Density Functional Theory

Density Functional Theory (DFT) is a computational quantum mechanical modeling method used in physics, chemistry, and materials science to investigate the electronic structure of many-body systems, particularly atoms, molecules, and condensed phases. It approximates the complex many-electron wavefunction with the electron density, significantly reducing computational cost while providing accurate predictions of properties like energy, structure, and reactivity. DFT is widely applied in materials design, drug discovery, and catalysis research.

Also known as: DFT, Density Functional Theory (DFT), Density Functional, DFT method, Kohn-Sham DFT

Why learn Density Functional Theory?

Developers should learn DFT when working in computational chemistry, materials science, or quantum physics simulations, as it enables efficient prediction of molecular and material properties without solving the full Schrödinger equation. It is essential for tasks like designing new materials, optimizing chemical reactions, or modeling electronic devices, offering a balance between accuracy and computational feasibility compared to more expensive methods like coupled cluster theory.

Learning Resources

• docs: DFT Wiki
• video: Introduction to DFT by Kieron Burke
• course: Practical DFT Course on Coursera
• book: DFT in Materials Science - Book by Richard M. Martin