Taking the “training wheels” off clean energy
At the 2025 MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
At the 2025 MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
The MIT-GE Vernova Energy and Climate Alliance includes research, education, and career opportunities across the Institute.
With the new system, farmers could significantly cut their use of pesticides and fertilizers, saving money and reducing runoff.
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.
For the past decade, the Abdul Latif Jameel Water and Food Systems Lab has strengthened MIT faculty efforts in water and food research and innovation.
The nitrogen product developed by the company, which was co-founded by Professor Chris Voigt, is being used across millions of acres of American farmland.
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
With technology developed at MIT, 6K is helping to bring critical materials production back to the U.S. without toxic byproducts.
The company builds water recycling, treatment, and purification solutions for some of the world’s largest brands.
The course challenges students to commercialize technologies and ideas in one whirlwind semester. Alumni of the class have founded more than 150 companies.
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
Special report describes targets for advancing technologically feasible and economically viable strategies.
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
Using the Earth itself as a chemical reactor could reduce the need for fossil-fuel-powered chemical plants.
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.