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

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.

Researchers show that MOF materials keep their electronic properties at the nanoscale, enabling miniaturization without loss of function. (Nanowerk News) IMDEA Nanociencia's "Switchable Materials" ...

CAMBRIDGE, MA -- Materials known as metal-organic frameworks (MOFs) have a rigid, cage-like structure that lends itself to a variety of applications, from gas storage to drug delivery. By changing the ...

(Nanowerk News) Generative AI techniques, machine learning and simulations give researchers new opportunities to identify environmentally friendly metal-organic framework materials. Carbon capture is ...

While metallic conductivity in MOFs has been predicted theoretically, it has so far only been put into practice in exceptional cases – and never before in thin-film form required for technical ...

Using AI and robot-assisted synthesis in a self-driving laboratory, researchers from Karlsruhe Institute of Technology (KIT), together with colleagues in Germany and Brazil, have now succeeded in ...

Results of research published today in the international peer-reviewed journal, Science. A durable and scalable metal-organic framework (MOF) captures CO 2 with high capacity, high stability and ...

Researchers developed a computational approach to predict which metal-organic framework (MOF) structures will be the most stable, and therefore the best candidates for applications such as capturing ...