Computer modeling
Computer modeling

Computer modeling

Algorithms Artificial Intelligence Climate Computer modeling IDSS machine learning Mechanical engineering MIT Schwarzman College of Computing Natural disasters Research School of Engineering Sustainability Weather

Generating scenarios for extreme events, without extreme data

A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.

Agriculture Artificial Intelligence chemistry Cleaner industry Computer modeling DMSE Emissions Food Industry machine learning Materials science and engineering Nuclear science and engineering Pollution Research School of Engineering School of Science Sustainability

Paving the way for greener ammonia production

New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.

3-D imaging Artificial Intelligence Computer graphics Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) Human-computer interaction Manufacturing MIT Schwarzman College of Computing Research School of Engineering Simulation

With a feel for physics, AI models simulate a wider range of real-world scenarios

“GeoPT” helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately.

Artificial Intelligence Batteries Computer modeling DMSE Electric vehicles Energy storage Lithium-ion Materials science and engineering MIT.nano National Science Foundation (NSF) Nuclear science and engineering Renewable energy Research School of Engineering Transportation

Solving the solvent problem

By focusing on electrolytes, MIT scientists are making sodium-metal batteries a more practical energy storage option.

Artificial Intelligence Automation Awards, honors and fellowships Computer modeling Department of Energy (DoE) Energy Graduate, postdoctoral Human-computer interaction Mechanical engineering Nuclear power and reactors Nuclear science and engineering Profile Renewable energy Research ROTC School of Engineering Software Students U.S. Armed Forces

Working to automate nuclear plant operations

PhD student Lauren Fortier is building on the experience she gained operating a nuclear plant for the Navy to solve a critical hurdle in the wider adoption of the energy source.

Algorithms Artificial Intelligence Computer modeling Computer science and technology Design machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Computing Research Lab Research School of Engineering Systems design

A better way to turn 2D designs into 3D models for rapid prototyping

Researchers developed an automated framework that helps AI models generate CAD programs more accurately and efficiently.

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 Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning Mathematics MIT Schwarzman College of Computing Research School of Engineering

When it comes to predicting people’s preferences, it pays to consider “the power of three”

MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.

Artificial Intelligence Computer modeling Energy Faculty machine learning Nuclear power and reactors Nuclear science and engineering Profile Renewable energy School of Engineering Sustainability

Working to advance the nuclear renaissance

Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.

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.