1.3. LAMMPS features¶
LAMMPS is a classical molecular dynamics (MD) code with these general classes of functionality:
1.3.1. General features¶
runs on a single processor or in parallel
distributed memory message-passing parallelism (MPI)
shared memory multi-threading parallelism (OpenMP)
spatial decomposition of simulation domain for MPI parallelism
particle decomposition inside of spatial decomposition for OpenMP and GPU parallelism
GPLv2 licensed open-source distribution
highly portable C++-11
modular code with most functionality in optional packages
only depends on MPI library for basic parallel functionality, MPI stub for serial compilation
other libraries are optional and only required for specific packages
GPU (CUDA, OpenCL, HIP, SYCL), 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 or SWIG based wrappers
couple with other codes: LAMMPS calls other code, other code calls LAMMPS, umbrella code calls both
1.3.2. Particle and model types¶
(See 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
finite-size rounded polygons (2d) and polyhedra (3d) particles
point dipole particles
particles with magnetic spin
rigid collections of n particles
hybrid combinations of these
1.3.3. Interatomic potentials (force fields)¶
(See 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, Streitz-Mintmire, 3-body polymorphic, BOP, Vashishta
machine learning potentials: SNAP, GAP, ACE, N2P2, RANN, AGNI
long-range interactions for charge, point-dipoles, and LJ dispersion: Ewald, Wolf, PPPM (similar to particle-mesh Ewald), MSM
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, mesoscopic tubular potential (MESONT)
semi-empirical potentials: multi-ion generalized pseudopotential theory (MGPT), second moment tight binding + QEq (SMTB-Q), density functional tight-binding (LATTE)
electron force field (eFF, AWPMD)
bond potentials: harmonic, FENE, Morse, nonlinear, class 2, quartic (breakable), tabulated
angle potentials: harmonic, CHARMM, cosine, cosine/squared, cosine/periodic, class 2 (COMPASS), tabulated
dihedral potentials: harmonic, CHARMM, multi-harmonic, helix, class 2 (COMPASS), OPLS, tabulated
improper potentials: harmonic, cvff, umbrella, class 2 (COMPASS), tabulated
polymer potentials: all-atom, united-atom, bead-spring, breakable
water potentials: TIP3P, TIP4P, SPC, SPC/E and variants
interlayer potentials for graphene and analogues
metal-organic framework potentials (QuickFF, MO-FF)
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 command
hybrid potentials: multiple pair, bond, angle, dihedral, improper potentials can be used in one simulation
overlaid potentials: superposition of multiple pair potentials (including many-body) with optional scale factor
1.3.4. Atom creation¶
(See 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¶
(See 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
motion constraints to manifold surfaces
Monte Carlo bond breaking, formation, swapping, template based reaction modeling
atom/molecule insertion and deletion
walls of various kinds, static and moving
non-equilibrium molecular dynamics (NEMD)
variety of additional boundary conditions and constraints
1.3.6. Integrators¶
(See 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¶
1.3.8. Output¶
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
custom partitioning (chunks) for binning, and static or dynamic grouping of atoms for analysis
spatial, time, and per-chunk averaging of per-atom quantities
time averaging and histogramming of system-wide quantities
atom snapshots in native, XYZ, XTC, DCD, CFG formats
1.3.9. Multi-replica models¶
path-integral MD: first variant <fix_pimd>, second variant <fix_ipi>
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 Tools 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 Optional Packages page for details.
These are LAMMPS capabilities which you may not think of as typical classical MD options:
static and dynamic load-balancing, optional with recursive bisectioning decomposition
real-time visualization and interactive MD, built-in renderer for images and movies
calculate virtual diffraction patterns
calculate finite temperature phonon dispersion and the dynamical matrix of minimized structures
atom-to-continuum coupling with finite elements
coupled rigid body integration via the POEMS library
Monte Carlo via GCMC and tfMC and atom swapping
Direct Simulation Monte Carlo for low-density fluids