MIT engineers have developed a new way to amplify the T-cell response to mRNA vaccines — an advance that could lead to much more powerful cancer vaccines and stronger protection against infectious diseases.

Most vaccines generate both antibodies and T cells that can target the vaccine antigen by activating antigen-presenting cells, such as dendritic cells. In this study, the researchers boosted the T-cell response with a new type of vaccine adjuvant (a material that can help stimulate the immune system). The new adjuvant consists of mRNA molecules encoding genes that turn on immune signaling pathways and promote a supercharged T-cell response. 

In studies in mice, this mRNA-encoded adjuvant enabled the immune system to completely eradicate most tumors, either on its own or delivered along with a tumor antigen. The adjuvant also boosted the T-cell response to vaccines against influenza and Covid-19.

“When these adjuvant mRNAs are included in the vaccines, the number of antigen-targeted T cells is substantially increased. These T cells play an important role in the immune response, assisting in the clearance of virally infected cells or, in the case of cancer, killing cancerous cells,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.

Anderson and Christopher Garris, an assistant professor at Harvard Medical School and Massachusetts General Hospital, are the senior authors of the study, which appears today in Nature Biotechnology. The paper’s lead authors are Akash Gupta, a former Koch Institute research scientist who is now an assistant professor at the University of Houston; Kaelan Reed, an MIT graduate student; and Riddha Das, a research fellow at Harvard Medical School and MGH. Robert Langer, the David H. Koch Institute Professor at MIT, and Ralph Weissleder, a professor of radiology and systems biology at MGH and Harvard Medical School, are also authors.

More powerful vaccines

Vaccines that stimulate the body’s immune system to attack tumors have shown promise in clinical trials, and a handful have been FDA-approved for certain cancers. In some patients, these vaccines stimulate a strong response, but in others, a weak response fails to kill the cancerous cells.

The MIT-MGH team wanted to find a way to make those immune responses more powerful. One way to do that is to deliver immune-stimulating molecules called cytokines along with a vaccine. However, cytokines can overstimulate the immune system, leading to potentially severe side effects.

As an alternative approach, the researchers decided to deliver mRNA strands encoding two genes, IRF8 and NIK, which are involved in antigen presentation and can switch immune cells into a more active state.

NIK is an enzyme that activates a signaling pathway involved in immunity and inflammation, while IRF8 is a transcription factor that helps program dendritic cells, particularly a subset called cDC1, which are especially effective at activating T cells. These antigen-presenting cells can digest foreign antigens and present them to T cells, stimulating the T cells to mount an immune response against the antigen.

“We see that the dendritic cells start shifting toward a more cDC1 phenotype, which is the most important dendritic cell phenotype and can generate a stronger T-cell response,” Gupta says. 

The researchers packaged the mRNA in lipid nanoparticles similar to those used to deliver mRNA Covid vaccines, but with a different chemical composition that promotes their delivery to the spleen after being injected intravenously. 

Inside the spleen, the particles encounter antigen-presenting cells, including dendritic cells. Within 24 hours, these cells begin expressing IRF8 and NIK, and both of these pathways help drive dendritic cells to mature and become activated so that they can prime an anti-tumor response. 

Over a few days to a week, the T-cell population expands. These T cells, along with other immune cells such as natural killer (NK) cells, can then recognize and attack tumors.

“Most cancer immunotherapies rely on external signals to activate immune cells. We take a different approach — reprogramming immune cells from within by targeting their internal signaling machinery, enabling a more potent and durable anti-tumor response,” Das says. 

Stronger T cells

The researchers tested the immune-remodeling mRNAs in several mouse models of cancer, including an aggressive bladder cancer, colon carcinoma, melanoma, and metastatic lung cancer. In nearly all of these mice, the injected mRNA stimulated a strong T-cell response that significantly slowed tumor growth and in many cases completely eradicated the tumors. This happened even when the mice were not given a vaccine against a specific cancer antigen. When they were, the response was even stronger.

“We showed that you can get an anti-cancer response with these adjuvants without including the antigen, just by activating the immune system. However, cancer-specific antigens with the adjuvants in a vaccine further improved the responses,” Anderson says.

The mRNA adjuvant also enhanced the immune response to immunotherapy drugs called checkpoint blockade inhibitors. These drugs, which work by lifting a brake that tumor cells put on T cells, are FDA-approved to treat several kinds of cancer. These drugs don’t work for all patients, but combining them with the mRNA vaccine adjuvant could offer a way to make them more effective, the researchers say.

“The microenvironment of solid tumors is often hostile to T cells and represents a major barrier to effective immunotherapy. We find that immune remodeling with these adjuvants creates a T cell–permissive environment and promotes tumor rejection,” Garris says.

The researchers also explored whether their new adjuvant could boost the immune response to vaccination against viral infection. When they delivered the mRNA particles along with Covid or flu vaccines, they found that the vaccine generated a 10-to-15-fold stronger T cell response in the mice.

The researchers now plan to test this approach in additional animal models, in hopes of developing it for use in both cancer and infectious diseases. 

“While there are differences between the mouse systems that we’ve worked in and humans, we are optimistic that these adjuvants will work in humans and could improve a range of different vaccines,” Anderson says.

The research was funded by Sanofi, the National Institutes of Health, the Marble Center for Cancer Nanomedicine, and the Koch Institute Support (core) Grant from the National Cancer Institute.

On April 28, 2025, the power grid serving continental Spain and Portugal went down, causing gridlock in cities, cutting communications networks, and stranding people on trains, in airports, and in elevators all across the Iberian peninsula and briefly in a small area in southwest France close to the Spanish border. The unprecedented, massive blackout lasted as long as 12 hours in some areas, including in the capital city, Madrid. Not surprisingly, placing blame for the outage was rapid. Quick reactions pointed to cyberattack, sabotage, and natural phenomena such as solar flares. 

But such theories were quickly laid to rest, and a panel of experts was formed to determine exactly what caused the blackout. After a year following the outage — and after much analysis by many experts — there isn’t a simple answer: In short, no one technology was to blame. While solar and wind generation was high, experts agree that the renewables weren’t at fault. 

In this Q&A, Pablo Duenas-Martinez, a research scientist at the MIT Energy Initiative and an assistant professor at Universidad Pontificia Comillas in Madrid, provides an update.

Q: How does a proper, well-functioning power grid behave, and what does the system operator do to help?

A: There are two components to the flows on a power grid. One is “active power” — the part that lights up our light bulbs and runs our engines. With active power, the demand on the grid must always equal supply. The other component is “reactive power,” the part we can’t see but controls the voltage at which the power is delivered so it suits our devices. If voltage is too low, lights will flicker. If voltage is too high, devices may not only fail to work, but be damaged beyond repair.

The operator of the transmission system — the TSO — must control both components, and that can be tricky. Active power supply and demand are largely coordinated through markets. But controlling reactive power is harder. The main way the TSO can control it is to call on operators of conventional power generators, so generators burning natural gas, or coal, or nuclear plants. Those systems can be adjusted to either absorb or inject reactive power as needed to control voltage on the power grid — indeed, they are typically required by law to provide “reactive power control.”

In contrast, solar and wind generators always absorb reactive power. The large solar and wind sources can provide reactive power control when it’s needed, but doing so is costly for them — and in Spain, unlike in most countries, it’s not mandated by law, so they typically don’t do it. Meanwhile, there are many small solar systems — imagine lots of rooftop solar installations and small solar farms. Those small systems are directly connected to the distribution system. As a result, they’re not controlled by the TSO; the TSO may not even know whether they’ve shut down or are still running and absorbing reactive power.

Sometimes, fluctuations in voltage called “oscillations” can happen on a power grid: for example, when a transmission line or a generator is connected or disconnected. Oscillations can increase and decrease the voltage rapidly, and if voltage gets too high, generators and user devices can start “tripping” — that is, automatically disconnecting to prevent being damaged. Operators have standard protocols to follow to bring oscillations under control.

Q: So what happened on April 28 of last year?

A: The Spanish grid is loosely connected to the French grid and in practice is merged with the grid serving Portugal. Within Spain, we have many large solar and wind farms and lots of small installations of solar systems, many located in the southwestern area of the country. On April 28 — as on most spring days, when demand is low — about two-thirds of the power on the grid came from renewable sources. The rest came from a mix of nuclear and natural gas plants.

The day before the blackout, the TSO confirmed that there were no conventional generators scheduled to run. So, to ensure safe operation the next day, the TSO took steps that included dispatching 12 conventional generators, 10 of them to provide reactive power control. One of the units in the south called him back and said, “I won’t be available. I cannot switch on tomorrow.” The TSO thought he had things under control and continued operations with only nine units available to provide reactive power control.

During the morning on April 28, several small oscillations on the power grid were detected coming from Europe, plus one from Spain. To stabilize the weakened grid, the TSO connected additional transmission lines and took other technical actions.

At 12:19 p.m., a major oscillation was detected on the grid, again coming from Europe. In response, the TSO — again following standard protocol — reduced exports to Portugal, switched the flows to France from alternating current to direct current, and connected five more transmission lines within Spain. While those steps stabilized the voltage, the TSO recognized that there was now limited capacity on the system to control voltage. So, he called on a different conventional generator to begin running. But that unit couldn’t be available for an hour.

Suddenly, as a consequence of the previous actions, the voltage increased dramatically, and generating units began to trip. Within half-a-second, many of the small solar generators — especially prone to damage from high voltages — automatically shut down. Twenty milliseconds later, a big solar plant in southwestern Spain tripped. Because the solar plants were no longer absorbing reactive power, voltage on the system went up even more, and more systems shut down. The grid went into what some have called a death spiral, resulting in a total blackout across the Iberian peninsula and some areas of southern France.

Q: What have we learned from this Iberian blackout, and have changes been implemented to ensure that the same won’t happen again — or happen elsewhere?

A: A resilient power system must prevent, mitigate, respond, and recover. In this case, the first three components clearly failed. Preventive mechanisms were insufficient; they initially mitigated the oscillatory events, but left the system in a weakened state, and the response triggered the death spiral that led to the final blackout.

The good news is that the recovery was quick. The northern and southern sections of the peninsula had power back within a few hours. I live in the suburbs of Madrid, and I had power back just six hours later. My parents live downtown, so that was far more challenging — a big city with a large, complex load. Even so, they had power back in 12 hours — and 12 hours is quick for such a major, widespread blackout.

In the end, experts and analysts have agreed that the blackout was caused by a series of events that were all happening in the same place, at the same time. And the experience did provide a number of valuable learnings:

Lesson 1

The experience clearly demonstrated the importance of having a sufficient number of conventional power plants prepared to provide reactive power control, or to turn on right away when called on. There’s a recommendation calling for a set ratio between conventional generators and renewables on a power grid. Conventional facilities such as nuclear, hydroelectric, and fossil fuel plants rely on heavy metal wheels to generate electricity. Those massive rotating wheels have high inertia, so they’ll keep running and can help stabilize frequency and voltage even when solar and wind plants shut down. Before the blackout, Spain had a sufficient number of “rotating units” to meet the recommended ratio. However, in southern Spain, there was just one such unit — well below the recommended number, given the huge number of small solar units plus several large solar units in the area.

The message here is that you can't just look at the country as a whole. You have to look at regions. Voltage is a local problem that can propagate at the system level. Before the blackout, southern Spain typically had at most three conventional power plants. Now the region usually has six or seven at the ready to help with reactive power control.

Lesson 2

The rules or protocols for controlling reactive power and dealing with oscillations were not well designed. By law, rotating generators must automatically — and without being paid — do a defined amount of reactive power control. But making the needed operational change costs money, and a plant can do less than the required amount and not incur any kind of penalty. However, the TSO doesn’t know in advance how much reactive power control a given plant will actually do. Now that loophole in the law has been reviewed by the regulator.

The main rules have been updated, and now also require large solar and wind power plants — those above 5 megawatts — to provide reactive power control. More importantly, voltage control will be auctioned and remunerated, incentivizing rotating conventional generators and bringing in a new money stream for solar and wind power plants. Those power plants that do not upgrade their installation for voltage control might be disconnected by the TSO if local voltage issues arise.

Lesson 3

Another learning concerns the many small solar power generators and the protections that cause them to trip. The TSO doesn’t know in advance when this may happen because the small solar sources are directly connected to the distribution system, and therefore are under the umbrella of the distribution system operator. So, the learning here is that there should be more communication and coordination between the operator of the transmission system — the TSO — and the operator of the distribution system.

Lesson 4

In most countries, laws dictate a range of voltage that is approved. In Spain, the upper limit is high — in fact, it’s very near a voltage at which equipment may be damaged. And the Spanish grid tends to hover close to that upper limit, even during normal operation, and that can be a big problem: If there are strong oscillations — as there were leading up to the blackout — voltage can reach that upper limit, and protections on devices will automatically trip. The panel of experts has strongly recommended to lower this upper limit in Spain and align it with the rules in neighboring countries, including Portugal and France. The TSO is still studying the recommended change.

Lesson 5

During normal operation, the TSO controls voltage by activating rotating generators that can provide reactive power control. But as we saw in conditions leading up to the blackout, the TSO doesn’t always have rotating generators available.

Theoretically, TSOs have two more ways to control voltage. They can connect a device called a shunt reactor, which absorbs reactive power — a means of dealing with voltage rise. And they can regulate voltage directly using a “STATCOM,” a special device that provides rapid, dynamic voltage control.

However, neither the shunt reactors nor the STATCOM could help prevent the blackout. The shunt reactors available at that time were operated manually, and collapse of the grid happened so quickly that the TSO didn’t have time to connect them. And at that time, there was a single STATCOM device on the Spanish system. Planning was under way to install three more devices — and that installation is being rapidly completed.

From newspaper articles and off-the-record conversations, I’ve learned that the system has — due to similar external circumstances — been close to blackout again during the past year. But in part due to the learnings and to changes that have been implemented as a result, it didn’t happen again.

The hallowed history of student pranks (often known as hacks) at MIT includes the annual Baker House Piano Drop and the MIT weather balloon at the Harvard-Yale football game in 1982. One hack that has shown remarkable staying power in local lore is the 1958 measurement of the Massachusetts Ave. Bridge in “smoots,” a now accepted unit of meausrement named for the 5-foot, 7-inch Oliver R. Smoot Jr. ’62. Then a first-year pledge at the Lambda Chi Alpha fraternity, Smoot famously laid down hundreds of times across the span one storied night as his peers painted markers across the bridge, totaling 364.4 smoots (plus 1 ear). Nearly 70 years later, the smoot markings remain.

On April 4, an MIT team set out on a similar journey across the Charles River to pull off a new hack, this time measuring the Longfellow Bridge in “kleins.” This new measurement is named after Smoot’s classmate Martin Klein ’62. One klein (4 feet, 9.5 inches) is equal to 0.85820896 smoots. The expedition was undertaken in honor of both Smoot and the 85th birthday of Klein.

Known as the father of commercial side-scan sonar, Martin Klein serves on the MIT Sea Grant Advisory Board and the MIT Museum Collections Committee. He is a life fellow of both the Marine Technology Society and the Explorers Club, an international organization dedicated to the advancement of field exploration and scientific inquiry. His sonar technology has been used worldwide to help locate countless famous shipwrecks, including the Titanic, the World War I ocean liner RMS Lusitania, and the treasure-laden Nuestra Señora de Atocha.

Appropriately, the MIT team used a “side-scan” method to survey the Longfellow Bridge. Reclined on a custom-engineered wooden cart topped with a mission-specific chaise lounge pillow, Klein himself acted as the official observation device — by looking to the sides — as the team pulled him along the bridge. Some of the noted anomalies and discoveries included a Duck Boat passing underneath, a mermaid tail, a kayak paddle, a sleeping goose, and a tenacious survey team.

The initiative was spearheaded by Makenna Reilly, a second-year undergraduate in mechanical engineering, and Andrew Bennett ’85, PhD ’97, MIT Sea Grant education administrator and senior lecturer in the Department of Mechanical Engineering (MechE). Over a dozen surveyors joined the expedition, including alumni, faculty, and staff from MechE, MIT Sea Grant, MIT Edgerton Center, MIT Museum Hart Nautical Collections, Harvard Extension School, and Woods Hole Oceanographic Institution. MIT students also joined the effort, including senior Teagan Sullivan, junior Adrienne Lai, and graduate students Ansel Garcia-Langley, Erin Menezes, Manuel Valencia, and Gerardo Berlanga Molina.

The Longfellow Bridge was determined to be 442 kleins (plus 2 legs) and was celebrated as the “Shortfellow Bridge” in a ceremony following the event. 

One klein = 57.5 inches = 146.05 centimeters = 1.4605 meters = .0009075126 miles = 1.597222 yards = 4.791667 feet = .0007886069 nautical miles = .007260087 furlongs = 0.7986111 fathoms = 172.5 barleycorns = 292,100,000 beard seconds = 647.4421 Ligne = 14.375 horse hands = 4.819655 shaku = .85820896 smoots.

Additional participants in the event include:

• Elisabeth (Libby) Meier, assistant curator for the Hart Nautical Collections at the MIT Museum;
• Dana Yoerger, PhD ’82, senior scientist applied ocean physics and engineering at WHOI;
• Professor George Buckley, assistant director of sustainability at Harvard University Extension School and diver of the year of the Boston Sea Rovers;
• Paul K. Matthias, senior program manager of the Ocean Observatories Initiative at the WHOI;
• Jim Bales, associate director of the Edgerton Center at MIT;
• John Freidah of MechE; and
• Joice Himawan ’83.

Dark matter is thought to make up most of the matter in the universe, but the only way it interacts with its surroundings is through gravity. If two colliding black holes spiral through a dense region of dark matter and merge, gravitational waves rippling across space and time could carry an imprint of that dark matter.

Now, physicists may be able to spot such imprints of dark matter in gravitational waves that are detected on Earth. 

Researchers at MIT and in Europe have developed a method that makes predictions for what a gravitational wave should look like if it were produced by black holes that moved through dark matter, rather than empty space. They applied the technique to publicly available gravitational-wave data previously recorded by LIGO-Virgo-KAGRA (LVK), the global network of observatories that detect gravitational waves from black hole mergers and other far-off astrophysical sources.

The researchers looked through the gravitational-wave signals recorded over the LVK’s first three observing runs. From 28 of the clearest signals, the team found that 27 originated from black holes that merged in a vacuum, as physicists expected. But the pattern of one signal, GW190728, showed possible signs of a dark matter imprint. 

The scientists emphasize that they have not detected dark matter. Rather, the new method offers a new way to screen gravitational-wave data for hints of dark matter, which physicists can then follow up and confirm with other techniques. 

“We know that dark matter is around us. It just has to be dense enough for us to see its effects,” says Josu Aurrekoetxea, a postdoc in the MIT Department of Physics. “Black holes provide a mechanism to enhance this density, which we can now search for by analyzing the gravitational waves emitted when they merge.”

Aurrekoetxea and his colleagues report their results in a study appearing today in Physical Review Letters. The study’s co-authors are LVK member Soumen Roy of Université Catholique de Louvain (UCLouvain) in Belgium, Rodrigo Vicente of the University of Amsterdam, Katy Clough of Queen Mary University of London, and Pedro Ferreira of Oxford University. 

A dark pull

Dark matter is an invisible, hypothetical form of matter that, unlike normal everyday matter, has no interactions with the electromagnetic force. Dark matter can pass through light, magnetic fields, and any other form of energy along the electromagnetic spectrum without leaving a trace. The only evidence that dark matter exists is through its apparent interaction with one other force: gravity. 

By observing how gravity bends around distant galaxies, astronomers have surmised that there must be an extra force, outside of the galaxies’ own gravitational pull, to explain the bending fields, or “lensing.” This extra force, physicists suspect, is dark matter, which could account for over 85 percent of the matter in the universe. But exactly what dark matter is is a matter of huge debate, with theories for dark matter particles that range widely in particle size and properties. 

One class of proposed dark matter consists of “light scalar” particles, whose masses are many orders of magnitude lighter than an electron. Theorists predict that such dark matter should behave not just as particles, but also as coordinated waves when moving near black holes.

When waves of dark matter come in contact with a rapidly spinning black hole, physicists predict that the black hole's rotational energy can be transferred to the dark matter, amplifying it. This phenomenon, known as superradiance, would whip up the waves to extremely high densities of dark matter, akin to churning cream into butter.

At high enough densities, light scalar dark matter, which is invisible by all other accounts, should leave an imprint on the gravitational waves that reverberate from the colliding black holes. 

But exactly what would that imprint look like? And could such an imprint be detectable in gravitational waves that arrive on Earth, from black holes that merged many millions of light years away? 

For answers to those questions, Aurrekoetxea and his colleagues developed a model to predict the gravitational waveform, or the pattern of gravitational waves that two black holes would produce, if they collided in an environment of dark matter, versus in a vacuum (empty space, with no dark matter). 

An imprint’s prediction

For their new study, the team performed detailed numerical simulations to predict the gravitational wave that would be produced given various properties of two colliding black holes — a system known as a “black hole binary.” They considered black hole binaries across a range of scenarios and properties, for example, varying the size and mass of each black hole, the environment of dark matter that the black holes might pass through, and the density of the dark matter that the black holes would spin up. 

They designed the model to predict what a gravitational wave from a black hole binary would look like if it carried an imprint of dark matter, and furthermore, what that wave would look like if it traveled a given distance across space and time, to eventually arrive at a detector on Earth.

With their model, they looked to see whether any gravitational-wave signals that have been detected on Earth match their predicted patterns of dark matter imprints. To do so, they applied the model to publicly-available data recorded by LVK over the observatories’ first three observing runs. The observatories have picked up hundreds of gravitational-wave signals during this period. For their purposes, the researchers focused on the clearest signals, comprising gravitational waves from 28 separate events. 

For each event, the team compared the pattern of the actual gravitational wave against their model of what the signal would look like if it were generated by the same event in an environment of dark matter. They also compared the gravitational wave to the more expected scenario in which the signal was produced in a vacuum. 

Of the 28 clearest signals that they analyzed, 27 were solidly within the predictions for having been produced in a vacuum. However, the pattern of one event, GW190728, showed a “preference,” or an agreement with the team’s dark matter model. In other words, the signal may carry an imprint of dark matter. 

GW190728 is a gravitational wave that is named after the date that it was detected — on July 28, 2019. Scientists previously determined that the gravitational wave originated from a black hole binary with a total mass of about 20 times the mass of the sun. With their model, the team showed that such a system could have merged through a dense cloud of dark matter and produced a similar gravitational wave to GW190728. 

“The statistical significance of this is not high enough to claim a detection of dark matter, and further checks should be performed by independent groups,” Aurrekoetxea says. “What we think is important to highlight is that without waveform models like ours, we could be detecting black hole mergers in dark matter environments, but systematically classifying them as having occurred in vacuum.”

“We now have the potential to discover dark matter around black holes as the LVK detectors keep collecting data in the coming years,” says co-author Soumen Roy, who led the data analysis part of the work. “It is an exciting time to search for new physics using gravitational waves.”

“Using black holes to look for dark matter would be fantastic,” adds co-author Rodrigo Vicente, who developed the analytical model of the signal. “We would be able to probe dark matter at scales much smaller than ever before.”

This work was supported, in part, by the U.S. National Science Foundation and MIT’s Center for Theoretical Physics — a Leinweber Institute.

Using a new technique that can create vacancies at any site across a material and then shrink it to about 1/2,000 of its original volume, MIT researchers have designed nanotechnology devices that could be used for optical computing and other applications involving the manipulation of visible light.

The new fabrication technique, known as “implosion carving,” allows researchers to imprint features throughout a hydrogel using photopatterning. If patterned with a resolution of about 800 nanometers, these features can then be shrunk to less than 100 nanometers. 

Because that resolution is smaller than the wavelength of light, the devices can bend light in specific ways that allow them to perform optical computations.

“In order to enable nanophotonic applications in visible light, we need to make nanostructures with feature sizes with a resolution less than 100 nanometers. Only in that way can we precisely create the structure that can manipulate visible light,” says Quansan Yang, a former MIT postdoc, now an assistant professor at the University of Washington, and one of the lead authors of the new study.

In their paper, the researchers demonstrated a photonic device that can perform a simple digit-classification task, but future versions could be used for high-speed imaging and information processing, they say.

Gaojie Yang, a former MIT postdoc, is the co-lead author of the paper, which appears today in Nature Photonics. The paper’s senior authors are Peter So, director of the MIT Laser Biomedical Research Center (LBCR) and an MIT professor of biological engineering and mechanical engineering, and Edward Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT and a professor of biological engineering, media arts and sciences, and brain and cognitive sciences. Boyden is also a Howard Hughes Medical Institute investigator and a member of MIT’s McGovern Institute for Brain Research, the Yang Tan Collective, and Koch Institute for Integrative Cancer Research.

Nanoscale feature sizes

Photonic devices, which transmit and manipulate light, hold potential for use as optical computer chips that could offer an energy-efficient alternative to semiconductor chips. However, existing techniques for creating 3D photonic devices haven’t yet achieved the 100-nanometer resolution that is needed to channel visible light, which has wavelengths between 380 and 750 nanometers.

Using an additive manufacturing technique called two-photon lithography, researchers can use light to create 3D nanoscale features, but with a resolution larger than 100 nanometers. Another technique, known as electron-beam lithography, can be used to etch smaller-resolution features onto a silicon chip, but it doesn’t generate 3D structures. 

To make 3D devices with the necessary feature size, the researchers extended the concept of “implosion fabrication,” which Boyden’s lab developed in 2018, to create a new variant called “implosion carving.” In implosion carving, a laser creates vacancies — tiny voids where the hydrogel material has been removed — at precisely targeted locations. These vacancies exhibit different optical properties than the surrounding hydrogel. The hydrogel is then shrunk to bring the patterned features down to the nanoscale.

The carving process begins with immersing the hydrogel in a photosensitizing dye. Then, the researchers use a laser to excite the photosensitizer at specific places in the gel, which in turn generates reactive oxygen species that cut the bonds holding the hydrogel together. This creates a vacancy in that spot.

Once the desired vacancy pattern has been carved into the hydrogel, the researchers shrink it using a two-step process. First, they soak it in a solution containing ions, which causes it to shrink about tenfold in each dimension. To shrink it a little more, and to remove the watery solution, the hydrogel then undergoes a process called supercritical drying, which can remove liquid from a gel without damaging it.

At the end of the process, the hydrogel has been shrunk more than tenfold in each dimension, leading to a 2,000-fold reduction in volume. 

Computing with light

To demonstrate the versatility of this technique, the researchers used it to create several 3D shapes, including a helix and a structure inspired by a butterfly wing. Some of these structures are too thin, and have too high an aspect ratio, to be stably created using conventional two-photon lithography.

The researchers also created a device that could perform a simple calculation known as digit classification, a task that is traditionally used to test the performance of neural networks. During this task, the device was presented with a digit, such as 1 or 5, and had to light up a specific location to indicate which number was detected.

To achieve this, the researchers patterned vacancies throughout the device so that it would act like a neural network. The pattern of vacancies would diffract input light as it passed through many layers of patterned hydrogel, so that the output light was determined by the shape of the digit that was entered into the system.

“This is a purely optical system that effectively performs optical computing,” So says. 

“One of the very attractive features of this technology is that you can manipulate the property of the material at every tiny location,” says Dushan Wadduwage, an assistant professor at Old Dominion University and former MIT postdoc, who is also an author of the paper. “You have millions of different locations that you need to decide the property of, and that turns into a really interesting design problem where we can use deep-learning algorithms to find designs over these millions of parameters and come up with parts that go into optical systems in new ways.”

The researchers now plan to use the same principles to build optical devices that could classify cells based on their state as they flow through a microfluidic device. This could help identify rare cells such as circulating tumor cells in a blood sample, they say. 

This approach could also enable the creation of high-throughput imaging techniques for applications such as analyzing tissue samples from biopsies or surgical specimens. And, if adapted to work with other materials such as hydrophobic polymers, it could also be used to create channels within 3D nanofluidic devices. 

Other authors of the paper include Gaojie Yang, Takahiro Nambara, Hiroyuki Kusaka, Yuichiro Kunai, Alex Matlock, Corban Swain, Brett Pryor, Yannick Salamin, Daniel Oran, Hasindu Kariyawasam, Ramith Hettiarachchi, and Marin Soljacic. 

The research was funded, in part, by the MIT-Fujikura Partnership Fund, the U.S. Army Research Office through the Institute for Soldier Nanotechnologies at MIT, Lisa Yang and Y. Eva Tan, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the U.S. National Institutes of Health.

Quantum computers could someday solve pressing problems that are too convoluted for classical computers, such as modeling complex molecular interactions to streamline drug discovery and materials development. 

But to build a superconducting quantum computer that is large and resilient enough for real-world applications, scientists must precisely engineer thousands of quantum circuits so they perform operations with the lowest possible error rate.

To help scientists design more predictable circuits, researchers from MIT and Lincoln Laboratory developed a technique to measure a property that can unexpectedly cause a superconducting quantum circuit to deviate from its expected behavior. Their analysis revealed the source of these distortions, known as second-order harmonic corrections, leading to underperforming circuit architectures.

The MIT researchers fabricated a device to detect second-order harmonic corrections, identify their origin, and precisely measure their strength. This technique could help scientists deliberately design quantum circuits that can counteract the effects of these deviations.

This is especially important in larger and more complicated quantum circuits, where the negative impact of second-order harmonic corrections can be amplified. 

“As we make our quantum computers bigger and we want to have more precise control over the parameters of these devices, identifying and measuring these effects is going to be important for us to have a precise understanding of how these systems are constructed. It is always important to keep diving down into the circuit to see if there is an effect you didn’t expect, which impacts how your device is performing,” says Max Hays, a research scientist in the Engineering Quantum Systems (EQuS) group of the Research Laboratory of Electronics (RLE) and co-lead author of a paper on this research.

Hays is joined on the paper by co-lead author Junghyun Kim, an electrical engineering and computer science (EECS) graduate student in the EQuS group; senior author William D. Oliver, the Henry Ellis Warren (1894) Professor of EECS and professor of physics, leader of the EQuS group, director of the Center for Quantum Engineering, and associate director of RLE; as well as others at MIT and Lincoln Laboratory. The research appears today in Nature Physics.

A pair-wise problem

In a quantum computer that utilizes superconducting circuits, which is one of many potential computing platforms, Josephson junctions are critical elements that enable the transfer and manipulation of information. These devices utilize two superconducting wires that are brought very close together, with a nanometer-scale barrier between them. Like a traditional circuit, the electric charge in Josephson junctions is carried by electrons. 

But in a superconducting circuit, charge-carrying electrons pair up, forming what are called Cooper pairs. These Cooper pairs can “quantum tunnel” through the barrier between the two wires, transporting current from one wire to the other.

Cooper pairs can usually only tunnel one pair at a time, which is a key property that makes quantum computation possible. 

“If you try to force more Cooper pairs through, it just doesn’t work. This non-linear effect is extremely important for all our circuits. If we didn’t have that effect, then we wouldn’t be able to control or manipulate any quantum information that we store in these circuits,” Hays explains.

But sometimes, Cooper pairs can unexpectedly squeeze through the barrier two at a time, an effect that is known as a second-order harmonic correction. This effect limits the performance of a quantum circuit that has been configured to only allow single-pair tunneling.

“If two Cooper pairs tunnel at the same time, then the assumption we used to build our circuit doesn’t apply anymore. We need to fix the circuit so it can handle that,” Kim says.

But before they can fix the circuit, scientists need to know the source and strength of these distortions.

To obtain this information, the MIT researchers fabricated a quantum circuit so it would be very sensitive to these effects. Essentially, the device is designed to suppress the quantum tunneling process of single Cooper pairs, while allowing the two-pair tunneling process to continue. 

In this way, they can detect the presence of second-order harmonic corrections and precisely measure their strength. 

Straight to the source

They can also use this circuit to pinpoint the source of these harmonics, which helps researchers identify the best way to correct for them. 

There are two potential sources of second-order harmonics — one source is intrinsic to the dynamics of the Josephson junction and the other is caused by the wires connecting the junction to other circuit elements. 

While prior research had indicated the second-order harmonics could be due to the dynamics of the junction, the MIT researchers found that additional inductance — the tendency to oppose changes in the flow of electric current —from wires in the circuit was the actual source in their devices. 

“This is important because, if we know where the second-order harmonic correction is coming from, we can predict how strong it is likely to be, and use that information to engineer more predictable circuits that will hopefully perform better,” Hays says.

In the future, the researchers want to design experiments that more accurately predict how a device will perform when second-order harmonic corrections occur. They also want to study other sources of second-order harmonic corrections and whether those sources could have negative impacts on a circuit under different fabrication conditions.

This work is funded, in part, by the U.S. Department of Energy, the U.S. Co-design Center for Quantum Advantage, the U.S. Air Force, the Korea Foundation for Advanced Studies, and the Intelligence Community Postdoctoral Research Fellowship Program at MIT. 

Despite regional variability in climate, electricity sources, congestion, and the wide variation in individual driving patterns, electric vehicles generate less greenhouse gas emissions and do not cost more than comparable gas-powered vehicles for drivers and vehicle fleet owners in most parts of the United States, according to a new study by MIT researchers.

The team’s approach captures many key factors that contribute to regional and individual differences in the life-cycle emissions and ownership cost of electric vehicles, including meteorological data, the distance and duration of trips, and fuel prices.

To paint a fuller picture of emissions and costs than was previously available, the researchers sourced data from thousands of U.S. zip codes and drilled down to the level of individual drivers within those locations. Their study considers time-averaged fuel prices so as not to be overly influenced by fluctuations in prices at any one point in time. They finalized their analysis at the end of 2024 and early 2025.

Their results indicate that a person’s driving behaviors can matter as much as regional factors like the local electricity mix when it comes to the emissions savings of an electric vehicle, compared to a similar gas-powered vehicle. In most locations, a battery-electric vehicle reduces emissions between 40 and 60 percent, with larger impacts in urban areas. 

They also found that colder climates do not reduce overall emission benefits as much as some media reports assume.

The researchers utilized this detailed analysis to update a public tool they previously developed, carboncounter.com, which enables individuals to compare the life-cycle emissions and total ownership costs of nearly any car on the market. A new version of carboncounter.com is also being released today.

“There are a lot of statements being thrown around, like that electric vehicles don’t reduce emissions very much in cool climates, and we wanted to analyze these factors systematically and evaluate these statements against one another simultaneously. Rather than simply asking, ‘Are EVs better?’, this paper helps answer ‘better for whom, and under what conditions?’” says Marco Miotti PhD ’20, a senior researcher at ETH Zurich who completed this research while a graduate student in the Institute for Data, Systems, and Society (IDSS) at MIT. 

He is joined on the paper by senior author Jessika Trancik, a professor in IDSS. The research appears today in Environmental Research Letters.

A holistic approach

Many prior studies that compare emissions and costs of electric vehicles (EVs) to combustion-engine vehicles cover a few factors, like the amount of renewable energy in the grid and how gas prices impact affordability, Miotti says.

“To our knowledge, there have been few efforts so far that bring all these factors together. But if someone wants to buy a car and have a better understanding of the factors that affect emissions and costs, this holistic approach is important,” he adds.

The researchers focused on two types of EVs: battery-electric vehicles, which only operate on electricity, and plug-in hybrid electric vehicles, which also have a combustion engine that works in tandem with the battery to optimize fuel savings.

The team expanded and improved a set of previously developed vehicle cost and emissions models to incorporate a wider variety of factors and data types.

For instance, they refined an existing model that estimates energy use and gas mileage so it could capture more nuances of local climate variability. 

“But the real effort was not just in extending these different models, but in bringing together all these different data and making them work with the models in a consistent manner,” Miotti says.

The team sourced data on a wide variety of factors for each U.S. zip code, such as typical drive cycles, the amount of traffic, local gas and electricity prices, makeup of the regional electricity mix, meteorological profiles, and more. They used statistical approaches to amalgamate different types of data. 

For example, the team used a probabilistic matching technique to combine data on how often people drive, which was drawn from nationwide travel surveys, with more detailed GPS data that includes factors like drivers’ acceleration patterns and the distance they usually drive on each day of the week.

The researchers designed their analysis to focus on the spatial picture of emissions and costs, based on U.S. zip codes, while simultaneously considering the impact of the size and features of each specific vehicle model.

“At the end of the day, it’s the vehicle and fleet owners who make decisions about vehicle purchases. So, we wanted to make sure to consider their wide-ranging individual perspectives rather than simply performing a region-by-region comparison,” says Trancik.

Lower emissions, comparable costs

In the end, their modeling framework revealed that all factors they analyzed matter about equally in determining emissions-reduction potential of EVs compared to internal combustion vehicles. 

EVs reduce emissions the most in areas with a cleaner electricity mix, denser traffic, higher annual travel distances, and a mild climate, in decreasing order of importance. In each area, emission reductions increase for drivers who drive more often, drive larger vehicles, and are more frequently stuck in traffic. 

In a colder area like North Dakota, fuel economy of battery-electric vehicles might be reduced by as much as 50 percent on a particularly frigid night, but the effect on annual emission benefits is minimal. 

“We even did a sensitivity study to see if the range is reduced in very cold climates, and we found that, even in the most unfavorable conditions, EVs still reduce emissions by a substantial amount,” Miotti says.

On the cost side, the models show that, in most places across the U.S., EVs are competitive with comparable combustion-engine vehicles in terms of lifetime ownership cost, even without clean vehicle tax credits. And in areas where electricity is relatively affordable, battery-electric vehicles tend to cost less than their plug-in hybrid or combustion-engine counterparts.

In the future, the researchers want to expand this analysis to include a temporal dimension, so the framework also considers how changes in vehicle, fuel, and electricity prices affect emissions and costs over time. 

“While we found that the electricity mix is a big driver of the spatial variation in emissions savings of EVs, the electricity grid is decarbonizing everywhere. As that happens, emissions savings across space will become more homogenous for EVs, but the differences across one driver to another will remain,” Miotti says.

They could also use the framework to explore regions outside the United States or incorporate data on hybrid-electric vehicles that cannot be plugged in.

This work was funded, in part, by the MIT Martin Family Society of Fellows for Sustainability.

A crepe cake.

That’s how Camille Cunin describes the polymer-metal “sandwiches” that became a highlight of her doctoral thesis at MIT’s Department of Materials Science and Engineering (DMSE). Over close to five years, these composites were a key component of her research on bioelectronics — devices designed to interface with the human body.

Cunin completed her PhD in February — she’ll attend commencement in May — but traces her interest in bioelectronics to a formative summer internship at Massachusetts General Hospital (MGH) in Boston in 2019. There, she saw a patient with Parkinson’s disease struggle to swallow a tethered “capsule” intended to function as an exploratory gut probe. The device failed, and the gap between lab-based design and real life became all too apparent.

The incident validated the career path Cunin had already begun to pursue: to make usable products that have a positive impact on people’s lives. It’s a purpose that hasn’t gone unnoticed. “Some might be happy with a sketch of a concept and no actual demonstration, but Camille has a remarkable ability in that she wants to do materials science that can translate to real-world applications,” says her advisor, Aristide Gumyusenge.

Building blocks

The daughter of a psychologist and an engineer, Cunin grew up in Paris, encouraged by her parents to be curious about the world around her. LEGO blocks featured prominently in her childhood. When her father found some old lights in a box in the attic, 9-year-old Camille strung them to decorate her LEGO castle by creating a circuit, complete with a fuse.

Strong grades earned her a spot in France’s elite post-secondary preparatory classes for admission to the country’s prestigious grandes écoles. The intensive and competitive prep classes, however, left Cunin with a sour aftertaste — “for a while I hated science, because the environment was too competitive for me,” she says — and a bit rudderless in engineering school.

It was the research internship thousands of miles from home, at MGH — part of her master’s in engineering at École Centrale de Marseille in France — that rebooted her love of science. The open-ended nature of research appealed to her curiosity and helped her regain confidence in solving problems. She was delighted to be accepted at MIT DMSE for her doctoral studies. “In Boston, I thrived in collaborative environments, and it felt like anything was possible,” she says.

Stretching possibilities

Before starting at MIT, Cunin had a wealth of interdisciplinary experience, from internships and her graduate studies. Unsure about how to slot it all together, she was looking for an advisor at a time when Gumyusenge, Henry L. Doherty Career Development Professor in Ocean Utilization and assistant professor of materials science and engineering, was himself just establishing his lab at DMSE.

When Gumyusenge shared plans to work on projects to turn biological signals into electronic data, Cunin was excited to build on her prior research in biomedical devices. “Here was a chance to fine-tune the materials and to optimize the performance of bioelectronic devices. I really felt I could leverage my strengths in Aristide’s lab,” she remembers.

Gumyusenge proved a great fit, supporting Cunin’s broad research ambitions while helping her shape and integrate them into a coherent doctoral project. She tackled everything from developing and characterizing new materials to fabricating transistors and learning surgery to test the devices in animal models. The final dissertation focused on organic transistors, which boost body signals for easier detection in soft electronics.

Biological signals, like those from nerves in the body, are weak, and transistors amplify them so they can be measured. The challenge with developing bioelectronic devices is that traditional components are hard and rigid, while the human body is not. Devices must perform as needed and be soft and flexible to avoid irritating human tissue.

Another complication: Biological processes involve charged ions moving through fluids, while electronics rely on electrons moving through materials. Before transistors can amplify signals, they first have to convert biological signals into electronic ones for circuits to pick up.

Cunin’s transistor design needed to solve two major challenges: first, to facilitate the movement of electrons and ions in the “channel,” the hub of all signal activity, in soft, hydrated environments; and second, to be pliable enough to conform to the human body.

It was no easy task.

Elegant simplicity

Gumyusenge’s lab typically uses chemistry to modify material behavior, but Cunin took a different tack. Since polymers are soft, and metals are good conductors, she looked to the classic French pastry mille-feuille, which inspired the layered design: thin metal sheets sandwiched between layers of porous elastomer. The metal stretches with the elastomer and forms microcracks. Charges get trapped in the cracks but can still flow through the stack, while the elastomer’s strong adhesion keeps the layers together.

Her approach won Cunin high marks from her advisor. “Camille was working on a complex problem, but she found a way to simplify it with a straightforward approach,” Gumyusenge says.

Of course, even an elegant solution needs test drives. “The more crystalline the polymers are, the better the charges percolate and travel in the material,” Cunin points out, referring to how ordered the semiconducting polymers in the transistor channel are. But if they’re packed too tightly, ions don’t move freely, and the transistor channel can’t switch properly. The arrangement of the spaghetti-like polymer chains controls this balance, so Cunin studied the composites’ structure to optimize both ionic and electronic performance.

Professor Polina Anikeeva, who co-advised Cunin with Gumyusenge and calls her “unstoppable,” says her innovation in the lab was remarkable — but not surprising.

“She didn’t have to be pushed into trying something new,” says Anikeeva, head of DMSE. “I would have higher and higher expectations, and she would consistently meet those higher and higher expectations.”

That drive continues in industry. Cunin now works at the Cambridge-based neurotechnology startup Axoft — just minutes from her former lab at MIT — researching soft electrodes that can be implanted in the brain. The electrodes detect electrical signals that can shed light on the brain’s many functions. “By understanding the brain better, we can eventually develop therapies and treatments that improve patient outcomes,” Cunin says.

Creative outlets

During her time at MIT, Cunin also made time for activities outside the lab, driven by the same curiosity that fueled her research. Committed to sharing her love of materials science and engineering, she was a leading member of the Polymer Graduate Student Association and organized several editions of MIT Polymer Day, a one-day symposium connecting students, faculty, and industry to showcase cutting-edge polymer research.

She also pursued creative outlets. After learning to use 3D graphics software Blender, Cunin illustrated some of the journal covers featuring her work.

She is also a diehard salsa fan and teaches the dance style a couple of times a week. Salsa’s social and collaborative forms appeal to Cunin, who enjoys sharing her passion, experimenting with choreography, and helping fellow dancers improve. “Salsa is fast — I love the mental challenge it brings. I also like that it exposes you to different aspects of the community; it pushes you out of your bubble,” she says.

Gumyusenge appreciates that Cunin made time for other pursuits throughout the grueling demands of a doctoral degree. “She’d work 14 hours a day in the lab, but also go do some hiking and take a break. I love that — it’s something that other PhD students seem to forget sometimes,” he says.

That balance reflects her determination and resolve. “Camille has never been shy about facing challenging research problems,” he says. “She had a research vision and was dedicated to learning the lessons she needed to get it all done. I learned to not get in her way because when Camille told you she would learn how to do something, she would.”