Official Resources
- Homepage: https://openmd.org/
- Documentation: https://openmd.org/documentation/
- Source Repository: https://github.com/OpenMD/OpenMD
- License: BSD 3-Clause License
Overview
OpenMD is an open source molecular dynamics engine written in C++ that is designed to simulate liquids, proteins, nanoparticles, interfaces, and other complex systems. It focuses on versatility and ease of use, with a particular emphasis on handling non-standard potentials and rigid body dynamics.
Scientific domain: Molecular dynamics, soft matter, metallic nanoparticles, interfaces
Target user community: Physical chemists, materials scientists
Theoretical Methods
- Classical Molecular Dynamics (NVE, NVT, NPT)
- Rigid Body Dynamics (quaternions)
- Electrostatics (SPME, damped shifted force)
- Minimization (SD, CG)
- Z-constraint methods (for free energy profiles)
- Thermodynamic Integration
- Langevin Hull method (NPT)
Capabilities (CRITICAL)
- Simulation of atomistic and rigid-body systems
- Embedded Atom Method (EAM) for metals
- Transition metal oxides and water
- Nanoparticle simulations (melting, interfaces)
- Slab geometry electrostatics
- Fluctuating charge models (EAM-µ, electronegativity equalization)
- Restraints and external fields
- Parallel execution (MPI)
Sources: OpenMD website, J. Chem. Phys. 124, 024109 (2006)
Key Strengths
Rigid Bodies:
- Quaternion dynamics
- Efficient for rigid molecules
- Coarse-grained models
Metals:
- EAM potentials
- Fluctuating charge
- Nanoparticle simulations
Simplicity:
- All-in-one input format
- Self-contained
- Good documentation
Inputs & Outputs
- Input formats: .omd file (XML-like structure + coordinates)
- Output data types: .dump (trajectory), .stat (thermodynamics), .eor (end of run)
Interfaces & Ecosystem
- Python: Analysis scripts
- VMD: Visualization support
- Standalone: All-in-one input format
Workflow and Usage
- Create
.omd file: Contains force field, topology, and initial coordinates
- Run simulation:
openmd system.omd
- Convert output:
Dump2XYZ or Dump2PDB
- Analysis:
StaticProps, DynamicProps tools
Performance Characteristics
- Good scaling on moderate clusters
- Specialized for rigid bodies and metals
- Not as ultra-optimized as GROMACS for biomolecules but efficient for general chemistry
Computational Cost
- Good for medium systems
- Efficient rigid body dynamics
- MPI parallelization
- Overall: Efficient for specialty applications
Best Practices
- Use appropriate ensemble
- Validate EAM parameters
- Check rigid body constraints
- Use analysis tools provided
Limitations & Known Constraints
- Smaller community than major codes
- Less optimized than GROMACS/LAMMPS
- Limited GPU support
- Niche applications
Application Areas
- Metallic nanoparticles and alloys
- Lipid bilayers
- Water interfaces
- Zeolites and minerals
- Ionic liquids
Comparison with Other Codes
- vs LAMMPS: OpenMD better rigid bodies, LAMMPS more general
- vs GROMACS: OpenMD metals/nanoparticles, GROMACS biomolecular
- Unique strength: Rigid body dynamics, metallic nanoparticles, fluctuating charge
Community and Support
- Open-source (BSD)
- Developed at University of Notre Dame (Gezelter group)
- Mailing list and issue tracker
Verification & Sources
Primary sources:
- Homepage: https://openmd.org/
- GitHub: https://github.com/OpenMD/OpenMD
- Publication: M. A. Meineke et al., J. Comput. Chem. 26, 252 (2005)
Secondary sources:
- OpenMD documentation
- Gezelter group publications
- Nanoparticle simulation applications
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Website: ACTIVE
- Documentation: COMPREHENSIVE
- Source: OPEN (GitHub)
- Development: ACTIVE (Notre Dame)
- Applications: MD, rigid bodies, metals, fluctuating charge