Series Overview
This practical series teaches molecular dynamics simulation using LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) through the lens of adatom diffusion—studying how individual atoms move across crystal surfaces. These simulations are fundamental to understanding catalysis, thin film growth, and surface chemistry.
What You’ll Learn
- LAMMPS fundamentals: Setting up simulations, choosing potentials, managing boundaries
- Surface science: Understanding adatoms, diffusion mechanisms, and thermal gradients
- Visualization techniques: Using Ovito for trajectory analysis and publication-quality figures
- Data analysis: Extracting meaningful patterns from atomic trajectories
- ML applications: How simulation data can train machine learning models
The Journey
Copper Adatom Diffusion introduces the complete LAMMPS workflow: from system setup through energy analysis and trajectory visualization. Copper provides an excellent starting point with well-studied parameters and moderate computational requirements.
Platinum Adatom Diffusion extends the framework to a different element, demonstrating how atomic properties affect surface dynamics. Platinum’s relevance to catalysis makes this particularly valuable for understanding real-world applications.
Practical Applications
These tutorials generate trajectory data useful for:
- Neural network potentials: Training ML models to replace expensive quantum calculations
- Rare event sampling: Using ML to identify and enhance diffusion pathways
- Catalyst design: Predicting how surface modifications affect reactivity
- Materials discovery: Screening new alloy compositions for desired properties
Future Directions
The series provides a foundation for more advanced topics:
- Mixed-metal surfaces and alloy effects
- Stepped surfaces and defect interactions
- Machine learning applications with the generated data
- Integration with quantum mechanical calculations
Perfect for graduate students, researchers, and practitioners interested in computational materials science, surface chemistry, or generating simulation data for potential machine learning applications.