•High efficiency thermal vaporiser designed and used for on-line reaction monitoring.•Concentration profiles of all reactants and products obtained from mass spectra.•By-product formed from the presence of an impurity detected by MS but not MIR.•Mass spectrometry can detect trace and bulk components unlike molecular spectrometry.A specially designed thermal vaporiser was used with a process mass spectrometer designed for gas analysis to monitor the esterification of butan-1-ol and acetic anhydride. The reaction was conducted at two scales: in a 150 mL flask and a 1 L jacketed batch reactor, with liquid delivery flow rates to the vaporiser of 0.1 and 1.0 mL min−1, respectively. Mass spectrometry measurements were made at selected ion masses, and classical least squares multivariate linear regression was used to produce concentration profiles for the reactants, products and catalyst. The extent of reaction was obtained from the butyl acetate profile and found to be 83% and 76% at 40 °C and 20 °C, respectively, at the 1 L scale. Reactions in the 1 L reactor were also monitored by in-line mid-infrared (MIR) spectrometry; off-line gas chromatography (GC) was used as a reference technique when building partial least squares (PLS) multivariate calibration models for prediction of butyl acetate concentrations from the MIR spectra. In validation experiments, good agreement was achieved between the concentration of butyl acetate obtained from in-line MIR spectra and off-line GC. In the initial few minutes of the reaction the profiles for butyl acetate derived from on-line direct liquid sampling mass spectrometry (DLSMS) differed from those of in-line MIR spectrometry owing to the 2 min transfer time between the reactor and mass spectrometer. As the reaction proceeded, however, the difference between the concentration profiles became less noticeable. DLSMS had advantages over in-line MIR spectrometry as it was easier to generate concentration profiles for all the components in the reaction. Also, it was possible to detect the presence of a simulated impurity of ethanol (at levels of 2.6 and 9.1% mol/mol) in butan-1-ol, and the resulting production of ethyl acetate, by DLSMS, but not by in-line MIR spectrometry.

A thermal vaporiser has been designed for analysis of liquid streams by a process mass spectrometer normally used for gas analysis. Concentrations of benzene, toluene and o-xylene at mg kg−1 levels in ethanol were determined from continuous vaporisation of the liquid. Ions with m/z values of 39, 57, 73, 77, 78, 91, 92 and 106 were selected and the optimal regression model (multiple linear regression with mean-centring) was found using an automated design of experiments approach to calibration model selection. It was discovered that the linearity of the response allowed excellent calibration to be performed using only four standards (at 0 and 110 mg kg−1 for each of the three analytes) and that there were minimal inter-analyte interferences. The detection limit of benzene, toluene and o-xylene was 0.5, 0.8 and 0.5 mg kg−1, respectively. Average differences between the actual and predicted concentrations, expressed as a percentage of the actual concentrations, for 27–82 mg kg−1 of benzene, toluene and o-xylene were 0.5–1.4%, 0.0–0.4% and 0.3–1.6%, respectively, while the average relative standard deviations were 1.3–2.6%, 1.0–2.5% and 1.1–2.3%, respectively. Detection of 3 mg kg−1 changes in the concentration of each of the analytes (at the 36 mg kg−1 level) was also demonstrated, indicating the sensitivity of the technique and the potential ability of the procedure to detect minor deviations in the specification of process streams from continuous analysis.

A 785 nm diode laser and probe with a 6 mm spot size were used to obtain spectra of stationary powders and powders mixing at 50 rpm in a high shear convective blender. Two methods of assessing the effect of particle characteristics on the Raman sampling depth for microcrystalline cellulose (Avicel), aspirin or sodium nitrate were compared: (i) the information depth, based on the diminishing Raman signal of TiO2 in a reference plate as the depth of powder prior to the plate was increased, and (ii) the depth at which a sample became infinitely thick, based on the depth of powder at which the Raman signal of the compound became constant. The particle size, shape, density and/or light absorption capability of the compounds were shown to affect the “information” and “infinitely thick” depths of individual compounds. However, when different sized fractions of aspirin were added to Avicel as the main component, the depth values of aspirin were the same and matched that of the Avicel: 1.7 mm for the “information” depth and 3.5 mm for the “infinitely thick” depth. This latter value was considered to be the minimum Raman sampling depth when monitoring the addition of aspirin to Avicel in the blender. Mixing profiles for aspirin were obtained non-invasively through the glass wall of the vessel and could be used to assess how the aspirin blended into the main component, identify the end point of the mixing process (which varied with the particle size of the aspirin), and determine the concentration of aspirin in real time. The Raman procedure was compared to two other non-invasive monitoring techniques, near infrared (NIR) spectrometry and broadband acoustic emission spectrometry. The features of the mixing profiles generated by the three techniques were similar for addition of aspirin to Avicel. Although Raman was less sensitive than NIR spectrometry, Raman allowed compound specific mixing profiles to be generated by studying the mixing behaviour of an aspirin–aspartame–Avicel mixture.Graphical abstractHighlights► Powder blending monitored non-invasively by wide area Raman spectrometry. ► Effect of particle size on sampling depth and Raman signal investigated for wide area illumination. ► Raman measurements used to monitor mixing dynamics, determine end-point and perform quantitative analysis. ► Higher chemical specificity of Raman compared to near infrared spectrometry offers advantages for multi-component mixtures.

A total of 383 tablets of a pharmaceutical product were analyzed by backscatter and transmission Raman spectrometry to determine the concentration of an active pharmaceutical ingredient (API), chlorpheniramine maleate, at the 2% m/m (4 mg) level. As the exact composition of the tablets was unknown, external calibration samples were prepared from chlorpheniramine maleate and microcrystalline cellulose (Avicel) of different particle size. The API peak at 1594 cm–1 in the second derivative Raman spectra was used to generate linear calibration models. The API concentration predicted using backscatter Raman measurements was relatively insensitive to the particle size of Avicel. With transmission, however, particle size effects were greater and accurate prediction of the API content was only possible when the photon propagation properties of the calibration and sample tablets were matched. Good agreement was obtained with HPLC analysis when matched calibration tablets were used for both modes. When the calibration and sample tablets are not chemically matched, spectral normalization based on calculation of relative intensities cannot be used to reduce the effects of differences in physical properties. The main conclusion is that although better for whole tablet analysis, transmission Raman is more sensitive to differences in the photon propagation properties of the calibration and sample tablets.

Transmission Raman measurements of a 1 mm thick sulfur-containing disk were made at different positions as it was moved through 4 mm of aspirin (150–212 μm) or microcrystalline cellulose (Avicel) of different size ranges (<38, 53–106, and 150–212 μm). The transmission Raman intensity of the sulfur interlayer at 218 cm–1 was lower when the disk was placed at the top or bottom of the powder bed, compared to positions within the bed and the difference between the sulfur intensity at the outer and inner positions increased with Avicel particle size. Also, the positional intensity difference was smaller for needle-shaped aspirin than for granular Avicel of the same size. The attenuation coefficients for the propagation of the exciting laser and transmitted Raman photons through the individual powders were the same but decreased as the particle size of Avicel increased; also, the attenuation coefficients for propagation through 150–212 μm aspirin were almost half of those through similar sized Avicel particles. The study has demonstrated that particulate size and type affect transmitted Raman intensities and, consequently, such factors need to be considered in the analysis of powders, especially if particle properties vary between the samples.

Analysis of needle-shaped particles of cellobiose octaacetate (COA) obtained from vacuum agitated drying experiments was performed using three particle size analysis techniques: laser diffraction (LD), focused beam reflectance measurements (FBRM) and dynamic image analysis. Comparative measurements were also made for various size fractions of granular particles of microcrystalline cellulose. The study demonstrated that the light scattering particle size methods (LD and FBRM) can be used qualitatively to study the attrition that occurs during drying of needle-shaped particles, however, for full quantitative analysis, image analysis is required. The algorithm used in analysis of LD data assumes the scattering particles are spherical regardless of the actual shape of the particles under evaluation. FBRM measures a chord length distribution (CLD) rather than the particle size distribution (PSD), which in the case of needles is weighted towards the needle width rather than their length. Dynamic image analysis allowed evaluation of the particles based on attributes of the needles such as length (e.g. the maximum Feret diameter) or width (e.g. the minimum Feret diameter) and as such, was the most informative of the techniques for the analysis of attrition that occurred during drying.

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 dm0.9 s−1 (n = 1.3) and 0.24 ± 0.018 mol−0.1 dm0.3 s−1 (n = 1.1), respectively, whereas the values obtained using a more laborious conventional methodology were 0.0335 ± 0.0032 mol−0.4 dm1.2 s−1 (n = 1.4) at 10 °C and 0.244 ± 0.032 mol−0.3 dm0.9 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.

The evaporation of methanol from needle-shaped particles of cellobiose octaacetate (COA) has been studied directly in a jacketed vacuum drier using in situ measurements by Raman spectrometry. A design of experiments (DoE) approach was used to investigate the effects of three parameters (method of agitation, % solvent loss on drying and jacket temperature), with the intention of minimising the drying time and extent of particle attrition. Drying curves based on Raman signals for methanol and COA in the spectra of the wet particles indicated the end of drying and revealed three stages in the drying process that could be used to monitor the progress of solvent removal in real time. Off-line particle size measurements based on laser diffraction were made to obtain information on the extent of attrition, to compare with the trends revealed by the Raman drying curves. The study demonstrated that non-invasive Raman spectrometry can be used to study the progress of drying during agitation of particles in a vacuum drier, allowing optimisation of operating conditions to minimise attrition and reduce drying times. Although a correlation between particle size and off-line Raman measurements of COA was demonstrated, it was not possible to derive equivalent information from the in situRaman spectra owing to the greater effects of particle motion or bulk density variations of the particles in the drier.

Broadband acoustic transducers, including an intrinsically safe device, were assessed for non-invasive monitoring of aspirin, citric acid or Avicel mixing in a bench scale convective blender. The frequency information content of the acoustic emission (AE) spectra depends on the response characteristics of the transducers, which vary depending on the design. As acoustic waves generated from the impact of particles propagated through and around the glass mixing vessel, comparable spectra were obtained from different locations on the glass. The intensity of AE increased as the impeller speed, mass of powder or density of the particles was increased. AE also increased with particle size, with a relatively greater increase in intensity at lower frequencies. Mixing profiles were generated in real time from the change in the integrated intensity over selected frequency ranges on addition of aspirin to Avicel; the AE signal initially increased and then came to a plateau as the mixture became homogeneous. The average plateau signal was plotted against concentration for three different particle size ranges of aspirin in Avicel; for aspirin concentrations <21% m/m the increase in the AE was relatively small with no discernable effects of the aspirin particle size; however, for >21% m/m aspirin, there was a proportionally greater increase in AE, and particle size effects were more obvious. The study has shown that AE is relatively easy to measure non-invasively during powder mixing, but has poorer sensitivity than NIR spectrometry for detection of effects caused by addition of secondary compounds, especially at smaller particle sizes.

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.

Non-invasive NIR spectrometry has been used to monitor in situ the seed stage of a streptomyces fermentation process. The main spectral change occurred at 7263 cm−1 in the 1st derivative spectrum, and from comparison with off-line NIR spectra acquired of components present in the fermentation broth, can be attributed to biomass. The biomass signal was constant for the first 20 h of the seed stage, after which it decreased before increasing again. The time at which the minimum occurred in the NIR profile was either the same or slightly earlier than that at which a maximum in the carbon dioxide evolution rate (CER) occurred. The changes observed for the biomass signal in the NIR spectra can be attributed to growth and then fragmentation of mycelia, which indicates a change in metabolic activity. Hence, it may be possible to use NIR spectrometryin situ to determine the optimum transfer time for the seed stage of a fermentation process. Spectra were also acquired of the final stage of the same fermentation process. The variation in the biomass signal in the NIR spectra was more complicated in the final stage owing to changes in stir rate, and biomass concentration and morphology.

Broadband acoustic emission signals were obtained by attaching a piezoelectric transducer, sensitive up to 750 kHz, to the external wall of a 1 L jacketed glass reactor. Measurements were acquired of itaconic acid particles mixing in toluene; the total area of the acoustic emission signal from 55–500 kHz increased when the particle concentration, particle size or stir rate were increased. Signals at frequencies above 200 kHz were less sensitive to changes in particle size than those at lower frequencies. From calculation of the area of the signal in the range 55–200 kHz as a percentage of the signal area over the range 55–500 kHz, for mixtures of different size ranges of itaconic acid, it was possible to obtain an estimate of the mean particle size of a mixture. The heterogeneous esterification reaction of itaconic acid and 1-butanol was monitored non-invasively. A decrease in the overall acoustic signal area between 60 and 500 kHz was observed as the reaction progressed. Particle size and concentration information were contained in the amplitude of the acoustic emission signal, while the emission frequency yielded information on changes in the mean particle size.

The suitability of non-invasive NIR and Raman spectrometries for determination of % ethanol content has been investigated. Samples of whisky, vodka and sugary alcoholic drinks were analysed in 200 mL (flat) and 700 mL (round) glass bottles. The NIR spectrometer used double transmission measurements and was limited mainly to analysis of the signal produced at about 10,000 cm−1 by water and ethanol in the samples. The Raman measurements, produced using a 785 nm laser, were based on a sharp signal from ethanol at 880 cm−1. A multivariate calibration model, based on a combined PCA–PLS algorithm, was required for analysis by NIR spectrometry, whereas a univariate calibration model was suitable for Raman spectrometry. Both techniques were limited to measurements in clear glass bottles as strong absorption/fluorescence occurred with coloured glass bottles. Bottle-to-bottle variations contributed the largest uncertainty to the measurements obtained for a 20% (v/v) ethanol solution in flat bottles: 2.3% R.S.D. for NIR spectrometry and 2.2% R.S.D. for Raman spectrometry. For 700 mL round bottles, which have stricter manufacturing tolerances on glass thickness, the bottle-to-bottle variability for Raman spectrometry was 1.4% R.S.D. When spirit samples with ethanol concentrations in the range 19.9–61.7% (v/v) were analysed, the precision (average R.S.D.) was 0.4 and 0.5% for NIR (flat bottles) and Raman (round bottles) spectrometries, respectively, and the average accuracy was 2.1 and 2.9%, respectively. When a calibration model constructed from NIR data acquired on 1 day was applied to data sets collected over a 15-day period, the average error was 3.9%.

A thermal vaporiser has been designed for analysis of liquid streams by a process mass spectrometer normally used for gas analysis. Concentrations of benzene, toluene and o-xylene at mg kg−1 levels in ethanol were determined from continuous vaporisation of the liquid. Ions with m/z values of 39, 57, 73, 77, 78, 91, 92 and 106 were selected and the optimal regression model (multiple linear regression with mean-centring) was found using an automated design of experiments approach to calibration model selection. It was discovered that the linearity of the response allowed excellent calibration to be performed using only four standards (at 0 and 110 mg kg−1 for each of the three analytes) and that there were minimal inter-analyte interferences. The detection limit of benzene, toluene and o-xylene was 0.5, 0.8 and 0.5 mg kg−1, respectively. Average differences between the actual and predicted concentrations, expressed as a percentage of the actual concentrations, for 27–82 mg kg−1 of benzene, toluene and o-xylene were 0.5–1.4%, 0.0–0.4% and 0.3–1.6%, respectively, while the average relative standard deviations were 1.3–2.6%, 1.0–2.5% and 1.1–2.3%, respectively. Detection of 3 mg kg−1 changes in the concentration of each of the analytes (at the 36 mg kg−1 level) was also demonstrated, indicating the sensitivity of the technique and the potential ability of the procedure to detect minor deviations in the specification of process streams from continuous analysis.