A look at how AI can be used to help support the clean energy transition by helping to manage power grid operations, plan infrastructure investments, guide the development of novel materials, and more.
At the MIT Energy Initiative’s Annual Research Conference, industry leaders agreed collaboration is key to advancing critical technologies amidst a changing energy landscape.
The new Schmidt Laboratory for Materials in Nuclear Technologies (LMNT) at the MIT Plasma Science and Fusion Center accelerates fusion materials testing using cyclotron proton beam irradiation, advancing fusion energy, nuclear power, and clean energy research at MIT.
MIT engineers developed a membrane that filters the components of crude oil by their molecular size, an advance that could dramatically reduce the amount of energy needed for crude oil fractionation.
New research emphasizes the importance of well-validated models and forecasting tools in evaluating choices for investments in clean energy technologies and policies by governments and companies.
MIT researchers developed a new fabrication method that could enable them to stack multiple active components, like transistors and memory units, on top of an existing circuit, which would improve the energy efficiency of electronic devices.
At the 2025 student-led MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
The MIT-GE Vernova Climate and Energy Alliance, a five-year collaboration between MIT and GE Vernova, aims to accelerate the energy transition and scale new innovations.
The MIT Energy Initiative's annual research spring symposium explored artificial intelligence as both a problem and solution for the clean energy transition.