Kent L. Wise

Comparison of Near-IR, Raman, and Mid-IR Spectroscopies for the Determination of BTEX in Petroleum Fuels

We report for the first time a direct comparison of the three most common vibrational analysis techniques for the determination of individual BTEX components (benzene, toluene, ethylbenzene, ortho-xylene, meta-xylene, and para-xylene) in blended commercial gasolines. Partial least-squares (PLS) regression models were constructed for each BTEX component by using each of the three spectroscopic techniques. A minimum of 120 types of blended gasolines were used in the training set for each BTEX component. Leave-one-out validation of the training sets yields lower standard errors for Raman and mid-IR spectroscopies when compared to near-IR for all six BTEX components. In general, mid-IR has slightly lower standard errors than Raman. These trends are upheld when the models are tested by using independent test sets with a minimum of 40 types of blended gasolines (all of which differ in composition from the training set).

Determination of Weight Percent Oxygen in Commercial Gasoline: A Comparison between FT-Raman, FT-IR, and Dispersive Near-IR Spectroscopies

The weight percent oxygen in commercial gasoline samples has been determined by using partial least-squares (PLS) regression analysis combined with either FT-Raman, FT-IR, or dispersive near-IR spectroscopy. Calibration models were constructed with the use of 33 MTBE oxygenated commercial gasolines. The minimum standard errors of validation with the use of leave-one-out validation are 0.156, 0.188, and 0.119 wt % oxygen for FT-Raman, FT-IR, and near-IR, respectively. An independent test set of 36 MTBE oxygenated commercial gasolines was used to further validate the PLS models. The minimum standard errors of prediction for the test set are 0.155, 0.143, and 0.131 wt % oxygen for FT-Raman, FT-IR, and near-IR, respectively. The wt % oxygen in all samples ranges from 0.2 to 3.262%.

Sequentially Shifted Excitation Raman Spectroscopy: Novel Algorithm and Instrumentation for Fluorescence-Free Raman Spectroscopy in Spectral Space

A novel Raman spectrometer is presented in a handheld format. The spectrometer utilizes a temperature-controlled, distributed Bragg reflector diode laser, which allows the instrument to operate in a sequentially shifted excitation mode to eliminate fluorescence backgrounds, fixed pattern noise, and room lights, while keeping the Raman data in true spectral space. The cost-efficient design of the instrument allows rapid acquisition of shifted excitation data with a shift time penalty of less than 2 s. The Raman data are extracted from the shifted excitation spectra using a novel algorithm that is typically three orders of magnitude faster than conventional shifted-excitation algorithms operating in spectral space. The superiority of the instrument and algorithm in terms of background removal and signal-to-noise ratio is demonstrated by comparison to FT-Raman, standard deviation spectra, shifted excitation Raman difference spectroscopy (SERDS), and conventional multiple-shift excitation methods.

Spatially compressed dual-wavelength excitation Raman spectrometer

The design and operation of a novel dual-laser excitation Raman instrument is described. The use of two lasers of differing wavelengths allows for a Raman spectrum covering all fundamental modes of vibration to be collected while minimizing fluorescence and allowing for spatial compression of the spectrum on an imaging detector. The use of diode lasers with integrated distributed Bragg reflector gratings facilitates the use of an integrated thermoelectric cooler to allow collection of shifted excitation spectra for both of the lasers, further enhancing the rejection of fluorescence. An example is given, which uses seven excitation wavelengths for each laser to reconstruct the Raman spectrum of a solvent in the presence of a highly fluorescent dye by using a sequentially shifted excitation Raman reconstruction algorithm.

Modulated FT-Raman Fiber-Optic Spectroscopy: A Technique for Remotely Monitoring High-Temperature Reactions in Real-Time.

A modification to a commercial FT-Raman spectrometer is presented for the elimination of thermal backgrounds in FT-Raman spectra. The modification involves the use of a mechanical chopper to modulate the CW laser, remote collection of the signal via fiber optics, and connection of a dual-phase digital signal processor lock-in amplifier between the detector and the spectrometers collection electronics to demodulate and filter the optical signals. The resulting modulated FT-Raman fiber-optic spectrometer is capable of completely eliminating thermal backgrounds at temperatures exceeding 370 °C. In addition, the signal/noise of generated Raman spectra is greater than for spectra collected with the conventional FT-Raman under identical conditions and incident laser power. This is true for both room-temperature and hot samples. The method allows collection of data using preexisting spectrometer software. The total cost of the modification (excluding fiber optics) is ∼

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

3000 and requires less than 2 h to implement. This is the first report of FT-Raman spectra collected at temperatures in excess of 300 °C in the absence of thermal backgrounds.

Wavelet Compressed PCA Models for Real-Time Image Registration in Augmented Reality Applications

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.

Determination of Octane Numbers and Reid Vapor Pressure of Commercial Petroleum Fuels Using FT-Raman Spectroscopy and Partial Least-Squares Regression Analysis

The use of augmented reality (AR) has shown great promise in enhancing medical training and diagnostics via interactive simulations. This paper presents a novel method to perform accurate and inexpensive image registration (IR) utilizing a pre-constructed database of reference objects in conjunction with a principal component analysis (PCA) model. In addition, a wavelet compression algorithm is utilized to enhance the speed of the registration process. The proposed method is used to perform registration of a virtual 3D heart model based on tracking of an asymmetric reference object. The results indicate that the accuracy of the method is dependent upon the extent of asymmetry of the reference object which required inclusion of higher order principal components in the model. A key advantage of the presented IR technique is the absence of a restart mechanism required by the existing approaches while allowing up to six orders of magnitude compression of the modeled image space. The results demonstrate that the method is computationally inexpensive and thus suitable for real-time augmented reality implementation.