In Situ Real-time Spectroscopic Analysis Of Complex Chemical And Bio-chemical Processes: Theory And Applications

Near infrared (NIR) spectrometry, mid infrared (MIR) spectrometry have been increasingly applied to in situ real-time monitoring of complex processes in pharmaceutical, tobacco, petroleum, environmental protection and other industries, due to their high measuring speed and requirement of less or even no sample preparations which make them highly suitable for in-line/on-line process monitoring. Compared with spectral data measured under well-controlled laboratory environment, the spectroscopic measurements collected during in situ real-time monitoring of complex processes are more complex, which contain not only the spectral variations introduced by the change in the concentration of the target analyte and also those caused by the optical differences of the optical fiber probes, the differences in samples physical properties and measurement conditions. It is therefore necessary to develop more advanced spectral calibration model capable of extracting useful chemical information from complex spectral measurements collected during in situ real-time monitoring of chemical and biochemical processes.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. When spectral measurements are subject to the changes and variations mentioned above, calibration model maintenance is needed to prevent degradation in the accuracy and reliability of multivariate calibration models.In the present thesis, an advanced calibration model for multiplexing fibre optic spectroscopy and a novel calibration model maintenance method have been developed and applied to the mid infrared spectral data of a model system of ternary mixtures, near infrared spectral data of a complex bio-process, and near infrared spectral data of pharmaceutical tablets, with a view to improve the quantitative results of in situ real-time spectroscopic analysis for complex systems. The main achievements of this thesis are as follows:1. Spectra recorded during in situ monitoring of multiple bioreactors by multiplexed fiber-optic spectroscopy contain not only spectral information of the chemical constituents but also contributions resulting from differences in the optical properties of the optical fiber probes. In this study, an advanced calibration model (Multiplex Calibration Model, MCM) was proposed for the calibration of multiplexed fiber-optic spectroscopy. In the proposed model, a multiplicative parameter was introduced to explicitly account for the spectral variations caused by the optical differences among fiber-optic probes. And then the detrimental effects of probe optical differences were effectively mitigated by the use of a "dual calibration" strategy developed by our Laboratory. The proposed MCM model has been tested on the multiplexed MIR data set of a ternary mixture system. Experimental results suggested that the proposed MCM model can effectively mitigate the detrimental effects of probe differences and hence provide much more accurate predictions than commonly used PLS method with/without pre-processed methods such as orthogonal signal correction (OSC), standard normal variate (SNV), and multiplicative scattering correction (MSC).2. The proposed multiplex calibration model was applied near infrared spectroscopic quantitative analysis of glucose concentration in a monoclonal antibody producing cell culture, and its performance has been compared with those of PLS calibration models built on spectra with or without preprocessing by OSC, SNV and MSC. Experimental results showed that the proposed MCM model could proved much more accurate predictions than other methods.3. A new calibration model maintenance 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. The performance of SST has been tested on the multiplexed MIR data set of a ternary mixture system. The experimental results revealed that SST can achieve satisfactory analyte predictions from spectroscopic measurements subject to probe alteration, when only a few standardization samples are used. Compared with the existing popular methods such as global PLS, univariate slope and bias correction (SBC) and piecewise direct standardization (PDS) designed for the same purpose, SST has the advantages of implementation simplicity, wider applicability and better performance in terms of predictive accuracy.4. The proposed SST was applied to the near infrared spectroscopic quantitative analysis of pharmaceutical tablets. The experimental results showed that SST can enable the calibration models built on the calibration spectra collected by one spectrometry to provide quite accurate predictions from the spectra measured by another spectrometry.