Materials of Tomorrow: MIT’s Breakthrough in Predicting Stable Metal-Organic Frameworks

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Materials of Tomorrow: MIT’s Breakthrough in Predicting Stable Metal-Organic Frameworks
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These highly stable metal-organic frameworks could be useful for applications such as capturing greenhouse gases. MIT researchers developed a computational model to predict the stability of metal-organic frameworks (MOFs) and identified 10,000 ultrastable MOF structures suitable for various appli

Materials known as metal-organic frameworks have a rigid, cage-like structure that lends itself to a variety of applications, from gas storage to drug delivery. Credit: David Kastner

However, not all possible MOF structures are stable enough to be deployed for applications such as catalyzing reactions or storing gases. To help researchers figure out which MOF structures might work best for a given application, MIT researchers have developed a computational approach that allows them to predict which structures will be the most stable.

MIT graduate student Aditya Nandy is the lead author of the paper, which was published on April 4 in the journal. Other authors are MIT postdoc Shuwen Yue, graduate students Changhwan Oh and Gianmarco Terrones, Chenru Duan PhD ’22, and Yongchul G. Chung, an associate professor of chemical and biomolecular engineering at Pusan National University.

Currently, the most common way to design MOFs is through trial and error. More recently, researchers have begun to try computational approaches to designing these materials. Most such studies have been based on predictions of how well the material will work for a particular application, but they don’t always take into account the stability of the resulting material.

By recombining these building blocks using about 750 different types of architectures, including many that are not usually included in such models, the researchers generated about 50,000 new MOF structures. “Designing a MOF requires consideration of many types of stability, but our models enable a near-zero-cost prediction of thermal and activation stability,” Nandy says. “By also understanding the mechanical stability of these materials, we provide a new way to identify promising materials.”

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