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      Seizing solar’s bright future

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      Consider the dizzying ascent of solar energy in the United States: In the past decade, solar capacity increased nearly 900 percent, with electricity production eight times greater in 2023 than in 2014. The jump from 2022 to 2023 alone was 51 percent, with a record 32 gigawatts (GW) of solar installations coming online. In the past four years, more solar has been added to the grid than any other form of generation. Installed solar now tops 179 GW, enough to power nearly 33 million homes. The U.S. Department of Energy (DOE) is so bullish on the sun that its decarbonization plans envision solar satisfying 45 percent of the nation’s electricity demands by 2050.But the continued rapid expansion of solar requires advances in technology, notably to improve the efficiency and durability of solar photovoltaic (PV) materials and manufacturing. That’s where Optigon, a three-year-old MIT spinout company, comes in.“Our goal is to build tools for research and industry that can accelerate the energy transition,” says Dane deQuilettes, the company’s co-founder and chief science officer. “The technology we have developed for solar will enable measurements and analysis of materials as they are being made both in lab and on the manufacturing line, dramatically speeding up the optimization of PV.”With roots in MIT’s vibrant solar research community, Optigon is poised for a 2024 rollout of technology it believes will drastically pick up the pace of solar power and other clean energy projects.Beyond siliconSilicon, the material mainstay of most PV, is limited by the laws of physics in the efficiencies it can achieve converting photons from the sun into electrical energy. Silicon-based solar cells can theoretically reach power conversion levels of just 30 percent, and real-world efficiency levels hover in the low 20s. But beyond the physical limitations of silicon, there is another issue at play for many researchers and the solar industry in the United States and elsewhere: China dominates the silicon PV market, from supply chains to manufacturing.Scientists are eagerly pursuing alternative materials, either for enhancing silicon’s solar conversion capacity or for replacing silicon altogether.In the past decade, a family of crystal-structured semiconductors known as perovskites has risen to the fore as a next-generation PV material candidate. Perovskite devices lend themselves to a novel manufacturing process using printing technology that could circumvent the supply chain juggernaut China has built for silicon. Perovskite solar cells can be stacked on each other or layered atop silicon PV, to achieve higher conversion efficiencies. Because perovskite technology is flexible and lightweight, modules can be used on roofs and other structures that cannot support heavier silicon PV, lowering costs and enabling a wider range of building-integrated solar devices.But these new materials require testing, both during R&D and then on assembly lines, where missing or defective optical, electrical, or dimensional properties in the nano-sized crystal structures can negatively impact the end product.“The actual measurement and data analysis processes have been really, really slow, because you have to use a bunch of separate tools that are all very manual,” says Optigon co-founder and chief executive officer Anthony Troupe ’21. “We wanted to come up with tools for automating detection of a material’s properties, for determining whether it could make a good or bad solar cell, and then for optimizing it.”“Our approach packed several non-contact, optical measurements using different types of light sources and detectors into a single system, which together provide a holistic, cross-sectional view of the material,” says Brandon Motes ’21, ME ’22, co-founder and chief technical officer.“This breakthrough in achieving millisecond timescales for data collection and analysis means we can take research-quality tools and actually put them on a full production system, getting extremely detailed information about products being built at massive, gigawatt scale in real-time,” says Troupe.This streamlined system takes measurements “in the snap of the fingers, unlike the traditional tools,” says Joseph Berry, director of the US Manufacturing of Advanced Perovskites Consortium and a senior research scientist at the National Renewable Energy Laboratory. “Optigon’s techniques are high precision and allow high throughput, which means they can be used in a lot of contexts where you want rapid feedback and the ability to develop materials very, very quickly.”According to Berry, Optigon’s technology may give the solar industry not just better materials, but the ability to pump out high-quality PV products at a brisker clip than is currently possible. “If Optigon is successful in deploying their technology, then we can more rapidly develop the materials that we need, manufacturing with the requisite precision again and again,” he says. “This could lead to the next generation of PV modules at a much, much lower cost.”Measuring makes the differenceWith Small Business Innovation Research funding from DOE to commercialize its products and a grant from the Massachusetts Clean Energy Center, Optigon has settled into a space at the climate technology incubator Greentown Labs in Somerville, Massachusetts. Here, the team is preparing for this spring’s launch of its first commercial product, whose genesis lies in MIT’s GridEdge Solar Research Program.Led by Vladimir Bulović, a professor of electrical engineering and the director of MIT.nano, the GridEdge program was established with funding from the Tata Trusts to develop lightweight, flexible, and inexpensive solar cells for distribution to rural communities around the globe. When deQuilettes joined the group in 2017 as a postdoc, he was tasked with directing the program and building the infrastructure to study and make perovskite solar modules.“We were trying to understand once we made the material whether or not it was good,” he recalls. “There were no good commercial metrology [the science of measurements] tools for materials beyond silicon, so we started to build our own.” Recognizing the group’s need for greater expertise on the problem, especially in the areas of electrical, software, and mechanical engineering, deQuilettes put a call out for undergraduate researchers to help build metrology tools for new solar materials.“Forty people inquired, but when I met Brandon and Anthony, something clicked; it was clear we had a complementary skill set,” says deQuilettes. “We started working together, with Anthony coming up with beautiful designs to integrate multiple measurements, and Brandon creating boards to control all of the hardware, including different types of lasers. We started filing multiple patents and that was when we saw it all coming together.”“We knew from the start that metrology could vastly improve not just materials, but production yields,” says Troupe. Adds deQuilettes, “Our goal was getting to the highest performance orders of magnitude faster than it would ordinarily take, so we developed tools that would not just be useful for research labs but for manufacturing lines to give live feedback on quality.”The device Optigon designed for industry is the size of a football, “with sensor packages crammed into a tiny form factor, taking measurements as material flows directly underneath,” says Motes. “We have also thought carefully about ways to make interaction with this tool as seamless and, dare I say, as enjoyable as possible, streaming data to both a dashboard an operator can watch and to a custom database.”Photovoltaics is just the startThe company may have already found its market niche. “A research group paid us to use our in-house prototype because they have such a burning need to get these sorts of measurements,” says Troupe, and according to Motes, “Potential customers ask us if they can buy the system now.” deQuilettes says, “Our hope is that we become the de facto company for doing any sort of characterization metrology in the United States and beyond.”Challenges lie ahead for Optigon: product launches, full-scale manufacturing, technical assistance, and sales. Greentown Labs offers support, as does MIT’s own rich community of solar researchers and entrepreneurs. But the founders are already thinking about next phases.“We are not limiting ourselves to the photovoltaics area,” says deQuilettes. “We’re planning on working in other clean energy materials such as batteries and fuel cells.”That’s because the team wants to make the maximum impact on the climate challenge. “We’ve thought a lot about the potential our tools will have on reducing carbon emissions, and we’ve done a really in-depth analysis looking at how our system can increase production yields of solar panels and other energy technologies, reducing materials and energy wasted in conventional optimization,” deQuilettes says. “If we look across all these sectors, we can expect to offset about 1,000 million metric tons of CO2 [carbon dioxide] per year in the not-too-distant future.”The team has written scale into its business plan. “We want to be the key enabler for bringing these new energy technologies to market,” says Motes. “We envision being deployed on every manufacturing line making these types of materials. It’s our goal to walk around and know that if we see a solar panel deployed, there’s a pretty high likelihood that it will be one we measured at some point.” More

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      in Environment

      HPI-MIT design research collaboration creates powerful teams

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      The recent ransomware attack on ChangeHealthcare, which severed the network connecting health care providers, pharmacies, and hospitals with health insurance companies, demonstrates just how disruptive supply chain attacks can be. In this case, it hindered the ability of those providing medical services to submit insurance claims and receive payments.This sort of attack and other forms of data theft are becoming increasingly common and often target large, multinational corporations through the small and mid-sized vendors in their corporate supply chains, enabling breaks in these enormous systems of interwoven companies.Cybersecurity researchers at MIT and the Hasso Plattner Institute (HPI) in Potsdam, Germany, are focused on the different organizational security cultures that exist within large corporations and their vendors because it’s that difference that creates vulnerabilities, often due to the lack of emphasis on cybersecurity by the senior leadership in these small to medium-sized enterprises (SMEs).Keri Pearlson, executive director of Cybersecurity at MIT Sloan (CAMS); Jillian Kwong, a research scientist at CAMS; and Christian Doerr, a professor of cybersecurity and enterprise security at HPI, are co-principal investigators (PIs) on the research project, “Culture and the Supply Chain: Transmitting Shared Values, Attitudes and Beliefs across Cybersecurity Supply Chains.”Their project was selected in the 2023 inaugural round of grants from the HPI-MIT Designing for Sustainability program, a multiyear partnership funded by HPI and administered by the MIT Morningside Academy for Design (MAD). The program awards about 10 grants annually of up to $200,000 each to multidisciplinary teams with divergent backgrounds in computer science, artificial intelligence, machine learning, engineering, design, architecture, the natural sciences, humanities, and business and management. The 2024 Call for Applications is open through June 3.Designing for Sustainability grants support scientific research that promotes the United Nations’ Sustainable Development Goals (SDGs) on topics involving sustainable design, innovation, and digital technologies, with teams made up of PIs from both institutions. The PIs on these projects, who have common interests but different strengths, create more powerful teams by working together.Transmitting shared values, attitudes, and beliefs to improve cybersecurity across supply chainsThe MIT and HPI cybersecurity researchers say that most ransomware attacks aren’t reported. Smaller companies hit with ransomware attacks just shut down, because they can’t afford the payment to retrieve their data. This makes it difficult to know just how many attacks and data breaches occur. “As more data and processes move online and into the cloud, it becomes even more important to focus on securing supply chains,” Kwong says. “Investing in cybersecurity allows information to be exchanged freely while keeping data safe. Without it, any progress towards sustainability is stalled.”One of the first large data breaches in the United States to be widely publicized provides a clear example of how an SME cybersecurity can leave a multinational corporation vulnerable to attack. In 2013, hackers entered the Target Corporation’s own network by obtaining the credentials of a small vendor in its supply chain: a Pennsylvania HVAC company. Through that breach, thieves were able to install malware that stole the financial and personal information of 110 million Target customers, which they sold to card shops on the black market.To prevent such attacks, SME vendors in a large corporation’s supply chain are required to agree to follow certain security measures, but the SMEs usually don’t have the expertise or training to make good on these cybersecurity promises, leaving their own systems, and therefore any connected to them, vulnerable to attack.“Right now, organizations are connected economically, but not aligned in terms of organizational culture, values, beliefs, and practices around cybersecurity,” explains Kwong. “Basically, the big companies are realizing the smaller ones are not able to implement all the cybersecurity requirements. We have seen some larger companies address this by reducing requirements or making the process shorter. However, this doesn’t mean companies are more secure; it just lowers the bar for the smaller suppliers to clear it.”Pearlson emphasizes the importance of board members and senior management taking responsibility for cybersecurity in order to change the culture at SMEs, rather than pushing that down to a single department, IT office, or in some cases, one IT employee.The research team is using case studies based on interviews, field studies, focus groups, and direct observation of people in their natural work environments to learn how companies engage with vendors, and the specific ways cybersecurity is implemented, or not, in everyday operations. The goal is to create a shared culture around cybersecurity that can be adopted correctly by all vendors in a supply chain.This approach is in line with the goals of the Charter of Trust Initiative, a partnership of large, multinational corporations formed to establish a better means of implementing cybersecurity in the supply chain network. The HPI-MIT team worked with companies from the Charter of Trust and others last year to understand the impacts of cybersecurity regulation on SME participation in supply chains and develop a conceptual framework to implement changes for stabilizing supply chains.Cybersecurity is a prerequisite needed to achieve any of the United Nations’ SDGs, explains Kwong. Without secure supply chains, access to key resources and institutions can be abruptly cut off. This could include food, clean water and sanitation, renewable energy, financial systems, health care, education, and resilient infrastructure. Securing supply chains helps enable progress on all SDGs, and the HPI-MIT project specifically supports SMEs, which are a pillar of the U.S. and European economies.Personalizing product designs while minimizing material wasteIn a vastly different Designing for Sustainability joint research project that employs AI with engineering, “Personalizing Product Designs While Minimizing Material Waste” will use AI design software to lay out multiple parts of a pattern on a sheet of plywood, acrylic, or other material, so that they can be laser cut to create new products in real time without wasting material.Stefanie Mueller, the TIBCO Career Development Associate Professor in the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory, and Patrick Baudisch, a professor of computer science and chair of the Human Computer Interaction Lab at HPI, are co-PIs on the project. The two have worked together for years; Baudisch was Mueller’s PhD research advisor at HPI.Baudisch’s lab developed an online design teaching system called Kyub that lets students design 3D objects in pieces that are laser cut from sheets of wood and assembled to become chairs, speaker boxes, radio-controlled aircraft, or even functional musical instruments. For instance, each leg of a chair would consist of four identical vertical pieces attached at the edges to create a hollow-centered column, four of which will provide stability to the chair, even though the material is very lightweight.“By designing and constructing such furniture, students learn not only design, but also structural engineering,” Baudisch says. “Similarly, by designing and constructing musical instruments, they learn about structural engineering, as well as resonance, types of musical tuning, etc.”Mueller was at HPI when Baudisch developed the Kyub software, allowing her to observe “how they were developing and making all the design decisions,” she says. “They built a really neat piece for people to quickly design these types of 3D objects.” However, using Kyub for material-efficient design is not fast; in order to fabricate a model, the software has to break the 3D models down into 2D parts and lay these out on sheets of material. This takes time, and makes it difficult to see the impact of design decisions on material use in real-time.Mueller’s lab at MIT developed software based on a layout algorithm that uses AI to lay out pieces on sheets of material in real time. This allows AI to explore multiple potential layouts while the user is still editing, and thus provide ongoing feedback. “As the user develops their design, Fabricaide decides good placements of parts onto the user’s available materials, provides warnings if the user does not have enough material for a design, and makes suggestions for how the user can resolve insufficient material cases,” according to the project website.The joint MIT-HPI project integrates Mueller’s AI software with Baudisch’s Kyub software and adds machine learning to train the AI to offer better design suggestions that save material while adhering to the user’s design intent.“The project is all about minimizing the waste on these materials sheets,” Mueller says. She already envisions the next step in this AI design process: determining how to integrate the laws of physics into the AI’s knowledge base to ensure the structural integrity and stability of objects it designs.AI-powered startup design for the Anthropocene: Providing guidance for novel enterprisesThrough her work with the teams of MITdesignX and its international programs, Svafa Grönfeldt, faculty director of MITdesignX and professor of the practice in MIT MAD, has helped scores of people in startup companies use the tools and methods of design to ensure that the solution a startup proposes actually fits the problem it seeks to solve. This is often called the problem-solution fit.Grönfeldt and MIT postdoc Norhan Bayomi are now extending this work to incorporate AI into the process, in collaboration with MIT Professor John Fernández and graduate student Tyler Kim. The HPI team includes Professor Gerard de Melo; HPI School of Entrepreneurship Director Frank Pawlitschek; and doctoral student Michael Mansfeld.“The startup ecosystem is characterized by uncertainty and volatility compounded by growing uncertainties in climate and planetary systems,” Grönfeldt says. “Therefore, there is an urgent need for a robust model that can objectively predict startup success and guide design for the Anthropocene.”While startup-success forecasting is gaining popularity, it currently focuses on aiding venture capitalists in selecting companies to fund, rather than guiding the startups in the design of their products, services and business plans.“The coupling of climate and environmental priorities with startup agendas requires deeper analytics for effective enterprise design,” Grönfeldt says. The project aims to explore whether AI-augmented decision-support systems can enhance startup-success forecasting.“We’re trying to develop a machine learning approach that will give a forecasting of probability of success based on a number of parameters, including the type of business model proposed, how the team came together, the team members’ backgrounds and skill sets, the market and industry sector they’re working in and the problem-solution fit,” says Bayomi, who works with Fernández in the MIT Environmental Solutions Initiative. The two are co-founders of the startup Lamarr.AI, which employs robotics and AI to help reduce the carbon dioxide impact of the built environment.The team is studying “how company founders make decisions across four key areas, starting from the opportunity recognition, how they are selecting the team members, how they are selecting the business model, identifying the most automatic strategy, all the way through the product market fit to gain an understanding of the key governing parameters in each of these areas,” explains Bayomi.The team is “also developing a large language model that will guide the selection of the business model by using large datasets from different companies in Germany and the U.S. We train the model based on the specific industry sector, such as a technology solution or a data solution, to find what would be the most suitable business model that would increase the success probability of a company,” she says.The project falls under several of the United Nations’ Sustainable Development Goals, including economic growth, innovation and infrastructure, sustainable cities and communities, and climate action.Furthering the goals of the HPI-MIT Joint Research ProgramThese three diverse projects all advance the mission of the HPI-MIT collaboration. MIT MAD aims to use design to transform learning, catalyze innovation, and empower society by inspiring people from all disciplines to interweave design into problem-solving. HPI uses digital engineering concentrated on the development and research of user-oriented innovations for all areas of life.Interdisciplinary teams with members from both institutions are encouraged to develop and submit proposals for ambitious, sustainable projects that use design strategically to generate measurable, impactful solutions to the world’s problems. More

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      in Energy

      Nuno Loureiro named director of MIT’s Plasma Science and Fusion Center

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      Nuno Loureiro, professor of nuclear science and engineering and of physics, has been appointed the new director of the MIT Plasma Science and Fusion Center, effective May 1.Loureiro is taking the helm of one of MIT’s largest labs: more than 250 full-time researchers, staff members, and students work and study in seven buildings with 250,000 square feet of lab space. A theoretical physicist and fusion scientist, Loureiro joined MIT as a faculty member in 2016, and was appointed deputy director of the Plasma Science and Fusion Center (PSFC) in 2022. Loureiro succeeds Dennis Whyte, who stepped down at the end of 2023 to return to teaching and research.Stepping into his new role as director, Loureiro says, “The PSFC has an impressive tradition of discovery and leadership in plasma and fusion science and engineering. Becoming director of the PSFC is an incredible opportunity to shape the future of these fields. We have a world-class team, and it’s an honor to be chosen as its leader.”Loureiro’s own research ranges widely. He is recognized for advancing the understanding of multiple aspects of plasma behavior, particularly turbulence and the physics underpinning solar flares and other astronomical phenomena. In the fusion domain, his work enables the design of fusion devices that can more efficiently control and harness the energy of fusing plasmas, bringing the dream of clean, near-limitless fusion power that much closer. Plasma physics is foundational to advancing fusion science, a fact Loureiro has embraced and that is relevant as he considers the direction of the PSFC’s multidisciplinary research. “But plasma physics is only one aspect of our focus. Building a scientific agenda that continues and expands on the PSFC’s history of innovation in all aspects of fusion science and engineering is vital, and a key facet of that work is facilitating our researchers’ efforts to produce the breakthroughs that are necessary for the realization of fusion energy.”As the climate crisis accelerates, fusion power continues to grow in appeal: It produces no carbon emissions, its fuel is plentiful, and dangerous “meltdowns” are impossible. The sooner that fusion power is commercially available, the greater impact it can have on reducing greenhouse gas emissions and meeting global climate goals. While technical challenges remain, “the PSFC is well poised to meet them, and continue to show leadership. We are a mission-driven lab, and our students and staff are incredibly motivated,” Loureiro comments.“As MIT continues to lead the way toward the delivery of clean fusion power onto the grid, I have no doubt that Nuno is the right person to step into this key position at this critical time,” says Maria T. Zuber, MIT’s presidential advisor for science and technology policy. “I look forward to the steady advance of plasma physics and fusion science at MIT under Nuno’s leadership.”Over the last decade, there have been massive leaps forward in the field of fusion energy, driven in part by innovations like high-temperature superconducting magnets developed at the PSFC. Further progress is guaranteed: Loureiro believes that “The next few years are certain to be an exciting time for us, and for fusion as a whole. It’s the dawn of a new era with burning plasma experiments” — a reference to the collaboration between the PSFC and Commonwealth Fusion Systems, a startup company spun out of the PSFC, to build SPARC, a fusion device that is slated to turn on in 2026 and produce a burning plasma that yields more energy than it consumes. “It’s going to be a watershed moment,” says Loureiro.He continues, “In addition, we have strong connections to inertial confinement fusion experiments, including those at Lawrence Livermore National Lab, and we’re looking forward to expanding our research into stellarators, which are another kind of magnetic fusion device.” Over recent years, the PSFC has significantly increased its collaboration with industrial partners such Eni, IBM, and others. Loureiro sees great value in this: “These collaborations are mutually beneficial: they allow us to grow our research portfolio while advancing companies’ R&D efforts. It’s very dynamic and exciting.”Loureiro’s directorship begins as the PSFC is launching key tech development projects like LIBRA, a “blanket” of molten salt that can be wrapped around fusion vessels and perform double duty as a neutron energy absorber and a breeder for tritium (the fuel for fusion). Researchers at the PSFC have also developed a way to rapidly test the durability of materials being considered for use in a fusion power plant environment, and are now creating an experiment that will utilize a powerful particle accelerator called a gyrotron to irradiate candidate materials.Interest in fusion is at an all-time high; the demand for researchers and engineers, particularly in the nascent commercial fusion industry, is reflected by the record number of graduate students that are studying at the PSFC — more than 90 across seven affiliated MIT departments. The PSFC’s classrooms are full, and Loureiro notes a palpable sense of excitement. “Students are our greatest strength,” says Loureiro. “They come here to do world-class research but also to grow as individuals, and I want to give them a great place to do that. Supporting those experiences, making sure they can be as successful as possible is one of my top priorities.” Loureiro plans to continue teaching and advising students after his appointment begins.MIT President Sally Kornbluth’s recently announced Climate Project is a clarion call for Loureiro: “It’s not hyperbole to say MIT is where you go to find solutions to humanity’s biggest problems,” he says. “Fusion is a hard problem, but it can be solved with resolve and ingenuity — characteristics that define MIT. Fusion energy will change the course of human history. It’s both humbling and exciting to be leading a research center that will play a key role in enabling that change.”  More

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      in Environment

      An AI dataset carves new paths to tornado detection

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      The return of spring in the Northern Hemisphere touches off tornado season. A tornado’s twisting funnel of dust and debris seems an unmistakable sight. But that sight can be obscured to radar, the tool of meteorologists. It’s hard to know exactly when a tornado has formed, or even why.

      A new dataset could hold answers. It contains radar returns from thousands of tornadoes that have hit the United States in the past 10 years. Storms that spawned tornadoes are flanked by other severe storms, some with nearly identical conditions, that never did. MIT Lincoln Laboratory researchers who curated the dataset, called TorNet, have now released it open source. They hope to enable breakthroughs in detecting one of nature’s most mysterious and violent phenomena.

      “A lot of progress is driven by easily available, benchmark datasets. We hope TorNet will lay a foundation for machine learning algorithms to both detect and predict tornadoes,” says Mark Veillette, the project’s co-principal investigator with James Kurdzo. Both researchers work in the Air Traffic Control Systems Group. 

      Along with the dataset, the team is releasing models trained on it. The models show promise for machine learning’s ability to spot a twister. Building on this work could open new frontiers for forecasters, helping them provide more accurate warnings that might save lives. 

      Swirling uncertainty

      About 1,200 tornadoes occur in the United States every year, causing millions to billions of dollars in economic damage and claiming 71 lives on average. Last year, one unusually long-lasting tornado killed 17 people and injured at least 165 others along a 59-mile path in Mississippi.  

      Yet tornadoes are notoriously difficult to forecast because scientists don’t have a clear picture of why they form. “We can see two storms that look identical, and one will produce a tornado and one won’t. We don’t fully understand it,” Kurdzo says.

      A tornado’s basic ingredients are thunderstorms with instability caused by rapidly rising warm air and wind shear that causes rotation. Weather radar is the primary tool used to monitor these conditions. But tornadoes lay too low to be detected, even when moderately close to the radar. As the radar beam with a given tilt angle travels further from the antenna, it gets higher above the ground, mostly seeing reflections from rain and hail carried in the “mesocyclone,” the storm’s broad, rotating updraft. A mesocyclone doesn’t always produce a tornado.

      With this limited view, forecasters must decide whether or not to issue a tornado warning. They often err on the side of caution. As a result, the rate of false alarms for tornado warnings is more than 70 percent. “That can lead to boy-who-cried-wolf syndrome,” Kurdzo says.  

      In recent years, researchers have turned to machine learning to better detect and predict tornadoes. However, raw datasets and models have not always been accessible to the broader community, stifling progress. TorNet is filling this gap.

      The dataset contains more than 200,000 radar images, 13,587 of which depict tornadoes. The rest of the images are non-tornadic, taken from storms in one of two categories: randomly selected severe storms or false-alarm storms (those that led a forecaster to issue a warning but that didn’t produce a tornado).

      Each sample of a storm or tornado comprises two sets of six radar images. The two sets correspond to different radar sweep angles. The six images portray different radar data products, such as reflectivity (showing precipitation intensity) or radial velocity (indicating if winds are moving toward or away from the radar).

      A challenge in curating the dataset was first finding tornadoes. Within the corpus of weather radar data, tornadoes are extremely rare events. The team then had to balance those tornado samples with difficult non-tornado samples. If the dataset were too easy, say by comparing tornadoes to snowstorms, an algorithm trained on the data would likely over-classify storms as tornadic.

      “What’s beautiful about a true benchmark dataset is that we’re all working with the same data, with the same level of difficulty, and can compare results,” Veillette says. “It also makes meteorology more accessible to data scientists, and vice versa. It becomes easier for these two parties to work on a common problem.”

      Both researchers represent the progress that can come from cross-collaboration. Veillette is a mathematician and algorithm developer who has long been fascinated by tornadoes. Kurdzo is a meteorologist by training and a signal processing expert. In grad school, he chased tornadoes with custom-built mobile radars, collecting data to analyze in new ways.

      “This dataset also means that a grad student doesn’t have to spend a year or two building a dataset. They can jump right into their research,” Kurdzo says.

      This project was funded by Lincoln Laboratory’s Climate Change Initiative, which aims to leverage the laboratory’s diverse technical strengths to help address climate problems threatening human health and global security.

      Chasing answers with deep learning

      Using the dataset, the researchers developed baseline artificial intelligence (AI) models. They were particularly eager to apply deep learning, a form of machine learning that excels at processing visual data. On its own, deep learning can extract features (key observations that an algorithm uses to make a decision) from images across a dataset. Other machine learning approaches require humans to first manually label features. 

      “We wanted to see if deep learning could rediscover what people normally look for in tornadoes and even identify new things that typically aren’t searched for by forecasters,” Veillette says.

      The results are promising. Their deep learning model performed similar to or better than all tornado-detecting algorithms known in literature. The trained algorithm correctly classified 50 percent of weaker EF-1 tornadoes and over 85 percent of tornadoes rated EF-2 or higher, which make up the most devastating and costly occurrences of these storms.

      They also evaluated two other types of machine-learning models, and one traditional model to compare against. The source code and parameters of all these models are freely available. The models and dataset are also described in a paper submitted to a journal of the American Meteorological Society (AMS). Veillette presented this work at the AMS Annual Meeting in January.

      “The biggest reason for putting our models out there is for the community to improve upon them and do other great things,” Kurdzo says. “The best solution could be a deep learning model, or someone might find that a non-deep learning model is actually better.”

      TorNet could be useful in the weather community for others uses too, such as for conducting large-scale case studies on storms. It could also be augmented with other data sources, like satellite imagery or lightning maps. Fusing multiple types of data could improve the accuracy of machine learning models.

      Taking steps toward operations

      On top of detecting tornadoes, Kurdzo hopes that models might help unravel the science of why they form.

      “As scientists, we see all these precursors to tornadoes — an increase in low-level rotation, a hook echo in reflectivity data, specific differential phase (KDP) foot and differential reflectivity (ZDR) arcs. But how do they all go together? And are there physical manifestations we don’t know about?” he asks.

      Teasing out those answers might be possible with explainable AI. Explainable AI refers to methods that allow a model to provide its reasoning, in a format understandable to humans, of why it came to a certain decision. In this case, these explanations might reveal physical processes that happen before tornadoes. This knowledge could help train forecasters, and models, to recognize the signs sooner. 

      “None of this technology is ever meant to replace a forecaster. But perhaps someday it could guide forecasters’ eyes in complex situations, and give a visual warning to an area predicted to have tornadic activity,” Kurdzo says.

      Such assistance could be especially useful as radar technology improves and future networks potentially grow denser. Data refresh rates in a next-generation radar network are expected to increase from every five minutes to approximately one minute, perhaps faster than forecasters can interpret the new information. Because deep learning can process huge amounts of data quickly, it could be well-suited for monitoring radar returns in real time, alongside humans. Tornadoes can form and disappear in minutes.

      But the path to an operational algorithm is a long road, especially in safety-critical situations, Veillette says. “I think the forecaster community is still, understandably, skeptical of machine learning. One way to establish trust and transparency is to have public benchmark datasets like this one. It’s a first step.”

      The next steps, the team hopes, will be taken by researchers across the world who are inspired by the dataset and energized to build their own algorithms. Those algorithms will in turn go into test beds, where they’ll eventually be shown to forecasters, to start a process of transitioning into operations.

      In the end, the path could circle back to trust.

      “We may never get more than a 10- to 15-minute tornado warning using these tools. But if we could lower the false-alarm rate, we could start to make headway with public perception,” Kurdzo says. “People are going to use those warnings to take the action they need to save their lives.” More

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      in Environment

      Two MIT teams selected for NSF sustainable materials grants

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      Two teams led by MIT researchers were selected in December 2023 by the U.S. National Science Foundation (NSF) Convergence Accelerator, a part of the TIP Directorate, to receive awards of $5 million each over three years, to pursue research aimed at helping to bring cutting-edge new sustainable materials and processes from the lab into practical, full-scale industrial production. The selection was made after 16 teams from around the country were chosen last year for one-year grants to develop detailed plans for further research aimed at solving problems of sustainability and scalability for advanced electronic products.

      Of the two MIT-led teams chosen for this current round of funding, one team, Topological Electric, is led by Mingda Li, an associate professor in the Department of Nuclear Science and Engineering. This team will be finding pathways to scale up sustainable topological materials, which have the potential to revolutionize next-generation microelectronics by showing superior electronic performance, such as dissipationless states or high-frequency response. The other team, led by Anuradha Agarwal, a principal research scientist at MIT’s Materials Research Laboratory, will be focusing on developing new materials, devices, and manufacturing processes for microchips that minimize energy consumption using electronic-photonic integration, and that detect and avoid the toxic or scarce materials used in today’s production methods.

      Scaling the use of topological materials

      Li explains that some materials based on quantum effects have achieved successful transitions from lab curiosities to successful mass production, such as blue-light LEDs, and giant magnetorestance (GMR) devices used for magnetic data storage. But he says there are a variety of equally promising materials that have shown promise but have yet to make it into real-world applications.

      “What we really wanted to achieve is to bring newer-generation quantum materials into technology and mass production, for the benefit of broader society,” he says. In particular, he says, “topological materials are really promising to do many different things.”

      Topological materials are ones whose electronic properties are fundamentally protected against disturbance. For example, Li points to the fact that just in the last two years, it has been shown that some topological materials are even better electrical conductors than copper, which are typically used for the wires interconnecting electronic components. But unlike the blue-light LEDs or the GMR devices, which have been widely produced and deployed, when it comes to topological materials, “there’s no company, no startup, there’s really no business out there,” adds Tomas Palacios, the Clarence J. Lebel Professor in Electrical Engineering at MIT and co-principal investigator on Li’s team. Part of the reason is that many versions of such materials are studied “with a focus on fundamental exotic physical properties with little or no consideration on the sustainability aspects,” says Liang Fu, an MIT professor of physics and also a co-PI. Their team will be looking for alternative formulations that are more amenable to mass production.

      One possible application of these topological materials is for detecting terahertz radiation, explains Keith Nelson, an MIT professor of chemistry and co-PI. This extremely high-frequency electronics can carry far more information than conventional radio or microwaves, but at present there are no mature electronic devices available that are scalable at this frequency range. “There’s a whole range of possibilities for topological materials” that could work at these frequencies, he says. In addition, he says, “we hope to demonstrate an entire prototype system like this in a single, very compact solid-state platform.”

      Li says that among the many possible applications of topological devices for microelectronics devices of various kinds, “we don’t know which, exactly, will end up as a product, or will reach real industrial scaleup. That’s why this opportunity from NSF is like a bridge, which is precious, to allow us to dig deeper to unleash the true potential.”

      In addition to Li, Palacios, Fu, and Nelson, the Topological Electric team includes Qiong Ma, assistant professor of physics in Boston College; Farnaz Niroui, assistant professor of electrical engineering and computer science at MIT; Susanne Stemmer, professor of materials at the University of California at Santa Barbara; Judy Cha, professor of materials science and engineering at Cornell University; industrial partners including IBM, Analog Devices, and Raytheon; and professional consultants. “We are taking this opportunity seriously,” Li says. “We really want to see if the topological materials are as good as we show in the lab when being scaled up, and how far we can push to broadly industrialize them.”

      Toward sustainable microchip production and use

      The microchips behind everything from smartphones to medical imaging are associated with a significant percentage of greenhouse gas emissions today, and every year the world produces more than 50 million metric tons of electronic waste, the equivalent of about 5,000 Eiffel Towers. Further, the data centers necessary for complex computations and huge amount of data transfer — think AI and on-demand video — are growing and will require 10 percent of the world’s electricity by 2030.

      “The current microchip manufacturing supply chain, which includes production, distribution, and use, is neither scalable nor sustainable, and cannot continue. We must innovate our way out of this crisis,” says Agarwal.

      The name of Agarwal’s team, FUTUR-IC, is a reference to the future of the integrated circuits, or chips, through a global alliance for sustainable microchip manufacturing. Says Agarwal, “We bring together stakeholders from industry, academia, and government to co-optimize across three dimensions: technology, ecology, and workforce. These were identified as key interrelated areas by some 140 stakeholders. With FUTUR-IC we aim to cut waste and CO2-equivalent emissions associated with electronics by 50 percent every 10 years.”

      The market for microelectronics in the next decade is predicted to be on the order of a trillion dollars, but most of the manufacturing for the industry occurs only in limited geographical pockets around the world. FUTUR-IC aims to diversify and strengthen the supply chain for manufacturing and packaging of electronics. The alliance has 26 collaborators and is growing. Current external collaborators include the International Electronics Manufacturing Initiative (iNEMI), Tyndall National Institute, SEMI, Hewlett Packard Enterprise, Intel, and the Rochester Institute of Technology.

      Agarwal leads FUTUR-IC in close collaboration with others, including, from MIT, Lionel Kimerling, the Thomas Lord Professor of Materials Science and Engineering; Elsa Olivetti, the Jerry McAfee Professor in Engineering; Randolph Kirchain, principal research scientist in the Materials Research Laboratory; and Greg Norris, director of MIT’s Sustainability and Health Initiative for NetPositive Enterprise (SHINE). All are affiliated with the Materials Research Laboratory. They are joined by Samuel Serna, an MIT visiting professor and assistant professor of physics at Bridgewater State University. Other key personnel include Sajan Saini, education director for the Initiative for Knowledge and Innovation in Manufacturing in MIT’s Department of Materials Science and Engineering; Peter O’Brien, a professor from Tyndall National Institute; and Shekhar Chandrashekhar, CEO of iNEMI.

      “We expect the integration of electronics and photonics to revolutionize microchip manufacturing, enhancing efficiency, reducing energy consumption, and paving the way for unprecedented advancements in computing speed and data-processing capabilities,” says Serna, who is the co-lead on the project’s technology “vector.”

      Common metrics for these efforts are needed, says Norris, co-lead for the ecology vector, adding, “The microchip industry must have transparent and open Life Cycle Assessment (LCA) models and data, which are being developed by FUTUR-IC.” This is especially important given that microelectronics production transcends industries. “Given the scale and scope of microelectronics, it is critical for the industry to lead in the transition to sustainable manufacture and use,” says Kirchain, another co-lead and the co-director of the Concrete Sustainability Hub at MIT. To bring about this cross-fertilization, co-lead Olivetti, also co-director of the MIT Climate and Sustainability Consortium (MCSC), will collaborate with FUTUR-IC to enhance the benefits from microchip recycling, leveraging the learning across industries.

      Saini, the co-lead for the workforce vector, stresses the need for agility. “With a workforce that adapts to a practice of continuous upskilling, we can help increase the robustness of the chip-manufacturing supply chain, and validate a new design for a sustainability curriculum,” he says.

      “We have become accustomed to the benefits forged by the exponential growth of microelectronic technology performance and market size,” says Kimerling, who is also director of MIT’s Materials Research Laboratory and co-director of the MIT Microphotonics Center. “The ecological impact of this growth in terms of materials use, energy consumption and end-of-life disposal has begun to push back against this progress. We believe that concurrently engineered solutions for these three dimensions will build a common learning curve to power the next 40 years of progress in the semiconductor industry.”

      The MIT teams are two of six that received awards addressing sustainable materials for global challenges through phase two of the NSF Convergence Accelerator program. Launched in 2019, the program targets solutions to especially compelling challenges at an accelerated pace by incorporating a multidisciplinary research approach. More

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      Bringing an investigator’s eye to complex social challenges

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      Anna Russo likes puzzles. They require patience, organization, and a view of the big picture. She brings an investigator’s eye to big institutional and societal challenges whose solutions can have wide-ranging, long-term impacts.

      Russo’s path to MIT began with questions. She didn’t have the whole picture yet. “I had no idea what I wanted to do with my life,” says Russo, who is completing her PhD in economics in 2024. “I was good at math and science and thought I wanted to be a doctor.”

      While completing her undergraduate studies at Yale University, where she double majored in economics and applied math, Russo discovered a passion for problem-solving, where she could apply an analytical lens to answering the kinds of thorny questions whose solutions could improve policy. “Empirical research is fun and exciting,” Russo says.

      After Yale, Russo considered what to do next. She worked as a full-time research assistant with MIT economist Amy Finkelstein. Russo’s work with Finkelstein led her toward identifying, studying, and developing answers to complex questions. 

      “My research combines ideas from two fields of economic inquiry — public finance and industrial organization — and applies them to questions about the design of environmental and health care policy,” Russo says. “I like the way economists think analytically about social problems.”

      Narrowing her focus

      Studying with and being advised by renowned economists as both an undergraduate and a doctoral student helped Russo narrow her research focus, fitting more pieces into the puzzle. “What drew me to MIT was its investment in its graduate students,” Russo says.

      Economic research meant digging into policy questions, identifying market failures, and proposing solutions. Doctoral study allowed Russo to assemble data to rigorously follow each line of inquiry.

      “Doctoral study means you get to write about something you’re really interested in,” Russo notes. This led her to study policy responses to climate change adaptation and mitigation. 

      “In my first year, I worked on a project exploring the notion that floodplain regulation design doesn’t do a good job of incentivizing the right level of development in flood-prone areas,” she says. “How can economists help governments convince people to act in society’s best interest?”

      It’s important to understand institutional details, Russo adds, which can help investigators identify and implement solutions. 

      “Feedback, advice, and support from faculty were crucial as I grew as a researcher at MIT,” she says. Beyond her two main MIT advisors, Finkelstein and economist Nikhil Agarwal — educators she describes as “phenomenal, dedicated advisors and mentors” — Russo interacted regularly with faculty across the department. 

      Russo later discovered another challenge she hoped to solve: inefficiencies in conservation and carbon offset programs. She set her sights on the United States Department of Agriculture’s Conservation Reserve Program because she believes it and programs like it can be improved. 

      The CRP is a land conservation plan administered by USDA’s Farm Service Agency. In exchange for a yearly rental payment, farmers enrolled in the program agree to remove environmentally sensitive land from agricultural production and plant species that will improve environmental health and quality.

      “I think we can tweak the program’s design to improve cost-effectiveness,” Russo says. “There’s a trove of data available.” The data include information like auction participants’ bids in response to well-specified auction rules, which Russo links to satellite data measuring land use outcomes. Understanding how landowners bid in CRP auctions can help identify and improve the program’s function. 

      “We may be able to improve targeting and achieve more cost-effective conservation by adjusting the CRP’s scoring system,” Russo argues. Opportunities may exist to scale the incremental changes under study for other conservation programs and carbon offset markets more generally.  

      Economics, Russo believes, can help us conceptualize problems and recommend effective alternative solutions.

      The next puzzle

      Russo wants to find her next challenge while continuing her research. She plans to continue her work as a junior fellow at the Harvard Society of Fellows, after which she’ll join the Harvard Department of Economics as an assistant professor. Russo also plans to continue helping other budding economists since she believes in the importance of supporting other students.   

      Russo’s advisors are some of her biggest supporters. 

      Finklestein emphasizes Russo’s curiosity, enthusiasm, and energy as key drivers in her success. “Her genuine curiosity and interest in getting to the bottom of a problem with the data — with an econometric analysis, with a modeling issue — is the best antidote for [the stress that can be associated with research],” Finklestein says. “It’s a key ingredient in her ability to produce important and credible work.”

      “She’s also incredibly generous with her time and advice,” Finklestein continues, “whether it’s helping an undergraduate research assistant with her senior thesis, or helping an advisor such as myself navigate a data access process she’s previously been through.”

      “Instead of an advisor-advisee relationship, working with her on a thesis felt more like a collaboration between equals,” Agarwal adds. “[She] has the maturity and smarts to produce pathbreaking research.

      “Doctoral study is an opportunity for students to find their paths collaboratively,” Russo says. “If I can help someone else solve a small piece of their puzzle, that’s a huge positive. Research is a series of many, many small steps forward.” 

      Identifying important causes for further investigation and study will always be important to Russo. “I also want to dig into some other market that’s not working well and figure out how to make it better,” she says. “Right now I’m really excited about understanding California wildfire mitigation.” 

      Puzzles are made to be solved, after all. More

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      in Environment

      MIT announces 2024 Bose Grants

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      MIT Provost Cynthia Barnhart announced four Professor Amar G. Bose Research Grants to support bold research projects across diverse areas of study, including a way to generate clean hydrogen from deep in the Earth, build an environmentally friendly house of basalt, design maternity clothing that monitors fetal health, and recruit sharks as ocean oxygen monitors.

      This year’s recipients are Iwnetim Abate, assistant professor of materials science and engineering; Andrew Babbin, the Cecil and Ida Green Associate Professor in Earth, Atmospheric and Planetary Sciences; Yoel Fink, professor of materials science and engineering and of electrical engineering and computer science; and Skylar Tibbits, associate professor of design research in the Department of Architecture.

      The program was named for the visionary founder of the Bose Corporation and MIT alumnus Amar G. Bose ’51, SM ’52, ScD ’56. After gaining admission to MIT, Bose became a top math student and a Fulbright Scholarship recipient. He spent 46 years as a professor at MIT, led innovations in sound design, and founded the Bose Corp. in 1964. MIT launched the Bose grant program 11 years ago to provide funding over a three-year period to MIT faculty who propose original, cross-disciplinary, and often risky research projects that would likely not be funded by conventional sources.

      “The promise of the Bose Fellowship is to help bold, daring ideas become realities, an approach that honors Amar Bose’s legacy,” says Barnhart. “Thanks to support from this program, these talented faculty members have the freedom to explore their bold and innovative ideas.”

      Deep and clean hydrogen futures

      A green energy future will depend on harnessing hydrogen as a clean energy source, sequestering polluting carbon dioxide, and mining the minerals essential to building clean energy technologies such as advanced batteries. Iwnetim Abate thinks he has a solution for all three challenges: an innovative hydrogen reactor.

      He plans to build a reactor that will create natural hydrogen from ultramafic mineral rocks in the crust. “The Earth is literally a giant hydrogen factory waiting to be tapped,” Abate explains. “A back-of-the-envelope calculation for the first seven kilometers of the Earth’s crust estimates that there is enough ultramafic rock to produce hydrogen for 250,000 years.”

      The reactor envisioned by Abate injects water to create a reaction that releases hydrogen, while also supporting the injection of climate-altering carbon dioxide into the rock, providing a global carbon capacity of 100 trillion tons. At the same time, the reactor process could provide essential elements such as lithium, nickel, and cobalt — some of the most important raw materials used in advanced batteries and electronics.

      “Ultimately, our goal is to design and develop a scalable reactor for simultaneously tapping into the trifecta from the Earth’s subsurface,” Abate says.

      Sharks as oceanographers

      If we want to understand more about how oxygen levels in the world’s seas are disturbed by human activities and climate change, we should turn to a sensing platform “that has been honed by 400 million years of evolution to perfectly sample the ocean: sharks,” says Andrew Babbin.

      As the planet warms, oceans are projected to contain less dissolved oxygen, with impacts on the productivity of global fisheries, natural carbon sequestration, and the flux of climate-altering greenhouse gasses from the ocean to the air. While scientists know dissolved oxygen is important, it has proved difficult to track over seasons, decades, and underexplored regions both shallow and deep.

      Babbin’s goal is to develop a low-cost sensor for dissolved oxygen that can be integrated with preexisting electronic shark tags used by marine biologists. “This fleet of sharks … will finally enable us to measure the extent of the low-oxygen zones of the ocean, how they change seasonally and with El Niño/La Niña oscillation, and how they expand or contract into the future.”

      The partnership with sharks will also spotlight the importance of these often-maligned animals for global marine and fisheries health, Babbin says. “We hope in pursuing this work marrying microscopic and macroscopic life we will inspire future oceanographers and conservationists, and lead to a better appreciation for the chemistry that underlies global habitability.”

      Maternity wear that monitors fetal health

      There are 2 million stillbirths around the world each year, and in the United States alone, 21,000 families suffer this terrible loss. In many cases, mothers and their doctors had no warning of any abnormalities or changes in fetal health leading up to these deaths. Yoel Fink and colleagues are looking for a better way to monitor fetal health and provide proactive treatment.

      Fink is building on years of research on acoustic fabrics to design an affordable shirt for mothers that would monitor and communicate important details of fetal health. His team’s original research drew inspiration from the function of the eardrum, designing a fiber that could be woven into other fabrics to create a kind of fabric microphone.

      “Given the sensitivity of the acoustic fabrics in sensing these nanometer-scale vibrations, could a mother’s clothing transcend its conventional role and become a health monitor, picking up on the acoustic signals and subsequent vibrations that arise from her unborn baby’s heartbeat and motion?” Fink says. “Could a simple and affordable worn fabric allow an expecting mom to sleep better, knowing that her fetus is being listened to continuously?”

      The proposed maternity shirt could measure fetal heart and breathing rate, and might be able to give an indication of the fetal body position, he says. In the final stages of development, he and his colleagues hope to develop machine learning approaches that would identify abnormal fetal heart rate and motion and deliver real-time alerts.

      A basalt house in Iceland

      In the land of volcanoes, Skylar Tibbits wants to build a case-study home almost entirely from the basalt rock that makes up the Icelandic landscape.

      Architects are increasingly interested in building using one natural material — creating a monomaterial structure — that can be easily recycled. At the moment, the building industry represents 40 percent of carbon emissions worldwide, and consists of many materials and structures, from metal to plastics to concrete, that can’t be easily disassembled or reused.

      The proposed basalt house in Iceland, a project co-led by J. Jih, associate professor of the practice in the Department of Architecture, is “an architecture that would be fully composed of the surrounding earth, that melts back into that surrounding earth at the end of its lifespan, and that can be recycled infinitely,” Tibbits explains.

      Basalt, the most common rock form in the Earth’s crust, can be spun into fibers for insulation and rebar. Basalt fiber performs as well as glass and carbon fibers at a lower cost in some applications, although it is not widely used in architecture. In cast form, it can make corrosion- and heat-resistant plumbing, cladding and flooring.

      “A monomaterial architecture is both a simple and radical proposal that unfortunately falls outside of traditional funding avenues,” says Tibbits. “The Bose grant is the perfect and perhaps the only option for our research, which we see as a uniquely achievable moonshot with transformative potential for the entire built environment.” More

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      Featured video: Moooving the needle on methane

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      Methane traps much more heat per pound than carbon dioxide, making it a powerful contributor to climate change. “In fact, methane emission removal is the fastest way that we can ensure immediate results for reduced global warming,” says Audrey Parker, a graduate student in the Department of Civil and Environmental Engineering.

      Parker and other researchers in the Methane Emission Removal Project are developing a catalyst that can convert methane to carbon dioxide. They are working to set up systems that would reduce methane in the air at dairy farms, which are major emitters of the gas. Overall, agricultural practices and waste generation are responsible for about 28 percent of the world’s methane emissions.

      “If we do our job really well, within the next five years, we will be able to reduce the operating temperature of this catalyst in a way that is net beneficial to the climate and potentially even economically incentivized for the farmer and for society,” says Desirée Plata, an associate professor of civil and environmental engineering who leads the Methane Emission Removal Project.

      Video by Melanie Gonick/MIT News | 4 minutes, 35 seconds More