Abstract: A new strategy for the quantitative determination of enantiomeric purity that combines guest-host complexation, spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares (“PLS-1”) regression. The PLS-1 regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity. In this strategy, the concentration of the chiral compound does not have to be fixed or known.

Abstract: A method for classifying textile samples and unknown fabrics into known categories using spectroscopy, chemometric modeling, and soft independent modeling of class analogies (“SIMCA”). The method involves collecting spectral data, preferably diffuse near infrared reflectance data, for a library of known fabric samples, creating a database of principal component analyses for each type of fabric, and using SIMCA to classify an unknown fabric sample according to the database.

Abstract: A method for determining sugar concentration using spectropolarimetry and multivariate regression modeling A set of fixed polarizers are used in association with a spectrometer, which enables the measurement of optical rotation as absorbance values over a range of wavelengths. The adverse effects of color within the samples is corrected by measuring a background level of absorbance that is not due to optical rotation and using this as a baseline. A regression model is then developed for predicting sugar concentration in unknown samples. This method is effective even if the sample is colored.

Abstract: A strategy, or method, for the quantitative determination of enantiomeric purity that combines lin situ enantiomer diastereomerization', spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares (“PLS-I”) regression. The PLS-I regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity. In this strategy, the guest-host complexation utilizes improved chiral selector molecules, including chiral amines and chiral alcohols such as phenylethylamine and 1,2-propanediol, that form ion pairs or covalent bonds with the chiral analytes.

Abstract: A new strategy for the quantitative determination of enantiomeric purity that combines guest-host complexation, spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares (“PLS-1”) regression. The PLS-1 regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity. In this strategy, the concentration of the chiral compound does not have to be fixed or known.

Abstract: A method for classifying textile samples and unknown fabrics into known categories using spectroscopy, chemometric modeling, and soft independent modeling of class analogies (“SIMCA”). The method involves collecting spectral data, preferably diffuse near infrared reflectance data, for a library of known fabric samples, creating a database of principal component analyses for each type of fabric, and using SIMCA to classify an unknown fabric sample according to the database.

Abstract: A method for determining sugar concentration using spectropolarimetry and multivariate regression modeling A set of fixed polarizers are used in association with a spectrometer, which enables the measurement of optical rotation as absorbance values over a range of wavelengths. The adverse effects of color within the samples is corrected by measuring a background level of absorbance that is not due to optical rotation and using this as a baseline. A regression model is then developed for predicting sugar concentration in unknown samples. This method is effective even if the sample is colored.

Abstract: A new strategy for the quantitative determination of enantiomeric purity that combines guest-host complexation, spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares (“PLS-1”) regression. The PLS-1 regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity.

Abstract: A new strategy for the quantitative determination of enantiomeric purity that combines guest-host complexation, spectroscopy, and chemometric modeling. Spectral data for samples of known enantiomeric composition is subjected to a type of multivariate regression modeling known as partial least squares (“PLS-1”) regression. The PLS-1 regression produces a mathematical model that can be used to predict the enantiomeric composition of a set of samples of unknown enantiomeric purity.

Abstract: A method and apparatus for quantitatively determining chlorine content and fractional abundance of chlorine isotopes in unknown samples. When using this method and apparatus to determine chlorine content, isotope dilution principles may be employed. Chlorine isotopes used for diluting an unknown sample may be .sup.35 Cl or .sup.37 Cl, and relative isotope content in the diluted mixture may be measured using infrared spectrometry.

Abstract: Apparatus and method for qualitatively and quantitatively analyzing infrared emission from excited molecules in the determination of, for example, total inorganic carbon, chloride and available chlorine in aqueous samples. Methods of exciting the gas-phase, infrared-active molecules to emit radiation include flame excitation, furnace excitation, excitation by electron impact in a gas discharge or excitation by collisions with a vibrationally excited diatomic molecule. The detector is optimized by use of dual beam system with background subtraction capabilities thereby eliminating background noise and fluctuations therein.

Abstract: Apparatus and method for qualitatively and quantitatively analyzing infrared emission from excited molecules in samples of interest is disclosed. Over the wavelength interval from 1 to 5 um, two strong emission bands are observed with a PbSe detector when organic compounds are introduced into an hydrogen/air flame. The band at 4.3 um (2326 cm.sup.-1 is due to the asymmetric stretch of carbon dioxide while the band at 2.7 um is due to both water and carbon dioxide emission. The carbon dioxide emission at 4.3 um is most intense at the tip of the flame, and increases with the amount of organic compound introduced into the flame. For chromatographic application, an optical filter can be used to isolate the 4.3 um emission band. The infrared emission detection system finds application in the determination of total inorganic carbon, chloride and available chlorine in aqueous samples.