Computational Chemistry: Concepts, Theories And Applications

Ab initio methods, Density Functional Theory methods

What you'll learn

Understanding the undelying theories of various computational methods such as ab initio, density functioanl theory, semi-empirical and molecular mechanics

Understanding the difference between wave function and density based methods in computational chemistry and their pros and cons

Understanding the cost and accuracy of various methods and basis sets

Learn to apply effective and time saving approaches to solve chemical problem with high accuracy and minimum cost (time)

Gain knowledge of different resources/databases useful for theoretical chemist

Requirements

Some knowledge of mathematics is needed as the course contains several equations

Description

Computational Chemistry involves application of numerical methods for solving the problems related to chemical systems. Mastering in computational chemistry involves not only hands on practice of Computational software, but also requires understanding the underlying theory, computational methods and approaches to solve chemical problems. In this course, students will learn the theoretical framework of computational chemistry methods necessary for understanding of methods. Practical understanding of the strengths, weaknesses, and ranges of applicability of different methods is also presented in this course. This knowledge will allow for the critical evaluation of the validity and accuracy of results and of the conclusions derived from the computational chemistry modelling of chemical problems. Finally, description of a few properties is also given which will give students an idea like how the properties are calculated through computational tools.The following topics will be discussed in this course:· Potential Energy Surface· Minima and Saddle Points· Thermodynamics and Normal Mode Analysis· Schrodinger Wave Equation· Molecular Hamiltonian and Born-Oppenheimer Approximation· Hartree-Fock Method· Post Hartree-Fock Methods· Static and Dynamic Correlation· Density Functional Theory· Basis Functions and Basis Sets· Excited States· Restricted and Open Shell Systems· Cost and Accuracy· Strategies to Reduce Cost of Computational methods· Molecular Mechanics· Semi-Empirical Methods· Properties Calculations

Overview

Section 1: Introduction

Lecture 1 Introduction of the course, computational chemistry methods

Section 2: Potential energy surface (PES)

Lecture 2 PES of N2 molecule and ozone

Lecture 3 Hypersurface

Section 3: Minima and Saddle points

Lecture 4 Newton Raphson Method

Lecture 5 Finding and characterizing stationary points

Section 4: Nomal mode anlysis, thermal correction to energies

Lecture 6 Normal mode analysis

Lecture 7 Partition functions

Lecture 8 different partition functions in energy and entropy

Section 5: Schordinger Equation and postulates of quantum mechanics

Lecture 9 Postulates of quantum Mechanics

Section 6: Molecular Hamiltonian and Born-Oppenheimer Approximation

Lecture 10 Molecular Hamiltonian and Born-Oppenheimer Approximation

Lecture 11 Many body problem and Variational approach

Section 7: Hartree Fock Method

Lecture 12 Contruction and optimization of trial wavefunction, Overlap and Resonance Integ

Lecture 13 Hartree Product, constraints of trial wavefunction

Lecture 14 Slater determinent wavefunction and Hartree Fock calculations

Lecture 15 Hartree Fock Energy

Lecture 16 SCF Procedure and Hartree Fock equation

Section 8: Static and Dynamic correlation, and Post Hartree Fock Methods

Lecture 17 Dynamic correlation and multideterminent wavefunction

Lecture 18 Perturbation Theory part 1

Lecture 19 Perturbation theory Part II, advantages and disadvantages

Lecture 20 Coupled Cluster post HF methods

Lecture 21 Static Correlation and Methods to capture Static Correlation

Section 9: Density Functional Theory

Lecture 22 DFT basic and the fundamental theorems such as Hohenberg-Kohn, Thomas Fermi

Lecture 23 Kohn Shame Theorem of DFT

Lecture 24 Exchange Correlation Functionals

Lecture 25 Classes of DFT methods and their functionals

Section 10: Basis set and Basis function

Lecture 26 Basis function

Lecture 27 Basis set

Lecture 28 Types of basis set and polarization function

Lecture 29 Diffuse functions, and the choice of basis sets

Lecture 30 plane wave basis sets

Section 11: Cost and Accuracy

Lecture 31 Cost and accuracy of methods

Lecture 32 Errors in geometries and energies of different methods

Lecture 33 Strategies to reduce computational cost

Lecture 34 solvation models and their associated costs

Lecture 35 Multilayer method

Section 12: Excited states

Lecture 36 Configuration Interaction singles

Lecture 37 Time dependent DFT

Section 13: Force Field methods

Lecture 38 Force Fields overview

Lecture 39 Bond stretching terms in force fields

Lecture 40 Bending, Torsion and non-bonding terms.

Lecture 41 steps in Force fields

Section 14: Semi-empirical methods

Lecture 42 Semi-empirical methods Huckel Theory

Lecture 43 Complete Neglet of Differential Overlap (CNDO)

Lecture 44 Intermediate Neglect of Differential Overlap and NNDO

Section 15: Properties Calculations

Lecture 45 Properties and Natural Bonding Orbitals

Lecture 46 Multipole moments and Molecular Electrostatic Potential

Lecture 47 IR and Raman spectra

Lecture 48 UV-Vis and NMR spectra

All those scientists who intend to learn/apply quantum mechanis or molecular mechanics based methods to their research