Self-modeling curve resolution analysis of on-line vibrational spectra of polymerisation and transesterification

This article discusses the potential of self-modeling curve resolution analysis (SMCR) for the evolution of on-line vibrational spectral data of polymerisation and transesterification. After the general introduction of the SMCR approach, representative SMCR techniques like orthogonal projection analysis (OPA) and simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) are briefly outlined. As examples the SMCR analysis of the Raman spectra of the block copolymerisation of styrene and 1,3-butadiene and that of the near-infrared (NIR) spectra of the melt-extrusion transesterification of ethylene-vinylacetate copolymer will be illustrated. In the last part of this review paper, a new powerful SMCR method that we have recently proposed is demonstrated.     

Identification of an artifact peak co-eluting with formaldehyde-2,4-dinitrophenylhydrazone derivative by GC-MS and chemometrics

A chemometric approach was utilized to identify an artifact peak co-eluting with formaldehyde-2,4-dinitophenylhydrazone. Application of the methods of principal component analysis to the mass spectra of the formaldehyde-hydrazone peaks collected at 200-280 °C has revealed the presence of two factors contributing to these spectra. Moreover, the use of self-modeling curve resolution (SMCR) techniques has enabled the reconstruction of the spectra of the pure components. One of the identified components that contribute to the spectra of the mixture was formaldehyde-2,4-dintrophenylhydrazone, whereas the other component was 1-amino-2,4-dinitrobenzene, a degradation product of 2,4-dintrophenylhydrazine.     

Self-modeling curve resolution (SMCR) by particle swarm optimization (PSO)

Particle swarm optimization (PSO) combined with alternating least squares (ALS) is introduced to self-modeling curve resolution (SMCR) in this study for effective initial estimate. The proposed method aims to search concentration profiles or pure spectra which give the best resolution result by PSO. SMCR sometimes yields insufficient resolution results by getting trapped in a local minimum with poor initial estimates. The proposed method enables to reduce an undesirable effect of the local minimum in SMCR due to the advantages of PSO. Moreover, a new criterion based on global phase angle is also proposed for more effective performance of SMCR. It takes full advantage of data structure, that is to say, a sequential change with respect to a perturbation can be considered in SMCR with the criterion. To demonstrate its potential, SMCR by PSO is applied to concentration-dependent near-infrared (NIR) spectra of mixture solutions of oleic acid (OA) and ethanol. Its curve resolution performances are compared with SMCR with evolving factor analysis (EFA). The results show that SMCR by PSO yields significantly better curve resolution performances than those by EFA. It is revealed that SMCR by PSO is less sensitive to a local minimum in SMCR and it can be a new effective tool for curve resolution analysis.     

Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.     

Chemometric resolution of ATR-IR spectra data for polycondensation reaction of bis(hydroxyethylterephthalate) with a combination of self-modeling curve resolution (SMCR) and local rank analysis

Self-modeling curve resolution (SMCR) methods, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and alternating least squares (ALS) were used to calculate pure concentration profiles and pure spectra for the two-way spectral data collected during the on-line polycondensation reaction of bis(hydroxyethylterephthalate) with an ATR-FT-IR spectrometer. In order to improve the resolution results, SIMPLISMA was combined with local rank analysis method, fixed size moving window evolving factor analysis (FSMWEFA) to search for selective regions of various components and then look for the purest wavenumber variables in the selective regions. Such combination allows more accurate determination of the number of chemical components in the reaction system and the calculations of more accurate concentration profiles and spectra.     

Self-modeling curve resolution method applied for the evaluation of dissolution testing data: A case study of meloxicam-mannitol binary systems

This paper introduces some chemometric methods, i.e., self-modeling curve resolution (SMCR), multivariate curve resolution-alternating least squares (MCR-ALS) and parallel factor analysis (PARAFAC and PARAFAC2), which are used to evaluate in vitro dissolution testing data detected by a UV-vis spectrophotometer on meloxicam-mannitol binary systems. These systems were chosen because of their relative simplicity to apply as part of the validation process illustrating the effectiveness of the developed and applied chemometric method. The paper illustrates the failure of PARAFAC methods used before for pharmaceutical data evaluations as well, and we suggest application of the feasible band form given by SMCR as a more general procedure.Steps to improve the dissolution behavior of drugs have become among the most interesting aspects of pharmaceutical technology, and our results show that a larger particle size of meloxicam is advantageous for dissolution. Instead of the use of only one characteristic wavelength, appropriate chemometric methods can furnish more information from dissolution testing data, i.e., the individual dissolution rate profiles and the individual spectra for all the components can be obtained without resorting to any separation techniques such as HPLC.     

Local resolution of two-way data from multicomponent equilibria

A self-modeling curve resolution (SMCR) method is proposed to calculate concentration and spectral profiles for the two-way spectral data from an equilibrium containing several chemical components. The proposed method has three main distinctive steps: (i) fixed size moving window evolving factor analysis (FSMWEFA) is used to identify the selective and zero concentration regions for a desired component, (ii) orthogonal projection resolution (OPR) is used to calculate its concentration profile and (iii) the component striping is done directly to resolve other components. The results of simulated and real polyprotic acid dissociation equilibria showed that the proposed combined method performs well even in situation when the successive stepwise equilibrium constants are close to each other. The applicability of method for resolving the triprotic acid system with rank deficiency due full spectral overlapping of two involved chemical species also is shown.     

Application of multivariate self-modeling curve resolution to the quantitation of trace levels of organophosphorus pesticides in natural waters from interlaboratory studies

Multivariate self-modeling curve resolution is applied to the quantitation of coeluted organophosphorus pesticides: fenitrothion, azinphos-ethyl, diazinon, fenthion and parathion-ethyl. Analysis of these pesticides at levels of 0.1 to 1 μg/l in the presence of natural interferences is achieved using automated on-line liquid-solid extraction (Prospekt) coupled to liquid chromatography and diode array detection followed by a recently developed multivariate self-modeling curve resolution method. The proposed approach uses only 100 ml of natural water sample and has improved resolution of the coeluted organophosphorus insecticides and their quantitation at trace level. The results have been compared with those obtained by different laboratories participating in the Aquacheck interlaboratory exercise (WRC, Medmenham, UK) where more conventional analytical techniques are being used.     

“On line” mass spectrometric detection of ammonia oxidation products generated by polypyrrole based amperometric sensors

Polypyrrole (PPy) is the conducting polymer most widely employed in electrochemical sensors for ammonia detection in the last decade. Although sensors have been described in depth in the literature, the mechanism of ammonia detection by polypyrrole is still a matter of controversy. The differential electrochemical mass spectrometry (DEMS) technique, together with UV-Vis spectroscopy, gives direct and conclusive evidence with respect to the ammonia oxidation products formed in NaOH solution (pH=10) at polyrrole or N-methyl polypyrrole film sensors polarized at 0.35 V (Ag/AgCl). Monitoring of the different possible ammonia oxidation products by on-line DEMS measurements indicates that only NO is formed and that other species such as N₂ or N₂O are absent. UV-Vis absorption spectroscopy also showed that ionic products such as nitrate or nitrite are not formed.     

In situ fabrication of nanostructured titania coating on the surface of titanium wire: A new approach for preparation of solid-phase microextraction fiber

Nanostructured titania-based solid-phase microextraction (SPME) fibers were fabricated through the in situ oxidation of titanium wires with H₂O₂ (30%, w/w) at 80 °C for 24 h. The obtained SPME fibers possess a ∼1.2 μm thick nanostructured coating consisting of ∼100 nm titania walls and 100-200 nm pores. The use of these fibers for headspace SPME coupled with gas chromatography with electron capture detection (GC-ECD) resulted in improved analysis of dichlorodiphenyltrichloroethane (DDT) and its degradation products. The presented method to detect DDT and its degradation products has high sensitivity (0.20-0.98 ng L⁻¹), high precision (relative standard deviation R.S.D. = 9.4-16%, n = 5), a wide linear range (5-5000 ng L⁻¹), and good linearity (coefficient of estimation R² = 0.991-0.998). As the nanostructured titania was in situ formed on the surface of a titanium wire, the coating was uniformly and strongly adhered on the titanium wire. Because of the inherent chemical stability of the titania coating and the mechanical durability of the titanium wire substrate, this new SPME fiber exhibited long life span (over 150 times).     

Multivariate curve resolution combined with gas chromatography to enhance analytical separation in complex samples: A review

This review describes the major advantages and pitfalls of iterative and non-iterative multivariate curve resolution (MCR) methods combined with gas chromatography (GC) data using literature published since 2000 and highlighting the most important combinations of GC coupled to mass spectrometry (GC–MS) and comprehensive two-dimensional gas chromatography with flame ionization detection (GC × GC-FID) and coupled to mass spectrometry (GC × GC–MS). In addition, a brief summary of some pre-processing strategies will be discussed to correct common issues in GC, such as retention time shifts and baseline/background contributions. Additionally, algorithms such as evolving factor analysis (EFA), heuristic evolving latent projection (HELP), subwindow factor analysis (SFA), multivariate curve resolution-alternating least squares (MCR-ALS), positive matrix factorization (PMF), iterative target transformation factor analysis (ITTFA) and orthogonal projection resolution (OPR) will be described in this paper. Even more, examples of applications to food chemistry, lipidomics and medicinal chemistry, as well as in essential oil research, will be shown. Lastly, a brief illustration of the MCR method hierarchy will also be presented.     

Self-modeling curve resolution techniques applied to comparative analysis of volatile components of Iranian saffron from different regions

Volatile components of saffron from different regions of Iran were extracted by ultrasonic-assisted solvent extraction (USE) and were analyzed by gas chromatography-mass spectrometry (GC-MS). Self-modeling curve resolution (SMCR) was proposed for resolving the co-eluted GC-MS peak clusters into pure chromatograms and mass spectra. Multivariate curve resolution-objective function minimization (MCR-FMIN) and multivariate curve resolution-alternating least square (MCR-ALS) were successfully used for this purpose. The accuracy of the qualitative and quantitative results was improved considerably using SMCR techniques. Comparison of the results of saffron from different regions of Iran showed that their volatile components are different from chemical components and relative percentages points of view. Safranal is the main component of all samples. In addition, 4-hydroxy-2,6,6-trimethyl-1-cyclohexene-1-carboxaldehyde (HTCC), 2(5H)-furanone, 2,4,4-trimethyl-3-carboxaldehyde-5-hydroxy-2,5-cyclohexadien-1-one and 2(3H)-furanone, dihydro-4-hydroxy were common in all samples with high percentages. The results proved that combining of SMCR techniques with USE-GC-MS produces a powerful tool for the analysis of the complex samples.     

Chemiluminescence behavior based on oxidation reaction of rhodamine B with cerium(IV) in sulfuric acid medium

The chemiluminescence (CL) of the rhodamine B (RhB)-cerium(IV) system was investigated by flow-injection. Rhodamine B was suggested to be a suitable chemiluminescent reagent in acidic conditions. When the concentration of rhodamine B was 100 mg l⁻¹ and cerium sulfate was 1.6 mmol l⁻¹ in sulfuric acid, the chemiluminescent intensity was found to be highest by using 0.3 mol l⁻¹ sulfuric acid as a carrier solution. The particular chemiluminescent system could tolerate such distinct acidic environments that it was utilized for detecting many compounds that are stable in acidic solutions. Furthermore, by virtue of IR, UV-Vis and luminescence spectroscopic measurements, the chemiluminescent behavior of rhodamine B was studied and a possible mechanism for this chemiluminescent reaction was proposed. The emitter was affirmed to be a radical species due to one of the oxidation products of RhB; the chemiluminescent emissive wavelength was about 425 nm.     

Quantification of sex pheromone from Anocentor nitens by gas chromatography-mass spectrometry-selected ion monitoring

Two highly sensitive and selective methods based on gas chromatography coupled to mass spectrometry (GC-MS) in the selected ion monitoring (SIM) mode have been developed for the quantification of 2,6-dichlorophenol (2,6-DCP), a sex pheromone of the tick females of Anocentor nitens. Standard addition method and calibration curve techniques using 5-bromine-4-hydroxy-3-methoxybenzaldehyde (5-BrV) as internal standard (IS) afforded detection limit of 0.1 ng ml⁻¹. The calibration curve was linear over the concentration range from 0.5 to 500 ng ml⁻¹ for 2,6-DCP. Results show that the concentration range of sex pheromone in the extracts samples was 1.08-10.35 ng ml⁻¹. The methods developed provided reliable procedures to determine amounts of 2,6-DCP present in ticks.     

Analytical challenges in doping control: Comprehensive two-dimensional gas chromatography with time of flight mass spectrometry,a promising option

Doping control screening based on the enhanced resolution of comprehensive two-dimensional (2D) gas chromatography hyphenated to time of flight mass spectrometer was investigated. The identification of anabolic agents (clenbuterol, norandrosterone, epimetendiol, two methyltestosterone metabolites and 3′-hydroxystanozolol) contained in a spiked urine sample (2 ng/ml) was demonstrated. Special emphasis was given to 3′-hydroxystanozolol, mainly considering the difficulty in its detection. In contrast to conventional GC–MS approaches that must use single-ion monitoring, the GC × GC–TOFMS method enabled the identification of that metabolite through the deconvolution of the full mass spectrum and also resolved the co-eluted peaks of 3′-hydroxystanozolol and an endogenous component.     

Simultaneous detection of ascorbate and uric acid using a selectively catalytic surface

The direct and selective detection of ascorbate at conventional carbon or metal electrodes is difficult due to its large overpotential and fouling by oxidation products. Electrode modification by electrochemical reduction of diazonium salts of different aryl derivatives is useful for catalytic, analytical and biotechnological applications. A monolayer of o-aminophenol (o-AP) was grafted on a glassy carbon electrode (GCE) via the electrochemical reduction of its in situ prepared diazonium salts in aqueous solution. The o-aminophenol confined surface was characterized by cyclic voltammetry. The grafted film demonstrated an excellent electrocatalytic activity towards the oxidation of ascorbate in phosphate buffer of pH 7.0 shifting the overpotential from +462 to +263 mV versus Ag/AgCl. Cyclic voltammetry and d.c. amperometric measurements were carried out for the quantitative determination of ascorbate and uric acid. The catalytic oxidation peak current was linearly dependent on the ascorbate concentration and a linear calibration curve was obtained using d.c. amperometry in the range of 2-20 μM of ascorbate with a correlation coefficient 0.9998, and limit of detection 0.3 μM. The effect of H₂O₂ on the electrocatalytic oxidation of ascorbate at o-aminophenol modified GC electrode has been studied, the half-life time and rate constant was estimated as 270 s, and 2.57 × 10⁻³ s⁻¹, respectively. The catalytically selective electrode was applied to the simultaneous detection of ascorbate and uric acid, and used for their determination in real urine samples. This o-AP/GCE showed high stability with time, and was used as a simple and precise amperometric sensor for the selective determination of ascorbate.     

A combination of spectral re-alignment and BTEM for the estimation of pure component NMR spectra from multi-component non-reactive and reactive systems

The deconvolution of multi-component mixtures in NMR spectroscopy is a challenging problem due to the spectral non-linearities. In the present contribution, two data sets were studied (A) 10 samples of a four-component non-reactive mixture measured with ¹H, ¹³C, ¹⁹F, ³¹P NMR and (B) a three-solute cyclo-addition reaction measured with ¹³C NMR. Both data sets were treated with a re-alignment procedure to correct for the non-stationary chemical shifts, followed by band-target entropy minimization (BTEM) analysis. For data set A, quite good spectral estimates of the two hydrogen-containing species, four carbon-containing species, two fluorine-containing species and two phosphorus-containing species were obtained from the multi-component data. For data set B quite good spectral estimates of all three carbon-containing reactants were obtained as well as their relative concentration profiles. The present contribution using model systems indicates the usefulness of re-alignment procedures for correcting non-stationary characteristics, prior to self-modeling curve resolution (SMCR), and the potential for investigating more complex problems.     

Monitoring of the insecticide trichlorfon by phosphorus-31 nuclear magnetic resonance (31P NMR) spectroscopy

Trichlorfon is an organophosphorus insecticide, which is extensively being used for protection of fruit crops. Trichlorfon is a thermal labile compound, which cannot be easily determined by gas chromatography (GC) and has no suitable group for sensitive detection by high performance liquid chromatography (HPLC). In this study, a ³¹P nuclear magnetic resonance (³¹P NMR) has been described for monitoring of trichlorfon without any separation step. The quantitative works of ³¹P NMR spectroscopy has been performed in the presence of an internal standard (hexamethylphosphoramide). Limit of detection (LOD) for this method has been found to be 55 mg L⁻¹, without any sample preparation, and the linear working range was 150-5500 mg L⁻¹. Relative standard deviation (R.S.D.%) of the method for three replicates within and between days was obtained ≤9%. The average recovery efficiency was approximately 99-112%. This method was applied for monitoring trichlorfon in a commercial insecticide sample and tomato sample.