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Systematic errors in diffusion coefficients from long-time molecular dynamics simulations at constant pressure.

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Summary
This summary is machine-generated.

A new particle unwrapping method corrects molecular dynamics simulations. This method avoids unphysical trajectories and exaggerated diffusion coefficients in long simulations at constant pressure.

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Area of Science:

  • Computational physics
  • Physical chemistry

Background:

  • Molecular dynamics (MD) simulations are crucial for understanding particle behavior.
  • Periodic boundary conditions (PBC) are standard in MD, requiring particle positions to be wrapped within a reference box.
  • Calculating diffusion coefficients using the Einstein relation necessitates unwrapping particle positions.

Purpose of the Study:

  • To identify limitations of a common particle unwrapping heuristic in MD simulations.
  • To propose and validate a novel, accurate unwrapping scheme for MD simulations.
  • To provide a method for assessing the impact of previous unwrapping inaccuracies on simulation results.

Main Methods:

  • The study analyzes a widely used heuristic particle unwrapping scheme.
  • A new unwrapping scheme is proposed, adding minimal displacement vectors based on instantaneous box geometry at each time step.
  • The new scheme was tested on extensive molecular dynamics and Brownian dynamics simulation data.

Main Results:

  • The heuristic unwrapping scheme was found unsuitable for long simulations at constant pressure.
  • Improper handling of box-volume fluctuations in the heuristic scheme leads to unphysical trajectories and inflated diffusion coefficients.
  • The proposed alternative scheme effectively resolves these issues, yielding accurate simulation data.

Conclusions:

  • The heuristic particle unwrapping method can introduce significant errors in diffusion coefficient calculations.
  • The newly proposed unwrapping scheme provides accurate particle trajectories and diffusion coefficients, even in long simulations at constant pressure.
  • A formula is provided to help researchers evaluate potential errors in prior simulation studies.