MAT 306 Computational Techniques for Materials Science

Spring '09-'10

 

Intended Audience: A junior/senior level course for MAT and BIO majors, PHYS minors, or anyone interested in understanding the microscopic basis of physically observed phenomena using modeling and simulation.

Aims: To introduce various modeling techniques operative at a broad range of time and length scales relevant to the understanding of the structure-property relationships of “materials” where a material is defined in the broad sense of anything that is utilized for a particular human defined purpose; to introduce a conceptual framework for the understanding of macroscopic observations of materials from a microscopic viewpoint; to include modeling and simulation on equal footing with experiments in attacking problems; to provide the background for choosing the appropriate technique suited to the system at hand.

Instructor: Canan Atýlgan – office: 2058; phone: 9523; e-mail: canan@sabanciuniv.edu

Assistant: TBA – office: TBA; phone: TBA; e-mail: ???@sabanciuniv.edu

Hours: Lecture - Mon 12:40 – 14:30 (2019), Tue 16:40 – 17:30 (L056); Discussion – Tue 18:40 – 19:30; Office – see schedule on my door

Textbook: Hinchliffe, Molecular Modelling for Beginners 2nd ed. Wiley (2008). ISBN: 978-0-470-51314-9

Supplementary Textbooks:   Frenkel & Smit, Understanding Molecular Simulation 2nd ed. Academic Press (2002). ISBN: 0-12-267351-4

                                                  Leach, Molecular Modelling 2nd ed. Prentice Hall (2001). ISBN: 0-582-38210-6

Course Organization: Structured instruction with accompanying assignments.

Evaluation will be based two midterms (20 % each), seven assignments (50 %) and participation (10 %).

 

COURSE OUTLINE:

Week 1: The problem of time and length scales; coordinate systems; potential energy surfaces; molecular graphics. Degrees of freedom of a system. DS Visualizer tutorial

Aim: Introduce tools operative at various time and length scales

Week 2: Tutorial on MatLab and other tools to be used in the Course (to be moderated by Deniz Turgut). HW1: Molecule visualization practice

Week 3: Introduction to all-atom methods; force fields for organic, inorganic, and solid-state systems; reactive force fields; force field parameterization. HW2: Calculation of internal coordinates

Aim: How to choose a force field suitable for a particular system of interest.

Week 4-5: Energy minimization; non-derivative, first- and second-derivative methods. HW 3: Coding interactions

Aim: How and when to choose a minimization algorithm suitable for a particular purpose. Introduce a method for the direct comparison of experiment and simulation.

Week 5-6: Normal mode analysis. Introduction to conformational searching; systematic and random search methods. Derivation of the Boltzmann distribution. HW4: Conformational search

Aim: Study of the conformations of a molecule and their influence on its properties.

Week 7: Systematic and random search methods. Review for the midterm exam. HW5: Conformational search and NMA

Aim: Study of the conformations of a molecule and their influence on its properties.

Week 8: Midterm I (Apr. 5) Derivation of the Boltzmann distribution.

Aim: Implement the idea of a trajectory and pave the way for the calculation of simple thermodynamic properties.

Week 9: Monte Carlo simulations; importance sampling. On- and off-lattice Monte Carlo, applications to polymers and dense systems. HW6: Random number generation

Aim: Introduce the concept of ergodicity, and sampling from different ensembles.

____________________________________________________Spring break HW7: Monte Carlo

Week 10: General comments on “trajectory” methods; cut-offs on non-bonded energy terms; periodic boundary conditions; some tricks for an efficient simulation. Introduction to molecular dynamics simulations.

Aim: Understand the capabilities and the limitations of a dynamic simulation method based on first principles.

Weeks 11: Principles of molecular dynamics simulations. HW8: Molecular Dynamics

Aim: To establish concepts of equipartition, energy conservation.

Week 12: MD continued & BD. Prediction of system properties from simulations: Thermodynamic properties.

Aim: Bridge theory and experiments that are based on the dynamics of molecules.

Week 13: Prediction of system properties from simulations: Radial distribution functions, correlation functions, diffusion coefficient.

Aim: Bridge theory and experiments that are based on the dynamics of molecules.

Week 14: Midterm II (May. 24) Introduction to coarse-graining; methods used on the mesoscale; dissipative particle dynamics. HW9: Dissipative Particle Dynamics

Aim: Introduce relatively new methods operative on the mesoscale; provide a link between microscopic scales and mesoscopic/macroscopic phenomena. Show how a simplistic elastic model can reproduce equilibrium properties of chain systems.

 

SOFTWARE:

o    Various molecular visualization software (e.g. DS Visualizer: http://accelrys.com/products/discovery-studio/visualization/index.html ; VMD: http://www.ks.uiuc.edu/Research/vmd/ )

o    NAMD (Molecular Dynamics software: http://www.ks.uiuc.edu/Research/namd/ )

o    ESPResSo (Molecular Dynamics software: www.espresso.mpg.de )

o    Some programming of your own (nothing fancy – just basic programming to analyze data you produce from the package programs above)