A computational model developed by researchers at the Massachusetts Institute of Technology (MIT) can be used to predict which metal-organic framework (MOF) structures will be most stable for a given application.
The model has been used to identify around 10,000 possible MOF structures classified as "ultrastable" for thermal stability and activation stability.
Said MIT's Heather Kulik, "We used data and our machine-learning models to come up with building blocks that were expected to have high stability, and when we recombined those in ways that were considerably more diverse, our dataset was enriched with materials with higher stability than any previous set of hypothetical materials people had come up with."
The researchers also determined that the ultrastable MOF structures had good "deliverable capacities" for methane and were mechanically stable. Further, they identified that gadolinium-containing molecules and porphyrin molecules generally produced more stable materials.
From MIT News
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