Researchers at MIT have developed a new method that can predict how plasma will behave in a tokamak reactor “given a set of initial conditions,” reports Gayoung Lee for Gizmodo. The finding “may have lowered one of the major barriers to achieving large-scale nuclear fusion,” explains Lee.
Prof. Caitlin Mueller has been named Innovator of the Year by Architectural Record for her work advancing a “vision for building design and construction that unites these disciplines with computation to create structure that are sustainable, high performing, and delightful,” reports Architectural Record. “Her group develops computational design and digital fabrication methods that integrate efficiency, performance, material circularity, and architectural expression,” Architectural Record notes. “This work spans robotic assembly of optimized trusses, fabrication of low-cost earthen and concrete systems, and algorithmic strategies for reusing salvaged wood and reassembled concrete parts.”
Architect reporter Blaine Brownell spotlights Prof. Caitlin Mueller’s work repurposing “discarded tree forks from urban forestry projects [and] repurposing the nodes as structural joints in hybrid reclaimed-engineered wood constructions.” Mueller and her team have “developed computer programs to catalog 3D scans of the tree forks as well as determine the appropriate cuts for their intended structural applications,” explains Brownell. “An algorithm matches prepared tree forks to three-dimensional intersections in the intended structural framework, streamlining the design process.”
A study by Prof. Noelle Selin has found that climate change will impact our ability to curb smoke and smog pollutants, reports Vivian La for WBUR. The researchers “used computer models to predict how air pollution will develop in the Eastern United States over the next few decades,” explains La. Selin underscored the importance of policies that reduce air pollution noting that: “what we’re doing to the atmosphere has impacts and it’s important not to roll these back.”
MIT astronomers have found evidence that a massive asteroid impact billions of years ago “may have briefly amplified the moon's old, weak magnetic field, leaving behind a magnetic imprint still detectable in lunar rocks,” reports Sharmila Kuthunur for Space.com. “While the moon once had a weak magnetic field generated by a small molten core, the team's research suggests it likely wouldn't have been strong enough on its own to magnetize surface rocks,” Kuthunur explains. “However, a massive asteroid impact may have changed that — at least briefly.”
Ars Technica reporter Jennifer Oulette writes that MIT researchers have found that a “large asteroid impact briefly boosted the Moon's early weak magnetic field—and that this spike is what is recorded in some lunar samples.”
Mohamed Elrefaie speaks with Automotive World reporter Will Girling about his work developing an open-source dataset of 8,000 car designs, including their aerodynamic characteristics, which could be used to develop novel car designs in a more efficient manner. “If an automaker wants to reduce drag and improve performance, it can guide the GenAI model to produce those specific designs,” Elrefaie explains. “The standard development cycle for a design using legacy tools can take anywhere from three to five years, as it requires collaboration between many specialized departments. With AI, you could validate up to 600 designs in just one or two minutes.”
Researchers at MIT and elsewhere have found that the sun’s magnetic field “could form much closer to the star’s surface than previously thought,” reports Will Sullivan for Smithsonian Magazine. “The findings could help improve forecasts of solar activity that can affect satellites, power grids and communications systems on Earth—and produce magnificent auroras,” explains Sullivan.
Researchers at MIT and elsewhere have developed a new machine-learning model capable of “predicting a physical system’s phase or state,” report Kyle Wiggers and Devin Coldewey for TechCrunch.
MIT researchers have developed a new technique that uses a large language model to allow robots to self-correct after making a mistake, reports Brian Heater for TechCrunch. “Researchers behind the study note that while imitation learning (learning to do a task through observation) is popular in the world of home robotics, it often can’t account for the countless small environmental variations that can interfere with regular operation, thus requiring a system to restart from square one,” writes Heater. “The new research addresses this, in part, by breaking demonstrations into smaller subsets."
MIT researchers are hoping to use Dyson maps “to translate the language of classical physics into terms that a quantum computer—a machine designed to solve complex quandaries by leveraging the unique properties of quantum particles—can understand,” reports Darren Orf for Popular Mechanics.
MIT researchers have developed SoftZoo, “an open framework platform that simulated a variety of 3D model animals performing specific tasks in multiple environmental settings,” reports Andrew Paul for Popular Science. “This computational approach to co-designing the soft robot bodies and their brains (that is, their controllers) opens the door to rapidly creating customized machines that are designed for a specific task,” says CSAIL director, Prof. Daniela Rus.
Researchers at MIT have developed “SoftZoo,” a platform designed to “study the physics, look and locomotion and other aspects of different soft robot models,” reports Brian Heater for TechCrunch. “Dragonflies can perform very agile maneuvers that other flying creatures cannot complete because they have special structures on their wings that change their center of mass when they fly,” says graduate student Tsun-Hsuan Wang. “Our platform optimizes locomotion the same way a dragonfly is naturally more adept at working through its surroundings.”
National Geographic reporter Maya Wei-Haas explores how the ancient art of origami is being applied to fields such a robotics, medicine and space exploration. Wei-Haas notes that Prof. Daniela Rus and her team developed a robot that can fold to fit inside a pill capsule, while Prof. Erik Demaine has designed complex, curving fold patterns. “You get these really impressive 3D forms with very simple creasing,” says Demaine.
MIT researchers have created Thesan, the most detailed model of the early universe to date, reports New Scientist. “Thesan shows how radiation shaped the universe from 400,000 to 1 billion years after the Big Bang,” writes New Scientist.