Feasibility of monitoring acetic acid process using near-infrared spectroscopy

Near-infrared (NIR) spectroscopy has been utilized to demonstrate its feasibility for the measurement of major components in the acetic acid process. In order to simulate the acetic acid process, synthetic mixtures were prepared from five different components: acetic acid, methyl acetate, methyl iodide, water, and potassium iodide. Partial least squares (PLS) regression was utilized to differentiate the spectral characteristics as well as to quantify each component for the mixtures. The spectral features of acetic acid, methyl acetate, methyl iodide, and water are noticeably different with each other over the entire NIR region. The quantity of iodide ion, which does not absorb NIR radiation, was determined using the wavelength shift and intensity change of water absorption band caused by the change of iodide ion concentration. The PLS calibration results of the five components show good correlation with reference data. They also demonstrate the technical feasibility of NIR spectroscopy for monitoring important components in the acetic acid process.     

Quantitative monitoring of an activated sludge reactor using on-line UV-visible and near-infrared spectroscopy

The performance of an activated sludge reactor can be significantly enhanced through use of continuous and real-time process-state monitoring, which avoids the need to sample for off-line analysis and to use chemicals. Despite the complexity associated with wastewater treatment systems, spectroscopic methods coupled with chemometric tools have been shown to be powerful tools for bioprocess monitoring and control. Once implemented and optimized, these methods are fast, nondestructive, user friendly, and most importantly, they can be implemented in situ, permitting rapid inference of the process state at any moment. In this work, UV-visible and NIR spectroscopy were used to monitor an activated sludge reactor using in situ immersion probes connected to the respective analyzers by optical fibers. During the monitoring period, disturbances to the biological system were induced to test the ability of each spectroscopic method to detect the changes in the system. Calibration models based on partial least squares (PLS) regression were developed for three key process parameters, namely chemical oxygen demand (COD), nitrate concentration (N-NO₃⁻), and total suspended solids (TSS). For NIR, the best results were achieved for TSS, with a relative error of 14.1% and a correlation coefficient of 0.91. The UV-visible technique gave similar results for the three parameters: an error of ~25% and correlation coefficients of ~0.82 for COD and TSS and 0.87 for N-NO₃⁻. The results obtained demonstrate that both techniques are suitable for consideration as alternative methods for monitoring and controlling wastewater treatment processes, presenting clear advantages when compared with the reference methods for wastewater treatment process qualification.     

Batch process monitoring and its application to polymerization systems

Slight changes in raw material properties or operating conditions during critical periods of operation of batch and semi-batch polymerization reactors may have a strong influence on reaction mechanism and impact final product quality. Online process monitoring, fault detection, fault diagnosis, and product quality prediction in real-time ensure safe reactor operation and warn operators about excursions from normal operation that may lead to deterioration in product properties. Multivariate statistical process monitoring and quality prediction using multiway principal components analysis and multiway partial least squares have been successful in detecting abnormalities in process operation and product quality. When abnormal process operation is detected, fault diagnosis tools are used to determine the source cause of the deviation. Illustrative case studies are presented via simulated polyvinyl acetate polymerization.     

Quantitative on-line high-resolution NMR spectroscopy in process engineering applications

In many technical processes, complex multicomponent mixtures have to be handled, for example, in reaction or separation equipment. High-resolution NMR spectroscopy is an excellent tool to study these mixtures and gain insight in their behavior in the processes. For on-line studies under process conditions, flow NMR probes can be used in a wide range of temperature and pressure. A major challenge in engineering applications of NMR spectroscopy is the need for quantitative evaluation. Flow rates, recovery times, and other parameters of the on-line NMR experiments have to be optimized for this purpose. Since it is generally prohibitive to use deuterated solvents in engineering applications, suitable techniques for field homogenization and solvent signal suppression are needed. Two examples for the application of on-line NMR spectroscopic experiments in process engineering are presented, studies on chemical equilibria and reaction kinetics of the technically important system formaldehyde-water-methanol and investigations on reactive gas absorption of CO(2) in aqueous solutions of monoethanolamine.     

Atomic emission spectroscopy for the on-line monitoring of incineration processes

A diagnostic measurement system based on atomic emission spectroscopy has been developed for the purpose of on-line monitoring of hazardous elements in industrial combustion gases. The aim was to construct a setup with a high durability for rough and variable experimental conditions, e.g. a strongly fluctuating gas composition, a high gas temperature and the presence of fly ash and corrosive effluents. Since the setup is primarily intended for the analysis of combustion gases with extremely high concentrations of pollutants, not much effort has been made to achieve low detection limits. It was found that an inductively coupled argon plasma was too sensitive to molecular gas introduction. Therefore, a microwave induced plasma torch, compromising both the demands of a high durability and an effective evaporation and excitation of the analyte was used as excitation source. The analysis system has been installed at an industrial hazardous waste incinerator and successfully tested on combustion gases present above the incineration process. Abundant elements as zinc, lead and sodium could be easily monitored.     

Development of a rapid process monitoring method for dry-coated tableting process by using near-infrared spectroscopy

A nondestructive transmittance near-infrared (NIR) method for detecting off-centered cores in dry-coated (DC) tablets was developed as a monitoring system in the DC tableting process. Caffeine anhydrate was used as a core active pharmaceutical ingredient (API), and DC tablets were made by the direct compression method. NIR spectra were obtained from these intact DC tablets using the transmittance method. The reference assay was performed with HPLC. Calibration models were generated by partial least squares (PLS) regression and principal component regression (PCR) utilizing external validations. Hierarchical cluster analysis (HCA) of the results confirmed that NIR spectroscopy correctly detected off-centered cores in DC tablets. We formulated and used the Centering Index (CI) to evaluate the precision of core alignment and generated an NIR calibration model that could correctly predict this index. The principal component (PC) 1 loading vector of the final calibration model indicated that it could specifically detect the misalignment of tablet cores. The model also had good linearity and accuracy. The CIs of unknown sample tablets predicted by the final calibration model and those calculated through the HPLC analysis were closely parallel with each other. These results demonstrate the validity of the final calibration model and the utility of the transmittance NIR spectroscopic method developed in this study as a monitoring system in DC tableting process.     

Use of FT-NIR spectroscopy for on-line monitoring of formaldehyde-based resin synthesis

A new method is being developed for the fast and reliable assessment of the pathway(s) followed during formaldehyde-based resin synthesis, both at laboratory and industrial scale. The method is based on Fourier transform Near Infrared (FT-NIR) chemometrics. No sample manipulation is necessary and the complete evaluation can be performed on- or off-line in less than 1 min. FT-NIR chemometrics were found to be valuable in providing a fast and consistent way of monitoring directly the effects of a change of resin formulation when evaluating new procedures at laboratory scale. Similarly, during industrial production, NIR will soon become a standard tool for ensuring reproducibility and improving overall quality. Measurements are performed on-line and deviations from the standard synthesis pathway can be detected early, allowing the necessary steps to be taken in order to return to the desired pathway. Furthermore, NIR methodologies have been developed to identify and check the conformity of raw materials and final products from urea and UFC solutions to laminated paper produced by impregnation with formaldehyde-based resins. This can prove particularly useful in applications (such as in laminated paper production) where the reproducibility of production and the effects of storage are both questionable and difficult to assess.     

Comparing near infrared and Raman spectroscopy for on-line monitoring of emulsion copolymerization reactions

In this work, Raman and Near InfraRed (NIR) spectroscopies are evaluated for the monitoring of different semicontinuous emulsion homo- and co-polymerization reactions. Important process variables, namely monomer concentrations and average particle sizes, were monitored by both techniques under realistic conditions that would be found in an industrial environment (e.g. low signal/noise ratio, probe placed in the reaction medium). Results suggest that Raman and NIR are suitable for on-line monitoring of emulsion polymerization reactions and that the success of their application is mainly related to representative calibration models used for the estimation of the properties of interest.     

Biomass estimation using on-line glucose monitoring by flow injection analysis

Applied Biochemistry and Biotechnology - A new Flow Injection Analysis (FIA) system was developed that permits the on-line monitoring of glucose. This information may be used to identify the...     

Real-time monitoring of polyurethane production using near-infrared spectroscopy

A process near-infrared (NIR) spectrophotometer was interfaced directly to a reactor by using a fiber optic bundle interactance immersion probe. This remote sensor configuration enables the production of polyurethanes to be monitored in real-time. A Beer's Law model was derived for the quantitative determination of isocyanate in the urethane polymerization reaction. Statistical process control was used to observe trends in the polymerization reaction. The integration of NIR process analytical instrumentation directly into the process provides real-time chemical information that yields improvements in product quality and consistency, while minimizing reaction time.     

Quantitative monitoring of yeast fermentation using Raman spectroscopy

Compared to traditional IR methods, Raman spectroscopy has the advantage of only minimal interference from water when measuring aqueous samples, which makes this method potentially useful for in situ monitoring of important industrial bioprocesses. This study demonstrates real-time monitoring of a Saccharomyces cerevisiae fermentation process using a Raman spectroscopy instrument equipped with a robust sapphire ball probe. A method was developed to correct the Raman signal for the attenuation caused by light scattering cell particulate, hence enabling quantification of reaction components and possibly measurement of yeast cell concentrations. Extinction of Raman intensities to more than 50 % during fermentation was normalized with approximated extinction expressions using Raman signal of water around 1,627 cm^?1 as internal standard to correct for the effect of scattering. Complicated standard multi-variant chemometric techniques, such as PLS, were avoided in the quantification model, as an attempt to keep the monitoring method as simple as possible and still get satisfactory estimations. Instead, estimations were made with a two-step approach, where initial scattering correction of attenuated signals was followed by linear regression. In situ quantification measurements of the fermentation resulted in root mean square errors of prediction (RMSEP) of 2.357, 1.611, and 0.633 g/L for glucose, ethanol, and yeast concentrations, respectively.     

Near-infrared diode laser spectroscopy in chemical process and environmental air monitoring

This review covers the rapidly expanding field of near-infrared tunable diode laser spectroscopy where the availability of new lasers has led to the development of simple and inexpensive spectroscopic systems for the detection and monitoring of gas species. The latest diode lasers and the specific techniques associated with diode laser spectroscopy are described. Specific examples covering chemical vapour deposition reaction diagnostics, remote vehicle emission sensing, balloon-borne atmospheric monitoring and combustion diagnostics then illustrate the technique advantages of rapid, highly selective, in situ monitoring.     

近红外光谱法用于纯化过程中鞣花酸含量的监控

采用近红外光谱技术结合遗传算法优化的小波神经网络,对大孔树脂纯化过程中橄榄果中的鞣花酸含量进行监控。通过小波变换对光谱进行去噪、压缩,作为人工神经网络的输入,同时以遗传算法优化神经网络的权值与阈值,并与常用的偏最小二乘(PLS)线性模型的建模效果进行比较。实验结果表明,两者都能够较准确的预测鞣花酸的含量,相对而言,人工神经网络(ANN)效果较好。     

Simplified Fourier-transform mid-infrared spectroscopy calibration based on a spectra library for the on-line monitoring of bioprocesses

In order to significantly reduce the time involved in mid-infrared spectroscopy calibrations, a novel approach based on a library of pure component spectra was developed and tested with an aerobic Saccharomyces cerevisiae fermentation. Instead of the 30-50 standards that would have been required to build a chemometric model, only five solutions were used to assemble the library, namely one for each compound (glucose, ethanol, glycerol, ammonium and acetate). Concentration profiles of glucose, ethanol and ammonium were monitored with a fair accuracy, leading to standard error of prediction (SEP) values of 0.86, 0.98 and 0.15 g L⁻¹. Prediction of the two minor metabolites, acetate and glycerol, was less accurate and presented a detection limit of around 0.5 g L⁻¹. The overall performance of the library-based method proved to be very similar to a 49-standard chemometrics model. The model was shown to be very robust and uncorrelated, since it was able to predict accurately the concentration changes during a spiking experiment. Even though simple, this method allows more advanced calculations, such as determination of the explained variance and detection of unexpected compounds using residuals analysis.     

In vivo monitoring of amine neurotransmitters using microdialysis with on-line capillary electrophoresis.

Microdialysis sampling was coupled via a flow-gated interface on-line to capillary electrophoresis with laser-induced fluorescence (LIF) detection for in vivo monitoring of neuroactive amino acids and amines. In the instrument, analytes are derivatized precolumn with o-phthaldehyde and beta-mercaptoethanol to form fluorescent isoindole products. The instrument was improved over previous designs by incorporating a sheath-flow cuvette for reduced background in LIF detection which improved sensitivity by 15-fold. The methodology was improved by utilizing a voltage ramped injection which allowed generation of 500000 theoretical plates with 20 s separations. Resolution of the isoindole derivatives was further improved by addition of hydroxypropyl-modified beta-cyclodextrin to the electrophoresis buffer. The new instrumentation and methods allow resolution and detection of glutamate, gamma-aminobutyric acid, glycine, aspartate, serine, taurine, glutamine and dopamine (if levels are elevated) collected from in vivo sampling probes every 20 s. The technique is suited to continuous monitoring for dynamic measurements of these compounds in vivo.     

Comparison of near-infrared and Raman spectroscopy for on-line monitoring of etchant solutions directly through a Teflon tube

Both near-infrared (NIR) and Raman spectroscopy have been studied for the quantitative measurement of components (H(3)PO(4), HNO(3), and CH(3)COOH) in an etchant solution and the corresponding prediction robustness has been evaluated. Both measurements were accomplished by illuminating radiation directly through a Teflon tube. Raman spectral features of each component were much clearer and more selective than those observed in the NIR spectrum. Especially, NIR spectral variation pertinent to H(3)PO(4) and HNO(3) were mostly based on the displacement and perturbation of water bands rather than due solely to NIR absorption. Therefore, the resulting spectral variations were not highly specific. When the validation set contained minor spectral variations resulting from a slight instrumental change, NIR prediction performance for all three components degraded substantially by showing obvious prediction bias. However, the accuracies of Raman predictions were maintained. Since partial least squares (PLS) models for each component were built using NIR spectra of poor specificity with broadly overlapping features, even minor spectral differences introduced by instrumental variations sensitively influenced the prediction performance of the NIR models. Overall, the selectivity (specificity) of a targeting spectroscopic method should be considered critically to secure prediction robustness for monitoring components in an etchant solution.     

Real-time monitoring of DNAzyme cleavage process using fluorescent assay

Detection of deoxyribozyme(DNAzyme) cleavage process usually needs complex and time-consuming radial labeling,gel electrophoresis and autoradiography.This paper reported an approach to detect DNAzyme cleavage process in real time using a fluorescence probe.The probe was employed as DNAzyme substrate to convert directly the cleavage information into fluorescence signal in real time.Compared with traditional approach,this non-isotope method not only brought a convenient means to monitor the DNAzyme cleavag...     

Continuous on-line monitoring of intracellular enzyme activity

For optimal cultivation of recombinant E. coli cells, it is necessary to monitor the intracellular enzyme activity by a fast, reliable and simple method. A modified air-segmented flow system is described for the on-line determination of intracellular penicillin-G-acylase (E.C. 3.5.1.11) during the cultivation of genetically modified E. coli 5K(pHM12). The results are compared to those obtained by different conventional off-line techniques.     

Performance monitoring of a mammalian cell based bioprocess using Raman spectroscopy

Being able to predict the final product yield at all stages in long-running, industrial, mammalian cell culture processes is vital for both operational efficiency, process consistency, and the implementation of quality by design (QbD) practices. Here we used Raman spectroscopy to monitor (in terms of glycoprotein yield prediction) a fed-batch fermentation from start to finish. Raman data were collected from 12 different time points in a Chinese hamster ovary (CHO) based manufacturing process and across 37 separate production runs. The samples comprised of clarified bioprocess broths extracted from the CHO cell based process with varying amounts of fresh and spent cell culture media. Competitive adaptive reweighted sampling (CoAdReS) and ant colony optimization (ACO) variable selection methods were used to enhance the predictive ability of the chemometric models by removing unnecessary spectral information. Using CoAdReS accurate prediction models (relative error of predictions between 2.1% and 3.3%) were built for the final glycoprotein yield at every stage of the bioprocess from small scale up to the final 5000 L bioreactor. This result reinforces our previous studies which indicate that media quality is one of the most significant factors determining the efficiency of industrial CHO-cell processes. This Raman based approach could thus be used to manage production in terms of selecting which small scale batches are progressed to large-scale manufacture, thus improving process efficiency significantly.     

Rapid monitoring of antibiotics using Raman and surface enhanced Raman spectroscopy

Comparatively few studies have explored the ability of Raman spectroscopy for the quantitative analysis of microbial secondary metabolites in fermentation broths. In this study we investigated the ability of Raman spectroscopy to differentiate between different penicillins and to quantify the level of penicillin in fermentation broths. However, the Raman signal is rather weak, therefore the Raman signal was enhanced using surface enhanced Raman spectroscopy (SERS) employing silver colloids. It was difficult by eye to differentiate between the five different penicillin molecules studied using Raman and SERS spectra, therefore the spectra were analysed by multivariate cluster analysis. Principal components analysis (PCA) clearly showed that SERS rather than the Raman spectra produced reproducible enough spectra to allow for the recovery of each of the different penicillins into their respective five groups. To highlight this further the first five principal components were used to construct a dendrogram using agglomerative clustering, and this again clearly showed that SERS can be used to identify which penicillin molecule was being analysed, despite their molecular similarities. With respect to the quantification of penicillin G it was shown that Raman spectroscopy could be used to quantify the amount of penicillin present in solution when relatively high levels of penicillin were analysed (>50 mM). By contrast, the SERS spectra showed reduced fluorescence, and improved signal to noise ratios from considerably lower concentrations of the antibiotic. This could prove to be advantageous in industry for monitoring low levels of penicillin in the early stages of antibiotic production. In addition, SERS may have advantages for quantifying low levels of high value, low yield, secondary metabolites in microbial processes.