*** Courses Taught at NJIT, USA ***
Spring 2021 : Thermodyanmics I (ME 311, S-004) : Total Students – 39
Fall 2020 : Thermodyanmics I (ME 311, S-001) : Total Students – 39
Spring 2020 : ME 618 – Special Topic (ST) Course :::: Atomistic and Molecular Simulations Methods in Mechanics and Materials Science ; Total Students – 30 ; Similar to Fall 208 course + Machine Learning
Fall 2019 : Thermodyanmics II (ME 312, S-004) : Total Students – 33
Spring 2019 : Thermodyanmics II (ME 312, S-004) : Total Students – 33
Fall 2018 : ME 618 – Special Topic (ST) Course :::: Atomistic and Molecular Simulations Methods in Mechanics and Materials Science ; Total Students – 10
The course covers the fundamental of Molecular Dynamics (MD), Kinetic Monte Carlo (KMC), Density Functional Theory (DFT), and Machine Learning (ML). In addition, there are many hands-on sessions on MD software LAMMPS and DFT software VASP.
Spring 2018 : Thermodyanmics II (ME 312, S-004) : Total Students – 42
Fall 2017 : Thermodynamics II (ME 312, S-001) : Total Students – 39
Spring 2017 : Thermodynamics II (ME 312, S-002) : Total Students – 41
Fall 2016 : Thermodynamics II (ME 312, S-001) : Total Students – 35
Courses Taught at Brown University, USA
Fall 2011 : Teaching Assistant for Advanced Mechanics of Solids (ENGN 175) (Instructor : Dr. K.-S. Kim)
Fall 2018: ME 618 – ST: Atomistic and Molecular Simulations Methods in Mechanics and Materials Science (AMSM3S)
* Week 1 *
Motivation for the Course
Why is this course very important? What will we learn? Examples of Molecular Simulations.
Review of the Fundamentals of Thermodynamics
Equilibrium and State Quantities – systems, phases, and state quantities; equilibrium and temperatures; pressure, work, and chemical potential; heat and heat capacity; The Laws of Thermodynamics – the zeroth law of thermodynamics, internal energy and the first law, entropy and the second law; Thermodynamic Potentials – free energy, enthalpy.
* Week 2 *
Review of the Fundamentals of Thermodynamics (Contd.)
Thermodynamic Potentials – the principle of maximum entropy, entropy and energy as thermodynamic potentials, maxwell relations, thermodynamic stability; Phase Transitions and Chemical Reactions – gibbs’ phase rule, phase equilibrium
Review of the Fundamentals of Statistical Mechanics
Number of Microstates Ω and Entropy S – foundations, phase space, statistical definition of entropy, quantum mechanical counting of Ω; Ensemble Theory and Microcanonical Ensemble- the microcanonical ensemble, entropy as an ensemble average; The Canonical Ensemble – calculation of observable as ensemble averages, connection between microcanonical and canonical ensembles.
* Week 3 *
Review of the Fundamentals of Statistical Mechanics (Contd.)
The Canonical Ensemble – virial theorem and equipartition theorem; Macrocanonical Ensemble – fluctuations in the macrocanonical ensemble
An Overview of Molecular Simulation – example of molecular simulations; fundamental components of molecular dynamics; newton’s equation of motion; a simple numerical integrator: verlet algorithm;Numerical Integrators – several versions of verlet algorithm; order of accuracy; other integrators; Perfect Crystal Structures – lattices and bases; miller indices.
* Week 4 *
Interatomic Interactions – why is it important? interatomic potential models; locality of interatomic interactions; computational cost of interatomic models; Energy minimization – why is it important? the steepest descent method; conjugate gradient relaxation; local and global minimization; Periodic Boundary Conditions – different boundary conditions; the importance of periodic boundary condition; Code – matlab code to make crystal structures; Application of MD in different fields – various problems in mechanics and materials science e.g. fracture, friction, nanofluidics, nanomedicine, environment, electronics, energy storage, etc.
* Week 5 *
Hands-on Session: MD software LAMMSP & visualization tool OVITO (Part I)
overview of LAMMPS; overview of OVITO visualization tool; shell-scripting; post-mortem of a simple LAMMPS script – MD for simple LJ (2D and 3D particles); coding to make 2D material graphene; analysis of LAMMPS script for graphene simulation.
* Week 6 *
Hands-on Session: MD software LAMMPS & visualization tool OVITO (Part II)
coding of bi- and multilayer graphene, LAMMPS script to compute bi- and multi-layer graphene (e.g. friction); coding of two-dimensional materials beyond graphene e.g. transition metal dichalcogenides (TMD); LAMMPS script for TMD; coding of graphene-TMD heterostructures; LAMMPS script of two-dimensional heterostructures.
* Week 7 *
Hands-on Session: MD software LAMMPS & visualization tool OVITO (Part III)
computation of pressure, diffusivity, and thermal conductivity using LAMMPS; indentation using LAMMPS; indentation of 2D materials using LAMMPS.
* Week 8 *
Monte Carlo Methods in Statistical Mechanics – theoretical background, algorithm; coding of MC methods; Monte Carlo methods in LAMMPS. Introduction to the Kinetic Monte Carlo Method (Part – I) – motivation: the time-scale problem; infrequent-event systems, state-to-state dynamics, and the KMC concept.
* Week 9 *
Introduction to the Kinetic Monte Carlo Method (Part – II) – The rate constant and first-order processes; The KMC procedure; determining the rates; the lattice assumption and the rate catalog; the low-barrier problem.
* Week 10 *
Hands-on Session: KMC Code in MATLAB
KMC code in MATLAB – Langmuir adsorption-desorption problem.
* Week 11 *
A Brief Introduction to Density Functional Theory (DFT)
elementary quantum mechanics – the Schrodinger equation, the variational principle, the Hartree-Fock approximation; the Kohn-Sham equations; the exchange-correlation functionals; the basic machinery of DFT – basis sets; DFT applications for various problems.
* Week 12 *
Hands-on Session: DFT software VASP & Visualization tool VESTA (Part I)
overview of VASP; example on graphene – writing direct and cartesian coordinates, optimization of KPOINTS and ENCUT.
* Week 13 *
Hands-on Session: DFT software VASP (Part II)
chemo-mechanics problem with DFT – evaluation of mechanical properties of materials with DFT (e.g., stress-strain response, elastic modulus, etc.)
* Week 14 *
Hands-on Session: DFT software VASP (Part III)
miscellaneous problems with DFT.
Spring 2020: ME 618 – ST: Atomistic and Molecular Simulations Methods in Mechanics and Materials Science (AMSM3S)
Same as Fall 2018 syllabus + Machine Learning Introduction