Materials science and engineering
Materials science and engineering

Materials science and engineering

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.

Artificial Intelligence Batteries Cleaner industry Climate Computer science and technology Electronics Energy health Industry Innovation and Entrepreneurship (I&E) Materials science and engineering MIT.nano Nanoscience and nanotechnology Photonics Quantum Computing School of Engineering School of Science Semiconductors Startups Superconductivity Technology and society

Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano

Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.

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 Biology Civil and environmental engineering Computational biology Health sciences and technology Materials science and engineering Mechanical engineering MIT-IBM Watson AI Lab Proteins Research School of Engineering Synthetic biology

MIT engineers design proteins by their motion, not just their shape

An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.

Algorithms Artificial Intelligence Astronomy and astrophysics chemistry Computer science and technology Data Faculty IDSS Interview Laboratory for Nuclear Science machine learning Materials science and engineering Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Physics Research School of Science

3 Questions: On the future of AI and the mathematical and physical sciences

Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.

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 Computer chips Computer science and technology Electrical engineering and computer science (EECS) Electronics Energy Materials science and engineering Microsystems Technology Laboratories MIT Schwarzman College of Computing MIT.nano Nanoscience and nanotechnology Research School of Engineering Sustainable computing

New materials could boost the energy efficiency of microelectronics

By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.

Artificial Intelligence Imaging Light machine learning Manufacturing Materials science and engineering Mechanical engineering Research School of Engineering

Checking the quality of materials just got easier with a new AI tool

Acting as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.

3-D printing Artificial Intelligence machine learning Materials science and engineering Mechanical engineering Research School of Engineering

Printable aluminum alloy sets strength records, may enable lighter aircraft parts

Incorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.