NIST - Physical and Chemical Properties Division

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Theory and Simulation of Complex Fluids

L. Lue, B.D. Butler, D.J. Evans (Australian Natl. Univ.), L.V. Woodcock (Univ. of Bradford), and S. Gay (Univ. of Colorado)

Objective: To develop new, more efficient computer simulation methods for complex fluid and solid systems; to improve our understanding of single component and multi-component atomic and molecular models, both in and out of equilibrium; and to improve current predictive models of fluid properties through a better understanding of model systems.

Problem: In general, computer simulation is not effective at predicting, from first principles, the behavior of real fluids with the accuracy required by chemical engineers. This is not only because of current limits on computational resources; the available simulation methods and algorithms also need to be improved. However, by providing an "ideal" laboratory in which to study the behavior of systems containing a large number of interacting particles, computer simulation provides an important tool in the study of the thermophysical properties of complex fluid and solid systems. This "ideal" laboratory allows precise testing of theories for real systems. In addition, computer simulation yields insights into the fundamental nature of the structure and dynamics of complex systems. These insights, for example, have been incorporated into semi-empirical equations that are used for the prediction of fluid properties in technologically important systems. The improvement and application of computer modeling algorithms are thus essential for progress in the development of prediction tools required by industry.

Approach: Our simulation and modeling activities concentrate on areas of current interest in the Division. Some examples include the process of aggregation in quenched systems as models of gelation phenomena, the effects of shear on the thermodynamic states of fluids, steric effects in binary systems and their implications on solid-fluid equilibrium, and the behavior of macromolecules. By identifying and isolating weaknesses in current methods and theories, alternatives are developed, tested, and improved.

Results and Future Plans: Aggregation phenomena have been investigated in systems with potential functions that contain a short-range attractive and long-range repulsive component. These systems reproduce many interesting effects observed in real aggregating systems, such as network formation. A crossover theory for the structure and thermodynamics of linear and star polymers in good solvents has been developed and tested using Monte Carlo methods. This theory is able to describe the scaling behavior of dilute to semidilute polymer solutions, as well as the properties of concentrated polymer systems. Monte Carlo studies have also been performed for dendritic polymer solutions (cf. figure). Methods to study depletion forces that arise from entropic considerations in binary hard-sphere systems have also been developed. The concept of "configurational temperature," which was previously developed and tested for atomic systems, has been extended to molecular systems. A generalization of the Poisson-Boltzmann equation that accounts for nonelectrostatic interactions has been developed. Future plans include the incorporation of the concept of configurational temperature to the thermostatting of nonequilibrium molecular dynamics models, the study of shear on aggregation processes, the simulation and modeling of glassy systems, and the testing of theoretical predictions of phase equilibria in binary mixtures.


Lue, L. and Kiselev, S.B., "Crossover Approach to Scaling Behavior in Dilute Polymer Solutions: Theory and Simulation," J. Chem. Phys. 110, 2684 (1999).

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Last modified: 21 February 2000