Effective Fragment Potential-Based Molecular Dynamics Studies of Diffusion in Acetone and Hexane

Abstract

To facilitate more reliable descriptions of transport properties in liquids, molecular dynamics (MD) simulations are performed based on the effective fragment potential (EFP) method derived from first-principles quantum mechanics (in contrast to MD based upon empirically fitted potentials). The EFP method describes molecular interactions in terms of Coulomb, polarization/induction, dispersion, exchange-repulsion, and charge-transfer interactions. The EFP MD simulations described in this paper, performed on hexane and acetone, are able to track the mean-square displacement of molecules for sufficient time to reliably extract translational diffusion coefficients. The results reported here are in reasonable agreement with experiment.

Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles

“…At the equilibrium geometry, the dispersion and Coulomb terms are the dominant interactions, both contributing ∼−7 kcal mol −1 to the net EFP interaction energy. The vertical intermolecular distance between monomers of the trans -sandwich geometry is 3.2 Å at the equilibrium point, 37 in good agreement with the lowest energy geometry predicted by the MP2 level of theory. 54 The potential energy surface of the antiparallel sandwich geometry in ref.…”

“…The sandwich binding energy is relatively small, and those of the linear species are even smaller. The previous EFP MD study 37 indicates no aggregation of acetone molecules in an acetone–hexane 1 : 1 volume ratio mixture. Based on the data in Table 3, the PNB–acetone and PNB–hexane interaction energies are very similar at the lowest energy parallel displaced arrangement.…”

“…However, the EFP method is orders of magnitude more computationally efficient than DFT. 37 Slipchenko et al have demonstrated, for example, that the EFP interaction energy of stacked benzene dimers is in good agreement with the interaction energies obtained from CCSD(T)/ aug-cc-pVQZ calculations and that the decomposition of the interaction energies into their components are in reasonable agreement with SAPT. 38 The EFP method has been applied to a broad range of noncovalent complexes, including DNA base pairs, 39 dimers of substituted benzenes, 40 water-benzene complexes, 41 water-amino acid complexes [42][43][44] and the S22 test set.…”

“…In a previous paper, the interactions of the hexane–acetone sandwich configuration were part of a study of the diffusion coefficient based on EFP-MD simulations. 37 It was concluded in that study that the permanent dipole of acetone exerts a strong acetone homo-molecular interaction. Therefore, the acetone–hexane interaction is weaker than the acetone homo–molecular interaction, thereby resulting in a higher self-diffusion coefficient for acetone in the acetone–hexane mixture than pure acetone.…”

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

“…Molecular dynamics (MD) has been used extensively for calculating self-diffusion in various systems, − using both classical MD and ab initio MD simulations. − MD simulations have been performed to determine self-diffusion in simple Lennard-Jones (LJ) fluids, − including binary and ternary LJ mixtures. − MD approaches have also been used to determine self-diffusion coefficients in confined fluids, including pure fluids in slit pores, , gases in metal–organic-frameworks (MOFs), and mixtures within nanoslits and nanopores. − While MD simulations have proven to be indispensable for diffusion predictions, they still require extensive time and dedication when exploring large spaces of mixture compositions or experimental conditions. Additionally, the MD simulation of mixtures in porous materials requires tailored force fields to represent the interactions between molecules and the material (e.g., pore walls and surfaces) accurately. , …”