T. Verstraelen

This work presents a novel parametrization for the ReaxFF formalism as a means to investigate reaction processes of chlorinated organic compounds. Force field parameters cover the chemical elements C, H, O, Cl and were obtained using a novel optimization approach involving relaxed potential energy surface scans as training targets. The resulting ReaxFF parametrization shows good transferability, as demonstrated on two independent ab initio validation sets. While this first part of our two-paper series focuses on force field parametrization, we apply our parameters to the simulation of chlorinated dibenzofuran formation and decomposition processes in Part II.

Viscosity is a crucial property of liquid lubricants, and it is theoretically a well-defined quantity in molecular dynamics (MD) simulations. However, no standardized protocol has been defined for calculating this property from equilibrium MD simulations. While best practices do exist, the actual calculation depends on several ad hoc decisions during the post-processing of the raw MD data. A common protocol for calculating the viscosity with equilibrium MD simulations is called the time decomposition method (TDM). Although the TDM attempts to standardize the viscosity calculation using the Green–Kubo method, it still relies on certain empirical rules and subjective user observations, e.g., the plateau region of the Green–Kubo integral or the integration cut-off time. It is known that the TDM works reasonably well for low-viscosity fluids, e.g., at high temperatures. However, modified heuristics have been proposed at high pressures, indicating that no single set of rules works well for all circumstances. This study examines the effect of heuristics and ad hoc decisions on the predicted viscosity of a short, branched lubricant molecule, 2,2,4-trimethylhexane. Equilibrium molecular dynamics simulations were performed at various operating conditions (high pressures and temperatures), followed by post-processing with three levels of uncertainty quantification. A new approach, “Enhanced Bootstrapping”, is introduced to assess the effects of individual ad hoc parameters on the viscosity. The results show a strong linear correlation (with a Pearson correlation coefficient of up to 36%) between the calculated viscosity and an ad hoc TDM parameter, which determines the integration cut-off time, under realistic lubrication conditions, particularly at high pressures. This study reveals that ad hoc decisions can lead to potentially misleading conclusions when the post-processing is performed ambiguously.

We develop a variational procedure for the iterative Hirshfeld (HI) partitioning scheme. The main practical advantage of having a variational framework is that it provides a formal and straightforward approach for imposing constraints (e.g., fixed charges on certain atoms or molecular fragments) when computing HI atoms and their properties. Unlike many other variants of the Hirshfeld partitioning scheme, HI charges do not arise naturally from the information-theoretic framework, but only as a reverse-engineered construction of the objective function. However, the procedure we use is quite general and could be applied to other problems as well. We also prove that there is always at least one solution to the HI equations, but we could not prove that its self-consistent equations would always converge for any given initial pro-atom charges. Our numerical assessment of the constrained iterative Hirshfeld method shows that it satisfies many desirable traits of atoms in molecules and has the potential to surpass existing approaches for adding constraints when computing atomic properties.

Published under an exclusive license by AIP Publishing.

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.