Jeffrey F. Aust

Multivariate optical computation for predictive spectroscopy.

A novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated using a data set from earlier work. In our approach, a regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal that is directly proportional to the chemical/physical property for which the regression vector was designed. This simple optical computational method for predictive spectroscopy is evaluated in several ways, using the example data for numeric simulation. First, we evaluate the sensitivity of the method to various types of spectroscopic errors commonly encountered and find the method to have the same susceptibilities toward error as standard methods. Second, we use propagation of errors to determine the effects of detector noise on the predictive power of the method, finding the optical computation approach to have a large multiplex advantage over conventional methods. Third, we use two different design approaches to the construction of the paired filter set for the example measurement to evaluate manufacturability, finding that adequate methods exist to design appropriate optical devices. Fourth, we numerically simulate the predictive errors introduced by design errors in the paired filters, finding that predictive errors are not increased over conventional methods. Fifth, we consider how the performance of the method is affected by light intensities that are not linearly related to chemical composition (as in transmission spectroscopy) and find that the method is only marginally affected. In summary, we conclude that many types of predictive measurements based on use of regression (or other) vectors and linear mathematics can be performed more rapidly, more effectly, and at considerably lower cost by the proposed optical computation method than by traditional dispersive or interferometric instrumentation. Although our simulations have used Raman experimental data, the method is equally applicable to Near-IR, UV-vis, IR, fluorescence, and other spectroscopies.

Novel In situ Probe for Monitoring Polymer Curing

A novel probe design for in situ fiber-optic Raman spectroscopy has been tested and employed for real-time monitoring of an epoxy curing. The epoxy system consists of diglycidylether of bisphenol-A and polyoxypropylenetriamine. The probe consists of a single fiber optic and a small section of Teflon® tubing. The tube acts as a waveguide and sample holder. Raman signal enhancements of 15 x were observed with the employment of the tube compared to those of spectra acquired with the single fiber alone. This analysis studied the C-H stretching region of the epoxide, where previously studies have centered around the fingerprint region. The small volume of the probe and large surface area allow it to be used effectively as a method of polymer thin-film measurement. It is also effective in bulk polymer measurements because of a negligible amount of heat trapped in the sample during curing. This gives the probe a temperature and reaction rate characteristic of the polymer surrounding it. Multivariate analysis was employed to interpret and analyze the numerous spectra taken during analyses. Multivariate techniques show that both curing and sample internal temperature information can be derived from the Raman spectra.

Precise Determination of Percent Cure of Epoxide Polymers and Composites via Fiber-Optic Raman Spectroscopy and Multivariate Analysis

A method for real-time determination of the percent cure of epoxies via in situ fiber-optic Raman spectroscopy has been developed. This method utilizes a probe design developed for real-time monitoring of polymer curing and multivariate analysis to interpret the data and determine percent cure. This method was demonstrated to be reliable to ±0.54% of cure in laboratory samples over a 50–99% cure range. A preliminary study measuring cure percentage in an industrial, glass-reinforced composite has been shown to be reliable to ±0.82% in the 40–90% cure range.

IN SITU SPECTROSCOPIC STUDY OF MICROWAVE POLYMERIZATION

Microwaves provide a commercially advantageous method of rapidly curing polymeric samples. Curing times of several hours with traditional ovens are easily reduced to several minutes by microwave curing. Many commonly used sample monitoring probes (e.g., thermocouples) contain metallic elements that are incompatible with microwave processing. Such accelerated polymer processing via rapid microwave heating would benefit from rapid in situ monitoring techniques using optical spectroscopy.

Multivariate optical computation for predictive spectroscopy

A novel optical approach to predicting chemical and physical properties based on principal component analysis (PCA) is proposed and evaluated using a data set from earlier work. In our approach, a regression vector produced by PCA is designed into the structure of a set of paired optical filters. Light passing through the paired filters produces an analog detector signal directly proportional to the chemical/physical property for which the regression vector was designed. This simple optical computational method for predictive spectroscopy is evaluated in several ways, using the example data for numeric simulation. First, we evaluate the sensitivity of the method to various types of spectroscopy errors commonly encountered, and find the method to have the same susceptibilities toward error as standard methods. Second, we use propagation of errors to determine the effects of detector noise on the predictive power of the method, finding the optical computation approach to have a large multiplex advantage over conventional methods. Third, we use two different design approaches to the construction of the paired filter set for the example measurement to evaluate manufacturability, finding that adequate methods exist to design appropriate optical devices. Fourth, we numerically simulate the predictive errors introduced by design errors in the paired filters, finding that predictive errors are not increased over conventional methods. Fifth, we consider how the performance of the method is affected by light intensities that are not linearly related to chemical composition, and find that the method is only marginally affected. In summary, we conclude that many types of predictive measurements based upon use of regression vectors and linear mathematics can be performed more rapidly, more effectively, and at considerably lower cost by the proposed optical computation method than by traditional dispersive or interferometric instrumentation. Although our simulations have used Raman experimental data, the method is equally applicable to NIR, UV-Vis, IR, fluorescence and other spectroscopies.

Fourier transform Raman spectroscopic studies of a polyimide curing reaction

Abstract Fourier transform (FT)-Raman spectroscopy was used to monitor the curing reaction of a polyimide bonding agent, the Ciba-Geigy Matrimid® system. Major Raman bands were assigned by comparison to spectra for small model molecules, by use of ab initio calculations, and by reference to previous literature. The set of FT-Raman spectra taken at various intervals during the curing process was modeled by principal component analysis (PCA). Cure percentage determined by differential scanning calorimetry was then regressed against scores on the first principal component for the different polymer samples. The PCA and regression results summarized significant trends in the FT-Raman spectra and led to a better understanding of the curing mechanism.

Pyrolysis gas chromatography/mass spectrometry investigation of a thermally cured polymer

Abstract The curing of the Matrimid 5292® polyimide system was studied by pyrolysis-gas chromatography/mass spectrometry. Pyrolysis products characteristic of both initial components and the cured polymer were identified. Changes in the pattern of pyrolysis products could be related to the progress of polymerization. Amounts of methylphenol isomers ( m/z 108), 4-succinimido-4′-aminodiphenylmethane ( m/z 265), and 2-(2-propenyl)-4-methylphenol were found to increase as degree of cure increases. Amounts of O , O ′-diallyl bisphenol A ( m/z 293) produced by pyrolysis decreased with increasing cure. Principal component and canonical variate analysis were used to visualize systematic trends in selected ion intensities from the pyrolysis data. Loading weights derived from orthogonal canonical variate analysis were also found to be useful in identifying pyrolysis products related to percentage cure. These results support the use of Py-GC/MS for monitoring the degree of cure of polymer systems.

IN SITU ANALYSIS OF A HIGH TEMPERATURE CURE REACTION IN REAL TIME USING MODULATED FIBER-OPTIC FT-RAMAN SPECTROSCOPY

The vibrational spectrum of a high-temperature (330 °C) polymerization reaction was successfully monitored in real time with the use of a modulated fiber-optic Fourier transform (FT)-Raman spectrometer. A phenylethynyl-terminated monomer was cured, and spectral evidence for two different reaction products was acquired. The products are a conjugated polyene chain and a cyclized trimer. This is the first report describing the use of FT-Raman spectroscopy to monitor a high temperature (>250 °C) reaction in real time.

Raman spectroscopy with a low-cost imaging CCD array

Abstract An inexpensive CCD camera, normally used in amateur astronomy, was evaluated as a spectroscopic detector for Raman scattering. Mechanical modifications of the Santa Barbara Instruments Group ST-6 camera and software were developed specifically for the application and are described. The performance of the system is evaluated at various temperatures and integration times, and sample data are presented. Results indicate that this inexpensive detector can produce relatively high-quality Raman spectra under most conditions.

Kinetic and spectroscopic profiles of three pyridine complexes at a silver electrode using surface-enhanced Raman scattering and evolving factor analysis

Abstract This work uses surface-enhanced Raman scattering (SERS) spectroscopy to examine the speciation of pyridine at a rough silver electrode surface during oxidation–reduction cycles. Evolving factor analysis (EFA), a form of self-modeling curve resolution, is used to analyze sequences of SER spectra. The EFA results are interpreted as the resolved spectra and potential-dependent profiles of discrete surface species, and results in information about the potential dependence of species. The profiles of at least two and possibly three species have been resolved. Two previously known species, an N-bound pyridine adduct of Ag + and a π-bound adduct of Ag 0 , have had their spectra deconvoluted and their potential dependence reassessed. Evidence for a third species at positive potentials is presented, its spectrum is deconvoluted, and it is tentatively assigned as an N-bound pyridine complex with Ag 0 .