Application of Multivariate curve resolution-alternating least square methods on the resolution of overlapping CE peaks from different separation conditions

Discussed in this paper is the development of a new strategy to improve resolution of overlapping CE peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added, respectively, in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3,4-Dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, and 10% relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three-way data) analysis.     

子窗口分析法用于偶氮染料GC-MS重叠峰的解析

 将子窗口因子分析法 (SWFA)应用于GC MS联用检测数据分析 ,并以两种偶氮染料 3,3′ 二氯联苯胺和 4,4′ 次甲基 双 (2 氯苯胺 )重叠图谱为例进行了解析。结果表明 ,此方法可直接进行目标组分的质谱分辨 ,得到目标组分的质谱图 ,进而得到该组分的色谱图。其结果准确、可靠。与窗口因子分析相比 ,子窗口的选择更加容易 ,人工干预少 ,解析速度快。     

Protonation effects on the resonance Raman properties of a novel (terpyridine)Ru(4H-imidazole) complex: an experimental and theoretical case study

The optically active states in a novel (terpyridine)Ru(4H-imidazole) complex displaying an unusually broad and red-shifted absorption in the visible range are investigated experimentally and theoretically. Since this property renders the complex promising for an application as sensitizer in dye-sensitized solar cells, a detailed knowledge on the correlation between features in the absorption spectrum and structural elements is indispensable in order to develop strategies for spectroscopy/theory-guided design of such molecular components. To this aim, time-dependent density functional theory calculations, including solvent effects, are employed to analyze the experimental UV-vis absorption and resonance Raman (RR) spectra of the unprotonated and protonated forms of the complex. This provides a detailed photophysical picture for a complex belonging to a novel class of Ru-polypyridine black absorbers, which can be tuned by external pH stimuli. The complex presents two absorption maxima in the visible region, which are assigned by the calculations to metal-to-ligand charge transfer (MLCT) and intra-ligand states, respectively. RR simulations are performed in resonance with both bands and are found to correctly reproduce the observed effects of protonation. Finally, the examination of the molecular orbitals and of the RR spectra for the MLCT state shows that protonation favors a charge transfer excitation to the 4H-imidazole ligand.     

UV-Vis spectroscopic and chemometric study on the aggregation of ionic dyes in water

The monomer-dimer equilibrium in several ionic dyes (Methylene Blue, Acridine Orange, Nile Blue A, Neutral Red, Rhodamine 6G and Safranine O) has been investigated by means of UV-Vis spectroscopy. The data have been processed by a recently developed method for quantitative analysis of undefined mixtures, based on simultaneous resolution of the overlapping bands in the whole set of absorption spectra. In the cases of Acridine Orange a second chemometric approach has been used as a reference. It is based on a decomposition of the recorded spectra into a product of target and projection matrices using non iterative partial least squares (NIPALS). The matrices are then rotated to give the correct concentrations, spectral profiles of the components and the equilibrium constant. The dimeric constants determined by the two methods were in excellent agreement, evidencing the accuracy of the analysis. From the calculated dimeric constant and monomer and dimer spectra, the structures of the dimeric forms of the studied dyes are estimated.     

Multicomponent analysis in luminescence spectroscopy

Multicomponent analysis of absorption spectra (infrared or electronic spectra) by factor analysis is a suitable method to use. The algorithm of factor analysis is now available for luminescence spectroscopy. The first possibility, as in absorption spectroscopy, is to determine pure components emission spectra for a unique set of spectra of mixtures in overdetermined conditions. On the other hand, it is also possible to extract pure components emission and excitation spectra of the only data corresponding to the 3D fluorescent spectrum of a single mixture. The results are evaluated in respect to noise level and concentrations ratio on both simulated and real spectra.     

Multicomponent analysis in luminescence spectroscopy

Multicomponent analysis of absorption spectra (infrared or electronic spectra) by factor analysis is a suitable method to use. The algorithm of factor analysis is now available for luminescence spectroscopy. The first possibility, as in absorption spectroscopy, is to determine pure components emission spectra for a unique set of spectra of mixtures in overdetermined conditions. On the other hand, it is also possible to extract pure components emission and excitation spectra of the only data corresponding to the 3D fluorescent spectrum of a single mixture. The results are evaluated in respect to noise level and concentrations ratio on both simulated and real spectra.     

Multiplexed detection of six labelled oligonucleotides using surface enhanced resonance Raman scattering (SERRS)

The labelling of target biomolecules followed by detection using some form of optical spectroscopy has become common practice to aid in their detection. This approach has allowed the field of bioanalysis to dramatically expand; however, most methods suffer from the lack of the ability to discriminate between the components of a complex mixture. Currently, fluorescence spectroscopy is the method of choice but its ability to multiplex is greatly hampered by the broad overlapping spectra which are obtained. Surface enhanced resonance Raman scattering (SERRS) holds many advantages over fluorescence both in sensitivity and, more importantly here, in its ability to identify components in a mixture without separation due to the sharp fingerprint spectra obtained. Here the first multiplexed simultaneous detection of six different DNA sequences, corresponding to different strains of the Escherichia coli bacterium, each labelled with a different commercially available dye label (ROX, HEX, FAM, TET, Cy3, or TAMRA) is reported. This was achieved with the aid of multivariate analysis, also known as chemometrics, which can involve the application of a wide range of statistical and data analysis methods. In this study, both exploratory discriminant analysis and supervised learning, by partial least squares (PLS) regression, were used and the ability to discriminate whether a particular labelled oligonucleotide was present or absent in a mixture was achieved using PLS with very high sensitivity (0.98-1), specificity (0.98-1), accuracy (range 0.99-1), and precision (0.98-1).     

Detailed assignment of the magnetic circular dichroism and UV-vis spectra of five-coordinate high-spin ferric [Fe(TPP)(Cl)

High-spin (hs) ferric heme centers occur in the catalytic or redox cycles of many metalloproteins and exhibit very complicated magnetic circular dichroism (MCD) and UV-vis absorption spectra. Therefore, detailed assignments of the MCD spectra of these species are missing. In this study, the electronic spectra (MCD and UV-vis) of the five-coordinate hs ferric model complex [Fe(TPP)(Cl)] are analyzed and assigned for the first time. A correlated fit of the absorption and low-temperature MCD spectra of [Fe(TPP)(Cl)] lead to the identification of at least 20 different electronic transitions. The assignments of these spectra are based on the following: (a) variable temperature and variable field saturation data, (b) time-dependent density functional theory calculations, (c) MCD pseudo A-terms, and (d) correlation to resonance Raman (rRaman) data to validate the assignments. From these results, a number of puzzling questions about the electronic spectra of [Fe(TPP)(Cl)] are answered. The Soret band in [Fe(TPP)(Cl)] is split into three components because one of its components is mixed with the porphyrin A2u72-->Eg82/83 (pi-->pi*) transition. The broad, intense absorption feature at higher energy from the Soret band is due to one of the Soret components and a mixed sigma and pi chloro to iron CT transition. The high-temperature MCD data allow for the identification of the Q v band at 20 202 cm(-1), which corresponds to the C-term feature at 20 150 cm(-1). Q is not observed but can be localized by correlation to rRaman data published before. Finally, the low energy absorption band around 650 nm is assigned to two P-->Fe charge transfer transitions, one being the long sought after A1u(HOMO)-->d pi transition.     

Intramolecular charge-transfer dynamics in covalently linked perylene-dimethylaniline and cyanoperylene-dimethylaniline

The excited-state dynamics of covalently linked electron donor-acceptor systems consisting of N, N-dimethylaniline (DMA) as electron donor and either perylene (Pe) or cyanoperylene (CNPe) as acceptor has been investigated in a large variety of solvents, including a room-temperature ionic liquid, by using femtosecond time-resolved fluorescence and absorption spectroscopy. The negligibly small solvent dependence of the absorption spectrum of both compounds and the strong solvatochromism of the fluorescence are interpreted by a model where optical excitation results in the population of a locally excited state (LES) and emission takes place from a charge-separated state (CSS). This interpretation is supported by the fluorescence up-conversion and the transient absorption measurements that reveal substantial spectral dynamics in polar solvents only, occurring on time scales going from a few hundreds of femtoseconds in acetonitrile to several tens of picoseconds in the ionic liquid. The early transient absorption spectra are similar to those found in nonpolar solvents and are ascribed to the LES absorption. The late spectra due to CSS absorption show bands that are red-shifted relative to those of the radical anion of the acceptor moiety by an amount that depends on solvent polarity, pointing to partial charge separation. Global analysis of the time-resolved data indicates that the charge separation dynamics in PeDMA is essentially solvent controlled, whereas that in CNPeDMA is faster than diffusive solvation, this difference being accounted for by a larger driving force for charge separation in the latter. On the other hand, the CSS lifetime of PeDMA is of the order of a few nanoseconds independently of the solvent, whereas that of CNPeDMA decreases with increasing solvent polarity from a few nanoseconds to a few hundreds of picoseconds. Comparison of these results with previously published data on the fluorescence quenching of Pe and CNPe in pure DMA shows that the charge separation and the ensuing charge recombination occur on similar time scales independently of whether these processes are intra- or intermolecular.     

Application of MATLAB package for the automation of the chemometric processing of spectrometric signals in the analysis of complex mixtures

We describe three types of automatic software for the chemometric processing of spectrometric data. The software was developed in the MATLAB working environment and includes data import, mathematical preprocessing, chemometric analysis, and generation of a report file. The software is designed to solve problems regarding identification of some components of multicomponent mixtures, determination of compounds with overlapping signals, and differentiation of samples by their spectral responses. To test the software, we present examples of spectrometric analyses of coffee, fruit juices, and alcoholic beverages using chemometric methods of independent component analysis (ICA) and partial least squares–discriminant analysis (PLS–DA). In particular, we simulated electronic absorption spectra for the identification of three artificial colors (E110, E102, and E122) in alcoholic beverages, NMR spectra for the simultaneous determination of five components (acetic acid, γ-aminobutyric acid, arginine, acetaldehyde, and proline) in orange juice without using reference standards, and NMR spectra of coffee samples to determine its varietal authenticity (Arabica or Robusta). The duration of automatic chemometric processing did not exceed 1 min per sample. The developed software can be optimized for other matrices and/or brands of spectrometers.     

The resolution of overlapping chromatographic peaks by evolving factor analysis

A completely model-free method for the resolution of overlapping chromatographic peaks is presented. Evolving factor analysis enhances the power of classical factor analysis by exploiting the additional information contained in the response data through the intrinsic order of the elution time. The results are the elution profiles and the normalized spectra of the components.     

HELP法在中草药分析中的应用研究-冬虫夏草的化学成分测定

基于直观推导式演进特征投影（ＨＥＬＰ）法,对冬虫夏草子座和虫体分别进行了多组分同时定性定量测定．结果表明,ＨＥＬＰ法能减少样本提取分离的步骤,降低色谱分离条件的要求,提高检测准确度．联用色谱检测与化学计量学解析法相结合将为复杂中草药分析提供一种全新手段     

Determination of Sudan I in chilli powder from solvent components gradual change-visible spectra data using second order calibration algorithms

It was discovered that a second order spectra data matrix of Sudan I produced from the solvent components gradual change-visible absorption spectra can be expressed as the combination of two bilinear data matrices. Based on this discovery, a new method for the determination of Sudan I in gray systems using second order calibration algorithms has been developed. The second order calibration algorithms were based on the popular parallel factor analysis (PARAFAC) and rank annihilation factor analysis (RAFA), respectively. In the method described here, the components of the solvent were changed gradually by adding ethanol into cyclohexane, the absorption spectra of Sudan I and chilli samples in a series of cyclohexane-ethanol mixed solvents with various ethanol volume fractions were recorded, and then the second order data were obtained from the solvent components gradual change-visible absorption spectra. Thus, the concentration of Sudan I in a gray system could be determined from the spectra matrices using second order calibration algorithms. This method is simple, convenient and dependable. The method has been used to determine Sudan I in chilli powder with satisfactory results.     

Computer-assisted optimization of reversed-phase HPLC isocratic separation of neutral compounds

An appropriate optimization strategy should be used to find a desired resolution or selectivity with a minimum number of experiments in a limited time, which could assure the baseline separation of all target compounds. It was usually realized by means of a specialized computer program. In this paper, mapping optimization method and overlapping resolution mapping were compared for the optimization of a reversed-phase high-performance liquid chromatography (HPLC) isocratic separation of neutral compounds. The calculated resolutions and separation time of 7 to 10 experiments are fitted by different equations, which were used to build a contour plot with a minimum effective resolution and maximum retention time as a function of a mobile phase composition. The balance between resolution and analysis time could be easily realized by the overlapping of the final overlapping resolution mapping and analysis time mapping. The validity of the two methods was confirmed by some typical experiments. The models are simple, visual, and common without theoretical arithmetic.     

Automatic analysis of mixed spectra : Generalised spectral subtraction applied to electron spin resonance spectroscopy

A new technique is described for estimating the pure component spectra from a set of linearly independent spectra. The process is one of generalised spectral subtraction in which an iterative combination of multivariate linear least-squares analysis and matrix transformation is applied to the input data to give estimates of the number of independent components in the original mixed spectra. This technique is applicable to bipolar data (e.g. from e.p.r. spectra) as well as absorption spectra determined by any spectroscopic technique, provided that the spectra may be reasonably assumed to be an additive mixture of unknown pure components. Numerical model examples are given together with an experimental application to electron spin resonance.     

Resolving batch chromatographic overlapping peaks of flavoring essence using stepwise key spectrum selection

Stepwise key spectrum selection (SKSS) was introduced to resolve batch overlapping peaks from gas chromatography-mass spectrometry (GC-MS) analysis of ten batch tobacco flavoring samples in different storage times. Resolution was implemented on a software platform that embedded the SKSS method. The data from GC-MS analysis of the samples were saved and prepared in ASCII files and then were inputted into the software platform for visual inspections. The data segment with overlapping peaks was precut for subsequent analysis. Spectral background in the data was removed using a linear fitting of the baseline. Four components in the overlapping peaks were automatically detected by the SKSS method. The resolution of the concentration profiles and spectra of the four components was conducted by setting only one parameter, the negative area ratio, as 0.01. The fixed size moving window evolving factor analysis and evolving factor analysis were applied to validate the resolved concentration profiles. The resolved mass spectra were validated by the searched standard through library search at the pure component regions revealed by the resolved concentration profiles. The results showed that the SKSS method could be a simple but powerful tool in resolving batch chromatographic overlapping peaks.     

多元曲线分辨-交替最小二乘方法在联用数据分辨中的应用

通过对模拟数据和高效毛细管电泳实验数据的分析,讨论了多元曲线分辨-交替最小二乘方法(MCR-ALS)在毛细管电泳-二极管阵列检测(CE-DAD)联用数据分辨中的应用.讨论了几种因素对MCR-ALS单个数据矩阵分辨结果的影响,包括待分析物光谱间的相似程度、浓度曲线的重叠程度以及由渐进因子分析(EFA)所得到的浓度初始值等.MCR-ALS还可用于多个数据矩阵的同时分析,即二阶MCR-ALS.结果表明,与一阶MCR-ALS相比,二阶MCR-ALS方法能够更好地解决各种分辨问题,得到合理和满意的分辨结果.     

Comparisons of measured rate constants with spectroscopically determined electron-transfer parameters

This work involves comparison of rate constants measured for an intervalence (IV) compound with electron-transfer parameters derived from its optical absorption spectrum. The temperature-dependent rate constants for the radical cation having 3-tert-butyl-2,3-diazabicyclo[2.2.2]oct-2-yl (hydrazine) charge-bearing units attached para to a tetramethylbenzene bridge (1+) were previously measured. In this study, resonance Raman is used to calculate the magnitudes of the distortions of normal modes of vibration caused by excitation into the intervalence absorption band. These data produce a vibrational reorganization energy lambdavsym of 9250 cm(-1), and averaged single-mode omegav for use in the Golden Rule equation of 697 cm(-1). Zhu-Nakamura theory has been used to calculate preexponential factors for analysis of the previously measured variable temperature optical spectra using quartic-enhanced intervalence bands to extract the total reorganization energy and the intramolecular electron-transfer rate constants for intramolecular electron transfer using electron spin resonance. In contrast to using the Golden Rule equation, separation of lambda into solvent and vibrational components is not significant for these data. The Zhu-Nakamura theory calculations produce ln(k/T) versus 1/T slopes that are consistent with the experimental data for electronic couplings that are somewhat larger than the values obtained from the optical spectra using Hush's method.     

Efficient and sample-specific interpretation of ToF-SIMS data by additional postprocessing of principal component analysis results

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful tool for surface analysis, but fragmentation of molecular species during the SIMS process may lead to complex mass spectra. While the fragmentation pattern is typically characteristic for each compound, industrial samples are engineered materials, and, thus, may contain a mixture of many compounds, which may result in a variety of overlapping peak patterns in ToF-SIMS spectra. Consequently, the process of data evaluation is challenging and time-consuming. Principal component analysis (PCA) can be used to simplify data analysis for complex sample systems. Especially, correlation loadings were observed as an ideal tool to identify relevant signals in PCA results, which induce the separation of different sample groups. This is because correlation loadings show the relevance of signals independent from their intensity in the raw data. In correlation loadings, however, fragmentation patterns are no longer observed and the identification of peaks' sum formulas is challenging. In this study, a new approach is presented, which simplifies peak identification and assignment in ToF-SIMS spectra after PCA is performed. The approach uses a mathematical transformation that projects PCA results, in particular loadings and correlation loadings, in the direction of specific sample groups. The approach does not change PCA results but rather presents them in a new way. This method allows to visualize characteristic spectra for specific sample groups that contain only relevant signals and, additionally, visualize fragmentation patterns. Data analysis is simplified and helps the user to focus on data interpretation rather than processing.