Molecular Dynamics

Molecular dynamics (MD) is a computer simulation method for analyzing the physical movements of atoms and molecules. The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamic “evolution” of the system. In the most common version, the trajectories of atoms and molecules are determined by numerically solving Newton’s equations of motion for a system of interacting particles, where forces between the particles and their potential energies are calculated using first-principles calculations (first-principles molecular dynamics, FPMD), or interatomic potentials and molecular mechanics force fields (classical molecular dynamics, CMD).

By setting calculation to be md or sto-md, ABACUS currently provides six different MD evolution methods, which is specified by keyword md_type in the INPUT file:

  • -1: FIRE method

  • 0: NVE ensemble

  • 1: NVT ensemble with Nose Hoover Chain

  • 2: NVT ensemble with Langevin thermostat

  • 3: NVT ensemble with Anderson thermostat

  • 4: MSST method

Furthermore, ABACUS also provides a list of keywords to control relevant parmeters used in MD simulations.

Examples of MD simulations are also provided. There are six INPUT files corresponding to six different MD evolution methods in the directory. For examlpe, INPUT_0 shows how to employ the NVE simulation.

To run any of the fix cases, users may enter the directory, copy the corresponding input file to INPUT, and run ABACUS.

FIRE

FIRE (fast inertial relaxation engine) is a MD-based minimization algorithm. It is based on conventional molecular dynamics with additional velocity modifications and adaptive time steps. The MD trajectory will descend to an energy-minimum.

NVE

NVE ensemble (i. e. microcanonical ensemble) is a statistical ensemble that represents the possible states of a mechanical system whose total energy is exactly specified. The system is assumed to be isolated in the sense that it cannot exchange energy or particles with its environment, so that the energy of the system does not change with time.

The primary macroscopic variables of the microcanonical ensemble are the total number of particles in the system (symbol: N), the system’s volume (symbol: V), as well as the total energy in the system (symbol: E). Each of these is assumed to be constant in the ensemble.

Currently NVE ensemble in ABACUS is implemented based on the velocity verlet algorithm.

Nose Hoover Chain

NVT ensemble (i. e. canonical ensemble) is the statistical ensemble that represents the possible states of a mechanical system in thermal equilibrium with a heat bath at a fixed temperature. The system can exchange energy with the heat bath, so that the states of the system will differ in total energy.

The principal thermodynamic variable of the canonical ensemble, determining the probability distribution of states, is the absolute temperature (symbol: T). The ensemble typically also depends on mechanical variables such as the number of particles in the system (symbol: N) and the system’s volume (symbol: V), each of which influence the nature of the system’s internal states. An ensemble with these three parameters is sometimes called the NVT ensemble.

ABACUS perform time integration on Nose-Hoover style non-Hamiltonian equations of motion which are designed to generate positions and velocities sampled from NVT ensemble.

Langevin

Langevin thermostat can be used for molecular dynamics equations by assuming that the atoms being simulated are embedded in a sea of much smaller fictional particles. In many instances of solute-solvent systems, the behavior of the solute is desired, and the behavior of the solvent is non-interesting(e.g. proteins, DNA, nanoparticles in solution). In these cases, the solvent influences the dynamics of the solute(typically nanoparticles) via random collisions, and by imposing a frictional drag force on the motion of the nanoparticle in the solvent. The damping factor and the random force combine to give the correct NVT ensemble.

Anderson

Anderson thermostat couples the system to a heat bath that imposes the desired temperature to simulate the NVT ensemble. The coupling to a heat bath is represented by stochastic collision that act occasionally on randomly selected particles.

MSST

ABACUS performs the Multi-Scale Shock Technique (MSST) integration to update positions and velocities each timestep to mimic a compressive shock wave passing over the system. The MSST varies the cell volume and temperature in such a way as to restrain the system to the shock Hugoniot and the Rayleigh line. These restraints correspond to the macroscopic conservation laws dictated by a shock front.