Raman Analysis of Dilute Aqueous Samples by Localized Evaporation of Submicroliter Droplets on the Tips of Superhydrophobic Copper Wires

Raman analysis of dilute aqueous solutions is normally prevented by their low signal levels. A very general method to increase the concentration to detectable levels is to evaporate droplets of the sample to dryness, creating solid deposits which are then Raman probed. Here, superhydrophobic (SHP) wires with hydrophilic tips have been used as supports for drying droplets, which have the advantage that the residue is automatically deposited at the tip. The SHP wires were readily prepared in minutes using electroless galvanic deposition of Ag onto copper wires followed by modification with a polyfluorothiol (3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-heptadecafluoro-1-decanethiol, HDFT). Cutting the coated wires with a scalpel revealed hydrophilic tips which could support droplets whose maximum size was determined by the wire diameter. Typically, 230 μm wires were used to support 0.6 μL droplets. Evaporation of dilute melamine droplets gave solid deposits which could be observed by scanning electron microscopy (SEM) and Raman spectroscopy. The limit of detection for melamine using a two stage evaporation procedure was 1 × 10^-6 mol dm^-3. The physical appearance of dried droplets of sucrose and glucose showed that the samples retained significant amounts of water, even under high vacuum. Nonetheless, the Raman detection limits of sucrose and glucose were 5 × 10^-4 and 2.5 × 10^-3 mol dm^-3, respectively, which is similar to the sensitivity reported for surface-enhanced Raman spectroscopy (SERS) detection of glucose. It was also possible to quantify the two sugars in mixtures at concentrations which were similar to those found in human blood through multivariate analysis.

Swellable polymer films containing Au nanoparticles for point-of-care therapeutic drug monitoring using surface-enhanced Raman spectroscopy

Large (10 × 10 cm) sheets of surface-enhanced Raman spectroscopy (SERS) active polymer have been prepared by stabilising metal nanoparticle aggregates within dry hydroxyethylcellulose (HEC) films. In these films the aggregates are protected by the polymer matrix during storage but in use they are released when aqueous analyte droplets cause the films to swell to their gel form. The fact that these "Poly-SERS" films can be prepared in bulk but then cut to size and stored in air before use means that they provide a cost effective and convenient method for routine SERS analysis. Here we have tested both Ag and Au Poly-SERS films for use in point-of-care monitoring of therapeutic drugs, using phenytoin as the test compound. Phenytoin in water could readily be detected using Ag Poly-SERS films but dissolving the compound in phosphate buffered saline (PBS) to mimic body fluid samples caused loss of the drug signal due to competition for metal surface sites from Cl^- ions in the buffer solution. However, with Au Poly-SERS films there was no detectable interference from Cl^- and these materials allowed phenytoin to be detected at 1.8 mg L^-1, even in PBS. The target range of detection of phenytoin in therapeutic drug monitoring is 10-20 mg L^-1. With the Au Poly-SERS films, the absolute signal generated by a given concentration of phenytoin was lower for the films than for the parent colloid but the SERS signals were still high enough to be used for therapeutic monitoring, so the cost in sensitivity for moving from simple aqueous colloids to films is not so large that it outweighs the advantages which the films bring for practical applications, in particular their ease of use and long shelf life.

Surface-enhanced Raman spectroscopy of novel psychoactive substances using polymer-stabilized Ag nanoparticle aggregates

A set of seized "legal high'' samples and pure novel psychoactive substances have been examined by surface-enhanced Raman spectroscopy using polymer-stabilized Ag nanoparticle (Poly-SERS) films. The films both quenched fluorescence in bulk samples and allowed identification of mu g quantities of drugs collected with wet swabs from contaminated surfaces.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

Idrossiapatite biologica e di sintesi: analisi attraverso spettroscopia Raman

Le tradizionali tecniche usate per l’analisi della struttura e della composizione comprendono, tra le altre, microscopia ottica, microscopia elettronica, diffrazione a raggi X e analisi chimica. In generale però, la maggior parte di questi metodi richiede una procedura di preparazione che può modificare la struttura o la composizione del campione. È necessario infatti che il campione non subisca alterazioni particolari durante la fase di preparazioni in modo tale che le condizioni fisiologiche rimangano il più possibile simili a quelle che si hanno in situ. Una tecnica che ultimamente sta diventando sempre più significativa in ambito biomedico è la spettroscopia Raman. Innanzitutto con l’analisi Raman la quantità di materiale da studiare per ottenere buoni risultati è minima, visto che possono essere studiati campioni che vanno dai micro ai nanogrammi; inoltre, possono essere analizzati campioni umidi e a pressione atmosferica, condizioni che rispecchiano verosimilmente quelle fisiologiche. Questo tipo di analisi è inoltre vantaggiosa dato che riesce a identificare diversi composti chimici, ha un’elevata risoluzione spaziale (0.6-1µm), riuscendo quindi ad analizzare campioni molto piccoli, ha tempi di misura brevi e può essere utilizzato più volte sullo stesso campione senza che quest’ultimo venga danneggiato. Nel seguente elaborato si sono riportati i risultati di diversi studi condotti sull’idrossiapatite naturale/biologica e sintetica ottenuti mediante questa tecnica spettroscopica. In particolare, ci si è soffermati sulla diversa concentrazione di OH- presente nell’apatite stechiometrica rispetto a quella biologica e di come tale concentrazione sia influenzata dalla presenza o meno dello ione carbonato. Si riportano inoltre le analisi condotte su campioni sintetici e biologici per comprendere se le molecole di acqua si trovino all’interno della struttura del minerale (acqua di bulk) o se siano solamente assorbite in superficie.

Concentración de cationes (Ca2+, Mg2+, Fe2+3+, K+) en semillas de frijol negro (Phaseolus vulgaris L.) usando espectroscopia de absorción atómica

Se investiga la concentración de cationes (Ca,Fe,K,Mg),en el frijol negro,(Phaseolus vulgaris L. var. Tineco), usando un analizador de absorción atómica. Para tal efecto se procede a secar la muestra y luego se digiere en un medio acido. Se preparan las soluciones standard correspondiente a los cationes que se quiere investigar y luego se comparan estas concentraciones con las concentraciones de los iones en la muestra. El cálculo de la concentración (desconocida), de los cationes en la muestra, se hace por medio de simple aritmética. En este trabajo se reporta la cantidad en p. p. m. de los elementos arriba mencionados, presente en un gramo de la muestra original. Los resultados obtenidos fueron: Fe = 337.5 p. p. m. ; Ca = 150 p. p. m. ; Mg = 150 p. p. m. y K = 4X104p. p. m.

Espectroscopia no infravermelho e método quimiométrico para a pesquisa de antimicrobianos em leite da microrregião de Pato Branco - PR

Considering the social and economic importance that the milk has, the objective of this study was to evaluate the incidence and quantifying antimicrobial residues in the food. The samples were collected in dairy industry of southwestern Paraná state and thus they were able to cover all ten municipalities in the region of Pato Branco. The work focused on the development of appropriate models for the identification and quantification of analytes: tetracycline, sulfamethazine, sulfadimethoxine, chloramphenicol and ampicillin, all antimicrobials with health interest. For the calibration procedure and validation of the models was used the Infrared Spectroscopy Fourier Transform associated with chemometric method based on Partial Least Squares regression (PLS - Partial Least Squares). To prepare a work solution antimicrobials, the five analytes of interest were used in increasing doses, namely tetracycline from 0 to 0.60 ppm, sulfamethazine 0 to 0.12 ppm, sulfadimethoxine 0 to 2.40 ppm chloramphenicol 0 1.20 ppm and ampicillin 0 to 1.80 ppm to perform the work with the interest in multiresidues analysis. The performance of the models constructed was evaluated through the figures of merit: mean square error of calibration and cross-validation, correlation coefficients and offset performance ratio. For the purposes of applicability in this work, it is considered that the models generated for Tetracycline, Sulfadimethoxine and Chloramphenicol were considered viable, with the greatest predictive power and efficiency, then were employed to evaluate the quality of raw milk from the region of Pato Branco . Among the analyzed samples by NIR, 70% were in conformity with sanitary legislation, and 5% of these samples had concentrations below the Maximum Residue permitted, and is also satisfactory. However 30% of the sample set showed unsatisfactory results when evaluating the contamination with antimicrobials residues, which is non conformity related to the presence of antimicrobial unauthorized use or concentrations above the permitted limits. With the development of this work can be said that laboratory tests in the food area, using infrared spectroscopy with multivariate calibration was also good, fast in analysis, reduced costs and with minimum generation of laboratory waste. Thus, the alternative method proposed meets the quality concerns and desired efficiency by industrial sectors and society in general.

Desenvolvimento e aplicação de modelo de calibração multivariada para determinação de açúcares e ácidos orgânicos em bebidas comerciais utilizando espectroscopia no infravermelho

The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).