Measurements and Correlation for Diffusion Coefficients for Large Molecules in Non-organic Solvents

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Although the Taylor dispersion method has been widely employed to measure diffusion coefficients of organic compounds in various solvents such as supercritical fluids and aqueous solutions, it is not suitable for polar compounds due to severe tailing. We have developed the chromatographic impulse response (CIR) method with a polymer coated capillary column for measurements for polar solutes. The objective of this project is to measure and correlate diffusion coefficients of various large molecular and/or polar compounds under supercritical carbon dioxide.To apply the CIR method to measurements for higher molecular weight compounds, two technical improvement methods have been developed : correction of the secondary flow effect and noise elimination technique for response curves having extremely low absorbance intensity. A conversion formula to correct for the secondary flow effect was derived from the second central moment of the CIR method with a coiled capillary column at relatively h … More igh flow rates. Its practical expression was obtained analytically by the perturbation method up to λ^<10>, where λ is the ratio of the tube radius to the coil radius. The effective range of DeSc^<1/2> < 8-9.5 without correction widened to DeSc^<1/2> < 18-19 to determine the diffusion coefficient within 1% error. The curve-fitting method with the noise elimination treatment was quite effective for determining the D_<12> values accurately, and was valid at the lowest absorbance intensities, on the order of 10^<-4> absorbance unit of UV-Vis multi-detector, corresponding to the smallest quantity of the solute. Using the CIR method with the noise elimination technique and the correction of the secondary flow effect, diffusion coefficients of various compounds such as acids, esters, glycerides, and alcohols were measured in supercritical carbon dioxide. Two predictive correlations, equation of D_<12>/T with solvent viscosity, and the Schmidt number correlation, were found effective for the prediction. Less