A computational scheme to evaluate Hamaker constants of molecules with practical size and anisotropy

TL;DR

This paper introduces a computational method to accurately evaluate Hamaker constants for practical, anisotropic molecules using diffusion Monte Carlo, enabling better predictions of material properties like wettability.

Contribution

The paper develops a novel computational scheme that accounts for anisotropy and biases in DMC calculations to evaluate Hamaker constants of complex molecules.

Findings

Successfully applied to cyclohexasilane molecule with A ≈ 105 ± 2 zJ

Scheme reduces statistical errors and biases in DMC evaluations

Supports broader use in materials informatics for property prediction

Abstract

We propose a computational scheme to evaluate Hamaker constants, $A$, of molecules with practical sizes and anisotropies. Upon the increasing feasibility of diffusion Monte Carlo (DMC) methods to evaluate binding curves for such molecules to extract the constants, we discussed how to treat the averaging over anisotropy and how to correct the bias due to the non-additivity. We have developed a computational procedure for dealing with the anisotropy and reducing statistical errors and biases in DMC valuations, based on possible validations on predicted $A$. We applied the scheme to cyclohexasilane molecule, Si$_6$H$_{12}$, used in 'printed electronics' fabrications, getting $A \sim 105 \pm 2$ [zJ], being in plausible range supported even by other possible extrapolations. The scheme provided here would open a way to use handy {\it ab initio} evaluations to predict wettabilities as in the form of materials informatics over broader molecules.