Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging ...from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.
Program Title: Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS)
CPC Library link to program files:https://doi.org/10.17632/cxbxs9btsv.1
Developer's repository link:https://github.com/lammps/lammps
Licensing provisions: GPLv2
Programming language: C++, Python, C, Fortran
Supplementary material:https://www.lammps.org
Nature of problem: Many science applications in physics, chemistry, materials science, and related fields require parallel, scalable, and efficient generation of long, stable classical particle dynamics trajectories. Within this common problem definition, there lies a great diversity of use cases, distinguished by different particle interaction models, external constraints, as well as timescales and lengthscales ranging from atomic to mesoscale to macroscopic.
Solution method: The LAMMPS code uses parallel spatial decomposition, distributed neighbor lists, and parallel FFTs for long-range Coulombic interactions 1. The time integration algorithm is based on the Størmer-Verlet symplectic integrator 2, which provides better stability than higher-order non-symplectic methods. In addition, LAMMPS supports a wide range of interatomic potentials, constraints, diagnostics, software interfaces, and pre- and post-processing features.
Additional comments including restrictions and unusual features: This paper serves as the definitive reference for the LAMMPS code.
1S. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117 (1995) 1–19.2L. Verlet, Computer experiments on classical fluids: I. Thermodynamical properties of Lennard–Jones molecules, Phys. Rev. 159 (1967) 98–103.
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•Moltemplate streamlines preparation of coarse-grained molecular dynamics simulations.•Moltemplate is designed to be as general as possible.•The moltemplate file format promotes ...validation and reproducibility of simulations.
Coarse-grained models have long been considered indispensable tools in the investigation of biomolecular dynamics and assembly. However, the process of simulating such models is arduous because unconventional force fields and particle attributes are often needed, and some systems are not in thermal equilibrium. Although modern molecular dynamics programs are highly adaptable, software designed for preparing all-atom simulations typically makes restrictive assumptions about the nature of the particles and the forces acting on them. Consequently, the use of coarse-grained models has remained challenging. Moltemplate is a file format for storing coarse-grained molecular models and the forces that act on them, as well as a program that converts moltemplate files into input files for LAMMPS, a popular molecular dynamics engine. Moltemplate has broad scope and an emphasis on generality. It accommodates new kinds of forces as they are developed for LAMMPS, making moltemplate a popular tool with thousands of users in computational chemistry, materials science, and structural biology. To demonstrate its wide functionality, we provide examples of using moltemplate to prepare simulations of fluids using many-body forces, coarse-grained organic semiconductors, and the motor-driven supercoiling and condensation of an entire bacterial chromosome.
We introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well ...as pre-processing and post-processing functions to prepare, execute and extract information from LAMMPS/VASP simulations. An overview of the program structure is provided. The current version contains modules to calculate elastic and mechanical properties such as lattice constant, cohesive energy, cold curve, elastic constants, bulk and shear modulus, volume conserving/non-conserving deformation path, vacancy/interstitial formation energy, surface energy, stacking fault energy, melting point, radial distribution function, and thermal expansion. These functionalities are demonstrated for different interatomic potentials and DFT calculations in Al.
Program title: LAVA
CPC Library link to program files:https://doi.org/10.17632/6grh8x4hgt.1
Licensing provisions: BSD 3-Clause License
Programming language: Python
Nature of problem: This program provides user-friendly and high throughput calculations for material properties via two widely-used LAMMPS and VASP code.
Solution method: LAVA can prepare the input scripts, extract, calculate and even plot the material properties from molecular dynamics simulations and density functional calculations together with bash and python scripts.
•An improved version of the FIRE algorithm is now implemented in LAMMPS.•The widely used FIRE algorithm requires a symplectic time integration scheme.•Default parameters are recommended to ensure ...optimal performance.•Its application is shown and discussed using multiple examples from materials science.
In atomistic simulations, pseudo-dynamical relaxation schemes often exhibit better performance and accuracy in finding local minima than line-search-based descent algorithms like steepest descent or conjugate gradient. Here, an improved version of the fast inertial relaxation engine (fire ) and its implementation within the open-source atomistic simulation code lammps is presented. It is shown that the correct choice of time integration scheme and minimization parameters is crucial for the performance of fire.
We describe a highly optimized implementation of MPI domain decomposition in a GPU-enabled, general-purpose molecular dynamics code, HOOMD-blue (Anderson and Glotzer, 2013). Our approach is inspired ...by a traditional CPU-based code, LAMMPS (Plimpton, 1995), but is implemented within a code that was designed for execution on GPUs from the start (Anderson et al., 2008). The software supports short-ranged pair force and bond force fields and achieves optimal GPU performance using an autotuning algorithm. We are able to demonstrate equivalent or superior scaling on up to 3375 GPUs in Lennard-Jones and dissipative particle dynamics (DPD) simulations of up to 108 million particles. GPUDirect RDMA capabilities in recent GPU generations provide better performance in full double precision calculations. For a representative polymer physics application, HOOMD-blue 1.0 provides an effective GPU vs. CPU node speed-up of 12.5×.
BackgroundExposure to high-intensity X-ray irradiation induces numerous defects in the thin films of optical components applied to X-ray free-electron laser (XFEL) facilities. These defects result in ...structural damage to the material and degradation of macroscopic properties, thereby affecting its service life and significantly compromising the reliability and stability of XFEL facilities.PurposeThis paper aims to design and implement an automated irradiation simulation software based on Python called automatic irradiation simulation based on LAMMPS (AISL) to support the simulation research of XFEL radiation damage to materials using molecular dynamics methods.MethodsAISL was designed to facilitate high-throughput automated studies on XFEL radiation damage by exploring the process of radiation-induced defects and promoting the accumulation of data for radiation-resistant materials. This software package established an automated workflow pipeline for simulation tasks, encompassing aspects such as batch submiss
Atomistic simulations are crucial for understanding material properties at the molecular level but are limited by high computational costs, especially for large, complex systems like bituminous ...materials. Our team developed a Force-matched United Atom (UA) Coarse Graining (CG) force field to enhance computational efficiency while retaining atomic detail. However, converting all-atom models to CG models is complex, requiring detailed atom-to-bead mapping and compatibility with molecular dynamics (MD) engines like LAMMPS. To address this, we introduce AA2UA, an open-source software that simplifies the conversion of PDB files into LAMMPS-readable structure topology files, facilitating broader use of the developed UA force field.
•AA2UA converts PDB files into their United Atom (UA) coarse-grained (CG) counterparts for use in molecular simulations.•It maps all-atom molecules using the force field bead types and masses described by our UA force field.•It generates structure.data files containing all the topologies necessary for execution with LAMMPS.•Self-contained and lightweight, it requires only Rdkit and standard Python libraries, making it well-suited for HPC environments.•Mapping rules, bead types, charges, and masses can be adjusted and expanded for various all-atom or coarser force fields.
Understanding the transport properties of the solid electrolyte interphase (SEI) is a critical piece in the development of lithium ion batteries (LIB) with better performance. We studied the lithium ...ion diffusivity in the main components of the SEI found in LIB with silicon anodes and performed classical molecular dynamics (MD) simulations on lithium fluoride (LiF), lithium oxide (Li2O) and lithium carbonate (Li2CO3) in order to provide insights and to calculate the diffusion coefficients of Li-ions at temperatures in the range of 250 K to 400 K, which is within the LIB operating temperature range. We find a slight increase in the diffusivity as the temperature increases and since diffusion is noticeable at high temperatures, Li-ion diffusion in the range of 1300 K to 1800 K was also studied and the diffusion mechanisms involved in each SEI compound were analyzed. We observed that the predominant mechanisms of Li-ion diffusion included vacancy assisted and knock-off diffusion in LiF, direct exchange in Li2O, and vacancy and knock-off in Li2CO3. Moreover, we also evaluated the effect of applied electric fields in the diffusion of Li-ions at room temperature.
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•MD simulation facilitates analysis of nanotribology to the atomic scale.•LAMMPS, AMBER, GROMACS, CHARMM, and GROMOS, are used for molecular analysis.•MD simulation is used to measure ...the interacting force of the molecules.•The script for nanoindentation provides guidance to the LAMMPS software.•MD simulations includes interfacial layer, nanoparticle’s plastic energy etc.
To improve the efficiency of a machinery component, it is necessary to enhance the quality of lubricants. Lubricants help to reduce the friction and wear between the two surfaces which are in relative motion. The study of friction and wear covers in the field of tribology. Recently tribological behavior has been studied in micro and nanoscale. Nanotribology deals with the study friction, adhesion, wear and lubrication of metal crystal, analyze dynamics and single asperity contacts during sliding, formation and propagation of voids, fracture and nucleation and motion of dislocations properties at atomic level and also study the interfacial properties between the two surfaces. The expensive nanotribological experimental studies and limited availability of experimental facility, motivates researchers to use simulation approach. Molecular Dynamic (MD) simulation facilitate to analysis at molecular level and nanoscale. Present review paper is elucidating the application of MD simulations in the field of Nanotribology. In addition, this study provides utter knowledge about the LAMMPS commands and also confabulate the capabilities of MD simulation in nanotribology area. This review paper is fully dedicated to all those readers who are fascinated to do research in field of nanotribology using molecular dynamics simulation in nanotribology with LAMMPS.
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