"AI-assisted Computational Modeling for Ultrastable Material Design"

MIT researchers have developed a computational approach to predict the stability of metal-organic frameworks (MOFs), which have a rigid, cage-like structure that makes them useful for applications such as gas storage and drug delivery. Using their model, the researchers identified about 10,000 possible MOF structures that they classify as “ultrastable,” making them good candidates for applications such as converting methane gas to methanol. The researchers also identified certain building blocks that tend to produce more stable materials, and have made their database of ultrastable materials available for researchers interested in testing them for their own scientific applications.
- Scientists use computational modeling to design “ultrastable” materials MIT News
- Merging Artificial Intelligence and Physics Simulations To Design Innovative Materials SciTechDaily
- Using artificial intelligence to design innovative materials Tech Xplore
- Scientists use computational modeling to design 'ultrastable' materials Phys.org
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