Uncertainty quantification confirms unreliable extrapolation toward high pressures for united-atom Mie λ-6 force field

Abstract

Molecular simulation results at extreme temperatures and pressures can supplement experimental data when developing fundamental equations of state. Since most force fields are optimized to agree with vapor-liquid equilibria (VLE) properties, however, the reliability of the molecular simulation results depends on the validity/transferability of the force field at higher temperatures and pressures. As demonstrated in this study, although state-of-the-art united-atom Mie λ-6 potentials for normal and branched alkanes provide accurate estimates for VLE, they tend to over-predict pressures for dense supercritical fluids and compressed liquids. The physical explanation for this observation is that the repulsive barrier is too steep for the "optimal" united-atom Mie λ-6 potential parameterized with VLE properties. Bayesian inference confirms that no feasible combination of nonbonded parameters ( , σ, and λ) is capable of simultaneously predicting saturated vapor pressures, saturated liquid densities, and pressures at high temperatures and densities. This conclusion has both practical and theoretical ramifications, as more realistic non-bonded potentials may be required for accurate extrapolation to high pressures of industrial interest.

Uncertainty quantification for classical effective potentials: an extension to potfit

“…There has also been work toward the quantification of uncertainty due to the potential fitting reference set [4], as well as a proposed framework to efficiently propagate parameter uncertainties to molecular dynamics (MD) outputs [5]. More specifically, quantification of parameter uncertainty for single potentials has been undertaken in a handful of cases [6][7][8][9]. We add to the growing body of uncertainty quantification (UQ) work in potential development and application by providing an open source implementation of the framework in [1] for use in future potential development projects.…”

Histogram-Free Reweighting with Grand Canonical Monte Carlo: Post-simulation Optimization of Non-bonded Potentials for Phase Equilibria

“…The results presented in this study were obtained by performing simulations with only a single reference force field. As shown in previous studies, a logical approach for improving the performance of MBAR is to include additional reference force fields. , For example, in section , we did not utilize the snapshots from λ CH 2 = 14 when computing properties for λ CH 2 = 16 and vice versa. Using multiple reference force fields would certainly increase the number of effective snapshots.…”

“…In related studies, Messerly et al. demonstrate how to combine MBAR with ITIC (MBAR-ITIC) to optimize generalized Lennard-Jones (Mie λ-6) potentials. , For MBAR-ITIC, a series of simulations are performed with a constant number of molecules, constant volume, and constant temperature ( NVT ) along a supercritical isotherm and liquid density isochore(s) with a “reference” force field(s) (θ ref ). Subsequently, the energies and forces are recomputed for the configurations sampled with θ ref using a different “rerun” force field (θ rr ).…”

Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review

“…The quantification of parametric uncertainty for single potentials has been undertaken in several cases [52,53] while Bayesian frameworks have also been proposed for a variety of interatomic models and force fields [54,55,56]. Furthermore, quantification of uncertainty due to the potential fitting reference set [57] was augmented by propagation of parametric uncertainties to MD outputs [58].…”