Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.

In a study that could help fill some holes in quantum theory, the team recreated a “quantum bomb tester” in a classical droplet test.

The realistic model could aid the development of better heart implants and shed light on understudied heart disorders.

The advance opens a path to next-generation devices with unique optical and electronic properties.

Using machine learning, the computational method can provide details of how materials work as catalysts, semiconductors, or battery components.

The molecules, known as acenes, could be useful as organic light-emitting diodes or solar cells, among other possible applications.

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

MIT CSAIL researchers established new connections between combinatorial and continuous optimization, which can find global solutions for complex motion-planning puzzles.

An accordion-textured clay called smectite efficiently traps organic carbon and could help buffer global warming over millions of years.

The wearable device, designed to monitor bladder and kidney health, could be adapted for earlier diagnosis of cancers deep within the body.