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.

EFF is filing against the Consumer Product Safety Council (CPSC) to ensure that the public has full access to the laws that govern us.

Our client Public.Resource.Org (Public Resource), a tiny non-profit founded by open records advocate Carl Malamud, has a mission that’s both simple and powerful: to make government information more accessible. Public Resource acquires and makes available online a wide variety of public documents such as tax filings, government-produced videos, and federal rules about safety and product designs. Those rules are initially created through private standards organizations and later incorporated into federal law. Such documents are often difficult to access otherwise, meaning the public cannot read, share, or comment on them. 

Working with Harvard Law School’s Cyberlaw Clinic, Public Resource has been submitting Freedom of Information Act requests to the CPSC requesting copies of the legally binding safety codes for children’s products—an area of law of intense interest to child safety advocates and consumer advocates, not to mention the families who use those products. But CPSC says it can’t release the codes, because the private association that coordinated their initial development insists that it retains copyright in them even after they have been adopted into law. That’s like saying a lobbyist who drafted a new tax law gets to control who reads it or shares it, even after it becomes a legal mandate.

Faced with similar claims, some courts, including the Court of Appeals for the Fifth Circuit, have held that the safety codes lose copyright protection when they are incorporated into law. Others, like the D.C. Circuit (in a case EFF defended on Public Resource’s behalf), have held that even if the standards lose copyright once they are incorporated into law, making them fully accessible and usable online is a lawful fair use. 

Now EFF has teamed up with the Cyberlaw Clinic to continue the fight. We’re asking a court to rule that copyright is no barrier to accessing and sharing the rules that are supposed to ensure the safety of our built environment and the products we use every day. With the rule of law under assault around the nation, it is more important than ever to defend our ability to read and speak the law, without restrictions.

In 2025, Google, Amazon, Microsoft and Meta collectively spent US$380 billion on building artificial-intelligence tools. That number is expected to surge still higher this year, to $650 billion, to fund the building of physical infrastructure, such as data centers (see go.nature.com/3lzf79q). Moreover, these firms are spending lavishly on one particular segment: top technical talent.

Meta reportedly offered a single AI researcher, who had cofounded a start-up firm focused on training AI agents to use computers, a compensation package of $250 million over four years (see ...

The conflict threatens to deflate global confidence in natural gas as President Donald Trump hopes to expand U.S. exports.

A former Trump energy adviser is urging the administration to study and regulate solar geoengineering before an adversary weaponizes it.

Republican state attorneys general say two of the nation’s leading scientific bodies helped develop educational materials that favor climate activists.

Republican lawmakers are rushing to defend an agency that has been under administration scrutiny.

The lawsuit is the Trump administration's latest challenge to state action on climate change.

Environmental and scientific groups can still access the underlying data and haven't shown an injury to sue over, the judge ruled.

The automotive package limits technological neutrality, while the Industrial Accelerator Act will hinder exports, CEO Oliver Zipse argues.

It's unclear if Sublime Systems can fulfill a deal with Microsoft to supply as much as 622,500 metric tons of cement over five to eight years.

The phenomenon is poised to add extra warmth to a planet that’s rapidly heating due to human-caused climate change.

Temperatures in Cape Town climbed to 108 degrees Fahrenheit on Wednesday, the highest since records began 66 years ago.

Nature Climate Change, Published online: 13 March 2026; doi:10.1038/s41558-026-02585-1

The massive carbon store in soils is vulnerable to anthropogenic warming. Now, a study shows that climate-driven changes in precipitation can mediate soil carbon responses to warming, with drought amplifying soil carbon losses.

Nature Climate Change, Published online: 13 March 2026; doi:10.1038/s41558-026-02583-3

Increasing risks of post-experimental ecology

Nature Climate Change, Published online: 13 March 2026; doi:10.1038/s41558-026-02580-6

Post-growth scholarship seeks to address the limitations of growth-oriented mitigation scenarios by exploring the potential of profound socio-economic transformations. This Perspective synthesizes core principles for modelling post-growth futures.

Nature Climate Change, Published online: 13 March 2026; doi:10.1038/s41558-026-02584-2

The response of soil carbon to warming is critical feedback that has been difficult to constrain. This study uses a long-term experiment to show that precipitation modulates microbial and therefore carbon dynamics; drought leads to carbon loss with warming, but wet conditions increase soil carbon.

Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient’s lungs, legs, feet, and other parts of the body. The condition is chronic and incurable, often leading to arrhythmias or sudden cardiac arrest. For many centuries, bloodletting and leeches were the treatment of choice, famously practiced by barber surgeons in Europe, during a time when physicians rarely operated on patients. 

In the 21st century, the management of heart failure has become decidedly less medieval: Today, patients undergo a combination of healthy lifestyle changes, prescription of medications, and sometimes use pacemakers. Yet heart failure remains one of the leading causes of morbidity and mortality, placing a substantial burden on health-care systems across the globe. 

“About half of the people diagnosed with heart failure will die within five years of diagnosis,” says Teya Bergamaschi, an MIT PhD student in the lab of Nina T. and Robert H. Rubin Professor Collin Stultz and the co-first author of a new paper introducing a deep learning model for predicting heart failure. “Understanding how a patient will fare after hospitalization is really important in allocating finite resources.”

The paper, published in Lancet eClinical Medicine by a team of researchers at MIT, Mass General Brigham, and Harvard Medical School, shares results from developing and testing PULSE-HF, which stands loosely for “Predict changes in left ventricULar Systolic function from ECGs of patients who have Heart Failure.” The project was conducted in Stultz’s lab, which is affiliated with the MIT Abdul Latif Jameel Clinic for Machine Learning in Health. Developed and retrospectively tested across three different patient cohorts from Massachusetts General Hospital, Brigham and Women’s Hospital, and MIMIC-IV (a publicly available dataset), the deep learning model accurately predicts changes in the left ventricular ejection fraction (LVEF), which is the percentage of blood being pumped out of the left ventricle of the heart.

A healthy human heart pumps out about 50 to 70 percent of blood from the left ventricle with each beat — anything less is considered a sign of a potential problem. “The model takes an [electrocardiogram] and outputs a prediction of whether or not there will be an ejection fraction within the next year that falls below 40 percent,” says Tiffany Yau, an MIT PhD student in Stultz’s lab who is also co-first author of the PULSE-HF paper. “That is the most severe subgroup of heart failure.” 

If PULSE-HF predicts that a patient’s ejection fraction is likely to worsen within a year, the clinician can prioritize the patient for follow-up. Subsequently, lower-risk patients can reduce their number of hospital visits and the amount of time spent getting 10 electrodes adhered to their body for a 12-lead ECG. The model can also be deployed in low-resource clinical settings, including doctors offices in rural areas that don’t typically have a cardiac sonographer employed to run ultrasounds on a daily basis.

“The biggest thing that distinguishes [PULSE-HF] from other heart failure ECG methods is instead of detection, it does forecasting,” says Yau. The paper notes that to date, no other methods exist for predicting future LVEF decline among patients with heart failure.

During the testing and validation process, the researchers used a metric known as "area under the receiver operating characteristic curve" (AUROC) to measure PULSE-HF’s performance. AUROC is typically used to measure a model’s ability to discriminate between classes on a scale from 0 to 1, with 0.5 being random and 1 being perfect. PULSE-HF achieved AUROCs ranging from 0.87 to 0.91 across all three patient cohorts.

Notably, the researchers also built a version of PULSE-HF for single-lead ECGs, meaning only one electrode needs to be placed on the body. While 12-lead ECGs are generally considered superior for being more comprehensive and accurate, the performance of the single-lead version of PULSE-HF was just as strong as the 12-lead version.

Despite the elegant simplicity behind the idea of PULSE-HF, like most clinical AI research, it belies a laborious execution. “It’s taken years [to complete this project],” Bergamaschi recalls. “It’s gone through many iterations.” 

One of the team’s biggest challenges was collecting, processing, and cleaning the ECG and echocardiogram datasets. While the model aims to forecast a patient’s ejection fraction, the labels for the training data weren’t always readily available. Much like a student learning from a textbook with an answer key, labeling is critical for helping machine-learning models correctly identify patterns in data.

Clean, linear text in the form of TXT files typically works best when training models. But echocardiogram files typically come in the form of PDFs, and when PDFs are converted to TXT files, the text (which gets broken up by line breaks and formatting) becomes difficult for the model to read. The unpredictable nature of real-life scenarios, like a restless patient or a loose lead, also marred the data. “There are a lot of signal artifacts that need to be cleaned,” Bergamaschi says. “It’s kind of a never-ending rabbit hole.”

While Bergamaschi and Yau acknowledge that more complicated methods could help filter the data for better signals, there is a limit to the usefulness of these approaches. “At what point do you stop?” Yau asks. “You have to think about the use case — is it easiest to have this model that works on data that is slightly messy? Because it probably will be.”

The researchers anticipate that the next step for PULSE-HF will be testing the model in a prospective study on real patients, whose future ejection fraction is unknown.

Despite the challenges inherent to bringing clinical AI tools like PULSE-HF over the finish line, including the possible risk of prolonging a PhD by another year, the students feel that the years of hard work were worthwhile. 

“I think things are rewarding partially because they’re challenging,” Bergamaschi says. “A friend said to me, ‘If you think you will find your calling after graduation, if your calling is truly calling, it will be there in the one additional year it takes you to graduate.’ … The way we’re measured as researchers in [the ML and health] space is different from other researchers in ML space. Everyone in this community understands the unique challenges that exist here.”

“There’s too much suffering in the world,” says Yau, who joined Stultz’s lab after a health event made her realize the importance of machine learning in health care. “Anything that tries to ease suffering is something that I would consider a valuable use of my time.” 

“It’s a real validation of all the work behind the scenes,” says Karl Berggren, faculty head of electrical engineering within the MIT Department of Electrical Engineering and Computer Science (EECS). He’s looking at the numbers of new enrollees in Course 6-5, Electrical Engineering With Computing, the flagship electrical engineering degree offered by EECS, which was launched last fall. 

The new major has been embraced by the MIT student community. “The fact that Course 6-5 is now the third-most selected major among first-year students shows that the department is clearly meeting a growing need for a curriculum that bridges electrical engineering and computing. This growth is coming from students already interested in pursuing a degree in EECS,” says Anantha Chandrakasan, MIT’s provost. “The major was thoughtfully designed to offer a strong foundation in core electrical engineering concepts — such as circuits, signals, systems, and architecture — while also providing well-structured specialization tracks that prepare students for the future of the field.”

Those tracks include structured paths to explore not only the traditional domains of electrical engineering (such as hardware design and energy systems), but cutting-edge fields such as nanoelectronics, quantum systems engineering, and photonics. 

“They are very flexible, and essentially allow me to take whatever I want, with the tracks filling up almost automatically,” says 6-5 major Charles Reischer. “For me, it essentially reduces the amount of specific required classes in the major, which has been helpful for choosing the classes I find interesting.” 

Jelena Notaros, who helped develop the Electromagnetics and Photonics track within the new major, has seen the new wave of student interest from the other side. “It’s been incredibly rewarding … I think students are excited to have the opportunity to take a class where they can learn about a cutting-edge field and test real state-of-the-art chip hardware using industry-standard equipment.” Notaros’s class, 6.2320  (Silicon Photonics), includes features not found in a university class anywhere else, such as a sequence in which students can test actual chips at three electronic-photonic probe stations. 

Another 6-5 track, Quantum Systems Engineering, features direct student access to quantum hardware, including electron-nuclear systems and state-of-the-art simulations methods and tools. Professor Dirk Englund, who teaches multiple courses within the track, explains, “it’s been so successful in part through strong industry support, including from QuTools Inc. Students work with the same tech we use in the Boston-Area Quantum Network Testbed — the metro quantum network linking MIT, Lincoln Lab, and Harvard, and the NSF CQN.” 

Many of Englund’s students have gone on to pursue a career in quantum information science, either in grad school or in industry. “Students recognize quantum engineering is the future. They see they’re building the foundation for metro-scale quantum networks.” 

The new curriculum’s emphasis on hands-on learning is deliberate, and ubiquitous throughout 6-5. Within the Circuits track, students who enroll in class 6.208 (Semiconductor Electronic Circuits) will get an opportunity not only to design a circuit, but to actually see their design made, in a process called “tape-out.” Professor Ruonan Han, who helped design the course, explains, “a tape-out is a perfect training that poses [real-life] constraints and forces the students to solve practical engineering problems. Through circuit simulation using mainstream industry CAD tools, the students better understand how deep-scaled transistors differ from the ideal behaviors taught in textbooks. By drawing the layouts of the silicon and metal patterns, the students learn how a modern chip is made, layer by layer. The complex (and often frustrating) rules of the layout also keep reminding the students of all the technical limitations during the chip manufacturing, and make them better appreciate all the accomplishments in semiconductor manufacturing. Even the firm and non-negotiable tape-out submission deadline forces the students to not only wisely manage their development timeline, but also to experience heart-beating moments when decisions on critical engineering trade-offs should be made (in order to deliver). To these students, it was such relentless efforts that gave them lots of satisfaction and pride when they finally hold their own chips in hand.” 

The sense of completing a full problem-solving cycle is echoed in class 6.900 (Engineering for Impact), a capstone course designed by Professor Joel Voldman, a former faculty head of electrical engineering, along with Senior Lecturer Joe Steinmeyer. Over the course of a semester, students team with city governments and nonprofits to solve complex local issues. The course is designed not only to introduce students to realistic project management factors (such as budgets, timelines, and stakeholders), but also to give them a taste of the satisfaction of engineering a solution that meets a real community’s need. 

“I’ve taken 6.900, and it’s been eye-opening in the collaboration of hardware, firmware, and software to create a cohesive and working product,” says Andrea Leang, a senior majoring in 6-2 who nonetheless decided to try the new course. “In my 6-2 experience, I spent the first two years taking more CS [computer science] classes, but as I went into junior year, I wanted to explore more EE [electrical engineering].” That desire led Leang to Voltage, the student group for electrical engineers. “Honestly, it was the first big community of EE I’ve joined. Joining Voltage opened my eyes to what MIT had to offer on EE, and a community who was enthusiastic to share their knowledge.” 

Matthew Kim, one of the executives of the Voltage group, echoes Leang’s experience. “​​It has been great working [...] to build a community for EE. We heard faculty say that they wanted to be more engaged with students and communicate more, and it has definitely been felt with the restart and support of Voltage. And I’m hopeful that the community will continue to grow.” 

That growth has been rapid. The new major’s enrollment is now roughly equivalent to the combined enrollment in the older 6-1 and 6-2 programs, showing the desirability of a major that incorporates fundamentals of both computing and electrical engineering. 

Department head Professor Asu Ozdaglar is thrilled with the energizing effect of the new major. “We are delighted to see the initial success of the 6-5 major, which provides our students an exciting and forward-looking curriculum, developed through extensive work and great deal of thought by electrical engineering faculty. The new curriculum reflects the critical role computing plays in electrical engineering, whether in designing new devices and circuits, analyzing data, or in studying complex systems, which almost invariably combine hardware and software."

“What excites me most about this major is how it empowers students to bring ideas to life — from the invisible signals that connect our world to the complex systems that drive modern technology,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Warren Professor of Electrical Engineering and Computer Science. “Students are using computation as a creative and analytical tool to expand the boundaries of engineering. They gain a deep understanding of how hardware and software come together to drive technological progress.” 

The new degree program’s designers are gratified by the swell of student interest. 

“The buzz surrounding the classes and the new 6-5 degree program is fantastic,” says Voldman. “It’s great to see the strong student interest in what we’ve put together.” 

Apple announcement:

…iPhone and iPad are the first and only consumer devices in compliance with the information assurance requirements of NATO nations. This enables iPhone and iPad to be used with classified information up to the NATO restricted level without requiring special software or settings—a level of government certification no other consumer mobile device has met.

This is out of the box, no modifications required.

Boing Boing post.