Agreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
As the use of generative AI continues to grow, Lincoln Laboratory's Vijay Gadepally describes what researchers and consumers can do to help mitigate its environmental impact.
At the MITEI Fall Colloquium, the administrator of the US Energy Information Administration explained why long-term energy models are not forecasting tools — and why they’re still vitally important.
MIT engineers developed the largest open-source dataset of car designs, including their aerodynamics, that could speed design of eco-friendly cars and electric vehicles.
Because it doesn’t need expensive energy storage for times without sunshine, the technology could provide communities with drinking water at low costs.
Anthropologists Manduhai Buyandelger and Lauren Bonilla discuss the humanistic perspective they bring to a project that is yielding promising results.
MIT startup AeroShield has opened a new facility for manufacturing highly insulating windows that will reduce building energy use and cut carbon emissions.
The MIT Electric Vehicle Team, Sustainable Engine Team, Solar Electric Vehicle Team, Motorsports Team, First Nations Launch Team, and Arcturus are each doing their part to improve the health of our planet.
MIT engineers have developed a fast and sustainable method for producing hydrogen fuel using aluminum, saltwater, and coffee grounds.
MIT spinout SiTration looks to disrupt industries with a revolutionary process for recovering and extracting critical materials.
With laser-based precision tools for measuring and tuning materials, MIT spinout Optigon aims to rev up the energy transition.
At the 2023 Clean Energy Education and Empowerment symposium, participants emphasize working together to achieve net zero emissions by 2050.
A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.
The findings, based on a single electrochemical process, could help cut emissions from the hardest-to-decarbonize industries, such as steel and cement.