Two new FWO postdoctoral fellowships

We are proud to announce that two of our postdoctoral researchers obtained a personal fellowship from the Research Foundation – Flanders (FWO) for three years to support their independent international research career. Jelle Vekeman started at CMM in October 2020 with the guidance of prof. Toon Verstraelen. Jenna Mancuso arrived at CMM in September 2021 to join the research group of prof. Veronique Van Speybroeck. We are pleased to continue our collaboration with them in the frame of their FWO postdoctoral fellowship. Congratulations!

About Jelle Vekeman

From the start Jelle was convinced that international experience and collaboration is a key to success. Already during his master year he went to the University of Girona in Spain for an Erasmus stay of 10 months. For his master thesis entitled ‘The role of electron correlation and atomic partition on bond Fukul functions’ he worked in the lab of prof. dr. Solà under supervision of dr. Matito and prof. dr. Bultinck at his home institute, Ghent University.

For his PhD he worked in two different institutes abroad, namely the University of Valencia, also in Spain, and the university of Perugia in Italy. Furthermore he performed secondments at Alya Technology & Innovation S.L., an industrial partner of the Marie-Sklodowska-Curie Innovative Training Network of which he was one of the early stage researchers (ESR). In Valencia he performed static CCSD(T) and DFT calculations and developed force fields which he later used for molecular dynamics simulations (in Perugia) and grand canonical Monte Carlo simulations (at Alya Technology & Innovation S.L.).

Back in Belgium he performed two postdoctoral projects at the Vrije Universiteit Brussel, the first on spectroscopic characterization of oxides using periodic DFT and the second on molecular dynamics simulations of polymer solubility. Since October 2020 he is a postdoctoral researcher at CMM and working on non-reactive molecular dynamics simulations of HSIL systems as precursors for zeolite formation.

About Jelle’s project – A Reactive Molecular Model for Aluminosilicate Chemistry to Study Zeolite Formation

Despite their large commercial importance, zeolite formation is poorly understood due to the complex, heterogeneous nature of traditional synthesis. COK-KAT (KU Leuven) recently reported a novel synthesis path via hydrated silicate ionic liquids (HSILs), completely homogeneous, inorganic liquids which yield zeolites at moderate conditions. HSILs are severely subhydrated, room temperature alkali-silicate melts consisting of small oligomers. Water is not present as bulk, but as a ligand to the ionic species. HSILs are very stable, until addition of aluminate triggers nucleation and zeolite growth even at room temperature (~6 months) or within minutes at 180°C. The unique properties of HSILs allow for development of a reactive molecular model for aluminosilicate chemistry at the Center for Molecular Modeling (CMM, Ghent University), which can be carefully tested against detailed experimental results obtained at COK-KAT. As zeolite formation involves successive condensation reactions, reactive neural network potentials will be trained on high-level DFT-D data to be used in large-scale molecular dynamics simulations. To minimize the amount of expensive DFT-D calculations, an active learning scheme will be employed. Enhanced sampling methods will be used to efficiently explore the free energy surface. This, in combination with detailed experimental insight, will lead to a better understanding of the relationship between HSIL composition and the experimentally observed topology.

About Jenna Mancuso

Jenna worked at the Hendon Materials Simulation group at the University of Oregon during her PhD. She focused on the application of DFT to metal-organic framework development for the purposes of catalysis and renewable energy (e.g. charge storage, supercapacitors, fuel cells, photomaterials). Additionally, she has extensive experimental experience relating to the mechanical, electronic and optical properties of functional polymeric components (e.g. in photovoltaic modules) as well as the synthesis, characterization, and purification of inorganic phosphors and optically active organic molecules. With expertise ranging across fields of polymer engineering, organic and inorganic synthesis, and theoretical chemistry she possesses a unique scientific perspective and ability to connect theory and experiment.

Jenna joined the CMM in September 2021 to provide atomic scale insights into the spatiotemporal evolution of chemical systems in industrial processes using a variety of computational methods, focusing on methanol-to-hydrocarbon conversions in zeolites. She mainly applies enhanced sampling methods of molecular dynamics to establish robust kinetic and thermodynamic models of realistic materials under operating conditions, utilizing rigorous spectroscopic benchmarking to experiment.

About Jenna’s project - Realistic molecular simulations of diffusion and reactivity in hierarchical zeolite catalysts

Methanol-to-hydrocarbon (MTH) conversion from renewable feedstocks is a viable source of light olefins or fuels, provided catalyst selectivity and lifetime can be enhanced. Hierarchical zeolite structures, imbued with a secondary mesopore system within the innate microporous crystal are promising architectures for improved MTH conversion. However, the origins of increased lifetime and short-olefin selectivity in these catalysts is poorly understood. To guide future catalyst development, this project will establish the first quantum mechanical models of hierarchical zeolites to clarify mesopore surface chemistry and elucidate the impact on diffusion and reactivity of key MTH intermediates and products. Rigorous structural validation with experiment will help define accurate structural models, to which state-of-the-art operando modeling techniques will be applied. To accelerate simulation times with first-principles accuracy and facilitate the use of larger models, machine learning potentials will be developed with the generated data. Thus, this work will provide crucial insights into mesopore chemistry and stimulate future reaction modeling in more accurate hierarchical models.