Coupling the Time-Warp Algorithm with the Graph-Theoretical KMC Approach for Catalysis Simulations on Mega-Lattices and Beyond

TH Department Seminar
Date: May 4, 2023
Time: 02:00 PM (Local Time Germany)
Speaker: Prof. Michail Stamatakis
Department of Chemical Engineering, University College London, UK | AvH Friedrich Wilhelm Bessel Research Awardee at Theory Department
Location: https://zoom.us/j/92388389926?pwd=NG5yRG52ZURHUkRYTzd3TFB1aWFYZz09
Room: Meeting ID: 923 8838 9926 | Passcode: 256657
Host: TH Department

Kinetic Monte-Carlo (KMC) simulations have been instrumental in multiscale catalysis studies, enabling the elucidation of the complex dynamics of heterogeneous catalysts and the prediction of macroscopic performance metrics, such as activity and selectivity. However, the accessible length- and timescales are still limited, and handling lattices containing millions of sites with “traditional” sequential KMC implementations becomes prohibitive due to large memory requirements and long simulation times.

Domain decomposition approaches could address these limitations, but they are challenging to implement in KMC simulation due to the inherently sequential nature thereof, by which one reactive event is causally linked to future (and past) events. These causal relations and the random time advancements of KMC steps, necessitate sophisticated protocols for conflict resolution at the boundaries between subdomains. Jefferson’s Time-Warp algorithm overcomes these challenges using local operations: sending and receiving messages/anti-messages, saving simulation state snapshots, and rolling-back in time to reinstate a previous state. Thus, any causality violations, arising transiently during simulation, are corrected, and the exact dynamics of the underlying stochastic model (the master equation) are finally reproduced.

In this work, we have coupled the Time-Warp algorithm with the Graph-Theoretical KMC framework enabling the handling of complex adsorbate lateral interactions and reaction events within large lattices. This approach has been implemented in Zacros, our general-purpose KMC software, and has been validated and benchmarked for efficiency in model systems as well as realistic chemistries. This work makes Zacros the first-of-its-kind general-purpose KMC code with distributed parallelisation capability to study heterogeneous catalysts.