8 Course Projects

Your grade in this course will be based on a small project, which you will hand in as a report of a maximum of 10 pages, and about which you will make a \(\sim \) 10 minute presentation during the final week of the term.

The goal of this project is to convince yourself that you have gained a working understanding of some aspect of molecular simulation that is of interest to you. For this reason, you are given a large amount of freedom in choosing your topic. Here you’ll find a compiled list of suggested project exercises, also found interspersed throughout the rest of the website.

You’ll also see the schedule. Sign-up is first-come, first-served. Please send me an email at cfa2@drexel.edu with your project title and your top three time-slot choices as soon as possible. There are 13 available slots as of May 14, 2004; as there are 10 of you officially giving presentations, this should be adequate.

8.1 Suggested Topics

Below is a list of suggested topics, and they are only weakly suggested. You can do almost anything else as long as you find it reasonably interesting. This could be using one of the codes provided by me or F&S, or your own code. You will write a short “report” (just a few pages, maybe a figure or two), and give a short presentation about your project. The goal in both cases is to document and demonstrate what you learned in doing the project, not so much to document and demonstrate anything new.

• Monte-Carlo simulations:

  • Suggested exercises for the Ising magnet (Sec. 3.2)
  • Orientational correlation functions in 2D dumbbells (Sec. 3.5)
  • Various displacement methods in MC simulation of LJ fluid
  • Orientational correlation in LJ Dumbbells in 3D (Sec. 3.7)

• Molecular dynamics simulations:

  • Structure in a liquid made of particle of two different sizes. Modify mdlj.c to handle a particle-specific value of \(\sigma \). Let there be two types of particles, \(A\) and \(B\), and let \(\sigma _A = \sigma = \sigma _B/2\). For any pair \(ij\), the \(\sigma \) used in evaluating the potential is \(\sigma _{ij} = 1/2(\sigma _i+\sigma _j)\). Modify rdf.c to compute the \(AA\), \(BB\), and \(AB\) radial distribution functions at a few compositions and overall densities.
  • Obstacles: Compute the effect on the diffusivity in a Lennard-Jones fluid at a given temperature and density by the presence of fixed obstacles in the domain which interact with the particles. These obstacles could be other particles which do not move, or “lines” of Lennard-Jones potential (See Sec. 10.1) arrayed on some grid or randomly. A relationship between \(\mathscr {D}/\mathscr {D_0}\) and \(\rho _{\rm obs}\), where \(\rho _{\rm obs}\) is the density of obstacles, might be interesting to see.
  • Any of the suggested exercises involving Stillinger-Weber silicon (Sec. 7.1)
• Case Study 15 from F&S: The overlapping distribution method for computing \(\mu _{\rm ex}\).
• Optimization: Apply one or more of the techniques in Appendix F to one of the Lennard-Jones codes (mclj.c or mdlj.c), and compare the performance to the standard \(N^2\) algorithm.

8.2 Schedule of Presentations