A Game of Order Parameters
Supervisors: Dr David Quigley (Physics) and Dr Gabriele C. Sosso (Chemistry)
Predicting if, how and when ice crystals will form [1] in clouds (and our own cells!) is important to atmospheric science (and cryopreservation! [2]) and the manufacture of pharmaceuticals [3]. Preventing crystals from nucleating is desirable instead in our brains (where aggregates of proteins can lead to neurological diseases [4]) and for the oil industry (where water-based crystals can block pipelines [5]). Computer modelling can, in principle, design strategies for optimal control over these processes: in fact, advanced atomistic simulation techniques are now able to calculate key properties such as crystal nucleation rates. Unfortunately, the comparison of these rates against experimental data is subject to uncertainties [6] which have not been rigorously quantified yet. Specifically, the choice of the particular mathematical object we use to identify atoms as part of a crystalline nucleus (the so-called “order parameter”) [7] has a major impact. We will use formal uncertainty quantification (which form part of the core HETSYS training) to rectify this, initially using simple models [8] – for which accurate results are available, and then moving onto scenarios of great practical importance - such as the formation of ice [9].
References
[2] J.O.M. Karlsson, Science 296 (2002) 655–656.
[3] J.R. Cox, L.A. Ferris, V.R. Thalladi, V. R. Angew. Chem. 46 (2007) 4333−4336.
[4] J.D. Harper, C.M. Lieber, P.T.Jr. Lansbury, Chem. Biol. 4 (1997) 951−959.
[5] D.E. Sloan, Nature 426 (2003) 426 353−363.
[8] Y. Lifanov, B. Vorselaars, D. Quigley, J. Chem. Phys. 145 (2016) 211912.