Heterogeneous nucleation is the primary pathway for ice nucleation in nature and has tremendous impact in fields such as agriculture, food industry, climate control, and transportation. In spite of the broad interests, the molecular mechanisms through which surfaces promote or inhibit ice nucleation remain elusive. The primary difficulty in studying ice nucleation is accessing the relevant length and timescales in experiments and computer simulations. While simulations are well-posed to probe the molecular details of heterogeneous ice nucleation, sampling nucleation is challenging. Ice nucleation is a rare event and therefore, in straightforward simulation methods (like molecular dynamics) large amount of computational resources are wasted on the uninteresting part of waiting for the event. In our work, we have built upon forward flux sampling (FFS) – a technique developed to sample rare events simulations. We have integrated state-of-the-art technologies to handle computational and data-intensive tasks with molecular simulations to develop a software platform, Scalable FFS (ScaFFS), to performs large-scale FFS calculations. Using ScaFFS, we have studied the effects of surface chemistry on two ice nucleating surfaces – silver iodide (AgI) and kaoice. Kaoice was formed by modifying the kaolinite surface to match ice lattice. The two surfaces have an exact match to ice, however differ in their surface chemistries. Kaoice has hydroxyl groups that hydrogen bond with water while AgI has positive and negative ions that contact water. We performed large scale FFS simulations and sampled ~400 nucleation events – largest number of nucleation events sampled so far in simulations. Our studies indicate that even though both surfaces have the same lattice match with ice, AgI is a more potent ice nucleating agent than kaoice. The nucleation mechanism is different at both the surfaces. In the poster, we will describe the ScaFFS software program and the results on heterogeneous ice nucleation.

Elucidating heterogeneous ice nucleation mechanisms using large scale rare event simulations

253rd National Meeting (2017)

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