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.
New findings could help manufacturers design gels, lotions, or even paving materials that last longer and perform more predictably.
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.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
MIT researchers designed an electrolyte that can break apart at the end of a battery’s life, allowing for easier recycling of components.
Brushett leads one-of-its-kind program that has been a bridge between education and industry for over a century.
By directly imaging material failure in 3D, this real-time technique could help scientists improve reactor safety and longevity.
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.
PhD student Erik Ballesteros is building “Doc Ock” arms for future astronauts.
New test could help determine if AI systems that make accurate predictions in one area can understand it well enough to apply that ability to a different area.
Solar electric vehicle pioneer James Worden ’89 brought his prototype solar electric boat to MIT to talk shop with students and share his vision for solar-powered boats.
By combining several cutting-edge imaging technologies, a new microscope system could enable unprecedentedly deep and precise visualization of metabolic and neuronal activity, potentially even in humans.
The MRL helps bring together academia, government, and industry to accelerate innovation in sustainability, energy, and advanced materials.
The ultrabroadband infrared frequency comb could be used for chemical detection in portable spectrometers or high-resolution remote sensors.
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.