The effect of concentration and polydispersity on the collective diffusion coefficient Dc, evaluated using Photon Correlation Spectroscopy (PCS), has been investigated on poly(methyl methacrylate) (PMMA) in acetone solutions. The concentration dependence of the collective diffusion coefficient follows a linear regression law, the slope being fairly independent of polydispersity, molecular weight and temperature. The diffusion coefficient at infinite dilution D0 obeys the scaling law D0 = AMw–ν in the range from Mw = 10 000 to Mw = 800 000; the value of the scaling exponent, ν = 0.57, proves the good solvent quality of acetone. The inversion of the scattered intensity autocorrelation data by the regularization method CONTIN allowed the evaluation of the molecular weight distribution function of the polymeric samples. Although this algorithm gives valuable information on average quantities or on the width of the distribution, it has limited resolution power; therefore a comparison with the results obtained by Size Exclusion Chromatography (SEC) was carried out for a set of samples having monomodal and bimodal distribution functions.
Possibilities and limits of photon correlation spectroscopy in determining polymer molecular weight distributions
MASCHIO, GIUSEPPE
1999
Abstract
The effect of concentration and polydispersity on the collective diffusion coefficient Dc, evaluated using Photon Correlation Spectroscopy (PCS), has been investigated on poly(methyl methacrylate) (PMMA) in acetone solutions. The concentration dependence of the collective diffusion coefficient follows a linear regression law, the slope being fairly independent of polydispersity, molecular weight and temperature. The diffusion coefficient at infinite dilution D0 obeys the scaling law D0 = AMw–ν in the range from Mw = 10 000 to Mw = 800 000; the value of the scaling exponent, ν = 0.57, proves the good solvent quality of acetone. The inversion of the scattered intensity autocorrelation data by the regularization method CONTIN allowed the evaluation of the molecular weight distribution function of the polymeric samples. Although this algorithm gives valuable information on average quantities or on the width of the distribution, it has limited resolution power; therefore a comparison with the results obtained by Size Exclusion Chromatography (SEC) was carried out for a set of samples having monomodal and bimodal distribution functions.Pubblicazioni consigliate
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