Noninvasive method for monitoring ethanol in fermentation processes using fiber-optic near-infrared spectroscopy

Short-wavelength near-infrared (SW-near-IR) spectroscopy (700-1100 nm) is used for the determination of ethanol during the time course of a fermentation. Measurements are performed noninvasively by means of a photodiode array spectrometer equipped with a fiber-optic probe placed on the outside of the glass-wall fermentation vessel. Pure ethanol/water and ethanol/yeast/water mixtures are studied to establish the spectral features that characterize ethanol and to show that determination of ethanol is independent of the yeast concentration. Analysis of the second-derivative data is accomplished with multilinear regression (MLR). The standard error of prediction (SEP) of ethanol in ethanol/water solutions is approximately 0.2% over a range of 0-15%; the SEP of ethanol in ethanol/yeast/water solutions is 0.27% (w/w). Results from the mixture experiments are then applied to actual yeast fermentations of glucose to ethanol. By use of a gas chromatographic method for validation, a good correlation is found between the intensity of backscattered light at 905 nm and the actual ethanol. Additional experiments show that a calibration model created for one fermentation can be used to predict ethanol production during the time course of others with a prediction error of 0.4%.     

On-line monitoring of airborne chemistry in levitated nanodroplets: in situ synthesis and application of SERS-active Ag-Sols for trace analysis by FT-Raman spectroscopy

We report a new strategy for on-line monitoring of chemical reactions in ultrasonically levitated, nanoliter-sized droplets by Raman spectroscopy. A flow-through microdispenser connected to an automated flow injection system was used to dose picoliter droplets into the node of an ultrasonic trap. Taking advantage of the flow-through characteristics of the microdispenser and the versatility of the automated flow system, a well-defined sequence of reagents could be injected via the microdispenser into the levitated droplet placed in the focus of the collection optics of the Fourier transform Raman spectrometer. In that way, chemical reactions could be carried out and monitored on-line. The developed system was used for fast, reproducible, in situ synthesis of a highly active surface enhanced Raman scattering (SERS) sol resulting from the reduction of silver nitrate with hydroxylamine hydrochloride in basic conditions. With this chemical system, SERS substrate preparation could be achieved at room temperature and in short time. The in situ prepared silver sol was used for trace analysis of several organic test molecules that were injected into the levitated SERS-active droplet again using the microdispenser. The concentration dependence of the SERS spectra was studied using 9-aminoacridine, revealing that down to the femtogram region high-quality SERS spectra could be obtained. Additionally, SERS spectra of 6-mercaptopurine, thiamine, and acridine were recorded in the levitated drop as well.     

In situ monitoring of adipogenesis with human-adipose-derived stem cells using surface-enhanced Raman spectroscopy

Methods capable of nondestructively collecting high-quality, real-time chemical information from living human stem cells are of increasing importance given the escalating relevance of stem cells in therapeutic and regenerative medicines. Raman spectroscopy is one such technique that can nondestructively collect real-time chemical information. Living cells uptake gold nanoparticles and transport these particles through an endosomal pathway. Once inside the endosome, nanoparticles aggregate into clusters that give rise to large spectroscopic enhancements that can be used to elucidate local chemical environments through the use of surface-enhanced Raman spectroscopy. This report uses 40-nm colloidal gold nanoparticles to create volumes of surface-enhanced Raman scattering (SERS) within living human-adipose-derived adult stem cells enabling molecular information to be monitored. We exploit this method to spectroscopically observe chemical changes that occur during the adipogenic differentiation of human-adipose-derived stem cells over a period of 22 days. It is shown that intracellular SERS is able to detect the production of lipids as little as one day after the onset of adipogenesis and that a complex interplay between lipids, proteins, and chemical messengers can be observed shortly thereafter. After 22 days of differentiation, the cells show visible and spectroscopic indications of completed adipogenesis yet still share spectral features common to the progenitor stem cells.     

Near-infrared spectroscopy: a tool for monitoring submerged fermentation processes using an immersion optical-fiber probe

Near-infrared (NIR) spectroscopy has been developed as a noninvasive tool for the direct, real-time monitoring of glucose, lactic acid, acetic acid, and biomass in liquid cultures of microrganisms of the genera Lactobacillus and Staphylococcus. This was achieved employing a steam-sterilizable optical-fiber probe immersed in the culture (In-line Interactance System). Second-derivative spectra obtained were subjected to partial least-squares (PLS) regression and the results were used to build predictive models for each analyte of interest. Multivariate regression was carried out on two different sets of spectra, namely whole broth minus the spectral subtraction of water, and raw spectra. A comparison of the two models showed that the first cannot be properly applied to real-time monitoring, so this work suggests calibration based on non-difference spectra, demonstrating it to be sufficiently reliable to allow the selective determination of the analytes with satisfactory levels of prediction (standard error of prediction (SEP) < 10%). Direct interfacing of the NIR system to the bioreactor control system allowed the implementation of completely automated monitoring of different cultivation strategies (continuous, repeated batch). The validity of the in-line analyses carried out was found to depend crucially on maintaining constant hydrodynamic conditions of the stirred cultures because both gas flow and stirring speed variations were found to markedly influence the spectral signal.     

Near-infrared spectroscopy for on-line monitoring of lube base oil processes

Near-infrared (NIR) spectroscopy has been utilized for monitoring the pour point of the lube base oil (LBO) process. Using partial least-squares (PLS) regression, necessary spectral features were successfully extracted and correlated to the reference pour-point data. In a preliminary laboratory feasibility study, it was found that PLS calibration performance was largely governed by the accuracy of the reference pour-point analysis. The same NIR spectroscopic methodology was moved to monitor the pour point continuously in an on-line manner. At this time, the NIR spectrometer was calibrated with the existing on-line pour-point analyzer, which was more accurate. In comparison with the on-line pour-point analyzer, NIR spectroscopy provided faster and more repeatable analytical data. With the help of NIR analysis, LBO process variations during product switch can be detected earlier, and necessary process-control strategy can be applied to improve the process efficiency.     

Photoacoustic spectroscopy of condensed media with a phase transition

The gas-microphone method of recording a photoacoustic (PA) Rosencwaig—Herschow signal is extended theoretically for consideration of material evaporation of a sample. For an excitation source of constant intensity and exponential saturation of vapor concentration, relations are derived to describe the transient dynamics of the PA response. Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 70, No. 1, pp. 153–155, January–February, 1997.     

Particle size determination in aluminum hydroxide suspensions using near-infrared transmittance spectroscopy

A new method for particle size determination in polystyrene and aluminum hydroxide suspensions using near-infrared transmittance spectroscopy is described. Mono-dispersed polystyrene particle size standards were used to establish the calibration model. The particle sizes used in the study are similar to the wavelength range of 700-1300 nm, where light scattering is wavelength dependent. The wavelength dependency of near-infrared (NIR) absorbance is found to be linear with the particle size when the analysis is based on the same spectrum starting point (the same absorbance at 700 nm). Partial least squares regression (PLSR) is applied to model this linear relationship. Compared to laser diffraction (LD) the NIR method has similar accuracy and precision in the measurement of particles with a uniform size. For a sample containing multiple sizes of particles, the mean size measured by the NIR method is shown to be weighted by the particle mass. The application of the model to aluminum hydroxide suspension shows that the NIR method is suitable for the detection of particle size changes during the production process and storage. The advantages of the NIR method are that no knowledge of the refractive index and the concentration of a sample are necessary and that the method is fast and easy to operate.     

Temperature-dependence of Raman spectroscopy on the phase transition in LuBO3

Temperature-dependence of Raman spectroscopy on LuBO₃ structure was performed in order to obtain information on structural changes induced by temperature evolution. The stability of the calcite phase and low-temperature vaterite phase of LuBO₃ were both evaluated. For the sample with low-temperature vaterite phase, a strong first-order phase transition occurred during 1000–1200 °C, as indicated by the behavior of the Raman modes: the Raman bands split and new bands appear. The transition was associated with the B–O bond being broken in the cyclic B₃O₉ groups at high temperature, forming an open B₃O₉ group consisting of BO₄ and BO₃. Moreover, the influence of In³⁺ content on the structural characteristics of LuBO₃ was investigated. It was found that the calcite phase of LuBO₃ can be stabilized up to 1550 °C at least when the n(In)/n(Lu + In) ratio was more than 20 at%. The crystal growth and characterizations of Lu_1?xIn_xBO₃:Ce materials deserve further investigation.     

Comparison of sampling techniques for in-line monitoring using Raman spectroscopy

Raman spectroscopy is currently of interest as a process monitoring tool for pharmaceutical unit operations. In this study, the performance characteristics of Raman spectrometers with different sampling optics have been investigated in the context of process monitoring, with emphasis being placed on assessing homogeneity in powder blends and following changes in solid-state form during wet granulation. A novel large spot non-contact Raman sampling device was compared with a traditional small spot size non-contact sampling device and an immersion probe. The large spot non-contact optics provided significant advantages over the standard systems both as a result of the enhanced sampling volume and because of the greater robustness of the system to fluctuations in the sampling distance during the wet granulation process.     

Attenuated total reflection infrared difference spectroscopy (ATR-IRDS) for quantitative reaction monitoring

Monitoring of chemical reactors is key to optimizing yield and efficiency of chemical transformation processes. Aside from tracking pressure and temperature, the measurement of the chemical composition is essential in this context. We present an infrared difference spectroscopy approach for determining the reactant (cyclooctene) and product (cyclooctane) concentrations during a catalytic hydrogenation reaction in the solvent cyclohexane, which is present in large excess. Subtracting the spectrum of the pure solvent from the reactor mixture spectra yields infrared (IR) spectra, which can ultimately be evaluated using a curve-fitting procedure based on spectral soft modeling. An important feature of our evaluation approach is that the calibration only requires recording the pure component spectra of the reactants, products, and solvent. Hence, no time-consuming preparation of mixtures for calibration is necessary. The IR concentration results are in good agreement with gas chromatography measurements.     

Quantitative methods for structural health management using in situ acoustic emission monitoring

This paper presents an end-to-end approach for structural health management using acoustic emission (AE) monitoring. Three quantitative methods are proposed to utilize the information obtained from in situ AE monitoring to improve structural integrity assessment. Fatigue crack growth tests with real-time acoustic emissions monitoring are conducted on CT specimens made of 7075-T6 aluminum. Proper filtration of the resulting AE signals reveals a log-linear relationship between fracture parameters (e.g. crack growth rate) and select AE features; a flexible statistical model is developed to describe the relationship between these parameters. Bayesian inference is used to estimate the model parameters from experimental data. The model is then used to calculate two important quantities that can be used for structural health management: (a) an AE-based instantaneous damage severity index, and (b) an AE-based estimate of the crack size distribution at a given point in time, assuming a known initial crack size distribution. Finally, recursive Bayesian estimation is used for online integration of the structural health assessment information obtained from AE monitoring, with crack size estimates obtained from empirical crack growth model. The data used in Bayesian updating includes observed crack sizes and/or crack growth rate observations.     

Terahertz time-domain spectroscopy and the quantitative monitoring of mechanochemical cocrystal formation

Terahertz (THz) radiation probes intermolecular interactions through crystal lattice vibrations, allowing the characterization of solid materials. Thus, THz spectroscopy is a promising alternative to mainstream solid-state analytical tools such as X-ray diffraction or thermal analysis. The method provides the benefits of online measurement, remote sampling and three-dimensional imaging, all of which are attractive for quality control and security applications. In the context of pharmaceutical solids, THz spectroscopy can differentiate and quantify different forms of active pharmaceutical ingredients. Here, we apply this technique to monitor a dynamic process involving two molecular crystals. In particular, we follow the mechanochemical construction of a two-component cocrystal by grinding together phenazine (phen) and mesaconic acid (mes). To rationalize the observed changes in the spectra, we conduct lattice dynamics calculations that lead to the tentative assignment of at least one feature in the cocrystal THz spectrum.     

Determination of elemental impurities in plastic calibration standards using laser-induced breakdown spectroscopy

Dual-energy computed tomography (CT) scanning is a rapidly emerging imaging technique employed in nondestructive evaluation of various materials. CT has been used for characterizing rocks and visualizing multiphase flow through rocks for over 25 years. The most common technique for dual-energy CT scanning relies on homogeneous calibration standards to produce the most accurate decoupled data. However, the use of calibration standards with impurities increases the probability of error in the reconstructed data and results in poor rock characterization. Laser-induced breakdown spectroscopy was used to determine impurity concentration in a set of commercially purchased calibration standards used in dual-energy scanning for material identification with coal samples. Two calibration models were developed by using univariate calibration with the internal ratio method and multiple linear regression. Seven elements (Al, Fe, Mg, Na, Ni, Sr, and Ti) were examined in five different samples containing varying amounts of each ion to compare calibration from univariate data analysis and from multivariate data analysis. The contaminant concentrations were also measured by a commercially available inductively coupled plasma optical emission spectroscopy instrument, and the data were used as a reference in developing calibration curves for a modified version of the single linear regression model and the multiple linear regression model.     

Pump-probe spectroscopy in organic semiconductors: monitoring fundamental processes of relevance in optoelectronics

In this review we highlight the contribution of pump-probe spectroscopy to understand elementary processes taking place in organic based optoelectronic devices. The techniques described in this article span from conventional pump-probe spectroscopy to electromodulated pump-probe and the state-of-the-art confocal pump-probe microscopy. The article is structured according to three fundamental processes (optical gain, charge photogeneration and charge transport) and the contribution of these techniques on them. The combination of these tools opens up new perspectives for assessing the role of short-lived excited states on processes lying underneath organic device operation.     

In situ probe nanophase transition in nanocomposite using thermal AFM

Nanocomposites made from inorganic nanoparticles and polymers have many applications in optics, electronics and biomaterials. However, the glass transition temperature (T_g) of a nanocomposite is very difficult to measure accurately by conventional thermal analysis such as DSC or TMA when the concentration of the nanoparticle reaches a threshold of the percolation network. At this threshold stage, the phase transition in the nano domains of the matrix is too small to be detected by macroscale thermal analysis. We have developed a methodology basis on thermal atomic force microscope (AFM) to monitor the nanophase transition of the nanocomposite in situ upon heating. This method has demonstrated the capability in determining the T_g of a nanocomposite made by spherical SiO₂ nanoparticles dispersed in polyacrylate. The threshold of the percolation network of this nanocomposite is at 40 wt% of SiO₂ nanoparticles according to the results of refractive index, AFM, nanoindentation, DSC, TMA and TGA.     

Statistical monitoring of multivariate multiple linear regression profiles in phase I with calibration application

In some statistical process control applications, there are some correlated quality characteristics which can be modeled as linear functions of some explanatory variables. We refer to this structure as multivariate multiple linear regression profiles. When the correlation structure between quality characteristics is ignored and profiles are monitored separately then misleading results could be expected. Hence, developing methods to account for this multivariate structure is required. In this paper, we specifically focus on phase I monitoring of multivariate multiple linear regression profiles and develop four methods for this purpose. The performance of the developed methods is compared through simulation studies in terms of probability of a signal. In addition, a diagnostic scheme to find the out‐of‐control samples is developed. Finally, the application of the proposed methods is illustrated using a calibration application at the National Aeronautics and Space Administration (NASA) Langley Research Center. Copyright © 2009 John Wiley & Sons, Ltd.     

Bagging for robust non-linear multivariate calibration of spectroscopy

This paper presents the application of the bagging technique for non-linear regression models to obtain more accurate and robust calibration of spectroscopy. Bagging refers to the combination of multiple models obtained by bootstrap re-sampling with replacement into an ensemble model to reduce prediction errors. It is well suited to “non-robust” models, such as the non-linear calibration methods of artificial neural network (ANN) and Gaussian process regression (GPR), in which small changes in data or model parameters can result in significant change in model predictions. A specific variant of bagging, based on sub-sampling without replacement and named subagging, is also investigated, since it has been reported to possess similar prediction capability to bagging but requires less computation. However, this work shows that the calibration performance of subagging is sensitive to the amount of sub-sampled data, which needs to be determined by computationally intensive cross-validation. Therefore, we suggest that bagging is preferred to subagging in practice. Application study on two near infrared datasets demonstrates the effectiveness of the presented approach.