Computational Chemistry
Copper adatom trajectory on Cu(100) surface

Copper Adatom Diffusion on Cu(100): LAMMPS Simulation

Watch copper atoms move across a crystal surface in this molecular dynamics simulation. This video demonstrates surface diffusion mechanisms important for understanding catalysis and crystal growth processes.

Computational Chemistry
Ball model representation of a crystal surface with steps, kinks, adatoms, and vacancies showing various surface features

LAMMPS Tutorial: Copper and Platinum Adatom Diffusion

Step-by-step LAMMPS tutorial for simulating copper and platinum adatom diffusion. Learn surface dynamics simulation, trajectory analysis, and how atomic mass affects diffusion for machine learning datasets.

Computational Chemistry
Adatom surface diffusion trajectory on FCC metal surface

Platinum Adatom Diffusion on Pt(100): LAMMPS Simulation

Visualize platinum atom diffusion on crystal surfaces in this LAMMPS molecular dynamics simulation. Understand surface mobility mechanisms crucial for catalysis and materials design.

Scientific Computing
Energy conservation plot showing kinetic, potential, and total energy oscillations for a copper adatom diffusion simulation

Automated Adatom Diffusion Workflow

A complete input-to-analysis workflow for simulating adatom diffusion on FCC metal surfaces using LAMMPS and EAM potentials, providing comparative datasets for copper and platinum that demonstrate how atomic mass and bonding strength affect surface dynamics, with automated Python analysis generating publication-ready visualizations.

Computational Biology
Molecular visualization of a methionine dipeptide structure from MD simulation

Generating Mini-Protein Trajectories with GROMACS

A practical guide to simulating mini-proteins using GROMACS; from alanine dipeptide to tryptophan systems for ML training data generation.

Computational Biology
Molecular visualization of a methionine dipeptide structure from MD simulation

Mini-Protein Trajectory Generation

An automated GROMACS pipeline for generating high-fidelity molecular dynamics datasets suitable for machine learning, simulating capped dipeptides across nine residue types with 0.1 ps resolution and atomic force extraction optimized for training Neural Network Potentials.