Unravelling Complexity in Heterogeneous Catalysis via High Fidelity Kinetic Monte Carlo Simulation

Michail Stamatakis

University College London, United Kingdom

Monday, 20 March 2023,17:15 s.t.

The talk will be given in hybrid mode.

You can join at:
Freihaus Hörsaal 7 (HS 7)
TU Freihaus, Yellow Area, 2nd floor
Wiedner Hauptstraße 8, 1040 Vienna

Or you can join the zoom meeting:
Meeting ID: 927 3941 7554     Passcode: X74b82XE

Unravelling Complexity in Heterogeneous Catalysis via High Fidelity Kinetic Monte Carlo Simulation

The importance of heterogeneous catalysis in modern applications that enhance the quality of life cannot be overstated: current estimates place the value of the catalyst market at more than $34 billion, and it has been estimated that every $1 spent on a catalyst can generate up to $1000 worth of product. Computational methods are crucial in gaining a fundamental understanding of the physicochemical phenomena resulting in catalytic activity and this understanding can guide the design of improved catalysts. Yet, the complexity encountered in heterogeneous catalysts renders such modelling efforts challenging. Complexity in these systems arises due to the various types of surface sites, which typically have distinct chemical properties; the presence of lateral interactions among reactants and spectators, which affect reaction rates; the multiple possible reaction pathways, which may collectively shape activity and selectivity trends; and finally, emergent phenomena at the meso- and macro-scales, which may lead to highly non-linear behaviours, such as oscillations and pattern formation. In this talk, we will discuss the development of a state-of-the-art modelling framework, which can address these challenges, thereby being able to model complexity in catalytic systems efficiently. The framework is based on the kinetic Monte Carlo (KMC) method and uses concepts from graph theory to represent reaction events, as well as energetic interactions among adsorbed species. Efficient algorithms, employing shared memory as well as distributed memory parallelism, enable the treatment of large domains and complex kinetics. We will further demonstrate the power of this approach on catalytic systems of interest in the environmental and sustainability fields. Our Graph-Theoretical KMC approach will thus be shown able to provide a wealth of information, which can be used to explain experimental observations and obtain insight in the design of materials with desired catalytic properties.

Bio of Michail Stamatakis

Michail Stamatakis is Professor of Chemical Engineering at UCL, where he has been a member of Academic Staff since 2012. Prior to joining UCL he performed post-doctoral research at the University of Delaware under the supervision of Prof. Dionisios G. Vlachos. He obtained his PhD from Rice University, where he worked under Prof. Kyriacos Zygourakis and Dr. Nikos Mantzaris. Michail also holds a Diploma in Chemical Engineering from the National Technical University of Athens (Greece), where he did his Diploma Thesis research under the advising of Prof. Andreas Boudouvis, as well as Dr. Nikos Mantzaris in the context of two short placements to Rice University as a Visiting Scholar.