An AAPS Open editorial spotlights chemical engineer Lucas Attia, whose PhD work matured nanoemulsion templating for drug ...

A machine-learning correction layer built by a team led from MIT has roughly doubled the accuracy of the European Centre for ...

US researchers have created a machine-learning-guided method to design better electrolytes for sodium-metal batteries. The Massachusetts Institute of Technology (MIT) team’s work could help make this ...

As artificial intelligence becomes more powerful, its ability to handle humanlike tasks is undeniable. Artificial neural networks can learn to recognize images, use language or write computer code.

Using machine learning, MIT chemical engineers have created a computational model that can predict how well any given molecule will dissolve in an organic solvent—a key step in the synthesis of nearly ...

Find out how this structured machine learning roadmap called I-Con could lead to breakthroughs in AI. A new “periodic table for machine learning” is reshaping how researchers explore AI, unlocking ...

As machine learning and generative AI reshape the world, MIT’s Schwarzman College of Computing is integrating these and other advanced computing technologies into classrooms and labs across campus.

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, ...