Introduction to computational chemistry, method, tools, and applications

 Computational Chemistry (Introduction)

Computational chemistry is a branch of chemistry that uses computer simulations, mathematical models and theoretical chemistry methods to study the structure, properties, and reactions of molecules. Instead of doing experiments only in laboratories, scientists use computers to predict molecular behavior, energies, and reaction mechanisms.

Or

Computational chemistry applies quantum mechanics, molecular mechanics, and statistical methods using computers to understand the chemical environment.

Why is it used?

It helps to:

·         Predict molecular structures

·         Calculate energy, stability, and reactivity

·         Study reaction mechanisms

·         Predict spectra (IR, UV-Vis, NMR)

·         Design new drugs and materials

·         Study solar cells, batteries, catalysts, etc.

Main Methods used in Computational Chemistry

1.      Quantum Mechanics (QM) Methods

Ø  Study electronic structure.

Ø  Examples: DFT, Hartree–Fock, post-HF methods.

Ø  Used for accurate molecular properties.

2.      Molecular Mechanics (MM)

Ø  Uses classical physics.

Ø  Suitable for large molecules like proteins.

Ø  Faster but less detailed electronically.

3.      Molecular Dynamics (MD)

Ø  Simulates motion of atoms over time.

Scope of computational chemistry

·         Predicting molecular structures and stability

·         Studying reaction mechanisms

·         Calculating energies and spectra

·         Designing drugs and new materials

·         Studying biological and material systems

It helps save time, cost, and experimental effort by predicting results before experiments are performed.

Common Software

Examples include:

·         Gaussian

·         MultiWFN

·         PyMolyZe

·         Autodock Vina

·         ORCA

·         VASP

Common Applications

·         Drug design and docking studies

·         Organic solar cell materials

·         Catalysis

·         Battery materials

·         Nanomaterials

·         Protein–ligand interactions