Physics projects for Y3 and Y4 students

Project description

Molecular Dynamics simulation of supercooled liquids and glasses

(supervisor: Edwin Flikkema)

Nature of project: data analysis, software

Available to students on full-time physics degree schemes or joint students.

Project description and methodology

Molecular Dynamics (MD) is a versatile simulation method, used in chemistry and physics to study phenomena in atomistic detail. MD is based on integrating Newton's equations of motion. The trajectories of all the particles in the system are calculated, starting from an initial set of coordinates and velocities. A crucial step in setting up an MD calculation is the choice of the force field. Force fields have been developed for many materials.

Upon cooling, many materials will solidify, when a temperature below the melting point is reached. However, quite often, a super-cooled liquid state can be reached, which is meta-stable with respect to the crystalline phase. Usually, the viscosity of the super-cooled liquid increases as the temperature is reduced. In some cases the viscosity reaches such a high value that, for all practical purposes, the system can be regarded as a solid. This state of matter is called a 'glass'. Although a glass is a solid, it lacks the crystalline order of a regular solid.

The aim of this project is to study glass-forming materials using the Molecular Dynamics simulation technique. Several implementations of the MD simulation method have been developed. DLPOLY is an example of such a computer code. It is quite versatile. DLPOLY includes an extensive library of force-fields. Bulk systems can be modeled through the use of periodic boundary conditions.

Silicates form an important class of glass-forming materials. Specific examples include Sodium-disilicate (Na2O)(SiO2)2 and Potassium-disilicate (K2O)(SiO2)2 or mixtures thereof. Here the silicon and oxygen atoms form a network that is essentially static at temperatures below 2000K. The alkali ions (Na, K) are still mobile at such temperatures. An interesting phenomenon to study in these systems is the diffusion of the alkali ions. Experiments have shown the 'mixed alkali effect', where the diffusion constant shows a minimum as a function of the Na/K ratio.

In the project, the students will perform MD simulations of silicate materials using the DLPOLY computer program. The students will look at the effect of cooling rate on properties such as cell parameters, network topology (e.g. through a 'Q-species' analysis) and the local chemical environment (first neighbour shell) of alkali and network atoms.

A successful project will develop beyond the above in one/some of the following directions:
To develop the project further, the students can look at dynamics of the Na/K ions and try to study the mixed alkali effect.

When considering where to take your project, please bear in mind the time available. It is preferable to do fewer things well than to try many and not get conclusive results on any of them. However, sometimes it is useful to have a couple of strands of investigation in parallel to work on in case delays occur.

This project is only available as a Y3 project.

Please speak to Edwin Flikkema if you consider doing this project.

Initial literature for students:

  1. https://www.scd.stfc.ac.uk/Pages/DL_POLY.aspx
  2. M.P. Allen, D.J. Tildesley, Computer Simulation of Liquids (Oxford Science Publications)
  3. D. Frenkel and B. Smit, Understanding molecular simulation, Academic Press (second edition, 2002)

Novelty, degree of difficulty and amount of assistance required

This project consist of applying an existing computer code (DLPOLY) to glass-forming materials, some of which have been studied before. Running the DLPOLY program does not involve any actual coding (the details of the calculations are controlled through keywords in the input files). However, the students are likely to need to write their own (short) programs to analyse the output generated by DLPOLY. This can be done in a number of programming languages (e.g. C/C++, Fortran or Python).

Project milestones and deliverables (including timescale)

milestoneto be completed by
Familiarisation with DLPOLYend of November
Input-files created, first production runs startedChristmas
Codes for data-analysis writtenmid-March
Data analysedEaster