The Nobel Prize in Chemistry for Metal-Organic Frameworks (MOFs) is a landmark moment. In my personal experience converting these lab curiosities into scaled solutions for defense, semiconductor, and specialty chemical customers, this Nobel Prize feels long overdue.
For leaders in materials and chemistry, the Prize announcement will undoubtedly spark the question: "What is our MOF strategy?"
Many have been down this road before. The promise of MOFs was immense, but the path to successful application was elusive. Many abandoned their efforts.
Some failed because they attempted to insert MOFs into workflows made for zeolites, carbons, or polymers. Others failed because the simplistic allure of "metal + organic -> MOF" blinded them to the real challenges of unit economics, synthetic reproducibility, and particle science. Many failed because they designed a MOF for a need better served by other porous materials.
This time can be different.
Instead of rebuilding a research program from the ground up, what if you could start with the encoded expertise of the world's top porous material scientists? When a new technology need arises, what if you could ask them when to - and when not to - reach for a MOF?
The team at Lila Sciences is building an AI platform that does just that: a faster, more intelligent way to do science. We can act as your specialized research partner or integrate our system directly into your R&D workflow.
If your team is thinking about rebuilding, let's chat about what we're building at Lila.