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Rational design of hydrophobic MOFs for energy applications

Project description

Machine learning model helps designing tailored metal-organic frameworks

Metal-organic frameworks (MOFs) are versatile materials with nanoporous structures, making them valuable in fields such as catalysis, gas storage and energy devices. Their unique ability to have tailored cavity properties has boosted their potential, particularly in hydrophobic MOFs, which use pressure cycles to move water in and out of their pores. This liquid intrusion/extrusion process has potential for energy storage and impact absorption but is highly complex, involving the unstable behaviour of water within the cavities. With the support of the Marie Skłodowska-Curie Actions programme, the HydroMOF project will tackle the need for expensive simulations by developing WetNet – a machine learning model that predicts water behaviour in MOFs. This model will enable efficient material design and open new possibilities for studying nanoconfined water.

Objective

Metal Organic Frameworks (MOFs) represent a class of nanoporous materials that is propelling groundbreaking innovation in fields that include catalysis, gas capture and storage. The success of MOFs hinges on the possibility to tailor, based on technological demand, the properties of their cavities, with a versatility that results from the combinatorial variety of their modular, molecularly-precise structures. Recently hydrophobic MOFs are becoming increasingly popular in energy devices that exploit pressure cycles to force water to intrude and extrude the material’s cavities. Different MOFs display different Intrusion/Extrusion (IE) behaviors enabling a variety of applications that range from mechanical energy storage to vibration damping and impact absorption. IE of liquids, unlike gas adsorption, is a complex phenomenon associated to the cavity-by-cavity motion of a liquid front determined by the metastability of wet and dry cavities, a datum that is only accessible via expensive molecular simulations. This vast complexity has so far prevented a first-principle design of IE materials, with only a handful of MOFs currently being exploited for IE. Addressing these challenges HydroMOF sets to enable the rational design of IE MOFs. This is achieved first via the creation of WetNet, a physically-informed machine learning model able to predict the stability of water inside the cavities of database MOFs. Circumventing the need for case-by-case free energy simulations WetNet enables the screening of thousands of MOFs yielding designs tailored around specific applications. At a later stage molecular insight will inform original lattice models able to simulate actual IE cycles through realistic MOF cavity networks, unprecedentedly encompassing non-equilibrium, finite-size and disorder-related effects. Through these advances HydroMOF’s impact extends beyond IE, opening new avenues in the design of liquid+reticular material devices and in the study of nanoconfined water.

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Topic(s)

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HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-PF-01

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Coordinator

UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 388 940,52
Address
Piazzale Aldo Moro 5
00185 Roma
Italy

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Region
Centro (IT) Lazio Roma
Activity type
Higher or Secondary Education Establishments
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Total cost

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