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We present a new method for introducing stable non-equilibrium concentration gradients in molecular dynamics simulations of mixtures. This method extends earlier Reverse Non-Equilibrium Molecular Dynamics (RNEMD) methods which use kinetic energy scaling moves to create temperature or velocity gradients. In the new scaled particle flux (SPF-RNEMD) algorithm, energies and forces are computed simultaneously for a molecule existing in two non-adjacent regions of a simulation box, and the system evolves under a linear combination of these interactions. A continuously increasing particle scaling variable is responsible for migration of the molecule between the regions as the simulation progresses, allowing for simulations under an applied particle flux. To test the method, we investigate diffusivity in mixtures of identical, but distinguishable particles, and in a simple mixture of multiple Lennard-Jones particles. The resulting concentration gradients provide Fick diffusion constants for mixtures. We also discuss using the new method to obtain coupled transport properties using simultaneous particle \textit{and} thermal fluxes to compute the temperature dependence of the diffusion coefficient and activation energies for diffusion from a single simulation. Lastly, we demonstrate the use of this new method in interfacial systems by computing the diffusive permeability for a molecular fluid moving through a nanoporous graphene membrane.
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This content will become publicly available on June 1, 2026
curvedSpaceSim: A framework for simulating particles interacting along geodesics
A large number of powerful, high-quality, and open-source simulation packages exist to efficiently perform molecular dynamics simulations, and their prevalence has greatly accelerated discoveries across a wide range of scientific domains. These packages typically simulate particles in flat (Euclidean) space, with options to specify a variety of boundary conditions. While more exotic, many physical systems are constrained to and interact across curved surfaces, such as organisms moving across the landscape, colloids pinned at curved fluid-fluid interfaces, and layers of epithelial cells forming highly curved tissues. The calculation of distances and the updating of equations of motion in idealized geometries (namely, on surfaces of constant curvature) can be done analytically, but it is much more challenging to efficiently perform molecular-dynamics-like simulations on arbitrarily curved surfaces. This article discusses a simulation framework which combines tools from particle-based simulations with recent work in discrete differential geometry to model particles that interact via geodesic distances and move on an arbitrarily curved surface. We present computational cost estimates for a variety of surface complexities with and without various algorithmic specializations (e.g., restrictions to short-range interaction potentials, or multi-threaded parallelization). Our flexible and extensible framework is set up to easily handle both equilibrium and non-equilibrium dynamics, and will enable researchers to access time- and particle-number-scales previously inaccessible.
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- Award ID(s):
- 2143815
- PAR ID:
- 10581476
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Computer Physics Communications
- Volume:
- 311
- Issue:
- C
- ISSN:
- 0010-4655
- Page Range / eLocation ID:
- 109545
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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