Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity. 

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.

“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.

Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.

Overcoming the limits

In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.

But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.

To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.

So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.

“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.

The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.

Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”

“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.

They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.

To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.

“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.

Leveraging magnetism

This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.

They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.

The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.

The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.

A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.

“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.

Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.

This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.

Accurate, up-to-date climate projections are essential for planning decisions that enhance the resilience of power grids, protect public health, maximize agricultural yields, and more.

Now, MIT researchers have developed a technique that streamlines the production of fast, trustworthy, and adaptable artificial intelligence models for climate prediction.

These specialized AI models, known as climate emulators, can rapidly simulate the effects of human activities onto a future climate, predicting impacts on temperatures or sea level, for example. 

Because emulators run in a matter of seconds, scientists use them to efficiently test thousands of varied climate scenarios. This provides more reliable estimates and can identify unexpected outcomes of regional interventions.

The MIT researchers developed a training technique that boosts the performance and adaptability of a climate emulator while using only a fraction of the data typically required. This significantly cuts production time for these practical scientific tools.

They show that an emulator trained with a much smaller amount of carefully selected synthetic data accurately predicts outcomes of scenarios it did not see during training, while traditional emulators failed to adapt to new situations.

“Climate emulators are especially well-suited for modeling policy-relevant scenarios. By using our method to generate optimized training data for an emulator, we can speed up the production of much more reliable emulators, so we can better trust their outputs for making policy decisions,” says Christoher Womack PhD ’26, who is now a postdoc at ETH Zurich and lead author of a paper on this technique.

He is joined on the paper by Shahine Bouabid, a postdoc in the MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS); Andrei Sokolov, a research scientist in MIT’s Center for Sustainability Science and Strategy (CS3); Popat Salunke, a postdoc in CS3; Glenn Flierl, a professor of oceanography in EAPS; Sebastian D. Eastham, an associate professor at Imperial College London; and senior author Noelle E. Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and EAPS, and director of CS3. The research appears this week in the Proceedings of the National Academy of Sciences. 

Speedier surrogates

Climate scientists typically use earth system models (ESMs) to make long-term projections about how global temperature or precipitation could change in response to varying greenhouse gas emissions.

These enormous, physics-based models capture the major components and interactions of the earth’s climate in extreme detail. While powerful, ESMs can take months to run on a cluster of supercomputers — and that’s only to project one possible future climate scenario. 

Selin and her collaborators design climate emulators, which are fast AI surrogate models that mimic the behavior of full-scale ESMs. Emulators help scientists test many scenarios, make more accurate forecasts, and explore specific pollutants and regional effects.

“Climate emulators can run in just a few seconds, so it really expands what we can do in terms of exploring these future climate scenarios,” Womack says.

When scientists design a climate emulator, they often train the AI model using a set of six to eight future scenarios based on realistic future trajectories of emissions. They must run each scenario through a full-scale ESM, making these datasets costly and time-consuming to generate. 

The MIT researchers recently found that using realistic future scenarios as training data can lead to underperforming emulators that fail to predict unfamiliar or novel scenarios. 

In this work, they developed an algorithm that generates a synthetic dataset of optimized climate scenarios tailored to boost one emulator’s predictive performance.

“Our algorithm might generate some weird scenarios which look nothing like a realistic future, but we don’t care so much if the training scenarios are realistic. We are just trying to make the best possible dataset to train an emulator,” Womack says.

Importantly, rather than needing to run a full ESM six or eight times to generate training data, a user would only need to run that model once.

Tuning the training data 

The researchers begin by generating an arbitrary climate scenario using a fast and simple climate model. They test how well their emulator can reproduce the results of that ESM, which gives them a measure of error.

Because of the programming technique they used to build the training pipeline, they can iteratively update the training data to increase the emulator’s predictive skill. For instance, the algorithm could increase CO2 emissions dramatically in the year 2050 or rapidly decrease methane emissions in 2037.

Then the optimization updates the training data until the emulator’s error level reaches a certain threshold.

In the end, rather than resembling realistic scenarios in which emissions follow smooth trajectories, the synthetic data contain rapid variations.

“By introducing these high-frequency wiggles and oscillations, our data enable the emulator to extract a lot more information about the overall system,” Womack explains.

Their training algorithm outputs these emissions scenarios, which they can use to train an emulator that is more accurate and adaptable.

“In the future, we are definitely going to see climates and scenarios we haven’t seen before. If we can simulate these different scenarios more robustly, we can provide more reliable information to the stakeholders who need it,” Selin says.

For instance, an emulator trained with their technique can capture the effects of local pollutant control policies that reduce one pollutant while other emissions continue rising. The traditional emulators they evaluated failed this test.  

In the long run, Womack hopes this work improves the usefulness of fast and adaptable climate emulators for policy formulation. 

“This is such an important piece of the pipeline when it comes to creating useful tools that speak to stakeholder needs. Because the process of training an emulator can takes months or even years, the emulators we have are usually out-of-date. By cutting down that production time, I think this technique will be a game-changer in terms of getting updated tools into the hands of researchers and practitioners,” Selin adds.

In the future, the researchers want to test their technique using an emissions scenario generated by a full ESM. They also want to apply it to other types of climate models and explore its effectiveness in broader machine learning and computer vision applications.

This research was part of the Bringing Computation to the Climate Challenge (BC3) project and supported by Schmidt Sciences through the MIT Grand Challenges.

When we need medical care, we expect decisions about our treatment to be made by our doctors, not a tech company's algorithm. But in January, the federal government launched a program that uses AI to to evaluate Medicare beneficiaries' requests for certain procedures.

EFF sued for records on WISeR, seeking badly needed transparency about Medicare's AI experiment. In our latest EFFector newsletter, we're talking about what happens when the government outsources treatment approval to private AI companies—without sufficient transparency, testing, or legal limits.

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For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This issue covers unconstitutional digital dragnets, a post office surveillance scheme, and what EFF uncovered about Medicare's AI experiment.

Prefer to listen in? EFFector is now available on all major podcast platforms. This time we're talking to EFF's Lena Cohen about WISeR records documenting improper denials, operational chaos, and lengthy delays that have left patients waiting in pain. You can find the episode and subscribe on your podcast platform of choice:

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Order has long been the rule in the design of synthetic “metamaterials,” which have internal structures that give the whole material exceptional properties not found in nature.

When scientists engineer a metamaterial, they design from a single building block, or “unit cell,” that is then copied and pasted many times over. The result is a precise, periodic microstructure that results in improved material performance. 

Now, a team from MIT and Northeastern University has found that engineering a little disorder into a material can further enhance its “meta” features. 

In an open-access study appearing today in the journal Nature, the researchers introduce a new way to design metamaterials, inspired by the types of networks that appear in a leaf’s vasculature, the veins in a dragonfly’s wings, and the virtual connections in a social network. These new metamaterials — termed “scale-rich metamaterials” — exhibit structures of varying sizes, which sprawl and connect to form a physical network.

For decades, networks have been used as theoretical constructs to describe everything from cities to the internet to connections between neurons. The team has now applied such network designs to physical materials. They designed metamaterials made not from repeating unit cells, but from tiny support beams of varying sizes, similar to a network’s dense, web-like patterns. 

When subjected to physical tests, the new materials attained a widely controllable range of stiffness and held up against sudden impacts better than conventional, ordered metamaterials. They also were able to cushion and protect fragile objects embedded within the materials.

The team designed their materials using an algorithm which generates an optimal network of microstructures for a desired material property. The procedure can be used to design resilient, impact-absorbing materials such as helmets and armor, as well as acoustic lenses — materials whose microstructure efficiently focuses sound or vibrations.

“This is a completely new way of thinking for metamaterials,” says study author Carlos Portela, associate professor of mechanical engineering at MIT. “Unlocking this network design for materials really frees us to think of new microstructures and mechanical benefits that haven’t been possible before.” 

The study’s MIT co-authors include Andrew Yen-Jong Chen, Mohammad Charara, and Jayna Wadhwa, along with Csaba Both, Ting-Ting Gao, and Albert-László Barabási of Northeastern University, and Niek Mooij of Utrecht University in the Netherlands.

Looking beyond order

Network science is a field of research that studies complex networks, the nodes and connections within a network, and how these elements relate to each other and to the network as a whole. Network science has been used to map and characterize a wide range of systems, from networks in nature, such as food webs, evolutionary trees, and neural connections, to financial markets, cellular and social networks, and the internet. 

Albert-László Barabási, a co-author of the new study, has been at the forefront of network science. A professor of physics at Northeastern University, Barabási explores the structure of complex networks across many disciplines, studying where a network may exhibit vulnerabilities and how it could be made more robust.

Most of Barabási’s work has involved conceptual networks, or networks that are mapped onto existing systems. Recently, he wondered: Could network science be applied to build a physical material with certain desired properties that are not possible in nature? 

For this, Barabási joined efforts with Portela, whose group at MIT specializes in metamaterials. The researchers engineer materials from the ground up, with precisely patterned microstructures that enhance the material’s performance overall. Like others in the field, Portela has built metamaterials from a single unit cell, repeating this building block in patterns such as square lattice structures and honeycomb architectures.

In many cases, Portela has found that such ordered patterns do improve a material’s strength and resilience. But if these materials are punctured or cracked, the rest quickly buckles and fails. He says that’s because the internal structure is all the same; if one region of the material is deformed, the surrounding, similar unit cells will respond and deform in kind.

“We’ve spent years looking at periodic and ordered microstructures, and we’ve learned there are a lot of limitations and non-ideal responses, such as this localization effect,” Portela says. “We wanted to break free of that notion and use network science to design these materials.”

Line by line

The team developed an algorithm to virtually generate a network of beams with the constraints of a physical material. When applying network science to something like the internet, researchers haven’t had to consider physical constraints, such as limiting the number, density, or intersection of connections. In a physical material, the number and thickness of beams, and the space between them, start to matter. 

To design a physical network, the team’s algorithm starts by drawing a point at a random coordinate in a domain representing the size of the final material. The program draws a line at a random angle, which stretches through the point and crosses the entire space. The program then repeats the process with a second point, at a second random coordinate, and a line drawn through the point at another random angle, until that second line reaches a boundary, of either the whole domain, or the first drawn line. The process then repeats, again and again, drawing progressively shorter, thinner lines. The resulting material represents a dense network of intersecting beams of many varying sizes. 

Scientists can vary the type of network that the program generates, by varying the thickness of the starting line and how fast that thickness decreases with each successive line drawn. By simply tuning these two parameters, the team found they could generate a huge range of networks. They then carried out simulations to predict how tuning one or the other, or both, by varying degrees, would change a material’s stiffness and other physical properties. 

“We see we can really tune the stiffness of a material just by changing these two parameters, which dictate how these network patterns get generated,” Portela says. 

The team then fabricated physical materials with microstructures that were patterned after the networks they virtually generated. They used 3D-printing methods to deposit polymer into patterns of tiny, interconnecting beams. Each resulting sample was a large square, about the size of a credit card, with internal beams that ranged from microns to centimeters in scale. 

They put the samples through various physical tests, such as dropping a large weight onto them and squeezing them with increasing force. They recorded the materials’ response, along with samples of conventional lattice and honeycomb metamaterials. The network-inspired samples, they found, were more resilient to compression and impacts. 

“Because there is such a richness of length scales in these networked materials, if one part fails, there is a strong web of structures around it that keeps the entire material from failing catastrophically,” Portela says. “It’s more efficient at distributing damage and absorbing energy.”

As another demonstration, the researchers designed a material inspired by the density-graded microstructure of a pomelo’s thick rind. They designed the material with edges made from a denser network of beams, and showed it could cushion and protect a fragile object that was embedded at the center of the network.

“This work provides a design framework for materials whose features vary over a very wide range,” says materials expert Tian “Tim” Chen, associate professor in the Department of Aeronautics at Imperial College London, who was not involved with the study. “That may lead to a next generation of materials with unprecedented physical behavior, for any structure that must carry load, absorb energy or control vibration.”

This work was supported, in part, by the U.S. National Science Foundation’s Designing Materials to Revolutionize and Engineer our Future (DMREF) program.

It’s hard to believe how lucrative this crime can be:

According to a press release from the United States attorney’s office for the southern district of New York, three men ­ Jacob Soall, Sharon Hazan, and Guy Sheetrit ­ were arrested for using AI to alter and impersonate the voices and images of executives and attorneys at various companies in order to convince employees to send over large payments. Soall and Hazan were arrested in Spain over the summer, while Sheetrit was arrested in the United Kingdom in September. The alleged fraud took place between 2024 and 2026...

The MIT Schwarzman College of Computing welcomes seven new faculty members in core computing and shared positions to the MIT community in 2026. They’re inventing and using artificial intelligence and computing technologies in new ways to transform areas such as environmental science, quantum computing, human-AI interaction, and macroeconomics and finance.

“It’s a pleasure to welcome these outstanding faculty members to MIT, whose innovative research is leading advances in AI and computing and its impact on society,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Panasonic Professor of Electrical Engineering and Computer Science.

These hires include core faculty with appointments in the Department of Electrical Engineering and Computer Science (EECS), which reports jointly to the MIT Schwarzman College of Computing and School of Engineering, as well as shared faculty positions between the college and other departments, including Urban Studies and Planning, Mathematics, Economics; and, at MIT Sloan School of Management, the Finance Group and the Work and Organization Studies Group.

The new shared faculty include:

David Bruns-Smith, an assistant professor at the MIT Sloan School of Management, who holds an MIT Schwarzman College of Computing shared position with EECS, joined MIT in September. He is also a member of the Laboratory for Information and Decision Systems. His recent research has focused on debiased machine learning with applications in macroeconomics and household finance. Previously, he was a postdoc at Stanford Data Science, and he completed his PhD in computer science at the University of California at Berkeley.

Zana Buçinca, an assistant professor at the MIT Sloan School of Management, who holds an MIT Schwarzman College of Computing shared position with EECS, joined MIT in September. She is also a member of the Laboratory for Information and Decision Systems. Her research interests lie at the intersection of human-AI interaction and the future of work, and involve designing human-AI interaction techniques that complement people and amplify their values in AI-assisted work. She was a postdoc at Microsoft in the Office of Applied Research, and received her PhD in computer science from Harvard University.

Alexandra Cabral, an assistant professor in the Department of Urban Studies and Planning, who holds an MIT Schwarzman College of Computing shared position with the Institute for Data, Systems, and Society (IDSS), joined MIT in September. Her research focus includes low-cost sensor networks, smart cities, environmental informatics, and low-resource computing. Previously, she was a postdoc in the Ka Moamoa Lab at Georgia Tech and served as a 2025-26 NSF ICICLE Educational Fellow. She earned her PhD in computer science from Harvard University.

Alexandru Damian, an assistant professor in the Department of Mathematics, who holds an MIT Schwarzman College of Computing shared position with EECS, joined MIT in September. He is also a member of the Laboratory for Information and Decision Systems. His work is focused on developing a predictive, and ultimately prescriptive, theory of deep learning. He holds a BS in mathematics from Duke University and a PhD in applied and computational mathematics from Princeton University.

Lindsey Raymond PhD ’24, an assistant professor in the Department of Economics, who holds an MIT Schwarzman College of Computing shared position with EECS, joined MIT in July. She is also a member of LIDS. Her research involves the effects of digital technologies and artificial intelligence on labor markets, firms, and market competition. She was a postdoc in economics and computation at Microsoft, and earned her PhD from MIT Sloan.

The new core faculty are:

Jas Brooks, the KDD Career Development Professor in Communications and Technology, joined EECS as an assistant professor in September. They are also a member of the Computer Science and Artificial Intelligence Laboratory. Their work focuses on perceptual engineering: the design of computational interfaces that sense and modulate human sensory perception. Previously, they were a Rising Star in EECS, a Siebel Scholar, and a National Science Foundation Graduate Research Fellow. They hold a BS and PhD in computer science from the University of Chicago. 

Hengyun (Harry) Zhou ’16 joined EECS as an assistant professor in March. He is also a member of the Research Laboratory of Electronics. His research focuses on accelerating the development of large-scale, fault-tolerant quantum computers through full-stack architectural innovation. Before coming to MIT, he previously served as the Quantum Error Correction Architecture Lead at QuEra Computing. He earned his PhD in physics from Harvard University.

The MIT School of Engineering welcomes new faculty members across six of its academic units in 2026. This new cohort of faculty members, who have recently started their roles at MIT, conduct research across a diverse range of disciplines.

“I’m pleased to welcome these talented colleagues to our engineering faculty,” says Paula T. Hammond, dean of engineering and an Institute Professor. “They bring fresh perspectives that will open new directions for research and create opportunities for our students to learn through discovery. I look forward to supporting them as they pursue ambitious ideas, build collaborations across MIT, and help our students grow, both in the classroom and in the lab.”

Faculty with appointments in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Data, Systems, and Society (IDSS) report into both the School of Engineering and the MIT Stephen A. Schwarzman College of Computing.

The new engineering faculty include:

Andrew Akerson joined the Department of Mechanical Engineering as an assistant professor last January. His research interests include optimal design, computational solid mechanics, and material characterization. He previously worked as a research scientist at Meta's Reality Labs Research. Akerson received his BS and MS in aerospace engineering and mechanics from the University of Minnesota and his PhD in mechanical engineering from Caltech.

Jake Hecla ’17, the Charles Stark Draper Career Development Professor, joined the departments of Aeronautics and Astronautics and Nuclear Science and Engineering as an assistant professor in July 2026. His current research interests focus on aerospace nuclear power and propulsion, heat rejection in space, and long-standoff characterization techniques for space nuclear systems. Previously, Hecla was a Stanton Postdoctoral Fellow in the MIT Laboratory for Nuclear Security and Policy. He holds a BS in nuclear science and engineering from MIT and an MS and PhD in nuclear engineering from the University of California at Berkeley.

Zachary Manchester, the Boeing Career Development Professor, joined the Department of Aeronautics and Astronautics as an associate professor in January. He is interested in building autonomous systems that match, and eventually surpass, the levels of performance, agility, and reliability of humans. He previously taught in the Robotics Institute at Carnegie Mellon University. Manchester received his BS in applied physics, his MEng in mechanical engineering, and his PhD in aerospace engineering from Cornell University.

Eric Sun joined the Department of Biological Engineering as an assistant professor in January. He develops new computational and machine learning models to study complex biology across multiple scales with applications in aging, rejuvenation, and immune interactions. Sun is also a member of the Ragon Institute of Mass General Brigham, MIT, and Harvard. He obtained his BS in chemistry and physics and his MS in applied mathematics from Harvard University and his PhD in biomedical informatics from Stanford University.

Haoning Tang joined the Department of Mechanical Engineering as an assistant professor in January. She conducts interdisciplinary research at the intersection of nanophotonics, optical instrumentation, and device engineering, with a focus on metamaterials, quantum materials, and MEMS-enabled platforms. She was previously an adjunct professor in the electrical engineering and computer science department at the University of California at Berkeley. Tang received her BS in electrical and electronics engineering from Hong Kong University of Science and Technology and her PhD in applied physics from Harvard University.

Stylianos Varchanis, the Raymond A. (1921) and Helen E. St. Laurent Career Development Professor, joined the Department of Chemical Engineering as an assistant professor in July. He develops theoretical and computational models to understand fundamental transport processes in complex fluids, soft matter, and living systems, with relevance to materials engineering, energy, and biotechnology. Before joining MIT, Varchanis was a Flatiron Research Fellow at the Flatiron Institute of the Simons Foundation in New York. He received his BS, MS, and PhD in chemical engineering from the University of Patras in Greece.

Hengyun Zhou ’17, the Thomas D. and Virginia W. Cabot Professor, joined the Department of Electrical Engineering and Computer Science as an assistant professor in March. He is developing full-stack architectures for resource-efficient, fault-tolerant quantum computing. His work spans quantum error correction, algorithms and compilation, and hardware architecture. Zhou previously worked as a research scientist for QuEra Computing Inc. He holds a BS in physics and mathematics from MIT and a PhD in physics from Harvard.

The School of Engineering is also welcoming Edward “Jas” Bordeau Brooks, the KDD Career Development Professor in Communications and Technology, who joined the Department of EECS as an assistant professor in September 2026. For more information about Brooks, read the Schwarzman College of Computing’s recent article. 

The School of Engineering also remembers Thomas Rose, MIT’s POSCO Professor of Materials Science and a member of MIT’s Center for Materials Research in Archaeology, who joined the Department of Materials Science and Engineering’s faculty in January. Rose died on Sept. 2 following a bicycle accident. His research focused on ancient metallurgy and pyrotechnology that shaped early human societies, including how copper and its alloys were produced, transformed, and circulated. The work integrated geochemistry, mineralogy, experimental archaeology, and materials science.

A senior studying mechanical engineering and finance, Dominic Hess is an Academic All-American with a packed study schedule. But he and his teammates still make room for about 20 hours a week of football during the regular season. (“It’s a little less in the spring,” he notes.) All this time practicing, working out, and playing in games, he says, doesn’t take away from his academic experience at MIT — it amplifies and improves it. In this interview, Hess discusses his experiences on and off the field at the Institute, as well as plans for the future.

Q: How would you compare your high school football experience to your MIT one? 

A: I'm originally from a small town, Damascus, in Maryland. On my way to high school, I would drive past seven farms and a lot of cornfields. 

Football was big there, and the town was historically really good; I think we’ve won 12 state championships. I grew up playing several sports and decided to stick with football going into high school. Being in a super-competitive environment was a great experience. In my freshman year, the No. 1 player in the nation was on my team. And as a 5'10", 135-pound kid playing with a guy who was 6'6" and 280 pounds, it was crazy — a very high level of football. 

I took my academics very seriously and decided I wanted to keep playing in college, but I knew I wasn’t good enough to play at a Division I school. Luckily, I ended up here — and it has been the most impactful four years of my life.

I’ll say, coming to MIT, it was different. I tell people that I play football here, and they're like — “MIT has a football team?” 

Q: How do you strike a balance between academics and football? 

A: It definitely took some getting used to, especially during freshman year. 

Football actually helped a lot. We come to campus in August, a few weeks before classes start. As a freshman, I had no idea about what classes to take, what the numbers all mean, what the names of things are — all that stuff. But I had all this time where I could talk to my teammates about careers, different majors, and what classes to take. I learned a lot. 

Once school starts, you're taking classes that are harder than anything you've ever taken in high school, and the workload is way more than you’ve had before. It's a huge adjustment, and the balance is not easy — but you get to do it with other people. The community in an athletics team, having built-in friends who can support you, really benefits you on the academic side. 

Also, to me, it’s a grounding thing. I have all this other stuff going on — academics, clubs, my fraternity, whatever. When I walk onto the practice field, I say: “I'm just going to focus on football right now.” Those two hours are the one time of my day when I don't have to worry about anything else. It's a blessing to be there.

Q: What was it like when you became a captain of the team? 

A: I was captain of my high school team, but coming into MIT was a reset. You're back to being a freshman, back to the bottom of the lineup, just trying to earn your stripes. You need to do the work to become a good player and a good teammate. Over my first three years, I was able to improve a lot. I guess my teammates and my coaches recognized that, and I ended up getting selected. 

I think a key thing about being a leader, especially on a sports team, is asking your teammates, What are your goals? And then, just as important, What steps are you going to take to get there? I really want to win a NEWMAC [New England Women's and Men's Athletic Conference] championship, and, obviously, the guys on the team want the same thing. Taking the steps to get there is what's important. You're not going to win a championship in a random way in December, but you can do something today and keep stacking it and getting better and better. 

Being a captain on the field is a little different. It's really about keeping players motivated. I've been watching this documentary about Nick Saban, the Alabama football coach. He talks about each play being six seconds — and all you have to do is focus on this play and go all-out for six seconds. 

Q: What motivates you, on and off the field?

A: I'd say, especially at MIT, the community really motivates me. I grew up with three brothers and was very close to my parents. My dad’s in tech consulting and worked at home, so I got to spend a lot of time with him growing up. My mom quit her job to raise us. Four boys is a lot of work. (They've made it to every game this season; my mom always jokes how this season will be the end of her “sports-mom” era.)

And so, coming here, I guess I was looking for a new family — and I was fortunate to find it in football. You hear a lot of things about MIT, like how hard it is and how students can feel alone. It can obviously be hard here, so I wanted to find that community. 

I've been with the same roommate all four years; we’ve gotten very close. I’m also in a fraternity, DKE [Delta Kappa Epsilon]. Also, being a part of the Catholic community has been really important. It turns out a lot of the guys on the team are also Catholic. I didn't know I'd find that here.

Q: What’s after MIT for you?

A: I interned in New York City the past three summers and am fortunate to have a job lined up for next year. My two older brothers already live and work there, so I'm planning to move in with them. Both my parents are actually from New York, so unfortunately that means I'm also a Jets fan, and unfortunately, now, I can say it means being a Yankees fan. But the Knicks…. 

Eminent theoretical physicist Jeffrey Goldstone, an MIT professor emeritus, Dirac Medalist, and holder of the Department of Physics’ Cecil and Ida Green chair, died Oct. 12 at age 93. 

A member of the MIT physics community for 49 years, Goldstone was especially known for his influential work in quantum field theory as well as contributions to quantum optimization algorithms. Notably, he is the namesake of the Goldstone boson and the related Goldstone theorem.

“Jeffrey was a giant of theoretical physics who will be long remembered and very much missed,” says Tracy Slatyer, director of the MIT Center for Theoretical Physics – a Leinweber Institute (CTP-LI) and professor of physics. “He contributed greatly to the CTP-LI over the years, and it was an honor to have him as a colleague.”

“Goldstone was a brilliant theoretical physicist and a charming, yet diffident and remarkably humble human being,” says Frank Wilczek, a CTP-LI colleague who is the Herman Feshbach Professor of Physics, Emeritus, and a 2004 Nobel laureate. “He made renowned, fundamental contributions to diverse areas of physics, ranging from condensed matter and quantum computing to string theory. Throughout, you can perceive a consistent style: enormous mathematical talent brought to bear on important, concrete, sharply posed physical problems.”

Goldstone is renowned for his remarkable range of groundbreaking discoveries. He began his career as a nuclear theorist. In his early work on nuclear matter with Hans Bethe, he developed the use of Feynman diagrams for non-relativistic many-fermion systems.  

He later turned to particle physics, investigating relativistic field theories with spontaneously broken symmetries. Building on ideas inspired by superconductivity, he demonstrated that spontaneously broken continuous symmetries must be accompanied by massless, spinless particles — now widely known as Goldstone bosons (or Nambu-Goldstone bosons, in recognition of Yoichiro Nambu’s earlier related insights). 

In subsequent work with Abdus Salam and Steven Weinberg, Goldstone formalized and generalized this result, which became known as the Goldstone theorem. With Claudio Rebbi, Charles Thorn, and Peter Goddard, he worked out the light-cone quantization of relativistic strings, a foundational result in string theory. Goldstone also worked with Roman Jackiw and Frank Wilczek on solitons in quantum field theory.  

Goldstone was born in 1933 in Manchester, England. He earned his PhD from Trinity College at the University of Cambridge in 1958 and completed postdoctoral work at Cambridge, Harvard University, CERN, and Copenhagen University. After shifting his focus to particle theory, he joined the faculty at Cambridge in 1962. He moved to MIT as a professor of physics in 1977 and as a researcher in the Laboratory for Nuclear Science, and was appointed the Cecil and Ida Green Professor of Physics in 1983. Goldstone served as director of the Center for Theoretical Physics (now known as the CTP-LI) from 1983 to 1989.  

“Goldstone’s name will always be associated with spontaneous symmetry breaking, where 'Goldstone’s theorem' and 'Goldstone bosons' feature prominently,” Wilczek notes. “His early, seminal papers relating the mathematical concept to physical phenomena gave firm foundations upon which people built fruitful theories of magnetism, meson physics, and eventually the Standard Model and early universe cosmology.

“Jeffrey Goldstone’s ideas are so deeply woven into physics that it takes an occasion like his passing to remind us how much we owe him. I had the pleasure to work with Jeffrey in the early days of fractional charge. The short paper we wrote together is one that I’m especially proud of. It contains the seeds of many later developments. Thank you, Jeffrey, for that fond memory.”

Alan Guth ’69, PhD ’72, MIT’s Victor F. Weisskopf Professor of Physics, Post-Tenure, says, “Jeffrey was a wonderful friend and colleague, and a towering figure in theoretical physics. When I was trying to arrange to come back to MIT after being a postdoc for nine years at other places, it was Jeffrey who I contacted to try to make this happen. When I first learned in 1981 that Andrei Linde had figured out how to make cosmic inflation work, in the form known as 'new inflation,’ I remember that I ran into Jeffrey's office to share my excitement. I have learned a great deal from Jeffrey over the years, and will forever have warm memories of our friendship.”

“Jeffrey Goldstone was a theoretical physicist of rare talent and impact,” says David Kaiser, MIT professor of physics and the Germeshausen Professor of the History of Science. “His landmark article, 'Field theories with superconductor solutions,' published in 1961, helped to launch the modern era of symmetry breaking in high-energy physics. Building on insights from neighboring fields such as condensed-matter physics, Goldstone demonstrated that for any model in which a continuous symmetry is spontaneously broken, there will emerge zero-mass, zero-spin particles now known as 'Goldstone bosons.' His watershed study, and several influential follow-up articles, have become central to our Standard Model of particle physics, with further application as far afield as early-universe cosmology to spin waves in magnetic materials and quantized vibrations in excited fluids. Later in his career, Goldstone turned his attention to quantum information science, helping to construct several novel algorithms for quantum computation. 

“Typically reserved, his close friends admired his droll humor. Writing to Harvard physicist Sidney Coleman in November 1976, for example, Goldstone declined Coleman’s invitation to attend an upcoming physics workshop. 'I expect to be in total confusion during January [1977] and wish to simplify my life,’ Goldstone replied. 'Forty-three years in the womb’ — including decades at his alma mater, the University of Cambridge — 'have unfitted me for coping with normal trivial details of survival. It’s probably a good thing I’m coming out, but the birth pangs are hell.’ 

“The birthing event to which Goldstone referred was his move to MIT to join the Physics Department faculty in 1977. Thank goodness he braved the move. Over nearly 50 years, Jeffrey Goldstone enriched our Department of Physics at MIT, and especially our Center for Theoretical Physics – A Leinweber Institute, with his deep insights and gentle manner.”

Even after retiring from MIT, he remained active in research for the next two decades, working in quantum computation. 

Edward Farhi, professor emeritus of physics and a frequent collaborator for over 20 years, describes Goldstone’s contribution to the field from its early stages as “very significant.”

“FFG [Farhi, Goldstone, and Samuel Gutmann] teamed up with Donner Professor of Mathematics Michael Sipser and showed that there was a problem which could not be sped up with a quantum computer, learning parity in the oracle setting,” Farhi says. “This was the first demonstration of this kind of limitation, although the same week another group proved the same thing by a different method. In 2000 FGG, along with Sipser, introduced the concept of Quantum Computation by Adiabatic Evolution. This is an all-purpose approach to optimization and was later shown to be universal, which means that any quantum computation can be encoded as quantum adiabatic. Furthermore, the company D-wave was founded to run this algorithm. D-wave is the progenitor of all of the superconducting hardware efforts such at the ones at Google and IBM. We later showed that using scattering theory a quantum computer could determine who wins a game provably faster than the best classical algorithm for this task.

“FGG introduced the Quantum Approximate Optimization Algorithm. This was the first time a general purpose quantum optimizer could provide worst-case performance guarantees for combinatorial optimization problems. These guarantees as of now (with one exception) do not beat the best classical. Still, this paper has over 6,000 citations, making QAOA one the most-studied quantum algorithms.

“In 2019, FGG and Leo Zhou applied the QAOA to the Sherrington-Kirkpatrick model. We showed how to analyze performance in the infinite size limit at any depth. Our work and others indicated that as depth increases with optimal parameters, the QAOA would approach the celebrated Parisi value. Recently the Open AI math dump, the conjecture that the QAOA would hit Parisi, was proven by the AI. I bet Jeffrey would have been surprised and impressed!”

Jeffrey Goldstone was a fellow of the American Physical Society Fellow, the Royal Society, and the American Academy of Arts and Sciences, and he was an honorary fellow of Trinity College, Cambridge. 

His honors included the Guthrie Medal of the Institute of Physics, the Dannie Heineman Prize for Mathematical Physics of the APS, and with Stanley Mandelstam the Dirac Medal (1991) of the Abdus Salam International Centre for Theoretical Physics, awarded for “his fundamental clarification of the phenomenon of spontaneous symmetry violation in relativistic field theory.”

He is survived by his son Andrew Goldstone, associate professor of English at Rutgers University’s New Brunswick campus; his daughter-in-law Anne Dewitt, a clinical associate professor at New York University’s Gallatin School of Individualized Study; and his granddaughter, Helen. His family is planning a memorial in 2027. 

It’s a bad one, and it’s been in the code for a decade:

A newly disclosed flaw involving OpenSSH and musl, dubbed “*sshole,” allows attackers to log in to certain Alpine Linux and other musl-based Linux accounts configured to block password authentication simply by entering an oversized password.

“Oversized” means longer than 256 bytes. Details.

Slashdot thread. And another news article.

MIT researchers will lead an up to $53 million effort, awarded by the U.S. Advanced Research Projects Agency for Health (ARPA-H) as part of its STREAM (Systems for Tracking and Resilience in Efficient Agricultural-input Management) program, to develop next-generation weed killers that help farmers and protect human health. 

More than 1 billion pounds of herbicide are used in the United States every year. Herbicides help farmers by preventing significant crop loss due to weeds, and they enable regenerative farming practices that protect the soil, but some weeds are becoming resistant to the most common herbicides. 

Exposure to herbicides may contribute to increased risk of cancer, metabolic and endocrine disorders, and other adverse health outcomes. Farm workers can be exposed from frequent herbicide use, but many U.S. residents are also exposed to these chemicals in small amounts through food and drinking water. 

The MIT-led research team will develop new generative artificial intelligence tools to help them discover herbicide alternatives that are more effective and developed with human health in mind. Such alternatives could also help to reduce U.S. dependency on imported phosphorus, which is a critical ingredient in a major herbicide, glyphosate.

“With herbicides like glyphosate and atrazine, there’s a real crisis because of resistance mutations that are coming,” says Christopher Voigt, head of MIT’s Department of Biological Engineering. “And if you combine the resistance mutations with issues around national security of the supply chain of the precursors to herbicides, we could find ourselves without these core agrochemicals that are absolutely essential for getting the high crop yields and economical prices that the United States now sees.”

Voigt is the principal investigator for the project, known as Precision Learning for On-target Weed control (PLOW). The team is also expected to include researchers from the Broad Institute of MIT and Harvard, the University of North Carolina at Chapel Hill, the University of Tennessee at Knoxville, the University of Illinois at Urbana-Champaign, and Robigo.

The researchers are grouped into three teams that will tackle different aspects of the project, aligned with the STREAM Technical Areas. The generative AI group will develop models that can predict molecules — either chemical compounds or small interfering RNA (siRNA) — that disrupt the same plant enzymes targeted by glyphosate and other herbicides.

Glyphosate kills weeds by interfering with an enzyme called EPSP synthase, which plants need to produce several critical amino acids. After many years of herbicide use, some weeds have begun to acquire genetic mutations that allow them to become resistant to those herbicides, which makes them less effective and poses a significant threat to crop yields.

“There’s a real need for new herbicides because of resistance mutations that have been arising,” Voigt says. “There are also concerns about herbicides’ possible impacts on the environment and on humans, so it’s important to identify alternative ways of making herbicides, which as a general class of molecule are really critical to agriculture.”

The MIT-led team plans to design generative AI models that will be able to predict molecules that can help prevent resistance from arising. The models will also optimize for other features such as low cost of synthesis, low risk of inducing resistance, and low risk of harming humans or causing ecological damage. 

The group developing these AI models is led by Connor Coley, the Warren K. Lewis Associate Professor of Chemical Engineering at MIT; Regina Barzilay, the School of Engineering Distinguished Professor for AI and Health at MIT; and Alexander Tropsha, the K.H. Lee Distinguished Professor in the UNC Eshelman School of Pharmacy.

The models are expected to generate billions of possible candidates, which will then be tested by a second research team. This high-throughput screening group will be led by Angela Koehler, the Charles W. and Jennifer C. Johnson Professor of Biological Engineering at MIT, and Jaime Cheah, the associate director of scientific outreach and collaborative screening in the Center for the Development of Therapeutics at the Broad Institute.

“Those libraries will be screened both to identify those molecules that hit their target, but also to then provide all of that screening data back to the computational approach in order to improve it,” Voigt says.

Once the candidate pools are narrowed down, researchers on a third team will begin greenhouse studies to evaluate how each molecule performs under different agricultural conditions. That team will be led by Neal Stewart and Scott Lenaghan, co-directors of the Center for Agricultural Synthetic Biology at UTK; Patrick Tranel, the Tom and Peggy Ainsworth Professor of Crop Sciences at the University of Illinois; Tim Willson, the Harold Kohn Distinguished Professor at the UNC Eshelman School of Pharmacy; and Andee Wallace PhD ’20, CEO and founder of Robigo. 

The first greenhouse tests of initial RNAi candidates are expected to be complete by the end of the first year of the program.

As part of this project, the research team will also develop living microbial systems that degrade agrochemicals before they reach food, soil, or waterways. Engineered bacteria, fungi, and srRNA will convert chemicals and formulation ingredients into biomass, providing a scalable strategy to reduce environmental and human exposure.

This research is funded by the Advanced Research Projects Agency for Health (ARPA-H) under agreement number 140D042690030. The views and conclusions contained in this article are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States government.

The United States used to be the world leader in metal casting, a process where liquid hot metal is poured into a mold to solidify into a desired shape. But more than 70 percent of American metal casting facilities have closed since the industry’s peak in the 1950s. Today, China and India dominate global metal casting production, which is critical for making the components of jet engines, nuclear and gas turbines, medical devices, and more.

Fabri is trying to revitalize American metal casting. The company, founded by Steven Davis ’24; Thomas Cole ’91, MBA ’13; and Pieter Coulier, is building a new kind of metal casting foundry that uses additive manufacturing, software, and vertical integration to eliminate many of the most labor-intensive steps associated with traditional metal casting. 

Fabri is already producing parts for a growing list of customers at its 16,000-square-foot plant in Billerica, Massachusetts, where it is applying its approach to one of the most multidisciplinary and challenging types of metal casting, known as investment casting. The company is working with Raytheon, Lockheed Martin, and Sikorsky Aircraft, among others, and is moving through qualification to make parts for the most critical aerospace and defense applications.

Fabri’s first foundry was designed to be quickly replicated. Even as it significantly expands capacity at its current plant, demand from customers is driving the company to build a far larger facility in 2027 that will produce bigger parts at higher volume as customer programs move into production.

“Metal casting is one of the oldest and most prevalent manufacturing methods in the world,” Davis says. “It’s a uniquely difficult process because there are so many different steps. There’s so much domain knowledge and experience you need to understand it. If we get cut off from the world’s casting capacity, that means no more pots and pans, no more storm drains and other basic things, but also no more aircraft. Lots of medical devices, like titanium hip implants, are cast. Power generation also depends on metal parts. These are very critical industries that we need to continue to produce.”

Faster metal production

Davis grew up competing in robotics competitions like BattleBots. The biggest challenge for his small, underfunded teams was getting the parts to make the robots.

Davis arrived at MIT in 2020, where he majored in mechanical engineering. As part of a summer internship after his sophomore year, he worked at Relativity Space, which builds reusable rockets. There he saw multi-million-dollar projects being delayed by the same hurdles he faced in robotics competitions. His team would wait weeks for expensive machines to make parts.

“I realized the problem was scale,” Davis says. “These production processes couldn’t even scale to aerospace, so they weren’t going to scale to far larger industries.”

When Davis returned to MIT that fall, he worked on adapting the precision and flexibility of 3D printing to producing metal parts. Davis also took several classes taught by John Hart, MIT’s Class of 1922 Professor and head of the Department of Mechanical Engineering. Hart co-founded several additive manufacturing companies including VulcanForms and Desktop Metal. He continues to advise Fabri.

“I was very interested in finding the best uses of additive manufacturing,” Davis recalls. “A lot of the most successful companies weren’t making end parts; they were making tools. My favorite example is Invisalign. They’re not printing the dental liners: They are printing the molds that make the aligners.”

Davis began thinking about starting a company roughly midway through his bachelor’s degree at MIT. He met Cole through his MIT network. Cole had founded a fully automated CNC machining company making dental implants that was acquired by AstraZeneca. Pieter Coulier, Fabri’s third co-founder, previously developed the simulation and metal 3D-printing algorithms at Velo3D that enabled SpaceX’s Raptor engines to be printable.

Davis also began visiting foundries, where he repeatedly heard their biggest bottleneck was labor.

“They all have huge ‘Help Wanted’ signs out front,” Davis says. “Capacity is going down. That’s why we realized automation had to be a core part of our thesis. According to the American Foundry Society, these workers are retiring at a rate of 3-to-1. It’s really hard to find these foundry engineers who understand what goes into the process and can design these molds. We have customers tell us they had an engineer retire and now they can’t make certain parts anymore. We want everything we learn to be encoded into our software forever.”

Investment casting is a complex, multistep process.

“Traditional investment casting starts by cutting a hard tool out of steel,” Davis explains. “Then you injection mold wax patterns into it. Those wax parts get glued together into what’s known as a tree. Then you dip the tree into liquid loaded with ceramic powder, you stucco it with sand, dry it, and repeat the process seven or eight times. That’s how you get the ceramic mold to pour your steel into to make the part.”

Fabri’s process starts with the part’s computer-aided design (CAD) file. The company’s proprietary software, FoundryOS, designs a pattern for each part, which Fabri prints in resin using established techniques including digital light processing (DLP) and stereolithography. The printed pattern is dipped in ceramic slurry to build the shell that molten metal is poured into. FoundryOS incorporates data from every step and uses machine learning models to improve the process and the parts with each casting.

“By printing that mold right off the bat, we remove the need for all those early steps,” Davis explains. “We fully automate the creation of the [complex patterns and channels] needed for making that tree. Instead, we print it all in one piece and consolidate a lot of that work.”

Davis says traditional tooling can cost upward of $1 million for complex enough designs and take many months to make — a big reason companies have to wait so long for parts.

Davis built the first prototype of Fabri’s printer in the basement of his MIT fraternity using funds from the MIT Sandbox Innovation Fund. After subleasing a space in Ashland, Massachusetts, Fabri was pouring metal within six months. Today, he says Fabri’s approach also cuts post processing and benefits from the increased flexibility of 3D printing, which allows Fabri to iterate on parts in days.

“What really hurts traditional foundries is they put a design into production, they tool up, they cut a tool, and when they get their first part, they realize something’s wrong,” Davis says. “Then they have to rework it or fix it. They’d like to fix the tooling in the process, but they can’t because they spent so much on the tool and waited six to nine months for it.”

Reinvigorating an industry

Fabri opened its first foundry in Ashland in 2025 and moved production to Billerica in spring of 2026. Davis says the company can go from receiving a design to producing a finished part in as little as a week. Fabri is making parts out of aluminum, copper alloys, and stainless steel, primarily for munitions, aviation, and naval applications. In early 2027, the company plans to begin casting nickel superalloys, the metals used in the turbine blades that can currently have four-year wait times.

The company’s process also enables complex geometries and organic topologies that hard tooling can’t produce.

“We’re building the software that can make these parts more intelligently and faster,” Davis says. “Qualifying for aerospace production with a company like Raytheon is a really big deal. Most startups and 3D-printing companies we know haven’t done it. The ability for us to go from opening our first facility in 2025 to now going into production with some of the nation’s most critical platforms is a huge milestone. We are going to be making parts that are going to fly in the systems and go into the munitions platforms that the country needs.”

When Andrew Voelsing was 8 years old, he decided he was going to MIT.

He was fascinated by space and dreamed of building spaceships. The Institute, and its well-known aerospace engineering program, seemed like the obvious destination. 

Years later, as a senior studying climate system science and engineering, Voelsing is preparing for a different kind of career: serving as a Navy officer, using his technical training to help the armed forces understand the ocean and atmosphere. 

Even during childhood, military service was never far from his mind. His mother attended the U.S. Naval Academy, and his father participated in the Reserve Officers’ Training Corps (ROTC) at the University of Notre Dame. The two met while serving in the Navy in Japan. Growing up, Voelsing heard their stories about military life and saw how their experiences as naval officers shaped their lives.

Voelsing was eventually accepted to the Naval Academy himself. But he chose MIT for the variety of faculty and activities he could pursue while also earning his commission as a Navy officer through the NROTC program. He will soon assume the highest-ranking student role of Battalion Commander, responsible for NROTC across Greater Boston.

But the path from an 8-year-old’s dream to his senior year in Cambridge, Massachusetts, was not quite as straightforward as he had imagined. After arriving at MIT, Voelsing struggled to find his footing academically.

“I thought I was smart in high school. I thought I was at the top of my class, and then I got here and I was failing midterms,” he says. “All my friends seemed to be getting things faster than I was, and I just felt really out of place.”

During the winter break of his first year, he talked with his father about how he was feeling. His father encouraged him to find something that combined what he was good at, what fulfilled him, and what the world needed.

The conversation helped Voelsing reconsider his academic path. He switched from aerospace engineering to climate system science and engineering (Course 1-12), a then-new major offered jointly by the departments of Civil and Environmental Engineering and of Earth, Atmospheric and Planetary Sciences, and returned to campus feeling energized by his studies. 

The change also helped him see how his education could serve a purpose beyond earning a degree. As he continued his ROTC training, he began to consider how technical knowledge about the environment could inform decisions with real-world significance.

The change, he says, was like night and day.

“I really figured out how to study,” he says. “Finding out my own vision of self and academic fulfillment helped me propel myself forward.”

A course in environmental history with Professor Susan Solomon, an atmospheric chemist who helped discover the cause of the Antarctic ozone hole, further shaped his interests. Each week, the class examined a different environmental issue, encouraging students to investigate primary sources and identify questions that had received less attention.

For his final paper, Voelsing researched an agroforestry project in Uganda. The project sparked a deeper interest in global agricultural and food systems, an area he hopes to explore in graduate school.

“There’s not going to be this one technology that comes along, and suddenly climate change isn’t an issue,” he says. “It will be a combination of 100 things making it 1 percent better for us to get across that finish line.”

Outside the classroom, one of Voelsing’s most formative experiences has come through Camp Kesem, a student-run nonprofit that provides free summer camps for children whose parents have been affected by cancer.

He joined MIT’s chapter as a first-year student. The chapter serves more than 200 campers, ages 5 to 18, giving them a week of sleepaway camp filled with activities such as ziplining, swimming, and games.

Over the years, he has taken on several leadership roles. He started as a counselor, then became operations coordinator, helping plan and run the camp. Later, he led alumni relations and organized a fundraising gala. As a senior, he returned to counseling, realizing that the part of the experience he valued most was spending time with the children.

“The thing I enjoy most isn’t all the planning; it’s not all the coordinating,” he says. “The thing I enjoy most is just spending time with kids.”

Camp Kesem also changed how he understands empathy. Before joining, he says, he was uncomfortable when other people cried. Through conversations with campers and fellow counselors, he learned the importance of sitting with someone through difficult emotions instead of trying to make those feelings go away.

“Being able to sit with a person as they grieve and experience that grief with them really changes your views on empathy and changes your views on what is actually important,” he says.

Voelsing has tried to bring that openness to his friendships on campus, too. He values conversations that allow people to understand how different experiences have shaped their perspectives, and he makes an effort to connect people who might not otherwise meet.

“I would give up a good night’s sleep seven nights a week for a good conversation or staying up talking to a friend,” he says. “And I often do.”

That same willingness to learn from others has informed his experience in ROTC. Through the program’s training and relationships with fellow midshipmen, Voelsing has gained a perspective on military service that extends beyond the family stories he grew up hearing.

He recently received his service assignment as a meteorology and oceanography officer, a specialty that will allow him to draw on his scientific background. 

Before beginning his service, however, Voelsing hopes to attend graduate school. He wants to deepen his expertise before joining the Navy full time, believing that further study will allow him to contribute more once he begins his career.

Balancing his academic work, ROTC commitments, and extracurricular activities requires him to be deliberate about how he spends his time. Rather than getting overwhelmed by everything on his plate, Voelsing tries to focus on the responsibility in front of him.   

“I’m trying to tackle it with enthusiasm, and trying to be where my feet are and do the thing well,” he says.

Looking back on his four years at MIT, Voelsing says the most important influence on him has not been a particular class or professor, but the community he has found among his friends. He values the way MIT brings together people with different interests, backgrounds, and ways of thinking, and he hopes to be someone who helps those people connect.

That sense of responsibility also informs how he thinks about the future. Whether in climate science or the military, he wants to approach difficult decisions with an awareness of their consequences and a willingness to take on challenges others might find daunting.

“Somebody’s got to do it. Why not me?” he says. “I think that is really the through line of what I want to do academically and the kind of life I want to lead.”

It was a landmark in history: In 1957, Ghana became the first sub-Saharan African state to achieve independence from colonial rule, having previously been under the control of Great Britain. 

But gaining political independence does not mean the past is left behind, and there has long been public debate about the many long-term effects of the colonial period on state and society in subsequent decades.  

Now, an empirically rich study explores one aspect of the Ghanaian state, the composition of its bureaucracy, during and after British rule. The study finds that two ethnic groups, the Ga and the Fante, which made up 14 percent of the population combined, held over 70 percent of public-sector positions in the 1950s, suggesting goods such as desirable jobs had been heavily distributed along group lines. 

“At the moment of independence, you have a state that is not meritocratic, and is highly captured by certain ethnic groups,” says MIT scholar Noah Nathan, co-author of a newly published paper detailing the study’s findings. As a result, he adds, “You can imagine the politics that creates, which are demands to equalize access to state power and state authority. And things start off on this foot of ethnic political competition over the state. That is in part a legacy of colonial state-building.”

At least in this case, “Independence in Africa wasn’t this hard break from the past,” suggests Nathan, a Ford International Professor of Political Science in MIT’s Department of Political Science. “Africans became the leaders of their countries, but the state institutions that they inherited weren’t born fresh at independence. They were carried over from the colonial period.”

The paper, “The Seeds of State Capture: Merit and Patrimonialism in the Colonial Bureaucracy,” is published in advance online form in the American Political Science Review. Nathan’s co-authors are Sarah Brierley, an associate professor at the London School of Economics and Political Science; George Kwaku Ofoso, an associate professor at the London School of Economics and Political Science; and Tingxuan Zhu PhD ’26, a recent graduate of MIT’s doctoral program in political science at MIT. 

Analyzing names

To conduct the study, the scholars dug into records from the period of British rule in Ghana, which extended from the 19th century until 1957. Using documents from the British National Archives, they examined individual-level employment records for 11,702 bureaucrats from the colonial-era civil service, building a dataset spanning from 1897 to 1955. The records included 6,879 Ghanaian civil servants and 4,805 European civil servants. The scholars’ aim was to shed light on the dynamics of civil service hiring and politics. 

British leaders at the time, and some commentators subsequently, have cast the colonial state as one built on rational, merit-based principles — what scholars call a “Weberian” bureaucracy, named after the famous German sociologist Max Weber. Scholars say that other types of bureaucracies, in contrast, display “patrimonialism,” with jobs being assigned not on merit but through patronage.

To analyze this question further, the scholars looked at 13.8 million names of registered voters from contemporary Ghana, along with localized ethnicity data from the 2010 national census. They used this to establish a baseline of the relationship between names and ethnicity in the country. Then, the scholars went back to the historical archives, and, using the names there, determined the ethnicities of past Ghanaian civil servants, from 1897 to 1955. 

Ultimately this approach showed that on the eve of independence, the Ga and Fante had managed to gain a percentage of civil service jobs that was five times greater than the percentage of the population they represented. That strongly suggests that the colonial-era bureaucracy built under British rule was not merit-based, at least in terms of overall composition. 

“Scholars have said this post-1957 independent Ghana brings with it the introduction of patrimonialism into the bureaucracy, and we’re saying this was going on long before,” Nathan explains. “It actually wasn’t meritocratic at all, and Kwame Nkrumah, the first president of Ghana, didn’t inherit some Weberian rational bureaucracy that he then destroyed. He inherited this thing rife with patrimonialism and patronage, that he then adapted. And that’s a very different interpretation of the post-independence period.”

Exams and education

To further examine the question of merit, the scholars even obtained individual-level results from Ghana’s civil service exams, then analyzed those in relation to which applicants got hired — or passed over for jobs. The results indicate little correspondence between exam results and job offers, again suggesting that ethnicity and social ties mattered more in hiring, on aggregate. 

“If you were from the right ethnic group, you were going to get a job, even if you did pretty poorly on the civil service exam,” Nathan says. “And people from disfavored ethnic groups who did much better on the exam were not getting the same positions.”

The study also rules out a seemingly logical explanation for at least part of the ethnic skew in the composition of the Ghanaian civil service — that hiring reflected levels of educational attainment, even if access to schooling itself might have reflected ethnic iniquities. But the data indicate that was not a factor. 

The scholars located every school in the country geographically, dating to the 1890s, and closely measured access to education for all ethnic groups over time. The Ga and Fante groups may have had some initial advantages in this regard, but by the 1930s, many other groups had caught up in educational attainment and still were not procuring the same relative numbers of civil services jobs through the 1950s. 

“At least in this case, that can’t explain why these two groups got favored in the hiring process,” Nathan says. “It wasn’t just a direct outcome of the fact that some parts of society had more education than others.”

As it happens, geographical proximity to civil service jobs is also not an explanatory factor; the scholars also examined the locations of government offices and found they cannot account for the quantity of jobs going to the Ga and Fante. 

Out of sight

Instead, the researchers believe the likeliest scenario is that, once established in the civil service, people from the Ga and Fante managed to use their social connections to get more and more jobs offered to others from their own groups. Moreover, they may have done so not necessarily with explicit British approval, but with something more resembling indifference on the part of the colonial rulers. 

“The mechanics of the hiring process were very decentralized,” Nathan says. “And the British didn’t know very much about the society they were governing. That created an information asymmetry where local bureaucrats could get friends into jobs in a way their superiors were either not aware of or didn’t have very much incentive to stop.”

All told, Nathan observes, “The ministry of finance in Ghana in 1957 isn’t some new thing that’s created from scratch. It’s the colonial ministry of finance that’s been in place for 60 years, and the bureaucrats in it showed up to work the next day in the same jobs. [The new leaders] inherited thousands of employees who had gotten there through this process.”

The study is one of several that Nathan has published using data to answer questions that span both political science and history. Quantifying the issue in a granular way helps illuminate the large-scale political dynamics.

“People have written about this in broad strokes, even the fact that certain ethnic groups in some countries got more access to positions than others, but they haven’t had detailed microdata on exactly who got which job and when,” Nathan says. “That’s the innovation of our paper … we could unpack the nuts and bolts of how this hiring process happened, and in doing so dispel some conventional wisdom about how African states were built in the colonial period.”

The new paper is not the only piece of scholarship taking this kind of data-intensive approach to studying colonial state-building and its legacy. Ada Johnson-Kanu, an assistant professor of political science at the University of Kentucky, has conducted this sort of study of Nigeria’s bureaucracy over time, in work she completed in 2021. 

Nathan, for his part, says he hopes that other scholars can expand upon this kind of data-driven approach to digging into certain historical questions. 

“There is just incredibly rich archival evidence out there in the world for a lot of countries,” Nathan observes. “I think this is a really fun way to do research.”

Nature Climate Change, Published online: 10 November 2026; doi:10.1038/s41558-026-02769-9

Data centres are among the world’s fastest growing electricity consumers. An analysis of more than 9,000 facilities worldwide links the artificial intelligence-era expansion of data centres to delayed coal plant retirements and around 2 Gt of additional carbon dioxide emissions.

Nature Climate Change, Published online: 10 November 2026; doi:10.1038/s41558-026-02789-5

Scientific grounds for a net-zero policy assume near-zero committed warming over a few decades after CO2 emissions cease. A modelling study suggests that if prior peak temperatures rise above 2 °C before cessation of CO2 emissions, committed warming increases, making it harder to stabilize global warming.

Nature Climate Change, Published online: 10 November 2026; doi:10.1038/s41558-026-02794-8

Data centre expansion may slow the coal-fired power plants phase-out, complicating decarbonization pathways. This study finds that coal units exposed to post-2020 data centres have lower retirement risks and their potential lifetime extensions could cause large additional CO2 emissions.

Nature Climate Change, Published online: 10 November 2026; doi:10.1038/s41558-026-02821-8

This work projects a decline in global emissions in 2026 as a result of clean energy and in response to conflicts. Energy demand has increased, and will continue to, with electric vehicles and solar and wind deployment mitigating emissions; accelerated deployment is needed to reduce emissions.

Today, along with the ACLU, EFF filed an amicus brief in the Sixth Circuit court of appeals in United States v. Sturdivant, a case where police warrantlessly tracked a suspect’s movements using Automated License Plate Reader (ALPR) data. Our brief details the vast, interconnected network of ALPRs that constantly track drivers around the country and argues that this tracking is a “search” under the meaning of the Fourth Amendment.

Sturdivant involves a series of robberies in and around Cleveland, Ohio. Using surveillance camera footage, police identified the make, model and color of the robber’s car, but they did not know its license plate number. After running an open-ended search of two ALPR databases, Flock and ELSAG, officers learned a car belonging to the defendant had been tracked near sites of the robberies, eventually leading to his arrest. Faced with a motion to suppress the ALPR evidence, the district court held that Mr. Sturdivant had no reasonable expectation of privacy in his license plate number because it could be observed by members of the public, and that therefore he had no Fourth Amendment interest in not having his car tracked in public places.

But ALPRs are simply not comparable to observing an individual license plate on a passing car. As we’ve explained in many amicus briefs and in our lawsuits directly challenging ALPR use in San Jose, California and Wisconsin, ALPRs give law enforcement “a virtual time machine to view suspects’, or anyone else’s, past movements (and much more) with just the click of a button.” Just last month, a federal district court agreed and held that ALPRs are a “form of indiscriminate mass surveillance” that can violate the Fourth Amendment.

We hope the Sixth Circuit will reverse the lower court in this case and hold that ALPR searches require a warrant.

Related Cases: Wisconsin Council of Churches v. Milwaukee, Racine, Kenosha & Green BaySIREN and CAIR-CA v. San Jose

The number of petitions being filed at the Patent Trial and Appeal Board (PTAB) has collapsed. That’s not reason for celebration. The PTAB is an important line of defense against low-quality software patents being used in lawsuits against people and companies.

The drop didn’t happen because suddenly patents have become higher quality. It’s simply because USPTO leadership is increasingly refusing to consider good challenges to patents, for reasons unrelated to the merits. The process has become so unreliable that many would-be patent challengers aren’t even trying.

Inter partes review (IPR) is a process that allows people to challenge patents at the Patent Office, rather than having to fight an expensive lawsuit in federal court. It’s one of the most important ways to get bad patents out of the system.

In the third quarter of 2026, July through September, only 97 IPR petitions were filed at the PTAB, compared to 327 petitions during the same period in 2025. Similarly, only 37 IPR petitions were filed in September 2026, compared to 129 petitions in December 2024—the last full month before the current USPTO leadership began reshaping how the Board handles patent challenges.

This dramatic decline shouldn’t just concern patent lawyers. EFF has fought bad patents because so many software and internet patents make claims to the basic tools of free expression online, like sending email, using online ads, or publishing web pages. When bad patents go unchallenged, they affect everyone who cares about the freedom to write new code and make new technology.

That’s why EFF has defended IPR since it came on the scene more than a decade ago. It provides a faster and less expensive way to challenge patents that should never have been granted. Congress created IPRs because the Patent Office makes mistakes. District court litigation is an extraordinarily expensive way to correct them. Without a meaningful administrative review process, bad patents remain powerful weapons in the hands of patent trolls and others seeking to extract settlements from companies that often did nothing wrong.

Now, USPTO leadership is dismantling that safeguard.

Petitions and Institution Rates Are Falling

Since Congress created the IPR patent challenge process in 2012, the PTAB has always had some discretion in deciding which petitions deserve review. But institution rates today are much lower than their typical historical range.

Between fiscal years 2022 and 2024, the PTAB instituted between 66% and 68% of IPR petitions. In fiscal year 2026, which concluded in September 2026, the institution rate fell to 41%. And institution is only the first step of an IPR—it means the PTAB has agreed to hear the challenge, not that the challenger won, and the patent will be invalidated.

That decline helps explain why fewer petitions are being filed in the first place. Preparing an IPR petition takes substantial time and money. While cheaper than federal court, it’s still a complicated administrative process. Before filing, a challenger typically needs to search for prior art, hire experts, and develop detailed technical and legal arguments about why the patent never should have been granted.

Companies were willing to pay for IPRs because, historically, they could expect a predictable process. Petitions that met the statutory standard generally had a reasonable prospect of being heard and decided on the merits. But the USPTO has made it harder to get petitions heard and is throwing them out for reasons that have nothing to do with the merits of the challenges. Faced with these odds, many potential challengers aren’t filing at all.

Even After a Challenge Is Accepted, The USPTO Director Can Cancel It

When the PTAB decides to hear an IPR case, that means the petition has been “instituted”—but that has never meant that the petitioner will definitely win. It means the PTAB has determined the challenge warrants a full merits review, and the parties could expect the proceeding to continue toward a final written decision. But under the current USPTO leadership, that expectation has disappeared. The PTAB’s institution decisions are being repeatedly vacated by the Director.

USPTO Director John Squires has vacated at least 29 decisions granting institution of IPR proceedings, and subsequently denied the petitions, terminating those proceedings before a final written decision. These include cases that PTAB judges had already agreed to hear, as well as proceedings that Squires himself had previously allowed to proceed. This level of retroactive intervention is unprecedented.

In some cases, the parties had already invested substantial time and money litigating before the PTAB, only to have the proceeding terminated based on new reasoning by the Director’s office that arose after institution.

For example, in Revvo Technologies v. Cerebrum Sensor Technologies, the Director vacated an institution decision and remanded the case to the Board. The Board then instituted review again, but the Director reversed that decision. Using a new approach, the Director said that the petition had inconsistencies between claim construction positions taken before the PTAB and in district court. Since then, that decision has been cited as a basis for terminating several other instituted proceedings.

The result is another layer of uncertainty for people who want to challenge bad patents. Getting through the front door of an institution decision is much harder than it used to be—and now, even getting through that door doesn’t mean the PTAB will decide your challenge. Predictability is one of the things that made IPRs work.

Congress Created the PTAB To Avoid Costly Litigation

Congress created IPRs in part because challenging a questionable patent in federal court is enormously expensive and risky. Patent examiners work under serious time constraints, and some patents that shouldn’t have been granted will inevitably issue. Not every patent dispute requires years of expensive district court litigation. Congress recognized that, and created an administrative process, staffed with experts more capable of correcting those mistakes.

That system has benefited the public. Since 2012, it has helped invalidate thousands of patent claims that never should have been issued. The IPR process has protected startups, software developers, nonprofits, and small businesses that otherwise would have faced crushing litigation costs simply for building products or offering services that use everyday internet technology.

EFF supports a balanced IPR system because it should be easier to fight against bogus patents that should never have been issued. The cost of fighting a patent can be a weapon in itself, and weak patents don't just burden large technology companies. Patent trolls routinely target small businesses and independent developers, and have gone after podcasters, retailers, and even coffee shops and nonprofits. These organizations have neither the resources nor the desire to spend years litigating over potentially invalid patents in federal court. IPR offers a chance to challenge those patents before litigation costs get out of control.

If we weaken the IPR system, bad patents become much harder and more expensive to challenge.

We Shouldn't Accept This as the New Normal

Some defenders of the current approach argue that lower institution rates reflect more balance in the patent system. But institution rates at the PTAB have plummeted from 68% to 41% in just two years—a nearly 40% decline. IPR petition filings have reached historic lows. And even proceedings that have already been instituted can now be terminated months later, without a decision on the merits.

These developments send a troubling message to members of the public who might want to use the PTAB: don't bother. The PTAB doesn’t need to institute every petition. But it does need to provide a process that is transparent, predictable, and fair. Right now, confidence in the system is disappearing.

If companies, individuals, and nonprofits conclude that IPRs aren’t worth pursuing, the consequences won't stop at the PTAB. More weak patents that never should have been granted will survive, and patent trolls will use them. That means more defendants facing expensive district court litigation or paying settlements driven by the cost of litigation.

That's not what Congress intended when it created IPRs. It should not become the PTAB's “new normal.”