MIT spinout turns plastic waste into resilient building materials

Paving the way for greener ammonia production

New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products.

MIT projects selected for funding under US Department of Energy’s Genesis Mission

Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.

MIT’s Initiative for New Manufacturing builds momentum

In its first year, INM has worked across research, workforce development, and industry engagement to help accelerate new manufacturing technologies and their real-world deployment.

MIT in the media: For the future of tech, "Massachusetts can absolutely lead"

Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles published alongside the outlet's annual list of 'Tech Power Players'

Media Advisory: MIT to establish regional quantum hub

With $25 million investment from the Commonwealth of Massachusetts, MIT to build a new shared-use facility to serve as a statewide quantum toolbox.

Sustainable Materials Discovery in the Era of Artificial Intelligence

arXiv:2601. 21527v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening.

MIT in the media: Exploring how curiosity-driven science is an essential ingredient in America’s success

“Scientific American” showcases the history and future of America’s scientific engine, highlighting promising young scientists and icons at MIT and beyond.

AI helps design new materials that work in the real world

The MIT-developed tool "CrysVCD" uses AI to design new materials that are chemically stable in real-world conditions. By predicting stability early, it can significantly reduce the time and cost associated with testing and discarding unstable material designs.

Wasted large language models: A life cycle thinking approach

The paper argues that large language models (LLMs) have a growing carbon footprint and that current efficiency gains are offset by rebound effects such as Jevons Paradox. It proposes applying the EU waste hierarchy—prevention, reuse, recycling, recovery, and disposal—to LLMs, suggesting that preventing waste and unnecessary use can significantly reduce environmental impact. The authors emphasize that treating LLMs as products that can become waste offers new ways to motivate more sustainable practices.

How an MIT research project became a global programming language

With millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.

MIT in the media: Innovating and educating for the next 250 years of America

During a "Washington Post Live" panel discussion with ASU President Michael Crow, President Sally Kornbluth explored how universities are preparing the next generation of scientists to lead in America’s rapidly changing technological landscape.

Introducing Modular Diffusers - Composable Building Blocks for Diffusion Pipelines