Computational Materials Science

Teacher

Dr. Subrata Sarangi

Category

Core Courses

Course Attendees

Still no participant

Course Reviews

Still no reviews

Computational Materials Science

Code(Credit) : CUTM1409(2-2-0)

Course Objectives

  • Expose the students to the challenges in the analyses of materials and how to address those challenges
  • Impart practice of developing Toy Models of Molecular Dynamics, Hartree Fock and Density Functional Theory in Python for small scale systems using various Pseudo-Potentials
  • Hands-on training on open source tools in Molecular Dynamics (LAMMPS) and Hartree-Fock and Density Functional Theory (Quantum Espresso); Data Visualization Tools like OVITO and VMD  

Learning Outcomes

A student who completes this course should be able to:

  • Get an idea of the issues and challenges involved in calculations of atomic, molecular and bulk properties of materials and how to approach their resolution using open source classical and quantum mechanical tools.
  • Code and execute concepts of Molecular Dynamics, Monte Carlo Methods in Molecular Dynamics and derive thermodynamic properties of materials ensuing from Classical Statistical Mechanics
  • Code and execute concepts of Hartree Fock Theory and Density Functional Theory using Python and derive various molecular and bulk material properties ensuing from electronic structure calculations involving Quantum Mechanics and Quantum Statistics
  • Use open source software like LAMMPS, Quantum Espresso, OVITO and VMD for analysis and visualization of various types of materials and their properties

Course Syllabus

Module-I

Models of Molecular Interactions:

Model Van der Waals interaction potentials between neutral atoms and molecules: The Lennard-Jones potential, Other Van der Waals Interactions: the Buckingham Potential, the Stockmayer Potential

Practice (1 hour sessions):

  1. Understanding the Lennard-Jones (LJ) Potential and its Parameters 
  2. Python simulation of Equation of State of Ideal Gases using LJ Interaction
  3. Python simulations of Equation of State of Ideal Gases with Buckingham and Stockmayer Potentials

Module-2

Molecular Dynamics

Molecular Dynamics theory and numerical implementation, Statistical Ensembles and Molecular Dynamics, Diffusion and Osmosis.

Practice (1 hour sessions):

4. Thermodynamics of a Real Gas using LJ potential using Python

5. Introduction to Molecular Dynamics in LAMMPS; Visualization using OVITO & VMD 

6. Simulation of Diffusion in LAMMPS 

7. Simulation of Osmosis using LAMMPS  

Module-3

Monte Carlo Methods 

Monte Carlo Simulations, Metropolis algorithm,  2D Ising Model and its simulation, Phase Transitions, Monte Carlo Grand Canonical (MCGC) simulation of Lennard Jones (LJ) Fluid Flow and Heat Transfer

Practice (1 hour sessions):

8. Introduction to Monte-Carlo-Metropolis Algorithm: Python Implementation

9. Simulation of 2D-Ising Model using Monte-Carlo-Metropolis algorithm

10. Simulation 0f Phase Transitions Using LAMMPS

11. Simulation of Lennard-Jones (LJ) Fluid Flow Using LAMMPS

12. Thermal Conductivity and Viscosity simulation using LAMMPS

Module-4

Hartree Fock Methods:

The Variational Principle, The Hartree Approximation, The Hartree-Fock Approximation, Electron Density Distribution in Many-Electron atoms and simple Di-atomic molecules, Beyond HF Theory: Coupled Cluster Approximation

Practice: (1 hour)

13. Introduction to Hartree Fock Implementation in Python

14. Creation of data files and running the HF code

15. Electron Density Distribution in H, He, Li atoms

16. Electron Density Distribution in simple diatomic molecules: H2, N2, O2, CO

Module-5

Density Functional Theory-I

Introduction to Density Functional Theory, The Hohenberg-Kohn Theorems, The Kohn-Sham Theory, Numerical Implementation

Module-6

Extensions of Density Functional Theory

The Local Density Approximation (LDA), The Generalized Gradient Approxiamtion (GGA) , Meta GGA, Adiabatic Connctions-Hybrid Orbitals, Perdew–Burke-Ernzerhof (PBE) Approximation, the Born-Oppenheimer Molecular Dynamics (BOMD), the Car-Parrinello Molecular Dynamics (CPMD)

 Module-7

Designing Materials with Quantum Espresso

Introduction to Quantum Espresso: Modules and Possibilities

Practice (1 hour sessions)

17. Introduction to Quantum Espresso software: Implementation of DFT

18. Loading Data Files and Execution of Quantum Espresso; Interpretation of Output

19. Ground State Electron Density Distributions in C, N, O using LDA

20. Ground State Electron Density Distribution in C, N, O, Si using GGA, Meta GGA, PBE

21. Ground State Properties of Simple Molecules like N2, O2, H2O, CO2 

22. Material Property Simulations in DFT with LDA/GGA/Meta GGA/PBE and their various combinations

23. Liquid-Gas Phase Transition Simulations in Born-Oppenheimer  Molecular Dynamics

24. Liquid-Gas Phase Transition Simulations in Car-Parrinello Molecular Dynamics

Text Books:

  1. Introduction to Computational Materials Science, Richard LeSar, (Cambridge University Press, 2016).
  2. Modern Quantum Chemistry: Introduction to Advanced Electronic Structure Theory. Attila Szabo, Neil S Ostlund. (Dover Publications Inc. 1996)

Reference Books and Online Materials:

  1. Computational Materials Science: An Introduction. June Gunn Lee, (CRC Press, 2011)
  2. For detailed calculation of van der Waals's forces/ Lennard-Jones Potential: https://www.youtube.com/watch?v=SntXBOUj5AE
  3. Modeling materials using density functional theory. John R Kitchin. http://kitchingroup.cheme.cmu.edu/dft-book/dft.html
  4. Practical Introduction to Hartree-Fock Algorithm using Python. Laksh, https://medium.com/analytics-vidhya/practical-introduction-to-hartree-fock-448fc64c107b
  5. LAMMPS Tutorial. (A set of 13 Videos Distributed by Wanying Pang). https://www.youtube.com/watch?v=GXA2PyqKYdY&list=PLhjeNfGGtHcNRKdDn6iVxWGSVa4iqtW_Q
  6. Tutorial on Diffusion, Calculation of Diffusivity..:  https://www.youtube.com/watch?v=k-vzqUBYF8k
  7. Tutorial on Monte Carlo Simulation: https://www.youtube.com/watch?v=GMCFVEfupDA
  8. Molecular Dynamics simulation of Carbon Nanotubes in water: https://www.youtube.com/watch?v=9GbjlSqY4Vk
  9. Ab-initio Green-Kubo Simulation of Thermal Transport in Liquids and Glasses. https://www.youtube.com/watch?v=9OkBHoZLBYg
  10. Introduction to Density Functional Theory. Nicola Marzari.https://www.youtube.com/watch?v=kYxOWYWxYcQ

Session Plan

Session 1

Model Van der Waals interaction potentials between neutral atoms and molecules: The Lenard Jones potential

https://www.youtube.com/watch?v=cERb1d6J4-M

https://www.youtube.com/watch?v=Wl5QHeS2UXE

https://www.youtube.com/watch?v=c3g3maYegBk

Session 3

Practice-1 (1 Hour):

Understanding the Lennard-Jones (LJ) Potential and its Parameters

https://www.youtube.com/watch?v=QWF0ES9Mo_Y&t=299s

Session 4

Practice-2 (1 Hour):

Simulation of Equation of State of Ideal Gas using LJ Interaction

Session 5

Session 7

Practice-4 (1 Hour) :

Thermodynamics of a Real Gas using LJ potential using Python

https://www.youtube.com/watch?v=-mZAsdJnnMM

Session 10

Molecular Dynamics simulations of (i) Diffusion (ii) Osmosis 

https://www.youtube.com/watch?v=iaMlAi1LN4M

https://www.youtube.com/watch?v=JnIkGtkO-Js

Session 11

Practice-6 (1 Hour):

Simulation of Diffusion in LAMMPS 

https://www.youtube.com/watch?v=AjdFNrUBD1c

Session 12

Practice-7 (1 Hour):

Simulation of Osmosis using LAMMPS

https://www.youtube.com/watch?v=OylJ58r0X8g

Session 13

Monte Carlo Simulations of MD: Theoretical aspects and numerical implementation

https://www.youtube.com/watch?v=mW9Tbdp1yCs

Session 14

The Metropolis algorithm in Monte Carlo Simulations: Theoretical aspects and numerical implementation

https://www.youtube.com/watch?v=mLXkTVDDpzs

https://www.youtube.com/watch?v=xVvUFB5Hk-g

Session 15

The 2D Ising Model and its simulation

https://www.youtube.com/watch?v=rN7g4gzO2sk

Session 16

Practice-8 (1 Hour):

Introduction to Monte-Carlo-Metropolis Algorithm: Python Implementation

https://www.youtube.com/watch?v=C_Ta9k_sUG8

Session 17

Practice-9 (1 Hour):

Simulation of 2D-Ising Model using Monte-Carlo-Metropolis algorithm

https://www.youtube.com/watch?v=kvf7aUPZCWk

https://www.youtube.com/watch?v=LOzcSuw3yOY

Session 18

Session 19

Practice-10 (1 Hour):

Simulations of Phase Transitions in LAMMPS

https://www.youtube.com/watch?v=MOeWvDfthbY&t=1040s

Session 20

Monte Carlo Grand Canonical (MCGC) simulation of Heat Transfer

https://www.youtube.com/watch?v=S-tZsXWj3aA

Session 21

Monte Carlo Grand Canonical (MCGC) simulation of Lennard-Jones (LJ) Fluid Flow

https://www.youtube.com/watch?v=vSmq2IjktYA

Session 22

Practice-11 (1 Hour):

MCGC simulation of Lennard-Jones (LJ) Fluid Flow in LAMMPS

Session 23

Practice-12 (1 Hour):

Thermal Conductivity and Viscosity simulation using LAMMPS

Session 24

The Variational Principle, The Hartree Approximation: Theoretical aspects and numerical implementation

https://www.youtube.com/watch?v=1yE8ls1X5Cw

https://www.youtube.com/results?search_query=hartree+method

Session 26

The Electron Density Distribution in Many-electron atoms: Using Hartee and Hartree-Fock Approximations; Beyond HF theory: Coupled Cluster Approximation

https://www.youtube.com/watch?v=ckc9cBMksUQ

https://www.youtube.com/watch?v=5LgGkrs4mjE&t=317s

https://www.youtube.com/watch?v=CFojijUelt8

Session 27

Practice-13 (1 Hour):

Introduction to Hartree Fock Implementation in Python

https://medium.com/analytics-vidhya/practical-introduction-to-hartree-fock-448fc64c107b

Session 28

Practice-14 (1 Hour):

Creation of data files and running the HF code

Session 29

Practice-15 (1 Hour):

Electron Density Distribution in H, He, Li atoms

https://www.youtube.com/watch?v=AXAcM-j9I-U

https://www.youtube.com/watch?v=5BZxa6fZHZU

Session 30

Practice-16 (1 Hour):

Electron Density Distribution in simple diatomic molecules: H2, N2, O2, CO

Session 32

Numerical implementation aspects of the DFT, the Local Density Approximation (LDA)

https://www.youtube.com/watch?v=gk6HAl7OmU&list=PLkNVwyLvX_TFBLHCvApmvafqqQUHb6JwF&index=29

Session 34

The  Perdew–Burke-Ernzerhof (PBE) Approximation, the Born-Oppenheimer Molecular Dynamics (BOMD) and the Car-Parrinello Molecular Dynamics (CPMD)

https://www.youtube.com/watch?v=DPTJaQnu4oI

https://www.youtube.com/watch?v=ffezEHeJnmk

https://www.youtube.com/watch?v=8Fdy1OcyLTA

Session 35

Session 36

Possibilities with the Quantum Espresso

https://www.youtube.com/watch?v=PHvgGL_980A

Session 37

Practice-17 (1 Hour):

Introduction to Quantum Espresso software: Implementation of DFT

https://www.youtube.com/watch?v=mQ1D3tXWqD4

Session 38

Practice-18 (1 Hour):

Loading Data Files and Execution of Quantum Espresso; Interpretation of Output

Session 39

Practice-19 (1 Hour):

Ground State Electron Density Distributions in C, N, O using LDA

https://www.youtube.com/watch?v=FrY8Sj0zUus

https://www.youtube.com/watch?v=FrY8Sj0zUus

Session 40

Practice-20 (1 Hour):

Ground State Electron Density Distributions in C, N, O using GGA, Meta GGA and PBE

Session 41

Practice-21 (1 Hour):

Ground State Properties of Simple Molecules like N2, O2, H2O, CO2

Session 42

Practice-22 (1 Hour):

Material Property Simulations in DFT with LDA/GGA/Meta GGA/PBE and their various combinations

Session 43

Practice-23 (1 Hour):

Liquid-Gas Phase Transition Simulations in Born-Oppenheimer  Molecular Dynamics

https://www.youtube.com/watch?v=jhhi7xbq3Jc

Session 44

Practice-24 (1 Hour):

Liquid-Gas Phase Transition Simulations in Car-Parrinello Molecular Dynamics

Case Studies

Case Studies

Our Main Teachers

Dr. Subrata Sarangi has a Masters’ Degree in Physics from IIT, Kanpur and a Ph.D in Nuclear Structure Theory from Physical Research Laboratory, Ahmedabad. He has 25 years’ experience in teaching at UG, PG and PhD levels. He has published over 20 peer reviewed research articles in areas of Atomic Nuclei, Nuclear Matter, Materials Sciences […]