Alison Nordon

Process NMR spectrometry

A review is presented, covering the many advantages of NMR in process applications including the possibility of standardless quantitative analysis. The technique may provide a useful alternative for quantitative monitoring of batch and continuous reactions but it will not be suitable for trace analysis.

Improved method for kinetic studies in microreactors using flow manipulation and noninvasive Raman spectrometry

A novel method has been devised to derive kinetic information about reactions in microfluidic systems. Advantages have been demonstrated over conventional procedures for a Knoevenagel condensation reaction in terms of the time required to obtain the data (fivefold reduction) and the efficient use of reagents (tenfold reduction). The procedure is based on a step change from a low (e.g., 0.6 μL min(-1)) to a high (e.g., 14 μL min(-1)) flow rate and real-time noninvasive Raman measurements at the end of the flow line, which allows location-specific information to be obtained without the need to move the measurement probe along the microreactor channel. To validate the method, values of the effective reaction order n were obtained employing two different experimental methodologies. Using these values of n, rate constants k were calculated and compared. The values of k derived from the proposed method at 10 and 40 °C were 0.0356 ± 0.0008 mol(-0.3) dm(0.9) s(-1) (n = 1.3) and 0.24 ± 0.018 mol(-0.1) dm(0.3) s(-1) (n = 1.1), respectively, whereas the values obtained using a more laborious conventional methodology were 0.0335 ± 0.0032 mol(-0.4) dm(1.2) s(-1) (n = 1.4) at 10 °C and 0.244 ± 0.032 mol(-0.3) dm(0.9) s(-1) (n = 1.3) at 40 °C. The new approach is not limited to analysis by Raman spectrometry and can be used with different techniques that can be incorporated into the end of the flow path to provide rapid measurements.

Real-time monitoring of powder mixing in a convective blender using non-invasive reflectance NIR spectrometry

A convective blender based on a scaled down version of a high shear mixer-granulator was used to produce binary mixtures of microcrystalline cellulose (Avicel) and aspirin, citric acid, aspartame or povidone. Spectra of stationary Avicel or aspirin powder provided an indication of the information depth achieved with the NIR spectrometer used in the study, and confirmed previously reported effects of particle size and wavenumber. However, it was demonstrated that for 10% w/w aspirin in Avicel, the information depth at the C-H second overtone of aspirin (about 2.4 mm) was unaffected by changes in the particle size of aspirin and was determined by the major component. By making non-invasive NIR measurements as powders were mixed, it was possible to illustrate differences in the mixing characteristics of aspirin, citric acid, aspartame or povidone with Avicel, which were related to differences in the cohesive properties of the particles. Mixing profiles based on second overtone signals were better for quantitative analysis than those derived from first overtone measurements. It was also demonstrated that the peak-to-peak noise of the mixing profile obtained from the second overtone of aspirin changed linearly with the particle size of aspirin added to Avicel. Hence, measurement of the mixing profile in real time with NIR spectrometry provided simultaneously the opportunity to study the dynamics of powder mixing, make quantitative measurements and monitor possible changes in particle size during blending.

Comparison of in-line NIR, Raman and UV-visible spectrometries, and at-line NMR spectrometry for the monitoring of an esterification reaction

In-line Raman, near infrared and UV-visible spectometries, and at-line low-field NMR spectrometry have been used to monitor the acid-catalysed esterification of crotonic acid and butan-2-ol. Repeat reactions were carried out in a 1 L batch reactor. Spectra taken during the reactions, along with reference ester concentrations determined by gas chromatography (GC), were used to determine the concentration of 2-butyl crotonate as the reaction proceeded. Ester concentrations were determined from 1st derivative Raman and UV-visible spectra by employing univariate calibration models, whereas the low-field NMR and NIR data required multivariate analysis by partial least squares regression. The techniques have been compared on the basis of the accuracy and between-run precision of the 2-butyl crotonate concentrations, and the ability to determine the rate constant of the reaction in the shortest possible time after the start of the reaction. The ester concentrations determined by all of the techniques were similar to those obtained by the GC reference method. In-line UV-visible spectrometry gave the poorest between-run precision. Raman and NIR spectrometries provided an estimate of the rate constant of the reaction after 90 min when the ester concentration had reached 0.09 mol dm−3, meaning that if the rate constant at this time was not as expected then corrective action could be taken to salvage the batch.

Effects of particle size and cohesive properties on mixing studied by non-contact NIR

A scaled-down convective blender was used along with non-invasive NIR spectrometry to study the mixing of citric acid, aspirin, aspartame or povidone with microcrystalline cellulose. NIR mixing profiles were generated in real time using measurements at the 2nd overtone wavelength of the added compounds. Trends demonstrated previously for aspirin were confirmed for additions of citric acid: the magnitude of the 2nd overtone NIR measurements is less affected by changes in particle size than that of the 1st overtone; the peak-to-peak noise of the 2nd overtone NIR mixing profile increases with the particle size of the added compound. The study has demonstrated the usefulness of continuous NIR measurements for rapid evaluation of the mixing process when deciding the best particle size of microcrystalline cellulose to mix with compounds of different particle shape and cohesive properties. Smaller particle sizes of microcrystalline cellulose (53-106 microm) were better for aspirin (212-250 microm), whereas larger particles (212-250 microm) were better for aspartame (212-250 microm). The characteristics of the compounds also need to be considered when deciding the order of addition of secondary compounds when mixed with microcrystalline cellulose. The time required to achieve a uniform mixture was much less when povidone was added before aspirin, rather than vice versa.

Detection of counterfeit Scotch whisky samples using mid-infrared spectrometry with an attenuated total reflectance probe incorporating polycrystalline silver halide fibres

Two methods of analysis were developed to permit detection of counterfeit Scotch whisky samples using a novel attenuated total reflectance (ATR) diamond-tipped immersion probe for mid-infrared (MIR) spectrometry. The first method allowed determination of the ethanol concentration (35-45% (v/v)) in situ without dilution of the samples; the results obtained compared well with the supplied concentrations (average relative error of 1.2% and 0.8% for univariate and multivariate partial least squares (PLS) calibration, respectively). The second method involved analysis of dried residues of the whisky samples and caramel solutions on the diamond ATR crystal; principal component analysis (PCA) of the spectra was used to classify the samples and investigate the colorant added. Seventeen test whisky samples were successfully categorised as either authentic or counterfeit in a blind study when both MIR methods were used.

Quantitative Analysis of Powder Mixtures by Raman Spectrometry: the influence of particle size and its correction

Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest. In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness.

Maintaining the predictive abilities of multivariate calibration models by spectral space transformation

In quantitative on-line/in-line monitoring of chemical and bio-chemical processes using spectroscopic instruments, multivariate calibration models are indispensable for the extraction of chemical information from complex spectroscopic measurements. The development of reliable multivariate calibration models is generally time-consuming and costly. Therefore, once a reliable multivariate calibration model is established, it is expected to be used for an extended period. However, any change in the instrumental response or variations in the measurement conditions can render a multivariate calibration model invalid. In this contribution, a new method, spectral space transformation (SST), has been developed to maintain the predictive abilities of multivariate calibration models when the spectrometer or measurement conditions are altered. SST tries to eliminate the spectral differences induced by the changes in instruments or measurement conditions through the transformation between two spectral spaces spanned by the corresponding spectra of a subset of standardization samples measured on two instruments or under two sets of experimental conditions. The performance of the method has been tested on two data sets comprising NIR and MIR spectra. The experimental results show that SST can achieve satisfactory analyte predictions from spectroscopic measurements subject to spectrometer/probe alteration, when only a few standardization samples are used. Compared with the existing popular methods designed for the same purpose, i.e. global PLS, univariate slope and bias correction (SBC) and piecewise direct standardization (PDS), SST has the advantages of implementation simplicity, wider applicability and better performance in terms of predictive accuracy.

Solid-state electronic absorption, fluorescence and 13C CPMAS NMR spectroscopic study of thermo- and photo-chromic aromatic Schiff bases

Solid-state electronic absorption, fluorescence emission and 13C CPMAS spectroscopies have been applied to a series of aromatic Schiff bases displaying both ground and excited state intramolecular proton transfer phenomena. All the results can be explained on the basis of a thermal equilibrium between enolimine and keto–enamine tautomeric forms in the crystalline state. Most of the studied compounds are thermochromic. However, a few are photochromic. The carbon-13 NMR data in the solid state show, in general, residual (13C, 14N) dipolar coupling effects. In certain cases, however, where fast proton transfer occurs in the ground state, these effects are shown to be self-decoupled.

Dependence of Signal on Depth in Transmission Raman Spectroscopy

Recently, transmission Raman spectroscopy has been shown to be a valuable tool in the volumetric quantification of pharmaceutical formulations. In this work a Monte Carlo simulation and experimental study are performed to elucidate the dependence of the Raman signal on depth from the viewpoint of probing pharmaceutical tablets and powders in this experimental configuration. The transmission Raman signal is shown to exhibit a moderate bias toward the center of the tablets and this can be considerably reduced by using a recently developed Raman signal-enhancing concept, the “photon diode.” The enhancing element not only reduces the bias but also increases the overall Raman signal intensity and consequently improves the signal-to-noise ratio of the measured spectrum. Overall, its implementation with appropriately chosen reflectivity results in a more uniform volumetric sampling across the half of the tablet where the photon diode is used (or across the tablets entire depth if two photon diodes are used on each side of tablet) and enhanced overall sensitivity. These findings are substantiated experimentally on a segmented tablet by inserting a poly(ethelyne terephthalate) (PET) film doped with TiO2 at different depths and monitoring its contribution to the overall transmission Raman signal from the segmented tablet. The numerical simulations also indicate considerable sensitivity of the overall Raman signal to the absorption of the sample, which is in line with large migration distances traversed by photons in these measurements. The presence of sample absorption was shown numerically to reduce the signal enhancement effect while the overall depth-dependence profile remained broadly unchanged. The absorption was also shown to produce a depth profile with the photon diode similar to that without it, although with a reduced absolute intensity of Raman signals and diminished enhancement effect.