Soft Matter under Pressure: Pushing Particle-Field Molecular Dynamics to the Isobaric Ensemble

06 February 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


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.


molecular dynamics
method development
density field
coarse grain

Supplementary materials

Supporting Information: Details of derivations and implementations
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.


Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.