DMSE
DMSE

DMSE

Artificial Intelligence Chemical engineering chemistry Computer modeling Computer science and technology DMSE machine learning Materials science and engineering Research School of Engineering

A better way to model the behavior of metal alloys

MIT researchers’ approach captures subtle atomic patterns, improving predictions of material properties.

Algorithms Artificial Intelligence Astronomy and astrophysics chemistry Collaboration Computer science and technology Data DMSE Funding IDSS machine learning Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Physics Research School of Engineering School of Science

NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery

IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.

Artificial Intelligence Batteries Computer modeling Department of Energy (DoE) DMSE Electrical engineering and computer science (EECS) machine learning Manufacturing Materials science and engineering Nanoscience and nanotechnology National Science Foundation (NSF) Nuclear science and engineering Research School of Engineering Semiconductors Solar

MIT researchers use AI to uncover atomic defects in materials

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

Artificial Intelligence DMSE Faculty machine learning Materials science and engineering Profile Research School of Engineering

Accelerating science with AI and simulations

Associate Professor Rafael Gómez-Bombarelli has spent his career applying AI to improve scientific discovery. Now he believes we are at an inflection point.

Artificial Intelligence Chemical engineering Computer science and technology DMSE machine learning Materials science and engineering National Science Foundation (NSF) Research School of Engineering

How generative AI can help scientists synthesize complex materials

MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.

Artificial Intelligence Batteries Carbon dioxide chemistry Cleaner industry Climate change Collaboration DMSE Electric grid Energy Energy storage Faculty Government Infrastructure Innovation and Entrepreneurship (I&E) Mechanical engineering MIT Energy Initiative Policy Renewable energy School of Engineering School of Science Special events and guest speakers Startups Students Sustainability The Engine Transportation

MIT Energy Initiative conference spotlights research priorities amidst a changing energy landscape

Industry leaders agree collaboration is key to advancing critical technologies.

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The brain power behind sustainable AI

PhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.

Artificial Intelligence DMSE Energy machine learning Materials science and engineering MIT.nano Nanoscience and nanotechnology Nuclear science and engineering Research School of Engineering

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.

Aeronautical and astronautical engineering Artificial Intelligence Computer modeling Computer science and technology Department of Energy (DoE) DMSE Electrical engineering and computer science (EECS) machine learning Mathematics Mechanical engineering MIT Schwarzman College of Computing Research School of Engineering School of Science Security studies and military Space Supercomputing

DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.

Alternative energy Artificial Intelligence Chemical engineering DMSE Electrical engineering and computer science (EECS) Emissions Energy Energy efficiency Faculty Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory MIT Energy Initiative Renewable energy School of Engineering Special events and guest speakers Staff Sustainability

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.