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.

When Francis Wang ’21, MEng ’22 first joined the MIT Edgerton Center’s Solar Electric Vehicle Team (SEVT), his approach to engineering projects was “to focus my energy and attention on a tidy problem with neat boundaries that I could completely control.”

“But on Solar Car, I realized it takes a very different mindset to manage a substantial project with many moving pieces. It takes engineering leadership,” he recalls.

Wang was determined to strengthen his leadership skills. When he became Solar Car captain, he applied and was accepted into the Gordon Engineering Leadership (GEL) Program.

GEL’s courses and hands-on labs equip students with capabilities they need to lead and contribute to complex, real-world engineering challenges. The one- or two-year program for juniors and seniors complements MIT’s technical education, teaching teamwork, leadership, and communication skills in an engineering context. GEL students also benefit from personalized coaching, mentoring, industry networking, and career support throughout their professional lives.

“Before GEL, I saw the leadership parts of my role as a necessary evil to get to the actual interesting parts, which was the engineering,” says Wang. “The GEL Program gave me an understanding of how engineering leadership is crucial, because in the real world any project worth working on is larger than the scope of an individual engineer.”

In GEL he improved capabilities such as decision-making, taking initiative, and negotiating. He became a more effective SEVT team captain, able to navigate the challenges of taking an engineering project from concept to completion.

“It was often the case that the challenges I faced on Solar Car were not solely technical, involving aspects of communication, coordination, and negotiation. From GEL, I had the framework and the language to approach them,” says Wang.

Each year, 30-40 Edgerton students are accepted into the GEL Program. They come from a variety of teams and clubs including Arcturus, Assistive Technology Club, ChemE Club, Combat Robotics Club, Design Build Fly (DBF), Design for America, Electric Vehicle Team, Engineers Without Borders, First Nations Launch, MIT Electronics Research Society (MITERS), Motorsports, Robotics Team, Rocket Team, and Solar Electric Vehicle Team (SEVT).

“MIT’s best engineering students have GEL training and authentic project management experience with our competition teams,” says Professor J. Kim Vandiver, director of the Edgerton Center.

Edgerton project teams are entirely student-run organizations responsible for all levels of project and team management including fundraising, recruiting, designing, testing, risk mitigation, and project validation. The most successful teams have skilled leaders.

“Many of the excellent Edgerton project team students admitted to GEL are team or sub-team leaders who credit their GEL experience, particularly the experiential learning component, with improving their leadership skills,” says Leo McGonagle, executive director of GEL.

“It’s a win-win-win. GEL gets hard-working, motivated Edgerton Program students who are intent on self-development and improvement. Edgerton project teams often perform better with leaders who are GEL-trained. And the students gain leadership, teamwork, and communication abilities that they can use beyond their project team — in their capstones, course projects, internships, and jobs after MIT,” says McGonagle.

The overlapping connection between GEL and Edgerton truly becomes obvious when students begin to take ownership of project milestones.

“When you become the leader of a technical project, no one gives you a roadmap to team success,” says senior Hailey Polson, former captain of First Nations Launch team. “Technical expertise is not enough to leverage the talent and skills of an entire team or the ability to coordinate a multifaceted project; that’s where the tools, skills, and leadership theory I learned in GEL helped me bridge the gap between knowing how to accomplish our goals and actually leading my team successfully.”

Faris Elnager ’25 served as testing lead on the Motorsports team, which designs, manufactures, and competes with a formula-style electric race car every year.

“Making tough decisions was something that I learned in GEL. On Motorsports, I had to make high-stakes decisions about testing time that affected how we performed at a competition,” he says.

He found that GEL’s weekly Engineering Leadership Labs were a way to test for himself specific leadership capabilities that he could use to improve his Motorsports team.

“One of the most useful skills from GEL was evaluating your stakeholders and learning how to balance their needs. I remember thinking, we’re doing this right now in the [GEL] lab, and then we’re going back to the [Edgerton] shop to do this for real!” says Elnager. “It’s like a positive feedback loop. GEL labs make you better on project teams, and project teams make you better in GEL.”

Now a startup co-founder, Elnager says that the communication skills that he learned through Motorsports and GEL have been critical to his company’s early success. “You can build the best tech in the world. If you can’t pitch it to people, you’re never going to raise any money. Being able to explain a technical project to anyone, whether they're an investor or someone in your industry, is something that’s incredibly valuable.”

Adrienne Lai ’25 served as both mechanical lead and then captain of the Solar Electric Vehicle Team. She recalls how her GEL training would kick in on race day.

“It’s quite tricky to be captain of a build team, because there’s no adult to tell you what to do. You have to figure it all out for yourself. When you’re competing, it can be very chaotic. You are trying to maximize a score by driving more miles, but that comes with a trade-off of spending energy or ending the day in a more rural area, or with less sun, so there are a lot of trade-offs to consider. Sometimes someone just has to make a decision. I was very comfortable doing that because I had learned how to take initiative, which is one of the GEL capabilities,” she says.

Now a course assistant in GEL, Lai helps design scenarios that enable GEL students to become better and more resilient leaders. She particularly enjoys playing the role of an uncooperative supplier.

“We close our store randomly. We don’t have what they need. We won’t tell them what we have,” she laughs. “Students get very frustrated. They think that we’re just being mean. But from a real-world perspective, that is all very true. It simulates unpredictability, which is important not just in a job, but in life.”

The value of the engineering leadership skills learned in GEL and honed on Edgerton project teams carries forward into industry, graduate studies, and entrepreneurial ventures.

“GEL preparation, coupled with authentic project management on a competition team, prepares MIT students for great careers in industry,” says Vandiver.

Henry Smith ’25 says he still relies on skills such as negotiation, communication, and understanding stakeholder needs that he used when he was a Motorsports mechanical lead.

“I was doing high-level management, planning, and organization on the team. Being in the GEL Program really increased my value for the team and helped me be prepared to enter the job field. When I graduated, I wasn’t worried about being ready or not. It was a definite yes,” says Smith.

As project teams continue to address ambitious engineering challenges, the synergy between Edgerton and the Gordon Engineering Leadership (GEL) Program ensures that as students graduate, they’re prepared to not only become strong technical contributors, but confident leaders prepared to tackle complex engineering problems in the real world.

Some genetic mutations that are expected to completely stop a gene from working surprisingly cause only mild or even no symptoms. Researchers in previous studies have discovered one reason why: Cells can ramp up the activity of other genes that perform similar functions to make up for the loss of an important gene’s function. 

A new study published Feb. 12 in the journal Science by researchers in the lab of Jonathan Weissman, an MIT professor of biology and Whitehead Institute for Biomedical Research member, now reveals insights into how cells can coordinate this compensation response.

Cells are constantly reading instructions stored in DNA. These instructions, called genes, tell them how to make the many proteins that carry out complex processes needed to sustain life. But first, they need to make a temporary copy of these genetic instructions called messenger RNA, or mRNA.

As part of normal maintenance, cells routinely break down these temporary messages. This process helps control gene activity — or how much protein is made from a given gene — and ensures that old or unnecessary messages don’t accumulate. Cells also destroy faulty mRNAs that contain errors. These messages, if used, could produce damaged proteins that clump together and interfere with normal cellular processes.

In 2019, external studies suggested that this cleanup could be serving as more than just a quality-control check. Researchers showed that when faulty mRNAs are broken down, this breakdown can signal cells to activate the compensation response. These works also suggested that cells decide which backup genes to turn up based on how closely these genes resemble the mRNA that’s being degraded. 

But mRNA decay is a process that happens in the cytoplasm, outside the nucleus where DNA, and thereby genes, are stored. So, Mohamed El-Brolosy, a postdoc in the Weissman Lab and lead author of the study, and colleagues wondered how those two processes in different compartments of the cell could be connected. Understanding this mechanism with greater depth could enable development of therapeutics that trigger it in a targeted fashion.

The researchers started by investigating a specific gene that scientists know triggers a compensation response when its mRNA is destroyed by causing a closely related gene to become more active. To find out which molecules within the cell aid this process, the researchers systematically switched other genes off, one at a time.

That’s when they found a protein called ILF3. When the gene encoding this protein was turned off, cells could no longer ramp up the activity of the backup gene following mRNA decay.

Upon further investigation, the researchers identified small RNA fragments — left behind when faulty mRNAs are destroyed — underlying this response. These fragments contain a special sequence that acts like an “address.” The team proposed that this address guides ILF3 to related backup genes that share the same sequence as the faulty mRNA.

In fact, when they introduced mutations in this sequence, the cells’ compensation response dropped, suggesting that the system relies on precise sequence matching to target the correct backup genes.

“That was very exciting for us,” says Weissman, who is also an investigator at the Howard Hughes Medical Institute. “It showed us that this isn’t a generic stress response. It’s a regulated system.”

The researchers’ findings point toward new therapeutic possibilities, where boosting the activity of a related gene could mitigate symptoms of certain genetic diseases. More broadly, their work characterizes a mysterious layer of gene regulation.

What if there were a way to create accurate replicas of ancient and historical instruments that could be played and heard? 

In late 2024, senior MIT postdoc Benjamin Sabatini wrote MIT Professor Eran Egozy to ask just that, and about a collaborative research project between the Center for Materials Research in Archeology and Ethnology (CMRAE) and the MIT School of Humanities, Arts, and Social Sciences (SHASS) to CT scan, chemically and structurally characterize, and produce replicas of the ancient and historical musical instruments housed at the Museum of Fine Arts, Boston (MFA).

He was soon introduced to Mark Rau, a newly hired MIT professor in music technology and electrical engineering. Sharing similar interests, the two together contacted Jared Katz, the Pappalardo Curator of Musical Instruments at the MFA, to propose a cross-institutional project. Rau, an avid museum-goer, particularly of musical instrument collections, has always wanted to hear the instruments on display, commenting that “my biggest qualm is often there are no accompanying audio examples. I want to hear these instruments; I want to play these instruments.” 

Katz, fortuitously, specializes in ancient musical practices and has developed a technique for 3D scanning and printing playable replicas of ancient instruments for his research. He had long dreamed of having access to a CT scanner to better understand how ancient instruments were constructed. The MFA was also an ideal institution for the project, since, according to Katz, the MFA’s musical instrument collection began in 1917 and has since grown to just over 1,450 instruments from six continents, with the earliest dating to approximately 1550 BCE. 

Rau and Sabatini, soon after, applied to and were funded by the MIT Human Insight Collaborative (MITHIC) with Katz's support. The team of five, including Nate Steele, program associate in the MFA’s Department of Musical Instruments and MIT postdoc Jin Woo Lee, now meets regularly at the MFA to scan and acoustically measure the instruments.

Using a CT scanner from Lumafield, a company founded by MIT alumni, the team measures both internal and external dimensions. When combined with non-destructive vibration and acoustic testing and numerical simulations, these measurements are used to digitally replicate the instruments’ sound accurately. 

“For example, if we’re trying to recreate a violin, we can use an impact hammer — a very small hammer with a transducer in it — so we’re imparting a known force signal into the instrument, and then measure the resulting [surface] vibrations with a laser Doppler vibrometer,” says Rau.

The team then uses 3D-printed copies of the instruments to create plaster mold negatives, which are cast into using slip, such as with the Paracas whistle, a ceramic artifact from Peru dating from 600-175 BCE, to replicate the instruments physically. The team demonstrated a playable replica at the MITHIC Annual Event in November. They also intend to build replicas of wooden instruments using old-growth wood in collaboration with local luthiers.

Sabatini, a member of CMRAE, sees the humanistic implications of the project and the importance of studying the instruments from a materials and archaeological perspective, which is to explore and understand the cultures that were involved in their production, stating that “[from our] perspective, we want to understand the people who made these instruments through both the materials that they’re made of, but also the sound that they have.”

With his team of Undergraduate Research Opportunities Program (UROP) students, including Irene Dong and Mouhammad Seck, Sabatini reproduced several ancient and historical clay instruments in the CMRAE archaeology lab, including the Paracas whistle, which was showcased at the MITHIC event.

So far, the team has scanned approximately 30 instruments from the MFA’s collection, with the goal of scanning at least 100 instruments over the duration of the project, documenting them, and supporting future study. The data from the scans are used to reconstruct the instruments, both physically and in software, matching their physical form and sound.

“They’re both visually beautiful and striking objects, but they are meant to be heard,” Katz says. Further stating that his “hope for this research is to provide us with a way to protect the original instrument while still allowing them to be heard and experienced in the way they were intended to be experienced.”

Katz also sees potential for outreach and community engagement through these playable replicas, which is a goal written into the project’s proposal, further stating that “[i]t shows how powerful it can be when art and science come together to create new understandings and to help us reactivate these instruments in exciting ways.”

Students have also been drawn to the project, including Victoria Pham, a second-year undergraduate in materials science and engineering, who is working with Sabatini as a UROP student. Pham was “drawn to this project because I love history,” she says. “I love wandering through the halls of the MFA and immersing myself in the descriptions of paintings and artifacts. I find learning about ancient peoples to be fascinating, especially in how their legacy affects us today.”

Her work involves finite element modeling of a Veracruz poly-glabular flute, dating to 500-900 CE, to investigate its acoustics non-destructively. She notes that “[m]y work is fulfilling because I was able to learn new software and problem-solve to improve my model, which was very satisfying.”

Pham thinks that “contributing to the new, budding field of music technology scratches an itch in my brain, and I hope that my work inspires others to get interested in archaeology, material science, or music technology.”

Alexander Mazurenko, a second-year undergraduate majoring in music and mathematics, has also been working on the project. He began last summer and continued during this year's Independent Activities Period in January.

Mazurenko notes that his involvement in this project has furthered his interdisciplinary education at MIT, commenting that “[t]he opportunity to participate in this UROP with Professor Rau was the perfect chance to begin to work in the intersection of my passions.” His work, and that of Pham, will be presented at upcoming conferences, and are expected to produce academic papers under the guidance of Sabatini and Rau.

As a professional mechanical engineer, Badri Ratnam was inspired when MIT started offering massive open online courses (MOOCs) in engineering and science in 2012. He wondered if he was up to the challenge of solving problem sets and successfully completing exams from MIT.

Ratnam first began his journey with the course 8.MReVx/8.MReV (Mechanics ReView), and he hasn’t looked back since. As he grew in his career in mechanical design and computer-aided engineering, he also completed nearly 40 MITx courses in physics, mechanical engineering, and materials science. 

Part of MIT Open Learning, MITx offers free online courses across a wide variety of subjects to learners around the world. Learners may also opt for the certificate track for a low fee. 

Ratnam has worked for companies such as Freudenberg e-Power Systems, Siemens, GE, and Westport Fuel Systems. His continued learning through MITx courses, as well as courses offered by other universities, has expanded his expertise to include areas such as physics, mechanics of materials, transport phenomena, failure and root cause analysis, validation and verification testing, vibration signal processing, certification and compliance statistical quality control, manufacturing, reliability, supplier selection, and more.

“There are many different learning styles,” says Ratnam. “Some people might need to be in a classroom, and others might be able to learn entirely on their own from a textbook. Personally, I benefit from some amount of structure, including having timelines and deadlines, as well as assignments and discussion forums. With MITx, there is also the excitement of the rigor that can be a boost of adrenaline — trying to see whether you can tackle some of the toughest material, presented by a top institution.”

Supplementing engineering education with extensive course offerings

Ratnam earned a bachelor’s degree in engineering from the University of Delhi. He says during his undergraduate program he tended to study the night before exams, and was “more focused on passing the subject than deep learning.”

He followed his undergrad studies with a master of science degree in mechanical engineering from the University of South Florida and an MS in computational and applied mathematics from Simon Fraser University in British Columbia. Even with all of his degrees, he felt that he needed to revisit the engineering subjects he had initially learned as an undergraduate student, pursuing online courses to review the fundamentals and gain greater understanding and mastery.

The MITx courses Ratnam has taken have covered many different areas within engineering, physics, mathematics, supply chains, and manufacturing. He has recently completed Vibrations and Waves, taught by Yen-Jie Lee, Alex Shvonski, and Michelle Tomasik.

“It’s an 18-week class with over 40 lessons, 13 assignments, and three exams, all designed very deliberately. I don’t think I could have ever learned this very difficult subject without this structure,” says Ratnam. “It’s also important to note that I paid less than $100 for this class. MITx does not follow the dictum that ‘you get what you pay for.’ It’s like getting a Ferrari for the price of an electric scooter.”

Ratnam has also recently finished Information Entropy: Energy and Exergy, taught by former MIT Open Learning dean for digital learning Krishna Rajagopal, Peter Dourmaskin, and Aidan MacDonagh, as well as Shvonski and Tomasik.

Although Ratnam says he can’t pick a favorite course — and is hard-pressed to even pick a few favorites of the many MITx courses he has taken — he says he has especially liked these recent courses and Elements of Structures, taught by Alexie M. Kolpak and Simona Socrate. In addition to the many MITx courses he has taken, he has also completed a few MIT Professional Education programs in smart manufacturing and design. 

“As I’ve taken more and more courses, I’ve learned to never fear learning new things and exploring new areas,” says Ratnam. “I used to think of more unfamiliar subjects and feel a little terrified, not knowing where to start, but I don’t feel that any more. I know that with some time and effort, I can pick up new skills and knowledge.”

Ratnam has found the discussion forums for MITx courses to be especially useful to the learning process.

“This is where the rigorous, engaging, yet automated, courses come to life,” says Ratnam. “Learners from all over the world help each other in the problem sets and discuss their conceptual doubts. And the forums are diligently monitored by MIT staff to ensure there are no open questions, and all errors are corrected.”

Increasing value in the workplace

Ratnam says that his MITx studies have deepened his understanding of a variety of engineering topics, which have given him new insights to apply as an engineer.

“My learnings from MITx courses have really helped me gain the confidence of having a deep understanding on the theoretical side,” says Ratman. “I’ve developed a wide base of knowledge and have become the go-to person whom people come to with questions.”

Ratnam has found MITx to be an excellent professional development resource. He notes that while many professionals have access to and complete courses offered at or through their workplaces, these usually aim to enable people to complete a very specific goal — such as performing a set task at work — within a short period of time. He says that with online courses, it’s a much different timeline and result.

“MITx classes have provided me with a much broader overview of engineering phenomena,” says Ratnam. “The benefit of the classes might not always come immediately. It can be a long gestation period for the information to all gel together. It’s much more of a profound and long-term benefit.”

Explore lifelong learning opportunities from the Institute, including online courses, resources, and professional programs, on MIT Learn.

When the densest objects in the universe collide and merge, the violence sets off ripples, in the form of gravitational waves, that reverberate across space and time, over hundreds of millions and even billions of years. By the time they pass through Earth, such cosmic ripples are barely discernible.

And yet, scientists are able to detect them, thanks to a global network of gravitational-wave observatories: the U.S.-based National Science Foundation Laser Interferometer Gravitational-Wave Observatory (NSF LIGO), the Virgo interferometer in Italy, and the Kamioka Gravitational Wave Detector (KAGRA) in Japan. Together, the observatories “listen” for faint wobbles in the gravitational field that could have come from far-off astrophysical smash-ups.

Now the LIGO-Virgo-KAGRA (LVK) Collaboration is publishing its latest compilation of gravitational-wave detections, presented in a forthcoming special issue of Astrophysical Journal Letters. From the findings, it appears that the universe is echoing all over with a kaleidoscope of cosmic collisions.

The LVK’s Gravitational-Wave Transient Catalog-4.0 (GWTC-4) comprises detections of gravitational waves from a portion of the observatories’ fourth and most recent observing run, which occurred between May 2023 and January 2024. During this nine-month period, the observatories detected 128 new gravitational-wave “candidates,” meaning that the signals are likely from extreme, far-off astrophysical sources. (The LVK detected about 300 mergers so far in the fourth run, but not all of these appear yet in the LVK catalog.)

This newest crop more than doubles the size of the gravitational-wave catalog, which previously contained 90 candidates compiled from all three previous observing runs.

“The beautiful science that we are able to do with this catalog is enabled by significant improvements in the sensitivity of the gravitational-wave detectors as well as more powerful analysis techniques,” says LVK member Nergis Mavalvala, who is dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics.

“In the past decade, gravitational wave astronomy has progressed from the first detection  to the observation of hundreds of black hole mergers,” says Stephen Fairhurst, a professor at Cardiff University and LIGO Scientific Collaboration spokesperson. “These observations enable us to better understand how black holes form from the collapse of massive stars, probe the cosmological evolution of the universe and provide increasingly rigorous confirmations of the theory of general relativity.”

“Pushing the edges”

Black holes are created when all the matter in a dying star collapses into a single point. Black holes are therefore among the densest objects in the universe. Black holes often form in pairs, bound together through the gravitational attraction. As they spiral toward each other, they emit enormous amounts of energy in the form of gravitational waves, before merging into a more massive black hole.

A binary black hole was the source of the very first gravitational-wave detection, made by NSF’s LIGO observatories in 2015, and colliding black holes are the source of many of the gravitational waves detected since then. Such “bread-and-butter” binaries typically consist of two black holes of similar size (usually several tens of times more massive than the sun) that merge into one larger black hole.

Gravitational waves can also be produced by the collision of a black hole with a neutron star, which is an extremely dense remnant core of a massive star. While the collision of two black holes only produces gravitational waves, a smash-up involving a neutron star can also generate light, which provides more information about the event that scientists can probe. In its first three observing runs, the LVK observatories detected signals from a handful of collisions involving a black hole and neutron star, as well as two collisions between two neutron stars.

The newest detections published today reveal a greater variety of binaries that produce gravitational waves. In addition to the black hole binaries, the updated catalog includes the heaviest black hole binary; a binary with black holes of asymmetric, lopsided masses; and a binary where both black holes have exceptionally high spins. The catalog also holds two black hole-neutron star binaries.

“The message from this catalog is: We are expanding into new parts of what we call ‘parameter space’ and a whole new variety of black holes,” says co-author Daniel Williams, a research fellow at the University of Glasgow and a member of the LVK. “We are really pushing the edges, and are seeing things that are more massive, spinning faster, and are more astrophysically interesting and unusual.”

Unusual signals

The LIGO, Virgo, and KAGRA observatories detect gravitational waves using L-shaped, kilometer-scale instruments, called interferometers. Scientists send laser light down the length of each tunnel and precisely measure the time it takes each beam to return to its source. Any slight difference in their timing can mean that a gravitational wave passed through and minutely wobbled the laser’s light.

For the first segment of the LVK’s fourth observing run, gravitational-wave detections were made using only LIGO’s identical interferometers — one located in Hanford, Washington, and the other in Livingston, Louisiana. Recent upgrades to LIGO’s detectors enabled them to search for signals from binary neutron stars as far out as 360 megaparsecs, or about 1 billion light-years away, and for signals from binaries including black holes tens of times farther away.

“You can’t ever predict when a gravitational wave is going to come into your detector,” says co-author and LVK member Amanda Baylor, a graduate student at the University of Wisconsin at Milwaukee who was involved in the signal search process. “We could have five detections in one day, or one detection every 20 days. The universe is just so random.”

Among the more unusual signals that LIGO detected in the first phase of the O4 observing run was GW231123_135430, which is the heaviest black hole binary detected to date. Scientists estimate that the signal arose from the collision of two heavier-than-normal black holes, each roughly 130 times as massive as the sun. (Most of the detected merging black holes are around 30 solar masses.) The much heavier black holes of GW231123_135430 suggest that each may be a product of a prior collision of lighter “progenitor” black holes.

Another standout is GW231028_153006, which is a black hole binary with the highest inspiral spin, meaning that both black holes appear to be spinning very fast, at about 40 percent the speed of light. Again, scientists suspect that these black holes were also products of previous mergers that spun them up as they were created from two smaller, inspiraling black holes.

The O4 run also detected GW231118_005626 — an unusually lopsided pair, with one black hole twice as massive as the other. 

“One of the striking things about our collection of black holes is their broad range of properties,” says co-author LVK member Jack Heinzel, an MIT graduate student who contributed to the catalog’s analysis. “Some of them are over 100 times the mass of our sun, others are as small as only a few times the mass of the sun. Some black holes are rapidly spinning, others have no measurable spin. We still don’t completely understand how black holes form in the universe, but our observations offer a crucial insight into these questions.”

Cosmic connections

From the newest gravitational-wave detections, scientists have begun to make connections about the properties of black holes as a population.

“For instance, this dataset has increased our belief that black holes that collided earlier in the history of the universe could more easily have had larger spins than the ones that collided later,” says LVK member Salvatore Vitale, associate professor of physics at MIT and member of the MIT LIGO Lab.

This idea raises interesting questions about what sort of conditions could have spun up black holes in the early universe.

The new detections have also allowed scientists to test Albert Einstein’s general theory of relativity, which describes gravity as a geometric property of space and time.

“Black holes are one of the most iconic and mind-bending predictions of general relativity,” says co-author and LVK member Aaron Zimmerman, associate professor of physics at the University of Texas at Austin, adding that when black holes collide, they “shake up space and time more intensely than almost any other process we can imagine observing. When testing our physical theories, it’s good to look at the most extreme situations we can, since this is where our theories are most likely to break down, and where we have the best chance of discovery.”

Scientists put Einstein’s theory to the test using GW230814_230901, which is one of the “loudest” gravitational-wave signals observed to date. The surprisingly clear signal gave scientists a chance to probe it in detail, to see if any aspects of the signal might deviate from what Einstein’s theory predicts. This signal pushed the limits of their tests of general relativity, passing most with flying colors but illustrating how environmental noise can challenge others in such an extreme scenario.

“So far, the theory is passing all our tests,” Zimmerman says. “But we’re also learning that we have to make even more accurate predictions to keep up with all the data the universe is giving us.”

The updated catalog is also helping scientists to nail down a key mystery in cosmology: How fast is the universe expanding today? Scientists have tried to answer this by measuring a rate known as the Hubble constant. Various methods, using different astrophysical sources, have given conflicting answers.

Gravitational waves offer an alternative way to measure the Hubble constant, since scientists are able to work out, in relatively straightforward fashion, how far these waves traveled from their source.

“Merging black holes have a really unique property: We can tell how far away they are from Earth just from analyzing their signals,” says co-author and LVK member Rachel Gray, a lecturer at the University of Glasgow who was involved in the cosmological interpretations of the catalog’s data. “So, every merging black hole gives us a measurement of the Hubble constant, and by combining all of the gravitational wave sources together, we can vastly improve how accurate this measurement is.”

By analyzing all the gravitational-wave detections in the LVK’s entire catalog, scientists have come up with a new, independent estimate of the Hubble constant, that suggests the universe is expanding at a rate of 76 kilometers, per second, per megaparsec (a square volume of about half a billion light-years wide).

“It’s still early days for this method, and we expect to significantly improve our precision as we detect more gravitational wave sources,” Gray says.

“Each new gravitational-wave detection allows us to unlock another piece of the universe’s puzzle in ways we couldn’t just a decade ago,” says Lucy Thomas, who led part of the catalog’s analysis, and is a postdoc in the Caltech LIGO Lab. “It’s incredibly exciting to think about what astrophysical mysteries and surprises we can uncover with future observing runs."

Plant growth is supported by millions of tiny soil microbes competing and cooperating with each other as they perform important roles at the plant root, including improving access to nutrients and protecting against pathogens. As a byproduct of their metabolism, soil microbes can also produce nitrous oxide, or N2O, a potent greenhouse gas that has mostly been studied for its impact on the climate. While some N2O occurs naturally, its production can spike due to fertilizer application and other factors.

While it has long been believed that nitrous oxide doesn’t meaningfully interact with living organisms, a new paper by two MIT researchers shows that it may in fact shape microbial communities, making some bacterial strains more likely to grow than others.

Based on the prevalence of the biological processes disrupted by nitrous oxide, the researchers estimate about 30 percent of all bacteria with sequenced genomes are susceptible to nitrous oxide toxicity, suggesting the substance could play an important and underappreciated role in the intricate microbial ecosystems that influence plant growth.

The researchers have published their findings today in mBio, a journal of the American Society for Microbiology. If their lab findings carry over to agricultural settings, it could influence the way farmers go about everyday tasks that expose crops to spikes in nitrous oxide, such as watering and fertilization.

“This work suggests N2O production in agricultural settings is worth paying attention to for plant health,” says senior author Darcy McRose, MIT’s Thomas D. and Virginia W. Cabot Career Development Professor, who wrote the paper with lead author and PhD student Philip Wasson. “It hasn’t been on people’s radar, but it is particularly harmful for certain microbes. This could be another knock against N2O in addition to its climate impact. With more research, you might be able to understand how the timing of N2O production influences these microbial relationships, and that timing could be managed to improve crop health.”

A toxic gas

Nitrous oxide was shown to be toxic decades ago when researchers realized it can deactivate vitamin B12 in the human body. Since then, it has mostly drawn attention as a long-lived greenhouse gas that can eat away at the ozone. But when it comes to agricultural settings, most people have assumed it doesn’t interact with organisms growing in the soil around the plant root, a region called the rhizosphere.

“In general, there’s an assumption that N2O is not harmful at all despite this history of published studies showing that it can be toxic in specific contexts,” says McRose, who joined the faculty of the Department of Civil and Environmental Engineering in 2022. “People have not extended that understanding to microbial communities in the rhizosphere.”

While some studies have shown nitrous oxide sensitivity in a handful of microorganisms, less is known about how it impacts the distribution of microbial communities at the plant root. McRose and Wasson sought to fill that research gap.

They started by looking at a ubiquitous process that cells use to grow called methionine biosynthesis. Methionine biosynthesis can be carried out by enzymes that are dependent on B12 — and by other enzymes that are not. Many bacteria have both types.

Using a well-studied microbe named Pseudomonas aeruginosa, the researchers genetically removed the enzyme that isn’t dependent on B12 and found the microbe became sensitive to nitrous oxide, with its growth harmed even by nitrous oxide it produced itself.

Next the researchers looked at a synthetic microbial community from the plant Arabidopsis thaliana, finding many root-based microbes were also sensitive to nitrous oxide. Combining sensitive microbes with nitrous oxide-producing bacteria hampered their growth.

“This suggests that N2O-producing bacteria can affect the survival of their immediate neighbors,” Wasson explains. Together, the experiments confirmed the researchers’ suspicion that the production of nitrous oxide can hamper the growth of soil bacteria dependent on vitamin B12 to make methionine.

“These results suggest nitrous oxide producers shape microbial communities,” McRose says. “In the lab the result is very clear, and the work goes beyond just looking at a single organism. The co-culture experiments aren’t the same as a study in the field, but it’s a strong demonstration.”

From the lab to the farm

In farms, soil commonly experiences spikes of nitrous oxide for days or weeks from the addition of nitrogen fertilizer, rainfall, thawing, and other events. The researchers caution that their lab experiments are only the first step toward understanding how nitrous oxide affects microbial populations in agricultural settings.

Wasson calls the paper a proof of concept and plans to study agricultural soil next.

“In agricultural environments, N2O has been historically high,” Wasson says. “We want to see if we can detect a signature for this N2O exposure through genome sequencing studies, where the only microbes sticking around are not sensitive to N2O. This is the obvious next step.”

McRose says the findings could lead to a new way for researchers and farmers to think about nitrous oxide.

“What’s important and exciting about this case is it predicts that microbes with one version of an enzyme are going to be sensitive to N2O and those with a different version of the enzyme are not going to be sensitive,” McRose says. “This suggests that in the environment, exposure to N2O is going to select for certain types of organisms based on their genomic content, which is a highly testable hypothesis.”

The work was supported, in part, by the MIT Research Support Committee and a MIT Health and Life Sciences Collaborative Graduate Fellowship (HEALS).

Expertise isn’t easy to pass down. Take riding a bike: A seasoned cyclist might talk a beginner through the basics of how to sit and when to push off. But other skills, like how hard to pedal to keep balanced, are more intuitive and harder to articulate. This implicit know-how is known as tacit knowledge, and very often, it can only be learned with experience and time.

But a team of MIT engineers wondered: Could an expert’s unconscious know-how be accessed, and even taught, to quickly bring a novice up to an expert’s level?

The answer appears to be “yes,” at least for a particular type of visual-learning task.

In a study published today in the Journal of Neural Engineering, the engineers identified tacit knowledge in volunteers who were tasked with classifying images of various shapes and patterns. As the volunteers were shown images to organize, the team recorded their eye movements and brain activity to measure their visual focus and cognitive attention, respectively.

The measurements showed that, over time, the volunteers shifted their focus and attention to a part of each image that made it easier to classify. However, when asked directly, the volunteers were not aware that they had made such a shift. The researchers concluded that this unconscious shift in attention and focus was a form of tacit knowledge that the volunteers possessed, even if they could not articulate it. What’s more, when the volunteers were made aware of this tacit knowledge, their accuracy in classifying images improved significantly.

The study is the first to directly show that visual attention can reveal unconscious, tacit knowledge during image classification tasks. It also finds for the first time that bringing this concealed knowledge to the surface can enhance experts’ performance.

While the results are specific to the study’s experiment, the researchers say they suggest that some forms of hidden know-how can be made explicit and applied to boost one’s learning experience. They suspect that tacit knowledge could be accessed for disciplines that require keen observation skills, including certain physical trades and crafts, sports, and image analysis, such as medical X-ray diagnoses.

“We as humans have a lot of knowledge, some that is explicit that we can translate into books, encyclopedias, manuals, equations. The tacit knowledge is what we cannot verbalize, that’s hidden in our unconscious,” says study author Alex Armengol-Urpi, a research scientist in MIT’s Department of Mechanical Engineering. “If we can make that knowledge explicit, we can then allow for it to be transferred easier, which can help in education and learning in general.”

The study’s co-authors include Andrés F. Salazar-Gomez, research scientist at the MIT Media Lab; Pawan Sinha, professor of vision and computational neuroscience in MIT’s Department of Brain and Cognitive Sciences; and Sanjay Sarma, the Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor in Mechanical Engineering.

Hidden gaze

The concept of tacit knowledge is credited to the scientist and philosopher Michael Polyani, who in the mid 20th century was the first to investigate the notion that “we know more than we can tell.” His insights revealed that humans can hold a form of knowledge that is internalized, almost second nature, and often difficult to express or translate to others.

Since Polyani’s work, many studies have highlighted how tacit knowledge may play a part in perfecting certain skills, spanning everything from diagnosing medical images to discerning the sex of cats from images of their faces.

For Armengol-Urpi, these studies raised a question: Could a person’s tacit knowledge be revealed through unconscious signals, such as patterns in their eye movements? His PhD work focused on visual attention, and he had developed methods to study how humans focus their attention, by using cameras to follow the direction of their gaze, and electroencephalography (EEG) monitors to record their brain activity. In his research, he learned of a previous study that used similar methods to investigate how radiologists diagnose nodules in X-ray images. That study showed that the doctors unconsciously focused on areas of an image that helped them to correctly detect the nodules.

“That paper didn’t focus on tacit knowledge, but it suggested that there are some hidden clues in our gaze that could be explored further,” Armengol-Urpi says.

The shape of knowledge

For their new study, the team looked at whether they could identify signs of tacit knowledge from measurements of visual focus and attention. In their experiment, they asked 30 volunteers to look sequentially at over 120 images. They could look at each image for several seconds and then were asked to classify the image as belonging to either group A, or group B, before they were shown the next image.

Each image contained two simple shapes on either side of the image — a square, a triangle, a circle, and any combination of the three, along with different colors and patterns for each shape. The researchers designed the images such that they should be classified into one of two groups, based on an intricate combination of shape, color, and pattern. Importantly, only one side of each image was relevant for the classification.

The volunteers, however, were given no guidelines on how to classify the images. Therefore, for about the first half of the experiment, they were considered “novices,” and more or less guessed at their classifications. Over time, and many more images, their accuracy improved to a level that the researchers considered “expert.” Throughout the experiment, the team used cameras to follow each participant’s eye movements, as a measure of visual focus.

They also outfitted volunteers with EEG sensors to record their brain waves, which they used as a measure of cognitive attention. They designed each image to show two shapes, each of which flickered at different, imperceptible frequencies. They found they could identify where a volunteer’s attention landed, based on which shape’s flicker their brain waves synced up with.

For each volunteer, the team created maps of where their gaze and attention were focused, both during their novice and expert phases. Overall, these maps showed that in the beginning, the volunteers focused on all parts of an image as they tried to make sense of how to classify it. Toward the end, as they got a grasp of the exercise and improved their accuracy, their attention shifted to just one side of each image. This side happened to be the side that the researchers designed to be most relevant, while the other side was just random noise.

The maps showed that the volunteers picked up some knowledge of how to accurately classify the images. But when they were given a survey and asked to articulate how they learned the task, they always maintained that they focused on each entire image. It seemed their actual shift in focus was an unconscious, tacit skill.

“They were unconsciously focusing their attention on the part of the image that was actually informative,” Armengol-Urpi says. “So the tacit knowledge they had was hidden inside them.”

Going a step further, the team then showed each participant the maps of their gaze and attention, and how the maps changed from their novice to expert phases. When they were then shown additional images, the volunteers seemed to use this once-tacit knowledge, and further improved their classification accuracy.

“We are currently extending this approach to other domains where tacit knowledge plays a central role,” says Armengol-Urpi, who is exploring tacit knowledge in skilled crafts and sports such as glassblowing and table tennis, as well as in diagnosing medical imaging. “We believe the underlying principle — capturing and reinforcing implicit expertise through physiological signals — can generalize to a wide range of perceptual and skill-based domains.”

This research was supported, in part, by Takeda Pharmaceutical Company.

Many engineering challenges come down to the same headache — too many knobs to turn and too few chances to test them. Whether tuning a power grid or designing a safer vehicle, each evaluation can be costly, and there may be hundreds of variables that could matter.

Consider car safety design. Engineers must integrate thousands of parts, and many design choices can affect how a vehicle performs in a collision. Classic optimization tools could start to struggle when searching for the best combination.

MIT researchers developed a new approach that rethinks how a classic method, known as Bayesian optimization, can be used to solve problems with hundreds of variables. In tests on realistic engineering-style benchmarks, like power-system optimization, the approach found top solutions 10 to 100 times faster than widely used methods.

Their technique leverages a foundation model trained on tabular data that automatically identifies the variables that matter most for improving performance, repeating the process to hone in on better and better solutions. Foundation models are huge artificial intelligence systems trained on vast, general datasets. This allows them to adapt to different applications.

The researchers’ tabular foundation model does not need to be constantly retrained as it works toward a solution, increasing the efficiency of the optimization process. The technique also delivers greater speedups for more complicated problems, so it could be especially useful in demanding applications like materials development or drug discovery.

“Modern AI and machine-learning models can fundamentally change the way engineers and scientists create complex systems. We came up with one algorithm that can not only solve high-dimensional problems, but is also reusable so it can be applied to many problems without the need to start everything from scratch,” says Rosen Yu, a graduate student in computational science and engineering and lead author of a paper on this technique.

Yu is joined on the paper by Cyril Picard, a former MIT postdoc and research scientist, and Faez Ahmed, associate professor of mechanical engineering and a core member of the MIT Center for Computational Science and Engineering. The research will be presented at the International Conference on Learning Representations.

Improving a proven method

When scientists seek to solve a multifaceted problem but have expensive methods to evaluate success, like crash testing a car to know how good each design is, they often use a tried-and-true method called Bayesian optimization. This iterative method finds the best configuration for a complicated system by building a surrogate model that helps estimate what to explore next while considering the uncertainty of its predictions.

But the surrogate model must be retrained after each iteration, which can quickly become computationally intractable when the space of potential solutions is very large. In addition, scientists need to build a new model from scratch any time they want to tackle a different scenario.

To address both shortcomings, the MIT researchers utilized a generative AI system known as a tabular foundation model as the surrogate model inside a Bayesian optimization algorithm.

“A tabular foundation model is like a ChatGPT for spreadsheets. The input and output of these models are tabular data, which in the engineering domain is much more common to see and use than language,” Yu says.

Just like large language models such as ChatGPT,  Claude, and Gemini, the model has been pre-trained on an enormous amount of tabular data. This makes it well-equipped to tackle a range of prediction problems. In addition, the model can be deployed as-is, without the need for any retraining.

To make their system more accurate and efficient for optimization, the researchers employed a trick that enables the model to identify features of the design space that will have the biggest impact on the solution.

“A car might have 300 design criteria, but not all of them are the main driver of the best design if you are trying to increase some safety parameters. Our algorithm can smartly select the most critical features to focus on,” Yu says.

It does this by using a tabular foundation model to estimate which variables (or combinations of variables) most influence the outcome.

It then focuses the search on those high-impact variables instead of wasting time exploring everything equally. For instance, if the size of the front crumple zone significantly increased and the car’s safety rating improved, that feature likely played a role in the enhancement.

Bigger problems, better solutions

One of their biggest challenges was finding the best tabular foundation model for this task, Yu says. Then they had to connect it with a Bayesian optimization algorithm in such a way that it could identify the most prominent design features.

“Finding the most prominent dimension is a well-known problem in math and computer science, but coming up with a way that leveraged the properties of a tabular foundation model was a real challenge,” Yu says.

With the algorithmic framework in place, the researchers tested their method by comparing it to five state-of-the-art optimization algorithms.

On 60 benchmark problems, including realistic situations like power grid design and car crash testing, their method consistently found the best solution between 10 and 100 times faster than the other algorithms.

“When an optimization problem gets more and more dimensions, our algorithm really shines,” Yu added.

But their method did not outperform the baselines on all problems, such as robotic path planning. This likely indicates that scenario was not well-defined in the model’s training data, Yu says.

In the future, the researchers want to study methods that could boost the performance of tabular foundation models. They also want to apply their technique to problems with thousands or even millions of dimensions, like the design of a naval ship.

“At a higher level, this work points to a broader shift: using foundation models not just for perception or language, but as algorithmic engines inside scientific and engineering tools, allowing classical methods like Bayesian optimization to scale to regimes that were previously impractical,” says Ahmed.

“The approach presented in this work, using a pretrained foundation model together with high‑dimensional Bayesian optimization, is a creative and promising way to reduce the heavy data requirements of simulation‑based design. Overall, this work is a practical and powerful step toward making advanced design optimization more accessible and easier to apply in real-world settings,” says Wei Chen, the Wilson-Cook Professor in Engineering Design and chair of the Department of Mechanical Engineering at Northwestern University, who was not involved in this research.

More than 10,000 Americans who suffer from chronic liver disease are on a waitlist for a liver transplant, but there are not enough donated organs for all of those patients. Additionally, many people with liver failure aren’t eligible for a transplant if they are not healthy enough to tolerate the surgery.

To help those patients, MIT engineers have developed “mini livers” that could be injected into the body and take over the functions of the failing liver.

In a new study in mice, the researchers showed that these injected liver cells could remain viable in the body for at least two months, and they were able to generate many of the enzymes and other proteins that the liver produces.

“We think of these as satellite livers. If we could deliver these cells into the body, while leaving the sick organ in place, that would provide booster function,” says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science at MIT, and a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science (IMES).

Bhatia is the senior author of the new study, which appears today in the journal Cell Biomaterials. MIT postdoc Vardhman Kumar is the paper’s lead author.

Restoring liver function

The human liver plays a role in about 500 essential functions, including regulation of blood clotting, removing bacteria from the bloodstream, and metabolizing drugs. Most of these functions are performed by cells called hepatocytes.

Over the past decade, Bhatia’s lab has been working on ways to restore hepatocyte function without a surgical liver transplant. One possible approach is to embed hepatocytes into a biomaterial such as a hydrogel, but these gels also have to be surgically implanted.

Another option is to inject hepatocytes into the body, which eliminates the need for surgery. In this study, Bhatia’s lab sought to improve on this strategy by providing an engineered niche that could enhance the cells’ survival and facilitate noninvasive monitoring of graft health.

To achieve that, the researchers came up with the idea of injecting cells along with hydrogel microspheres that would help them stay together and form connections with nearby blood vessels. These spheres have special properties that allow them to act like a liquid when they are closely packed together, so they can be injected through a syringe and then regain their solid structure once inside the body.

In recent years, researchers have explored using hydrogel microspheres to promote wound healing, as they help cells to migrate into the spaces between the spheres and build new tissue. In the new study, the MIT team adapted them to help hepatocytes form a stable tissue graft after injection.

“What we did is use this technology to create an engineered niche for cell transplantation,” Kumar says. “If the cells are injected in the absence of these spheres, they would not integrate efficiently with the host, but these microspheres provide the hepatocytes with a niche where they can stay localized and become connected to the host circulation much faster.”

The injected mixture also includes fibroblast cells — supportive cells that help the hepatocytes survive and promote the growth of blood vessels into the tissue.

Working with Nicole Henning, an ultrasound research specialist at the Koch Institute, the researchers developed a way to inject the cell mixture using a syringe guided by ultrasound. After injection, the researchers can also use ultrasound to monitor the long-term stability of the implant.

In this study, the mini livers were injected into the fat tissue in the belly. In the future, similar grafts could be delivered to other sites in the body, such as into the spleen or near the kidneys. As long as they have enough space and access to blood vessels, the injected hepatocytes can function similarly to hepatocytes in the liver.

“For a vast majority of liver disorders, the graft does not need to sit close to the liver,” Kumar says.

An alternative to transplantation

In tests in mice, the researchers injected the mixture of liver cells and microspheres into an area of fatty tissue known as the perigonadal adipose tissue. Once the cells are localized in the body, they form a stable, compact structure. Over time, blood vessels begin to grow into the graft area, helping the injected hepatocytes to stay healthy.

“The new blood vessels formed right next to the hepatocytes, which is why they were able to survive,” Kumar says. “They were able to get the nutrients delivered right to them, they were able to function the way they're supposed to, and they produced the proteins that we expect them to.”

After injection, the cells remained viable and able to secrete specialized proteins into the host circulation for eight weeks, the length of the study. That suggests that the therapy could potentially work as a long-term treatment for liver disease, the researchers say.

“The way we see this technology is it can provide an alternative to surgery, but it can also serve as a bridge to transplantation where these grafts can provide support until a donor organ becomes available,” Kumar says. “And if we think they might need another therapy or more grafts, the barriers to do that are much less with this injectable technology than undergoing another surgery.”

With the current version of this technology, patients would likely need to take immunosuppressive drugs, but the researchers are exploring the possibility of developing “stealthy” hepatocytes that could evade the immune system, or using the hydrogel microspheres to deliver immunosuppressants locally.

The research was funded by the Koch Institute Support (core) grant from the National Cancer Institute, the National Institutes of Health, the Wellcome Leap HOPE Program, a National Science Foundation Graduate Research Fellowship, and the Howard Hughes Medical Institute.

LAB14 GmbH, a corporate network based in Germany that unites eight high-tech companies focused on nanofabrication, microfabrication, and surface analysis, has joined the MIT.nano Consortium.

“The addition of LAB14 to the MIT.nano Consortium reinforces the importance of collaboration to advance the next set of great ideas,” says Vladimir Bulović, the founding faculty director of MIT.nano and the Fariborz Maseeh (1990) Professor of Emerging Technologies at MIT. “At MIT.nano, we are thrilled when our shared-access facility leads to cross-disciplinary discoveries. LAB14 carries this same motivation by assembling the constellation of remarkable interconnected industry partners.”

Comprising eight companies — Heidelberg Instruments, Nanoscribe, GenISys, Notion Systems, 40-30, Amcoss, SPECSGROUP, and Nanosurf — LAB14 is focused on developing products and services that are fundamental to micro- and nanofabrication technologies, supporting industrial and research-driven applications with complex manufacturing and analysis requirements.

The companies of LAB14 operate under a shared organizational structure that enables closer coordination in technology development. This setup allows for faster research progress and more efficient manufacturing workflows.

“Joining the MIT.nano Consortium marks a significant milestone for LAB14 and our companies,” says Martin Wynaendts van Resandt, CEO of LAB14. “This participation allows our network to collaborate directly with world-leading researchers, accelerating innovation in micro- and nanotechnology."

As part of this engagement, LAB14 will provide two pieces of equipment to be installed at MIT.nano within the coming year. The VPG 300 DI maskless stepper, a high-performance, direct-write system from Heidelberg Instruments, will be positioned inside MIT.nano’s cleanroom. This tool will allow MIT.nano users to pattern structures smaller than 500 nanometers directly onto wafers with accuracy and uniformity comparable to typical high resolution i-line lithography. Equipped with advanced multi-layer alignment and mix‑and‑match functions, the VPG creates a seamless link between laser direct writing and e‑beam lithography.

The EnviroMETROS X-ray photoelectron spectroscopy (XPS/HAXPES) tool by SPECSGROUP will join the suite of Characterization.nano instruments. This unique system is specialized in nondestructive depth profile measurements using multiple X-ray energies to determine the thickness of thin-film samples and their chemical compositions with highest precision. It supports various analyses across a wide pressure range, allowing MIT.nano users to examine thin‑film materials under more realistic environmental conditions and to observe how they change during operation.

The MIT.nano Consortium is a platform for academia-industry collaboration, fostering research and innovation in nanoscale science and engineering. Consortium members gain unparalleled access to MIT.nano and its dynamic user community, providing opportunities to share expertise and guide advances in nanoscale technology.

MIT.nano continues to welcome new companies as sustaining members. For details, and to see a list of current members, visit the MIT.nano Consortium page.

Flying on Mars — or any other world — is an extraordinary challenge. An autonomous spacecraft, operating millions of miles from pilots or engineers who could intervene on Earth, must be able to navigate unfamiliar and changing environments, avoid obstacles, land on uncertain terrain, and make decisions entirely on its own. Every maneuver depends on careful perception, planning, and control systems that are fault-tolerant, allowing the craft to recover if something goes wrong. A single miscalculation can leave a multi-million dollar spacecraft face-down on the surface, ending the mission before it even begins.

“This problem is in no way solved, in industry or even in research settings,” says Nicholas Roy, the Jerome C. Hunsaker Professor in the MIT Department of Aeronautics and Astronautics (AeroAstro). “You’ve got to bring together a lot of pieces of code, software, and integrate multiple pieces of hardware. Putting those together is not trivial.”

Not trivial, but for students nearing the culmination of their Course 16 undergraduate careers, far from impossible. In class 16.85 Autonomy Capstone (Design and Testing of Autonomous Vehicles), students design, implement, deploy, and test a full software architecture for flying autonomous systems. These systems have wide-ranging applications, from urban air-mobility and reusable launch vehicles to extraterrestrial exploration. With robust autonomous technology, vehicles can operate far from home while engineers watch from mission control centers not too different from the high bay in AeroAstro’s Kresa Center for Autonomous Systems.

Roy and Jonathan How, Ford Professor of Engineering, developed the new course to build on the foundations of class 16.405 (Robotics: Science and Systems), which introduces students to working with complex robotic platforms and autonomous navigation through ground vehicles with pre-built software. 16.85 applies those same principles to flight, with a basic quadrotor drone and an entirely blank slate to build their own navigation systems. The vehicles are then tested on an obstacle course featuring dubious landing pads and uncertain terrain. Students work in large teams (for this first run, two teams of seven — the SLAMdunkers and the Spelunkers) designed to mirror real-world missions where coordination across roles is essential. 

“The vehicles need to be able to differentiate between all these hidden risks that are in the mission and the environment that they’re in and still survive,” says How. “We really want the students to learn how to make a system that they have confidence in.”

Mission: Figure it out, together

“The specific mission we gave them this semester is to imagine that you are an aircraft of some kind, and you’ve got to go and explore the surface of an extraterrestrial body like Mars or the moon,” Roy explains. “You need to use onboard sensors to fly around and explore, build a map, identify interesting objects, and then land safely on what is probably not a flat surface, or not a perfectly horizontal surface.”

A mission of this magnitude is far too complex for any one engineer to tackle alone, but that too poses a challenge for a large team. “The hardest problems these days are coordination problems,” says Andrew Fishberg, a graduate student in the Aerospace Controls Laboratory and one of three teaching assistants (TAs) for the course. “To use the robotics term, a team of this size is something of a heterogeneous swarm. Not everyone has the same skill set, but everyone shows up with something to contribute, and managing that together is a challenge.”

The challenge asks students to apply multiple types of “systems thinking” to the task. Relationships, interdependencies, and feedback loops are critical to their software architecture, and equally important in how students communicate and coordinate with their teammates. “Writing the reports and communicating with a team feels like overhead sometimes, but if you don’t communicate, you have a team of one,” says Fishberg. “We don’t have these ‘solo inventor’ situations where one person figures everything out anymore — it’s hundreds of people building this huge thing.”

The new faces of flight

Students in the class say they are eager to enter the rapidly evolving field, working with unconventional tools and vehicles that go beyond traditional applications.

“We continue to send rovers to extraterrestrial bodies. But there is an increasing interest in deploying unmanned systems to explore Earth,” says Roy. “There’s lots of places on Earth where we want to send robots to go and explore, places where it’s hazardous for humans to go.” That expanding set of applications is exactly what draws students to the field.

“I was really excited for the idea of a new class, especially one that was focused on autonomy, because that’s where I see my career going,” says senior Norah Miller. “This class has given me a really great experience in what it feels like to develop software from zero to a full flying mission.”

The Design and Testing of Autonomous Vehicles course offers a unique perspective for instructors and TAs who have known many of the students throughout their undergraduate careers. As a capstone, it provides an opportunity to see that growth come full circle. “A couple years ago we’re solving differential equations, and now they’re implementing software they wrote on a quadrotor in the high bay,” says How.

After weeks of learning, building, testing, refinement, and finally, flight, the results reflected the goals of the course. “It was exactly what we wanted to see happen,” says Roy. “We gave them a pretty challenging mission. We gave them hardware that should be capable of completing the mission, but not guaranteed. And the students have put in a tremendous amount of effort and have really risen to the challenge.”

A prestigious grant from the W.M. Keck Foundation to Alison E. Ringel, an MIT assistant professor of biology, will support groundbreaking healthy aging research at the Institute.

Ringel, who is also a core member of the Ragon Institute of Mass General Brigham, MIT, and Harvard, will draw on her background in cancer immunology to create a more comprehensive biomedical understanding of the cause and possible treatments for aging-related decline.

“It is such an honor to receive this grant,” Ringel says. “This support will enable us to draw new connections between immunology and aging biology. As the U.S. population grows older, advancing this research is increasingly important, and this line of inquiry is only possible because of the W.M. Keck Foundation.”

Understanding how to extend healthy years of life is a fundamental question of biomedical research with wide-ranging societal implications. Although modern science and medicine have greatly expanded global life expectancy, it remains unclear why everyone ages differently; some maintain physical and cognitive fitness well into old age, while others become debilitatingly frail later in life.

Our immune systems are adaptable, but they do naturally decline as we get older. One critical component of our immune system is CD8+ T cells, which are known to target and destroy cancerous or damaged cells. As we age, our tissues accumulate cells that can no longer divide. These senescent cells are present throughout our lives, but reach seemingly harmful levels as a normal part of aging, causing tissue damage and diminished resilience under stress.

There is now compelling evidence that the immune system plays a more active role in aging than previously thought.

“Decades of research have revealed that T cells can eliminate cancer cells, and studies of how they do so have led directly to the development of cancer immunotherapy,” Ringel says. “Building on these discoveries, we can now ask what roles T cells play in normal aging, where the accumulation of senescent cells, which are remarkably similar to cancer cells in some respects, may cause health problems later in life.”

In animal models, reconstituting elements of a young immune system has been shown to improve age-related decline, potentially due to CD8+ T cells selectively eliminating senescent cells. CD8+ T cells progressively losing the ability to cull senescent cells could explain some age-related pathology.

Ringel aims to build models for the express purpose of tracking and manipulating T cells in the context of aging and to evaluate how T cell behavior changes over a lifespan.

“By defining the protective processes that slow aging when we are young and healthy, and defining how these go awry in older adults, our goal is to generate knowledge that can be applied to extend healthy years of life,” Ringel says. “I’m really excited about where this research can take us.”

The W.M. Keck Foundation was established in 1954 in Los Angeles by William Myron Keck, founder of The Superior Oil Co. One of the nation’s largest philanthropic organizations, the W.M. Keck Foundation supports outstanding science, engineering, and medical research. The foundation also supports undergraduate education and maintains a program within Southern California to support arts and culture, education, health, and community service projects.

Leslie “Les” Perelman, an influential figure in college writing assessment; a champion of writing instruction across all subject matters for over three decades at MIT; and a former MIT associate dean for undergraduate education, died on Nov. 12, 2025, at home in Lexington, Massachusetts. He was 77.

A Los Angeles native, Perelman attended the University of California at Berkeley, joining in its lively activist years, and in 1980 received his PhD in English from the University of Massachusetts at Amherst. After stints at the University of Southern California and Tulane University, he returned to Massachusetts — to MIT — in 1987, and stayed for the next 35 years.

Perelman became best known for his dogged critique of autograding systems and writing assessments that didn’t assess actual college writing. The Boston Globe dubbed him “The man who killed the SAT essay.” He told NPR that colleges “spend the first year deprogramming [students] from the five-paragraph essay.” 

His widow, MIT Professor Emerita Elizabeth Garrels, says that while attending a conference, Perelman — who was practically blind without his glasses — arranged to stand at one end of a room in order to “grade” essays held up for him on the other side. “He would call out the grade that each essay would likely receive on standardized scoring,” Garrels says. “And he was consistently right.” Perelman was doing what automatic scorers were: He was, he said in the NPR interview, “mirroring how automated or formulaic grading systems often reward form over substance.” 

Perelman also “ruffled a lot of feathers” in industry, says Garrels, with his 2020 paper documenting his BABEL (“Basic Automatic B.S. Essay Language”) Generator, which output nonsense that commercial autograders nevertheless gave top marks. He saved some of his most systematic criticism for autograders’ defenders in academia, at one point calling out peers at the University of Akron for the methodology in their widely-touted paper claiming autograders performed just as well as human graders. 

At least one service, though, E.T.S., partly welcomed Perelman’s critique by making its autograder available to him for testing. (Others, like Pearson and Vantage Learning, declined.) He discovered he could ace the tests, even when his essay included non-factual gibberish and typographical errors:

Teaching assistants are paid an excessive amount of money. The average teaching assistant makes six times as much money as college presidents. In addition, they often receive a plethora of extra benefits such as private jets, vacations in the south seas, a staring roles in motion pictures. Moreover, in the Dickens novel Great Expectation, Pip makes his fortune by being a teaching assistant. It doesn’t matter what the subject is, since there are three parts to everything you can think of.

MIT career

Within MIT, Perelman’s legacy was his push to embed writing instruction into the whole of MIT’s curriculum, not as standalone expository writing subjects, let alone as merely a writing exam that incoming students could use to pass out of writing subjects altogether. Supported by a $325,000 National Science Foundation grant, he convinced MIT to hire writing instructors who were also subject matter experts, often with STEM PhDs. They were tasked with collaborating with departments to plant writing instruction into both existing curricula and new subjects. That effort eventually became the Writing Across the Curriculum program (today named Writing, Rhetoric, and Professional Communication) with a staff of more than 30 instructors.

Building out the infrastructure wasn’t quick, however. Perelman’s successor, Suzanne Lane ’85, says it took him almost 15 years. It started with proving to others just how uneven writing instruction at MIT actually was. “A whole cohort of students who took a lot of writing classes or got communication instruction in various places would make great progress,” Lane says. “But it was definitely possible to get through all of MIT without doing much writing at all.” 

To bolster his case, Perelman turned to alumni surveys. “The surveys asked how well MIT prepared you for your career,” says Lane. “The technical skills scored really high, but — what is horribly termed, sometimes, as ‘soft skills’ — communication skills, collaboration, etc., these scored really high on importance to career, but really low on how well MIT had prepared them.”

In other words, MIT alumni knew their stuff but were bad at communicating it, at a cost to their careers.

This led Perelman and others to push for a new undergraduate communication requirement. That NSF grant supported a 1997 pilot, designing experiments for courses that would be communication-intensive. It was a huge success. Every department participated. It involved 24 subjects and roughly 300 students. MIT faculty, following “lively” discussion at an April 1999 faculty meeting, approved the proposal of the creation of a report on the communication requirement’s implementation, followed a year later by its formal passage, effective fall 2001.

From that initial pilot of 24, there are now nearly 300 subjects that count toward the requirement, from ​​class 1.013 (Senior Civil and Environmental Engineering Design) to 24.918 (Workshop in Linguistic Research).

Connections beyond MIT

Early in his career, Perelman worked with Vincent DiMarco, a literature scholar at the University of Massachusetts at Amherst, to publish “The Middle English Letter of Alexander to Aristotle” (Brill, 1978). With Wang Computers as publisher, he was a technical writer and project leader on the “DOS Release 3.30 User’s Reference Guide.” He edited a book and chapter on writing studies and assessment with New Jersey Institute of Technology professor Norbert Elliot. And in a project he was particularly proud of, he worked with the New South Wales Teachers Federation in 2018 to convince Australia to reject the adoption of an automated essay grading regime. 

“Les was brilliant, with a Talmudic way of asking questions and entering academic debates,” says Nancy Sommers, whose work on undergraduate writing assessment at Harvard University paralleled Perelman’s. “I loved the way his eyes sparkled when he was ready to rip an adversary or a colleague who wasn’t up to his quick mind and vast, encyclopedic knowledge.” 

Openness to rhetorical combat didn’t keep Perelman from being a wonderful friend, Sommers says, saying he once waited for her at the airline gate with a sandwich and a smile after a canceled flight. “That was Les, so gracious, generous, anticipating the needs of friends, always there to offer sustenance and friendship.”

Donations in Perelman’s name can be made to UNICEF’s work supporting children in Ukraine, the Lexington Refugee Assistance Program, Doctors Without Borders, and the Ash Grove Movie Finishing Fund.

Each April in Japan, people participate in a tradition called “hanami,” or cherry-blossom viewing, where they picnic under the blooming trees. The tradition has a second purpose: The presence of people at these gatherings, often by water, helps solidify riverbanks and protect them from spring floods. The celebration has a dual purpose, by addressing, however incrementally, the threat of natural disaster.

The practice of creating things that also protect against disasters can be seen all over Japan, where many new or renovated school buildings have design features unfamiliar to students elsewhere. In Tokyo, one elementary school has a roof swimming pool that stores water and is used to help the building’s toilets flush, plus an additional rainwater catchment tank and exterior stairs leading to a large balcony that wraps around one side of the building.

Why? Well, Japan is prone to natural disasters, such as tsunamis, earthquakes, and flooding. The country’s schools often double as evacuation sites for local residents, and design practices increasingly reflect this. In normal times, the roof pool is where students learn to swim and helps keep the school cool, and the large balcony is used by spectators watching the adjacent school athletics field. In emergencies, water storage is crucial and exterior stairs help people ascend quickly to the gymnasium, built on the second floor — to keep evacuees safer during flooding.

Meanwhile, in one Tokyo district, rooftop solar power is now common. Some schools feature skylights and courtyards to bring in natural light. Again, these architectural features serve dual purposes. Solar power, for one, lowers annual operating costs, and it provides electricity even in case of grid troubles.

These are examples of what MIT scholar Miho Mazereeuw has termed “anticipatory design,” in which structures and spaces are built with dual uses, for daily living and for when crisis strikes.

“The idea is to have these proactive measures in place rather than being reactionary and jumping into action only after something has happened,” says Mazereeuw, an associate professor in MIT’s Department of Architecture and a leading expert on resilient design.

Now Mazereeuw has a new book on the subject, “Design Before Disaster: Japan’s Culture of Preparedness,” published by the University of Virginia Press. Based on many years of research, with extensive illustrations, Mazereeuw examines scores of successful design examples from Japan, both in terms of architectural features and the civic process that created them.

“I’m hoping there can be a culture shift,” Mazereeuw says. “Wherever you can invent design outcomes to help society be more resilient beforehand, it is not at exorbitant cost. You can design for exceptional everyday spaces but embed other infrastructure and flexibility in there, so when there is a flood event or earthquake, those buildings have more capability.”

Bosai and barbecue

Mazereeuw, who is also the head of MIT’s Urban Risk Lab, has been studying disaster preparedness for over 30 years. As part of the Climate Project at MIT, she is also one of the mission directors and has worked with communities around the world on resiliency planning.

Japan has a particularly well-established culture of preparedness, often referred to through the Japanese word “bosai.” Mazereeuw has been studying the country’s practices carefully since the 1990s. In researching the book, she has visited hundreds of sites in the country and talked to many officials, designers, and citizens along the way.

Indeed, Mazereeuw emphasizes, “A major theme in the book is connecting the top-down and bottom-up.” Some good design ideas come from planners and architects. Other have come from community groups and local residents. All these sources are important.

“The Japanese government does invest a lot in disaster research and recovery,” Mazereeuw says. “But I would hate for people in other countries to think this isn’t possible elsewhere. It’s the opposite. There are a lot of examples in here that don’t cost extra, because of careful design through community participation.”

As one example, Mazereeuw devotes a chapter of the book to public parks, which are often primary evacuation spaces for residents in case of emergency. Some have outdoor cooking facilities, which in normal times are used for, say, a weekend barbecue or local community events but are also there in case of emergency. Some parks also have water storage, or restroom facilities designed to expand if needed, and many serve as flood reservoirs, protecting the surrounding neighborhood.

“The barbecue facilities are a great example of dual use, connecting the everyday with disaster preparedness,” Mazereeuw says. “You can bring food into this beautiful park, so you’re used to using this space for cooking already. The idea is that your cognitive map of where you should go is connected to fun things you have done in the past.”

Some of the parks Mazereeuw surveys in the book are tiny pocket parks, which are also filled with useful resilience tools.

“Anticipatory design does not have to be monumental,” Mazereeuw writes in the book.

Negotiating through design

To be sure, some disaster mitigation measures are difficult to enact. In the Naiwan district of Kesennuma, as Mazereeuw outlines in the book, much of the local port area was destroyed in the 2011 tsunami, and the government wanted to build a seawall as part of the reconstruction plan. Some local residents and fishermen were unenthusiastic; a seawall could limit ocean access. Finally, after extended negotiations, designers created a seawall integrated into a new commercial district with cafes and stores, as well as new areas of public water access.

“This project used the power of design to negotiate between prefectural and local regulations, structural integrity and aesthetics, ocean access and safety,” Mazereeuw says.

Ultimately, working to build a coalition in support of resilience measures can help create more interesting and useful designs.

Other scholars have praised “Design Before Disaster.” Daniel P. Aldrich, a professor at Northeastern University, has called the book a “well-researched, clearly written investigation” into Japanese disaster-management practices, adding that any officials or citizens around the world “who seek to keep residents and communities safe from shocks of all kinds will learn something important from this book. It sets a high bar for future scholarship in the field.”

For her part, Mazereeuw emphasizes, “We can learn from the Japanese example, but it’s not a copy-paste thing. The book is so people can understand the essence of it and then create their own disaster preparedness culture and approach. This should be an all-hands process. Emergency management is not about relying on managers. It’s figuring out how we all play a part.”

During a summer internship at MIT Lincoln Laboratory, Ivy Mahncke, an undergraduate student of robotics engineering at Olin College of Engineering, took a hands-on approach to testing algorithms for underwater navigation. She first discovered her love for working with underwater robotics as an intern at the Woods Hole Oceanographic Institution in 2024. Drawn by the chance to tackle new problems and cutting-edge algorithm development, Mahncke began an internship with Lincoln Laboratory's Advanced Undersea Systems and Technology Group in 2025. 

Mahncke spent the summer developing and troubleshooting an algorithm that would help a human diver and robotic vehicle collaboratively navigate underwater. The lack of traditional localization aids — such as the Global Positioning System, or GPS — in an underwater environment posed challenges for navigation that Mahncke and her mentors sought to overcome. Her work in the laboratory culminated in field tests of the algorithm on an operational underwater vehicle. Accompanying group staff to field test sites in the Atlantic Ocean, Charles River, and Lake Superior, Mahncke had the opportunity see her software in action in the real world.

"One of the lead engineers on the project had split off to go do other work. And she said, 'Here's my laptop. Here are the things that you need to do. I trust you to go do them.' And so I got to be out on the water as not just an extra pair of hands, but as one of the lead field testers," Mahncke says. "I really felt that my supervisors saw me as the future generation of engineers, either at Lincoln Lab or just in the broader industry."

Says Madeline Miller, Mahncke's internship supervisor: "Ivy's internship coincided with a rigorous series of field tests at the end of an ambitious program. We figuratively threw her right in the water, and she not only floated, but played an integral part in our program's ability to hit several reach goals."

Lincoln Laboratory's summer research program runs from mid-May to August. Applications are now open. 

Video by Tim Briggs/MIT Lincoln Laboratory | 2 minutes, 59 seconds

It’s not every day that aspiring teenage engineers can see firsthand how planes are built. But a collaboration between nonprofit Engineering Tomorrow, aerospace firm Boeing, and alumni of the MIT Leaders for Global Operations (LGO) program working at Boeing is aiming to turn curiosity about aerospace engineering into possible careers for young students.

Boeing is LGO’s longest-standing industry collaborator, hosting LGO internships, recruiting LGO alumni, and hosting plant treks for future engineers. Engineering Tomorrow, a nonprofit dedicated to inspiring the next generation of engineers, frames the U.S. engineering workforce shortage as an economic and national security issue — and says the shortage isn’t in just engineers with degrees, but also in trained operators and technicians. They also recognize that many kids often start as natural tinkerers, but get scared off by higher-level math.

To bring more kids into the engineering fold, the organization delivers no-cost engineering labs to middle and high school students by collaborating with influential mentors, such as LGO graduates at organizations like Boeing.

“We want to inspire students by exposing them to professional engineers to illustrate the pathways for them to be problem-solvers in society,” explains Alex Dickson, Engineering Tomorrow’s program coordinator. “The demand for engineers has just gone up dramatically. It’s about being competitive on a global scale. We try to illustrate to students that there are many pathways into these careers.”

How MIT LGO makes engineering dreams a reality

Engineering Tomorrow’s collaboration with MIT LGO grew organically, through a robust alumni network. One of the nonprofit’s board members, LGO alumna Kristine Budill SM ’93, recognized a shared interest: the sizable Boeing LGO community wanted concrete ways to connect more directly with communities, and Engineering Tomorrow does just that.

Budill connected the organization with fellow LGO alumnus Cameron Hoffman MBA ’24, SM ’24, a Boeing manufacturing strategy manager who helped translate that shared mission into a real-world opportunity: an on-site Boeing experience that made engineering tangible for high school students.

The result: One lucky high school engineering design class from Mercer Island, Washington, recently got to experience Boeing 737s being built in person. In November 2025, 30 ninth graders at Mercer Island High School traveled to Boeing’s Renton, Washington, facility to learn how planes are constructed and understand what it really takes to have a career building them.

From the outset, the goal was to avoid the typical spectator field trip. Instead, Engineering Tomorrow and Hoffman designed a structured, multi-touch experience that prepared students before they ever set foot in the factory.

First, an Engineering Tomorrow liaison introduced key aerospace concepts and an associated lab challenge to the class via Zoom, then returned in person to guide Mercer students through a hands-on airplane-design lab, helping them translate theory into practice and answer questions about engineering pathways. Students then visited Boeing’s production facility, where they spoke with engineers from multiple disciplines — not just aerospace — and toured the factory floor.

By the time they arrived, students weren’t just impressed by the scale of the operation; they understood what they were seeing, asked informed questions, and left with a sharp sense of the many routes into engineering and manufacturing careers, Dickson says.

“Cameron set up an incredible on-site experience for the students that really made real-world engineering a more tangible experience for them,” Dickson says. “Many people think Boeing is just about aerospace engineering, because Boeing is an aerospace company. But they got to hear from mechanical engineers, electrical engineers, and workers with all sorts of backgrounds who made it clear that there’s no one set pathway into engineering or manufacturing.”

Then came the best part: Students got a VIP tour of the production facility, led by Boeing staff.

A snack and a tour

“It’s awe-inspiring: Dozens of unfinished airplanes are under one site, and you see all of the real-world production engineering that goes into something that oftentimes we take for granted when we step onto an airplane,” Dickson says.

When the big day arrived, students also met with engineering teams to learn about the history of the plant, complete with fun facts geared to high schoolers. (Did you know that a 737 takes off or lands every two seconds?) They learned about different career pathways, from design to production. It was easy to envision themselves working there, Hoffman says.

“Boeing is a company that a lot of folks work at for their entire career and take a lot of pride in the work that they do. We showed them: What does that look like? Do you want to be an engineer for your entire career? Do you want to be a people leader in the facility? Do you want to be a technical expert?” Hoffman says. “And the kids asked great questions.”

Then, the students — after snacks, of course — toured the production floor, where engineers assembled planes and tested parts. For Hoffman, that experience was deeply personal: He wished he’d experienced something similar growing up.

A 10-year Boeing veteran, Hoffman led the group throughout. He started at Boeing in 2015 as a recent college graduate, where he encountered several LGO alums who recommended the program.

“I’d been deeply interested in manufacturing since my early undergrad days. Boeing was an amazing place to work because our products are so complex, and the production systems are so fascinating,” he recalls.

Over time, he wanted to transition into people leadership with an MBA degree. His Boeing colleagues, well-represented among the LGO ranks, urged him toward the MIT program.

“LGO’s network is what makes it so special,” he says.

Upon returning to Boeing after completing his LGO degrees, Hoffman joined Boeing’s LGO/Tauber Leadership Development Program, which allows him to stay regularly engaged with the MIT LGO Program. One such activity where he remains engaged with the program is through the MIT LGO Alumni Board. As part of the board, Hoffman focuses on the social good committee, and the Engineering Tomorrow high school partnership was a perfect fit to meet that committee’s goals.

For Hoffman, these leadership initiatives are what makes LGO distinctive.

“When you graduate from a program like LGO, you’re often so forward-looking. It helps to take time to reflect on what an inspiration you can be to the people who come after you. MIT LGO focuses on both engineering and business. Our students want to study engineering because they want to be problem-solvers. The LGO program, which is at the intersection of engineering and business leadership, is just an incredible inspirational program for young students to see,” Hoffman says.

It was an opportunity he didn’t get as an ambitious young high schooler.

“As a kid, the only engineering class that was available to me was architectural drafting. If this opportunity was offered to me when I was in high school, I would’ve jumped out of my shoes at the chance. You get to see products that are just so complex; you really can't believe it until you see it,” he says.

Setting a positive precedent across industries

Mercer Island engineering design teacher Michael Ketchum had high praise for the field trip, considering it transformative for his students. He estimates that roughly 80 percent of them want to be engineers. He was impressed that the experience was more than just a tour, that it also included classroom support and airplane design kits, reinforcing core engineering concepts. The collaboration allowed them to broaden a previously CAD-focused class into one that also includes 3D printing, electronics, and aerospace applications. 

“For freshmen and sophomores, field trips are key. They stick in their head a bit longer than just school learning. If they get to see people getting excited talking about engineering, and it embeds it a little bit better in their brain,” Ketchum says.

In a post-trip survey, students reported being more likely to consider engineering after the experience.

“They expressed the idea that the conversations with engineers inspired them, and 100 percent of students said that seeing a production facility was one of the coolest parts of the program, which led to them being more inclined to want to be an engineer,” Engineering Tomorrow’s Dickson says.

Next year, the LGO network hopes to expand to partner with additional companies, from health care to biotech.

“The goal is to continue to create exposure. This visit was a really great proof of concept to see what’s valuable to students,” Hoffman says — and, ideally, future LGO alumni.

In a narrow strip of land along the Andes mountain range in central Chile, an Indigenous community has long celebrated the bark of a rare tree for its medicinal properties. Modern science only recently caught up to the tradition, finding the so-called soapbark tree contains potent compounds for boosting the human immune system.

The molecules have since been harnessed to make the world’s first malaria vaccine and to boost the effectiveness of vaccines for everything from shingles to Covid-19 and cancer. Unfortunately, unsustainable harvesting has threatened the existence of the tree species, leading the Chilean government to severely restrict lumbering.

The soapbark tree’s story is not unique. Plants are the foundation of industries such as pharmaceuticals, beauty, agriculture, and forestry, yet around 45 percent of plant species are in danger of going extinct. At the same time, human demand for plant products continues to rise. Ashley Beckwith SM ’18, PhD ’22 believes meeting that demand requires rethinking how plants are grown. Her company, Foray Bioscience, aims to make plant production faster, more adaptable, and less damaging to fragile natural supply chains.

The company is working to make it possible to grow any plant or plant product from single cells using biomanufacturing powered by artificial intelligence. Foray has already developed molecules, materials, and fabricated seeds with various partners, including academic researchers, nurseries, conservationists, and companies.

In one new partnership, Foray is working with the nursery West Coast Chestnut to deploy a more disease-resistant version of the chestnut trees that once filled forests across the eastern U.S. but have since been wiped out. The project is just one example of how AI and plant science can be leveraged to protect the plant populations that bring so much value to humans and the planet.

“Plant systems underpin every aspect of our daily lives, from the air we breathe to the food we eat, the clothes we wear, the homes we live in, and more,” Beckwith says. “But these plant systems are fragile and in decline. We need new strategies to ensure lasting access to the plant products and ecosystems we depend on.”

From human cells to plants

Beckwith focused on biology and materials manufacturing as a master’s student in MIT’s Department of Mechanical Engineering. Her research involved building platforms to enable precision treatments for human diseases. After graduating, she worked on a regenerative, self-sufficient farm that mimicked natural ecosystems, and began thinking about applying her work to address the fragility of plant systems.

Beckwith returned to MIT for her PhD to explore the idea of regenerative plant systems, studying in the lab of Research Scientist Luis Fernando Velásquez-García in the Department of Electrical Engineering and Computer Science.

“To address organ shortages for transplants, scientists aspire to grow kidneys that don’t have to be harvested from a human using tissue engineering,” Beckwith says. “What if we could do something similar for our plant systems?”

Beckwith went on to publish papers showing she could grow wood-like plant material in a lab. By adjusting certain chemicals, the researchers could precisely control properties like stiffness and density.

“I was thinking about how we build products, like wood, from the cell up instead of extracting from the top down,” Beckwith recalls. “It led to some foundational demonstrations that underpin the work we do at Foray today, but it also opened up questions: Where are these new approaches most urgently needed? What would it take to apply these tools where they’re needed, fast?”

Beckwith began exploring the idea of starting a company in 2021, participating in accelerator programs run by the E14 Fund and The Engine — both MIT-affiliated initiatives designed to support breakthrough science ventures. She officially founded Foray in February of 2022 after completing her PhD.

“Our early research showed that we could grow wood-like material directly from plant cells,” she says. “We are now able to grow not just wood without the tree, but also produce harvest-free molecules, materials, and even seeds by steering single cells to develop precisely into the products we need without ever having to grow the whole plant.”

Beckwith describes her lab-grown wood innovation as analogous to Uber if there were no internet — a powerful idea without the digital backbone to scale. To create the data foundation and ecosystem to scale plant innovation, Foray is now building the Pando AI platform to enable rapid discovery and deployment of these novel plant solutions.

“Pando functions like a Google Maps for plant growth,” Beckwith says. “It helps scientists navigate a really complex field of variables and arrive at a research destination efficiently — because to steer a cell to produce a particular product, there might be 50 different variables to tweak. It would take a lifetime to explore each of those, and that’s one reason why plant research is so slow today.”

The “operating system for plant science”

Foray’s team includes experts in plant biology, artificial intelligence, machine learning, computational biology, and process engineering.

“This is a very intersectional problem,” Beckwith says. “One of the most exciting things for me is building this highly capable team that is able to deliver solutions that could never be created in a silo.”

After a year of pilot collaborations with select researchers, Foray is preparing for a broader public launch of its Pando platform early this year.

Over the next several years, Beckwith hopes Foray will serve as an innovation engine for researchers and companies working across agriculture, materials, pharmaceuticals, and conservation. Foray already uses Pando internally to create plant solutions that overcome limitations in natural production.       

“Fabricated seeds are one capability that we’re really excited about,” Beckwith says. “Being able to grow seeds from cells lets you create really timely and scalable seed supplies to address gaps in restoration, or shorten the path to market for new, resilient crop varieties. There’s a lot to be gained by making our plant systems more adaptive.”

“We want to shorten plant development timelines, so solutions can be built in months, not decades,” Beckwith says. “We’re excited to be building tools that represent a step change in the way plant production can be done.”

As Foray’s products scale and more researchers use its platform, the company is hoping to help the plant science industry respond to some of our planet’s most pressing challenges.

“Right now, we’re focused on plants in labs,” Beckwith says. “In five years, we aim to be the operating system for all of plant science, making it possible to build anything from a single plant cell.”

In industrial plants around the world, tiny bubbles cause big problems. Bubbles clog filters, disrupt chemical reactions, reduce throughput during biomanufacturing, and can even cause overheating in electronics and nuclear power plants.

MIT Professor Kripa Varanasi has long studied methods to reduce bubble disruption. In a new study, Varanasi, along with PhD candidate Bert Vandereydt and former postdoc Saurabh Nath, have uncovered the physics behind a promising type of debubbling membrane material that is “aerophilic” — Greek for “air-loving.” The material can be used in systems of all types, allowing anyone to optimize their machine’s performance by breaking free from bubble-borne disruptions.

“We have figured out the structure of these bubble-attracting membrane materials to allow gas to evacuate in the fastest possible manner,” says Varanasi, the senior author of the study. “Think of trying to push honey through a coffee strainer: It’s not going to go through easily, whereas water will move through, and gas will move through even more easily. But even gas will reach a throughput limit, which depends on the properties of the gas and the liquid involved. By uncovering those limits, our research allows engineers to build better membranes for their systems.”

In the paper, which appears in the journal PNAS this week, the researchers distill their findings into a graph that allows anyone to plot a few characteristics of their system — like the viscosity of their gas and the surrounding liquid — and find the best membrane to make bubble removal near-instantaneous. Using their approach, the research team demonstrated a 1,000-fold acceleration in bubble removal in a bioreactor that’s used in the pharmaceutical industry, food and beverage manufacturing, cosmetics, chemical production, and more.

The researchers say the membranes, which repel water, could be used to improve the throughput of a wide range of advanced systems whose operation has been plagued to date by bubbles.

Better bubble breakers

Companies today try everything to burst bubbles. They deploy foam breakers that physically shear them, chemicals that act as antifoaming agents, even ultrasound. Such approaches have drawbacks in tightly controlled environments like bioreactors, where chemical defoamers can be toxic to cells, while mechanical agitation can damage delicate biological materials. Similar limitations apply to other industries where contamination or physical disturbance is unacceptable. As a result, many applications that cannot tolerate chemical defoamers or mechanical intervention remain fundamentally bottlenecked by foam formation.

“Biomanufacturing has really taken off in the last 10 years,” Vandereydt says. “We’re making a lot more out of biologic systems like cells and bacteria, and our reactors have increased in throughput from 5 million cells per millimeter of solution to 100 million cells per millimeter. However, the bubble evacuation and defoaming haven’t kept up — it’s becoming a significant rate-limiting step.”

To better understand the interaction between aerophilic membranes and bubbles, the MIT researchers used MIT.nano facilities to create a series of tiny porous silicon membranes with holes ranging in size from 10 microns to 200 microns. They coated the membranes with hydrophobic silica nanoparticles.

Placing them on the surface of different liquids, the researchers released single bubbles with varying viscosity and recorded the interaction using high-speed imaging as each collided with the membranes.

“We started by trying to take a very complicated system, like foam being generated in a bioreactor, and study it in the simplest form to understand what’s happening,” Vandereydt says.

At first, the bigger the holes, the faster the bubbles disappeared. The researchers also changed the bubble gas from air to hydrogen, which has half the viscosity, and found the speed of bubble destruction doubled.

But after about a 1,000-fold acceleration in bubble destruction, the researchers hit a wall no matter how big the membrane holes were. They had run up against a different physical limit to investigate.

The researchers then tried changing the viscosity of their liquid, from water to something closer to honey. They found viscosity only plays a role in the speed of bubble destruction when the liquid is 200 times the viscosity of liquid. Further experiments revealed the biggest factor for slowing bubble evacuation was inertial resistance in the liquid.

“Through experimentation, we showed there are three different limits [to the speed of bubble destruction],” Vandereydt says. “There is the viscous limit of the gas in a low-viscosity, low-permeability setup. Then there’s the viscous resistance of the liquid in the high-permeability, high-viscosity regime. Then we have the inertial limit of the liquid.”

The team used a bioreactor to experimentally validate their findings and charted them in a map that engineers can use to enter the characteristics of their system and find both the best membrane for their situation and the biggest factor slowing bubble evacuation.

The science of bubbles

The research should be useful for anyone trying to accelerate the destruction of bubbles in their industrial device, but it also improves our understanding of the physics underpinning bubble dynamics.

“We have identified three different throughput limits, and the physics behind those limits, and we have reduced it to very simple laws,” Nath explains. “How fast you can go is first dictated between surface tension and inertia. But you may also hit a different limit, where the pores are extremely small, so the gas finds it difficult to move through them. In that case, the viscosity of the gas is meaningful. But you may also have a bubble which was originally in something like honey, which means it’s not enough the gas is moving, the liquid also must refill the space behind it. No matter what your conditions are, you will be switching between these three limits.”

Varanasi says health care companies, chemical manufacturers, and even breweries have expressed interest in the work. His team plans to commercially develop the membranes for industrial use.

“These physical insights allowed us to design membranes that, quite surprisingly, evacuate bubbles even faster than a free liquid-gas interface,” says Varanasi.

The researchers’ design map could also be used to model natural systems and even liquid-liquid systems, which could be used to create membranes that remove oil spills from water or help efficiently extract hydrogen from water-splitting electrodes. Ultimately the biggest beneficiaries of the findings will be companies grappling with bubbles.

“Though small, bubbles quietly dictate the performance limits of many advanced technologies,” says Varanasi. “Our results provide a way to eliminate that bottleneck and unlock entirely new levels of performance across industries. These membranes can be readily retrofitted into existing systems, and our framework allows them to be rapidly designed and optimized for specific applications. We’re excited to work with industry to translate these insights into impact.”

The work was supported, in part, by MIT Lincoln Laboratory and used MIT.nano facilities.

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning.

But developing reasoning models demands an enormous amount of computation and energy due to inefficiencies in the training process. While a few of the high-power processors continuously work through complicated queries, others in the group sit idle.

Researchers from MIT and elsewhere found a way to use this computational downtime to efficiently accelerate reasoning-model training.

Their new method automatically trains a smaller, faster model to predict the outputs of the larger reasoning LLM, which the larger model verifies. This reduces the amount of work the reasoning model must do, accelerating the training process.

The key to this system is its ability to train and deploy the smaller model adaptively, so it kicks in only when some processors are idle. By leveraging computational resources that would otherwise have been wasted, it accelerates training without incurring additional overhead.

When tested on multiple reasoning LLMs, the method doubled the training speed while preserving accuracy. This could reduce the cost and increase the energy efficiency of developing advanced LLMs for applications such as forecasting financial trends or detecting risks in power grids.

“People want models that can handle more complex tasks. But if that is the goal of model development, then we need to prioritize efficiency. We found a lossless solution to this problem and then developed a full-stack system that can deliver quite dramatic speedups in practice,” says Qinghao Hu, an MIT postdoc and co-lead author of a paper on this technique.

He is joined on the paper by co-lead author Shang Yang, an electrical engineering and computer science (EECS) graduate student; Junxian Guo, an EECS graduate student; senior author Song Han, an associate professor in EECS, member of the Research Laboratory of Electronics and a distinguished scientist of NVIDIA; as well as others at NVIDIA, ETH Zurich, the MIT-IBM Watson AI Lab, and the University of Massachusetts at Amherst. The research will be presented at the ACM International Conference on Architectural Support for Programming Languages and Operating Systems.

Training bottleneck

Developers want reasoning LLMs to identify and correct mistakes in their critical thinking process. This capability allows them to ace complicated queries that would trip up a standard LLM.

To teach them this skill, developers train reasoning LLMs using a technique called reinforcement learning (RL). The model generates multiple potential answers to a query, receives a reward for the best candidate, and is updated based on the top answer. These steps repeat thousands of times as the model learns.

But the researchers found that the process of generating multiple answers, called rollout, can consume as much as 85 percent of the execution time needed for RL training.

“Updating the model — which is the actual ‘training’ part — consumes very little time by comparison,” Hu says.

This bottleneck occurs in standard RL algorithms because all processors in the training group must finish their responses before they can move on to the next step. Because some processors might be working on very long responses, others that generated shorter responses wait for them to finish.

“Our goal was to turn this idle time into speedup without any wasted costs,” Hu adds.

They sought to use an existing technique, called speculative decoding, to speed things up. Speculative decoding involves training a smaller model called a drafter to rapidly guess the future outputs of the larger model.

The larger model verifies the drafter’s guesses, and the responses it accepts are used for training.

Because the larger model can verify all the drafter’s guesses at once, rather than generating each output sequentially, it accelerates the process.

An adaptive solution

But in speculative decoding, the drafter model is typically trained only once and remains static. This makes the technique infeasible for reinforcement learning, since the reasoning model is updated thousands of times during training.

A static drafter would quickly become stale and useless after a few steps.

To overcome this problem, the researchers created a flexible system known as “Taming the Long Tail,” or TLT.

The first part of TLT is an adaptive drafter trainer, which uses free time on idle processors to train the drafter model on the fly, keeping it well-aligned with the target model without using extra computational resources.

The second component, an adaptive rollout engine, manages speculative decoding to automatically select the optimal strategy for each new batch of inputs. This mechanism changes the speculative decoding configuration based on the training workload features, such as the number of inputs processed by the draft model and the number of inputs accepted by the target model during verification.

In addition, the researchers designed the draft model to be lightweight so it can be trained quickly. TLT reuses some components of the reasoning model training process to train the drafter, leading to extra gains in acceleration.

“As soon as some processors finish their short queries and become idle, we immediately switch them to do draft model training using the same data they are using for the rollout process. The key mechanism is our adaptive speculative decoding — these gains wouldn’t be possible without it,” Hu says.

They tested TLT across multiple reasoning LLMs that were trained using real-world datasets. The system accelerated training between 70 and 210 percent while preserving the accuracy of each model.

As an added bonus, the small drafter model could readily be utilized for efficient deployment as a free byproduct.

In the future, the researchers want to integrate TLT into more types of training and inference frameworks and find new reinforcement learning applications that could be accelerated using this approach.

“As reasoning continues to become the major workload driving the demand for inference, Qinghao’s TLT is great work to cope with the computation bottleneck of training these reasoning models. I think this method will be very helpful in the context of efficient AI computing,” Han says.

This work is funded by the MIT-IBM Watson AI Lab, the MIT AI Hardware Program, the MIT Amazon Science Hub, Hyundai Motor Company, and the National Science Foundation.