About the Density Functional Theory Course
Program Highlights
Course Curriculum
Module 1: Day 1 – Introduction & DFT Fundamentals
- Explore MXene basics and their role in EV batteries
- Grasp core DFT theory and electronic‑structure prediction
- Set up a DFT environment and run a simple MXene cell calculation
Module 2: Day 2 – Advanced DFT Modeling & MXene Heterostructures
- Construct and optimise MXene heterostructures
- Analyse band structures, DOS, and charge‑density maps
- Predict intercalation potentials and ion‑diffusion pathways
Module 3: Day 3 – Application, Analysis & Optimization
- Screen MXene candidates for high‑energy EV storage
- Perform defect engineering and capacity prediction
- Integrate computational results with experimental/industry data and explore emerging design trends
Tools, Techniques, or Platforms Covered
Quantum ESPRESSO
Gaussian
VESTA
XCrySDen
Python
Matplotlib
NumPy
Pandas
HPC clusters
Real-World Applications
- Apply Density Functional Theory Modeling of MXene Heterostructures for EV Battery Materials skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical materials science competencies
- Solve industry-relevant problems using Density Functional Theory Modeling of MXene Heterostructures for EV Battery Materials methodologies and tools
- Contribute to open-source projects and collaborative research in materials science
- Prepare for competitive examinations, interviews, and professional certifications in materials science
Who Should Attend & Prerequisites
- Industry‑recognized e‑Certification + e‑Marksheet from NSTC
- Hands‑on training with practical projects and real‑world EV battery datasets
- Dedicated expert mentorship and doubt‑resolution sessions
Prerequisites:







