2019 AIChE Annual Meeting

(490e) Predicting Phase Equilibria and Thermodynamic Properties Using Ab Initio Potentials

Author

Sadus, R. - Presenter, Swinburne Univ of Technology
In the context of molecular simulation [1], the calculation of both phase equilibria and thermodynamic properties has been largely confined to using either empirical or semi-empirical intermolecular potentials. The Lennard-Jones potential arguably forms some part of the overwhelming majority of molecular simulations either as a representation of the interaction between atoms or to obtain the non-bonded contributions in commonly used molecular force fields [2]. The extended Lennard-Jones, or Mie potentials can be accurately fitted [3] to reproduce the vapor-liquid equilibria of a wide variety of molecular fluids. In parallel with the widespread use of empirical potentials, advances in quantum chemistry, most notably the CCSD(T) method [4], has witnessed the development of accurate two-body potentials for both atomic systems and some simple molecules [5]. However, application of these advances to the prediction of either phase equilibria or thermodynamic properties has been scant. Two practical limitations of ab initio potentials are (a) computational complexity; and (b) the restriction to two-body interactions. The former means that calculations are much more costly compared with empirical potentials, whereas the latter limitation means the predictions are not sufficiently accurate in most cases.

Recent theoretical developments [6] mean that the computational bottleneck of complexity has been significantly overcome and viable techniques are available [7] to address the accuracy issue. In this work, we demonstrate that ab initio potentials can be used to predict both vapor-liquid equilibria and thermodynamic properties more accurately than commonly used empirical potentials. Furthermore, the calculations can be performed without the significant computational cost of traditional ab initio calculations.

[1] R. J. Sadus, Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation, Elsevier, Amsterdam, 1999.

[2] B. R. Brooks, R. E. Bruccoleri, B. D. Olafson, D. J. States, S. Swaminathan, and M. Karplus, J. Comput. Chem., 4, 187 (1983).

[3] J. R. Mick, M. S. Barhaghi, B. Jackman, L. Rushaidat, L. Schwiebert and J. J. Potoff, J. Chem. Phys.,143, 114504 (2015).

[4] E. Clementi, in Theory and Applications in Computational Chemistry: The First Decade of the Second Millennium, edited by E. Clementi, J. M. André, and J. A. McCommon, AIP Conference Proceedings, 2012, Vol. 1456, p. 5.

[5] R. Hellmann, B. Jäjer and E. Bich, J. Chem. Phys., 147, 034304 (2017).

[6] U. K. Deiters and R. J. Sadus, J. Chem. Phys.,150, 134504 (2019).

[7] R. J. Sadus, J. Chem. Phys., 150, 024503 (2019).