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MIT engineers develop a magnetic transistor for more energy-efficient electronics
Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.
MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity.
The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.
The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.
“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.
Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.
Overcoming the limits
In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.
But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.
To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.
So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.
“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.
The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.
Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”
“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.
They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.
To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.
“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.
Leveraging magnetism
This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.
They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.
The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.
The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.
A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.
“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.
Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.
This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.
Papa Johns Surveillance-Based Advertising
Papa Johns is spying on people’s buying activities to predict when they are low on food:
The pizza chain recently tapped NBCUniversal, Instacart and the dentsu-owned media agency Carat for help reaching consumers when they’re low on groceries—and thus more likely to be swayed by a mouth-watering ad. The idea is to reach hungry consumers by “knowing what is in their fridge without being too creepy,” said Carrie Drinkwater, chief investment officer at Carat.
To achieve that goal, NBCU and Instacart created a custom audience of shoppers who regularly purchase grocery staples on Instacart, such as eggs, milk, meat and produce. Based on that data, Papa Johns can determine which days of the week certain consumers are likely to run out of groceries and serve them an ad on NBCU streaming content accordingly. The brand served custom creatives to consumers based on their food preferences—such as whether they buy meat regularly—with QR codes and calls to action such as, “Light on groceries?” or “Empty fridge?”...
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Publisher Correction: Multi-centennial response of marine carbon pumps to global warming
Nature Climate Change, Published online: 01 July 2026; doi:10.1038/s41558-026-02719-5
Publisher Correction: Multi-centennial response of marine carbon pumps to global warmingThe brain’s language network is more extensive than previously thought
For decades, neuroscientists have known that specific regions in the brain’s left hemisphere are responsible for processing language. However, a new study by MIT researchers shows that language processing also occurs in many other parts of the brain.
Using functional magnetic resonance imaging (fMRI) data from more than 700 people, the researchers identified 17 additional regions of the brain that appear to play a role in language. These regions are scattered across the brain, including parts of the cerebellum, hippocampus, and cerebral cortex, and they make up about 5 percent of the total volume of the adult brain — about the size of a large strawberry.
“Even though there are all these distant components, it’s pretty restricted in terms of volume. You don’t need that much of the brain to do language,” says Evelina Fedorenko, an MIT associate professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research,and the senior author of the study.
Exactly how these regions contribute to language processing is still to be discovered, although the researchers have made some progress toward determining the functions of the cerebellar regions that they identified.
MIT postdoc Agata Wolna is the lead author of the paper, which appears in the Journal of Neuroscience. Other authors include Aaron Wright, a K. Lisa Yang Post-Baccalaureate Research Scholar at MIT; Colton Casto, a graduate student at Harvard University; Samuel Hutchinson, a graduate student at MIT; and Benjamin Lipkin PhD ’26.
Tracking language
The brain’s language processing centers include Broca’s area, first discovered in the 1800s, plus additional regions in the left frontal and temporal lobes of the brain. Scientists have found that some of the corresponding areas of the right hemisphere also contribute to processing language, especially the social-emotional components of language.
There have also been hints that other parts of the brain might be involved in language processing. Early in her career, Fedorenko’s language studies often showed active brain regions outside of the canonical language centers, but she says she was discouraged from including them in her papers.
“When we initially started looking at language, in the first couple of papers, I tried to be comprehensive and include anything that seemed consistent across participants, and there was a huge amount of resistance,” she says. “People would say things like, ‘Well, we know those are not language areas, so please focus on the language areas.’”
In the new study, she and Wolna wanted to revisit those brain scans and see if they could systematically identify language regions outside of the standard language-processing areas.
To do that, they analyzed data from 772 people who had been scanned in Fedorenko’s lab since 2013. Each of these participants underwent a task known as a language localizer, which is used to determine the location of language processing areas for each subject.
During the test, participants read or listen to sentences as well as sequences of nonwords. For each person, the researchers measure the difference in strength of response when reading real sentences or nonsense sequences. The brain areas that work harder during the sentence condition are considered to be doing something relevant to language, especially if they respond while both reading and listening to sentences.
“It’s a very simple paradigm that lets you identify this core language system in individual brains,” Wolna says.
When searching for language areas, the researchers usually use a relatively strict statistical threshold. In this study, they relaxed the threshold and also used some targeted searches in subcortical areas, in hopes of finding all areas that may contribute to language processing.“We always see this frontal temporal network, but there’s quite a lot of evidence that there are other regions that are also critical for language processing,” Wolna says. “By using a laxer threshold and zooming in on areas with weak MRI signal, we tried to maximize the chances of finding small and weakly responsive regions outside of this left frontal temporal system.”
A widespread network
For about 490 of the participants, the researchers also had data on how their brain responded during a spatial working memory task — remembering the locations of flashing squares on a grid. This task engages a brain network called the multiple demand system, which does not overlap with the core language areas.
This task allowed the researchers to ask whether any of the newly identified language-sensitive regions specifically respond to language and not more general cognitive processes.
Of the 17 new language sites that were revealed by this study, five are located in the cerebellum, which is mainly involved in coordinating the body’s movement. In a study published earlier this year, researchers led by Casto found that three of those cerebellar regions also became engaged during some nonlinguistic cognitive tasks, which was also seen in the new study.
“Those areas that respond to both language and some other tasks could be really interesting and important because they may be doing something like integrating information from different cortical systems,” Fedorenko says.
They also found language-selective regions in the medial frontal cortex, the bottom surface of the left temporal lobe, the hippocampus, and the amygdala. The researchers now plan to further study how these brain regions might contribute to language processing.
“We can now test some ideas from past work, and also more rigorously characterize these regions across different kinds of language manipulations, and different kinds of nonlinguistic tasks, to try to understand what it is that they’re doing,” Fedorenko says.
The research was funded by the Simons Center for the Social Brain at MIT, the McGovern Institute, MIT’s Department of Brain and Cognitive Sciences, and the MIT Siegel Family Quest for Intelligence.
MIT-Kalaniyot program expands, with new cohort of scholars
As a new academic year dawns, the MIT-Kalaniyot program is welcoming its second cohort of scholars to campus, expanding an innovative effort to build new connections between MIT and researchers from Israel.
In fall 2026, MIT-Kalaniyot has 11 new scholars arriving at MIT to pursue research, collaborating with Institute faculty across a wide variety of disciplines. They consist of seven new Kalaniyot Postdoctoral Fellows and four new Kalaniyot Sabbatical Scholars, who are faculty on leave from institutions in Israel.
It is another step forward for a program which, less than two years ago was still an idea on a drawing board. The project aims to enhance research and create stronger community ties — not only among those connected to the program, but across the MIT campus.
“The goals of the program are to build academic ties between MIT and Israel, alongside a strong, supportive community,” says Or Hen, an MIT nuclear physicist and a co-founder of MIT-Kalaniyot. “MIT has a mission that revolves around research, education, and entrepreneurship, and MIT-Kalaniyot strengthens MIT, to help meet that mission for the world.”
The scholars will be working on a wide range of topics, including mathematics, materials science, behavioral economics, architecture, modern history, chemistry, quantum computing, and computational methods for examining cellular activity.
“We designed Kalaniyot to strengthen MIT’s research and its community at the same time,” says Ernest Fraenkel, a professor of biological engineering and a co-founder of MIT-Kalaniyot. “We now have scholars in the program working in each of MIT’s five schools. The academic breadth shows our model is working.” MIT-Kalaniyot will also feature its first teaching fellow at the Institute, hosted by MIT’s History program.
MIT-Kalaniyot was founded by Hen and Fraenkel as a constructive response to discord over conflict in the Middle East. Hen is the Class of 1956 Associate Professor of Physics and associate director of the Laboratory for Nuclear Science; Fraenkel is the Grover M. Hermann Professor in Health Sciences and Technology.
Fraenkel and Hen credit multiple members of MIT’s community and upper administration for backing the MIT-Kalaniyot idea from the start, making it feasible for the program to launch.
“When we first shared the idea, we were very encouraged by the response from MIT’s senior leadership,” Fraenkel says. “They understood the value of a faculty-led effort, and their constructive response gave us confidence that our approach could be successful.”
“This would be impossible to do the way we’re doing it without the administration’s support,” Hen says. “The program is faculty-led and institution-backed. That’s what you want.”
Hen adds: “I think MIT today is home to one of the most, if not the most, accepting and welcoming communities for Israelis, and I can stand by that statement very strongly. The way our community grew these past years is remarkable.”
Embedded at MIT
MIT-Kalaniyot, named for a well-known flower that grows in Israel and other parts of the region, welcomed its first cohort of scholars to the MIT campus for the 2025-26 academic year. Hen and Fraenkel also give Tal Cohen, an associate professor in MIT’s Department of Civil and Environmental Engineering, substantial credit for developing the concept.
Scholars at Israel’s nine state-recognized universities are eligible to seek the MIT-Kalaniyot fellowships, which enable research, collaboration, and training at the Institute. The scholars come from a range of academic and personal backgrounds, including both Arab and Jewish citizens of Israel.
The program is highly competitive, with many more applicants than positions currently available. Applicants are encouraged to identify in advance MIT faculty they would like to work with; accepted applicants then already have a “faculty host” lined up. Many of the new fellows will be working with researchers in established MIT labs, for instance.
“When they’re here, they are treated exactly like anybody else in an academic unit at MIT and that’s really important,” Fraenkel says. “They’re embedded in these places.”
The program is also intended to generate the kinds of community connections that help scholars flourish, both professionally and personally. MIT-Kalaniyot features weekly lunches, attended by people from the larger community, where scholars can forge connections and friendship.
The program also features informal academic talks and discussions, with the talks given by MIT researchers both within and outside of MIT-Kalaniyot. Hen, for one, has already seen the benefits of such events; one paper he has recently co-authored directly stemmed from discussions he had at a program event.
“The range of MIT faculty who stepped forward as hosts has been one of the most gratifying parts of the program,” Fraenkel says. “It shows that this is not confined to one field or one corner of the Institute. It is becoming part of MIT’s broader academic life.”
Adds Hen: “I think it sends a very strong and important message. We’re able to move forward at MIT and build collaborative partnerships with strong ties.”
An additional facet of the program is the potential impact of MIT-based research in practical, tangible ways. One of the 2025 fellows, a leading physician, focused her MIT work on new methods of breast cancer detection, and now, back in Israel, is working to apply those findings in active medical settings.
Plans for future growth
Having first taken root at MIT, the MIT-Kalaniyot concept is now spreading to other places. In the last two years, Columbia University, Cornell University, Dartmouth College, Harvard University, the University of Pennsylvania, and the University of Southern California have implemented the concept, with other universities in the process of adopting it as well.
“This national movement all started by replicating the MIT model,” Hen says. “Each university then innovated in their own way. They start from the MIT approach, and then they adapt to what’s happening on their campus. They learn from us, we learn from them, and together we support a broad academic network.”
The progress at MIT and elsewhere has led Hen and Fraenkel to feel optimistic about the ongoing evolution of MIT-Kalaniyot.
“We started at a tense time on our campus, not really knowing what the future would hold, and it’s exceeded our hopes,” Fraenkel says. “Now we want Kalaniyot to become a recognized center at MIT, funding seed grants for research that wouldn’t happen any other way.”
While Fraenkel and Hen do not yet have a firm timetable for those developments, they regard them as being realistic.
“Now we see Kalaniyot as a program that helps MIT well beyond our community,” Hen says. After all, he observes, simply as a vehicle for research, the program has the potential to provide added capacity for MIT, as well as the further connections to top scholars being generated by the effort.
Indeed, Hen reflects, he is motivated the question: “How do we best support MIT in realizing its mission for the world?” Overall, he says, “I think that’s the ultimate goal of Kalaniyot. We do it in one way, other people can do it in other ways, and as long as you do net good, and support the MIT mission, we value and treasure that, and just want to be part of it.”
“I really believe this is the DNA of MIT,” Fraenkel says. “We’re all about finding practical solutions to society’s biggest problems. Kalaniyot brings extraordinary people here to do exactly that, and the whole Institute is stronger for it.”
MIT student teams win top honors in NASA competition
Three teams comprising 35 students across eight different MIT departments and Wellesley College have been at work since fall 2025, designing critical early infrastructure elements that a moon base would require. This June, their designs were recognized with five awards at NASA’s 2026 Revolutionary Aerospace Systems Concepts — Academic Linkage (RASC-AL) Forum.
Among 75 submissions and 14 finalists, the MIT teams earned first and second place in the competition, as well as three best-in-theme awards. The Exploration-Class Lunar Integrated Power SystEm (ECLIPSE) team won first place overall and first in its theme category, lunar surface power. The communications and navigation constellation team, MELIORA, won second place overall and first in its theme category on Mars communications, position navigation and timing, which included a strategy for proving the design at the moon. And CHEESEBURGER, a campaign to mine and process lunar regolith into oxygen, metals, and bricks, won first in its theme category, lunar technology demonstrations.
“NASA spent the spring telling the world what critical early infrastructure their upcoming permanent moon base will need,” says George Lordos, a research scientist and lecturer in the Department of Aeronautics and Astronautics (AeroAstro) and in System Design and Management (SDM), who co-advised all three teams. “Over 30 MIT students spent this academic year designing much of the moon base — systems for generating, storing, and distributing power; robust systems for positioning, navigating, and communicating; and early experiments with essential technologies to live sustainably off the moon’s own dirt.”
A power grid for surviving lunar night and winter
The hardest constraint on NASA’s moon base is staying powered, because a failure in life-support power would doom the crew within hours. ECLIPSE is a reference design for a lunar grid engineered to stay up for more than 99.995 percent of the time — fewer than 27 minutes of downtime a year in the worst-case scenario, the standard demanded of the most critical data centers on Earth. It pairs two power sources that fail in different ways: banks of 20-meter solar masts in the sunlit highlands near the south pole, and, for the roughly 18-day stretch each year when the sun drops below the horizon, a pair of buried 20 kilowatt microreactors the team named CARROT, (Compact Autonomous Regolith-shielded Reactor Operating for Ten years). The CARROT reactor, a novel design developed independently by the ECLIPSE team, ended up being similar in design to NASA’s SR-1 reactor for the 2028 mission to Mars, both aiming to maximize speed-to-deployment.
“Burying each reactor 1.3 meters down shrinks the keep-out zone from kilometers to meters, so crews can work nearby, and it saves tons on required shielding mass,” says Taylor Hampson, a PhD student in the Department of Nuclear Science and Engineering and ECLIPSE team co-lead.
The full design delivers an initial 120 kilowatts using a grid of buried aluminum cables and shielded direct-current power equipment. Laser-equipped rovers provide “Frontier Power” capability, beaming up to 10 kilowatts to sites beyond any cable, from a shadowed crater to a new outpost before its own grid exists. Patrick Riley, a graduate student in the Department of AeroAstro and ECLIPSE team co-lead, says the design’s point is to put reliability ahead of mass: “We sized it so the most likely failures never reach the moon base inhabitants, and so it scales from a first crew of six up to industrial demand without interrupting a commercial lunar economy.”
A network for exploring the moon and Mars, and calling home
MELIORA acts as the base’s relay and GPS. Although RASC-AL framed the communications, positioning, navigation, and timing competition sub-theme around Mars, the team also proposed a plan to validate their design in lunar geometry first, in step with the agency’s strategy to prove technology on the moon before extending it to Mars. To find the best design, the team ran a trade study across 5,764 candidate constellation geometries. The result grows from an initial three satellites to 23, returns more than 100 megabits per second to Earth-orbiting data networks over free-space optical links, and pins a user’s position to within 10 meters. For the Mars design, four relay satellites parked at gravitationally stable Lagrange points keep the link alive even during solar conjunction, the weeks when the sun sits between the two worlds and ordinarily cuts communication. On the surface, a user needs only a portable radio terminal and a chip-scale atomic clock — a timekeeper the size of a matchbox.
“You should never have to think about whether the network is there — it just is, the way you don’t think about a cell tower,” says Ekaterina Tiukhtikova, an undergraduate studying both AeroAstro and electrical engineering and computer science (EECS), and a MELIORA team co-lead. “We put almost all the complexity up in orbit, so everything on the surface stays portable and simple,” adds Clayton Lieberman, a graduate of the SDM program and team co-lead who wrote his thesis on MELIORA.
Making oxygen, metal, and bricks from lunar dirt
After power and communications, the third essential pillar of a lunar base is living off the land. The moon’s own regolith can supply oxygen to breathe and burn, metal to build with, and shielding to hide behind for protection from deadly radiation. CHEESEBURGER is a campaign of five robotic payloads that prove the supply chain one link at a time, followed by integration of the five into the first end-to-end lunar industry.
The payloads carry a kitchen’s worth of names: SWISS prospects for the richest ore, BRIOCHES digs and sorts the regolith, BACON casts it into bricks, GRILLED MEAT melts it electrically to pull out metal and oxygen, and AVOCADO is the robotic builder that stacks the products into structures, including interlocking Moon BRICCSS that shield a habitat from radiation. The food theme was born during a January team outing at Sandwich, Massachusetts. “Naming the prospector SWISS and the metal extractor GRILLED MEAT turned a wall of acronyms into something the whole team could enjoy,” says Cesar Meza, a graduate student in AeroAstro and CHEESEBURGER co-lead. “It sounds like a joke until you see that each acronym clearly describes a serious piece of hardware doing one job in the pipeline.”
Thirty students, eight departments, and three teams for one moon base
More than 30 students contributed across the teams, from AeroAstro, SDM, Nuclear Science and Engineering (NSE), EECS, Mechanical Engineering (MechE), the Technology and Policy Program, the MIT Sloan School of Management, and Earth, Atmospheric and Planetary Sciences (EAPS), along with a student from Wellesley College. Several student mentors and faculty advisors worked across more than one team, which is why ECLIPSE’s grid is sized to power CHEESEBURGER’s processing, CHEESEBURGER’s regolith handling is used to bury and shield ECLIPSE’s grid, and all three projects are designed to translate moon base lessons for a future mission to Mars. The teams were advised by Olivier de Weck, the Apollo Program Professor of Astronautics and Engineering Systems and interim department head of AeroAstro, who led ECLIPSE; Kerri Cahoy, the Sheila Evans Widnall Professor of Aerospace Engineering, who led MELIORA; Jeffrey Hoffman, professor of the practice in AeroAstro and a former NASA astronaut, who led CHEESEBURGER; Koroush Shirvan, Atlantic Richfield Career Development Professor in Energy Studies in Nuclear Science and Engineering, who co-advised ECLIPSE; and Lordos, who co-advised all three. Much of the day-to-day mentorship work is led by PhD student volunteers and runs through the MIT Space Resources Workshop, which Lordos founded in 2019.
“The winning teams demonstrated how academic innovation can support Artemis mission goals,” says Daniel Mazanek, RASC-AL program sponsor and senior space systems engineer at NASA’s Langley Research Center, in NASA's announcement of the awards. “Their work highlights the important role student research plays in shaping future space exploration.”
NASA expects astronauts living on the lunar surface for months at a time by the early 2030s — the window ECLIPSE, MELIORA, and CHEESEBURGER were designed for. The picture the three teams had worked toward is unified: a crew at the lunar south pole, the lights on through the winter night, the network always up, and the first oxygen and bricks coming out of the ground beneath them.
“A permanent base is no longer a slide in a strategy deck; NASA begins landing the first elements in 2027,” says de Weck. “Studies like these three let the agency see, before the concrete sets, how its power, communications, and resource choices depend on one another. That is precisely when independent, integrated architecture work has the most influence on the real plan.”
RASC-AL is administered by the National Institute of Aerospace on behalf of NASA. MIT has a long record in NASA’s student design competitions, with recent winning teams including the HYDRATION Mars water production system, the Pale Red Dot Mars homesteading architecture, the deployable lunar tower MELLTT, the MARTEMIS lunar Mars analog campaign, the MAPLE autonomous lunar robot pathfinding system, the CERBERUZ lunar recycling project, and the THERMOS cryogenic fluid management system. This work was supported in part by NASA, the Massachusetts Space Grant, MIT AeroAstro, and the MIT Space Resources Workshop. One student was supported by a NASA Space Technology Graduate Research Opportunity Fellowship.
The full teams:
ECLIPSE — Team leads: Taylor Hampson (graduate student, Nuclear Science and Engineering) and Patrick Riley (graduate student, AeroAstro). Reactor team: Liliana Arias, Sydney Menne, Julian Rocher and Pavel Shilenko (graduate students, NSE). Power management and distribution team: Evrard Constant and Mary Foxen (graduate students, AeroAstro), Janhavi Joglekar and Asma Patel (undergraduate students, AeroAstro). Solar and architecture team: Zachary Dawson (graduate student, System Design and Management), Sreeja Akula and Ian Jimenez (undergraduate students, AeroAstro; EAPS), Yohan Lim (graduate student, AeroAstro/Technology and Policy Program), CJ Taglienti (graduate student, AeroAstro/MBA). Student co-advisors: Yana Charoenboonvivat, Lanie McKinney (AeroAstro), Palak Patel (MechE). Industry mentor: Sully Marigliano-Crevecoeur (Technetics). Faculty: Olivier de Weck (lead) and Jeffrey Hoffman (AeroAstro), George Lordos (AeroAstro and SDM), and Koroush Shirvan (NSE).
MELIORA — Team leads: Clayton Lieberman and Katiyayni Balachandran (System Design and Management), Ekaterina Tiukhtikova (undergraduate, AeroAstro and EECS), Celvi Lisy (AeroAstro). Team members: Thomas Harrington and Zachary T. Barnes (SDM), Asael Acosta (undergraduate, AeroAstro). Student co-advisor: Lanie McKinnery (AeroAstro). Faculty: Kerri Cahoy (lead), Jeffrey Hoffman and Olivier de Weck (AeroAstro), and George Lordos (AeroAstro and SDM).
CHEESEBURGER — Team leads: Cesar Meza (graduate student, AeroAstro) and Elizabeth Romero (undergraduate, AeroAstro). Team members: Rachel Dunphy, Shreya Kothnur, Hailey Polson (undergraduates, AeroAstro), Christopher Kwon, Jose Soto, Lanie McKinney (graduate students, AeroAstro), Marvin Martinez (undergraduate, MechE), Ananda Santos Figueiredo (graduate student, Technology and Policy Program), Evangeline Haiqi Wang (undergraduate, Computer Science and Psychology, Wellesley College). Faculty: Jeffrey Hoffman (lead) and Olivier de Weck (AeroAstro), and George Lordos (AeroAstro and SDM).
MIT researchers advance toward greater bandwidth, more energy-efficient communications
An MIT-led research program aimed at creating future microsystems capable of sustainably transmitting data with greater bandwidth and higher efficiency than is possible today has made several significant advances since it was established in 2022.
These include the invention of devices within systems that can much more easily integrate electronics — manipulating data with electricity — with photonics, which does the same with light. The microsystems, the first of their kind, also promise to be cost-effective because, among other advantages, they can be manufactured using existing equipment in traditional electronics foundries and packaging houses.
“Our disruptive electronic-photonic integrated solutions will enable us to leap from [transmitting data at] hundreds of terabits per second to greater than 1 petabit per second,” said Anu Agarwal, who leads MIT’s FUTUR-IC, at an April webinar titled, “Shaping the Future of Semiconductors: Power, Performance, and Possibility.” The event was sponsored by the MIT Industrial Liaison Program and Startup Exchange.
An advanced system using co-packaged optics can provide improved bandwidth and energy savings compared to what is used today, which is electronics-only or pluggable optics.
Toward sustainability
The microchips behind everything from smartphones to medical imaging can be traced to about 500 megatons of carbon dioxide-equivalent lifetime emissions in 2021, and every year the world produces more than 50 million tons of electronic waste. Further, the huge data centers necessary for complex computations like on-demand video are growing, and will require close to 10 percent of the world’s electricity by 2030.
“This is neither scalable nor sustainable, and cannot continue,” Agarwal has reiterated over the years. FUTUR-IC, funded by the National Science Foundation Convergence Accelerator, was created to address these resource-efficiency issues.
For example, integrating photonics with the electronics that underpin today’s microchips could address energy use because the transmission, or communication of data, using light is much more energy efficient. “Our mantra is to use electronics for computation and photonics for communication to bring this energy crisis under control,” says Agarwal.
Currently, however, it is difficult and expensive to connect electronic chips with their photonic counterparts within a single package. That’s partly because the supply-chain ecosystem for co-packaged optics is still immature.
New devices
Enter two new devices developed through FUTUR-IC aimed at making it easier — and less expensive — to integrate photonic chips with microchips. One, the evanescent coupler, was featured on the cover of Advanced Engineering Materials last year. Another, known as the graded index coupler (GRIN), was reported in the March 2026 print issue of the Journal of Physics: Photonics.
A third new coupler was developed by an MIT team led by Professor Juejun Hu of the Department of Materials Science and Engineering. It was reported in a 2023 issue of Laser & Photonics Reviews. That work was supported by the Department of Energy.
The three couplers are the first optical equivalents of “solder bumps,” or the tiny dots of metal that allow chip-to-chip or chip-to-substrate connections for electron flow. Until this MIT work, there were no analogous “optical bump” options for photonics.
And if photonics is to be integrated with electronics, “you’ll need both metal bumps and optical bumps, because there are devices on your photonics chip that will require both an electrical signal and an optical signal,” says Drew Weninger PhD ’25, first author of the papers on both the evanescent and GRIN couplers. Weninger is now at the National Institute of Standards and Technology.
As with electronics, many options of optical bumps will be necessary, as “each type has substantial trade-offs,” wrote Weninger and colleagues in a review article in Nature about coupler advances published earlier this year.
For example, the GRIN coupler can be used over a wider spectrum of light than is possible with the evanescent coupler, Weninger says. The evanescent coupler, however, is easier to fabricate and can be packed in tighter to form a higher number of connections.
Additional advances
FUTUR-IC is organized into three dimensions: Technology (the coupler work is a good example), Value Chain Innovation, and Workforce.
Under the Value Chain sector, researchers developed a new tool to support companies’ decisions toward sustainability. Earthster provides a visual model for quickly determining the energy, materials usage, and environmental sustainability across a company’s products. For example, says Agarwal, “looking at [Earthster], a supplier can tell right away their hot spots for carbon emissions, and start working to minimize them.”
FUTUR-IC has also developed several programs aimed at developing a future workforce for next-generation microchips. For example, “it is introducing an online course on semiconductor resource efficiency,” Agarwal says. “We also offer gamified digital learning and problem-based learning, plus a summer academy and a hands-on bootcamp.” For K-12 awareness, FUTUR-IC has created TED-Ed videos.
Agarwal concluded her April webinar by acknowledging the range of industries FUTUR-IC aims to help. “If you’re a packaging vendor, a materials vendor, or you are in the supply chain for data centers, FUTUR-IC can provide value.”
Additional authors of the paper on the GRIN coupler are Agarwal; Lionel Kimerling, the Thomas Lord Professor in the Department of Materials Science and Engineering; Christian Duessel BS ’25, now at SiLC Technologies, a silicon photonics company; and Samuel Serna, professor of physics, photonics, and optical engineering at Bridgewater State University.
Additional authors of the Nature review paper are Serna; Luigi Ranno PhD ’25, now at Ayar Labs; Kimerling; and Agarwal.
Q&A: What is agentic AI today, and what do we want it to be?
The deployment of automated software systems called AI agents has recently exploded. A November 2025 report by MIT Sloan School of Management and Boston Consulting Group found that 35 percent of surveyed businesses had already deployed AI agents, while another 44 percent planned to implement agentic AI soon.
To understand the fundamentals and potential impacts of these increasingly popular tools, MIT News spoke with Phillip Isola, an associate professor in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), who studies the intelligence AI agents possess, as well as the underlying models and mechanisms that power agentic AI systems.
Q: What is agentic AI and how is it different from generative AI models like ChatGPT and Claude?
A: Agentic AI is AI that takes actions in the world. These actions could be a physical action, like robotic manipulation, or a digital action, like booking a flight. On the other hand, we think of generative AI as making up stories, poems, art, and images, rather than taking actions for us.
The word “agent” is just a brand name. It usually means AI that is going to help people interact with an application, a website, or the physical world. Most agents we encounter today are digital agents, like customer service agents you can talk with about product complaints.
Most companies that offer agents use the same few AI models under the hood and give them the ability to take actions and remember what happened. An agent starts with a fundamental generative AI system, like Claude, at the core. Then companies put different wrappers around that foundation model for their product or application. Those wrappers might be specific tools that agent can use, and those tools depend on the application. Maybe the agent has access to a calculator so it can solve math problems, or maybe it has access to a more complicated hard drive and operating system so it can remember a firm’s financial data and past business negotiations.
The biggest challenge in developing agentic AI comes from a lack of training data. If I want to create a system that can go online and book a flight for me, that seems pretty simple. But we don’t have a lot of data that spells out exactly how to do that — where to move the mouse, which buttons to click on, what to do if something goes wrong, or how to call somebody and negotiate about the price of the airline ticket. One way to train a system like this is to have the AI agent visit airline websites, try things out, and see what works and what doesn’t work. These environments are hard to model, so often the agent must learn by trial and error.
Q: What are some promising applications of agentic AI?
A: I think the area where we’ve seen the most success has been with coding agents. This is something that evolved from generative AI. People trained language models on code, and then they can predict what a human would do to solve a coding problem. In addition, an agent can learn to do this by going through a feedback loop where it tries out different solutions and checks to see if it got the answer right. As long as it can check the answer, the AI agent can perform this trial-and-error loop until it figures out a good strategy.
But there is always a balance between automating decision making versus simply assisting and informing humans. Analytical AI methods, like the systems that help predict possible outcomes of decisions, are not agentic in nature, but are very informative to human decision-makers. For cases that are either high-stakes or safety-critical, like medicine, security, high-level business policies, etc., the technology might not be ready for AI to completely automate those processes, or we might not even be comfortable with that.
Q: Are there risks we should be thinking about when using AI agents?
A: One big risk area comes from the fact that it is often very easy to get agents to do certain types of work for you. With coding agents, you can “vibe code” and just ask the agent to make a code for you, so you don’t have to do the hard work yourself. There is a big risk that, because it is so easy, people will not put enough effort into verifying that it is doing the right thing. Bugs will be introduced, private data will get leaked — this is already happening.
Agents aren’t perfect, in the sense that they might make mistakes because they are not well-trained and don’t know what to do. But even if they are very competent, if a human doesn’t use them appropriately or gives them an instruction that is too vague, the AI agent could make a mistake because the human made a mistake. If humans are less involved in thinking through all the consequences, I think we might be more prone to making those mistakes.
An additional aspect is the risk of de-skilling. It is unclear how far this will go, but when we are relying on agents to do our homework, our coding, and our math, we might lose the ability to do that ourselves, and we might lose that ability too soon because the technology is not yet ready to fully automate those processes.
Q: What does the future hold for agentic AI?
A: What we think of now as agentic AI refers to large language models using tools to interact with digital and physical systems. One obvious limitation is that, under the hood, these have the architecture of a language model and are trained on text data. To make even more powerful AI agents, we might need to model videos, physical forces, time series, radar scans, and other modalities. We might need to have models with fundamentally different architectures that can handle continuous data, high-dimensional data, stochastic data, and so on.
But, on the other hand, maybe an extremely good coding model could act as a puppeteer to interface with sensors, actuators, and web APIs? Perhaps, once you have a super-smart reasoning system that understands math, language, and code, you can give it a camera and a keyboard and it will figure out what to do in the spatial domain. Is the next wave of AI just going to be Claude with sensors, actuators, and tools, or is it going to be something built in a new way from the ground up? That’s the big question a lot of people in AI are grappling with right now.
The Realities of AI Video Surveillance
The Financial Times has a good article on how AI is changing the capabilities of video surveillance, with information from both Israel/Iran and Russia.
I wrote about this sort of thing a few years ago, how AI enables mass spying in the way that computers and networks enabled mass surveillance. The interesting development in the article is that AI allows people to ask natural language questions about video footage to AIs—and AIs can answer them.
In contrast with older tools restricted to a few dozen preset searches, these new tools allow an almost unlimited range of enquiries by enabling language-based searches on video...
