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

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

A low-field medium-resolution NMR spectrometer, with an operating frequency of 29 MHz for 1H, has been assessed for on-line process analysis. A flow cell that incorporates a pre-magnetisation region has been developed to minimise the decrease in the signal owing to incomplete polarisation effects. The homogeneous esterification reaction of crotonic acid and 2-butanol was monitored using a simple sampling loop; it was possible to monitor the progression of the reaction through changes in CH signal areas of butanol and butyl crotonate. On-line analysis of heterogeneous water-toluene mixtures proved more challenging and a fast sampling loop system was devised for use with a 5 L reactor. The fast sampling loop operated at a flow rate of 8 L min(-1) and a secondary sampling loop was used to pass a sub-sample through the NMR analyser at a slower (mL min(-1)) rate. It was shown that even with super-isokinetic sampling conditions, unrepresentative sampling could occur owing to inadequate mixing in the reactor. However, it was still possible to relate the 1H NMR signal obtained at a flow rate of 60 mL min(-1) to the composition of the reactor contents.

Two novel methods are described for direct quantitative analysis of NMR free induction decay (FID) signals. The methods use adaptations of the generalized rank annihilation method (GRAM) and the direct exponential curve resolution algorithm (DECRA). With FID-GRAM, the Hankel matrix of the sample signal is compared with that of a reference mixture to obtain quantitative data about the components. With FID-DECRA, a single-sample FID matrix is split into two matrices, allowing quantitative recovery of decay constants and the individual signals in the FID. Inaccurate results were obtained with FID-GRAM when there were differences between the frequency or transverse relaxation time of signals for the reference and test samples. This problem does not arise with FID-DECRA, because comparison with a reference signal is unnecessary. Application of FID-DECRA to 19F NMR data, which contained overlapping signals from three components, gave concentrations comparable to those derived from partial least squares (PLS) analysis of the Fourier transformed spectra. However, the main advantage of FID-DECRA was that accurate (<5% error) and precise (2.3% RSD) results were obtained using only one calibration sample, whereas with PLS, a training set of 10 standard mixtures was used to give comparable accuracy and precision.