MIT chemists developed a battery cathode based on organic materials, which could reduce the EV industry’s reliance on scarce metals.

New insights into how proton-coupled electron transfers occur at an electrode could help researchers design more efficient fuel cells and electrolyzers.

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

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.

Chemists discover the structures of open and closed states of the channel, which could help the development of antiviral drugs to reduce inflammation.

The findings, based on a single electrochemical process, could help cut emissions from the hardest-to-decarbonize industries, such as steel and cement.

MIT engineers developed a new way to create these arrays, by scaffolding quantum rods onto patterned DNA.

A new approach opens the door to a greater understanding of protein-microbe interactions.

A new study shows that truncated versions of the Tau protein are more likely to form the sticky filaments seen in the brains of people with Alzheimer’s disease.