Quantitative analysis using Raman spectroscopy without spectral standardization

Abstract

Compared with other spectroscopic techniques, Raman spectroscopy has not generally been applied to problems of quantitative analysis, primarily because it is assumed that spectral irreproducibility due to source, sample or optical parameters requires standardization of the Raman signal. However, a custom-built Raman spectrometer with a 785 nm excitation source has yielded a spectral peak height reproducibility of 0.5% relative standard deviation. Quantitative studies of glucose in water, ethanol in water and p-xylene in m-xylene, described here, illustrate the linearity and precision of the Raman system. In order to estimate the linear dynamic range of the instrument, detection limits were determined for benzene in water and in CCl 4 , demonstrating a range from sub-ppm to 100% concentration. Specific factors affecting spectral reproducibility, and therefore quantitative results, are discussed. The quality of the results presented indicates that Raman spectroscopy should be a more common quantitative spectroscopic technique.

Organic semiconductor distributed feedback (DFB) laser as excitation source in Raman spectroscopy

“…Since the first reports in 1928 [1,2], Raman spectroscopy has played an increasingly important role in chemometrics [3,4], material science [5][6][7][8], life science [9][10][11][12], quality control in industrial processes [13,14] and recently in nanostructure characterization [15][16][17]. The advent of laser as an intense and monochromatic source of excitation light improved the Raman signals dramatically [18][19][20].…”

Quantitative of pesticide residue on the surface of navel orange by confocal microscopy Raman spectrometer

“…12,13 Quantitative Raman analyses have been directly applied to liquids. [14][15][16] The development of Raman spectroscopy is based on the Raman scattering. Comparing with conventional chemical analysis methods, Raman spectroscopic technique's features are nondestructive, rapid, environmentally protective, highly sensitive and require no sample preparation.…”

Development and Integration of Block Operations for Data Invariant Automation of Digital Preprocessing and Analysis of Biological and Biomedical Raman Spectra

“…It is used to make spectra from different samples directly comparable with one another 134 and to facilitate the determination of analyte concentrations. 135 A number of normalization methods exist, but not all of them are suitable for quantification or comparative use with heterogeneous spectra, and we will not address them here. Among the remainder, constant sum normalization (or the related vector normalization) is suitable only for homogenous spectra where a dilution effect is present, 102,103,134 but a variant 103 can be applied to heterogeneous spectra if the most probable dilution effect can be estimated.…”

“…Normalization based on an internal standard is a common and excellent method to correct for undesirable variations in instruments and some sample characteristics. 135 The incorporation of an internal standard is not always possible (e.g., when working with live cells or tissues), and hence proxies 106,136 are often resorted to, which are less reliable. External standards can be useful to compensate for some instrumental variation, such as those due to lasers and optics 104,135 and where a tight relationship between external standards and analyte exists, such as with the volume-exclusion method, 102 for sample variations as well.…”

“…Normalization, however, is not always necessary where the instrumentation is very stable, and sample variations do not pose problems. 135 The results of volume-exclusion normalization are shown in Fig. 7.…”