FEATURE Oli & Gas
Advancing green energy through functionalised metal-organic frameworks
Researchers at the University of Crete and Toyota Motor Europe improved the hydrogen storage profile of metal- organic frameworks (MOFs) as potential materials for use in hydrogen-powered cars and provided a proof of concept for the application of machine learning in MOF design
M
metal-organic frameworks, or MOFs, are network structures that contain metal clusters coordinated
to organic molecules, called ligands. Here, the ligands are substituted benzene rings. Because they’re usually porous, MOFs are well suited to store gases, like hydrogen. For example, tanks that contain hydrogen bound to MOFs may require lower pressure than tanks that contain just hydrogen. Such tanks have applications in hydrogen-powered vehicles. Like battery-powered cars, hydrogen-
powered cars may help reduce our dependence on fossil fuels. Dr George E. Froudakis is a Professor of Computational Chemistry at the University of Crete and a co-author of the recent paper on this subject. He says that mainly it’s the mechanism for energy storage that diff erentiates conventional electric vehicles from hydrogen-powered ones. One has a battery while the other has a hydrogen tank and a fuel cell where the hydrogen is burned to produce electricity and water. “All the other components may be the same,” said Prof. Froudakis. “Towards green transportation, battery technology is mostly targeted to light vehicles, while hydrogen can be applied to heavy and large vehicles, too – trucks, trains, boats, submarines, etc.”
He says another advantage of hydrogen cars is that refuelling can take place in a few minutes at a hydrogen-fuelling station. However, this does require hydrogen tanks with sizes that can fi t in a car, which is why the industry wants to improve storage performance.
Hydrogen storage The researchers sought to design MOFs with improved hydrogen storage capabilities. They did this by strategically selecting 58 benzene-based functionalised
38 December/January 2022 | Automation
linkers that can be building blocks of MOFs, and then calculated the hydrogen- MOF binding energy using computational chemistry techniques. Several of the functionalised MOFs saw an increase in hydrogen interaction strength of 15% to 25%. One saw an improved interaction of 80%. The team then used these fi ndings to train a model through machine learning (ML) to predict binding energy, with good results – even with the limited data from their functionalisation eff orts. They hope this proof of concept ML approach can be used in future eff orts, potentially saving time and resources on computationally- heavy calculations.
Functionalising MOFs The researchers functionalised their Isoreticular (IR) MOFs using base structures from MOFs found in the Cambridge Structural Database (CSD). “We selected three robust well-known MOFs from the fi rst generation of IR- MOFs in order to test our functionalisation strategy. We wanted to prove that the linker functionalisation is vital for obtaining a signifi cant enhancement of the hydrogen uptake in many porous materials like MOFs, Covalent-Organic Frameworks (COFs), Zeolitic imidazolate
frameworks (ZIFs), and so on. We expect that this strategy will be followed by other researchers for the synthesis of novel functionalised MOFs with superior hydrogen-storage capacities,” said Prof. Froudakis.
The CSD contains over 100,000 MOF- like frameworks, collated together in two enriched and curated subsets. Suzanna Ward is Head of Data and Community at the Cambridge Crystallographic Data Centre (CCDC), which houses the CSD. “MOFs have a huge potential to help us tackle climate change, and it is clear that harnessing knowledge from the wealth of available data can help with the research,” she said. “With MOFs on the rise in the CSD, it is certainly exciting to see how this data coupled with machine learning could help improve hydrogen storage that could one day lead to greener transportation.” To help support such eff orts, the CCDC makes over 10,000 computationally-ready, 3D, porous MOFs freely accessible for academic research.
“Recent developments make it easier for scientists to utilise knowledge from MOF structures through curated subsets and a MOF collection designed for high- throughput analysis,” said Ward.
automationmagazine.co.uk
Linker functionalisation strategy for improved hydrogen storage profile of MOFs, with applications in automotive storage tanks
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