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NICKEFFECT aims to develop novel ferromagnetic Ni-based coating materials to replace the scarce and costly Platinum and ensure high efficiency in key applications.

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NICKEFFECT project Tag

Recycling as a key of material circularity and societal acceptance   Production of energy from renewable sources is one of the keys to face the ongoing environmental crisis. The intermittency of renewable energies (wind, solar) pushed the emergence of energy storage technologies and industries such as the battery industry for storage as electrical energy, or the hydrogen industry for storage as chemical energy. Hydrogen can be produced through water electrolysis during energy overproduction periods to be transported and used on a different location and time using fuel cells, and notably Proton Exchange Membrane Fuel Cells (PEMFCs). These devices can convert hydrogen back into electricity and only emit water and heat, however, they rely on the use of raw materials that are expensive and can be critical or pose environmental issues such as platinum group metals, and perfluorinated polymers. There is a necessity to guarantee the recyclability of the constitutive materials of new...

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Materials selection is at the heart of the NICKEFFECT project. Replacing Pt-group metals with Ni is far from trivial. Materials with new compositions, structures, and topologies have to be explored and their physical and chemical properties need to be assessed. Traditionally, this exploration has been performed experimentally: a material is first synthesized and then tested in a lab to check whether it fulfills the requirements related to its application. This approach is long, requires resources, and can lead to failure at any step of the process. The scientist iterates through materials until a good solution is found, through trial and error or serendipity.   Fortunately, in the last few decades, computational tools have reached a maturity where the stability and physical properties of materials can be predicted before synthesizing them. These tools rely on density-functional theory (DFT) or more recently on machine learning (ML) when data is available. Such computations are not...

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