Nature Communications (Mar 2025)

Entropy scaling for diffusion coefficients in fluid mixtures

  • Sebastian Schmitt,
  • Hans Hasse,
  • Simon Stephan

DOI
https://doi.org/10.1038/s41467-025-57780-z
Journal volume & issue
Vol. 16, no. 1
pp. 1 – 10

Abstract

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Abstract Entropy scaling is a powerful technique that has been used for predicting transport properties of pure components over a wide range of states. However, modeling mixture diffusion coefficients by entropy scaling is an unresolved task. We tackle this issue and present an entropy scaling framework for predicting mixture self-diffusion coefficients as well as mutual diffusion coefficients in a thermodynamically consistent way. The predictions of the mixture diffusion coefficients are made based on information on the self-diffusion coefficients of the pure components and the infinite-dilution diffusion coefficients. This is accomplished using information on the entropy of the mixture, which is taken here from molecular-based equations of state. Examples for the application of the entropy scaling framework for the prediction of diffusion coefficients in mixtures illustrate its performance. It enables predictions over a wide range of temperatures and pressures including gaseous, liquid, supercritical, and metastable states—also for strongly non-ideal mixtures.