfully resolved. Non-quadrilinear type 4 data, constituted by liquid chromatographic elution times (LC) and excitation-emission fluorescence matrices (EEFMs), were on-line measured using conventional equipment. Thus, third-order/four-way data, valuable for giving rise to highly sensitive and selective methods, were obtained minimizing significantly the experimental work and time, in comparison with the reported strategies for the acquisition of LC-EEFM data.

On-line generation of third-order liquid chromatography-excitation-emission fluorescence matrix data. Quantitation of heavy-polycyclic aromatic hydrocarbons.

For the first time, third-order liquid chromatography with excitation-emission fluorescence matrix detection (LC-EEFM) data were generated on-line and chemometrically processed for the simultaneous quantitation of the heavy-polycyclic aromatic hydrocarbons fluoranthene, pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, benzo[a]pyrene, and dibenz[a,h]anthracene. The applied experimental strategy is very simple, and is based on the reduction of the linear flow rate by fitting a larger diameter connecting-tube between the column outlet and the fluorimetric detector. In this way, EEFMs were successfully recorded on-line, without involving a large total analysis time.

Multivariate curve resolution applied to kinetic-spectroscopic data matrices: Dye determination in foods by means of enzymatic oxidation.

In this work, the combination of chemometric techniques with kinetic-spectroscopic data allowed quantifying two dyes (tartrazine and carminic acid) in complex matrices as mustard, ketchup, asparagus soup powder, pumpkin soup powder, plum jam and orange-strawberry juice. Quantitative analysis was performed without the use of tedious sample pretreatment, due to the achievement of the second-order advantage. The results obtained showed an improvement in simplicity, speed and cost with respect to usual separation techniques, allowing to properly quantifying these dyes obtaining limits of detection below 0.

Excitation-emission fluorescence-kinetic data obtained by Fenton degradation. Determination of heavy-polycyclic aromatic hydrocarbons by four-way parallel factor analysis.

For the first time, a simple and environmentally friendly third-order/four-way calibration was applied for the simultaneous determination of five heavy-polycyclic aromatic hydrocarbons (PAHs) in interfering environments. The kinetic evolution of the Fenton degradation of benzo[a]pyrene, dibenz[a,h]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene and benz[a]anthracene was followed by recording full excitation-emission fluorescence matrices (EEFMs) of the samples at different reaction times, obtaining third-order EEFM-kinetic (EEFM-K) data. The sensitivity of the method was increased by carrying out the reaction in the presence of methyl-β-cyclodextrin.

Scope of partial least-squares regression applied to the enantiomeric composition determination of ketoprofen from strongly overlapped chromatographic profiles.

Valuable quantitative information could be obtained from strongly overlapped chromatographic profiles of two enantiomers by using proper chemometric methods. Complete separation profiles where the peaks are fully resolved are difficult to achieve in chiral separation methods, and this becomes a particularly severe problem in case that the analyst needs to measure the chiral purity, i.e.

Recent applications of first- and second-order multivariate calibration to analytical chemistry.

This report reviews recent literature on the application of multivariate calibration techniques to both first- and second-order data, aimed at the analytical determination of analytes of interest or sample properties in a variety of industrial, pharmaceutical, food, and environmental samples, including examples of process control. The most used data processing tools are briefly described, with emphasis on the advantages that can be obtained by applying specific combinations of multivariate data and algorithms. The main focus is on works devoted to first-order data (i.

Determination of five pesticides in juice, fruit and vegetable samples by means of liquid chromatography combined with multivariate curve resolution.

The aim of this work was to quantify five commonly used pesticides (propoxur, carbaryl, carbendazim, thiabendazole and fuberidazole) in real samples as: tomato, orange juice, grapefruit juice, lemon and tangerine. The method used for the determination of these analytes in the complex matrices was high-performance liquid chromatography with diode array detection. In order to work under isocratic conditions and to complete each run in less than 10 min, the analysis was carried out applying multivariate curve resolution coupled to alternating least-squares (MCR-ALS).

Determination of enantiomeric composition of ibuprofen in pharmaceutical formulations by partial least-squares regression of strongly overlapped chromatographic profiles.

In this report, we demonstrate how chiral liquid chromatography combined with multivariate chemometric techniques, specifically unfolded-partial least-squares regression (U-PLS), provides a powerful analytical methodology. Using U-PLS, strongly overlapped enantiomer profiles in a sample could be successfully processed and enantiomeric purity could be accurately determined without requiring baseline enantioresolution between peaks. The samples were partially enantioseparated with a permethyl-β-cyclodextrin chiral column under reversed-phase conditions.

A review on second- and third-order multivariate calibration applied to chromatographic data.

Quantitative analytical works developed by processing second- and third-order chromatographic data are reviewed. The various modes in which data of complex structure can be measured are discussed, with chromatographic separation providing either one or two of the data dimensions. This produces second-order data (matrices from uni-dimensional chromatography with multivariate detection or from two-dimensional chromatography) or third-order data (three-dimensional data arrays from two-dimensional chromatography with multivariate detection).

Chemometrics-assisted fluorimetry for the rapid and selective determination of heavy polycyclic aromatic hydrocarbons in contaminated river waters and activated sludges.

The most concerned polycyclic aromatic hydrocarbons (PAHs) benzo[a]pyrene, dibenz[a,h]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene and benz[a]anthracene were simultaneously determined in the presence of other 10 interfering PAHs, applying second-order multivariate calibration to the data obtained with a flow-through optosensor interfaced to a fast-scanning spectrofluorimeter. Using a sample volume of 2.5 mL, detection limits in the range 5-115 ng L(-1) were obtained in interfering samples, with a sample frequency of ca.

Non-trilinear chromatographic time retention-fluorescence emission data coupled to chemometric algorithms for the simultaneous determination of 10 polycyclic aromatic hydrocarbons in the presence of interferences.

Multivariate calibration coupled to high-performance liquid chromatography-fast scanning fluorescence spectroscopy (HPLC-FSFS) was employed for the analysis of 10 selected polycyclic aromatic hydrocarbons (PAHs), six of which correspond to heavy PAHs. The goal of the present study was the successful resolution of a system even in the presence of real interferences. Second-order HPLC-FSFS data matrices were obtained in a short time with a chromatographic system operating in isocratic mode.

Chemometrics-assisted excitation-emission fluorescence spectroscopy on nylon membranes. Simultaneous determination of benzo[a]pyrene and dibenz[a,h]anthracene at parts-per-trillion levels in the presence of the remaining EPA PAH priority pollutants as interferences.

This work presents a novel approach for the simultaneous ultratrace determination of benzo[ a]pyrene and dibenzo[ a,h]anthracene, the two most carcinogenic polycyclic aromatic hydrocarbons (PAHs), in a very interfering environment, combining the recently discovered ability of the nylon membrane to strongly retain and concentrate PAHs on its surface, the sensitivity of molecular fluorescence, and the selectivity of second-order chemometric algorithms. The fluorescence excitation-emission matrices, directly measured on a nylon-membrane surface, are processed by applying parallel factor analysis (PARAFAC) and unfolded partial least-squares coupled to residual bilinearization (U-PLS/RBL). The superiority of U-PLS/RBL to quantify BaP and DBA at concentrations below 10 ng L (-1) in the presence of the remaining 14 US EPA (United States Environmental Protection Agency) PAHs at total concentrations ranging from 1400 and 14,000 ng L (-1) is demonstrated.

Screening of oil samples on the basis of excitation-emission room-temperature phosphorescence data and multiway chemometric techniques. Introducing the second-order advantage in a classification study.

Room-temperature phosphorescence excitation-emission matrices and multiway methods have been analyzed as potential tools for screening oil samples, based on full matrix information for polyaromatic hydrocarbons. Crude oils obtained from different sources of similar geographic origin, as well as light and heavy lubricating oils, were analyzed. The room-temperature phosphorescence matrix signals were processed by applying multilayer perceptron artificial neural networks, parallel factor analysis coupled to linear discriminant analysis, discriminant unfolded partial least-squares, and discriminant multidimensional partial least-squares (DN-PLS).

Room-temperature excitation-emission phosphorescence matrices and second-order multivariate calibration for the simultaneous determination of pyrene and benzo[a]pyrene.

The present article describes the simultaneous phosphorimetric determination of pyrene and benzo[a]pyrene, two highly toxic polycyclic aromatic hydrocarbons, through excitation-emission phosphorescence matrices (EEPMs) and second-order calibration. The developed approach enabled us to determine both compounds at microg L(-1) concentration levels without the necessity of applying separation steps, as well as significantly reducing the experimental time. An artificial neural network (ANN) approach was applied to optimize the chemical variables which have an influence on the room-temperature phosphorescence emission of the studied analytes.

Second-order advantage achieved by unfolded-partial least-squares/residual bilinearization modeling of excitation-emission fluorescence data presenting inner filter effects.

A second-order multivariate calibration approach, based on a combination of unfolded-partial least-squares with residual bilinearization (U-PLS/RBL), has been applied to fluorescence excitation-emission matrix data for multicomponent mixtures showing inner filter effects. The employed chemometric algorithm is the most successful one regarding the prediction of analyte concentrations when significant inner filter effects occur, even in the presence of unexpected sample components, which require strict adherence to the second-order advantage. Results for simulated fluorescence excitation-emission data are described, in comparison with the classical approach based on parallel factor analysis and other second-order algorithms, including generalized rank annihilation, bilinear least squares combined with residual bilinearization and multivariate curve resolution-alternating leastsquares.

Second-order advantage achieved with four-way fluorescence excitation-emission-kinetic data processed by parallel factor analysis and trilinear least-squares. Determination of methotrexate and leucovorin in human urine.

Four-way fluorescence data recorded by following the kinetic evolution of excitation-emission fluorescence matrices (EEMs) have been analyzed by parallel factor analysis and trilinear least-squares algorithms. These methodologies exploit the second-order advantage of the studied data, allowing analyte concentrations to be estimated even in the presence of an uncalibrated fluorescent background. They were applied to the simultaneous determination of the components of the anticancer combination of methotrexate and leucovorin in human urine samples.

First- and second-order multivariate calibration applied to biological samples: determination of anti-inflammatories in serum and urine.

First- and second-order multivariate calibration of fluorescence data have been compared as regards the determination of anti-inflammatories and metabolites in the biological fluids serum and urine. The simultaneous resolution of naproxen-salicylic acid mixtures in serum and naproxen-salicylic acid-salicyluric acid mixtures in urine was accomplished and employed for a discussion of the relative advantages of the applied chemometric tools. The analysis of second-order fluorescence excitation-emission matrices was performed using iteratively reweighted generalized rank annihilation method (IRGRAM), parallel factor analysis (PARAFAC), and self-weighted alternating trilinear decomposition (SWATLD).