1.3. LAMMPS features

LAMMPS is a classical molecular dynamics (MD) code with these general classes of functionality:

  1. General features

  2. Particle and model types

  3. Interatomic potentials (force fields)

  4. Atom creation

  5. Ensembles, constraints, and boundary conditions

  6. Integrators

  7. Diagnostics

  8. Output

  9. Multi-replica models

  10. Pre- and post-processing

  11. Specialized features (beyond MD itself)

1.3.1. General features

  • runs on a single processor or in parallel

  • distributed-memory message-passing parallelism (MPI)

  • spatial-decomposition of simulation domain for parallelism

  • open-source distribution

  • highly portable C++

  • optional libraries used: MPI and single-processor FFT

  • GPU (CUDA and OpenCL), Intel Xeon Phi, and OpenMP support for many code features

  • easy to extend with new features and functionality

  • runs from an input script

  • syntax for defining and using variables and formulas

  • syntax for looping over runs and breaking out of loops

  • run one or multiple simulations simultaneously (in parallel) from one script

  • build as library, invoke LAMMPS through library interface or provided Python wrapper

  • couple with other codes: LAMMPS calls other code, other code calls LAMMPS, umbrella code calls both

1.3.2. Particle and model types

(atom style command)

  • atoms

  • coarse-grained particles (e.g. bead-spring polymers)

  • united-atom polymers or organic molecules

  • all-atom polymers, organic molecules, proteins, DNA

  • metals

  • granular materials

  • coarse-grained mesoscale models

  • finite-size spherical and ellipsoidal particles

  • finite-size line segment (2d) and triangle (3d) particles

  • point dipole particles

  • rigid collections of particles

  • hybrid combinations of these

1.3.3. Interatomic potentials (force fields)

(pair style, bond style, angle style, dihedral style, improper style, kspace style commands)

  • pairwise potentials: Lennard-Jones, Buckingham, Morse, Born-Mayer-Huggins, Yukawa, soft, class 2 (COMPASS), hydrogen bond, tabulated

  • charged pairwise potentials: Coulombic, point-dipole

  • many-body potentials: EAM, Finnis/Sinclair EAM, modified EAM (MEAM), embedded ion method (EIM), EDIP, ADP, Stillinger-Weber, Tersoff, REBO, AIREBO, ReaxFF, COMB, SNAP, Streitz-Mintmire, 3-body polymorphic

  • long-range interactions for charge, point-dipoles, and LJ dispersion: Ewald, Wolf, PPPM (similar to particle-mesh Ewald)

  • polarization models: QEq, core/shell model, Drude dipole model

  • charge equilibration (QEq via dynamic, point, shielded, Slater methods)

  • coarse-grained potentials: DPD, GayBerne, REsquared, colloidal, DLVO

  • mesoscopic potentials: granular, Peridynamics, SPH

  • electron force field (eFF, AWPMD)

  • bond potentials: harmonic, FENE, Morse, nonlinear, class 2, quartic (breakable)

  • angle potentials: harmonic, CHARMM, cosine, cosine/squared, cosine/periodic, class 2 (COMPASS)

  • dihedral potentials: harmonic, CHARMM, multi-harmonic, helix, class 2 (COMPASS), OPLS

  • improper potentials: harmonic, cvff, umbrella, class 2 (COMPASS)

  • polymer potentials: all-atom, united-atom, bead-spring, breakable

  • water potentials: TIP3P, TIP4P, SPC

  • implicit solvent potentials: hydrodynamic lubrication, Debye

  • force-field compatibility with common CHARMM, AMBER, DREIDING, OPLS, GROMACS, COMPASS options

  • access to the OpenKIM Repository of potentials via kim_init, kim_interactions, and kim_query commands

  • hybrid potentials: multiple pair, bond, angle, dihedral, improper potentials can be used in one simulation

  • overlaid potentials: superposition of multiple pair potentials

1.3.4. Atom creation

(read_data, lattice, create_atoms, delete_atoms, displace_atoms, replicate commands)

  • read in atom coords from files

  • create atoms on one or more lattices (e.g. grain boundaries)

  • delete geometric or logical groups of atoms (e.g. voids)

  • replicate existing atoms multiple times

  • displace atoms

1.3.5. Ensembles, constraints, and boundary conditions

(fix command)

  • 2d or 3d systems

  • orthogonal or non-orthogonal (triclinic symmetry) simulation domains

  • constant NVE, NVT, NPT, NPH, Parrinello/Rahman integrators

  • thermostatting options for groups and geometric regions of atoms

  • pressure control via Nose/Hoover or Berendsen barostatting in 1 to 3 dimensions

  • simulation box deformation (tensile and shear)

  • harmonic (umbrella) constraint forces

  • rigid body constraints

  • SHAKE bond and angle constraints

  • Monte Carlo bond breaking, formation, swapping

  • atom/molecule insertion and deletion

  • walls of various kinds

  • non-equilibrium molecular dynamics (NEMD)

  • variety of additional boundary conditions and constraints

1.3.6. Integrators

(run, run_style, minimize commands)

  • velocity-Verlet integrator

  • Brownian dynamics

  • rigid body integration

  • energy minimization via conjugate gradient or steepest descent relaxation

  • rRESPA hierarchical timestepping

  • rerun command for post-processing of dump files

1.3.7. Diagnostics

  • see various flavors of the fix and compute commands

1.3.8. Output

(dump, restart commands)

  • log file of thermodynamic info

  • text dump files of atom coords, velocities, other per-atom quantities

  • binary restart files

  • parallel I/O of dump and restart files

  • per-atom quantities (energy, stress, centro-symmetry parameter, CNA, etc)

  • user-defined system-wide (log file) or per-atom (dump file) calculations

  • spatial and time averaging of per-atom quantities

  • time averaging of system-wide quantities

  • atom snapshots in native, XYZ, XTC, DCD, CFG formats

1.3.10. Pre- and post-processing

  • A handful of pre- and post-processing tools are packaged with LAMMPS, some of which can convert input and output files to/from formats used by other codes; see the Toos doc page.

  • Our group has also written and released a separate toolkit called Pizza.py which provides tools for doing setup, analysis, plotting, and visualization for LAMMPS simulations. Pizza.py is written in Python and is available for download from the Pizza.py WWW site.

1.3.11. Specialized features

LAMMPS can be built with optional packages which implement a variety of additional capabilities. See the Packages doc page for details.

These are LAMMPS capabilities which you may not think of as typical classical MD options: