Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...

Omar Yaghi, the James and Neeltje Tretter Chair in UC Berkeley's College of Chemistry and an affiliate at Lawrence Berkeley ...

A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...

Solid sorbents are a step change for carbon capture but the challenge is to merge all of the desirable commercially viable features into a robust framework material with a low manufacturing cost.

Scientists at Oregon State University have discovered a method to significantly enhance the carbon dioxide absorption capacity of a chemical structure, more than doubling its effectiveness for ...