Renato Lajarim Carneiro

Electrical conductivity and emerging contaminant as markers of surface freshwater contamination by wastewater

The use of chemical markers of undoubted anthropogenic sources for surface freshwater contamination by wastewaters was evaluated employing correlations observed between measured physico-chemical parameters as the electrical conductivity and the concentration of different emerging organic compounds. During the period from April/2011 to April/2012 spatial-temporal variations and contamination patterns of two rivers (Piraí and Jundiaí rivers), São Paulo state, Brazil were evaluated. Seven physico-chemical parameters and concentrations of different classes of emerging contaminants were determined in samples collected in seven field campaigns. The high linear correlation coefficients obtained for the compounds diclofenac (r=0.9085), propanolol (r=0.8994), ibuprofen (r=0.8720) and atenolol (r=0.7811) with electrical conductivity, also corroborated by principal component analysis (PCA), point to the potential use of these compounds as markers of investigated surface water contamination by wastewaters. Due to specific inputs, these environmental markers showed very good effectiveness for the identification and differentiation of water body contamination by discharges of treated and untreated urban sewage.

Evaluation of analytical tools and multivariate methods for quantification of co-former crystals in ibuprofen-nicotinamide co-crystals.

Co-crystals are multicomponent substances designed by the addition of two or more different molecules in a same crystallographic pattern, in which it differs from the crystallographic motif of its co-formers. The addition of highly soluble molecules, like nicotinamide, in the crystallographic pattern of ibuprofen enhances its solubility more than 7.5 times, improving the properties of this widely used drug. Several analytical solid state techniques are used to characterize the ibuprofen-nicotinamide co-crystal, being the most used: mid-infrared (ATR-FTIR), differential scanning calorimetry (DSC), X-ray diffraction (XRPD) and Raman spectroscopy. These analytical solid state techniques were evaluated to quantify a mixture of ibuprofen-nicotinamide co-crystal and its co-formers in order to develop a calibration model to evaluate the co-crystal purity after its synthesis. Raman spectroscopy showed better result than all other techniques with a combination of multivariate calibration tools, presenting lower values of calibration and prediction errors. The partial least squares regression model gave a mean error lower than 5% for all components presented in the mixture. DSC and mid-infrared spectroscopy proved to be insufficient for quantification of the ternary mixture. XRPD presented good results for quantification of the co-formers, ibuprofen and nicotinamide, but fair results for the co-crystal. This is the first report of quantification of ibuprofen-nicotinamide co-crystal, among its co-formers. The quantification is of great importance to determine the yield of the co-crystallization reactions and the purity of the product obtained.

Green chromatographic fingerprinting: An environmentally friendly approach for the development of separation methods for fingerprinting complex matrices

A chromatographic fingerprint is a comprehensive method that reveals the distinctive pattern of peaks across the chromatogram for a given sample. It is considered an effective strategy to assess the identity and quality of herbal materials, as well as for the control of the quality of their derived products. HPLC is the most employed technique for these purposes and it is used routinely for quality control in industry. Hence, its impact on the environment should not be neglected. This work provides a rational and generic procedure to qualitatively fingerprint complex matrices. Resource- and time-saving experimental designs were selected; an alternative safer organic solvent was tested and a time-saving and innovative response entitled the green chromatographic fingerprinting response was developed and employed. This procedure was applied in the development of chromatographic fingerprints for extracts of Bauhinia forficata and Casearia sylvestris. Moreover, the response proposed here can be combined with a complementary metric available in the literature to compare methods using different solvents. According to this, the chromatographic fingerprints developed here using ethanol as the organic solvent provided a performance better than that of reference methods in which more harmful acetonitrile or methanol were employed.

Interval multivariate curve resolution in the dereplication of HPLC-DAD data from Jatropha gossypifolia.

INTRODUCTION Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. OBJECTIVE To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. METHODS Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). RESULTS The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. CONCLUSION The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples.

Laser-induced breakdown spectroscopy (LIBS) combined with hyperspectral imaging for the evaluation of printed circuit board composition.

In this study, laser-induced breakdown spectroscopy (LIBS) was combined with chemometric strategies (PCA, Principal Component Analysis) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to investigate the metal composition of a printed circuit board (PCB) sample from a mobile phone. Scanning electron microscopy-EDS was used for two main reasons: it was possible at the same time to visualize the sample surface, craters (made by the laser pulses) and also the chemical composition of the samples. A 30 mm×40 mm area of the mobile phone PCB sample, which was manufactured in 2011, was investigated. In this case, a matrix with 30 rows and 40 columns (1200 points) was analyzed, and 10 pulses were performed at each point. A total of 12,000 emission spectra were recorded in the wavelength range from 186 to 1040 nm. After an initial exploratory investigation using PCA, 18 emission lines were selected (representing the elements Al, Au, Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sb, Si, Sn, Ti and Zn) and then normalized by the relative intensities, and a new PCA was calculated with the autoscaled data. For example, Au and Si were mainly observed in the superficial electrical contacts and in the bulk of the PCB, respectively. A second sample (a mouse PCB) was also analyzed and Pb (emission lines 357.273, 363.956, 368.346, 373.994 and 405.780 nm) was identified in the solders. In addition, this element was determined using FAAS (flame atomic absorption spectrometry) and the Pb concentration was around 25% (w/w). This study opens the possibility for improved recycling processes and the chemical investigation of solid samples measuring a few millimeters in dimension without sample preparation.

Determination of acetylsalicylic acid in commercial tablets by SERS using silver nanoparticle-coated filter paper

In this work, filter paper was used as a low cost substrate for silver nanoparticles in order to perform the detection and quantification of acetylsalicylic acid by SERS in a commercial tablet. The reaction conditions were 150mM of ammonium hydroxide, 50mM of silver nitrate, 500mM of glucose, 12min of the reaction time, 45°C temperature, pretreatment with ammonium hydroxide and quantitative filter paper (1-2μm). The average size of silver nanoparticles deposited on the paper substrate was 180nm. Adsorption time of acetylsalicylic acid on the surface of the silver-coated filter paper was studied and an adsorption time of 80min was used to build the analytical curve. It was possible to obtain a calibration curve with good precision with a coefficient of determination of 0.933. The method proposed in this work was capable to quantify acetylsalicylic acid in commercial tablets, at low concentration levels, with relative error of 2.06% compared to the HPLC. The preparation of filter paper coated with silver nanoparticles using Tollens reagent presents several advantages such as low cost of synthesis, support and reagents; minimum amount of residuals, which are easily treated, despite the SERS spectroscopy presenting fast analysis, with low sample preparation and low amount of reactants as in HPLC analysis.

Multivariate curve resolution of pH gradient flow injection mixture analysis with correction of the Schlieren effect.

Multivariate curve resolution using alternating least squares (MCR-ALS) was used to quantify ascorbic (AA) and acetylsalicylic (ASA) acids in four pharmaceutical samples using a flow injection analysis (FIA) system with pH gradient and a diode array (DAD) spectrometer as a detector. Four different pharmaceutical drugs were analyzed, giving a data array of dimensions 51 x 291 x 61, corresponding respectively to number of samples, FIA times and spectral wavelengths. MCR-ALS was applied to these large data sets using different constraints to have optimal resolution and optimal quantitative estimations of the two analytes (AA and ASA). Since both analytes give an acid-basic pair of species contributing to the UV recorded signal, at least four components sholuld be proposed to model AA and ASA in synthetic mixture samples. Moreover, one additional component was needed to resolve accurately the Schlieren effect and another additional component was also needed to model the presence of possible interferences (like caffeine) in the commercial drugs tablets, giving therefore a total number of 6 independent components needed. The best quantification relative errors were around 2% compared to the reference values obtained by HPLC and by the oxidation-reduction titrimetric method, for ASA and AA respectively. In this work, the application of MCR-ALS allowed for the first time the full resolution of the FIA diffusion profile due to the Schlieren effect as an independent signal contribution, suggesting that the proposed MCR-ALS method allows for its accurate correction in FIA-DAD systems.

Acetone as a greener alternative to acetonitrile in liquid chromatographic fingerprinting

A considerable amount of chemical waste from liquid chromatography analysis is generated worldwide. Acetonitrile is the most employed solvent in liquid chromatography analyses since it exhibits favorable physicochemical properties for separation and detection, but it is an unwelcome solvent from an environmental point of view. Acetone might be a much greener alternative to replace acetonitrile in reversed-phase liquid chromatography, since both share similar physicochemical properties, but its applicability with ultraviolet absorbance-based detectors is limited. In this work, a reference method using acetonitrile and high-performance liquid chromatography coupled to an ultraviolet photodiode array detector coupled to a corona charged aerosol detector system was developed to fingerprint a complex sample. The possibility of effectively substituting acetonitrile with acetone was investigated. Design of experiments was adopted to maximize the number of peaks acquired in both fingerprint developments. The methods with acetonitrile or acetone were successfully optimized and proved to be statistically similar when only the number of peaks or peak capacity was taken into consideration. However, the superiority of the latter was evidenced when parameters of separation and those related to greenness were heuristically combined. A green, comprehensive, time- and resource-saving approach is presented here, which is generic and applicable to other complex matrices. Furthermore, it is in line with environmental legislation and analytical trends.

Simultaneous Quantification of Three Polymorphic Forms of Carbamazepine in the Presence of Excipients Using Raman Spectroscopy

The occurrence of polymorphic transitions is a serious problem for pharmaceutical companies, because it can affect the bioavailability of the final product. With several known polymorphic forms carbamazepine is one of the most problematic drugs in this respect. Raman spectroscopy is a vibrational technique that is becoming very important in the pharmaceutical field, mainly due to its highly specific molecular fingerprint capabilities and easy use as a process analytical tool. However, multivariate methods are necessary both for identification and quantification. In this work an analytical methodology using Raman spectroscopy and interval Partial Least Squares Regression (iPLS), was developed in order to quantify mixtures of carbamazepine polymorphs in the presence of the most common excipients. The three polymorphs CBZ I, CBZ III and CBZ DH (which is a dihydrate) were synthesized and characterized by PXRD and DSC. Subsequently, tablets were manufactured using excipients and 15 different mixtures of carbamazepine polymorphs. The iPLS model presented average prediction validation errors of 1.58%, 1.04% and 0.22% wt/wt, for CBZ I, CBZ III and CBZ DH, respectively, considering the whole mass of the tablet. The model presents a good prediction capacity and the proposed methodology could be used to perform quality control in final products.

Tracking the degradation of fresh orange juice and discrimination of orange varieties: An example of NMR in coordination with chemometrics analyses

Brazil is currently the largest exporter of concentrated orange juice and, unlike the other exporter countries, the domestic consumption is mainly based on the fresh orange juice. The quality control by evaluating the major chemical constituents under the influence of the most important factors, such as temperature and storage time of the product, is very important in this context. Therefore, the objective of this study was to evaluate the influence of temperature and time on the degradation of fresh orange juice for 24h, by using (1)H NMR technique and chemometric tools for data mining. The storage conditions at 24h led to the production of the formic, fumaric and acetic acids; and an increase of succinic and lactic acids and ethanol, which were observed at low concentration at the initial time. Furthermore, analysis by PCA has successfully distinguished the juice of different species/varieties as well as the metabolites responsible for their separation.