Infrared spectroscopy and multivariate calibration to monitor stability quality parameters of biodiesel

This paper evaluates analytical methods based on near infrared (NIR) and middle infrared (MIR) spectroscopy and multivariate calibration to monitor the stability of biodiesel. There was a focus on three parameters: oxidative stability index, acid number and water content. Ethylic and methylic biodiesel from different feedstocks were used in experiments of accelerated aging, in order to take into account the wide variety of oilseeds and feedstocks available in Brazil. Partial least squares (PLS) and multiple linear regression (MLR) models were developed. Different pre-processing techniques and spectral variable/regions selection algorithms were evaluated. For MLR models, the successive projection algorithm (SPA) was employed. Interval PLS (iPLS) and selection of variables taking into account the significant regression coefficients were used for PLS models. Results showed that both near and middle infrared regions, and all variable selection methods tested were efficient for predicting these three important quality parameters of B100, the root mean squares error of prediction (RMSEP) values being comparable to the reproducibility of the corresponding standard method for each property investigated.     

A novel algorithm for linear multivariate calibration based on the mixed model of samples

We present a novel algorithm for linear multivariate calibration that can generate good prediction results. This is accomplished by the idea of that testing samples are mixed by the calibration samples in proper proportion. The algorithm is based on the mixed model of samples and is therefore called MMS algorithm. With both theoretical support and analysis of two data sets, it is demonstrated that MMS algorithm produces lower prediction errors than partial least squares (PLS2) model, has similar prediction performance to PLS1. In the anti-interference test of background, MMS algorithm performs better than PLS2. At the condition of the lack of some component information, MMS algorithm shows better robustness than PLS2.     

Infrared spectroscopy of acetone-water liquid mixtures. II. Molecular model

In aqueous acetone solutions, the strong bathochromic shifts observed on the OH and CO stretch infrared (IR) bands are due to hydrogen bonds between these groups. These shifts were evaluated by factor analysis (FA) that separated the band components from which five water and five acetone principal factors were retrieved [J. Chem. Phys. 119, 5632 (2003)]. However, these factors were abstract making them difficult to interpret. To render them real an organization model of molecules is here developed whose abundances are compared to the experimental ones. The model considers that the molecules are randomly organized limited by the hydrogen bond network formed between the water hydrogen atoms and the acetone or water oxygen atoms, indifferently. Because the oxygen of water has two covalent hydrogen atoms which are hydrogen-bonded and may receive up to two hydrogen atoms from neighbor molecules hydrogen-bonded to it, three types of water molecules are found: OH2, OH3, and OH4 (covalent and hydrogen bonds). In the OH stretch region these molecules generate three absorption regimes composed of nu3, nu1, and their satellites. The strength of the H-bond given increases with the number of H-bonds accepted by the oxygen atom of the water H-bond donor, producing nine water situations. Since FA cannot separate those species that evolve concomitantly the nine water situations are regrouped into five factors, the abundance of which compared exactly to that retrieved by FA. From the factors' real spectra the OH stretch absorption are simulated to, respectively, give for the nu3 and nu1 components the mean values for OH2, 3608, 3508; OH3, 3473, 3282 and OH4, 3391, 3223 cm(-1). The mean separations from the gas-phase position which are respectively about 150, 330, and 400 cm(-1) are related to the vacancy of the oxygen electron doublets: two, one, and zero, respectively. No acetone hydrate that sequesters water molecules is formed. Similarly, acetone produces ten species, two of which evolve concomitantly. Spectral similarities further reduce these to five principal IR factors, the abundance of which compared adequately to the experimental results obtained from FA. The band assignment of the five-acetone spectra is given.     

Infrared spectroscopy provides a green analytical chemistry tool for direct diagnosis of cancer

Diagnosis of cancer is one of the most important aspects of medical research and has become the main aim of biomedical investigations. Misdiagnosis is the main drawback in most of the diagnostic routes introduced, while some of these methods are invasive and expensive.Recently, infrared spectroscopy (IR) was proposed as a rapid, accurate and sensitive technique in biomedical research, especially for detection of patterns of illness. We discuss research into cancer detection by IR, the role of data processing in quality assurance of the results obtained and novel proposals, such as bio-fluid analysis for diagnosis. We conclude that IR provides a novel green analytical chemistry approach to clinical oncology and cancer research.     

Infrared spectroscopy of acetone-hexane liquid mixtures

Acetone and hexane mixtures covering the whole solubility range were studied by Fourier transform infrared attenuated total reflectance spectroscopy. Factor analysis separates the spectra into four principal factor spectra and multiplying factors. Those containing negative factors are abstract, but the spectra are real. A statistical distribution model of the molecules in the solutions rendered the factors real. From these we define the intermediate species that occur in a 1:2 molar ratio of acetone in hexane, present principally in the low acetone concentration regions, and in a 2:1 molar ratio of acetone in hexane, present principally in the higher acetone concentration region. However, except at the concentration range limits where only pure acetone and pure hexane are present, the four species are present over the whole solubility range. The IR spectra of the species indicated very little displacement of the CH stretch bands, HCH deformation bands, and CC stretch bands, although there are some small intensity variations. Most of the modifications are observed on the acetone C=O stretch band. From the gas phase position, a strong bathochromic shift of 19 cm(-1) of the pure liquid is assigned to dipole-dipole interactions. In the 2:1 groupings, the shift that decreases to 15 cm(-1) is due to the diminished dipole-dipole interactions. In the 1:2 groupings, no dipole-dipole interaction can exist, and the bathochromic displacement of 9 cm(-1) is attributed to van der Waals interactions. In the one acetone to two hexanes grouping, no dipole-dipole interaction can exist, and the bathochromic displacement of 9 cm(-1) is attributed to van der Waals interactions. From the statistical distribution of the molecules, we determine that mixtures of hexane and acetone form a random organization with no preferred association or complex.     

Local electric discharge in liquid as a source of atomization and excitation for atomic emission spectroscopy

The article describes an atomization and excitation source for analysis of solutions by atomic spectrometry. The concentration of the energy in a pulse high-voltage discharge through a capillary in a dielectric wall separating the solution forms plasma that excites emission by atoms of compounds in the solution. The role of the electrode deposited near the aperture of the capillary and the sign of its potential in the intensity of the registered spectrum is demonstrated. The opportunities of the quantitative and qualitative analysis of solutions with element concentrations below 10 μg/L are considered. The conditions of analyte accumulation on the electrode are implemented. The opportunities for the determination of analytes in the flow mode are demonstrated.     

Simultaneous determination of albumin and immunoglobulin G with fluorescence spectroscopy and multivariate calibration

A method is proposed for the simultaneous determination of albumin and immunoglobulin G (IgG1) with fluorescence spectroscopy and multivariate calibration with partial least squares regression (PLS). The influence of some instrumental parameters were investigated with two experimental designs comprising 19 and 11 experiments, respectively. The investigated parameters were excitation and emission slit, detection voltage and scan rate. When a suitable instrumental setting had been found, a minor calibration and test set were analysed and evaluated. Thereafter, a larger calibration of albumin and IgG1 was made out of 26 samples (0-42 μg ml⁻¹ albumin and 0-12.7 μg ml⁻¹ IgG1). This calibration was validated with a test set consisting of 14 samples in the same concentration range. The precision of the method was estimated by analysing two test set samples for six times each. The scan modes tested were emission scan and synchronous scan Δ60 nm. The results showed that the method could be used for determination of albumin and IgG1 (albumin, root mean square error of prediction (RMSEP) <2, relative standard error of prediction (RSEP) <6% and IgG1, RMSEP <1, RSEP <8%) in spite of the overlapping fluorescence of the two compounds. The estimated precision was relative standard deviation (R.S.D.) <1.7%. The method was finally applied for the analysis of some sample fractions from an albumin standard used in affinity chromatography.     

Photoelectron emission spectroscopy of liquid water

The threshold energy E_t = 10.06 eV (0.002 eV standard deviation) is determined for photoelectron emission by liquid water and is correlated with E_t = 8.45 eV for OH^? (aq). Free energy changes and standard reduction potentials are calculated for both emission processes. Reorganization free energies are correlated to solvation free energies for H₂O⁺(aq) and OH^?(aq).     

Multi-elemental analysis of solidified mineral melt samples by Laser-Induced Breakdown Spectroscopy coupled with a linear multivariate calibration

Laser-Induced Breakdown Spectroscopy (LIBS) has been successfully applied for multi-elemental analysis of solidified mineral melt samples containing several oxides present in various concentrations. The plasma was generated using a Nd:YAG laser and the spectra were acquired using an Echelle spectrometer, coupled to an ICCD detector, which covers a spectral range from 200 to 780 nm. Using a set of 19 calibration samples, we first established univariate calibration curves for the major elements (Al, Fe, Mg, Ca, Ti and Si). We found out that the presence of matrix effects makes such a model, traditionally used in LIBS, not satisfying for quantitative analysis of such samples. Indeed, no sufficiently linear trends can be extracted from the calibration curves for the elements of interest considering all the samples. Instead, a much more robust calibration approach was obtained by considering a multivariate model. The matrix effects are then taken into account by correcting the spectroscopic signals emitted by a given species due the presence of the others ones. More specifically, we established here a calibration model using a 2nd order polynomial linear multivariate inverse regression. The capability of this approach was then checked using a 2nd set of samples with an unknown composition. A good agreement was observed between the analysis provided by X-ray fluorescence (XRF) and the LIBS measurements coupled to the multivariate model for the unknown samples.     

Determination of acetonitrile and ethanol in water by guided microwave spectroscopy with multivariate calibration

The feasibility of using guided microwave spectroscopy (GMS) utilizing the frequency range 0.25-3.20 GHz, was combined with multivariate calibration for the determination of acetonitrile or ethanol concentration in water. A wide range of different concentrations was used (up to 30% v/v). Partial least squares (PLS) and weighted ridge regression (WRR) was applied to generate a model for prediction, based upon the microwave spectra. A high level of collinearity was observed in both of the sample data sets and this was reduced by background subtraction. The prediction ability for the two types of regression models were found to be comparable with the percentage error of prediction (PEP) being approximately 2.5% for the acetonitrile samples and 1.1% for ethanol samples.     

Determination of motor gasoline adulteration using FTIR spectroscopy and multivariate calibration

In this paper, an attempt has been made to develop a feasible procedure for the prediction of quality parameters of motor gasoline and to discriminate between the different adulterated motor gasoline samples using density values, distillation temperatures and Fourier transform infrared (FTIR) analyses along with multivariate calibrations without the need for using chromatographic separation or other expensive instruments such as an octane number analyser. Ten blend mixtures of regular and super motor gasoline were prepared in order to study density, distillation temperatures and FTIR spectra characteristics for each blend. Distillation temperatures for the pure and blend mixtures of regular and super motor gasoline at initial boiling point (IBP) to final boling point (FBP) at 5%Vol. interval were obtained. Accurate and complete distillation data on the uncontaminated fuel would be essential for comparison. Thirteen peaks of the absorbance at the wavenumbers: 434, 461, 484, 673, 694, 1030, 1086, 1217, 1231, 1460, 1497, 1606 and 3028 cm(-1) were chosen to perform the multivariate calibration. The results obtained were expected to be useful in determination and differentiation purposes, providing information on whether the density values, distillation temperatures and FTIR analyses along with multivariate method could be an appropriate feature for differentiating a particular pure motor gasoline sample from the others. The observed differences in the specific spectral bands are investigated and discussed. They have proven to be an effective combination in the pursuit of management's differentiation goals.     

Raman spectroscopy as a process analytical technology tool for the understanding and the quantitative in-line monitoring of the homogenization process of a pharmaceutical suspension

The aim of this study was to propose a Process Analytical Technology (PAT) strategy for the quantitative in-line monitoring of an aqueous pharmaceutical suspension using Raman spectroscopy. A screening design was used to study the significance of process variables (mixing speed and height of the stirrer in the reactor) and of formulation variables (concentration of the active pharmaceutical ingredient (API) ibuprofen and the viscosity enhancer (xanthan gum)) on the time required to homogenize an aqueous pharmaceutical model suspension as response variable. Ibuprofen concentration (10% and 15% (w/v)) and the height of stirrer (position 1 and 2) were discrete variables, whereas the viscosity enhancer (concentration range: 1-2 g L-1) and the mixing speed (700-1000 rpm) were continuous variables. Next, a multilevel full factorial design was applied to study the effect of the remaining significant variables upon the homogenization process and to establish the optimum conditions for the process. Interactions between these variables were investigated as well. During each design experiment, the conformity index (CI) method was used to monitor homogeneity of the suspension mixing system in real-time using Raman spectroscopy in combination with a fibre optical immersion probe. Finally, a principal component regression (PCR) model was developed and evaluated to perform quantitative real-time and in-line measurements of the API during the mixing process. The experimental design results showed that the suspension homogenization process is an irregular process, for which it is impossible to model the studied variables upon the measured response variable. However, applying the PCR model it is possible to predict in-line and real-time the concentration of the API in a suspension during a mixing process. In this study, it is shown that Raman spectroscopy is a suitable PAT tool for the control of the homogenization process of an aqueous suspension. Raman spectroscopy not only allowed real-time monitoring of the homogeneity of the suspension, but also helped (in combination with experimental design) to understand the process. Further, the technique allowed real-time and in-line quantification of the API during the mixing process.     

Optofluidic differential spectroscopy for absorbance detection of sub-nanolitre liquid samples

We present a novel optofluidic differential method for carrying out absorbance spectroscopy of sub-nanolitre volumes of liquid samples on a microfluidic chip. Due to the reduction of liquid volume, the absorbance detection in microfluidics is often hindered by either low sensitivity or complex fabrication. To address this issue, we introduced an optofluidic modulator which can be easily integrated into a PDMS (polydimethylsiloxane) based microfluidic chip. The modulator was controlled by the fluid pressure and the absorbance spectrum of the analyte was obtained by taking differential measurements between the analyte and reference medium. An advantage is that this method doesn't need a complicated fabrication step. It is compatible with conventional microfluidic chips and measurements can be carried out on a normal transmission microscope. The performance of the device was tested by measuring solutions containing methylene blue, with concentrations as low as 13 μM.     

Determination of the content and identity of lidocaine solutions with UV-visible spectroscopy and multivariate calibration

A method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of ultraviolet-visible (UV-Vis) spectroscopy, orthogonal signal correction (OSC) and multivariate calibration with soft independent modelling of class analogy (SIMCA) classification and partial least squares (PLS) regression. The content was determined with PLS regression and the identity with PLS regression and SIMCA classification. The method was tested on the local anaesthetic compound lidocaine. For the validation, external test sets of both manufactured sample solutions and samples from a stability study were used. For comparison with this new method, liquid chromatography was used as a reference method. The results show that in respect of accuracy, precision and repeatability, the new method is comparable to the reference method. The main advantage over liquid chromatography is the much shorter time of analysis and the simpler analytical procedure. An estimate of the analysis time saved with the proposed method compared with using liquid chromatography, together with practical considerations, is given.     

Potentiometric sensor array for the determination of lysine in feed samples using multivariate calibration methods

A potentiometric sensor array has been developed for the determination of lysine in feed samples. The sensor array consists of a lysine biosensor and seven ion-selective electrodes for NH4+, K+, Na+, Ca2+, Mg2+, Li+, and H+, all based on all-solid-state technology. The potentiometric lysine biosensor comprises a lysine oxidase membrane assembled on an NH4+ electrode. Because the selectivity of the lysine biosensor towards other cation species is not sufficient, there is severe interference with the potentiometric response. This poor selectivity can be circumvented mathematically by analysis of the richer information contained in the multi-sensor data. The sensor array takes advantage of the cross-selectivity of lysine for each electrode, which differs from the other species and quantification of lysine in complex feed sample extracts is accomplished with multivariate calibration methods, such as partial least-squares regression. The results obtained are in a reasonable agreement with those given by the standard method for amino acid analysis.     

Intracellular applications of analytical SERS spectroscopy and multispectral imaging

The aim of this tutorial review is to give an overview of the state of the art of intracellular applications of analytical SERS spectroscopy. We pay particular attention to nanoparticle-based SERS spectroscopy since this currently dominates the published literature on non-disturbing analysis of live cells. We describe recent advances in this domain due to the development of multispectral imaging and to the combined use of SERRS (surface-enhanced resonance Raman scattering) and fluorescence spectroscopy. Finally, a perspective view is given on the tip-based approaches like tip-enhanced Raman spectroscopy (TERS) which allow micrometric and nanometric resolution.     

Use of indirect multivariate calibration for quality control of agricultural products by near infrared spectroscopy

In the near infrared (NIR) region, (=800–2500 nm) of the spectrum, most organic molecules have weak but reproducibly measurable absorption bands. This phenomenon has been increasingly exploited for the rapid, quantitative analysis of major constituents of agricultural products. As there is strong spectral overlap and an interaction of constituents in NIR, the calibration of instrumentation has to be performed indirectly with a training set of samples applying multivariate methods. A software package for IBM compatible personal computers includes programs to select samples to be used for calibration, to compute multiple linear regression equations, to cross-validate regression equations and to detect unusual samples. These methods are applied to rapidly determine the oil content of over a thousand rapeseed samples of the harvest of 1986. A considerable saving of time, labour, and costs can be achieved, the agreement with the standard laboratory method is very satisfactory.     

Determination of biodiesel content when blended with mineral diesel fuel using infrared spectroscopy and multivariate calibration

In this work, multivariable calibration models based on middle- and near-infrared spectroscopy were developed in order to determine the content of biodiesel in diesel fuel blends, considering the presence of raw vegetable oil. Soybean, castor and used frying oils and their corresponding esters were used to prepare the blends with conventional diesel. Results indicated that partial least squares (PLS) models based on MID or NIR infrared spectra were proven suitable as practical analytical methods for predicting biodiesel content in conventional diesel blends in the volume fraction range from 0% to 5%. PLS models were validated by independent prediction set and the RMSEPs were estimated as 0.25 and 0.18 (%, v/v). Linear correlations were observed for predicted vs. observed values plots with correlation coefficient (R) of 0.986 and 0.994 for the MID and NIR models, respectively. Additionally, principal component analysis (PCA) in the MID region 1700 to 1800 cm^− 1 was suitable for identifying raw vegetable oil contaminations and illegal blends of petrodiesel containing the raw vegetable oil instead of ester.     

Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration

A method for sulfur determination in diesel fuel employing near infrared spectroscopy, variable selection and multivariate calibration is described. The performances of principal component regression (PCR) and partial least square (PLS) chemometric methods were compared with those shown by multiple linear regression (MLR), performed after variable selection based on the genetic algorithm (GA) or the successive projection algorithm (SPA). Ninety seven diesel samples were divided into three sets (41 for calibration, 30 for internal validation and 26 for external validation), each of them covering the full range of sulfur concentrations (from 0.07 to 0.33% w/w). Transflectance measurements were performed from 850 to 1800 nm. Although principal component analysis identified the presence of three groups, PLS, PCR and MLR provided models whose predicting capabilities were independent of the diesel type. Calibration with PLS and PCR employing all the 454 wavelengths provided root mean square errors of prediction (RMSEP) of 0.036% and 0.043% for the validation set, respectively. The use of GA and SPA for variable selection provided calibration models based on 19 and 9 wavelengths, with a RMSEP of 0.031% (PLS-GA), 0.022% (MLR-SPA) and 0.034% (MLR-GA). As the ASTM 4294 method allows a reproducibility of 0.05%, it can be concluded that a method based on NIR spectroscopy and multivariate calibration can be employed for the determination of sulfur in diesel fuels. Furthermore, the selection of variables can provide more robust calibration models and SPA provided more parsimonious models than GA.