’A computer server transformed by MOFs . Credit: Kevin Jablonka (EPFL)
'A computer server transformed by MOFs . Credit: Kevin Jablonka (EPFL) Researchers at EPFL and KAIST have developed a new AI model that significantly improves the understanding of metal-organic frameworks (MOFs), promising materials for hydrogen storage and other applications. How does an iPhone predict the next word you're going to type in your messages? The technology behind this, and also at the core of many AI applications, is called a transformer; a deep-learning algorithm that detects patterns in datasets. Now, researchers at EPFL and KAIST have created a transformer for Metal-Organic Frameworks (MOFs), a class of porous crystalline materials. By combining organic linkers with metal nodes, chemists can synthesize millions of different materials with potential applications in energy storage and gas separation. The "MOFtransformer" is designed to be the ChatGPT for researchers that study MOFs. It's architecture is based on an AI called Google Brain that can process natural language and forms the core of popular language models such as GPT-3, the predecessor to ChatGPT.
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