lunes, 22 de diciembre de 2025

One pull of a string is all it takes to deploy these complex structures

MIT researchers have developed a new method for designing 3D structures that can be transformed from a flat configuration into their curved, fully formed shape with only a single pull of a string.

This technique could enable the rapid deployment of a temporary field hospital at the site of a disaster such as a devastating tsunami — a situation where quick medical action is essential to save lives.

The researchers’ approach converts a user-specified 3D structure into a flat shape composed of interconnected tiles. The algorithm uses a two-step method to find the path with minimal friction for a string that can be tightened to smoothly actuate the structure.

The actuation mechanism is easily reversible, and if the string is released, the structure quickly returns to its flat configuration. This could enable complex, 3D structures to be stored and transported more efficiently and with less cost.

In addition, the designs generated by their system are agnostic to the fabrication method, so complete structures can be produced using 3D printing, CNC milling, molding, or other techniques.

This method could enable the creation of transportable medical devices, foldable robots that can flatten to enter hard-to-reach spaces, or even modular space habitats that can be actuated by robots working on the surface of Mars.

“The simplicity of the whole actuation mechanism is a real benefit of our approach. The user just needs to provide their intended design, and then our method optimizes it in such a way that it holds the shape after just one pull on the string, so the structure can be deployed very easily. I hope people will be able to use this method to create a wide variety of different, deployable structures,” says Akib Zaman, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this new method.

He is joined on the paper by MIT graduate student Jacqueline Aslarus; postdoc Jiaji Li; Associate Professor Stefanie Mueller, leader of the Human-Computer Interaction (HCI) Engineering Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL); and senior author Mina Konaković Luković, an assistant professor and leader of the Algorithmic Design Group in CSAIL. The research was presented at the Association for Computing Machinery’s SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia.

From ancient art to an algorithm

Creating deployable structures from flat pieces simplifies on-site assembly and could be especially useful in constructing emergency shelters after natural disasters. On a smaller scale, items like foldable bike helmets could improve the safety of riders who would otherwise be unable to carry a bulky helmet.

But converting flat, deployable objects into their 3D shape often requires specialized equipment or multiple steps, and the actuation mechanism is typically difficult to reverse.

“Because of these challenges, deployable structures tend to be manually designed and quite simple, geometrically. But if we can create more complex geometries, while simplifying the actuation mechanism, we could enhance the capabilities of these deployables,” Zaman says.

To do this, the researchers created a method that automatically converts a user’s 3D design into a flat structure comprised of tiles, connected by rotating hinges at the corners, which can be fully actuated by pulling a single string one time.

Hand pulls a string and a soft, curved lid-like structure is formed out of interconnected blocks.

Their method breaks a user design into a grid of quadrilateral tiles inspired by kirigami, the ancient Japanese art of paper cutting. With kirigami, by cutting a material in certain ways, they can encode it with unique properties. In this case, they use kirigami to create an auxetic mechanism, which is a structure that gets thicker when stretched and thinner when compressed.

After encoding the 3D geometry into a flat set of auxetic tiles, the algorithm computes the minimum number of points that the tightening string must lift to fully deploy the 3D structure. Then, it finds the shortest path that connects those lift points, while including all areas of the object’s boundary that must be connected to guide the structure into its 3D configuration. It does these calculations in such a way that the optimal string path minimizes friction, enabling the structure to be smoothly actuated with just one pull.

“Our method makes it easy for the user. All they have to do is input their design, and our algorithm automatically takes care of the rest. Then all the user needs to do is to fabricate the tiles exactly the way it has been computed by the algorithm,” Zaman says.

For instance, one could fabricate a structure using a multi-material 3D printer that prints the hinges of the tiles with a flexible material and the other surfaces with a hard material.

A scale independent method

One of the biggest challenges the researchers faced was figuring out how the string route and the friction within the string channel can be effectively modeled as close to physical reality.

“While playing with a few fabricated models, we observed that closing boundary tiles is a must to enable a successful deployment and the string must be routed through them. Later, we proved this observation mathematically. Then, we looked back at an age-old physics equation and used it to formulate the optimization problem for friction minimization,” he says.

They built their automatic algorithm into an interactive user interface that allows one to design and optimize configurations to generate manufacturable objects.

The researchers used their method to design several objects of different sizes, from personalized medical items including a splint and a posture corrector to an igloo-like portable structure. They also fabricated a deployable, human-scale chair they designed using their method.

A long rectangular strip of interconnected blocks becomes a tiny chair with curved features.

This method is scale independent, so it could be used to create tiny deployable objects that are injected and actuated inside the body, or architectural structures, like the frame of a building, that are deployed and actuated on-site using cranes.

In the future, the researchers want to further explore the design of tiny structures, while also tackling the engineering challenges involved in creating architectural installations, such as determining the ideal cable thickness and the necessary strength of the hinges. In addition, they want to create a self-deploying mechanism, so the structures do not need to be actuated by a human or robot.

This research is funded, in part, by an MIT Research Support Committee Award.



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3 Questions: How to launch a successful climate and energy venture

In 2013, Martin Trust Center for MIT Entrepreneurship Managing Director Bill Aulet published “Disciplined Entrepreneurship: 24 Steps to a Successful Startup,” which has since sold hundreds of thousands of copies and been used to teach entrepreneurship at universities around the world. One MIT course where it’s used is 15.366 (Climate and Energy Ventures), where instructors have tweaked the framework over the years. In a new book, “Disciplined Entrepreneurship for Climate and Energy Ventures,” they codify those changes and provide a new blueprint for entrepreneurs working in the climate and energy spaces.

MIT News spoke with lead author and Trust Center Entrepreneur-in-Residence Ben Soltoff, who wrote the book with Aulet, Senior Lecturer Tod Hynes, Senior Lecturer Francis O’Sullivan, and Lecturer Libby Wayman. Soltoff explains why climate and energy entrepreneurship is so challenging and talks about some of the new steps in the book.

Q: What are climate and energy ventures?

A: It’s a broad umbrella. These ventures aren’t all in a specific industry or structured in the same way. They could be software, they could be hardware, or they could be deep tech coming out of labs. This book is also written for people working in government, large corporations, or nonprofits. Each of those folks can benefit from the entrepreneurial framework in this book. We very intentionally refer to them as climate and energy ventures in the book, not just climate and energy startups.

One common theme is meeting the challenge of providing enough energy for current and future needs without exacerbating, or even while reducing, the impact we have on our planet. Generally, climate and energy ventures are less likely to be only software. Many of the solutions we need are around molecules, not bits. A lot of it is breakthrough technology and science from research labs. You could be making a useful fuel, removing CO2 from the atmosphere, or delivering something in a novel way. Your venture might produce a chemical or molecule that’s already being provided and is a commodity. It needs to be not only more sustainable, but better for your customers — either cheaper, more reliable, or more securely delivered. Ultimately, all of these ventures have to provide value. They also often involve physical infrastructure that you have to scale up — not just 10 times or 100 times, but 1,000 times or more — from original lab demonstrations.

Q: How should climate and energy entrepreneurs be thinking about navigating financing and working with the government?

A: One of the major themes of the book is the importance of figuring out if policy is in your favor and constantly applying a policy lens to what you’re building. Finance is another major theme. In climate and energy, these things are fundamental, and we need to consider them from the beginning. We talk about different “valleys of death” — the idea that going from one stage to the next stage requires this jump in time and resources that presents a big challenge. That also relates to the jump in scale of the technology, from a lab scale to something you can produce and sell in a quantity and at a cost the market is interested in. All of that requires financing.

At an early stage, a lot of these ventures are funded through grants and research funding. Later, they start getting early-stage capital — often venture capital. Eventually, as folks are scaling, they move to debt and project financing. Companies need to be very intentional about the type of financing they’re going to pursue and at what stage. We have an entire step on creating a long-term capital plan. Entrepreneurs need to be very clear about the story they’re going to tell investors at different stages. Otherwise, they can paint themselves into a corner and fail to build a company for the next stage of capital they need.

In terms of policy, entrepreneurs should use the policy environment as a filter for selecting a market. We have a story in the book about a startup that switched from working in sub-Saharan Africa to the U.S. after the Inflation Reduction Act passed. As those incentives began disappearing, they still had the option to return to their original market. It’s not ideal for them, but they are still able to build profitable projects. You shouldn’t build a company based on the incentives alone, but you should understand which way the wind is blowing and take advantage of policy when it’s in your favor. That said, policy can always change.

Q: How should climate and energy entrepreneurs select the right market “stepping stones”?

A: Each of the “Disciplined Entrepreneurship” books talks about the importance of selecting customers and listening to your customers. When thinking about their beachhead market, or where to initially focus, climate and energy entrepreneurs need to look for the easiest near-term opportunity to plug in their technology. Subsequent market selection is also driven by technology. Instead of just picking a beachhead market and figuring everything else out later, there often needs to be an intentional choice of what we call market stepping stones. You start by focusing on an initial market in the early days — land and expand — but there needs to be a long-term strategy, so you don’t go down a dead end. These ventures don’t have a lot of flexibility as they build out potentially expensive technologies. Being intentional means having a pathway planned from the beachhead market up to the big prize that makes the entire enterprise worthwhile. The prize means having a big impact but also targeting a big market opportunity.

We have an example in the book of a company that can turn CO2 into useful products. They knew the big prize was turning it into fuel, most likely aviation fuel, but they couldn’t produce at the right volume or cost early on, so they looked at other applications. They started with making vodka from CO2 because it was low-volume and high-margin. Then the pandemic happened, so they made hand sanitizer. Then they made perfume, which had the highest margins of all. By that point, they were ready to start moving into the fuel market. The stepping stones are about figuring out who is willing to buy the simple version of your technology or product and pay a premium. Initially, looking at that company, you might say, “They’re not going to save the planet by selling vodka.” But it was a critical stepping stone to get to the big prize. Long-term thinking is essential for ventures in this space.



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Study: High-fat diets make liver cells more likely to become cancerous

One of the biggest risk factors for developing liver cancer is a high-fat diet. A new study from MIT reveals how a fatty diet rewires liver cells and makes them more prone to becoming cancerous.

The researchers found that in response to a high-fat diet, mature hepatocytes in the liver revert to an immature, stem-cell-like state. This helps them to survive the stressful conditions created by the high-fat diet, but in the long term, it makes them more likely to become cancerous.

“If cells are forced to deal with a stressor, such as a high-fat diet, over and over again, they will do things that will help them survive, but at the risk of increased susceptibility to tumorigenesis,” says Alex K. Shalek, director of the Institute for Medical Engineering and Sciences (IMES), the J. W. Kieckhefer Professor in IMES and the Department of Chemistry, and a member of the Koch Institute for Integrative Cancer Research at MIT, the Ragon Institute of MGH, MIT, and Harvard, and the Broad Institute of MIT and Harvard.

The researchers also identified several transcription factors that appear to control this reversion, which they believe could make good targets for drugs to help prevent tumor development in high-risk patients.

Shalek; Ömer Yilmaz, an MIT associate professor of biology and a member of the Koch Institute; and Wolfram Goessling, co-director of the Harvard-MIT Program in Health Sciences and Technology, are the senior authors of the study, which appears today in Cell. MIT graduate student Constantine Tzouanas, former MIT postdoc Jessica Shay, and Massachusetts General Brigham postdoc Marc Sherman are the co-first authors of the paper.

Cell reversion

A high-fat diet can lead to inflammation and buildup of fat in the liver, a condition known as steatotic liver disease. This disease, which can also be caused by a wide variety of long-term metabolic stresses such as high alcohol consumption, may lead to liver cirrhosis, liver failure, and eventually cancer.

In the new study, the researchers wanted to figure out just what happens in cells of the liver when exposed to a high-fat diet — in particular, which genes get turned on or off as the liver responds to this long-term stress.

To do that, the researchers fed mice a high-fat diet and performed single-cell RNA-sequencing of their liver cells at key timepoints as liver disease progressed. This allowed them to monitor gene expression changes that occurred as the mice advanced through liver inflammation, to tissue scarring and eventually cancer.

In the early stages of this progression, the researchers found that the high-fat diet prompted hepatocytes, the most abundant cell type in the liver, to turn on genes that help them survive the stressful environment. These include genes that make them more resistant to apoptosis and more likely to proliferate.

At the same time, those cells began to turn off some of the genes that are critical for normal hepatocyte function, including metabolic enzymes and secreted proteins.

“This really looks like a trade-off, prioritizing what’s good for the individual cell to stay alive in a stressful environment, at the expense of what the collective tissue should be doing,” Tzouanas says.

Some of these changes happened right away, while others, including a decline in metabolic enzyme production, shifted more gradually over a longer period. Nearly all of the mice on a high-fat diet ended up developing liver cancer by the end of the study.

When cells are in a more immature state, it appears that they are more likely to become cancerous if a mutation occurs later on, the researchers say.

“These cells have already turned on the same genes that they’re going to need to become cancerous. They’ve already shifted away from the mature identity that would otherwise drag down their ability to proliferate,” Tzouanas says. “Once a cell picks up the wrong mutation, then it’s really off to the races and they’ve already gotten a head start on some of those hallmarks of cancer.”

The researchers also identified several genes that appear to orchestrate the changes that revert hepatocytes to an immature state. While this study was going on, a drug targeting one of these genes (thyroid hormone receptor) was approved to treat a severe form of steatotic liver disease called MASH fibrosis. And, a drug activating an enzyme that they identified (HMGCS2) is now in clinical trials to treat steatotic liver disease.

Another possible target that the new study revealed is a transcription factor called SOX4, which is normally only active during fetal development and in a small number of adult tissues (but not the liver).

Cancer progression

After the researchers identified these changes in mice, they sought to discover if something similar might be happening in human patients with liver disease. To do that, they analyzed data from liver tissue samples removed from patients at different stages of the disease. They also looked at tissue from people who had liver disease but had not yet developed cancer.

Those studies revealed a similar pattern to what the researchers had seen in mice: The expression of genes needed for normal liver function decreased over time, while genes associated with immature states went up. Additionally, the researchers found that they could accurately predict patients’ survival outcomes based on an analysis of their gene expression patterns.

“Patients who had higher expression of these pro-cell-survival genes that are turned on with high-fat diet survived for less time after tumors developed,” Tzouanas says. “And if a patient has lower expression of genes that support the functions that the liver normally performs, they also survive for less time.”

While the mice in this study developed cancer within a year or so, the researchers estimate that in humans, the process likely extends over a longer span, possibly around 20 years. That will vary between individuals depending on their diet and other risk factors such as alcohol consumption or viral infections, which can also promote liver cells’ reversion to an immature state.

The researchers now plan to investigate whether any of the changes that occur in response to a high-fat diet can be reversed by going back to a normal diet, or by taking weight-loss drugs such as GLP-1 agonists. They also hope to study whether any of the transcription factors they identified could make good targets for drugs that could help prevent diseased liver tissue from becoming cancerous.

“We now have all these new molecular targets and a better understanding of what is underlying the biology, which could give us new angles to improve outcomes for patients,” Shalek says.

The research was funded, in part, by a Fannie and John Hertz Foundation Fellowship, a National Science Foundation Graduate Research Fellowship, the National Institutes of Health, and the MIT Stem Cell Initiative through Foundation MIT.



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Anything-goes “anyons” may be at the root of surprising quantum experiments

In the past year, two separate experiments in two different materials captured the same confounding scenario: the coexistence of superconductivity and magnetism. Scientists had assumed that these two quantum states are mutually exclusive; the presence of one should inherently destroy the other.

Now, theoretical physicists at MIT have an explanation for how this Jekyll-and-Hyde duality could emerge. In a paper appearing today in the Proceedings of the National Academy of Sciences, the team proposes that under certain conditions, a magnetic material’s electrons could splinter into fractions of themselves to form quasiparticles known as “anyons.” In certain fractions, the quasiparticles should flow together without friction, similar to how regular electrons can pair up to flow in conventional superconductors.

If the team’s scenario is correct, it would introduce an entirely new form of superconductivity — one that persists in the presence of magnetism and involves a supercurrent of exotic anyons rather than everyday electrons.

“Many more experiments are needed before one can declare victory,” says study lead author Senthil Todadri, the William and Emma Rogers Professor of Physics at MIT. “But this theory is very promising and shows that there can be new ways in which the phenomenon of superconductivity can arise.”

What’s more, if the idea of superconducting anyons can be confirmed and controlled in other materials, it could provide a new way to design stable qubits — atomic-scale “bits” that interact quantum mechanically to process information and carry out complex computations far more efficiently than conventional computer bits.

“These theoretical ideas, if they pan out, could make this dream one tiny step within reach,” Todadri says.

The study’s co-author is MIT physics graduate student Zhengyan Darius Shi.

“Anything goes”

Superconductivity and magnetism are macroscopic states that arise from the behavior of electrons. A material is a magnet when electrons in its atomic structure have roughly the same spin, or orbital motion, creating a collective pull in the form of a magnetic field within the material as a whole. A material is a superconductor when electrons passing through, in the form of voltage, can couple up in “Cooper pairs.” In this teamed-up state, electrons can glide through a material without friction, rather than randomly knocking against its atomic latticework.

For decades, it was thought that superconductivity and magnetism should not co-exist; superconductivity is a delicate state, and any magnetic field can easily sever the bonds between Cooper pairs. But earlier this year, two separate experiments proved otherwise. In the first experiment, MIT’s Long Ju and his colleagues discovered superconductivity and magnetism in rhombohedral graphene — a synthesized material made from four or five graphene layers.

“It was electrifying,” says Todadri, who recalls hearing Ju present the results at a conference. “It set the place alive. And it introduced more questions as to how this could be possible.”

Shortly after, a second team reported similar dual states in the semiconducting crystal molybdenium ditelluride (MoTe2). Interestingly, the conditions in which MoTe2 becomes superconductive happen to be the same conditions in which the material exhibits an exotic “fractional quantum anomalous Hall effect,” or FQAH — a phenomenon in which any electron passing through the material should split into fractions of itself. These fractional quasiparticles are known as “anyons.”

Anyons are entirely different from the two main types of particles that make up the universe: bosons and fermions. Bosons are the extroverted particle type, as they prefer to be together and travel in packs. The photon is the classic example of a boson. In contrast, fermions prefer to keep to themselves, and repel each other if they are too near. Electrons, protons, and neutrons are examples of fermions. Together, bosons and fermions are the two major kingdoms of particles that make up matter in the three-dimensional universe.

Anyons, in contrast, exist only in two-dimensional space. This third type of particle was first predicted in the 1980s, and its name was coined by MIT’s Frank Wilczek, who meant it as a tongue-in-cheek reference to the idea that, in terms of the particle’s behavior, “anything goes.”

A few years after anyons were first predicted, physicists such as Robert Laughlin PhD ’79, Wilczek, and others also theorized that, in the presence of magnetism, the quasiparticles should be able to superconduct.

“People knew that magnetism was usually needed to get anyons to superconduct, and they looked for magnetism in many superconducting materials,” Todadri says. “But superconductivity and magnetism typically do not occur together. So then they discarded the idea.”

But with the recent discovery that the two states can, in fact, peacefully coexist in certain materials, and in MoTe2 in particular, Todadri wondered: Could the old theory, and superconducting anyons, be at play?

Moving past frustration

Todadri and Shi set out to answer that question theoretically, building on their own recent work. In their new study, the team worked out the conditions under which superconducting anyons could emerge in a two-dimensional material. To do so, they applied equations of quantum field theory, which describes how interactions at the quantum scale, such as the level of individual anyons, can give rise to macroscopic quantum states, such as superconductivity. The exercise was not an intuitive one, since anyons are known to stubbornly resist moving, let alone superconducting, together.

“When you have anyons in the system, what happens is each anyon may try to move, but it’s frustrated by the presence of other anyons,” Todadri explains. “This frustration happens even if the anyons are extremely far away from each other. And that’s a purely quantum mechanical effect.”

Even so, the team looked for conditions in which anyons might break out of this frustration and move as one macroscopic fluid. Anyons are formed when electrons splinter into fractions of themselves under certain conditions in two-dimensional, single-atom-thin materials, such as MoTe2. Scientists had previously observed that MoTe2 exhibits the FQAH, in which electrons fractionalize, without the help of an external magnetic field.

Todadri and Shi took MoTe2 as a starting point for their theoretical work. They modeled the conditions in which the FQAH phenomenon emerged in MoTe2, and then looked to see how electrons would splinter, and what types of anyons would be produced, as they theoretically increased the number of electrons in the material.

They noted that, depending on the material’s electron density, two types of anyons can form: anyons with either 1/3 or 2/3 the charge of an electron. They then applied equations of quantum field theory to work out how either of the two anyon types would interact, and found that when the anyons are mostly of the 1/3 flavor, they are predictably frustrated, and their movement leads to ordinary metallic conduction. But when anyons are mostly of the 2/3 flavor, this particular fraction encourages the normally stodgy anyons to instead move collectively to form a superconductor, similar to how electrons can pair up and flow in conventional superconductors.

“These anyons break out of their frustration and can move without friction,” Todadri says. “The amazing thing is, this is an entirely different mechanism by which a superconductor can form, but in a way that can be described as Cooper pairs in any other system.”

Their work revealed that superconducting anyons can emerge at certain electron densities. What’s more, they found that when superconducting anyons first emerge, they do so in a totally new pattern of swirling supercurrents that spontaneously appear in random locations throughout the material. This behavior is distinct from conventional superconductors and is an exotic state that experimentalists can look for as a way to confirm the team’s theory. If their theory is correct, it would introduce a new form of superconductivity, through the quantum interactions of anyons.

“If our anyon-based explanation is what is happening in MoTe2, it opens the door to the study of a new kind of quantum matter which may be called ‘anyonic quantum matter,’” Todadri says. “This will be a new chapter in quantum physics.”

This research was supported, in part, by the National Science Foundation. 



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viernes, 19 de diciembre de 2025

Statement on Professor Nuno Loureiro

MIT has shared the following statement following last night’s announcements by authorities in Rhode Island and Massachusetts about the individual responsible for the murders of Prof. Nuno Loureiro at his home in Brookline and two students during a mass shooting at Brown University.
 
"We are grateful to all who played a part in identifying and tracking down the suspect in the killing of Prof. Loureiro. Our community continues to mourn and remember Nuno — an incredible scientist, colleague, mentor, and friend. Our thoughts are also with the Brown University community, which suffered so much loss this week.

As the authorities work to answer remaining questions, our continuing position is to refer to the law enforcement agencies and the U.S. Attorney of Massachusetts for information.

For now, our focus is on our community, on Nuno’s family, and all those who knew him.”


Remembering Nuno

 
The MIT News obituary will continue to be updated with remembrances from our community members who worked alongside Nuno.
 
In time, the many communities Nuno belonged to will create opportunities to mourn his loss and celebrate his life.

This page may be updated as there is additional public information to share.


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MIT goes quantum

Everyone is talking about new quantum technologies, but what exactly is quantum and why are scientists, engineers and technologists so excited by the potential for this new field? On Monday, December 8, MIT will launch the MIT Quantum Initiative (or QMIT), an Institute-wide effort to apply quantum breakthroughs to the most consequential challenges in science, technology, industry, and national security. 

The interdisciplinary endeavor, the newest of MIT President Sally Kornbluth’s strategic initiatives, will bring together MIT researchers and domain experts from a range of industries to identify and tackle practical challenges wherever quantum solutions could achieve the greatest impact. In collaboration with MIT Lincoln Laboratory, industry leaders and end users from all domains, researchers from across the traditional quantum disciplines will work to identify and advance the most significant practical applications in science, technology, industry and national security.

The QMIT launch event will feature:

More information on QMIT can be found here and the full agenda can be found here



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jueves, 18 de diciembre de 2025

“Wait, we have the tech skills to build that”

Students can take many possible routes through MIT’s curriculum, which can zigag through different departments, linking classes and disciplines in unexpected ways. With so many options, charting an academic path can be overwhelming, but a new tool called NerdXing is here to help.

The brainchild of senior Julianna Schneider and other students in the MIT Schwarzman College of Computing Undergraduate Advisory Group (UAG), NerdXing lets students search for a class and see all the other classes students have gone on to take in the past, including options that are off the beaten track.

“I hope that NerdXing will democratize course knowledge for everyone,” Schneider says. “I hope that for anyone who's a freshman and maybe hasn't picked their major yet, that they can go to NerdXing and start with a class that they would maybe never consider — and then discover that, ‘Oh wait, this is perfect for this really particular thing I want to study.’”

As a student double-majoring in artificial intelligence and decision-making and in mathematics, and doing research in the Biomimetic Robotics Laboratory in the Department of Mechanical Engineering, Schneider knows the benefits of interdisciplinary studies. It’s a part of the reason why she joined the UAG, which advises the MIT Schwarzman College of Computing’s leadership as it advances education and research at the intersections between computing, engineering, the arts, and more.

Through all of her activities, Schneider seeks to make people’s lives better through technology.

“This process of finding a problem in my community and then finding the right technology to solve that — that sort of approach and that framework is what guides all the things I do,” Schneider says. “And even in robotics, the things that I care about are guided by the sort of skills that I think we need to develop to be able to have meaningful applications.”

From Albania to MIT

Before she ever touched a robot or wrote code, Schneider was an accomplished young classical pianist in Albania. When she discovered her passion for robotics at age 13, she applied some of the skills she had learned while playing piano.

“I think on some fundamental level, when I was a pianist, I thought constantly about my motor dynamics as a human being, and how I execute really complex skills but do it over and over again at the top of my ability,” Schneider says. “When it came to robotics, I was building these robotic arms that also had to operate at the top of their ability every time and do really complex tasks. It felt kind of similar to me, like a fun crossover.”

Schneider joined her high school’s robotics team as a middle schooler, and she was so immediately enamored that she ended up taking over most of the coding and building of the team’s robot. She went on to win 14 regional and national awards across the three teams she led throughout middle and high school. It was clear to her that she’d found her calling.

NerdXing wasn’t Schneider’s first experience building new technology. At just 16, she built an app meant to connect English-speaking volunteers from her international school in Tirana, Albania, to local charities that only posted jobs in Albanian. By last year, the platform, called VoluntYOU, had 18 ambassadors across four continents. It has enabled volunteers to give out more than 2,000 burritos in Reno, Nevada; register hundreds of signatures to support women’s rights legislation in Albania; and help with administering Covid-19 vaccines to more than 1,200 individuals a day in Italy.

Schneider says her experience at an international school encouraged her to recognize problems and solutions all around her.

“When I enter a new community and I can immediately be like, ‘Oh wait, if we had this tool, that would be so cool and that would help all these people,’ I think that’s just a derivative of having grown up in a place where you hear about everyone’s super different life experiences,” she says.

Schneider describes NerdXing as a continuation of many of the skills she picked up while building VoluntYOU.

“They were both motivated by seeing a challenge where I thought, ‘Wait, we have the tech skills to build that. This is something that I can envision the solution to.’ And then I wanted to actually go and make that a reality,” Schneider says.

Robotics with a positive impact

At MIT, Schneider started working in the Biomimetic Robotics Laboratory of Professor Sangbae Kim, where she has now participated in three research projects, one of which she’s co-authoring a paper on. She’s part of a team that tests how robots, including the famous back-flipping mini cheetah, move, in order to see how they could complement humans in high-stakes scenarios.

Most of her work has revolved around crafting controllers, including one hybrid-learning and model-based controller that is well-suited to robots with limited onboard computing capacity. It would allow the robot to be used in regions with less access to technology.

“It’s not just doing technology for technology's sake, but because it will bridge out into the world and make a positive difference. I think legged robotics have some of the best potential to actually be a robotic partner to human beings in the scenarios that are most high-stakes,” Schneider says.

Schneider hopes to further robotic capabilities so she can find applications that will service communities around the world. One of her goals is to help create tools that allow a surgeon to operate on a patient a long distance away. 

To take a break from academics, Schneider has channeled her love of the arts into MIT’s vibrant social dancing scene. This year, she’s especially excited about country line dancing events where the music comes on and students have to guess the choreography.

“I think it's a really fun way to make friends and to connect with the community,” she says.



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Building reuse into the materials around us

In a field defined by discovering, designing, and processing the materials that underpin modern technology, Diran Apelian ScD ’73 has a resounding message: Reuse can’t remain just the focus of a PhD thesis or a startup. It needs to be engineered from the beginning.

Apelian, a metallurgist and MIT alumnus known for his pioneering work in molten metal processing, framed his plea with a look at society’s growing needs for materials like copper, nickel, iron, and manganese — and how demand for them has surged alongside population growth over the past 150 years.

“We’re using more and more stuff — that’s the takeaway,” said Apelian, the speaker for the MIT Department of Materials Science and Engineering (DMSE)’s Wulff Lecture on Nov. 19. “Now, where’s all this stuff coming from? It doesn’t come from Home Depot. It comes from the Earth — planet Earth — where we take the ores out of the Earth, and we have to extract them out.”

And more and more everyday goods depend on those ores, depleting the planet’s supplies while expending massive amounts of energy to do it, Apelian said. As one example, Apelian pointed out that computer chips, which incorporated 11 elements in 1980, now contain 52.

Instead of simply taking, processing, and eventually discarding materials — often after passing them through inefficient recycling systems — Apelian proposes another approach: designing materials and products so that the value inside them can be recovered.

Examples include aerospace-grade materials made from scrap aluminum alloys, optimized using AI-driven alloy blending, and shredding lithium-ion batteries to produce “black mass,” a mixture rich in cobalt, nickel, and lithium that can be refined into new cathode materials for the next generation of batteries.

“Sustainable growth, sustainability, the development of the planet Earth is a challenge,” said Apelian — one that materials scientists and engineers are in a prime position to tackle. “It’s a profound change, but it requires material issues and challenges that are also an opportunity for us.”

Reshaping materials design

The Wulff Lecture is no stranger to sustainability and climate issues — past speakers have discussed green iron and steel production and hydrogen-powered fuel cells. But what marked Apelian’s talk was a call for an overhaul of how materials are produced, used, and — crucially — used again. The key, he said, is “materials circularity,” which keeps Earth-derived minerals moving through the economy as long as possible, instead of being extracted, processed, used, and thrown away.

Apelian referenced the “materials tetrahedron,” the classic framework connecting processing, structure, properties, and performance — the foundation underlying the development of most materials around us. Highlighting what’s missing, he asked DMSE students about materials at the end of their life cycle: “You don’t really spend too much time on it, right?”

He proposed a new framework of concentric circles that reimagines the materials life cycle — from mining, extraction, processing, and design, to new phases focused on repair, reuse, remanufacturing, and recycling — “all the R’s,” he said.

One pathway to more sustainable materials use, Apelian said, is tackling post-consumer waste — the everyday products people throw away once they’re done using them.

“How can we take the waste and recover it and reuse it?” Apelian asked.

One example is aluminum scrap processing, which has seen several advances in recent years. Traditionally, end-of-life vehicles were stripped of valuable parts and fed through giant shredders; the resulting mix of metals were melted together, forfeiting much of its engineered value, and “downcycled” into cast alloys used for products like engine blocks or patio furniture.

Today, advancements in automated sensor-based sorting, machine learning and robotics, and improved melting practices mean aluminum scrap can now be directed into higher-value applications, including aerospace components and structural automotive parts — beams and supports that form a vehicle’s frame.

“So that’s the aim, that’s the motivation: creating value out of waste,” Apelian said.

He highlighted ongoing efforts to modernize scrap processing. He is a co-founder of Solvus Global Inc., which develops systems to convert metal scrap into high-value products, and Valis Insights, a Solvus spinout that uses sensor-based systems to identify and sort metal scraps with high precision.

At the University of California at Irvine — where Apelian serves as distinguished professor of materials science and engineering — his group is “studying the DNA” of mixed scrap, analyzing and testing blends to prepare them for high-value applications. He has also done significant work in lithium-ion battery recycling, including co-inventing the process, commercialized by Ascend Elements, that shreds batteries and produces as a byproduct the black mass used as feedstock for new cathode materials.

Believing in circularity

Apelian also pointed to ways of extracting value from industrial waste: recovering metals from red mud — the highly alkaline byproduct of aluminum production — and reclaiming rare-earth elements from mine tailings. And he spotlighted the work of Shaolou Wei ScD ’22, a DMSE alum joining the faculty in 2026, who has developed ways to bypass the long, energy-intensive sequences traditionally used to make many alloys — reducing energy consumption and eliminating processing steps.

Stressing that business models and policy play a critical role in enabling a circular economy, Apelian offered a scenario: “Right now, in America, when you buy a car, it’s yours. At the end of life, it’s your problem.” Owners can trade it in or sell it, but ultimately, they need to dispose of it, he said. He then mused about reversing this responsibility — requiring manufacturers to take cars back at end of life. “I’ve got to tell you, when that happens, things are going to be designed very differently.”

Audience member Evia Rodriguez, a senior in materials science and engineering, was struck by Apelian’s emphasis on circularity. She pointed to Patagonia — one of Apelian’s examples — as a company weaving circularity into its business model by encouraging customers to repair clothing instead of replacing it.

“That definitely represents an optimistic idea of what could happen,” Rodriguez said. “I tend to be more skeptical, but I like to think that we could get there someday, and that we could have all companies operating on a more sustainable front.”

First-year undergraduate Brandon Mata shared a similar outlook — balancing doubt with hope. “I think it’s easy to be pessimistic about how companies are going to act. You’re going to say people are always going to be greedy. They’re going to be selfish,” Mata said. “But regardless, I think it’s still important to have somebody like that saying, even just stating, ‘It’s important that we do this, and doing this would clearly benefit the world.’”

Yanna Tenorio, a first-year undergraduate who’s interested in the energy side of materials science, zoomed out to the overarching questions raised in the talk. “Thinking about what happens at the end of these materials’ life, how can they be reused? How can we take accountability for them?” Tenorio asked. “What I find very exciting about material science in general is how much there is to be discovered.”



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Guided learning lets “untrainable” neural networks realize their potential

Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.

Their findings suggest that many so-called “ineffective” networks may simply start from less-than-ideal starting points, and that short-term guidance can place them in a spot that makes learning easier for the network. 

The team’s guidance method works by encouraging a target network to match the internal representations of a guide network during training. Unlike traditional methods like knowledge distillation, which focus on mimicking a teacher’s outputs, guidance transfers structural knowledge directly from one network to another. This means the target learns how the guide organizes information within each layer, rather than simply copying its behavior. Remarkably, even untrained networks contain architectural biases that can be transferred, while trained guides additionally convey learned patterns. 

“We found these results pretty surprising,” says Vighnesh Subramaniam ’23, MEng ’24, MIT Department of Electrical Engineering and Computer Science (EECS) PhD student and CSAIL researcher, who is a lead author on a paper presenting these findings. “It’s impressive that we could use representational similarity to make these traditionally ‘crappy’ networks actually work.”

Guide-ian angel 

A central question was whether guidance must continue throughout training, or if its primary effect is to provide a better initialization. To explore this, the researchers performed an experiment with deep fully connected networks (FCNs). Before training on the real problem, the network spent a few steps practicing with another network using random noise, like stretching before exercise. The results were striking: Networks that typically overfit immediately remained stable, achieved lower training loss, and avoided the classic performance degradation seen in something called standard FCNs. This alignment acted like a helpful warmup for the network, showing that even a short practice session can have lasting benefits without needing constant guidance.

The study also compared guidance to knowledge distillation, a popular approach in which a student network attempts to mimic a teacher’s outputs. When the teacher network was untrained, distillation failed completely, since the outputs contained no meaningful signal. Guidance, by contrast, still produced strong improvements because it leverages internal representations rather than final predictions. This result underscores a key insight: Untrained networks already encode valuable architectural biases that can steer other networks toward effective learning.

Beyond the experimental results, the findings have broad implications for understanding neural network architecture. The researchers suggest that success — or failure — often depends less on task-specific data, and more on the network’s position in parameter space. By aligning with a guide network, it’s possible to separate the contributions of architectural biases from those of learned knowledge. This allows scientists to identify which features of a network’s design support effective learning, and which challenges stem simply from poor initialization.

Guidance also opens new avenues for studying relationships between architectures. By measuring how easily one network can guide another, researchers can probe distances between functional designs and reexamine theories of neural network optimization. Since the method relies on representational similarity, it may reveal previously hidden structures in network design, helping to identify which components contribute most to learning and which do not.

Salvaging the hopeless

Ultimately, the work shows that so-called “untrainable” networks are not inherently doomed. With guidance, failure modes can be eliminated, overfitting avoided, and previously ineffective architectures brought into line with modern performance standards. The CSAIL team plans to explore which architectural elements are most responsible for these improvements and how these insights can influence future network design. By revealing the hidden potential of even the most stubborn networks, guidance provides a powerful new tool for understanding — and hopefully shaping — the foundations of machine learning.

“It’s generally assumed that different neural network architectures have particular strengths and weaknesses,” says Leyla Isik, Johns Hopkins University assistant professor of cognitive science, who wasn’t involved in the research. “This exciting research shows that one type of network can inherit the advantages of another architecture, without losing its original capabilities. Remarkably, the authors show this can be done using small, untrained ‘guide’ networks. This paper introduces a novel and concrete way to add different inductive biases into neural networks, which is critical for developing more efficient and human-aligned AI.”

Subramaniam wrote the paper with CSAIL colleagues: Research Scientist Brian Cheung; PhD student David Mayo ’18, MEng ’19; Research Associate Colin Conwell; principal investigators Boris Katz, a CSAIL principal research scientist, and Tomaso Poggio, an MIT professor in brain and cognitive sciences; and former CSAIL research scientist Andrei Barbu. Their work was supported, in part, by the Center for Brains, Minds, and Machines, the National Science Foundation, the MIT CSAIL Machine Learning Applications Initiative, the MIT-IBM Watson AI Lab, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. Department of the Air Force Artificial Intelligence Accelerator, and the U.S. Air Force Office of Scientific Research.

Their work was recently presented at the Conference and Workshop on Neural Information Processing Systems (NeurIPS).



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miércoles, 17 de diciembre de 2025

Teen builds an award-winning virtual reality prototype thanks to free MIT courses

When Freesia Gaul discovered MIT Open Learning’s OpenCourseWare at just 14 years old, it opened up a world of learning far beyond what her classrooms could offer. Her parents had started a skiing company, and the seasonal work meant that Gaul had to change schools every six months. Growing up in small towns in Australia and Canada, she relied on the internet to fuel her curiosity.

“I went to 13 different schools, which was hard because you're in a different educational system every single time,” says Gaul. “That’s one of the reasons I gravitated toward online learning and teaching myself. Knowledge is something that exists beyond a curriculum.”

The small towns she lived in often didn’t have a lot of resources, she says, so a computer served as a main tool for learning. She enjoyed engaging with Wikipedia, ultimately researching topics and writing and editing content for pages. In 2018, she discovered MIT OpenCourseWare, part of MIT Open Learning, and took her first course. OpenCouseWare offers free, online, open educational resources from more than 2,500 MIT undergraduate and graduate courses. 

“I really got started with the OpenCourseWare introductory electrical engineering classes, because I couldn’t find anything else quite like it online,” says Gaul, who was initially drawn to courses on circuits and electronics, such as 6.002 (Circuits and Electronics) and 6.01SC (Introduction to Electrical Engineering and Computer Science). “It really helped me in terms of understanding how electrical engineering worked in a practical sense, and I just started modding things.”

In true MIT “mens et manus” (“mind and hand”) fashion, Gaul spent much of her childhood building and inventing, especially when she was able to access a 3D printer. She says that a highlight was when she built a life-sized, working version of a Mario Kart, constructed out of materials she had printed.

Gaul calls herself a “serial learner,” and has taken many OpenCourseWare courses. In addition to classes on circuits and electronics, she also took courses in linear algebra, calculus, and quantum physics — in which she took a particular interest. 

When she was 15, she participated in Qubit by Qubit. Hosted by The Coding School, in collaboration with universities (including MIT) and tech companies, this two-semester course introduces high schoolers to quantum computing and quantum physics. 

During that time she started a blog called On Zero, representing the “zero state” of a qubit. “The ‘zero state’ in a quantum computer is the representation of creativity from nothing, infinite possibilities,” says Gaul. For the blog, she found different topics and researched them in depth. She would think of a topic or question, such as “What is color?” and then explore it in great detail. What she learned eventually led her to start asking questions such as “What is a hamiltonian?” and teaching quantum physics alongside PhDs.

Building on these interests, Gaul chose to study quantum engineering at the University of New South Wales. She notes that on her first day of university, she participated in iQuHack, the MIT Quantum Hackathon. Her team worked to find a new way to approximate the value of a hyperbolic function using quantum logic, and received an honorable mention for “exceptional creativity.”

Gaul’s passion for making things continued during her college days, especially in terms of innovating to solve a problem. When she found herself on a train, wanting to code a personal website on a computer with a dying battery, she wondered if there might be a way to make a glove that can act as a type of Bluetooth keyboard — essentially creating a way to type in the air. In her spare time, she started working on such a device, ultimately finding a less expensive way to build a lightweight, haptic, gesture-tracking glove with applications for virtual reality (VR) and robotics.

Gaul says she has always had an interest in VR, using it to create her own worlds, reconstruct an old childhood house, and play Dungeons and Dragons with friends. She discovered a way to put into a glove some small linear resonant actuators, which can be found in a smartphone or gaming controller, and map to any object in VR so that the user can feel it.

An early prototype that Gaul put together in her dorm room received a lot of attention on YouTube. She went on to win the People’s Choice award for it at the SxSW Sydney 2025 Tech and Innovation Festival. This design also sparked her co-founding of the tech startup On Zero, named after her childhood blog dedicated to the love of creation from nothing.

Gaul sees the device, in general, as a way of “paying it forward,” making improved human-computer interaction available to many — from young students to professional technologists. She hopes to enable creative freedom in as many as she can. “The mind is just such a fun thing. I want to empower others to have the freedom to follow their curiosity, even if it's pointless on paper.

“I’ve benefited from people going far beyond what they needed to do to help me,” says Gaul. “I see OpenCourseWare as a part of that. The free courses gave me a solid foundation of knowledge and problem-solving abilities. Without these, it wouldn’t be possible to do what I’m doing now.”



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MIT-Hood Pediatric Innovation Hub convenes leaders to advance pediatric health

Facing hospital closures, underfunded pediatric trials, and a persistent reliance on adult-oriented tools for children, the Hood Pediatric Innovation Hub welcomed nearly 200 leaders at Boston’s Museum of Science for MIT-Hood Pediatric Innovation 2025, an event focused on transforming the future of pediatric care through engineering and collaboration.

Hosted by the Hood Pediatric Innovation Hub — established at MIT through a gift by the Hood Foundation — the event brought together attendees from academia, health care, and industry to rethink how medical and technological breakthroughs can reach children faster. The gathering marked a new phase in the hub’s mission to connect scientific discovery with real-world impact.

“We have extraordinary science emerging every day, but the translation gap is widening,” said Joseph Frassica, professor of the practice in MIT’s Institute for Medical Engineering and Science and executive director of the Hood Pediatric Innovation Hub. “We can’t rely on the old model of innovation — we need new connective tissue between ideas, institutions, and implementation.”

Building collaboration across sectors

Speakers emphasized that pediatric medicine has long faced structural disadvantages compared with other fields — from smaller patient populations to limited commercial incentives. Yet they also described a powerful opportunity: to make pediatric innovation a proving ground for smarter, more human-centered health systems.

“The Hood Foundation has always believed that if you can improve care for children, you improve care for everyone,” said Neil Smiley, president of the Charles H. Hood Foundation. “Pediatrics pushes medicine to be smarter, more precise, and more humane — and that’s why this collaboration with MIT feels so right.”

Participants discussed how aligning efforts across universities, hospitals, and industry partners could help overcome the fragmentation that slows innovation, and ultimately translation. Speakers at the event highlighted case studies where cross-sector collaboration is already yielding results — from novel medical devices to data-driven clinical insights.

Connecting discovery to delivery

In his remarks, Elazer R. Edelman, the Edward J. Poitras Professor in Medical Engineering and Science at MIT and faculty lead for the Hood Pediatric Innovation Hub, reflected on how MIT’s engineering and medical communities can help close the loop between research and clinical application.

“This isn’t about creating something new for the sake of it — it’s about finally connecting the extraordinary expertise that already exists, from the lab to the clinic to the child’s bedside,” Edelman said. “That’s what MIT does best — we connect the dots.”

Throughout the day, attendees shared experiences from both the engineering and clinical viewpoints — acknowledging the complexities of regulation, funding, and adoption, while highlighting the shared responsibility to move faster on behalf of children.

A moment of convergence

The conversation also turned to the economics of innovation and the broader societal benefits of investing in pediatric health.

“The economic and social stakes couldn’t be higher,” said Jonathan Gruber, Ford Professor of Economics at MIT. “When we invest in children’s health, we invest in longer lives, stronger communities, and greater prosperity. The energy in this room shows what’s possible when we stop working in silos.”

By the end of the event, discussions had shifted from identifying barriers to designing solutions. Participants explored ideas ranging from translational fellowships and shared data platforms to new models for academic–industry partnership — each aimed at accelerating impact where it is needed most.

Looking ahead

“There’s a feeling that this is the moment,” Frassica said. “We have the tools, the data, and the will to transform how we care for children. The key now is keeping that spirit of collaboration alive — because when we do, we move the whole field forward.”

Building on the momentum from MIT-Hood Pediatric Innovation 2025, the Hood Pediatric Innovation Hub will continue to serve as a connector across disciplines and institutions, advancing projects that translate cutting-edge research into improved outcomes for children everywhere. In January, a new cohort of MIT Catalyst Fellows — early-career researchers embedded with frontline clinicians to identify unmet needs — will begin exploring solutions to challenges in pediatric and neonatal health care in partnership with the hub. 

This work is also part of a wider Institute effort. The Hood Pediatric Innovation Hub contributes to the broader mission of the MIT Health and Life Sciences Collaborative (HEALS), which brings together faculty, clinicians, and industry partners to accelerate breakthroughs across all areas of human health. As the hub deepens its own collaborations, its connection to HEALS helps ensure that advances in pediatric medicine are integrated into MIT’s larger push to improve health outcomes at scale.

The hub will also release a request for proposals in the coming months for the development of its first mentored projects — designed to bring together teams from engineering, medicine, and industry to accelerate progress in children’s health. Updates and details will be available at hoodhub.mit.edu.

As Smiley noted, progress in pediatric health often drives progress across all of medicine — and this gathering underscored that shared belief: when we work together for children, we build a healthier future for everyone.



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New study suggests a way to rejuvenate the immune system

As people age, their immune system function declines. T cell populations become smaller and can’t react to pathogens as quickly, making people more susceptible to a variety of infections.

To try to overcome that decline, researchers at MIT and the Broad Institute have found a way to temporarily program cells in the liver to improve T-cell function. This reprogramming can compensate for the age-related decline of the thymus, where T cell maturation normally occurs.

Using mRNA to deliver three key factors that usually promote T-cell survival, the researchers were able to rejuvenate the immune systems of mice. Aged mice that received the treatment showed much larger and more diverse T cell populations in response to vaccination, and they also responded better to cancer immunotherapy treatments.

If developed for use in patients, this type of treatment could help people lead healthier lives as they age, the researchers say.

“If we can restore something essential like the immune system, hopefully we can help people stay free of disease for a longer span of their life,” says Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT, who has joint appointments in the departments of Brain and Cognitive Sciences and Biological Engineering.

Zhang, who is also an investigator at the McGovern Institute for Brain Research at MIT, a core institute member at the Broad Institute of MIT and Harvard, an investigator in the Howard Hughes Medical Institute, and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT, is the senior author of the new study. Former MIT postdoc Mirco Friedrich is the lead author of the paper, which appears today in Nature.

A temporary factory

The thymus, a small organ located in front of the heart, plays a critical role in T-cell development. Within the thymus, immature T cells go through a checkpoint process that ensures a diverse repertoire of T cells. The thymus also secretes cytokines and growth factors that help T cells to survive.

However, starting in early adulthood, the thymus begins to shrink. This process, known as thymic involution, leads to a decline in the production of new T cells. By the age of approximately 75, the thymus is greatly reduced.

“As we get older, the immune system begins to decline. We wanted to think about how can we maintain this kind of immune protection for a longer period of time, and that's what led us to think about what we can do to boost immunity,” Friedrich says.

Previous work on rejuvenating the immune system has focused on delivering T cell growth factors into the bloodstream, but that can have harmful side effects. Researchers are also exploring the possibility of using transplanted stem cells to help regrow functional tissue in the thymus.

The MIT team took a different approach: They wanted to see if they could create a temporary “factory” in the body that would generate the T-cell-stimulating signals that are normally produced by the thymus.

“Our approach is more of a synthetic approach,” Zhang says. “We're engineering the body to mimic thymic factor secretion.”

For their factory location, they settled on the liver, for several reasons. First, the liver has a high capacity for producing proteins, even in old age. Also, it’s easier to deliver mRNA to the liver than to most other organs of the body. The liver was also an appealing target because all of the body’s circulating blood has to flow through it, including T cells.

To create their factory, the researchers identified three immune cues that are important for T-cell maturation. They encoded these three factors into mRNA sequences that could be delivered by lipid nanoparticles. When injected into the bloodstream, these particles accumulate in the liver and the mRNA is taken up by hepatocytes, which begin to manufacture the proteins encoded by the mRNA.

The factors that the researchers delivered are DLL1, FLT-3, and IL-7, which help immature progenitor T cells mature into fully differentiated T cells.

Immune rejuvenation

Tests in mice revealed a variety of beneficial effects. First, the researchers injected the mRNA particles into 18-month-old mice, equivalent to humans in their 50s. Because mRNA is short-lived, the researchers gave the mice multiple injections over four weeks to maintain a steady production by the liver.

After this treatment, T cell populations showed significant increases in size and function.

The researchers then tested whether the treatment could enhance the animals’ response to vaccination. They vaccinated the mice with ovalbumin, a protein found in egg whites that is commonly used to study how the immune system responds to a specific antigen. In 18-month-old mice that received the mRNA treatment before vaccination, the researchers found that the population of cytotoxic T-cells specific to ovalbumin doubled, compared to mice of the same age that did not receive the mRNA treatment.

The mRNA treatment can also boost the immune system’s response to cancer immunotherapy, the researchers found. They delivered the mRNA treatment to 18-month-old mice, who were then implanted with tumors and treated with a checkpoint inhibitor drug. This drug, which targets the protein PD-L1, is designed to help take the brakes off the immune system and stimulate T cells to attack tumor cells.

Mice that received the treatment showed much higher survival rates and longer lifespan that those that received the checkpoint inhibitor drug but not the mRNA treatment.

The researchers found that all three factors were necessary to induce this immune enhancement; none could achieve all aspects of it on their own. They now plan to study the treatment in other animal models and to identify additional signaling factors that may further enhance immune system function. They also hope to study how the treatment affects other immune cells, including B cells.

Other authors of the paper include Julie Pham, Jiakun Tian, Hongyu Chen, Jiahao Huang, Niklas Kehl, Sophia Liu, Blake Lash, Fei Chen, Xiao Wang, and Rhiannon Macrae.

The research was funded, in part, by the Howard Hughes Medical Institute, the K. Lisa Yang Brain-Body Center, part of the Yang Tan Collective at MIT, Broad Institute Programmable Therapeutics Gift Donors, the Pershing Square Foundation, J. and P. Poitras, and an EMBO Postdoctoral Fellowship.



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martes, 16 de diciembre de 2025

Nuno Loureiro, professor and director of MIT’s Plasma Science and Fusion Center, dies at 47

This article may be updated.

Nuno Loureiro, a professor of nuclear science and engineering and of physics at MIT, has died. He was 47.

A lauded theoretical physicist and fusion scientist, and director of the MIT Plasma Science and Fusion Center, Loureiro joined MIT’s faculty in 2016. His research addressed complex problems lurking at the center of fusion vacuum chambers and at the edges of the universe.

Loureiro’s research at MIT advanced scientists’ understanding of plasma behavior, including turbulence, and uncovered the physics behind astronomical phenomena like solar flares. He was the Herman Feshbach (1942) Professor of Physics at MIT and was named director of the Plasma Science and Fusion Center in 2024, though his contributions to fusion science and engineering began far before that.

His research on magnetized plasma dynamics, magnetic field amplification, and confinement and transport in fusion plasmas helped inform the design of fusion devices that could harness the energy of fusing plasmas, bringing the dream of clean, near-limitless fusion power closer to reality.

“Nuno was not only a brilliant scientist, he was a brilliant person,” says Dennis Whyte, the Hitachi America Professor of Engineering, who previously served as the head of the Department of Nuclear Science and Engineering and director of the Plasma Science and Fusion Center. “He shone a bright light as a mentor, friend, teacher, colleague and leader, and was universally admired for his articulate, compassionate manner. His loss is immeasurable to our community at the PSFC, NSE and MIT, and around the entire fusion and plasma research world.”

“Nuno was a champion for plasma physics within the Physics Department, a wonderful and engaging colleague, and an inspiring and caring mentor for graduate students working in plasma science.  His recent work on quantum computing algorithms for plasma physics simulations was a particularly exciting new scientific direction,” says Deepto Chakrabarty, the William A. M. Burden Professor in Astrophysics and head of the Department of Physics.

Whether working on fusion or astrophysics research, Loureiro merged fundamental physics with technology and engineering, to maximize impact.

“There are people who are driven by technology and engineering, and others who are driven by fundamental mathematics and physics. We need both,” Loureiro said in 2019. “When we stimulate theoretically inclined minds by framing plasma physics and fusion challenges as beautiful theoretical physics problems, we bring into the game incredibly brilliant students — people who we want to attract to fusion development.”

Loureiro majored in physics at Instituto Superior Tecnico (IST) in Portugal and obtained a PhD in physics at Imperial College London in 2005. He conducted postdoctoral work at the Princeton Plasma Physics Laboratory for the next two years before moving to the UKAEA Culham Center for Fusion Energy in 2007. Loureiro returned to IST in 2009, where he was a researcher at the Institute for Plasmas and Nuclear Fusion until coming to MIT in 2016.

He wasted no time contributing to the intellectual environment at MIT, spending part of his first two years at the Institute working on the vexing problem of plasma turbulence. Plasma is the super-hot state of matter that serves as the fuel for fusion reactors. Loureiro’s lab at PSFC illuminated how plasma behaves inside fusion reactors, which could help prevent material failures and better contain the plasma to harvest electricity.

“Nuno was not only an extraordinary scientist and educator, but also a tremendous colleague, mentor, and friend who cared deeply about his students and his community. His absence will be felt profoundly across NSE and far beyond,” Benoit Forget, the KEPCO Professor and head of the Department of Nuclear Science and Engineering, wrote in an email to the department today.

On other fronts, Loureiro’s work in astrophysics helped reveal fundamental mechanisms of the universe. He put forward the first theory of turbulence in pair plasmas, which differ from regular plasmas and may be abundant in space. The work was driven, in part, by unprecedented observations of a binary neutron star merger in 2018.

As an assistant professor and then a full professor at MIT, Loureiro taught course 22.612 (Intro to Plasma Physics) and course 22.615 (MHD Theory of Fusion Systems), for which he was twice recognized with the Department of Nuclear Science and Engineering’s PAI Outstanding Professor Award.

Loureiro’s research earned him many prominent awards throughout his prolific career, including the National Science Foundation Career Award and the American Physical Society Thomas H. Stix Award for Outstanding Early Career Contributions to Plasma Physics Research. He was also an APS fellow. Earlier this year, he earned the Presidential Early Career Award for Scientists and Engineers.



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How cement “breathes in” and stores millions of tons of CO₂ a year

The world’s most common construction material has a secret. Cement, the “glue” that holds concrete together, gradually “breathes in” and stores millions of tons of carbon dioxide (CO2) from the air over the lifetimes of buildings and infrastructure.  

A new study from the MIT Concrete Sustainability Hub quantifies this process, carbon uptake, at a national scale for the first time. Using a novel approach, the research team found that the cement in U.S. buildings and infrastructure sequesters over 6.5 million metric tons of CO2 annually. This corresponds to roughly 13 percent of the process emissions — the CO2 released by the underlying chemical reaction — in U.S. cement manufacturing. In Mexico, the same building stock sequesters about 5 million tons a year.   

But how did the team come up with those numbers? 

Scientists have known how carbon uptake works for decades. CO2 enters concrete or mortar — the mixture that glues together blocks, brick, and stones — through tiny pores, reacts with the calcium-rich products in cement, and becomes locked into a stable mineral called calcium carbonate, or limestone. 

The chemistry is well-known, but calculating the magnitude of this at scale is not. A concrete highway in Dallas sequesters CO2 differently than Mexico City apartments made from concrete masonry units (CMUs), also called concrete blocks or, colloquially, cinder blocks. And a foundation slab buried under the snow in Fairbanks, Alaska, “breathes in” CO2 at a different pace entirely. 

As Hessam AzariJafari, lead author and research scientist in the MIT Department of Civil and Environmental Engineering, explains, “Carbon uptake is very sensitive to context. Four major factors drive it: the type of cement used, the product we make with it — concrete, CMUs, or mortar — the geometry of the structure, and the climate and conditions it’s exposed to. Even within the same structure, uptake can vary five-fold between different elements.” 

As no two structures sequester CO2 in the same way, estimating uptake nationwide would normally require simulating an array of cement-based elements: slabs, walls, beams, columns, pavements, and more. On top of that, each of those has its own age, geometry, mixture, and exposure condition to account for.  

Seeing that this approach would be like trying to count every grain of sand on a beach, the team took a different route. They developed hundreds of archetypes, typical designs that could stand in for different buildings and pieces of infrastructure. It’s a bit like measuring the beach instead by mapping out its shape, depth, and shoreline to estimate how much sand usually sits in a given spot.  

With these archetypes in hand, the team modeled how each one sequesters CO2 in different environments and how common each is across every state in the United States and Mexico. In this way, they could estimate not just how much CO2 structures sequester, but why those numbers differ.  

Two factors stood out. The first was the “construction trend,” or how the amount of new construction had changed over the previous five years. Because it reflects how quickly cement products are being added to the building stock, it shapes how much cement each state consumes and, therefore, how much of that cement is actively carbonating. The second was the ratio of mortar to concrete, since porous mortars sequester CO2 an order of magnitude faster than denser concrete. 

In states where mortar use was higher, the fraction of CO2 uptake relative to process emissions was noticeably greater. “We observed something unique about Mexico: Despite using half the cement that the U.S. does, the country has three-quarters of the uptake,” notes AzariJafari. “This is because Mexico makes more use of mortars and lower-strength concrete, and bagged cement mixed on-site. These practices are why their uptake sequesters about a quarter of their cement manufacturing emissions.” 

While care must be taken for structural elements that use steel reinforcement, as uptake can accelerate corrosion, it’s possible to enhance the uptake of many elements without negative impacts. 

Randolph Kirchain, director of the MIT Concrete Sustainability Hub, principal research scientist in the MIT Materials Research Laboratory, and the senior author of this study, explains: “For instance, increasing the amount of surface area exposed to air accelerates uptake and can be achieved by foregoing painting or tiling, or choosing designs like waffle slabs with a higher surface area-to-volume ratio. Additionally, avoiding unnecessarily stronger, less-porous concrete mixtures than required would speed up uptake while using less cement.” 

“There is a real opportunity to refine how carbon uptake from cement is represented in national inventories,” AzariJafari comments. “The buildings around us and the concrete beneath our feet are constantly ‘breathing in’ millions of tons of CO2. Nevertheless, some of the simplified values in widely used reporting frameworks can lead to higher estimates than what we observe empirically. Integrating updated science into international inventories and guidelines such as the Intergovernmental Panel on Climate Change (IPCC) would help ensure that reported numbers reflect the material and temporal realities of the sector.” 

By offering the first rigorous, bottom-up estimation of carbon uptake at a national scale, the team’s work provides a more representative picture of cement’s environmental impact. As we work to decarbonize the built environment, understanding what our structures are already doing in the background may be just as important as the innovations we pursue moving forward. The approach developed by MIT researchers could be extended to other countries by combining global building-stock databases with national cement-production statistics. It could also inform the design of structures that safely maximize uptake. 

The findings were published Dec. 15 in the  Proceedings of the National Academy of Sciences. Joining AzariJafari and Kirchain on the paper are MIT researchers Elizabeth Moore of the Department of Materials Science and Engineering and the MIT Climate Project and former postdocs Ipek Bensu Manav SM ’21, PhD ’24 and Motahareh Rahimi, along with Bruno Huet and Christophe Levy from the Holcim Innovation Center in France.



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A new immunotherapy approach could work for many types of cancer

Researchers at MIT and Stanford University have developed a new way to stimulate the immune system to attack tumor cells, using a strategy that could make cancer immunotherapy work for many more patients.

The key to their approach is reversing a “brake” that cancer cells engage to prevent immune cells from launching an attack. This brake is controlled by sugar molecules known as glycans that are found on the surface of cancer cells.

By blocking those glycans with molecules called lectins, the researchers showed they could dramatically boost the immune system’s response to cancer cells. To achieve this, they created multifunctional molecules known as AbLecs, which combine a lectin with a tumor-targeting antibody.

Animation shows, over 5 hours, red dots indicating killed cancer cells.

“We created a new kind of protein therapeutic that can block glycan-based immune checkpoints and boost anti-cancer immune responses,” says Jessica Stark, the Underwood-Prescott Career Development Professor in the MIT departments of Biological Engineering and Chemical Engineering. “Because glycans are known to restrain the immune response to cancer in multiple tumor types, we suspect our molecules could offer new and potentially more effective treatment options for many cancer patients.”

Stark, who is also a member of MIT’s Koch Institute for Integrative Cancer Research, is the lead author of the paper. Carolyn Bertozzi, a professor of chemistry at Stanford and director of the Sarafan ChEM Institute, is the senior author of the study, which appears today in Nature Biotechnology.

Releasing the brakes

Training the immune system to recognize and destroy tumor cells is a promising approach to treating many types of cancer. One class of immunotherapy drugs known as checkpoint inhibitors stimulate immune cells by blocking an interaction between the proteins PD-1 and PD-L1. This removes a brake that tumor cells use to prevent immune cells like T cells from killing cancer cells.

Drugs targeting the PD-1- PD-L1 checkpoint have been approved to treat several kinds of cancer. In some of these patients, checkpoint inhibitors can lead to long-lasting remission, but for many others, they don’t work at all.

In hopes of generating immune responses in a greater number of patients, researchers are now working on ways to target other immunosuppressive interactions between cancer cells and immune cells. One such interaction occurs between glycans on tumor cells and receptors found on immune cells.

Glycans are found on nearly all living cells, but tumor cells often express glycans that are not found on healthy cells, including glycans that contain a monosaccharide called sialic acid. When sialic acids bind to lectin receptors, located on immune cells, it turns on an immunosuppressive pathway in the immune cells. These lectins that bind to sialic acid are known as Siglecs.

“When Siglecs on immune cells bind to sialic acids on cancer cells, it puts the brakes on the immune response. It prevents that immune cell from becoming activated to attack and destroy the cancer cell, just like what happens when PD-1 binds to PD-L1,” Stark says.

Currently, there aren’t any approved therapies that target this Siglec-sialic acid interaction, despite a number of drug development approaches that have been tried. For example, researchers have tried to develop lectins that could bind to sialic acids and prevent them from interacting with immune cells, but so far, this approach hasn’t worked well because lectins don’t bind strongly enough to accumulate on the cancer cell surface in large numbers.

To overcome that, Stark and her colleagues developed a way to deliver larger quantities of lectins by attaching them to antibodies that target cancer cells. Once there, the lectins can bind to sialic acid, preventing sialic acid from interacting with Siglec receptors on immune cells. This lifts the brakes off the immune response, allowing immune cells such as macrophages and natural killer (NK) cells to launch an attack on the tumor.

“This lectin binding domain typically has relatively low affinity, so you can’t use it by itself as a therapeutic. But, when the lectin domain is linked to a high-affinity antibody, you can get it to the cancer cell surface where it can bind and block sialic acids,” Stark says.

A modular system

In this study, the researchers designed an AbLec based on the antibody trastuzumab, which binds to HER2 and is approved as a cancer therapy to treat breast, stomach, and colorectal cancers. To form the AbLec, they replaced one arm of the antibody with a lectin, either Siglec-7 or Siglec-9.

Tests using cells grown in the lab showed that this AbLec rewired immune cells to attack and destroy cancer cells.

The researchers then tested their AbLecs in a mouse model that was engineered to express human Siglec receptors and antibody receptors. These mice were then injected with cancer cells that formed metastases in the lungs. When treated with the AbLec, these mice showed fewer lung metastases than mice treated with trastuzumab alone.

The researchers also showed that they could swap in other tumor-specific antibodies, such as rituximab, which targets CD20, or cetuximab, which targets EGFR. They could also swap in lectins that target other glycans involved in immunosuppression, or antibodies that target checkpoint proteins such as PD-1.

“AbLecs are really plug-and-play. They’re modular,” Stark says. “You can imagine swapping out different decoy receptor domains to target different members of the lectin receptor family, and you can also swap out the antibody arm. This is important because different cancer types express different antigens, which you can address by changing the antibody target.”

Stark, Bertozzi, and others have started a company called Valora Therapeutics, which is now working on developing lead AbLec candidates. They hope to begin clinical trials in the next two to three years.

The research was funded, in part, by a Burroughs Wellcome Fund Career Award at the Scientific Interface, a Society for Immunotherapy of Cancer Steven A. Rosenberg Scholar Award, a V Foundation V Scholar Grant, the National Cancer Institute, the National Institute of General Medical Sciences, a Merck Discovery Biologics SEEDS grant, an American Cancer Society Postdoctoral Fellowship, and a Sarafan ChEM-H Postdocs at the Interface seed grant.



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lunes, 15 de diciembre de 2025

“Robot, make me a chair”

Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.

In an effort to make design faster and more accessible for non-experts, researchers from MIT and elsewhere developed an AI-driven robotic assembly system that allows people to build physical objects by simply describing them in words.

Their system uses a generative AI model to build a 3D representation of an object’s geometry based on the user’s prompt. Then, a second generative AI model reasons about the desired object and figures out where different components should go, according to the object’s function and geometry.

The system can automatically build the object from a set of prefabricated parts using robotic assembly. It can also iterate on the design based on feedback from the user.

The researchers used this end-to-end system to fabricate furniture, including chairs and shelves, from two types of premade components. The components can be disassembled and reassembled at will, reducing the amount of waste generated through the fabrication process.

They evaluated these designs through a user study and found that more than 90 percent of participants preferred the objects made by their AI-driven system, as compared to different approaches.

While this work is an initial demonstration, the framework could be especially useful for rapid prototyping complex objects like aerospace components and architectural objects. In the longer term, it could be used in homes to fabricate furniture or other objects locally, without the need to have bulky products shipped from a central facility.

“Sooner or later, we want to be able to communicate and talk to a robot and AI system the same way we talk to each other to make things together. Our system is a first step toward enabling that future,” says lead author Alex Kyaw, a graduate student in the MIT departments of Electrical Engineering and Computer Science (EECS) and Architecture.

Kyaw is joined on the paper by Richa Gupta, an MIT architecture graduate student; Faez Ahmed, associate professor of mechanical engineering; Lawrence Sass, professor and chair of the Computation Group in the Department of Architecture; senior author Randall Davis, an EECS professor and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); as well as others at Google Deepmind and Autodesk Research. The paper was recently presented at the Conference on Neural Information Processing Systems.

Generating a multicomponent design

While generative AI models are good at generating 3D representations, known as meshes,  from text prompts, most do not produce uniform representations of an object’s geometry that have the component-level details needed for robotic assembly.

Separating these meshes into components is challenging for a model because assigning components depends on the geometry and functionality of the object and its parts.

The researchers tackled these challenges using a vision-language model (VLM), a powerful generative AI model that has been pre-trained to understand images and text. They task the VLM with figuring out how two types of prefabricated parts, structural components and panel components, should fit together to form an object.

“There are many ways we can put panels on a physical object, but the robot needs to see the geometry and reason over that geometry to make a decision about it. By serving as both the eyes and brain of the robot, the VLM enables the robot to do this,” Kyaw says.

A user prompts the system with text, perhaps by typing “make me a chair,” and gives it an AI-generated image of a chair to start.

Then, the VLM reasons about the chair and determines where panel components go on top of structural components, based on the functionality of many example objects it has seen before. For instance, the model can determine that the seat and backrest should have panels to have surfaces for someone sitting and leaning on the chair.

It outputs this information as text, such as “seat” or “backrest.” Each surface of the chair is then labeled with numbers, and the information is fed back to the VLM.

Then the VLM chooses the labels that correspond to the geometric parts of the chair that should receive panels on the 3D mesh to complete the design.

Human-AI co-design

The user remains in the loop throughout this process and can refine the design by giving the model a new prompt, such as “only use panels on the backrest, not the seat.”

“The design space is very big, so we narrow it down through user feedback. We believe this is the best way to do it because people have different preferences, and building an idealized model for everyone would be impossible,” Kyaw says.

“The human‑in‑the‑loop process allows the users to steer the AI‑generated designs and have a sense of ownership in the final result,” adds Gupta.

Once the 3D mesh is finalized, a robotic assembly system builds the object using prefabricated parts. These reusable parts can be disassembled and reassembled into different configurations.

The researchers compared the results of their method with an algorithm that places panels on all horizontal surfaces that are facing up, and an algorithm that places panels randomly. In a user study, more than 90 percent of individuals preferred the designs made by their system.

They also asked the VLM to explain why it chose to put panels in those areas.

“We learned that the vision language model is able to understand some degree of the functional aspects of a chair, like leaning and sitting, to understand why it is placing panels on the seat and backrest. It isn’t just randomly spitting out these assignments,” Kyaw says.

In the future, the researchers want to enhance their system to handle more complex and nuanced user prompts, such as a table made out of glass and metal. In addition, they want to incorporate additional prefabricated components, such as gears, hinges, or other moving parts, so objects could have more functionality.

“Our hope is to drastically lower the barrier of access to design tools. We have shown that we can use generative AI and robotics to turn ideas into physical objects in a fast, accessible, and sustainable manner,” says Davis.



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