Density Functional Theory (DFT) Course: From Theory to Practice

Visualization of electron density and electronic structure in Density Functional Theory

Density Functional Theory (DFT) is one of the most powerful theoretical frameworks for studying the electronic structure of atoms, molecules, and solids. It is widely used in condensed matter physics, quantum chemistry, and computational materials science to accurately predict the structural, electronic, magnetic, and optical properties of complex materials.

Course Syllabus

This course bridges the gap between rigorous quantum mechanical theory and state-of-the-art computational materials science. You will move systematically from fundamental equations to running real-world software applications.

Part I: Foundation

Starting from the quantum many-body problem, we detail the exact mathematical proofs and approximations required for real-world materials modeling.

  • Introduction
  • Hohenberg-Kohn Theorem
  • Kohn-Sham Equations
  • Exchange-Correlation Functionals
  • Basis Sets
  • Spin-Dependent DFT
  • DFT+U

Part II: Implementation

Theoretical knowledge is only half the battle. The second half of the course opens the black box of industry-standard DFT simulation codes, translating continuous mathematics into robust iterative algorithms.

  • Self-Consistent Field (SCF) Convergence
  • Brillouin Zone Integration
  • Eigenvalue Solvers

Meet Your Instructor

Rudra Banerjee

Prerequisites

Participants should be familiar with:

  • Basic Quantum Mechanics
  • Thermodynamics and Statistical Mechanics
  • Solid State Physics
  • Elementary linear algebra and differential equations

Course Objectives

By the end of this course, participants will be able to:

  • Understand the deep theoretical foundations of Density Functional Theory (DFT).
  • Explain the derivation and significance of the Hohenberg–Kohn and Kohn–Sham formalisms.
  • Select the appropriate exchange–correlation functionals for specific material properties.
  • Perform, troubleshoot, and analyze hands-on DFT calculations using modern software.
  • Apply advanced computational extensions such as DFT+U and time-dependent DFT (TDDFT).

Target Audience

This computational physics course is designed for:

  • Graduate students and postdocs in Physics, Chemistry, and Materials Science.
  • Experimental researchers entering the field of computational materials modeling.
  • Anyone interested in mastering electronic structure theory.

Rudra Banerjee
Rudra Banerjee
Assistant Professor, Computational Condensed Matter

Computational physicist exploring energy and quantum materials through DFT, Monte Carlo, and machine learning methods.