Perovskites, a broad class of compounds with a particular kind of crystal structure, have long been seen as a promising alternative or supplement to today’s silicon or cadmium telluride solar panels. They could be far more lightweight and inexpensive, and could be coated onto virtually any substrate, including paper or flexible plastic that could be rolled up for easy transport.

In their efficiency at converting sunlight to electricity, perovskites are becoming comparable to silicon, whose manufacture still requires long, complex, and energy-intensive processes. One big remaining drawback is longevity: They tend to break down in a matter of months to years, while silicon solar panels can last more than two decades. And their efficiency over large module areas still lags behind silicon. Now, a team of researchers at MIT and several other institutions has revealed ways to optimize efficiency and better control degradation, by engineering the nanoscale structure of perovskite devices.

The study reveals new insights on how to make high-efficiency perovskite solar cells, and also provides new directions for engineers working to bring these solar cells to the commercial marketplace. The work is described today in the journal Nature Energy, in a paper by Dane deQuilettes, a recent MIT postdoc who is now co-founder and chief science officer of the MIT spinout Optigon, along with MIT professors Vladimir Bulovic and Moungi Bawendi, and 10 others at MIT and in Washington state, the U.K., and Korea.

“Ten years ago, if you had asked us what would be the ultimate solution to the rapid development of solar technologies, the answer would have been something that works as well as silicon but whose manufacturing is much simpler,” Bulovic says. “And before we knew it, the field of perovskite photovoltaics appeared. They were as efficient as silicon, and they were as easy to paint on as it is to paint on a piece of paper. The result was tremendous excitement in the field.”

Nonetheless, “there are some significant technical challenges of handling and managing this material in ways we’ve never done before,” he says. But the promise is so great that many hundreds of researchers around the world have been working on this technology. The new study looks at a very small but key detail: how to “passivate” the material’s surface, changing its properties in such a way that the perovskite no longer degrades so rapidly or loses efficiency.

“The key is identifying the chemistry of the interfaces, the place where the perovskite meets other materials,” Bulovic says, referring to the places where different materials are stacked next to perovskite in order to facilitate the flow of current through the device.

Engineers have developed methods for passivation, for example by using a solution that creates a thin passivating coating. But they’ve lacked a detailed understanding of how this process works — which is essential to make further progress in finding better coatings. The new study “addressed the ability to passivate those interfaces and elucidate the physics and science behind why this passivation works as well as it does,” Bulovic says.

The team used some of the most powerful instruments available at laboratories around the world to observe the interfaces between the perovskite layer and other materials, and how they develop, in unprecedented detail. This close examination of the passivation coating process and its effects resulted in “the clearest roadmap as of yet of what we can do to fine-tune the energy alignment at the interfaces of perovskites and neighboring materials,” and thus improve their overall performance, Bulovic says.

While the bulk of a perovskite material is in the form of a perfectly ordered crystalline lattice of atoms, this order breaks down at the surface. There may be extra atoms sticking out or vacancies where atoms are missing, and these defects cause losses in the material’s efficiency. That’s where the need for passivation comes in.

“This paper is essentially revealing a guidebook for how to tune surfaces, where a lot of these defects are, to make sure that energy is not lost at surfaces,” deQuilettes says. “It’s a really big discovery for the field,” he says. “This is the first paper that demonstrates how to systematically control and engineer surface fields in perovskites.”

The common passivation method is to bathe the surface in a solution of a salt called hexylammonium bromide, a technique developed at MIT several years ago by Jason Jungwan Yoo PhD ’20, who is a co-author of this paper, that led to multiple new world-record efficiencies. By doing that “you form a very thin layer on top of your defective surface, and that thin layer actually passivates a lot of the defects really well,” deQuilettes says. “And then the bromine, which is part of the salt, actually penetrates into the three-dimensional layer in a controllable way.” That penetration helps to prevent electrons from losing energy to defects at the surface.

These two effects, produced by a single processing step, produces the two beneficial changes simultaneously. “It’s really beautiful because usually you need to do that in two steps,” deQuilettes says.

The passivation reduces the energy loss of electrons at the surface after they have been knocked loose by sunlight. These losses reduce the overall efficiency of the conversion of sunlight to electricity, so reducing the losses boosts the net efficiency of the cells.

That could rapidly lead to improvements in the materials’ efficiency in converting sunlight to electricity, he says. The recent efficiency records for a single perovskite layer, several of them set at MIT, have ranged from about 24 to 26 percent, while the maximum theoretical efficiency that could be reached is about 30 percent, according to deQuilettes.

An increase of a few percent may not sound like much, but in the solar photovoltaic industry such improvements are highly sought after. “In the silicon photovoltaic industry, if you’re gaining half of a percent in efficiency, that’s worth hundreds of millions of dollars on the global market,” he says. A recent shift in silicon cell design, essentially adding a thin passivating layer and changing the doping profile, provides an efficiency gain of about half of a percent. As a result, “the whole industry is shifting and rapidly trying to push to get there.” The overall efficiency of silicon solar cells has only seen very small incremental improvements for the last 30 years, he says.

The record efficiencies for perovskites have mostly been set in controlled laboratory settings with small postage-stamp-size samples of the material. “Translating a record efficiency to commercial scale takes a long time,” deQuilettes says. “Another big hope is that with this understanding, people will be able to better engineer large areas to have these passivating effects.”

There are hundreds of different kinds of passivating salts and many different kinds of perovskites, so the basic understanding of the passivation process provided by this new work could help guide researchers to find even better combinations of materials, the researchers suggest. “There are so many different ways you could engineer the materials,” he says.

“I think we are on the doorstep of the first practical demonstrations of perovskites in the commercial applications,” Bulovic says. “And those first applications will be a far cry from what we’ll be able to do a few years from now.” He adds that perovskites “should not be seen as a displacement of silicon photovoltaics. It should be seen as an augmentation — yet another way to bring about more rapid deployment of solar electricity.”

“A lot of progress has been made in the last two years on finding surface treatments that improve perovskite solar cells,” says Michael McGehee, a professor of chemical engineering at the University of Colorado who was not associated with this research. “A lot of the research has been empirical with the mechanisms behind the improvements not being fully understood. This detailed study shows that treatments can not only passivate defects, but can also create a surface field that repels carriers that should be collected at the other side of the device. This understanding might help further improve the interfaces.”

The team included researchers at the Korea Research Institute of Chemical Technology, Cambridge University, the University of Washington in Seattle, and Sungkyunkwan University in Korea. The work was supported by the Tata Trust, the MIT Institute for Soldier Nanotechnologies, the U.S. Department of Energy, and the U.S. National Science Foundation.

One of the most contentious issues faced at the 28th Conference of Parties (COP28) on climate change last December was a proposal for a U.N.-sanctioned market for trading carbon credits. Such a mechanism would allow nations and industries making slow progress in reducing their own carbon emissions to pay others to take emissions-reducing measures, such as improving energy efficiency or protecting forests.

Such trading systems have already grown to a multibillion-dollar market despite a lack of clear international regulations to define and monitor the claimed emissions reductions. During weeks of feverish negotiations, some nations, including the U.S., advocated for a somewhat looser approach to regulations in the interests of getting a system in place quickly. Others, including the European Union, advocated much tighter regulation, in light of a history of questionable or even counterproductive projects of this kind in the past. In the end, no agreement was reached on the subject, which will be revisited at a later meeting.

The concept seems simple enough: Offset emissions in one place by preventing or capturing an equal amount of emissions elsewhere. But implementing that idea has turned out to be far more complex and fraught with problems than many expected.

For example, projects that aim to preserve a section of forest — which can remove carbon dioxide from the air and sequester it in the soil — face numerous issues. Will the preservation of one parcel just lead to the clearcutting of an adjacent parcel? Would the preserved land have been left uncut anyway? And what if it ends up being destroyed by wildfire, drought, or insect infestation — all of which are expected to become more likely with climate change?

Similarly, projects that aim to capture carbon dioxide emissions and inject them into the ground are sometimes used to justify increasing the production of petroleum or natural gas, negating the intended climate mitigation of the process.

Several experts at MIT now say that the system could be effective, at least in certain circumstances, but it must be thoroughly evaluated and regulated.

Carbon removal, natural or mechanical

Sergey Paltsev, deputy director of MIT’s Joint Program on the Science and Policy of Global Change, co-led a study and workshop last year that included policymakers, industry representatives, and researchers. They focused on one kind of carbon offsets, those based on natural climate solutions — restoration or preservation of natural systems that not only sequester carbon but also provide other benefits, such as greater biodiversity. “We find a lot of confusion and misperceptions and misinformation, even about how you define the term carbon credit or offset,” he says.

He points out that there has been a lot of criticism of the whole idea of carbon offsets, “and that criticism is well-placed. I think that’s a very healthy conversation, to clarify what makes sense and what doesn’t make sense. What are the real actions versus what is greenwashing?”

He says that government-mandated and managed carbon trading programs in some places, including British Columbia and parts of Europe, have been somewhat effective because they have clear standards in place, whereas unregulated carbon credit systems have often been abused.

Charles Harvey, an MIT professor of civil and environmental engineering, should know, having been actively involved in both sides of the issue over the last two decades. He co-founded a company in 2008 that was the first private U.S. company to attempt to remove carbon dioxide from emissions on a commercial scale, a process called carbon capture and sequestration, or CCS. Such projects have been a major recipient of federal subsidies aimed at combatting climate change, but Harvey now says these are largely a waste of money and in most cases do not achieve their stated objective.

In fact, he says that according to industry sources, as of 2021 more than 90 percent of CCS projects in the U.S. have been used for the production of more fossil fuels — oil and natural gas. Here's how it works: Natural gas wells often produce methane mixed with carbon dioxide, which must be removed to produce a marketable natural gas. This carbon dioxide is then injected into oil wells to stimulate more production. So, the net effect is the creation of more total greenhouse gas emissions rather than less, explains Harvey, who recently received a grant from the Rockefeller Foundation to explore CCS projects and whether they can be made to contribute to true emissions reductions.

What went wrong with the ambitious startup CCS company Harvey co-founded? “What happened is that the prices of renewables and energy storage are now incredibly cheap,” he says. “It makes no sense to do this, ever, on power plants because honestly, fossil fuel power plants don’t even really make economic sense anymore.”

Where does Harvey see potential for carbon credits to work? One possibility is the preservation or restoration of tropical peatlands, which he has received another grant to study. These are vast areas of permanently waterlogged land in which dead plant matter —and the carbon it contains — remains in place because the water prevents the normal decomposition processes that would otherwise release the stored carbon back into the air.

While it is virtually impossible to quantify the amount of carbon stored in the soil of forest or farmland, in peatlands that’s easy to do because essentially all of the submerged material is carbon-based. Simply measuring changes in the elevation of such land, which can be done remotely by plane or satellite, gives a precise measure of how much carbon has been stored or released. When a patch of peat forest that has been clear-cut to build plantations or roads is reforested, the amount of carbon emissions that were prevented can be measured accurately.

Because of that potential for accurate documentation, protecting or restoring peat bogs can also be a good way to achieve meaningful offsets for carbon emissions elsewhere, Harvey says. Rewetting a previously drained peat forest can immediately counteract the release of its stored carbon and can keep it there as long as it is not drained again — something that can be verified using satellite data.

Paltsev adds that while such nature-based systems for countering carbon emissions can be a key component of addressing climate change, especially in very difficult-to-decarbonize industries such as aviation, carbon credits for such programs “shouldn’t be a replacement for our efforts at emissions reduction. It should be in addition.”

Criteria for meaningful offsets

John Sterman, the Jay W. Forrester Professor of Management at the MIT Sloan School of Management, has published a set of criteria for evaluating proposed carbon offset plans to make sure they would provide the benefits they claim. At present, “there’s no regulation, there’s no oversight” for carbon offsets, he says. “There have been many scandals over this.”

For example, one company was providing what it claimed was certification for carbon offset projects but was found to have such lax standards that the claimed offsets were often not real. For example, there were multiple claims to protect the same piece of forest and claims to protect land that was already legally protected.

Sterman’s proposed set of criteria goes by the acronym AVID+. “It stands for four principles that you have to meet in order for your offset to be legitimate: It has to be additional, verifiable, immediate, and durable,” he says. “And then I call it AVID+,” he adds, the “plus” being for plans that have additional benefits as well, such as improving health, creating jobs, or helping historically disadvantaged communities.

Offsets can be useful, he says, for addressing especially hard-to-abate industries such as steel or cement manufacturing, or aviation. But it is essential to meet all four of the criteria, or else real emissions are not really being offset. For example, planting trees today, while often a good thing to do, would take decades to offset emissions going into the atmosphere now, where they may persist for centuries — so that fails to meet the “immediate” requirement.

And protecting existing forests, while also desirable, is very hard to prove as being additional, because “that requires a counterfactual that you can never observe,” he says. “That’s where a lot of squirrely accounting and a lot of fraud comes in, because how do you know that the forest would have been cut down but for the offset?” In one well-documented case, he points out, a company tried to sell carbon offsets for a section of forest that was already an established nature preserve.

Are there offsets that can meet all the criteria and provide real benefits in helping to address climate change? Yes, Sterman and Harvey say, but they need to be evaluated carefully.

“My favorite example,” Sterman says, “is doing deep energy retrofits and putting solar panels on low-income housing.” These measures can help address the so-called landlord-tenant problem: If tenants typically pay the utility bills, landlords have little incentive to pay for efficiency improvements, and the tenants don’t have the capital to make such improvements on their own. “Policies that would make this possible are pretty good candidates for legitimate offsets, because they are additional — low-income households can’t afford to do it without assistance, so it’s not going to happen without a program. It’s verifiable, because you’ve got the utility bills pre and post.” They are also quite immediate, typically taking only a year or so to implement, and “they’re pretty durable,” he says.

Another example is a recent plan in Alaska that allows cruise ships to offset the emissions caused by their trips by paying into a fund that provides subsidies for Alaskan citizens to install heat pumps in their homes, thus preventing emissions from wood or fossil fuel heating systems. “I think this is a pretty good candidate to meet the criteria, certainly a lot better than much of what’s being done today,” Sterman says.

But eventually, what is really needed, the researchers agree, are real, enforceable standards. After COP28, carbon offsets are still allowed, Sterman says, “but there is still no widely accepted mandatory regulation. We’re still in the wild West.”

Paltsev nevertheless sees reasons for optimism about nature-based carbon offset systems. For example, he says the aviation industry has recently agreed to implement a set of standards for offsetting their emissions, known as CORSIA, for carbon offsetting and reduction scheme for international aviation. “It’s a point for optimism,” he says, “because they issued very tough guidelines as to what projects are eligible and what projects are not.”

He adds, “There is a solution if you want to find a good solution. It is doable, when there is a will and there is the need.”

MIT graduate student Sydney Rose Johnson has never seen the steel mills in central India. She’s never toured the American Midwest’s hulking steel plants or the mini mills dotting the Mississippi River. But in the past year, she’s become more familiar with steel production than she ever imagined.

A fourth-year dual degree MBA and PhD candidate in chemical engineering and a graduate research assistant with the MIT Energy Initiative (MITEI) as well as a 2022-23 Shell Energy Fellow, Johnson looks at ways to reduce carbon dioxide (CO2) emissions generated by industrial processes in hard-to-abate industries. Those include steel.

Almost every aspect of infrastructure and transportation — buildings, bridges, cars, trains, mass transit — contains steel. The manufacture of steel hasn’t changed much since the Iron Age, with some steel plants in the United States and India operating almost continually for more than a century, their massive blast furnaces re-lined periodically with carbon and graphite to keep them going.

According to the World Economic Forum, steel demand is projected to increase 30 percent by 2050, spurred in part by population growth and economic development in China, India, Africa, and Southeast Asia.

The steel industry is among the three biggest producers of CO2 worldwide. Every ton of steel produced in 2020 emitted, on average, 1.89 tons of CO2 into the atmosphere — around 8 percent of global CO2 emissions, according to the World Steel Association.

A combination of technical strategies and financial investments, Johnson notes, will be needed to wrestle that 8 percent figure down to something more planet-friendly.

Johnson’s thesis focuses on modeling and analyzing ways to decarbonize steel. Using data mined from academic and industry sources, she builds models to calculate emissions, costs, and energy consumption for plant-level production.

“I optimize steel production pathways using emission goals, industry commitments, and cost,” she says. Based on the projected growth of India’s steel industry, she applies this approach to case studies that predict outcomes for some of the country’s thousand-plus factories, which together have a production capacity of 154 million metric tons of steel. For the United States, she looks at the effect of Inflation Reduction Act (IRA) credits. The 2022 IRA provides incentives that could accelerate the steel industry’s efforts to minimize its carbon emissions.

Johnson compares emissions and costs across different production pathways, asking questions such as: “If we start today, what would a cost-optimal production scenario look like years from now? How would it change if we added in credits? What would have to happen to cut 2005 levels of emissions in half by 2030?”

“My goal is to gain an understanding of how current and emerging decarbonization strategies will be integrated into the industry,” Johnson says.

Grappling with industrial problems

Growing up in Marietta, Georgia, outside Atlanta, the closest she ever came to a plant of any kind was through her father, a chemical engineer working in logistics and procuring steel for an aerospace company, and during high school, when she spent a semester working alongside chemical engineers tweaking the pH of an anti-foaming agent.

At Kennesaw Mountain High School, a STEM magnet program in Cobb County, students devote an entire semester of their senior year to an internship and research project.

Johnson chose to work at Kemira Chemicals, which develops chemical solutions for water-intensive industries with a focus on pulp and paper, water treatment, and energy systems.

“My goal was to understand why a polymer product was falling out of suspension — essentially, why it was less stable,” she recalls. She learned how to formulate a lab-scale version of the product and conduct tests to measure its viscosity and acidity. Comparing the lab-scale and regular product results revealed that acidity was an important factor. “Through conversations with my mentor, I learned this was connected with the holding conditions, which led to the product being oxidized,” she says. With the anti-foaming agent’s problem identified, steps could be taken to fix it.

“I learned how to apply problem-solving. I got to learn more about working in an industrial environment by connecting with the team in quality control as well as with R&D and chemical engineers at the plant site,” Johnson says. “This experience confirmed I wanted to pursue engineering in college.”

As an undergraduate at Stanford University, she learned about the different fields — biotechnology, environmental science, electrochemistry, and energy, among others — open to chemical engineers. “It seemed like a very diverse field and application range,” she says. “I was just so intrigued by the different things I saw people doing and all these different sets of issues.”

Turning up the heat

At MIT, she turned her attention to how certain industries can offset their detrimental effects on climate.

“I’m interested in the impact of technology on global communities, the environment, and policy. Energy applications affect every field. My goal as a chemical engineer is to have a broad perspective on problem-solving and to find solutions that benefit as many people, especially those under-resourced, as possible,” says Johnson, who has served on the MIT Chemical Engineering Graduate Student Advisory Board, the MIT Energy and Climate Club, and is involved with diversity and inclusion initiatives.

The steel industry, Johnson acknowledges, is not what she first imagined when she saw herself working toward mitigating climate change.

“But now, understanding the role the material has in infrastructure development, combined with its heavy use of coal, has illuminated how the sector, along with other hard-to-abate industries, is important in the climate change conversation,” Johnson says.

Despite the advanced age of many steel mills, some are quite energy-efficient, she notes. Yet these operations, which produce heat upwards of 3,000 degrees Fahrenheit, are still emission-intensive.

Steel is made from iron ore, a mixture of iron, oxygen, and other minerals found on virtually every continent, with Brazil and Australia alone exporting millions of metric tons per year. Commonly based on a process dating back to the 19th century, iron is extracted from the ore through smelting — heating the ore with blast furnaces until the metal becomes spongy and its chemical components begin to break down.

A reducing agent is needed to release the oxygen trapped in the ore, transforming it from its raw form to pure iron. That’s where most emissions come from, Johnson notes.

“We want to reduce emissions, and we want to make a cleaner and safer environment for everyone,” she says. “It’s not just the CO2 emissions. It’s also sometimes NOx and SOx [nitrogen oxides and sulfur oxides] and air pollution particulate matter at some of these production facilities that can affect people as well.”

In 2020, the International Energy Agency released a roadmap exploring potential technologies and strategies that would make the iron and steel sector more compatible with the agency’s vision of increased sustainability. Emission reductions can be accomplished with more modern technology, the agency suggests, or by substituting the fuels producing the immense heat needed to process ore. Traditionally, the fuels used for iron reduction have been coal and natural gas. Alternative fuels include clean hydrogen, electricity, and biomass.

Using the MITEI Sustainable Energy System Analysis Modeling Environment (SESAME), Johnson analyzes various decarbonization strategies. She considers options such as switching fuel for furnaces to hydrogen with a little bit of natural gas or adding carbon-capture devices. The models demonstrate how effective these tactics are likely to be. The answers aren’t always encouraging.

“Upstream emissions can determine how effective the strategies are,” Johnson says. Charcoal derived from forestry biomass seemed to be a promising alternative fuel, but her models showed that processing the charcoal for use in the blast furnace limited its effectiveness in negating emissions.

Despite the challenges, “there are definitely ways of moving forward,” Johnson says. “It’s been an intriguing journey in terms of understanding where the industry is at. There’s still a long way to go, but it’s doable.”

Johnson is heartened by the steel industry’s efforts to recycle scrap into new steel products and incorporate more emission-friendly technologies and practices, some of which result in significantly lower CO2 emissions than conventional production.

A major issue is that low-carbon steel can be more than 50 percent more costly than conventionally produced steel. “There are costs associated with making the transition, but in the context of the environmental implications, I think it’s well worth it to adopt these technologies,” she says.

After graduation, Johnson plans to continue to work in the energy field. “I definitely want to use a combination of engineering knowledge and business knowledge to work toward mitigating climate change, potentially in the startup space with clean technology or even in a policy context,” she says. “I’m interested in connecting the private and public sectors to implement measures for improving our environment and benefiting as many people as possible.”

MIT senior Sadhana Lolla has won the prestigious Gates Cambridge Scholarship, which offers students an opportunity to pursue graduate study in the field of their choice at Cambridge University in the U.K.

Established in 2000, the Gates Cambridge Scholarship offers full-cost post-graduate scholarships to outstanding applicants from countries outside of the U.K. The mission of the scholarship is to build a global network of future leaders committed to improving the lives of others.

Lolla, a senior from Clarksburg, Maryland, is majoring in computer science and minoring in mathematics and literature. At Cambridge, she will pursue an MPhil in technology policy.

In the future, Lolla aims to lead conversations on deploying and developing technology for marginalized communities, such as the rural Indian village that her family calls home, while also conducting research in embodied intelligence.

At MIT, Lolla conducts research on safe and trustworthy robotics and deep learning at the Distributed Robotics Laboratory with Professor Daniela Rus. Her research has spanned debiasing strategies for autonomous vehicles and accelerating robotic design processes. At Microsoft Research and Themis AI, she works on creating uncertainty-aware frameworks for deep learning, which has impacts across computational biology, language modeling, and robotics. She has presented her work at the Neural Information Processing Systems (NeurIPS) conference and the International Conference on Machine Learning (ICML). 

Outside of research, Lolla leads initiatives to make computer science education more accessible globally. She is an instructor for class 6.s191 (MIT Introduction to Deep Learning), one of the largest AI courses in the world, which reaches millions of students annually. She serves as the curriculum lead for Momentum AI, the only U.S. program that teaches AI to underserved students for free, and she has taught hundreds of students in Northern Scotland as part of the MIT Global Teaching Labs program.

Lolla was also the director for xFair, MIT’s largest student-run career fair, and is an executive board member for Next Sing, where she works to make a cappella more accessible for students across musical backgrounds. In her free time, she enjoys singing, solving crossword puzzles, and baking. 

“Between Sadhana's impressive research in the Distributed Robotics Group, her volunteer teaching with Momentum AI, and her internship and extracurricular experiences, she has developed the skills to be a leader,” says Kim Benard, associate dean of distinguished fellowships in Career Advising and Professional Development. “Her work at Cambridge will allow her the time to think about reducing bias in systems and the ethical implications of her work. I am proud that she will be representing MIT in the Gates Cambridge community.”

Hundreds of robots zip back and forth across the floor of a colossal robotic warehouse, grabbing items and delivering them to human workers for packing and shipping. Such warehouses are increasingly becoming part of the supply chain in many industries, from e-commerce to automotive production.

However, getting 800 robots to and from their destinations efficiently while keeping them from crashing into each other is no easy task. It is such a complex problem that even the best path-finding algorithms struggle to keep up with the breakneck pace of e-commerce or manufacturing. 

In a sense, these robots are like cars trying to navigate a crowded city center. So, a group of MIT researchers who use AI to mitigate traffic congestion applied ideas from that domain to tackle this problem.

They built a deep-learning model that encodes important information about the warehouse, including the robots, planned paths, tasks, and obstacles, and uses it to predict the best areas of the warehouse to decongest to improve overall efficiency.

Their technique divides the warehouse robots into groups, so these smaller groups of robots can be decongested faster with traditional algorithms used to coordinate robots. In the end, their method decongests the robots nearly four times faster than a strong random search method.

In addition to streamlining warehouse operations, this deep learning approach could be used in other complex planning tasks, like computer chip design or pipe routing in large buildings.

“We devised a new neural network architecture that is actually suitable for real-time operations at the scale and complexity of these warehouses. It can encode hundreds of robots in terms of their trajectories, origins, destinations, and relationships with other robots, and it can do this in an efficient manner that reuses computation across groups of robots,” says Cathy Wu, the Gilbert W. Winslow Career Development Assistant Professor in Civil and Environmental Engineering (CEE), and a member of a member of the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS).

Wu, senior author of a paper on this technique, is joined by lead author Zhongxia Yan, a graduate student in electrical engineering and computer science. The work will be presented at the International Conference on Learning Representations.

Robotic Tetris

From a bird’s eye view, the floor of a robotic e-commerce warehouse looks a bit like a fast-paced game of “Tetris.”

When a customer order comes in, a robot travels to an area of the warehouse, grabs the shelf that holds the requested item, and delivers it to a human operator who picks and packs the item. Hundreds of robots do this simultaneously, and if two robots’ paths conflict as they cross the massive warehouse, they might crash.

Traditional search-based algorithms avoid potential crashes by keeping one robot on its course and replanning a trajectory for the other. But with so many robots and potential collisions, the problem quickly grows exponentially.

“Because the warehouse is operating online, the robots are replanned about every 100 milliseconds. That means that every second, a robot is replanned 10 times. So, these operations need to be very fast,” Wu says.

Because time is so critical during replanning, the MIT researchers use machine learning to focus the replanning on the most actionable areas of congestion — where there exists the most potential to reduce the total travel time of robots.

Wu and Yan built a neural network architecture that considers smaller groups of robots at the same time. For instance, in a warehouse with 800 robots, the network might cut the warehouse floor into smaller groups that contain 40 robots each.

Then, it predicts which group has the most potential to improve the overall solution if a search-based solver were used to coordinate trajectories of robots in that group.

An iterative process, the overall algorithm picks the most promising robot group with the neural network, decongests the group with the search-based solver, then picks the next most promising group with the neural network, and so on.

Considering relationships

The neural network can reason about groups of robots efficiently because it captures complicated relationships that exist between individual robots. For example, even though one robot may be far away from another initially, their paths could still cross during their trips.

The technique also streamlines computation by encoding constraints only once, rather than repeating the process for each subproblem. For instance, in a warehouse with 800 robots, decongesting a group of 40 robots requires holding the other 760 robots as constraints. Other approaches require reasoning about all 800 robots once per group in each iteration.

Instead, the researchers’ approach only requires reasoning about the 800 robots once across all groups in each iteration.

“The warehouse is one big setting, so a lot of these robot groups will have some shared aspects of the larger problem. We designed our architecture to make use of this common information,” she adds.

They tested their technique in several simulated environments, including some set up like warehouses, some with random obstacles, and even maze-like settings that emulate building interiors.

By identifying more effective groups to decongest, their learning-based approach decongests the warehouse up to four times faster than strong, non-learning-based approaches. Even when they factored in the additional computational overhead of running the neural network, their approach still solved the problem 3.5 times faster.

In the future, the researchers want to derive simple, rule-based insights from their neural model, since the decisions of the neural network can be opaque and difficult to interpret. Simpler, rule-based methods could also be easier to implement and maintain in actual robotic warehouse settings.

“This approach is based on a novel architecture where convolution and attention mechanisms interact effectively and efficiently. Impressively, this leads to being able to take into account the spatiotemporal component of the constructed paths without the need of problem-specific feature engineering. The results are outstanding: Not only is it possible to improve on state-of-the-art large neighborhood search methods in terms of quality of the solution and speed, but the model generalizes to unseen cases wonderfully,” says Andrea Lodi, the Andrew H. and Ann R. Tisch Professor at Cornell Tech, and who was not involved with this research.

This work was supported by Amazon and the MIT Amazon Science Hub.

The Federal Laboratory Consortium (FLC) has selected MIT Lincoln Laboratory’s Timely Address Space Randomization (TASR) as one of the recipients of their 2024 Excellence in Technology Transfer Award. This cybersecurity technology was transferred in 2019 and 2021 to two companies that develop cloud-based services.

TASR has the potential to help harden many cloud-based servers and user applications against rampant information-leakage attacks. These attacks have been involved in several recent high-profile breaches in which cyber criminals used sensitive information to commit fraud or identity theft, steal financial assets, or gain unauthorized access to other restricted or mission-critical systems. TASR is the first technology that mitigates the impact of such attacks regardless of the attack mechanism or underlying system vulnerability.

A nationwide network of more than 300 government laboratories, agencies, and research centers, FLC helps facilitate the transfer of technologies out of research labs and into the marketplace to benefit the U.S. economy, society, and national security. On an annual basis, FLC confers awards to commend outstanding technology transfer achievements of employees of FLC member labs and their partners from industry, academia, nonprofits, and state and local governments. The Excellence in Technology Transfer Award recognizes exemplary transfer of federally developed technology.

“We are honored to receive this FLC award recognizing our excellence in such technology transfer — in this case, of a cutting-edge cybersecurity technology for protecting everyday users of cloud infrastructure,” says Lincoln Laboratory Chief Technology Ventures Officer Asha Rajagopal.

The Lincoln Laboratory team behind TASR initially developed the technology under sponsorship by the National Security Agency (NSA), following a survey of existing cyber defenses and their vulnerabilities. The three-year development of TASR led to a research prototype in 2015 and a U.S. patent in 2019. In 2020, the U.S. Department of Homeland Security (DHS) selected TASR for its Commercialization Accelerator Program, through which the team matured the technology and connected with commercial companies. Given the growing need for hardening cloud-based services, TASR offers an attractive solution, as it protects Linux-based applications and servers from cyberattacks. Originally developed for personal computers based on Intel’s x86 architecture, the Linux operating system now runs more than 80 percent of all internet servers, 90 percent of public cloud workloads, all 500 of the world’s fastest supercomputers, and the majority of smartphones using Android.

TASR works by automatically and transparently shuffling (rerandomizing) the location of code in memory every time an application processes an input-and-output pair. Information may leak to an attacker whenever the application sends an output, such as a file write or data packet transmitted over a network. But with TASR, the information that may be leaked during system output will have changed at the next point the attacker is able to act on such information (i.e., at system input). Through this moving-target approach, TASR addresses a significant problem contributing to information-leakage attacks: target homogeneity. Once attackers devise an attack against an application, they can easily compromise millions of computers at once because all installations of that application look alike internally. By continuously rerandomizing memory throughout the application’s execution, TASR prevents such action.

“From the first day we started working on TASR, our focus was on making the technology as practical as possible to facilitate its transition to real users. We are honored to be recognized by the FLC for the decade-long journey leading to the transfer of TASR,” says principal investigator Hamed Okhravi, senior staff in the laboratory’s Secure Resilient Systems and Technology Group. Okhravi led the nearly decade-long process of conception, NSA and DHS sponsorship, development, maturation, and transfer phases for TASR, with support from the laboratory’s Technology Ventures Office and MIT’s Technology Licensing Office. The other team members are David Bigelow, Jason Martin, and William Streilein, and former staff members Thomas Hobson and Robert Rudd. TASR was previously recognized with a 2022 R&D 100 Award, acknowledged as one of the year’s 100 most innovative technologies available for sale or license.

The TASR team and awardees in the other categories will be honored at an award ceremony on April 10 during the 2024 FLC National Meeting in Dallas, Texas.

In the Dzaleka Refugee Camp in Malawi, Jospin Hassan didn’t have access to the education opportunities he sought. So, he decided to create his own. 

Hassan knew the booming fields of data science and artificial intelligence could bring job opportunities to his community and help solve local challenges. After earning a spot in the 2020-21 cohort of the Certificate Program in Computer and Data Science from MIT Refugee Action Hub (ReACT), Hassan started sharing MIT knowledge and skills with other motivated learners in Dzaleka.

MIT ReACT is now Emerging Talent, part of the Jameel World Education Lab (J-WEL) at MIT Open Learning. Currently serving its fifth cohort of global learners, Emerging Talent’s year-long certificate program incorporates high-quality computer science and data analysis coursework from MITx, professional skill building, experiential learning, apprenticeship work, and opportunities for networking with MIT’s global community of innovators. Hassan’s cohort honed their leadership skills through interactive online workshops with J-WEL and the 10-week online MIT Innovation Leadership Bootcamp. 

“My biggest takeaway was networking, collaboration, and learning from each other,” Hassan says.

Today, Hassan’s organization ADAI Circle offers mentorship and education programs for youth and other job seekers in the Dzaleka Refugee Camp. The curriculum encourages hands-on learning and collaboration.

Launched in 2020, ADAI Circle aims to foster job creation and reduce poverty in Malawi through technology and innovation. In addition to their classes in data science, AI, software development, and hardware design, their Innovation Hub offers internet access to anyone in need. 

Doing something different in the community

Hassan first had the idea for his organization in 2018 when he reached a barrier in his own education journey. There were several programs in the Dzaleka Refugee Camp teaching learners how to code websites and mobile apps, but Hassan felt that they were limited in scope. 

“We had good devices and internet access,” he says, “but I wanted to learn something new.” 

Teaming up with co-founder Patrick Byamasu, Hassan and Byamasu set their sights on the longevity of AI and how that might create more jobs for people in their community. “The world is changing every day, and data scientists are in a higher demand today in various companies,” Hassan says. “For this reason, I decided to expand and share the knowledge that I acquired with my fellow refugees and the surrounding villages.”

ADAI Circle draws inspiration from Hassan's own experience with MIT Emerging Talent coursework, community, and training opportunities. For example, the MIT Bootcamps model is now standard practice for ADAI Circle’s annual hackathon. Hassan first introduced the hackathon to ADAI Circle students as part of his final experiential learning project of the Emerging Talent certificate program. 

ADAI Circle’s annual hackathon is now an interactive — and effective — way to select students who will most benefit from its programs. The local schools’ curricula, Hassan says, might not provide enough of an academic challenge. “We can’t teach everyone and accommodate everyone because there are a lot of schools,” Hassan says, “but we offer another place for knowledge.” 

The hackathon helps students develop data science and robotics skills. Before they start coding, students have to convince ADAI Circle teachers that their designs are viable, answering questions like, “What problem are you solving?” and “How will this help the community?” A community-oriented mindset is just as important to the curriculum.

In addition to the practical skills Hassan gained from Emerging Talent, he leveraged the program’s network to help his community. Thanks to a social media connection Hassan made with the nongovernmental organization Give Internet after one of Emerging Talent’s virtual events, Give Internet brought internet access to ADAI Circle.

Bridging the AI gap to unmet communities

In 2023, ADAI Circle connected with another MIT Open Learning program, Responsible AI for Social Empowerment and Education (RAISE), which led to a pilot test of a project-based AI curriculum for middle school students. The Responsible AI for Computational Action (RAICA) curriculum equipped ADAI Circle students with AI skills for chatbots and natural language processing. 

“I liked that program because it was based on what we’re teaching at the center,” Hassan says, speaking of his organization’s mission of bridging the AI gap to reach unmet communities.

The RAICA curriculum was designed by education experts at MIT Scheller Teacher Education Program (STEP Lab) and AI experts from MIT Personal Robots group and MIT App Inventor. ADAI Circle teachers gave detailed feedback about the pilot to the RAICA team. During weekly meetings with Glenda Stump, education research scientist for RAICA and J-WEL, and Angela Daniel, teacher development specialist for RAICA, the teachers discussed their experiences, prepared for upcoming lessons, and translated the learning materials in real time. 

“We are trying to create a curriculum that's accessible worldwide and to students who typically have little or no access to technology,” says Mary Cate Gustafson-Quiett, curriculum design manager at STEP Lab and project manager for RAICA. “Working with ADAI and students in a refugee camp challenged us to design in more culturally and technologically inclusive ways.”

Gustafson-Quiett says the curriculum feedback from ADAI Circle helped inform how RAICA delivers teacher development resources to accommodate learning environments with limited internet access. “They also exposed places where our team's western ideals, specifically around individualism, crept into activities in the lesson and contrasted with their more communal cultural beliefs,” she says.

Eager to introduce more MIT-developed AI resources, Hassan also shared MIT RAISE’s Day of AI curricula with ADAI Circle teachers. The new ChatGPT module gave students the chance to level up their chatbot programming skills that they gained from the RAICA module. Some of the advanced students are taking initiative to use ChatGPT API to create their own projects in education.

“We don’t want to tell them what to do, we want them to come up with their own ideas,” Hassan says.

Although ADAI Circle faces many challenges, Hassan says his team is addressing them one by one. Last year, they didn’t have electricity in their Innovation Hub, but they solved that. This year, they achieved a stable internet connection that’s one of the fastest in Malawi. Next up, they are hoping to secure more devices for their students, create more jobs, and add additional hubs throughout the community. The work is never done, but Hassan is starting to see the impact that ADAI Circle is making. 

“For those who want to learn data science, let’s let them learn,” Hassan says.

MIT’s Laboratory for Information and Decision Systems (LIDS) has been awarded $1,365,000 in funding from the Appalachian Regional Commission (ARC) to support its involvement with an innovative project, “Forming the Smart Grid Deployment Consortium (SGDC) and Expanding the HILLTOP+ Platform.”

The grant was made available through ARC's Appalachian Regional Initiative for Stronger Economies, which fosters regional economic transformation through multi-state collaboration.

Led by Kalyan Veeramachaneni, research scientist and principal investigator at LIDS' Data to AI Group, the project will focus on creating AI-driven generative models for customer load data. Veeramachaneni and colleagues will work alongside a team of universities and organizations led by Tennessee Tech University, including collaborators across Ohio, Pennsylvania, West Virginia, and Tennessee, to develop and deploy smart grid modeling services through the SGDC project.

These generative models have far-reaching applications, including grid modeling and training algorithms for energy tech startups. When the models are trained on existing data, they create additional, realistic data that can augment limited datasets or stand in for sensitive ones. Stakeholders can then use these models to understand and plan for specific what-if scenarios far beyond what could be achieved with existing data alone. For example, generated data can predict the potential load on the grid if an additional 1,000 households were to adopt solar technologies, how that load might change throughout the day, and similar contingencies vital to future planning.

The generative AI models developed by Veeramachaneni and his team will provide inputs to modeling services based on the HILLTOP+ microgrid simulation platform, originally prototyped by MIT Lincoln Laboratory. HILLTOP+ will be used to model and test new smart grid technologies in a virtual “safe space,” providing rural electric utilities with increased confidence in deploying smart grid technologies, including utility-scale battery storage. Energy tech startups will also benefit from HILLTOP+ grid modeling services, enabling them to develop and virtually test their smart grid hardware and software products for scalability and interoperability.

The project aims to assist rural electric utilities and energy tech startups in mitigating the risks associated with deploying these new technologies. “This project is a powerful example of how generative AI can transform a sector — in this case, the energy sector,” says Veeramachaneni. “In order to be useful, generative AI technologies and their development have to be closely integrated with domain expertise. I am thrilled to be collaborating with experts in grid modeling, and working alongside them to integrate the latest and greatest from my research group and push the boundaries of these technologies.”

“This project is testament to the power of collaboration and innovation, and we look forward to working with our collaborators to drive positive change in the energy sector,” says Satish Mahajan, principal investigator for the project at Tennessee Tech and a professor of electrical and computer engineering. Tennessee Tech’s Center for Rural Innovation director, Michael Aikens, adds, “Together, we are taking significant steps towards a more sustainable and resilient future for the Appalachian region.”

As Media Lab students in 2010, Karthik Dinakar SM ’12, PhD ’17 and Birago Jones SM ’12 teamed up for a class project to build a tool that would help content moderation teams at companies like Twitter (now X) and YouTube. The project generated a huge amount of excitement, and the researchers were invited to give a demonstration at a cyberbullying summit at the White House — they just had to get the thing working.

The day before the White House event, Dinakar spent hours trying to put together a working demo that could identify concerning posts on Twitter. Around 11 p.m., he called Jones to say he was giving up.

Then Jones decided to look at the data. It turned out Dinakar’s model was flagging the right types of posts, but the posters were using teenage slang terms and other indirect language that Dinakar didn’t pick up on. The problem wasn’t the model; it was the disconnect between Dinakar and the teens he was trying to help.

“We realized then, right before we got to the White House, that the people building these models should not be folks who are just machine-learning engineers,” Dinakar says. “They should be people who best understand their data.”

The insight led the researchers to develop point-and-click tools that allow nonexperts to build machine-learning models. Those tools became the basis for Pienso, which today is helping people build large language models for detecting misinformation, human trafficking, weapons sales, and more, without writing any code.

“These kinds of applications are important to us because our roots are in cyberbullying and understanding how to use AI for things that really help humanity,” says Jones.

As for the early version of the system shown at the White House, the founders ended up collaborating with students at nearby schools in Cambridge, Massachusetts, to let them train the models.

“The models those kids trained were so much better and nuanced than anything I could’ve ever come up with,” Dinakar says. “Birago and I had this big ‘Aha!’ moment where we realized empowering domain experts — which is different from democratizing AI — was the best path forward.”

A project with purpose

Jones and Dinakar met as graduate students in the Software Agents research group of the MIT Media Lab. Their work on what became Pienso started in Course 6.864 (Natural Language Processing) and continued until they earned their master’s degrees in 2012.

It turned out 2010 wasn’t the last time the founders were invited to the White House to demo their project. The work generated a lot of enthusiasm, but the founders worked on Pienso part time until 2016, when Dinakar finished his PhD at MIT and deep learning began to explode in popularity.

“We’re still connected to many people around campus,” Dinakar says. “The exposure we had at MIT, the melding of human and computer interfaces, widened our understanding. Our philosophy at Pienso couldn’t be possible without the vibrancy of MIT’s campus.”

The founders also credit MIT’s Industrial Liaison Program (ILP) and Startup Accelerator (STEX) for connecting them to early partners.

One early partner was SkyUK. The company’s customer success team used Pienso to build models to understand their customer’s most common problems. Today those models are helping to process half a million customer calls a day, and the founders say they have saved the company over £7 million pounds to date by shortening the length of calls into the company’s call center.

“The difference between democratizing AI and empowering people with AI comes down to who understands the data best — you or a doctor or a journalist or someone who works with customers every day?” Jones says. “Those are the people who should be creating the models. That’s how you get insights out of your data.”

In 2020, just as Covid-19 outbreaks began in the U.S., government officials contacted the founders to use their tool to better understand the emerging disease. Pienso helped experts in virology and infectious disease set up machine-learning models to mine thousands of research articles about coronaviruses. Dinakar says they later learned the work helped the government identify and strengthen critical supply chains for drugs, including the popular antiviral remdesivir.

“Those compounds were surfaced by a team that did not know deep learning but was able to use our platform,” Dinakar says.

Building a better AI future

Because Pienso can run on internal servers and cloud infrastructure, the founders say it offers an alternative for businesses being forced to donate their data by using services offered by other AI companies.

“The Pienso interface is a series of web apps stitched together,” Dinakar explains. “You can think of it like an Adobe Photoshop for large language models, but in the web. You can point and import data without writing a line of code. You can refine the data, prepare it for deep learning, analyze it, give it structure if it’s not labeled or annotated, and you can walk away with fine-tuned, large language model in a matter of 25 minutes.”

Earlier this year, Pienso announced a partnership with GraphCore, which provides a faster, more efficient computing platform for machine learning. The founders say the partnership will further lower barriers to leveraging AI by dramatically reducing latency.

“If you’re building an interactive AI platform, users aren’t going to have a cup of coffee every time they click a button,” Dinakar says. “It needs to be fast and responsive.”

The founders believe their solution is enabling a future where more effective AI models are developed for specific use cases by the people who are most familiar with the problems they are trying to solve.

“No one model can do everything,” Dinakar says. “Everyone’s application is different, their needs are different, their data is different. It’s highly unlikely that one model will do everything for you. It’s about bringing a garden of models together and allowing them to collaborate with each other and orchestrating them in a way that makes sense — and the people doing that orchestration should be the people who understand the data best.”

A lot of behind-the-scenes work goes into creating an art installation or a theater production – not just by those making or performing their craft, but also by the staff members who coordinate the logistics of exhibits and events. One of the people at MIT who helps artists bring their projects to life is Lydia Brosnahan.  

In her role as associate producer in the Office of the Arts, Brosnahan works with several different arts initiatives including the MIT Center for Art, Science and Technology (CAST) and the Council for the Arts at MIT (CAMIT).  

“The arts at MIT are alive and well,” says Brosnahan, who has worked at the Institute for six years. “My job involves administering grants to faculty for their own artistic work as well as visiting artist residency projects where faculty members invite an artist to campus to collaborate with them, their students, and with the MIT community. Every visiting artist residency has some sort of public component, which could be an event or an activity.” 

It’s a collaborative effort in the Office of the Arts and the tasks of the department do not end with grant selection, distribution, and event execution. Brosnahan’s colleagues are also involved in student art programs, with running the MIT Arts Studios classes, and with the Wiesner Student Art Gallery, which features exhibitions of artwork by MIT students.  

“I also coordinate the CAMIT grants program, which primarily supports artistic projects by students,” Brosnahan explains. “Right now, for example, there is an exhibition in the Wiesner Student Art Gallery that was supported by a grant from CAMIT. 

“When I tell people outside of the Institute that I work in the arts at MIT they usually respond with, ‘There are arts programs at MIT?’ I think that is kind of the general impression. Outside of our visiting artists programs, we also have public art collections, architecture...there are so many student artists who are doing it as part of their career or to enhance their degree. There are theater groups who put on productions and organizations that take part in music and dance. I want people to know that the arts here are rich and amazing.” 

One of the projects Brosnahan is most proud to have worked in was part of a collaboration between CAST and the MIT Museum. “The first collaborative project that we did, that I got to help launch, was an exhibition called Arachnodrone. It's an installation that is based on research about spiderwebs and is a collaboration between engineers in civil and environmental engineering, researchers, and musicians who took the vibrational frequency of spiderwebs and turned it into music. It is both an installation and a performance.”

She also enjoys producing Arts on the Radar, a big kick-off celebration in the first week of September. “It is basically a way to say 'The arts are here. Come check them out!' We have demonstrations by students and collaborate with other arts units on campus including the List Visual Arts Center; the Art, Culture, and Technology program; the Department of Architecture; the Morningside Academy for Design; and Music and Theater Arts. We come together to throw a big party with the goal of helping people learn about what opportunities are available in the arts. It’s fun!”

Soundbytes

Q: What do you like the most about your job? 

Brosnahan: The people. Every project I work on is a little bit different because everyone who comes to us has a cool idea for a project. There is never a dull moment! Often there are projects that bring together art, science, and technology in new ways. I learn a lot just from being around interesting people and projects. 

Q: If someone was about to start working in MIT, what advice would you give them? 

Brosnahan: Wander around campus. Get lost, explore, and try to meet people from every corner of MIT. When you start working here, there is a rush of new things to learn. It’s beneficial, and just great, to learn about everything going on here. I still find myself walking around, getting lost on campus, and discovering a different research lab I didn’t know about.  

Q: Are you involved in any groups or clubs offered to staff members outside of your job? 

Brosnahan: I'm a big fan of, and participant in, the MIT Language Conversation Exchange. LCE holds language lunches where you can sit at a specific language table and practice speaking that language with language learners and native speakers. They also have a program where you get matched with partners of MIT students, staff, and faculty as a one-on-one conversation partner. You note what language(s) you speak, which you want to learn, and then you can see if someone speaks one you want to learn. I'm really into foreign languages and I was excited to learn about that opportunity and get involved in the wider community.

Imagine being able to build an entire dialysis machine using nothing more than a 3D printer.

This could not only reduce costs and eliminate manufacturing waste, but since this machine could be produced outside a factory, people with limited resources or those who live in remote areas may be able to access this medical device more easily.

While multiple hurdles must be overcome to develop electronic devices that are entirely 3D printed, a team at MIT has taken an important step in this direction by demonstrating fully 3D-printed, three-dimensional solenoids.

Solenoids, electromagnets formed by a coil of wire wrapped around a magnetic core, are a fundamental building block of many electronics, from dialysis machines and respirators to washing machines and dishwashers.

The researchers modified a multimaterial 3D printer so it could print compact, magnetic-cored solenoids in one step. This eliminates defects that might be introduced during post-assembly processes.

This customized printer, which could utilize higher-performing materials than typical commercial printers, enabled the researchers to produce solenoids that could withstand twice as much electric current and generate a magnetic field that was three times larger than other 3D-printed devices.

In addition to making electronics cheaper on Earth, this printing hardware could be particularly useful in space exploration. For example, instead of shipping replacement electronic parts to a base on Mars, which could take years and cost millions of dollars, one could send a signal containing files for the 3D printer, says Luis Fernando Velásquez-García, a principal research scientist in MIT’s Microsystems Technology Laboratories (MTL).

“There is no reason to make capable hardware in only a few centers of manufacturing when the need is global. Instead of trying to ship hardware all over the world, can we empower people in distant places to make it themselves? Additive manufacturing can play a tremendous role in terms of democratizing these technologies,” adds Velásquez-García, the senior author of a new paper on the 3D printed solenoids that appears in the journal Virtual and Physical Prototyping.

He is joined on the paper by lead author Jorge Cañada, an electrical engineering and computer science graduate student; and Hyeonseok Kim, a mechanical engineering graduate student.

Additive advantages

A solenoid generates a magnetic field when an electrical current is passed through it. When someone rings a doorbell, for instance, electric current flows through a solenoid, which generates a magnetic field that moves an iron rod so it strikes a chime.

Integrating solenoids onto electrical circuits manufactured in a clean room poses significant challenges, as they have very different form factors and are made using incompatible processes that require post assembly. Consequently, researchers have investigated making solenoids utilizing many of the same processes that make semiconductor chips. But these techniques limit the size and shape of solenoids, which hampers performance.

With additive manufacturing, one can produce devices that are practically any size and shape. However, this presents its own challenges, since making a solenoid involves coiling thin layers made from multiple materials that may not all be compatible with one machine.

To overcome these challenges, the researchers needed to modify a commercial extrusion 3D printer.

Extrusion printing fabricates objects one layer at a time by squirting material through a nozzle. Typically, a printer uses one type of material feedstock, often spools of filament.

“Some people in the field look down on them because they are simple and don’t have a lot of bells and whistles, but extrusion is one of very few methods that allows you to do multimaterial, monolithic printing,” says Velásquez-García.

This is key, since the solenoids are produced by precisely layering three different materials — a dielectric material that serves as an insulator, a conductive material that forms the electric coil, and a soft magnetic material that makes up the core.

The team selected a printer with four nozzles — one dedicated to each material to prevent cross-contamination. They needed four extruders because they tried two soft magnetic materials, one based on a biodegradable thermoplastic and the other based on nylon.

Printing with pellets

They retrofitted the printer so one nozzle could extrude pellets, rather than filament. The soft magnetic nylon, which is made from a pliable polymer studded with metallic microparticles, is virtually impossible to produce as a filament. Yet this nylon material offers far better performance than filament-based alternatives.

Using the conductive material also posed challenges, since it would start melting and jam the nozzle. The researchers found that adding ventilation to cool the material prevented this. They also built a new spool holder for the conductive filament that was closer to the nozzle, reducing friction that could damage the thin strands.

Even with the team’s modifications, the customized hardware cost about $4,000, so this technique could be employed by others at a lower cost than other approaches, adds Velásquez-García.

The modified hardware prints a U.S. quarter-sized solenoid as a spiral by layering material around the soft magnetic core, with thicker conductive layers separated by thin insulating layers.

Precisely controlling the process is of paramount importance because each material prints at a different temperature. Depositing one on top of another at the wrong time might cause the materials to smear.

Because their machine could print with a more effective soft magnetic material, the solenoids achieved higher performance than other 3D-printed devices.

The printing method enabled them to build a three-dimensional device comprising eight layers, with coils of conductive and insulating material stacked around the core like a spiral staircase. Multiple layers increase the number of coils in the solenoid, which improves the amplification of the magnetic field.

Due to the added precision of the modified printer, they could make solenoids that were about 33 percent smaller than other 3D-printed versions. More coils in a smaller area also boosts amplification.

In the end, their solenoids could produce a magnetic field that was about three times larger than what other 3D-printed devices can achieve.

“We were not the first people to be able to make inductors that are 3D-printed, but we were the first ones to make them three-dimensional, and that greatly amplifies the kinds of values you can generate. And that translates into being able to satisfy a wider range of applications,” he says.

For instance, while these solenoids can’t generate as much magnetic field as those made with traditional fabrication techniques, they could be used as power convertors in small sensors or actuators in soft robots.

Moving forward, the researchers are looking to continue enhancing their performance.

For one, they could try using alternate materials that might have better properties. They are also exploring additional modifications that could more precisely control the temperature at which each material is deposited, reducing defects.

This work is funded by Empiriko Corporation.

As early as middle school, Branden Spitzer loved to watch cooking shows and experiment with recipes in his family’s kitchen. It was a clear harbinger of his interest in materials science, he says now. Once he discovered that he could delight others with a perfectly executed pie, he began to see the many ways that his passion for baking might branch into other areas requiring technical acuity.

“We have this deep connection to food, the things that we wear, the products around us that we experience or work with every day,” says the MIT senior. “I hope we can make those things even better using science and engineering.”

Spitzer is a materials science and engineering major and has rounded out his education by cross registering for food science classes at Harvard University. He has pursued a variety of research opportunities related to food and sustainability, from extending the shelf-life of produce to developing lab-grown meat.

Spitzer also sees food as a means of social nourishment. He enjoys exploring restaurants and having dinners with friends, and takes special pleasure in planning and putting together meals. “I love making pies and cooking because you can share something with people that they think is really tasty,” he says. “And by eating the food they can understand all the thought and everything that went into it. I want the work or research I go on to do to have that same sort of tangible impact.”

Sampling a huge menu

Upon beginning his first year at MIT, Spitzer was overwhelmed by the seemingly endless amount of activities the Institute had to offer. He says the busy student culture was one of the things that attracted him to MIT, yet once he was face-to-face with it all, he didn’t know where to begin. He recalls one of his first-year advisors instructing him to “ride the wave,” and he took this to heart. Open to trying anything, Spitzer set forth on several academic and extracurricular journeys that would lead him in completely different directions through his four years.

He pursued research projects centered on food and sustainability. In one of his first research positions, Spitzer worked for Mori, a Cambridge-based startup that makes a silk-based coating that slows the spoiling of fruits and vegetables. His longest-running research project, in Professor Markus Buehler’s Laboratory for Atomistic and Molecular Mechanics, involves working with mycelium, the root systems of mushrooms, to improve and alter the growth of the material for use in 3D printing. He spent a summer interning for a company in South Africa that is working on a lab-grown meat product, and currently he is interning for Faerm, a plant-based cheese company in Copenhagen, Denmark. He hopes to continue this in this direction after graduation, either at a startup or in graduate school studying materials science or biological engineering.

Spitzer also strives to make a positive impact on his local community at MIT through his work. He participated in activities ranging from physical education to the arts, and everything in between. He joined the student organization MCG, the MIT Consulting Group, solving real-world business problems for clients. Spitzer is also a member of the Phi Delta Theta fraternity, where he served as vice president for three semesters and introduced an initiative to prioritize inclusivity and mental health awareness. And, he joined MIT’s lighting design group, which he says exposed him to new entirely new communities of artists and engineers.  

Spitzer has been fond of traveling since he was a child. He recalls taking trips with his family often, visiting historical and global landmarks. In the past four years he has embarked on multiple study abroad and work experiences through MISTI and is enthusiastic about the unexpected places his internships have taken him. He has spent time in the U.K., Brazil, and South Africa, and will be studying in Denmark this semester.

In Brazil, Spitzer helped to develop and teach a materials science program and class. He says it was exciting to share the subjects of polymers, recycling, and sustainability with students in a different part of the world. In South Africa, Spitzer interned for the Mzansi Meat Co. (now Newform Foods), which he came across by surprise after searching for companies that were making cultured meat products.

Pirates at MIT

Spurred by MIT’s physical education requirements, Spitzer has found a passion for several sports activities. Sailing, for example, has become one of his favorite hobbies. “It’s super cool that we have a chance to do these crazy things,” he says when referring to his time spent taking out sailboats to practice for his sailing class on the Charles River.

Sailing is one of four physical education classes needed to obtain the MIT Pirate Certificate, an incentive that encourages participation in MIT’s P.E. offerings. Spitzer pursued this achievement, enrolling in archery, rifle, and fencing classes over several semesters. The diverse course selection allowed for unexpected discoveries. “I was surprised and blown away by how much the rifle practice was an exercise in thought, focus, and meditation,” he says. “It was very different than I expected, in a very pleasant way.”

Ice skating is another discovery Spitzer made through his four required gym classes. He has taken many more classes by now though since they are “super fun.” Beginning as a nervous newcomer with no experience, Spitzer now takes an intermediate skating class where he develops his skills in turns and speed skating.

Spitzer also enjoys recreational cycling and indoor rock climbing in his spare time, as well as yoga and dancing. He has taken multiple dance classes in his time at MIT and has been a member of the organization MIT DanceTroupe for four years.

Whether in the kitchen, lab, or gym, Spitzer has found a robust community in all corners of the MIT campus and beyond. Rather than choosing one area of focus, Spitzer states the most integral aspect of his student experience at MIT was getting a taste for everything: “You just try things out here. You learn the things you love or the things you hate, and get to do something really cool along the way.”

After a week of festivities around campus, members of the MIT community gathered Saturday evening in the Boston Marriott Kendall Square ballroom to celebrate the life and legacy of Martin Luther King Jr. Marking 50 years of this annual celebration at MIT, the gala event’s program was loosely organized around a line in King’s essay, “The Purpose of Education,” which he penned as an undergraduate at Morehouse College:

“We must remember that intelligence is not enough,” King wrote. “Intelligence plus character — that is the goal of true education.”

Senior Myles Noel was the master of ceremonies for the evening and welcomed one and all. Minister DiOnetta Jones Crayton, former director of the Office of Minority Education and associate dean of minority education, delivered the invocation, exhorting the audience to embrace “the fiery urgency of now.” Next, MIT President Sally Kornbluth shared her remarks.

She acknowledged that at many institutions, diversity and inclusion efforts are eroding. Kornbluth reiterated her commitment to these efforts, saying, “I want to be clear about how important I believe it is to keep such efforts strong — and to make them the best they can be. The truth is, by any measure, MIT has never been more diverse, and it has never been more excellent. And we intend to keep it that way.”

Kornbluth also recognized the late Paul Parravano, co-director of MIT’s Office of Government and Community Relations, who was a staff member at MIT for 33 years as well as the longest-serving member on the MLK Celebration Committee. Parravano’s “long and distinguished devotion to the values and goals of Dr. Martin Luther King, Jr. inspires us all,” Kornbluth said, presenting his family with the 50th Anniversary Lifetime Achievement Award. 

Next, students and staff shared personal reflections. Zina Queen, office manager in the Department of Political Science, noted that her family has been a part of the MIT community for generations. Her grandmother, Rita, her mother, Wanda, and her daughter have all worked or are currently working at the Institute. Queen pointed out that her family epitomizes another of King’s oft-repeated quotes, “Every man is an heir to a legacy of dignity and worth.”

Senior Tamea Cobb noted that MIT graduates have a particular power in the world that they must use strategically and with intention. “Education and service go hand and hand,” she said, adding that she intends “every one of my technical abilities will be used to pursue a career that is fulfilling, expansive, impactful, and good.”

Graduate student Austin K. Cole ’24 addressed the Israel-Hamas conflict and the MIT administration. As he spoke, some attendees left their seats to stand with Cole at the podium. Cole closed his remarks with a plea to resist state and structural violence, and instead focus on relationship and mutuality.

After dinner, incoming vice president for equity and inclusion Karl Reid ’84, SM ’85 honored Adjunct Professor Emeritus Clarence Williams for his distinguished service to the Institute. Williams was an assistant to three MIT presidents, served as director of the Office of Minority Education, taught in the Department of Urban Planning, initiated the MIT Black History Project, and mentored hundreds of students. Reid was one of those students, and he shared a few of his mentor’s oft repeated phrases:

“Do the work and let the talking take care of itself.”

“Bad ideas kill themselves; great ideas flourish.”

In closing, Reid exhorted the audience to create more leaders who, like Williams, embody excellence and mutual respect for others.

The keynote address was given by civil rights activist Janet Moses, a member of the Student Nonviolent Coordinating Committee (SNCC) in the 1960s; a physician who worked for a time as a pediatrician at MIT Health; a longtime resident of Cambridge, Massachusetts; and a co-founder, with her husband, Robert Moses, of the Algebra Project, a pioneering program grounded in the belief “that in the 21st century every child has a civil right to secure math literacy — the ability to read, write, and reason with the symbol systems of mathematics.”

A striking image of a huge new building planned for New York City appeared on the screen behind Moses during her address. It was a rendering of a new jail being built at an estimated cost of $3 billion. Against this background, she described the trajectory of the “carceral state,” which began in 1771 with the Mansfield Judgement in England. At the time, “not even South Africa had a set of race laws as detailed as those in the U.S.,” Moses observed.

Today, the carceral state uses all levels of government to maintain a racial caste system that is deeply entrenched, Moses argued, drawing a connection between the purported need for a new prison complex and a statistic that Black people in New York state are three times more likely than whites to be convicted for a crime.

She referenced a McKinsey study that it will take Black people over three centuries to achieve a quality of life on parity with whites. Despite the enormity of this challenge, Moses encouraged the audience to “rock the boat and churn the waters of the status quo.” She also pointed out that “there is joy in the struggle.”

Symbols of joy were also on display at the Gala in the forms of original visual art and poetry, and a quilt whose squares were contributed by MIT staff, students, and alumni, hailing from across the Institute.

Quilts are a physical manifestation of the legacy of the enslaved in America and their descendants — the ability to take scraps and leftovers to create something both practical and beautiful. The 50th anniversary quilt also incorporated a line from King’s highly influential “I Have a Dream Speech”:

“One day, all God’s children will have the riches of freedom and the security of justice.”

Experimental computer memories and processors built from magnetic materials use far less energy than traditional silicon-based devices. Two-dimensional magnetic materials, composed of layers that are only a few atoms thick, have incredible properties that could allow magnetic-based devices to achieve unprecedented speed, efficiency, and scalability.

While many hurdles must be overcome until these so-called van der Waals magnetic materials can be integrated into functioning computers, MIT researchers took an important step in this direction by demonstrating precise control of a van der Waals magnet at room temperature.

This is key, since magnets composed of atomically thin van der Waals materials can typically only be controlled at extremely cold temperatures, making them difficult to deploy outside a laboratory.

The researchers used pulses of electrical current to switch the direction of the device’s magnetization at room temperature. Magnetic switching can be used in computation, the same way a transistor switches between open and closed to represent 0s and 1s in binary code, or in computer memory, where switching enables data storage.

The team fired bursts of electrons at a magnet made of a new material that can sustain its magnetism at higher temperatures. The experiment leveraged a fundamental property of electrons known as spin, which makes the electrons behave like tiny magnets. By manipulating the spin of electrons that strike the device, the researchers can switch its magnetization.

“The heterostructure device we have developed requires an order of magnitude lower electrical current to switch the van der Waals magnet, compared to that required for bulk magnetic devices,” says Deblina Sarkar, the AT&T Career Development Assistant Professor in the MIT Media Lab and Center for Neurobiological Engineering, head of the Nano-Cybernetic Biotrek Lab, and the senior author of a paper on this technique. “Our device is also more energy efficient than other van der Waals magnets that are unable to switch at room temperature.”

In the future, such a magnet could be used to build faster computers that consume less electricity. It could also enable magnetic computer memories that are nonvolatile, which means they don’t leak information when powered off, or processors that make complex AI algorithms more energy-efficient.

“There is a lot of inertia around trying to improve materials that worked well in the past. But we have shown that if you make radical changes, starting by rethinking the materials you are using, you can potentially get much better solutions,” says Shivam Kajale, a graduate student in Sarkar’s lab and co-lead author of the paper.

Kajale and Sarkar are joined on the paper by co-lead author Thanh Nguyen, a graduate student in the Department of Nuclear Science and Engineering (NSE); Corson Chao, a graduate student in the Department of Materials Science and Engineering (DSME); David Bono, a DSME research scientist; Artittaya Boonkird, an NSE graduate student; and Mingda Li, associate professor of nuclear science and engineering. The research appears this week in Nature Communications.

An atomically thin advantage

Methods to fabricate tiny computer chips in a clean room from bulk materials like silicon can hamper devices. For instance, the layers of material may be barely 1 nanometer thick, so minuscule rough spots on the surface can be severe enough to degrade performance.

By contrast, van der Waals magnetic materials are intrinsically layered and structured in such a way that the surface remains perfectly smooth, even as researchers peel off layers to make thinner devices. In addition, atoms in one layer won’t leak into other layers, enabling the materials to retain their unique properties when stacked in devices.

“In terms of scaling and making these magnetic devices competitive for commercial applications, van der Waals materials are the way to go,” Kajale says.

But there’s a catch. This new class of magnetic materials have typically only been operated at temperatures below 60 kelvins (-351 degrees Fahrenheit). To build a magnetic computer processor or memory, researchers need to use electrical current to operate the magnet at room temperature.

To achieve this, the team focused on an emerging material called iron gallium telluride. This atomically thin material has all the properties needed for effective room temperature magnetism and doesn’t contain rare earth elements, which are undesirable because extracting them is especially destructive to the environment.

Nguyen carefully grew bulk crystals of this 2D material using a special technique. Then, Kajale fabricated a two-layer magnetic device using nanoscale flakes of iron gallium telluride underneath a six-nanometer layer of platinum.

Tiny device in hand, they used an intrinsic property of electrons known as spin to switch its magnetization at room temperature.

Electron ping-pong

While electrons don’t technically “spin” like a top, they do possess the same kind of angular momentum. That spin has a direction, either up or down. The researchers can leverage a property known as spin-orbit coupling to control the spins of electrons they fire at the magnet.

The same way momentum is transferred when one ball hits another, electrons will transfer their “spin momentum” to the 2D magnetic material when they strike it. Depending on the direction of their spins, that momentum transfer can reverse the magnetization.

In a sense, this transfer rotates the magnetization from up to down (or vice-versa), so it is called a “torque,” as in spin-orbit torque switching. Applying a negative electric pulse causes the magnetization to go downward, while a positive pulse causes it to go upward.

The researchers can do this switching at room temperature for two reasons: the special properties of iron gallium telluride and the fact that their technique uses small amounts of electrical current. Pumping too much current into the device would cause it to overheat and demagnetize.

The team faced many challenges over the two years it took to achieve this milestone, Kajale says. Finding the right magnetic material was only half the battle. Since iron gallium telluride oxidizes quickly, fabrication must be done inside a glovebox filled with nitrogen.

“The device is only exposed to air for 10 or 15 seconds, but even after that I have to do a step where I polish it to remove any oxide,” he says.

Now that they have demonstrated room-temperature switching and greater energy efficiency, the researchers plan to keep pushing the performance of magnetic van der Waals materials.

“Our next milestone is to achieve switching without the need for any external magnetic fields. Our aim is to enhance our technology and scale up to bring the versatility of van der Waals magnet to commercial applications,” Sarkar says.

This work was carried out, in part, using the facilities at MIT.Nano and the Harvard University Center for Nanoscale Systems.

MIT’s School of Humanities, Arts, and Social Sciences (SHASS) has announced that 35 MIT undergraduate sophomores and juniors have been named Burchard Scholars for 2024.

Elected by the Burchard Committee from a large pool of impressive applicants, all students chosen for the program have demonstrated excellence and engagement in the humanistic fields, but can major in science, design, and engineering fields as well as the humanities, arts, and social sciences.

In the course of this calendar year, the Burchard Scholars will attend seminar dinners with members of the SHASS faculty, during which they will have the chance to engage with the faculty and one another. The program is designed to both broaden horizons for promising students and provide scholars the chance to engage in friendly but challenging discussions in which to hone skills for expressing, critiquing, and debating ideas with peers and mentors.

During the course of the calendar year, the scholars also attend several cultural events in the Boston metropolitan area.

The key features of these dinners are presentations by SHASS’ faculty, on topics ranging from nuclear security to an economic view of artificial intelligence to cross-cultural histories in centuries-old manuscripts. Drawing on the school’s vast and varied fields of expertise, the seminars offer near-endless avenues of exploration for ambitious scholars.

It is perhaps no surprise that a high percentage of the MIT students who receive Rhodes, Marshall, and other major scholarships and fellowships are former Burchard Scholars. “These students are an extraordinary group of MIT undergraduates," says Margery Resnick, associate professor of literature and director of the Burchard program. “They are thoughtful, smart, and enthusiastic about the opportunity to discuss a wide range of ideas with faculty and fellow students.”

The 2024 Burchard Scholars, their academic years, and majors are:

• Mustafa Al-Obaidi, junior, mechanical engineering;
• Saul Balcarcel-Salazar, junior, physics;
• Miguel Buitrago, sophomore, philosophy;
• Julia Camacho, junior, urban studies and planning;
• Kaelyn Dunnell, junior, literature;
• Isabella Gandara, junior, biological engineering;
• Renee Ge, junior, electrical engineering and computer science;
• Graham Guite, sophomore, biological engineering;
• Janka Hamori, junior, electrical engineering and computer science;
• Vivian Hir, junior, electrical engineering and computer science;
• Sashko Horokh, junior, mathematics;
• Janvi Huria, junior, electrical engineering and computer science;
• Emily Kang, junior, electrical engineering and computer science;
• Kelly Kim, sophomore, literature;
• Esther Kinyanjui, junior, electrical engineering and computer science;
• Alice Le, junior, writing;
• Rumi Lee, junior, electrical engineering and computer science;
• Effaima Longe, junior, chemistry;
• Tarang Lunawat, junior, electrical engineering and computer science;
• Ariel McGee, sophomore, writing;
• Leena Mehendale, sophomore, biological engineering;
• Zev Moore, sophomore, management;
• Franklin Nguyen, junior, electrical engineering and computer science;
• Mishael Quraishi, junior, materials science and engineering;
• Syd Robinson, junior, materials science and engineering;
• James Rock, sophomore, political science;
• Katie Spivakovsky, sophomore, Biological Engineering;
• Mohamed Suufi, junior, electrical engineering and computer science;
• Alex Tang, sophomore, biology;
• Margaret Wang, junior, mathematics;
• Ashley Williams, junior, electrical engineering and computer science;
• Felicia Xiao, junior, physics;
• Kaitlyn Yanna, junior, nuclear science and engineering;
• Elizabeth Zhang, sophomore, electrical engineering and computer science; and
• Grace Zhang, junior, mathematics.

The electron is the basic unit of electricity, as it carries a single negative charge. This is what we’re taught in high school physics, and it is overwhelmingly the case in most materials in nature.

But in very special states of matter, electrons can splinter into fractions of their whole. This phenomenon, known as “fractional charge,” is exceedingly rare, and if it can be corralled and controlled, the exotic electronic state could help to build resilient, fault-tolerant quantum computers.

To date, this effect, known to physicists as the “fractional quantum Hall effect,” has been observed a handful of times, and mostly under very high, carefully maintained magnetic fields. Only recently have scientists seen the effect in a material that did not require such powerful magnetic manipulation.

Now, MIT physicists have observed the elusive fractional charge effect, this time in a simpler material: five layers of graphene — an atom-thin layer of carbon that stems from graphite and common pencil lead. They report their results today in Nature.

They found that when five sheets of graphene are stacked like steps on a staircase, the resulting structure inherently provides just the right conditions for electrons to pass through as fractions of their total charge, with no need for any external magnetic field.

The results are the first evidence of the “fractional quantum anomalous Hall effect” (the term “anomalous” refers to the absence of a magnetic field) in crystalline graphene, a material that physicists did not expect to exhibit this effect.

“This five-layer graphene is a material system where many good surprises happen,” says study author Long Ju, assistant professor of physics at MIT. “Fractional charge is just so exotic, and now we can realize this effect with a much simpler system and without a magnetic field. That in itself is important for fundamental physics. And it could enable the possibility for a type of quantum computing that is more robust against perturbation.”

Ju’s MIT co-authors are lead author Zhengguang Lu, Tonghang Han, Yuxuan Yao, Aidan Reddy, Jixiang Yang, Junseok Seo, and Liang Fu, along with Kenji Watanabe and Takashi Taniguchi at the National Institute for Materials Science in Japan.

A bizarre state

The fractional quantum Hall effect is an example of the weird phenomena that can arise when particles shift from behaving as individual units to acting together as a whole. This collective “correlated” behavior emerges in special states, for instance when electrons are slowed from their normally frenetic pace to a crawl that enables the particles to sense each other and interact. These interactions can produce rare electronic states, such as the seemingly unorthodox splitting of an electron’s charge.

In 1982, scientists discovered the fractional quantum Hall effect in heterostructures of gallium arsenide, where a gas of electrons confined in a two-dimensional plane is placed under high magnetic fields. The discovery later won the group a Nobel Prize in Physics.

“[The discovery] was a very big deal, because these unit charges interacting in a way to give something like fractional charge was very, very bizarre,” Ju says. “At the time, there were no theory predictions, and the experiments surprised everyone.”

Those researchers achieved their groundbreaking results using magnetic fields to slow down the material’s electrons enough for them to interact. The fields they worked with were about 10 times stronger than what typically powers an MRI machine.

In August 2023, scientists at the University of Washington reported the first evidence of fractional charge without a magnetic field. They observed this “anomalous” version of the effect, in a twisted semiconductor called molybdenum ditelluride. The group prepared the material in a specific configuration, which theorists predicted would give the material an inherent magnetic field, enough to encourage electrons to fractionalize without any external magnetic control.

The “no magnets” result opened a promising route to topological quantum computing — a more secure form of quantum computing, in which the added ingredient of topology (a property that remains unchanged in the face of weak deformation or disturbance) gives a qubit added protection when carrying out a computation. This computation scheme is based on a combination of fractional quantum Hall effect and a superconductor. It used to be almost impossible to realize: One needs a strong magnetic field to get fractional charge, while the same magnetic field will usually kill the superconductor. In this case the fractional charges would serve as a qubit (the basic unit of a quantum computer).

Making steps

That same month, Ju and his team happened to also observe signs of anomalous fractional charge in graphene — a material for which there had been no predictions for exhibiting such an effect.

Ju’s group has been exploring electronic behavior in graphene, which by itself has exhibited exceptional properties. Most recently, Ju’s group has looked into pentalayer graphene — a structure of five graphene sheets, each stacked slightly off from the other, like steps on a staircase. Such pentalayer graphene structure is embedded in graphite and can be obtained by exfoliation using Scotch tape. When placed in a refrigerator at ultracold temperatures, the structure’s electrons slow to a crawl and interact in ways they normally wouldn’t when whizzing around at higher temperatures.

In their new work, the researchers did some calculations and found that electrons might interact with each other even more strongly if the pentalayer structure were aligned with hexagonal boron nitride (hBN) — a material that has a similar atomic structure to that of graphene, but with slightly different dimensions. In combination, the two materials should produce a moiré superlattice — an intricate, scaffold-like atomic structure that could slow electrons down in ways that mimic a magnetic field.

“We did these calculations, then thought, let’s go for it,” says Ju, who happened to install a new dilution refrigerator in his MIT lab last summer, which the team planned to use to cool materials down to ultralow temperatures, to study exotic electronic behavior.

The researchers fabricated two samples of the hybrid graphene structure by first exfoliating graphene layers from a block of graphite, then using optical tools to identify five-layered flakes in the steplike configuration. They then stamped the graphene flake onto an hBN flake and placed a second hBN flake over the graphene structure. Finally, they attached electrodes to the structure and placed it in the refrigerator, set to near absolute zero.

As they applied a current to the material and measured the voltage output, they started to see signatures of fractional charge, where the voltage equals the current multiplied by a fractional number and some fundamental physics constants.

“The day we saw it, we didn’t recognize it at first,” says first author Lu. “Then we started to shout as we realized, this was really big. It was a completely surprising moment.”

“This was probably the first serious samples we put in the new fridge,” adds co-first author Han. “Once we calmed down, we looked in detail to make sure that what we were seeing was real.”

With further analysis, the team confirmed that the graphene structure indeed exhibited the fractional quantum anomalous Hall effect. It is the first time the effect has been seen in graphene.

“Graphene can also be a superconductor,” Ju says. “So, you could have two totally different effects in the same material, right next to each other. If you use graphene to talk to graphene, it avoids a lot of unwanted effects when bridging graphene with other materials.”

For now, the group is continuing to explore multilayer graphene for other rare electronic states.

“We are diving in to explore many fundamental physics ideas and applications,” he says. “We know there will be more to come.”

This research is supported in part by the Sloan Foundation, and the National Science Foundation.

Pollsters trying to predict presidential election results and physicists searching for distant exoplanets have at least one thing in common: They often use a tried-and-true scientific technique called Bayesian inference.

Bayesian inference allows these scientists to effectively estimate some unknown parameter — like the winner of an election — from data such as poll results. But Bayesian inference can be slow, sometimes consuming weeks or even months of computation time or requiring a researcher to spend hours deriving tedious equations by hand. 

Researchers from MIT and elsewhere have introduced an optimization technique that speeds things up without requiring a scientist to do a lot of additional work. Their method can achieve more accurate results faster than another popular approach for accelerating Bayesian inference.

Using this new automated technique, a scientist could simply input their model and then the optimization method does all the calculations under the hood to provide an approximation of some unknown parameter. The method also offers reliable uncertainty estimates that can help a researcher understand when to trust its predictions.

This versatile technique could be applied to a wide array of scientific quandaries that incorporate Bayesian inference. For instance, it could be used by economists studying the impact of microcredit loans in developing nations or sports analysts using a model to rank top tennis players.

“When you actually dig into what people are doing in the social sciences, physics, chemistry, or biology, they are often using a lot of the same tools under the hood. There are so many Bayesian analyses out there. If we can build a really great tool that makes these researchers lives easier, then we can really make a difference to a lot of people in many different research areas,” says senior author Tamara Broderick, an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS) and a member of the Laboratory for Information and Decision Systems and the Institute for Data, Systems, and Society.

Broderick is joined on the paper by co-lead authors Ryan Giordano, an assistant professor of statistics at the University of California at Berkeley; and Martin Ingram, a data scientist at the AI company KONUX. The paper was recently published in the Journal of Machine Learning Research.

Faster results

When researchers seek a faster form of Bayesian inference, they often turn to a technique called automatic differentiation variational inference (ADVI), which is often both fast to run and easy to use.

But Broderick and her collaborators have found a number of practical issues with ADVI. It has to solve an optimization problem and can do so only approximately. So, ADVI can still require a lot of computation time and user effort to determine whether the approximate solution is good enough. And once it arrives at a solution, it tends to provide poor uncertainty estimates.

Rather than reinventing the wheel, the team took many ideas from ADVI but turned them around to create a technique called deterministic ADVI (DADVI) that doesn’t have these downsides.

With DADVI, it is very clear when the optimization is finished, so a user won’t need to spend extra computation time to ensure that the best solution has been found. DADVI also permits the incorporation of more powerful optimization methods that give it an additional speed and performance boost.

Once it reaches a result, DADVI is set up to allow the use of uncertainty corrections. These corrections make its uncertainty estimates much more accurate than those of ADVI.

DADVI also enables the user to clearly see how much error they have incurred in the approximation to the optimization problem. This prevents a user from needlessly running the optimization again and again with more and more resources to try and reduce the error.

“We wanted to see if we could live up to the promise of black-box inference in the sense of, once the user makes their model, they can just run Bayesian inference and don’t have to derive everything by hand, they don’t need to figure out when to stop their algorithm, and they have a sense of how accurate their approximate solution is,” Broderick says.

Defying conventional wisdom

DADVI can be more effective than ADVI because it uses an efficient approximation method, called sample average approximation, which estimates an unknown quantity by taking a series of exact steps.

Because the steps along the way are exact, it is clear when the objective has been reached. Plus, getting to that objective typically requires fewer steps.

Often, researchers expect sample average approximation to be more computationally intensive than a more popular method, known as stochastic gradient, which is used by ADVI. But Broderick and her collaborators showed that, in many applications, this is not the case.

“A lot of problems really do have special structure, and you can be so much more efficient and get better performance by taking advantage of that special structure. That is something we have really seen in this paper,” she adds.

They tested DADVI on a number of real-world models and datasets, including a model used by economists to evaluate the effectiveness of microcredit loans and one used in ecology to determine whether a species is present at a particular site.

Across the board, they found that DADVI can estimate unknown parameters faster and more reliably than other methods, and achieves as good or better accuracy than ADVI. Because it is easier to use than other techniques, DADVI could offer a boost to scientists in a wide variety of fields.

In the future, the researchers want to dig deeper into correction methods for uncertainty estimates so they can better understand why these corrections can produce such accurate uncertainties, and when they could fall short.

“In applied statistics, we often have to use approximate algorithms for problems that are too complex or high-dimensional to allow exact solutions to be computed in reasonable time. This new paper offers an interesting set of theory and empirical results that point to an improvement in a popular existing approximate algorithm for Bayesian inference,” says Andrew Gelman ’85, ’86, a professor of statistics and political science at Columbia University, who was not involved with the study. “As one of the team involved in the creation of that earlier work, I'm happy to see our algorithm superseded by something more stable.”

This research was supported by a National Science Foundation CAREER Award and the U.S. Office of Naval Research. 

Seated at the grand piano in MIT’s Killian Hall last fall, first-year student Jacqueline Wang played through the lively opening of Mozart’s “Sonata in B-flat major, K.333.” When she’d finished, Mi-Eun Kim, pianist and lecturer in MIT’s Music and Theater Arts Section (MTA), asked her to move to the rear of the hall. Kim tapped at an iPad. Suddenly, the sonata she'd just played poured forth again from the piano — its keys dipping and rising just as they had with Wang’s fingers on them, the resonance of its strings filling the room. Wang stood among a row of empty seats with a slightly bemused expression, taking in a repeat of her own performance.

“That was a little strange,” Wang admitted when the playback concluded, then added thoughtfully: “It sounds different from what I imagine I’m playing.”

This unusual lesson took place during a nearly three-week residency at MIT of the Steinway Spirio | r, a piano embedded with technology for live performance capture and playback. “The residency offered students, faculty, staff, and campus visitors the opportunity to engage with this new technology through a series of workshops that focused on such topics as the historical analysis of piano design, an examination of the hardware and software used by the Spirio | r, and step-by-step guidance of how to use the features,” explains Keeril Makan, head of MIT Music and Theater Arts and associate dean of the School of Humanities, Arts, and Social Sciences.

Wang was one of several residency participants to have the out-of-body experience of hearing herself play from a different vantage point, while watching the data of her performance scroll across a screen: color-coded rectangles indicating the velocity and duration of each note, an undulating line charting her use of the damper pedal. Wang was even able to edit her own performance, as she discovered when Kim suggested her rhythmic use of the pedal might be superfluous. Using the iPad interface to erase the pedaling entirely, they listened to the playback again, the notes gaining new clarity.

“See? We don’t need it,” Kim confirmed with a smile.

“When MIT’s new music building (W18) opens in spring 2025, we hope it will include this type of advanced technology. It would add value not just to Wang’s cohort of 19 piano students in the Emerson/Harris Program, which provides a total of 71 scholars and fellows with support for conservatory-level instruction in classical, jazz, and world music. But could also offer educational opportunities to a much wider swath of the MIT community,” says Makan. “Music is the fifth-most popular minor at MIT; 1,700 students enroll in music and theater arts classes each semester, and the Institute is brimming with vocalists, composers, instrumentalists, and music history students.”

According to Kim, the Spirio enables insights beyond what musicians could learn from a conventional recording; hearing playback directly from the instrument reveals sonic dimensions an MP3 can’t capture. “Speaker systems sort of crunch everything down — the highs and the lows, they all kind of sound the same. But piano solo music is very dynamic. It’s supposed to be experienced in a room,” she says.

During the Spirio | r residency, students found they could review their playing at half speed, adjust the volume of certain notes to emphasize a melody, transpose a piece to another key, or layer their performance — prerecording one hand, for example, then accompanying it live with the other.

“It helps the student be part of the learning and the teaching process,” Kim says. “If there’s a gap between what they imagined and what they hear and then they come to me and say, ‘How do I fix this?’ they’re definitely more engaged. It’s an honest representation of their playing, and the students who are humbled by it will become better pianists.”

For Wang, reflecting on her lesson with Kim, the session introduced an element she’d never experienced since beginning her piano studies at age 5. “The visual display of how long each key was played and with what velocity gave me a more precise demonstration of the ideas of voicing and evenness,” Wang says. “Playing the piano is usually dependent solely on the ears, but this combines with the auditory experience a visual experience and statistics, which helped me get a more holistic view of my playing.”

As a first-year undergraduate considering a Course 6 major (electrical engineering and computer science, or EECS), Wang was also fascinated to watch Patrick Elisha, a representative from Steinway dealer M. Steinert & Sons, disassemble the piano action to point out the optical sensors that measure the velocity of each hammer strike at 1,020 levels of sensitivity, sampled 800 times per second.

“I was amazed by the precision of the laser sensors and inductors,” says Wang. “I have just begun to take introductory-level courses in EECS and am just coming across these concepts, and this certainly made me more excited to learn more about these electrical devices and their applications. I was also intrigued that the electrical system was added onto the piano without interfering with the mechanical structure, so that when we play the Spirio, our experience with the touch and finger control was just like that of playing a usual Steinway.”

Another Emerson/Harris scholar, Víctor Quintas-Martínez, a PhD candidate in economics who resumed his lapsed piano studies during the Covid-19 pandemic, visited Killian Hall during the residency to rehearse a Fauré piano quartet with a cellist, violist, and violinist. “We did a run of certain passages and recorded the piano part. Then I listened to the strings play with the recording from the back of the hall. That gave me an idea of what I needed to adjust in terms of volume, texture, pedal, etc., to achieve a better balance. Normally, when you’re playing, because you’re sitting behind the strings and close to the piano, your perception of balance may be somewhat distorted,” he notes.

Kim cites another campus demographic ripe for exploring these types of instruments like the Spirio | r and its software: future participants in MIT’s relatively new Music Technology Master's Program, along with others across the Institute whose work intersects with the wealth of data the instrument captures. Among them is Praneeth Namburi, a research scientist at the MIT.nano Immersion Lab. Typically, Namburi focuses his neuroscience expertise on the biomechanics of dancing and expert movement. For two days during the MTA/Spirio residency, he used the sensors at the Immersion Lab, along with those of the Spirio, to analyze how pianists use their bodies.

“We used motion capture that can help us contrast the motion paths of experts such as Mi-Eun from those of students, potentially aiding in music education,” Namburi recounts, “force plates that can give scientific insights into how movement timing is organized, and ultrasound to visualize the forearm tissues during playing, which can potentially help us understand musicianship-related injuries.”

“The encounter between MTA and MIT.nano was something unique to MIT,” Kim believes. “Not only is this super useful for the music world, but it’s also very exciting for movement researchers, because playing piano is one of the most complex activities that humans do with our hands.”

In Kim’s view, that quintessentially human complexity is complemented by these kinds of technical possibilities. “Some people might think oh, it's going to replace the pianist,” she says. “But in the end it is a tool. It doesn’t replace all of the things that go into learning music. I think it's going to be an invaluable third partner: the student, the teacher, and the Spirio — or the musician, the researcher, and the Spirio. It's going to play an integral role in a lot of musical endeavors.”

The driving mission of MIT Solve is inviting new voices and proposed solutions to world problems as a way to achieve a more sustainable and equitable future for all. To that end, Solve recently announced the 2024 Global Challenges and the Indigenous Communities Fellowship to help find and scale the best. 

Solve invites anyone from anywhere in the world to submit a solution to this year’s Global Challenges by April 18. Solve is seeking solutions that use technology in innovative and equitable ways to make learning more inclusive, mitigate and adapt to the climate crisis, improve access to quality health care, build peaceful and prosperous economies, and strengthen Indigenous communities.

Selected innovators will form the 2024 Solver Class, pitch their solutions during U.N. General Assembly Week, and share over $1 million of available funding. Innovators also take part in a nine-month support program that includes capital, leadership, and community support to scale their solutions.

"MIT Solve is on a quest to find the amazing innovators solving the pressing challenges of their communities and the world. And once we select the best, we mobilize the Solve community to help them scale," says Hala Hanna, executive director of MIT Solve. "We can't do this without our generous and foresighted supporters."

Funding available for selected Solvers and fellows includes:

• MIT Solve funding: $10,000 to each Solver and fellow selected;
• GM Prize (supported by General Motors) for solutions that help create smart, safe, and sustainable communities around the world, selected from the 2024 Global Learning Challenge, the 2024 Global Climate Challenge, and the 2024 Indigenous Communities Fellowship;
• GSR Foundation Prize (supported by GSR Foundation) for solutions that use technology in an innovative way to address pressing issues in their communities, especially solutions that remove barriers to financial inclusion and place a strong emphasis on learning, selected from any 2024 Global Challenge;
• Morgridge Family Foundation AI Innovation Prize (supported by Morgridge Family Foundation) for solutions that use AI to boldly spark change through innovation, disruption, and transformation, selected from any 2024 Global Challenge or from any Solver class;
• AI for Humanity Prize (supported by The Patrick J. McGovern Foundation) for solutions that leverage data science, artificial intelligence, and/or machine learning to benefit humanity, selected from any 2024 Global Challenge; and
• Prince Albert II of Monaco Ocean Innovation Prize (supported by Prince Albert II of Monaco Foundation) for a solution that supports innovation for coasts, oceans, and the broader blue economy, selected from the 2024 Global Climate Challenge.

Additional prizes will also be announced.

The Solve community will convene on MIT’s campus for its flagship event, Solve at MIT, May 22-23 to celebrate the past 2023 Solver Class. Members of the public may request an invitation, while press interested in attending the event should contact maya.bingaman@solve.mit.edu.

You’ve likely met someone who identifies as a visual or auditory learner, but others absorb knowledge through a different modality: touch. Being able to understand tactile interactions is especially important for tasks such as learning delicate surgeries and playing musical instruments, but unlike video and audio, touch is difficult to record and transfer.

To tap into this challenge, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and elsewhere developed an embroidered smart glove that can capture, reproduce, and relay touch-based instructions. To complement the wearable device, the team also developed a simple machine-learning agent that adapts to how different users react to tactile feedback, optimizing their experience. The new system could potentially help teach people physical skills, improve responsive robot teleoperation, and assist with training in virtual reality.

An open-access paper describing the work was published in Nature Communications on Jan. 29.

Will I be able to play the piano?

To create their smart glove, the researchers used a digital embroidery machine to seamlessly embed tactile sensors and haptic actuators (a device that provides touch-based feedback) into textiles. This technology is present in smartphones, where haptic responses are triggered by tapping on the touch screen. For example, if you press down on an iPhone app, you’ll feel a slight vibration coming from that specific part of your screen. In the same way, the new adaptive wearable sends feedback to different parts of your hand to indicate optimal motions to execute different skills.

The smart glove could teach users how to play the piano, for instance. In a demonstration, an expert was tasked with recording a simple tune over a section of keys, using the smart glove to capture the sequence by which they pressed their fingers to the keyboard. Then, a machine-learning agent converted that sequence into haptic feedback, which was then fed into the students’ gloves to follow as instructions. With their hands hovering over that same section, actuators vibrated on the fingers corresponding to the keys below. The pipeline optimizes these directions for each user, accounting for the subjective nature of touch interactions.

“Humans engage in a wide variety of tasks by constantly interacting with the world around them,” says Yiyue Luo MS ’20, lead author of the paper, PhD student in MIT’s Department of Electrical Engineering and Computer Science (EECS), and CSAIL affiliate. “We don’t usually share these physical interactions with others. Instead, we often learn by observing their movements, like with piano-playing and dance routines.

“The main challenge in relaying tactile interactions is that everyone perceives haptic feedback differently,” adds Luo. “This roadblock inspired us to develop a machine-learning agent that learns to generate adaptive haptics for individuals’ gloves, introducing them to a more hands-on approach to learning optimal motion.”

The wearable system is customized to fit the specifications of a user’s hand via a digital fabrication method. A computer produces a cutout based on individuals’ hand measurements, then an embroidery machine stitches the sensors and haptics in. Within 10 minutes, the soft, fabric-based wearable is ready to wear. Initially trained on 12 users’ haptic responses, its adaptive machine-learning model only needs 15 seconds of new user data to personalize feedback.

In two other experiments, tactile directions with time-sensitive feedback were transferred to users sporting the gloves while playing laptop games. In a rhythm game, the players learned to follow a narrow, winding path to bump into a goal area, and in a racing game, drivers collected coins and maintained the balance of their vehicle on their way to the finish line. Luo’s team found that participants earned the highest game scores through optimized haptics, as opposed to without haptics and with unoptimized haptics.

“This work is the first step to building personalized AI agents that continuously capture data about the user and the environment,” says senior author Wojciech Matusik, MIT professor of electrical engineering and computer science and head of the Computational Design and Fabrication Group within CSAIL. “These agents then assist them in performing complex tasks, learning new skills, and promoting better behaviors.”

Bringing a lifelike experience to electronic settings

In robotic teleoperation, the researchers found that their gloves could transfer force sensations to robotic arms, helping them complete more delicate grasping tasks. “It’s kind of like trying to teach a robot to behave like a human,” says Luo. In one instance, the MIT team used human teleoperators to teach a robot how to secure different types of bread without deforming them. By teaching optimal grasping, humans could precisely control the robotic systems in environments like manufacturing, where these machines could collaborate more safely and effectively with their operators.

“The technology powering the embroidered smart glove is an important innovation for robots,” says Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT, CSAIL director, and author on the paper. “With its ability to capture tactile interactions at high resolution, akin to human skin, this sensor enables robots to perceive the world through touch. The seamless integration of tactile sensors into textiles bridges the divide between physical actions and digital feedback, offering vast potential in responsive robot teleoperation and immersive virtual reality training.”

Likewise, the interface could create more immersive experiences in virtual reality. Wearing smart gloves would add tactile sensations to digital environments in video games, where gamers could feel around their surroundings to avoid obstacles. Additionally, the interface would provide a more personalized and touch-based experience in virtual training courses used by surgeons, firefighters, and pilots, where precision is paramount.

While these wearables could provide a more hands-on experience for users, Luo and her group believe they could extend their wearable technology beyond fingers. With stronger haptic feedback, the interfaces could guide feet, hips, and other body parts less sensitive than hands.

Luo also noted that with a more complex artificial intelligence agent, her team's technology could assist with more involved tasks, like manipulating clay or driving an airplane. Currently, the interface can only assist with simple motions like pressing a key or gripping an object. In the future, the MIT system could incorporate more user data and fabricate more conformal and tight wearables to better account for how hand movements impact haptic perceptions.

Luo, Matusik, and Rus authored the paper with EECS Microsystems Technology Laboratories Director and Professor Tomás Palacios; CSAIL members Chao Liu, Young Joong Lee, Joseph DelPreto, Michael Foshey, and professor and principal investigator Antonio Torralba; Kiu Wu of LightSpeed Studios; and Yunzhu Li of the University of Illinois at Urbana-Champaign.

The work was supported, in part, by an MIT Schwarzman College of Computing Fellowship via Google and a GIST-MIT Research Collaboration grant, with additional help from Wistron, Toyota Research Institute, and Ericsson.