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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02
Oct