Abstract
Hamiltonian hybrid particle-field molecular dynamics is a computationally efficient method to study large soft matter systems. In this work, we extend this approach to constant pressure (NPT) simulations. We reformulate the calculation of internal pressure from the density field by taking into account the intrinsic spread of the particles in space, which naturally lead to a direct anisotropy in the pressure tensor. The anisotropic contribution is crucial for reliably describing the physics of systems under pressure, demonstrated by a series of tests on analytical and monoatomic model systems as well as realistic water/lipid biphasic systems. Using Bayesian optimization, we parameterise the field interactions of phospholipids to reproduce the structural properties of their lamellar phases, including area per lipid, and local density profiles. The resulting model excels in providing pressure profiles in qualitative agreement with all-atom modeling, surface tension, and area compressibility in quantitative agreement with experimental values, indicating the correct description of long wavelength undulations in large membranes. Finally, we demonstrate that the model is capable of reproducing the formation of lipid droplets inside a lipid bilayer.
Supplementary materials
Title
Supporting Information: Details of derivations and implementations
Description
Coarse-grained mapping for DPPC, Hamiltonian hybrid particle-field pressure derivation and implementation, analytic model for biphasic system confirming anisotropy in pressure, details of the Bayesian Optimization protocol to optimise model parameters and details of constant area simulations.
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