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 Atilgan – office: 2058; phone: 9523; e-mail: canan@sabanciuniv.edu
Assistant: Gokhan Kacar - office: 2102; phone: 2111; e-mail: gokhankacar@su.sabanciuniv.edu
Hours: Lecture - Monday 11:40 – 13:30 (L030), Wednesday 8:40 – 9:30 (G015); Office – please make an appointment
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), assignments (25%), one final project (25%), and participation (10%)
DETAILED COURSE OUTLINE:
Week 1: The problem of time and length scales; coordinate systems; potential energy surfaces; molecular graphics.
Aim: Introduce tools operative at various time and length scales
Week 2: Introduction to all-atom methods; force fields for organic, inorganic, and solid-state systems; reactive force fields; force field parameterization.
Aim: How to choose a force field suitable for a particular system of interest.
Week 3: Energy minimization; non-derivative, first- and second-derivative methods. Normal mode analysis.
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 4: Conformational searching; systematic and random search methods; biasing the search towards the low-energy regions.
Aim: Study of the conformations of a molecule and their influence on its properties.
Week 5: Introduction to “trajectory” methods; cut-offs on non-bonded energy terms; periodic boundary conditions; some tricks for an efficient simulation.
Aim: Implement the idea of a trajectory and pave the way for the calculation of simple thermodynamic properties.
Week 6: Monte Carlo simulations; importance sampling; on- and off-lattice Monte Carlo; applications to polymers and dense systems.
Aim: Introduce the concept of ergodicity, and sampling from different ensembles.
Week 7: Review and midterm I (Apr. 9)
Weeks 8-9: Molecular dynamics simulations.
Aim: Understand the capabilities and the limitations of a dynamic simulation method based on first principles.
Week 10: Correlation functions and their relation to experimental observables.
Aim: Bridge theory and experiments that are based on the dynamics of molecules..
Week 11: Introduction to coarse-graining; network models and related methods.
Aim: Demonstrate that a very simplistic modelling approach can lead to valuable information.
Week 12: Methods used on the mesoscale; dissipative particle dynamics.
Aim: Introduce relatively new methods operative on the mesoscale; provide a link between microscopic scales and mesoscopic/macroscopic phenomena.
Week 13: Agent-based modelling in example problems: Grain growth, crystallization, polymer dynamics, diffusion…
Aim: Use of heuristics to describe phenomena that occur on the micro-scale.
Week 14: Review and midterm II (May. 28).
SOFTWARE:
o Various molecular visualization software (e.g. WebLab Viewer, VMD)
o NAMD and ESPResSo (Molecular Dynamics software)
o NetLogo (Agent-based modelling software)
o Some programming of your own (nothing fancy – just basic programming to analyze data you produce from the package programs above)