A new generative AI approach to predicting chemical reactions
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
3 Questions: The pros and cons of synthetic data in AI
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
Soft materials hold onto “memories” of their past, for longer than previously thought
New findings could help manufacturers design gels, lotions, or even paving materials that last longer and perform more predictably.
3 Questions: On biology and medicine’s “data revolution”
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
MIT researchers develop AI tool to improve flu vaccine strain selection
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
New self-assembling material could be the key to recyclable EV batteries
MIT researchers designed an electrolyte that can break apart at the end of a battery’s life, allowing for easier recycling of components.
Fikile Brushett named director of MIT chemical engineering practice school
Brushett leads one-of-its-kind program that has been a bridge between education and industry for over a century.
New method could monitor corrosion and cracking in a nuclear reactor
By directly imaging material failure in 3D, this real-time technique could help scientists improve reactor safety and longevity.
On the joys of being head of house at McCormick Hall
Raul Radovitzky and Flavia Cardarelli reflect on a decade of telling bad dad jokes, learning Taylor Swift songs, and sharing a home with hundreds of students.
Engineering fantasy into reality
PhD student Erik Ballesteros is building “Doc Ock” arms for future astronauts.