Potential

eON supports a large number of potentials, some vendored within the executable and libraries and others via interfaces.

Note

Some of these require flags to be set, details are in the installation instructions

Supported Potentials

External

VASP [POT_KFurthmuller96]

Vienna Ab-Initio Simulation Program (VASP) I/O interface.

LAMMPS [POT_Pli95, POT_TAB+22]

Library interface, detailed documentation here

EXT_POT

Writes box size and coordinates to the file from_eon_to_ext and makes a system call to ext_pot which must populate from_ext_to_eon

Added in version 2.0:

AMS(-IO)

Amsterdam modeling suite [POT_teVeldeBB+01], both I/O and library ASE_ORCA

Atomic simulation environment [POT_LMB+17] interface to ORCA [POT_NWBR20] XTB

Extended Tight binding models via native Fortran-C interfce [POT_BCE+21]

Vendored

CuH2

Copper Hydride system

FeHe

Iron-hydrides

EAM_Al

Embedded atom method parameterized for Aluminum.

QSC [POT_KQCG98]

Quantum Sutton-Chen potential, for FCC metals.

EMT

Effective medium theory, for metals.

LJ [POT_Jon24]

Lennard-Jones in reduced units

Morse_Pt

Hard sphere morse potential for Platinum

Lenosky_Si [POT_LSA+00]

Lenosky potential, for silicon.

SW_SI [POT_SW85]

Stillinger-Weber potential, for silicon.

Tersoff_SI [POT_Ter88]

Tersoff pair potential with angular terms, for silicon.

EDIP [POT_JBK+98]

Environment-Dependent Interatomic Potential, for carbon.

TIP4P [POT_JCM+83]

Point charge model for water, also for water-hydrogen and water on platinum.

SPCE [POT_BGS87]

Extended simple point charge model for water

Deprecated since version 2.0: These potentials are missing in the SVN sources.. bopfox : Bond order potential, for metals

Configuration

[Potential]

pydantic model eon.schema.PotentialConfig

Show JSON schema

{
   "title": "PotentialConfig",
   "type": "object",
   "properties": {
      "mpi_poll_period": {
         "default": 0.25,
         "description": "Polling period for MPI potential.",
         "title": "Mpi Poll Period",
         "type": "number"
      },
      "potential": {
         "default": "lj",
         "description": "Type of potential to execute.",
         "enum": [
            "ams",
            "ams_io",
            "ase_orca",
            "bop",
            "bopfox",
            "cuh2",
            "eam_al",
            "edip",
            "emt",
            "ext",
            "fehe",
            "gpr",
            "imd",
            "lammps",
            "lenosky_si",
            "lj",
            "ljcluster",
            "morse_pt",
            "mpi",
            "pyamff",
            "python",
            "qsc",
            "spce",
            "sw_si",
            "tersoff_si",
            "tip4p",
            "tip4p_h",
            "tip4p_pt",
            "unknown",
            "vasp",
            "xtb"
         ],
         "title": "Potential",
         "type": "string"
      },
      "log_potential": {
         "anyOf": [
            {
               "type": "boolean"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "If true, write timing information about each force call to client.log.",
         "title": "Log Potential"
      }
   }
}

Config:

• use_attribute_docstrings: bool = True

Fields:

• log_potential (bool | None)

• mpi_poll_period (float)

• potential (Literal['ams', 'ams_io', 'ase_orca', 'bop', 'bopfox', 'cuh2', 'eam_al', 'edip', 'emt', 'ext', 'fehe', 'gpr', 'imd', 'lammps', 'lenosky_si', 'lj', 'ljcluster', 'morse_pt', 'mpi', 'pyamff', 'python', 'qsc', 'spce', 'sw_si', 'tersoff_si', 'tip4p', 'tip4p_h', 'tip4p_pt', 'unknown', 'vasp', 'xtb'])

field log_potential: bool | None = None

If true, write timing information about each force call to client.log.

field mpi_poll_period: float = 0.25

Polling period for MPI potential.

field potential: Literal['ams', 'ams_io', 'ase_orca', 'bop', 'bopfox', 'cuh2', 'eam_al', 'edip', 'emt', 'ext', 'fehe', 'gpr', 'imd', 'lammps', 'lenosky_si', 'lj', 'ljcluster', 'morse_pt', 'mpi', 'pyamff', 'python', 'qsc', 'spce', 'sw_si', 'tersoff_si', 'tip4p', 'tip4p_h', 'tip4p_pt', 'unknown', 'vasp', 'xtb'] = 'lj'

Options:

• ams: Amsterdam Modeling Suite potential.

• ams_io: Amsterdam Modeling Suite via the I/O.

• ase_orca: ASE interface for ORCA quantum chemistry package.

• bop: Bond order potential for metals. [unused]

• bopfox: Bond order potential, for metals. [unused]

• cuh2: Potential for copper hydride systems.

• eam_al: Embedded atom method parameterized for aluminum.

• edip: Environment-Dependent Interatomic Potential, for carbon.

• emt: Effective medium theory, for metals.

• ext: External potential with system call interface.

• fehe: Potential for iron-hydrogen systems.

• gpr: Gaussian process regression potential.

• imd: IMD simulation package interface.

• lammps: The LAMMPS potentials.

• lenosky_si: Lenosky potential, for silicon.

• lj: Lennard-Jones potential in reduced units.

• ljcluster: Lennard-Jones cluster potential.

• morse_pt: Morse potential for platinum.

• mpi: Communicate with an MPI process to calculate energy and forces.

• pyamff: Python implementation of the AMFF potential.

• python: Custom python potential.

• qsc: Quantum Sutton-Chen potential, for FCC metals.

• spce: Simple Point Charge model for water.

• sw_si: Stillinger-Weber potential, for silicon.

• tersoff_si: Tersoff pair potential with angular terms, for silicon.

• tip4p: Point charge model for water.

• tip4p_h: TIP4P model for water with hydrogen.

• tip4p_pt: TIP4P model for water on platinum.

• unknown: Placeholder for unknown potential type.

• vasp: Vienna Ab-Initio Simulation Program (VASP) interface.

• xtb: Extended Tight Binding model.

Type of potential to execute.

classmethod set_log_potential(v, values)

References

[POT_BCE+21]

Christoph Bannwarth, Eike Caldeweyher, Sebastian Ehlert, Andreas Hansen, Philipp Pracht, Jakob Seibert, Sebastian Spicher, and Stefan Grimme. Extended tight-binding quantum chemistry methods. WIREs Computational Molecular Science, 11(2):e1493, 2021. doi:10.1002/wcms.1493.

[POT_BGS87]

H. J. C. Berendsen, J. R. Grigera, and T. P. Straatsma. The missing term in effective pair potentials. The Journal of Physical Chemistry, 91(24):6269–6271, November 1987. doi:10.1021/j100308a038.

[POT_Jon24]

Lennard Jones. On the determination of molecular fields. —II. From the equation of state of a gas. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 106(738):463–477, October 1924. doi:10.1098/rspa.1924.0082.

[POT_JCM+83]

William L. Jorgensen, Jayaraman Chandrasekhar, Jeffry D. Madura, Roger W. Impey, and Michael L. Klein. Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2):926–935, July 1983. doi:10.1063/1.445869.

[POT_JBK+98]

João F. Justo, Martin Z. Bazant, Efthimios Kaxiras, V. V. Bulatov, and Sidney Yip. Interatomic potential for silicon defects and disordered phases. Physical Review B, 58(5):2539–2550, August 1998. doi:10.1103/PhysRevB.58.2539.

[POT_KQCG98]

Yoshitaka Kimura, Yue Qi, Tahir Cagin, and William Goddard. The Quantum Sutton-Chen Many-Body Potential for Properties of fcc Metals. N/A, September 1998.

[POT_KFurthmuller96]

G. Kresse and J. Furthmüller. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Physical Review B, 54(16):11169–11186, October 1996. doi:10.1103/PhysRevB.54.11169.

[POT_LMB+17]

Ask Hjorth Larsen, Jens Jørgen Mortensen, Jakob Blomqvist, Ivano E. Castelli, Rune Christensen, Marcin Du\lak, Jesper Friis, Michael N. Groves, Bjørk Hammer, Cory Hargus, Eric D. Hermes, Paul C. Jennings, Peter Bjerre Jensen, James Kermode, John R. Kitchin, Esben Leonhard Kolsbjerg, Joseph Kubal, Kristen Kaasbjerg, Steen Lysgaard, Jón Bergmann Maronsson, Tristan Maxson, Thomas Olsen, Lars Pastewka, Andrew Peterson, Carsten Rostgaard, Jakob Schiøtz, Ole Schütt, Mikkel Strange, Kristian S. Thygesen, Tejs Vegge, Lasse Vilhelmsen, Michael Walter, Zhenhua Zeng, and Karsten W. Jacobsen. The atomic simulation environment—a Python library for working with atoms. Journal of Physics: Condensed Matter, 29(27):273002, June 2017. doi:10.1088/1361-648X/aa680e.

[POT_LSA+00]

Thomas J Lenosky, Babak Sadigh, Eduardo Alonso, Vasily V Bulatov, Tomas Diaz De La Rubia, Jeongnim Kim, Arthur F Voter, and Joel D Kress. Highly optimized empirical potential model of silicon. Modelling and Simulation in Materials Science and Engineering, 8(6):825–841, November 2000. doi:10.1088/0965-0393/8/6/305.

[POT_NWBR20]

Frank Neese, Frank Wennmohs, Ute Becker, and Christoph Riplinger. The ORCA quantum chemistry program package. The Journal of Chemical Physics, 152(22):224108, June 2020. doi:10.1063/5.0004608.

[POT_Pli95]

Steve Plimpton. Fast Parallel Algorithms for Short-Range Molecular Dynamics. Journal of Computational Physics, 117(1):1–19, March 1995. doi:10.1006/jcph.1995.1039.

[POT_SW85]

Frank H. Stillinger and Thomas A. Weber. Computer simulation of local order in condensed phases of silicon. Physical Review B, 31(8):5262–5271, April 1985. doi:10.1103/PhysRevB.31.5262.

[POT_Ter88]

J. Tersoff. Empirical interatomic potential for silicon with improved elastic properties. Physical Review B, 38(14):9902–9905, November 1988. doi:10.1103/PhysRevB.38.9902.

[POT_TAB+22]

Aidan P. Thompson, H. Metin Aktulga, Richard Berger, Dan S. Bolintineanu, W. Michael Brown, Paul S. Crozier, Pieter J. In 'T Veld, Axel Kohlmeyer, Stan G. Moore, Trung Dac Nguyen, Ray Shan, Mark J. Stevens, Julien Tranchida, Christian Trott, and Steven J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Computer Physics Communications, 271:108171, February 2022. doi:10.1016/j.cpc.2021.108171.

[POT_teVeldeBB+01]

G. te Velde, F. M. Bickelhaupt, E. J. Baerends, C. Fonseca Guerra, S. J. A. van Gisbergen, J. G. Snijders, and T. Ziegler. Chemistry with ADF. Journal of Computational Chemistry, 22(9):931–967, 2001. doi:10.1002/jcc.1056.