About Workshop
This workshop introduces Molecular Dynamics (MD) simulations for studying material behavior at the atomic scale. Participants will learn how to build simulation systems, select suitable force fields, run tensile and thermal simulations, visualize atomic structures, and extract engineering properties such as thermal conductivity, Young’s modulus, yield strength, and stress-strain behavior using open-source tools.
Aim
To provide practical training in MD simulation workflows using LAMMPS, GROMACS, OVITO, PACKMOL, VMD, Avogadro, and Python for predicting mechanical and thermal properties of materials.
What Participants Will Learn
- Understand MD fundamentals, ensembles, boundary conditions, and force fields.
- Build and simulate CNTs, polymers, and metallic alloy systems.
- Run tensile deformation and thermal conductivity simulations.
- Analyze atomic trajectories using OVITO and visualization tools.
- Extract stress-strain curves, heat flux data, and material property values using Python.
Structure
🗓️ Day 1: Foundations, System Building & Nanomaterials (CNTs)
Core Concepts:
- Introduction to MD fundamentals: thermodynamic ensembles such as NVT, NPT, NVE, and periodic boundary conditions.
- Force field selection criteria: AIREBO for carbon networks, EAM for alloys, and OPLS-AA for polymers.
- Structure generation workflows: creating perfect and defective Carbon Nanotubes (CNTs) using free open-source tools.
- Deciphering the input script: anatomy of a molecular dynamics run script.
💻 Hands-on Lab (Google Colab)
- Task: Run a mini-tensile strain simulation on a Single-Walled Carbon Nanotube (SWCNT) using LAMMPS.
- Deliverable: Generate and export a .lammpstrj trajectory file ready for structural deformation rendering in OVITO.
🗓️ Day 2: Polymers & Thermal Properties (GROMACS/LAMMPS)
Core Concepts:
- Amorphous structures: using PACKMOL to density-pack and build disordered polymer chains.
- Relaxation protocols: equilibrating high-density polymer matrices without system overlaps or explosive crashes.
- Thermal transport theory: understanding Green-Kubo relations versus Non-Equilibrium MD (NEMD) approaches.
- Calculating thermal conductivity (κ) across interfaces and bulk materials.
💻 Hands-on Lab (Google Colab)
- Task: Execute a thermal dissipation workflow to calculate the thermal conductivity of a material matrix.
- Deliverable: Write a Python parser to plot the heat flux autocorrelation function and extract the numerical thermal conductivity coefficient.
🗓️ Day 3: Alloys, Mechanical Testing & Publication Analysis
Core Concepts:
- Metallic alloys: implementing Embedded Atom Method (EAM) potentials for multi-element metal systems.
- Defect tracking: simulating grain boundaries, vacancies, and dislocation loops.
- Virtual mechanical testing: setting up algorithms for uniaxial tensile, compression, and shear testing.
- Data extraction: translating raw atomic data into engineering metrics such as Young’s Modulus, Yield Strength, and Ultimate Tensile Strength.
💻 Hands-on Lab (Google Colab)
- Task: Simulate a dynamic stress-strain deformation test on a metallic alloy crystal lattice.
- Deliverable: Auto-generate a publication-ready stress-strain curve directly from the raw simulation data logs using Python.
Important Dates
Registration Ends
07: 15 PM IST
Workshop Dates
18 September 2026
08:15 PM IST
08:15 PM IST
What You Will Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Outcomes
- Set up basic molecular dynamics simulation workflows.
- Generate CNT, polymer, and alloy material structures.
- Run LAMMPS/GROMACS simulations for mechanical and thermal studies.
- Visualize atomic deformation, defects, and structural changes using OVITO.
- Calculate thermal conductivity from simulation data.
- Extract stress-strain curves and mechanical property values.
- Create publication-ready plots using Python.
Who Should Attend
- Students from materials science, nanotechnology, mechanical engineering, chemical engineering, polymer science, and related fields.
- PhD scholars and researchers working in computational materials science, molecular simulations, nanomaterials, polymers, or alloys.
- Academicians and faculty members interested in MD simulation-based teaching and research.
- Industry professionals working in materials design, R&D, simulation, manufacturing, thermal analysis, or mechanical testing.
- Learners interested in using LAMMPS, GROMACS, OVITO, PACKMOL, VMD, Avogadro, and Python for material property prediction.
- Set up basic molecular dynamics simulation workflows.
- Generate CNT, polymer, and alloy material structures.
- Run LAMMPS/GROMACS simulations for mechanical and thermal studies.
- Visualize atomic deformation, defects, and structural changes using OVITO.
- Calculate thermal conductivity from simulation data.
- Extract stress-strain curves and mechanical property values.
- Create publication-ready plots using Python.