Concentration-dependent diffusion coefficients from a single experiment using model-based Raman spectroscopy

Abstract

Diffusion in liquids can still be predicted only with high uncertainty due to the lack of sufficient experimental data. Diffusion experiments are complex and time-consuming. Furthermore, the concentration dependence of the diffusion coefficients requires usually several experiments even for binary mixtures. The possibility to extract this information from one short Raman diffusion experiment is explored here. A general identification framework is provided which does not require the a priori specification of a diffusion coefficient model structure but establishes the concentration dependence directly from the data. The methodology is used to determine the diffusion coefficient in the mixture ethyl acetate-cyclohexane in a wide concentration range.

On the interpretation of ternary diffusion measurements in low-molecular weight fluids by dynamic light scattering

“…Thus, it seems that the use of conventional diffusion experiments such as Taylor dispersion and Gouy/Rayleigh interferometry [39] cannot be avoided for determination of the full diffusion matrix. Recent advantages in the use of spectroscopic measurement techniques hold the promise to provide easier access to multicomponent diffusion data [40][41][42]. These may then be complemented by DLS data near critical regions for which DLS measurements are invaluable.…”

Entropy Diagnostics for Fourth Order Partial Differential Equations in Conservation Form

“…Similarly, solute transport coefficients may depend on concentration (e.g. [17]). In some applications of parabolic equations, the transport equations may depend also on derivatives of the dependent variable (e.g.…”

Direct determination of the concentration dependence of diffusivities using combined model-based Raman and NMR experiments

“…These models are fitted toD 12 (x) using an unconstrained least-squares approach. As the candidate models chosen in [14] are linear in the parameters, the resulting linear parameter estimation problem can be solved analytically. This procedure already gives good initial estimates of the concentration dependenceD initial 12 (x, ϑ initial ).…”

“…However, the strategy suffers from the fact that the gradients of the concentration profiles are small at very high and low concentrations [14]. In these regions error noise is strongly amplified.…”

“…The method facilitates the efficient generation of candidate model structures and delivers good initial model parameter estimates. The approach was validated using the binary system ethyl acetate-cyclohexane [14]. From a single Raman diffusion experiment, the concentration dependence of the binary diffusion coefficient could be reproduced in a large concentration interval from 20 to 85 mol%.…”