Energy
Energy

Energy

Aeronautical and astronautical engineering Artificial Intelligence Computer modeling Energy Fluid dynamics Fusion Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Nuclear power and reactors Plasma Science and Fusion Center Renewable energy Research School of Engineering Sustainability

New prediction model could improve the reliability of fusion power plants

The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.

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Lincoln Lab unveils the most powerful AI supercomputer at any US university

Optimized for generative AI, TX-GAIN is driving innovation in biodefense, materials discovery, cybersecurity, and other areas of research and development.

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Responding to the climate impact of generative AI

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.

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AI system learns from many types of scientific information and runs experiments to discover new materials

The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.

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New tool makes generative AI models more likely to create breakthrough materials

With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.

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Model predicts long-term effects of nuclear waste on underground disposal systems

The simulations matched results from an underground lab experiment in Switzerland, suggesting modeling could be used to validate the safety of nuclear disposal sites.

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Confronting the AI/energy conundrum

The MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.

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The MIT-Portugal Program enters Phase 4

New phase will support continued exploration of ideas and solutions in fields ranging from AI to nanotech to climate — with emphasis on educational exchanges and entrepreneurship.

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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.

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Puzzling out climate change

Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.