Savva, Giannis;
(2022)
Development, implementation and efficiency optimization of novel methods to accelerate kinetic Monte Carlo simulations of reactive systems.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
On-lattice Kinetic Monte Carlo (KMC) is a powerful computational method that is widely used to study chemical reaction on catalytic surfaces. It is an exact method able to capture surface inhomogeneities, e.g. due to interactions among the participating species, and handle systems with complex chemistries. KMC is exact in the sense that the method itself does not introduce approximations of any kind. Therefore, the results produced from a KMC simulation depend exclusively on the input, i.e. the lattice, the chemical reaction model, and the kinetic and energetic parameters thereof. However, KMC simulations of realistic systems tend to be computationally demanding, mainly due to the inherently serial nature of KMC since the reaction events are scheduled and executed one at a time. This thesis focuses on methods and approaches to accelerate KMC simulations of reactive systems. First, the focus is on the scheduling of KMC events undertaken by suitable queueing systems. Different data structures are developed, implemented and benchmarked to identify those that deliver the best computational performance. Next, detailed performance evaluation and optimisation studies are performed for a newly implemented algorithm that enables distributed, on-lattice, KMC simulations. Lastly, the focus turns towards well-mixed chemical reaction systems exhibiting timescale disparity, i.e. system in which some reactions occur much more frequently than others. To tackle timescale disparity, a novel method is developed that reduces (downscales) the appropriate rate constants on the fly in an optimal and data-driven way. The developed method also provides estimates for the error introduced by the downscaling procedure. The approaches developed and benchmarked enable KMC simulations to reach temporal and spatial scales that were previously unattainable. Thus, these methodological advancements are expected to have significant positive impact in future studies of complex systems.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Development, implementation and efficiency optimization of novel methods to accelerate kinetic Monte Carlo simulations of reactive systems |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2022. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10152249 |
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