Ashland, Inc.

Other

Old Dominion University Research Foundation

Bruker Optics, Inc.

The United States of America As Represented by the Administrator of the

Micron Optical Systems

John Brittain Cooper

Kent L Wise

William T Welch

William Evans Turner

Michael B Sumner

Denis P Biglin, Jr

Mohamed F Abdelkader

Jeffrey F Aust

Brian J Jensen

Brian K Wilt

Roy R Bledsoe, Jr

Christian Lee Schoen

Philip E Flecher, Jr

Philip E Flecher

A spectrometer is provided for acquiring a Raman spectrum from a sample. The spectrometer includes a first laser, a second laser, a detector and a processing device. The first laser is adapted to produce a first laser beam for generating first Raman spectra from the sample. The second laser is adapted to produce a second laser beam for generating second Raman spectra from the sample. The detector is adapted to collect the first Raman spectra and the second Raman spectra. The processing device is adapted to process the collected first and second Raman spectra to provide the Raman spectrum.

Acquiring a Raman spectrum with multiple lasers

One embodiment of a Raman spectrometer having a temperature controlled diode laser with Bragg grating optical feedbackwhich provides a means for the acquisition of Raman spectra using sequentially shifted excitations and provides a means for spectral processing to obtain a Raman spectrum which is free from background interference such as fluorescence.

Method and apparatus for acquiring Raman spectra without background interferences

A method and apparatus for determining the concentration of a constituent in a fluid by directing a beam of light into the fluid and sensing the intensity of components of the light emerging from the fluid at various wavelengths. The light emerging from the fluid can be light that has been attenuated by absorption or induced by fluorescent radiation. The effect of scattering on the light is minimized by normalizing the component intensities, which are then applied to an algorithm incorporating weighting factors that weighs the influence that the intensity at each wavelength has on the determination of the concentration of the constituent for which the algorithm was developed. The algorithm is developed by a regression analysis based upon a plurality of known mixtures containing various concentrations of the constituent of interest.

Apparatus and method for analyzing fluids

A compact dispersive near-IR Raman spectrometer is disclosed. The Raman spectrometer consists of a diode pumped solid state (DPSS) laser emitting light at 1064 nm and an InGaAs diode array detector. The DPSS laser is used as an excitation source for stimulating Raman scattering of the sample being analyzed. The Raman signal is collected and filtered to remove the DPSS laser Rayleigh scatter. The collected and filtered Raman signal is dispersed using a volume holographic grating. The dispersed Raman signal is detected using a linear InGaAs diode array detector that is sensitive to light in the wavelength region 900-1700 nm. The dispersive near-IR Raman spectrometer is rugged and compact and enables the collection of high signal-to-noise Raman spectra with high wavelength stability and without the presence of interfering fluorescent backgrounds.

Dispersive near-IR Raman spectrometer

A modification to a commercial Fourier Transform (FT) Raman spectrometer is presented for the elimination of thermal backgrounds in the FT Raman spectra. The modification involves the use of a mechanical optical chopper to modulate the continuous wave laser, remote collection of the signal via fiber optics, and connection of a dual-phase digital-signal-processor (DSP) lock-in amplifier between the detector and the spectrometer's collection electronics to demodulate and filter the optical signals. The resulting Modulated Fourier Transform Raman Fiber-Optic Spectrometer is capable of completely eliminating thermal backgrounds at temperatures exceeding 300.degree. C.

Modulated Fourier Transform Raman fiber-optic spectroscopy

A Fourier-Transform Raman spectrometer was used to collect the Raman spectra of (208) commercial petroleum fuels. The individual motor and research octane numbers (MON and RON, respectively) were determined experimentally using the industry standard ASTM knock engine method. Partial Least Squares (PLS) regression analysis can be used to build regression models which correlate the Raman spectra (175) of the fuels with the experimentally determined values for MON, RON, and pump octane number (the average of MON and RON) of the fuels. Each of the models was validated using leave-one-out validation. The standard errors of validation (SEV) are 0.415, 0.535, and 0.410 octane numbers for MON, RON, and pump octane number, respectively. By comparing the standard error of validation to the standard deviation for the experimentally determined octane numbers, it is evident that the accuracy of the Raman determined values is limited by the accuracy of the training set used in creating the models. The Raman regression models were used to predict the octane numbers for the fuels which were not used to build the models. The results compare favorably with the leave-one-out validation. Also, it is demonstrated that the experimentally determined Reid Vapor Pressures are highly correlated with the Raman spectra of the fuel samples and can be predicted with a standard error of 0.568 psi.

Process and apparatus for octane numbers and reid vapor pressure by

A distributed Bragg reflector (DBR) diode laser is used as excitation source for fiber optic Raman spectroscopy utilizing charge coupled device (CCD) detection and an image-corrected spectrograph. The DBR diode laser is superior to index guided diode lasers (Fabry-Perot) for elimination of mode hopping, elimination of frequency hysteresis as a function of both temperature and current changes, and reduction in laser broadband emission. These advantages allow the DBR laser to be used in industrial process control applications which are too demanding for index guided diode lasers.

Distributed bragg reflector diode laser for Raman excitation and method

Benzene and substituted aromatic hydrocarbons can be predicted within .+-.0.31% vol or better, using Raman NIR spectroscopy and multivariate analysis, with optional fiberoptics multistreaming, preferably with Partial Least Squares regression analysis. The resulting signal can be used to control concentration of such compounds in product to desired levels.

Hydrocarbon analysis and control by raman spectroscopy

Oxygenated hydrocarbons can be predicted within .+-.0.2% wt or better, using Raman NIR spectroscopy and multivariate analysis, with optional fiberoptics multistreaming. The resulting signal can be used to control concentration of such compounds in product to desired levels.

Growing community of inventors

Virginia Beach, VA, United States of America

John Brittain Cooper