Multivariate control charts based on net analyte signal (NAS) for characterization of the polymorphic composition of Piroxicam using near infrared spectroscopy

Near infrared spectroscopic and multivariate statistical control charts based on the net analyte signal (NAS) were applied to the polymorphic characterization of Piroxicam samples. Three different polymorphic forms (I, II and III) were studied, using X-ray powder diffraction (XRPD) and scanning electron microscopy as reference techniques. Samples containing form I were considered inside the quality specifications and forms II and III were impurities. Three control charts were developed: the NAS chart that corresponds to the analyte of interest (polymorphic form I), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variation. From the limits estimated for each chart using samples inside the quality specifications, it was possible to identify samples that did not present polymorphic form I. The use of multivariate control charts provides a rapid evaluation of purity and the polymorphic composition of pharmaceutical formulations based on Piroxicam.     

Effect of gold nanoparticle attached multi-walled carbon nanotube-layered indium tin oxide in monitoring the effect of paracetamol on the release of epinephrine

Raman spectroscopy and control charts based on the net analyte signal (NAS) were applied to polymorphic characterization of carbamazepine. Carbamazepine presents four polymorphic forms: I-IV (dihydrate). X-ray powder diffraction was used as a reference technique. The control charts were built generating three charts: the NAS chart that corresponds to the analyte of interest (form III in this case), the interference chart that corresponds to the contribution of other compounds in the sample and the residual chart that corresponds to nonsystematic variations. For each chart, statistical limits were developed using samples within the quality specifications. It was possible to identify the different polymorphic forms of carbamazepine present in pharmaceutical formulations. Thus, an alternative method for the quality monitoring of the carbamazepine polymorphic forms after the crystallization process is presented.     

Monitoring of an industrial process by multivariate control charts based on principal component analysis

The control and monitoring of an industrial process is performed in this paper by the multivariate control charts. The process analysed consists of the bottling of the entire production of 1999 of the sparkling wine "Asti Spumante". This process is characterised by a great number of variables that can be treated with multivariate techniques. The monitoring of the process performed with classical Shewhart charts is very dangerous because they do not take into account the presence of functional relationships between the variables. The industrial process was firstly analysed by multivariate control charts based on Principal Component Analysis. This approach allowed the identification of problems in the process and of their causes. Successively, the SMART Charts (Simultaneous Scores Monitoring And Residual Tracking) were built in order to study the process in its whole. In spite of the successful identification of the presence of problems in the monitored process, the Smart chart did not allow an easy identification of the special causes of variation which casued the problems themselves.     

Monitoring of pigmented and wooden surfaces in accelerated ageing processes by FT-Raman spectroscopy and multivariate control charts

Two of the most suitable analytical techniques used in the field of cultural heritage are NIR (near-infrared) and Raman spectroscopy. FT-Raman spectroscopy coupled to multivariate control charts is applied here for the development of a new method for monitoring the conservation state of pigmented and wooden surfaces. These materials were exposed to different accelerated ageing processes in order to evaluate the effect of the applied treatments on the goods surfaces. In this work, a new approach based on the principles of statistical process control (SPC) to the monitoring of cultural heritage, has been developed: the conservation state of samples simulating works-of-art has been treated like an industrial process, monitored with multivariate control charts, owing to the complexity of the spectroscopic data collected.The Raman spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart and cumulative sum (CUSUM) control charts. These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surfaces. CUSUM charts however proved to be more effective in the identification of the exact beginning of the applied treatment. In the case of wooden boards, where a sufficient number of PCs were available, simultaneous scores monitoring and residuals tracking (SMART) charts were also investigated. The exposure to a basic attack and to high temperatures produced deep changes on the wooden samples, clearly identified by the multivariate Shewhart, CUSUM and SMART charts. A change on the pigment surface was detected after exposure to an acidic solution and to the UV light, while no effect was identified on the painted surface after the exposure to natural atmospheric events.     

Simultaneous gas chromatographic determination of methanol and free glycerol in biodiesel

Summary The methanol and free glycerol content of vegetable oil methyl esters used as diesel fuel (biodiesel) is very important in describing the quality of this fuel and is therefore limited by specifications. A previously described GLC method for the determination of free glycerol in biodiesel has been further developed and also allows the simultaneous determination of methanol. Sample preparation includes dissolving in dimethylformamide, silylation with bis-trimethylsilyltrifluoracetamide (BSTFA) and separation on a methylsilicone fluid, coated-capillary column using either FID or MS-detection. Ethanol and 1,4-butanediol were used as internal standards. Both detection systems show sufficient sensitivity for concentrations relevant to biodiesel samples. The recovery was tested using a RME-sample containing known amounts of methanol and glycerol.     

Stainless Steel Electrodes to Determine Biodiesel Content in Petroleum Diesel Fuel by Electrochemical Impedance Spectroscopy

The blending ratio of biodiesel in petroleum diesel has become one of the most important parameters to ensure the quality of diesel/biodiesel blend. This paper presents a fast and simple method based on electrochemical impedance spectroscopy to determine the biodiesel content in diesel fuel. Different from the method reported in the literature, using a pair of two identical screen printed carbon paste electrodes, in the present work we used two electrodes made from 304 stainless steel with dimensions of 0.8×0.3 cm for the EIS measurements. Improved results were obtained in terms of sensitivity, stability of measurements, electrode reuse, and cost. In this procedure the charge transfer resistance is proportionally related to the biodiesel content, which is used to construct a calibration curve for the analysis of biodiesel content. The procedure was validated by an official method, using two samples, being one of them, certified through an official interlaboratory program of the Brazilian government (Interlaboratory Program for Biodiesel of National Agency of Petroleum, Natural Gas and Biofuels (PIB)/ANP). Good results were obtained in terms of recovery (102.6 %‐102.8 %), precision (coefficient of variation lower than 2.3 %), limit of detection (0.24 %) and limit of quantification (0.80 %). These results indicate that this method is sufficiently suitable as an alternative method to the official method for determining biodiesel content in commercial diesel fuel.     

Thermal investigation of biodiesel blends derived from rapeseed oil

Over the last few years, the production of biodiesel from vegetable oil has significantly increased in Romania due to its obligatory use in the composition of diesel fuel. In this study, biodiesel from rapeseed oil was produced using methanol and a base catalyst. Four samples of biodiesel/diesel blends were prepared for analysis to determine the main thermal decomposition processes and calorimetric events. The thermal profiles were compared to reference diesel. The data obtained on the Thermogravimetry/Differential thermogravimetry and DTA curves show the quality of biodiesel/diesel blends and the possibility that the fuel be used in diesel engines. It was found that biodiesel blends with higher percentage of biodiesel in their compositions were more thermally stable than diesel fuel.     

Application of capability indices and control charts in the analytical method control strategy

In this study, we assessed the usefulness of control charts in combination with the process capability indices, C _pm and C _pk, in the control strategy of an analytical method. The traditional X‐chart and moving range chart were used to monitor the analytical method over a 2‐year period. The results confirmed that the analytical method is in‐control and stable. Different criteria were used to establish the specifications limits (i.e. analyst requirements) for fixed method performance (i.e. method requirements). If the specification limits and control limits are equal in breadth, the method can be considered “capable” (C _pm = 1), but it does not satisfy the minimum method capability requirements proposed by Pearn and Shu (2003). Similar results were obtained using the C _pk index. The method capability was also assessed as a function of method performance for fixed analyst requirements. The results indicate that the method does not meet the requirements of the analytical target approach. A real‐example data of a SEC with light‐scattering detection method was used as a model whereas previously published data were used to illustrate the applicability of the proposed approach.     

Characterization of Gasoline by 1H Nuclear Magnetic Resonance and Chemometrics

Automotive fuel adulteration is an old and significant problem. One common type of fuel adulteration is the addition of diesel to gasoline. Unsupervised models were developed through hierarchical cluster and principal component analysis models. Supervised models through partial least square discriminant analysis using ¹H nuclear magnetic resonance spectra as the input were used to classify samples as adulterated or unadulterated. Quantitative models were developed using partial least squares to determine the gasoline and diesel concentrations in the samples. This set contained samples composed of pure gasoline and anhydrous ethanol reproducing commercial gasoline and other samples treated with diesel. Hierarchical cluster and principal component analysis did not distinguish between adulterated and unadulterated samples except for the most adulterated materials. However, partial least square discriminant analysis classified 100% of the samples correctly. The partial least square algorithm provided excellent regression models for the gasoline and diesel content. The determination coefficient was 0.9920 for both models, whereas the root mean square error of cross-validation and root mean square error of prediction for the diesel model were 2.32 and 1.42%, respectively, and 2.40 and 1.38% for the gasoline model.     

Critical review on analytical methods for biodiesel characterization

Biodiesel is an alternative fuel composed of mono-alkyl esters and obtained mainly from the base-catalyzed transesterification reaction of oils or fats. Its use (pure or blended) does not demand any modification in the diesel engine and in the existing fuel distribution and storage infrastructure. Moreover, biodiesel has a high energetic yield, fixes the solar energy and contains insignificant amounts of sulphur. Therefore, biodiesel is currently the best substitute for fossil diesel fuel.Besides mono-alkyl esters, glycerol (main co-product), alcohol, catalyst, free fatty acids, tri-, di- and monoglycerides compose the final mixture of biodiesel production process. These and other kinds of contaminants can lead to severe operational and environmental problems. Therefore, the quality control of biodiesel is greatly significant to the success of its commercialization and market acceptance. Some important issues on the biodiesel quality control involve the monitoring of transesterification reaction, the quantification of mono-alkyl esters and free- and bonded glycerol as well as determination of residual catalysts and alcohol. Moreover, the determination of blend levels is another key aspect of biodiesel analyses. Chromatography and spectroscopy are the analytical methods most used for the biodiesel characterization, but procedures based on physical properties are also available.Previously, a review on analytical methods used to evaluate biodiesel quality was written by Knothe. Due to the importance of this field, we made an update of Knothes’ review. Therefore, in this paper, we will describe new developments in biodiesel analyses and some references showed in Knothes’ paper. Specially, we will describe analytical methods used for quantification of glycerol, mono-, di-, triglycerides, methanol, water, Na, K, P, and steroids in biodiesel or along the transesterification reaction. Also, the determination of biodiesel content in blends and some physicochemical parameters are discussed. At the end, we will assess the available techniques and point out some improvements on analytical methods for biodiesel characterization.     

Quality control samples for routine use in water laboratories

Summary Quality management systems in water laboratories have steadily improved during the past years, and the use of quality control samples is becoming routine. A selection of quality control samples has been designed and prepared by the Danish reference laboratory for water analysis. The samples cover 38 parameters at up to three concentration levels that are typical for environmental water. The samples have been produced in quantities that enable frequent use. Some samples are distributed together with preconstructed control charts for laboratory staff with limited knowledge of control chart statistics. Other users apply a Quality 4.0 computer programme for administration and statistical handling of quality control data with construction of control charts.     

Simultaneous determination of free and total glycerol in biodiesel by capillary electrophoresis using multiple short‐end injection

A rapid method for the simultaneous determination of free glycerol (FG) and total glycerol (TG) in biodiesel by CE using a short‐end multiple injection (SE/MI) configuration system is described. The sample preparation for FG involves the extraction of glycerol with water and for TG a saponification reaction is carried out followed by extraction as in the case of FG. The glycerol extracted in both cases is submitted to periodate oxidation and the iodate ions formed are measured on a CE‐SE/MI system. The relevance of this study lies in the fact that no analytical procedure has been previously reported for the determination of TG (or of FG and TG simultaneously) by CE. The optimum conditions for the saponification/extraction process were 1.25% KOH and 25°C, with a time of only 5 min, and biodiesel mass in the range of 50.0–200.0 mg can be used. Multiple injections were performed hydrodynamically with negative pressure as follows: 50 mbar/3s (FG sample); 50 mbar/6s (electrolyte spacer); 50 mbar/3s (TG sample). The linear range obtained was 1.55–46.5 mg/L with R²> 0.99. The LOD and LOQ were 0.16 mg/L and 0.47 mg/L, respectively for TG. The method provides acceptable throughput for application in quality control and monitoring biodiesel synthesis process. In addition, it offers simple sample preparation (saponification process), it can be applied to a variety biodiesel samples (soybean, castor, and waste cooking oils) and it can be used for the determination of two key parameters related to the biodiesel quality with a fast separation (less than 30 s) using an optimized CE‐SE/MI system.     

Quantitative analysis of biodiesel in blends of biodiesel and conventional diesel by comprehensive two-dimensional gas chromatography and multivariate curve resolution

In this paper, a method to determine the composition of blends of biodiesel with mineral diesel (BXX) by multivariate curve resolution with Alternating Least Squares (MRC-ALS) combined to comprehensive two-dimensional gas chromatography with Flame Ionization Detection (GC × GC-FID) is presented. Chromatographic profiles of BXX blends produced with biodiesels from different sources were used as input data. An initial evaluation carried out after multiway principal component analysis (MPCA) was used to reveal regions of the chromatograms were the signal was likely to be dependent on the concentration of biodiesel, regardless its vegetable source. After this preliminary step MCR-ALS modeling was carried out only using relevant parts of the chromatograms. The resulting procedure was able to predict accurately the concentration of biodiesel in the BXX samples regardless of its origin.     

Simultaneous spectrophotometric determination of phenanthridine, phenanthridinone and phenanthridine N-oxide using multivariate calibration methods

The multivariate calibration methods, partial least squares (PLS) and principle component regression (PCR) have been used to determine phenanthridine, phenanthridinone and phenanthridine N-oxide in spiked human plasma samples. Resolution of binary and ternary mixtures of analytes with minimum sample pre-treatment and without analyte separation has been successfully achieved analyzing the UV spectral data. The net analyte signal (NAS) concept was also used to calculate multivariate analytical figures of merit such as limit of detection, selectivity and sensitivity. The simultaneous determination of three analytes was possible by PLS and PCR processing of sample absorbance in the 210–355 nm region. Good recoveries were obtained for both synthetic mixtures and spiked human plasma samples.     

Multivariate near infrared spectroscopy models for predicting the iodine value, CFPP, kinematic viscosity at 40 degrees C and density at 15 degrees C of biodiesel

Biodiesel is one of the main alternatives to fossil diesel. It is a non-toxic renewable resource, which leads to lower emissions of polluting gases. In fact, European governments are targeting the incorporation of 20% of biofuels in the fossil fuels until 2020.Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils or fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties.This work reports the use of near infrared (NIR) spectroscopy to determine some important biodiesel properties: the iodine value, the cold filter plugging point, the kinematic viscosity at 40 °C and the density at 15 °C. Principal component analysis was used to perform a qualitative analysis of the spectra and partial least squares regression to develop the calibration models between analytical and spectral data. The results support that NIR spectroscopy, in combination with multivariate calibration, is a promising technique applied to biodiesel quality control, in both laboratory and industrial-scale samples.     

Multivariate near infrared spectroscopy models for predicting the methyl esters content in biodiesel

Biodiesel is the main alternative to fossil diesel. The key advantages of its use are the fact that it is a non-toxic renewable resource, which leads to lower emissions of polluting gases. European governments are targeting the incorporation of 20% of biofuels in the general fuels until 2020.Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils/fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties.This work reports the use of near infrared (NIR) spectroscopy to determine the esters content in biodiesel as well as the content in linolenic acid methyl esters (C18:3) in industrial and laboratory-scale biodiesel samples. Furthermore, calibration models for myristic (C14:0), palmitic (C16:0), stearic (C18:0), oleic (C18:1), linoleic (C18:2) acid methyl esters were also obtained. Principal component analysis was used for the qualitative analysis of the spectra, while partial least squares regression was used to develop the calibration models between analytical and spectral data. The results confirm that NIR spectroscopy, in combination with multivariate calibration, is a promising technique to assess the biodiesel quality control in both laboratory-scale and industrial scale samples.     

Evaluation of statistical control charts for on-line radiation monitoring

Statistical control charts are presented for the evaluation of time series radiation counter data from flow cells used for monitoring of low levels of ⁹⁹TcO₄⁻ in environmental solutions. Control chart methods consisted of the 3-sigma (3σ) chart, the cumulative sum (CUSUM) chart, and the exponentially weighted moving average (EWMA) chart. Each method involves a control limit based on the detector background which constitutes the detection limit. Both the CUSUM and EWMA charts are suitable to detect and estimate sample concentration requiring less solution volume than when using a 3σ control chart. Data presented here indicate that the overall accuracy and precision of the CUSUM method is the best.     

Determination of residual oil in diesel oil by spectrofluorimetric and chemometric analysis

Multivariate calibration (PLS), principal components analysis (PCA) and linear discriminant analysis (LDA), associated to synchronous spectrofluorimetry, were used to identify and quantify non-transesterified residual vegetable oil in diesel oil with the addition of 2% of biodiesel (B2). The addition of residual oil, one of the easiest ways of adultering fuel, damages engines and leads to tax evasion. Using this method, the samples of diesel oil, B2, and B2 contaminated with residual oil were classified correctly and separated into three well-defined groups. The quantification of residual oil in B2 was carried out in the 0-25% (w/w) band, RMSEC and RMSEP values ranging from 0.26 to 0.48% (w/w) and 1.6-2.6% (w/w), respectively. The method is highly sensitive and efficient to identify and quantify this type of adulterant in which 100% of the samples were correctly classified and the average relative error was approximately 4% in the range 0.5-25% (w/w).     

Simultaneous determination of antazoline and naphazoline by the net analyte signal standard addition method and spectrophotometric technique

A novel net analyte signal standard addition method (NASSAM) was used for simultaneous determination of the drugs anthazoline and naphazoline. The NASSAM can be applied for determination of analytes in the presence of known interferents. The proposed method is used to eliminate the calibration and prediction steps of multivariate calibration methods; the determination is carried out in a single step for each analyte. The accuracy of the predictions against the H-point standard addition method is independent of the shape of the analyte and interferent spectra. The net analyte signal concept was also used to calculate multivariate analytical figures of merit, such as LOD, selectivity, and sensitivity. The method was successfully applied to the simultaneous determination of anthazoline and naphazoline in a commercial eye drop sample.     

Characterization of Biodiesel by Infrared Spectroscopy with Partial Least Square Discriminant Analysis

This paper reports a method to simultaneously classify 7% biodiesel and 93% diesel based on vegetable oil as the source of the biodiesel. Mafurra, moringa, and cotton biodiesel blends were characterized by infrared spectroscopy with partial least square discriminant analysis. The efficiency of model was evaluated based on the sensitivity and specificity. The model showed excellent results as all samples were correctly classified based on the raw material. Hence, the sensitivity and specificity parameters showed values of 1, which means 100% correct characterization of the samples in the calibration and prediction sets. Therefore, infrared spectroscopy with partial least square discriminant analysis is suitable for the characterization of biodiesel/diesel blends.