963 resultados para surface–enhanced Raman spectroscopy


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The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C-4-C-24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration nu(C = O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm(-1). Further, molar unsaturation could be correlated with the ratio of the nu(C = O) to either nu(C = C) or delta(H-C = ) with R-2 > 0.995. Chain length was correlated with the delta(CH2)(tw)/nu(C = O) ratio, (where "tw" indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R-2 > 0.99 for liquid samples. Combining the odd- ani even-numbered carbon chain data in a single plot reduced the correlation to R-2 = 0.94-0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R-2 > 0.99) was nu(C = C)/delta(CH2)(SC) (where "sc" indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

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Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R-2=0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was 1.25%. The Raman method has the best prediction ability for unsaturated FA (R-2=0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 tDelta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R-2=0.80) and solid fat content at low temperature (R-2=0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R-2=0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.

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The potential of Raman spectroscopy for the determination of meat quality attributes has been investigated using data from a set of 52 cooked beef samples, which were rated by trained taste panels. The Raman spectra, shear force and cooking loss were measured and PLS used to correlate the attributes with the Raman data. Good correlations and standard errors of prediction were found when the Raman data were used to predict the panels' rating of acceptability of texture (R-2 = 0.71, Residual Mean Standard Error of Prediction (RMSEP)% of the mean (mu) = 15%), degree of tenderness (R-2 = 0.65, RMSEP% of mu = 18%), degree of juiciness (R-2 = 0.62, RMSEP% of mu = 16%), and overall acceptability (R-2 = 0.67, RMSEP% of mu = 11%). In contrast, the mechanically determined shear force was poorly correlated with tenderness (R-2 = 0.15). Tentative interpretation of the plots of the regression coefficients suggests that the alpha-helix to beta-sheet ratio of the proteins and the hydrophobicity of the myofibrillar environment are important factors contributing to the shear force, tenderness, texture and overall acceptability of the beef. In summary, this work demonstrates that Raman spectroscopy can be used to predict consumer-perceived beef quality. In part, this overall success is due to the fact that the Raman method predicts texture and tenderness, which are the predominant factors in determining overall acceptability in the Western world. Nonetheless, it is clear that Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of beef quality parameters.

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The ability of Raman spectroscopy and Fourier transform infrared (FT-IR) microscopy to discriminate between resins used for the manufacture of architectural finishes was examined in a study of 39 samples taken from a commercial resin library. Both Raman and FT-IR were able to discriminate between different types of resin and both split the samples into several groups (six for FT-IR, six for Raman), each of which gave similar, but not identical, spectra. In addition, three resins gave unique Raman spectra (four in FTIR). However, approximately half the library comprised samples that were sufficiently similar that they fell into a single large group, whether classified using FT-IR or Raman, although the remaining samples fell into much smaller groups. Further sub-division of the FT-IR groups was not possible because the experimental uncertainty was of similar magnitude to the within-group variation. In contrast, Raman spectroscopy was able to further discriminate between resins that fell within the same groups because the differences in the relative band intensities of the resins, although small, were larger than the experimental uncertainty.

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The potential of Raman spectroscopy to discriminate between architectural finishes (household paint) has been investigated using a test set of 51

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Previous work by the authors Walker et al. [2007b. Fluidised bed characterisation using Raman spectroscopy: applications to pharmaceutical processing. Chemical Engineering Science 62, 3832–3838] illustrated that Raman spectroscopy could be used to provide 3-D maps of the concentration and chemical structure of particles in motion in a fluidised bed, within a relatively short (120 s) time window. Moreover, we reported that the technique, as outlined, has the potential to give detailed in-situ information on how the structure and composition of granules/powders within the fluidised bed (dryer or granulator) vary with the position and evolve with time. In this study we extended the original work by shortening the time window of the Raman spectroscopic analysis to 10 s, which has allowed the in-situ real-time characterisation of a fluidised bed granulation process. Here we show an important new use of the technique which allows in-situ measurement of the composition of the material within the fluidised bed in three spatial dimensions and as a function of time. This is achieved by recording Raman spectra using a probe positioned within the fluidised bed on a long-travel x–y–z stage. In these experiments the absolute Raman intensity is used to provide a direct measure of the amount of any given material in the probed volume, i.e. a particle density. Particle density profiles have been calculated over the granulation time and show how the volume of the fluidised bed decreases with an increase mean granule size. The Raman spectroscopy analysis indicated that nucleation/coalescence in this co-melt fluidised hot melt granulation system occurred over a relatively short time frame (t<30 s). The Raman spectroscopic technique demonstrated accurate correlation with independent granulation experiments which provided particle size distribution analysis. The similarity of the data indicates that the Raman spectra accurately represent solids ratios within the bed, and thus the techniques quantitative capabilities for future use in the pharmaceutical industry.

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Raman microscopy is used to investigate the spectral features of selected compounds known to be involved in the development of the eye disease age-related macular degeneration (AMD). Diagnostic features were identified in synthetic samples of these compounds and in a biological matrix. The study demonstrates the potential of Raman microscopy for the development of diagnostic markers of the onset of AMD. Copyright (C) 2008 John Wiley & Sons, Ltd.

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In this investigation Raman spectroscopy was shown to be a method that could be used to monitor the polymerisation of PMMA bone cement. Presently there is no objective method that orthopaedic surgeons can use to quantify the curing process of cement during surgery. Raman spectroscopy is a non-invasive, non-destructive technique that could offer such an option. Two commercially available bone cements (Palacos® R and SmartSet® HV) and different storage conditions (4 and 22°C) were used to validate the technique. Raman spectroscopy was found to be repeatable across all conditions with the completion of the polymerisation process particularly easy to establish. All tests were benchmarked against current temperature monitoring methods outlined in ISO and ASTM standards. There was found to be close agreement with the standard methods and the Raman spectroscopy used in this study.