Download Computational Chemistry: Concepts, Theories and Applications 2024
Computational Chemistry: Concepts, Theories and Applications video course download, Ab initio methods, Density Functional Theory methods. Computational Chemistry involves application of numerical methods for solving the problems related to chemical systems. Master’s 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.
- 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
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
Course content
- 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
Course details
- Video quality: MP4 | Video: h264, 1280 × 720
- Audio quality: Audio: AAC, 44.1 KHz, 2 Ch
- Last updated 10/2024
- Video duration: 13h 18m
- Number of lessons: 15 sections, 48 lectures
- Language: Language: English
- Compressed file size: 2.5 GB
