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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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How a common metal like Nickel could replace Platinum in electrolysers and accelerate the EU's green transition   Imagine trying to replace the world’s best performer with a budget alternative—and not just match it, but get close enough to change the game. That’s the challenge facing scientists working to reduce the use of platinum in hydrogen production. And it’s the bold mission of the Horizon Europe project NICKEFFECT.   Why Hydrogen, and why now?   Hydrogen is a key pillar of the European Union’s plan to decarbonise its economy and reach climate neutrality by 2050. Produced through water electrolysis, hydrogen offers a clean energy carrier—especially when powered by renewables. The EU has set an ambitious target: installing 40 GW of electrolyser capacity by 2030, which would produce millions of tonnes of green hydrogen annually.   But there's a catch. The most efficient technology for hydrogen production—Proton Exchange Membrane Water Electrolysers (PEMWE)—relies on rare and expensive platinum group metals...

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The NICKEFFECT project participated in the Artificial Intelligence for Advanced Materials Conference (AI4AM 2024), held from July 2nd to 4th in the city of Barcelona, Spain. This cross-disciplinary international event brought together top experts from industry and research institutions who utilise Artificial Intelligence (AI) to advance discoveries in materials science. The conference's main goal is to refine automated designs for both structural and electronic material models in engineering, focusing on improving interoperability among material databases and enabling reverse material engineering.   Konrad Eiler, from NICKEFFECT's project partner Universitat Autònoma de Barcelona, did a presentation on the active learning approach used to accelerate experiments as part of the project. Konrad gave some insights on the practical benefits of the Active Learning methodology in guiding experimentalists to find the best conditions for growing Ni-W films for catalysis.     Active Learning in Materials Science   Konrad's presentation highlighted how AI, particularly Active Learning, significantly aids experimentalists in determining optimal...

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