How artificial intelligence can help achieve a clean energy future
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
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
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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
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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
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MIT engineers created a carbon-cement supercapacitor that can store large amounts of energy. Made of just cement, water, and carbon black, the device could form the basis for
By utilising off-peak tariffs and incorporating various energy-saving features, modern storage heaters are significantly cheaper to run than standard electric heaters or central heating systems.
MIT Energy Initiative researchers calculated the economic and environmental impact of future ammonia energy production and trade pathways.
At the MIT Energy Initiative''s Annual Research Conference, industry leaders agreed collaboration is key to advancing critical technologies amidst a changing energy landscape.
Founded by a team from MIT, Lamarr.AI utilizes drones, thermal imaging, and AI to identify energy waste and structural issues in buildings and recommend retrofits.
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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
Geothermal energy, a clean, continuous energy source accessible in many locations, has been slow to catch on. Nearly 2,000 years ago, the Romans made extensive use of geothermal
MIT News explores the environmental and sustainability implications of generative AI technologies and applications.
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