Spectroscopic Qualitative Analysis

Duckworth, James

doi:10.1016/b978-012764070-9/50007-x

Cited by 6 publications

(2 citation statements)

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“…It is worth noting that portable instruments can also automatically determine the measurement time required to obtain the spectrum of a sample suitable for result generation, either qualitative or quantitative. Benchtop FT-IR instruments have traditionally used the Euclidean distance algorithm for spectral matching (or a close relative, like correlation), 555,556 which was originally developed for vapor phase gas chromatographic-infrared (GC/IR) spectra. 557,558 Typically, these IR spectra have flat baselines, as compared to condensed phase samples, and narrow features in the O-H stretching region where there is little hydrogen bonding in the vapor phase.…”

Section: Applications Development For Portable Spectrometersmentioning

confidence: 99%

Portable Spectroscopy

Crocombe¹

2018

Appl Spectrosc

348

233

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Until very recently, handheld spectrometers were the domain of major analytical and security instrument companies, with turnkey analyzers using spectroscopic techniques from X-ray fluorescence (XRF) for elemental analysis (metals), to Raman, mid-infrared, and near-infrared (NIR) for molecular analysis (mostly organics). However, the past few years have seen rapid changes in this landscape with the introduction of handheld laser-induced breakdown spectroscopy (LIBS), smartphone spectroscopy focusing on medical diagnostics for low-resource areas, commercial engines that a variety of companies can build up into products, hyphenated or dual technology instruments, low-cost visible-shortwave NIR instruments selling directly to the public, and, most recently, portable hyperspectral imaging instruments. Successful handheld instruments are designed to give answers to non-scientist operators; therefore, their developers have put extensive resources into reliable identification algorithms, spectroscopic libraries or databases, and qualitative and quantitative calibrations. As spectroscopic instruments become smaller and lower cost, ''engines'' have emerged, leading to the possibility of being incorporated in consumer devices and smart appliances, part of the Internet of Things (IOT). This review outlines the technologies used in portable spectroscopy, discusses their applications, both qualitative and quantitative, and how instrument developers and vendors have approached giving actionable answers to non-scientists. It outlines concerns on crowdsourced data, especially for heterogeneous samples, and finally looks towards the future in areas like IOT, emerging technologies for instruments, and portable hyphenated and hyperspectral instruments.

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Section: Applications Development For Portable Spectrometersmentioning

confidence: 99%

Portable Spectroscopy

Crocombe¹

2018

Appl Spectrosc

348

233

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“…The usefulness of the R 2 values is discussed further in the validation of the calibration models. The mahalanobis distance (M-distance) [54,55] measures the distance of outlier points from the mean of the group samples, according to a scale derived from the variability in the training set. This method was found to be unsuccessful in identifying outliers in cross-validation experiments as none of the samples were identified as outliers except for the model unaged and light aged samples.…”

Section: Calibration Model Developmentmentioning

confidence: 99%

Developing a non-invasive tool to assess the impact of oxidation on the structural integrity of historic wool in Tudor tapestries

et al. 2017

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Near infrared spectroscopy (NIR) can be a useful diagnostic tool in the assessment of quality in textile, agricultural and various other industries. In cultural heritage applications, NIR as a non-invasive assessment tool is advantageous for understanding the composition or degradation of fragile historic objects that cannot be sampled. The direct interpretation of measured NIR spectra is complicated by overlapping bands produced from overtone and combination bands of chemical bonds. However, in combination with multivariate partial least squares (PLS) models and principal component analysis, the physicochemical properties of historic materials can potentially be identified by calibrating against a measured component. In this research, wool fibres from a sacrificial collection of historic tapestry fragments housed at Hampton Court Palace were analysed. The cystine oxidation products of historic wools which can be related to the embrittlement of fibres and ultimately fibre loss, were recorded using Fourier transform infrared (FTIR) spectroscopy. A PLS predictive model was then developed using previously measured NIR spectra for the same historic tapestry fragments to predict the ratios of the cystine oxidation species in historic wools measured in this research. The prediction of a validation set of historic tapestry fragments with known oxidation product ratios was found to be accurate to root mean squared errors of prediction (RMSEP) of 0.11 for cysteic acid/cystine dioxide, 0.03 for an oxidation ratio of cysteic acid/cystine monoxide and 0.06 for cystine dioxide/cystine monoxide. The model was applied successfully to an independent set of historic tapestry fragments with unknown oxidation ratios with an M-distance pass limit of 3. The models were also applied to NIR measurements of historic tapestries on open display with limited success. Alternative methods to investigate and account for errors in this research are proposed. The potential for NIR to be used by conservators as a non-invasive tool for the assessment of textiles, complementing current condition audit practices in use at heritage institutions is also discussed.

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