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    Developing electricity-powered, low-emissions alternatives to carbon-intensive industrial processes

    On April 11, 2022, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This is the second article in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

    One of the biggest leaps that humankind could take to drastically lower greenhouse gas emissions globally would be the complete decarbonization of industry. But without finding low-cost, environmentally friendly substitutes for industrial materials, the traditional production of steel, cement, ammonia, and ethylene will continue pumping out billions of tons of carbon annually; these sectors alone are responsible for at least one third of society’s global greenhouse gas emissions. 

    A major problem is that industrial manufacturers, whose success depends on reliable, cost-efficient, and large-scale production methods, are too heavily invested in processes that have historically been powered by fossil fuels to quickly switch to new alternatives. It’s a machine that kicked on more than 100 years ago, and which MIT electrochemical engineer Yet-Ming Chiang says we can’t shut off without major disruptions to the world’s massive supply chain of these materials. What’s needed, Chiang says, is a broader, collaborative clean energy effort that takes “targeted fundamental research, all the way through to pilot demonstrations that greatly lowers the risk for adoption of new technology by industry.”

    This would be a new approach to decarbonization of industrial materials production that relies on largely unexplored but cleaner electrochemical processes. New production methods could be optimized and integrated into the industrial machine to make it run on low-cost, renewable electricity in place of fossil fuels. 

    Recognizing this, Chiang, the Kyocera Professor in the Department of Materials Science and Engineering, teamed with research collaborator Bilge Yildiz, the Breene M. Kerr Professor of Nuclear Science and Engineering and professor of materials science and engineering, with key input from Karthish Manthiram, visiting professor in the Department of Chemical Engineering, to submit a project proposal to the MIT Climate Grand Challenges. Their plan: to create an innovation hub on campus that would bring together MIT researchers individually investigating decarbonization of steel, cement, ammonia, and ethylene under one roof, combining research equipment and directly collaborating on new methods to produce these four key materials.

    Many researchers across MIT have already signed on to join the effort, including Antoine Allanore, associate professor of metallurgy, who specializes in the development of sustainable materials and manufacturing processes, and Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in the Department of Materials Science and Engineering, who is an expert in materials economics and sustainability. Other MIT faculty currently involved include Fikile Brushett, Betar Gallant, Ahmed Ghoniem, William Green, Jeffrey Grossman, Ju Li, Yuriy Román-Leshkov, Yang Shao-Horn, Robert Stoner, Yogesh Surendranath, Timothy Swager, and Kripa Varanasi.

    “The team we brought together has the expertise needed to tackle these challenges, including electrochemistry — using electricity to decarbonize these chemical processes — and materials science and engineering, process design and scale-up technoeconomic analysis, and system integration, which is all needed for this to go out from our labs to the field,” says Yildiz.

    Selected from a field of more than 100 proposals, their Center for Electrification and Decarbonization of Industry (CEDI) will be the first such institute worldwide dedicated to testing and scaling the most innovative and promising technologies in sustainable chemicals and materials. CEDI will work to facilitate rapid translation of lab discoveries into affordable, scalable industry solutions, with potential to offset as much as 15 percent of greenhouse gas emissions. The team estimates that some CEDI projects already underway could be commercialized within three years.

    “The real timeline is as soon as possible,” says Chiang.

    To achieve CEDI’s ambitious goals, a physical location is key, staffed with permanent faculty, as well as undergraduates, graduate students, and postdocs. Yildiz says the center’s success will depend on engaging student researchers to carry forward with research addressing the biggest ongoing challenges to decarbonization of industry.

    “We are training young scientists, students, on the learned urgency of the problem,” says Yildiz. “We empower them with the skills needed, and even if an individual project does not find the implementation in the field right away, at least, we would have trained the next generation that will continue to go after them in the field.”

    Chiang’s background in electrochemistry showed him how the efficiency of cement production could benefit from adopting clean electricity sources, and Yildiz’s work on ethylene, the source of plastic and one of industry’s most valued chemicals, has revealed overlooked cost benefits to switching to electrochemical processes with less expensive starting materials. With industry partners, they hope to continue these lines of fundamental research along with Allanore, who is focused on electrifying steel production, and Manthiram, who is developing new processes for ammonia. Olivetti will focus on understanding risks and barriers to implementation. This multilateral approach aims to speed up the timeline to industry adoption of new technologies at the scale needed for global impact.

    “One of the points of emphasis in this whole center is going to be applying technoeconomic analysis of what it takes to be successful at a technical and economic level, as early in the process as possible,” says Chiang.

    The impact of large-scale industry adoption of clean energy sources in these four key areas that CEDI plans to target first would be profound, as these sectors are currently responsible for 7.5 billion tons of emissions annually. There is the potential for even greater impact on emissions as new knowledge is applied to other industrial products beyond the initial four targets of steel, cement, ammonia, and ethylene. Meanwhile, the center will stand as a hub to attract new industry, government stakeholders, and research partners to collaborate on urgently needed solutions, both newly arising and long overdue.

    When Chiang and Yildiz first met to discuss ideas for MIT Climate Grand Challenges, they decided they wanted to build a climate research center that functioned unlike any other to help pivot large industry toward decarbonization. Beyond considering how new solutions will impact industry’s bottom line, CEDI will also investigate unique synergies that could arise from the electrification of industry, like processes that would create new byproducts that could be the feedstock to other industry processes, reducing waste and increasing efficiencies in the larger system. And because industry is so good at scaling, those added benefits would be widespread, finally replacing century-old technologies with critical updates designed to improve production and markedly reduce industry’s carbon footprint sooner rather than later.

    “Everything we do, we’re going to try to do with urgency,” Chiang says. “The fundamental research will be done with urgency, and the transition to commercialization, we’re going to do with urgency.” More

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    Computing our climate future

    On Monday, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This article is the first in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

    With improvements to computer processing power and an increased understanding of the physical equations governing the Earth’s climate, scientists are continually working to refine climate models and improve their predictive power. But the tools they’re refining were originally conceived decades ago with only scientists in mind. When it comes to developing tangible climate action plans, these models remain inscrutable to the policymakers, public safety officials, civil engineers, and community organizers who need their predictive insight most.

    “What you end up having is a gap between what’s typically used in practice, and the real cutting-edge science,” says Noelle Selin, a professor in the Institute for Data, Systems and Society and the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and co-lead with Professor Raffaele Ferrari on the MIT Climate Grand Challenges flagship project “Bringing Computation to the Climate Crisis.” “How can we use new computational techniques, new understandings, new ways of thinking about modeling, to really bridge that gap between state-of-the-art scientific advances and modeling, and people who are actually needing to use these models?”

    Using this as a driving question, the team won’t just be trying to refine current climate models, they’re building a new one from the ground up.

    This kind of game-changing advancement is exactly what the MIT Climate Grand Challenges is looking for, which is why the proposal has been named one of the five flagship projects in the ambitious Institute-wide program aimed at tackling the climate crisis. The proposal, which was selected from 100 submissions and was among 27 finalists, will receive additional funding and support to further their goal of reimagining the climate modeling system. It also brings together contributors from across the Institute, including the MIT Schwarzman College of Computing, the School of Engineering, and the Sloan School of Management.

    When it comes to pursuing high-impact climate solutions that communities around the world can use, “it’s great to do it at MIT,” says Ferrari, EAPS Cecil and Ida Green Professor of Oceanography. “You’re not going to find many places in the world where you have the cutting-edge climate science, the cutting-edge computer science, and the cutting-edge policy science experts that we need to work together.”

    The climate model of the future

    The proposal builds on work that Ferrari began three years ago as part of a joint project with Caltech, the Naval Postgraduate School, and NASA’s Jet Propulsion Lab. Called the Climate Modeling Alliance (CliMA), the consortium of scientists, engineers, and applied mathematicians is constructing a climate model capable of more accurately projecting future changes in critical variables, such as clouds in the atmosphere and turbulence in the ocean, with uncertainties at least half the size of those in existing models.

    To do this, however, requires a new approach. For one thing, current models are too coarse in resolution — at the 100-to-200-kilometer scale — to resolve small-scale processes like cloud cover, rainfall, and sea ice extent. But also, explains Ferrari, part of this limitation in resolution is due to the fundamental architecture of the models themselves. The languages most global climate models are coded in were first created back in the 1960s and ’70s, largely by scientists for scientists. Since then, advances in computing driven by the corporate world and computer gaming have given rise to dynamic new computer languages, powerful graphics processing units, and machine learning.

    For climate models to take full advantage of these advancements, there’s only one option: starting over with a modern, more flexible language. Written in Julia, a part of Julialab’s Scientific Machine Learning technology, and spearheaded by Alan Edelman, a professor of applied mathematics in MIT’s Department of Mathematics, CliMA will be able to harness far more data than the current models can handle.

    “It’s been real fun finally working with people in computer science here at MIT,” Ferrari says. “Before it was impossible, because traditional climate models are in a language their students can’t even read.”

    The result is what’s being called the “Earth digital twin,” a climate model that can simulate global conditions on a large scale. This on its own is an impressive feat, but the team wants to take this a step further with their proposal.

    “We want to take this large-scale model and create what we call an ‘emulator’ that is only predicting a set of variables of interest, but it’s been trained on the large-scale model,” Ferrari explains. Emulators are not new technology, but what is new is that these emulators, being referred to as the “Earth digital cousins,” will take advantage of machine learning.

    “Now we know how to train a model if we have enough data to train them on,” says Ferrari. Machine learning for projects like this has only become possible in recent years as more observational data become available, along with improved computer processing power. The goal is to create smaller, more localized models by training them using the Earth digital twin. Doing so will save time and money, which is key if the digital cousins are going to be usable for stakeholders, like local governments and private-sector developers.

    Adaptable predictions for average stakeholders

    When it comes to setting climate-informed policy, stakeholders need to understand the probability of an outcome within their own regions — in the same way that you would prepare for a hike differently if there’s a 10 percent chance of rain versus a 90 percent chance. The smaller Earth digital cousin models will be able to do things the larger model can’t do, like simulate local regions in real time and provide a wider range of probabilistic scenarios.

    “Right now, if you wanted to use output from a global climate model, you usually would have to use output that’s designed for general use,” says Selin, who is also the director of the MIT Technology and Policy Program. With the project, the team can take end-user needs into account from the very beginning while also incorporating their feedback and suggestions into the models, helping to “democratize the idea of running these climate models,” as she puts it. Doing so means building an interactive interface that eventually will give users the ability to change input values and run the new simulations in real time. The team hopes that, eventually, the Earth digital cousins could run on something as ubiquitous as a smartphone, although developments like that are currently beyond the scope of the project.

    The next thing the team will work on is building connections with stakeholders. Through participation of other MIT groups, such as the Joint Program on the Science and Policy of Global Change and the Climate and Sustainability Consortium, they hope to work closely with policymakers, public safety officials, and urban planners to give them predictive tools tailored to their needs that can provide actionable outputs important for planning. Faced with rising sea levels, for example, coastal cities could better visualize the threat and make informed decisions about infrastructure development and disaster preparedness; communities in drought-prone regions could develop long-term civil planning with an emphasis on water conservation and wildfire resistance.

    “We want to make the modeling and analysis process faster so people can get more direct and useful feedback for near-term decisions,” she says.

    The final piece of the challenge is to incentivize students now so that they can join the project and make a difference. Ferrari has already had luck garnering student interest after co-teaching a class with Edelman and seeing the enthusiasm students have about computer science and climate solutions.

    “We’re intending in this project to build a climate model of the future,” says Selin. “So it seems really appropriate that we would also train the builders of that climate model.” More

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    Finding the questions that guide MIT fusion research

    “One of the things I learned was, doing good science isn’t so much about finding the answers as figuring out what the important questions are.”

    As Martin Greenwald retires from the responsibilities of senior scientist and deputy director of the MIT Plasma Science and Fusion Center (PSFC), he reflects on his almost 50 years of science study, 43 of them as a researcher at MIT, pursuing the question of how to make the carbon-free energy of fusion a reality.

    Most of Greenwald’s important questions about fusion began after graduating from MIT with a BS in both physics and chemistry. Beginning graduate work at the University of California at Berkeley, he felt compelled to learn more about fusion as an energy source that could have “a real societal impact.” At the time, researchers were exploring new ideas for devices that could create and confine fusion plasmas. Greenwald worked on Berkeley’s “alternate concept” TORMAC, a Toroidal Magnetic Cusp. “It didn’t work out very well,” he laughs. “The first thing I was known for was making the measurements that shut down the program.”

    Believing the temperature of the plasma generated by the device would not be as high as his group leader expected, Greenwald developed hardware that could measure the low temperatures predicted by his own “back of the envelope calculations.” As he anticipated, his measurements showed that “this was not a fusion plasma; this was hardly a confined plasma at all.”

    With a PhD from Berkeley, Greenwald returned to MIT for a research position at the PSFC, attracted by the center’s “esprit de corps.”

    He arrived in time to participate in the final experiments on Alcator A, the first in a series of tokamaks built at MIT, all characterized by compact size and featuring high-field magnets. The tokamak design was then becoming favored as the most effective route to fusion: its doughnut-shaped vacuum chamber, surrounded by electromagnets, could confine the turbulent plasma long enough, while increasing its heat and density, to make fusion occur.

    Alcator A showed that the energy confinement time improves in relation to increasing plasma density. MIT’s succeeding device, Alcator C, was designed to use higher magnetic fields, boosting expectations that it would reach higher densities and better confinement. To attain these goals, however, Greenwald had to pursue a new technique that increased density by injecting pellets of frozen fuel into the plasma, a method he likens to throwing “snowballs in hell.” This work was notable for the creation of a new regime of enhanced plasma confinement on Alcator C. In those experiments, a confined plasma surpassed for the first time one of the two Lawson criteria — the minimum required value for the product of the plasma density and confinement time — for making net power from fusion. This had been a milestone for fusion research since their publication by John Lawson in 1957.

    Greenwald continued to make a name for himself as part of a larger study into the physics of the Compact Ignition Tokamak — a high-field burning plasma experiment that the U.S. program was proposing to build in the late 1980s. The result, unexpectedly, was a new scaling law, later known as the “Greenwald Density Limit,” and a new theory for the mechanism of the limit. It has been used to accurately predict performance on much larger machines built since.

    The center’s next tokamak, Alcator C-Mod, started operation in 1993 and ran for more than 20 years, with Greenwald as the chair of its Experimental Program Committee. Larger than Alcator C, the new device supported a highly shaped plasma, strong radiofrequency heating, and an all-metal plasma-facing first wall. All of these would eventually be required in a fusion power system.

    C-Mod proved to be MIT’s most enduring fusion experiment to date, producing important results for 20 years. During that time Greenwald contributed not only to the experiments, but to mentoring the next generation. Research scientist Ryan Sweeney notes that “Martin quickly gained my trust as a mentor, in part due to his often casual dress and slightly untamed hair, which are embodiments of his transparency and his focus on what matters. He can quiet a room of PhDs and demand attention not by intimidation, but rather by his calmness and his ability to bring clarity to complicated problems, be they scientific or human in nature.”

    Greenwald worked closely with the group of students who, in PSFC Director Dennis Whyte’s class, came up with the tokamak concept that evolved into SPARC. MIT is now pursuing this compact, high-field tokamak with Commonwealth Fusion Systems, a startup that grew out of the collective enthusiasm for this concept, and the growing realization it could work. Greenwald now heads the Physics Group for the SPARC project at MIT. He has helped confirm the device’s physics basis in order to predict performance and guide engineering decisions.

    “Martin’s multifaceted talents are thoroughly embodied by, and imprinted on, SPARC” says Whyte. “First, his leadership in its plasma confinement physics validation and publication place SPARC on a firm scientific footing. Secondly, the impact of the density limit he discovered, which shows that fuel density increases with magnetic field and decreasing the size of the tokamak, is critical in obtaining high fusion power density not just in SPARC, but in future power plants. Third, and perhaps most impressive, is Martin’s mentorship of the SPARC generation of leadership.”

    Greenwald’s expertise and easygoing personality have made him an asset as head of the PSFC Office for Computer Services and group leader for data acquisition and computing, and sought for many professional committees. He has been an APS Fellow since 2000, and was an APS Distinguished Lecturer in Plasma Physics (2001-02). He was also presented in 2014 with a Leadership Award from Fusion Power Associates. He is currently an associate editor for Physics of Plasmas and a member of the Lawrence Livermore National Laboratory Physical Sciences Directorate External Review Committee.

    Although leaving his full-time responsibilities, Greenwald will remain at MIT as a visiting scientist, a role he says will allow him to “stick my nose into everything without being responsible for anything.”

    “At some point in the race you have to hand off the baton,“ he says. “And it doesn’t mean you’re not interested in the outcome; and it doesn’t mean you’re just going to walk away into the stands. I want to be there at the end when we succeed.” More

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    Q&A: Climate Grand Challenges finalists on using data and science to forecast climate-related risk

    Note: This is the final article in a four-part interview series featuring the work of the 27 MIT Climate Grand Challenges finalist teams, which received a total of $2.7 million in startup funding to advance their projects. This month, the Institute will name a subset of the finalists as multiyear flagship projects.

    Advances in computation, artificial intelligence, robotics, and data science are enabling a new generation of observational tools and scientific modeling with the potential to produce timely, reliable, and quantitative analysis of future climate risks at a local scale. These projections can increase the accuracy and efficacy of early warning systems, improve emergency planning, and provide actionable information for climate mitigation and adaptation efforts, as human actions continue to change planetary conditions.

    In conversations prepared for MIT News, faculty from four Climate Grand Challenges teams with projects in the competition’s “Using data and science to forecast climate-related risk” category describe the promising new technologies that can help scientists understand the Earth’s climate system on a finer scale than ever before. (The other Climate Grand Challenges research themes include building equity and fairness into climate solutions, removing, managing, and storing greenhouse gases, and decarbonizing complex industries and processes.) The following responses have been edited for length and clarity.

    An observational system that can initiate a climate risk forecasting revolution

    Despite recent technological advances and massive volumes of data, climate forecasts remain highly uncertain. Gaps in observational capabilities create substantial challenges to predicting extreme weather events and establishing effective mitigation and adaptation strategies. R. John Hansman, the T. Wilson Professor of Aeronautics and Astronautics and director of the MIT International Center for Air Transportation, discusses the Stratospheric Airborne Climate Observatory System (SACOS) being developed together with Brent Minchew, the Cecil and Ida Green Career Development Professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and a team that includes researchers from MIT Lincoln Laboratory and Harvard University.

    Q: How does SACOS reduce uncertainty in climate risk forecasting?

    A: There is a critical need for higher spatial and temporal resolution observations of the climate system than are currently available through remote (satellite or airborne) and surface (in-situ) sensing. We are developing an ensemble of high-endurance, solar-powered aircraft with instrument systems capable of performing months-long climate observing missions that satellites or aircraft alone cannot fulfill. Summer months are ideal for SACOS operations, as many key climate phenomena are active and short night periods reduce the battery mass, vehicle size, and technical risks. These observations hold the potential to inform and predict, allowing emergency planners, policymakers, and the rest of society to better prepare for the changes to come.

    Q: Describe the types of observing missions where SACOS could provide critical improvements.

    A: The demise of the Antarctic Ice Sheet, which is leading to rising sea levels around the world and threatening the displacement of millions of people, is one example. Current sea level forecasts struggle to account for giant fissures that create massive icebergs and cause the Antarctic Ice Sheet to flow more rapidly into the ocean. SACOS can track these fissures to accurately forecast ice slippage and give impacted populations enough time to prepare or evacuate. Elsewhere, widespread droughts cause rampant wildfires and water shortages. SACOS has the ability to monitor soil moisture and humidity in critically dry regions to identify where and when wildfires and droughts are imminent. SACOS also offers the most effective method to measure, track, and predict local ozone depletion over North America, which has resulted in increasingly severe summer thunderstorms.

    Quantifying and managing the risks of sea-level rise

    Prevailing estimates of sea-level rise range from approximately 20 centimeters to 2 meters by the end of the century, with the associated costs on the order of trillions of dollars. The instability of certain portions of the world’s ice sheets creates vast uncertainties, complicating how the world prepares for and responds to these potential changes. EAPS Professor Brent Minchew is leading another Climate Grand Challenges finalist team working on an integrated, multidisciplinary effort to improve the scientific understanding of sea-level rise and provide actionable information and tools to manage the risks it poses.

    Q: What have been the most significant challenges to understanding the potential rates of sea-level rise?

    A: West Antarctica is one of the most remote, inaccessible, and hostile places on Earth — to people and equipment. Thus, opportunities to observe the collapse of the West Antarctic Ice Sheet, which contains enough ice to raise global sea levels by about 3 meters, are limited and current observations crudely resolved. It is essential that we understand how the floating edge of the ice sheets, often called ice shelves, fracture and collapse because they provide critical forces that govern the rate of ice mass loss and can stabilize the West Antarctic Ice Sheet.

    Q: How will your project advance what is currently known about sea-level rise?

    A: We aim to advance global-scale projections of sea-level rise through novel observational technologies and computational models of ice sheet change and to link those predictions to region- to neighborhood-scale estimates of costs and adaptation strategies. To do this, we propose two novel instruments: a first-of-its-kind drone that can fly for months at a time over Antarctica making continuous observations of critical areas and an airdropped seismometer and GPS bundle that can be deployed to vulnerable and hard-to-reach areas of the ice sheet. This technology will provide greater data quality and density and will observe the ice sheet at frequencies that are currently inaccessible — elements that are essential for understanding the physics governing the evolution of the ice sheet and sea-level rise.

    Changing flood risk for coastal communities in the developing world

    Globally, more than 600 million people live in low-elevation coastal areas that face an increasing risk of flooding from sea-level rise. This includes two-thirds of cities with populations of more than 5 million and regions that conduct the vast majority of global trade. Dara Entekhabi, the Bacardi and Stockholm Water Foundations Professor in the Department of Civil and Environmental Engineering and professor in the Department of Earth, Atmospheric, and Planetary Sciences, outlines an interdisciplinary partnership that leverages data and technology to guide short-term and chart long-term adaptation pathways with Miho Mazereeuw, associate professor of architecture and urbanism and director of the Urban Risk Lab in the School of Architecture and Planning, and Danielle Wood, assistant professor in the Program in Media Arts and Sciences and the Department of Aeronautics and Astronautics.

    Q: What is the key problem this program seeks to address?

    A: The accumulated heating of the Earth system due to fossil burning is largely absorbed by the oceans, and the stored heat expands the ocean volume leading to increased base height for tides. When the high tides inundate a city, the condition is referred to as “sunny day” flooding, but the saline waters corrode infrastructure and wreak havoc on daily routines. The danger ahead for many coastal cities in the developing world is the combination of increasing high tide intrusions, coupled with heavy precipitation storm events.

    Q: How will your proposed solutions impact flood risk management?

    A: We are producing detailed risk maps for coastal cities in developing countries using newly available, very high-resolution remote-sensing data from space-borne instruments, as well as historical tides records and regional storm characteristics. Using these datasets, we aim to produce street-by-street risk maps that provide local decision-makers and stakeholders with a way to estimate present and future flood risks. With the model of future tides and probabilistic precipitation events, we can forecast future inundation by a flooding event, decadal changes with various climate-change and sea-level rise projections, and an increase in the likelihood of sunny-day flooding. Working closely with local partners, we will develop toolkits to explore short-term emergency response, as well as long-term mitigation and adaptation techniques in six pilot locations in South and Southeast Asia, Africa, and South America.

    Ocean vital signs

    On average, every person on Earth generates fossil fuel emissions equivalent to an 8-pound bag of carbon, every day. Much of this is absorbed by the ocean, but there is wide variability in the estimates of oceanic absorption, which translates into differences of trillions of dollars in the required cost of mitigation. In the Department of Earth, Atmospheric and Planetary Sciences, Christopher Hill, a principal research engineer specializing in Earth and planetary computational science, works with Ryan Woosley, a principal research scientist focusing on the carbon cycle and ocean acidification. Hill explains that they hope to use artificial intelligence and machine learning to help resolve this uncertainty.

    Q: What is the current state of knowledge on air-sea interactions?

    A: Obtaining specific, accurate field measurements of critical physical, chemical, and biological exchanges between the ocean and the planet have historically entailed expensive science missions with large ship-based infrastructure that leave gaps in real-time data about significant ocean climate processes. Recent advances in highly scalable in-situ autonomous observing and navigation combined with airborne, remote sensing, and machine learning innovations have the potential to transform data gathering, provide more accurate information, and address fundamental scientific questions around air-sea interaction.

    Q: How will your approach accelerate real-time, autonomous surface ocean observing from an experimental research endeavor to a permanent and impactful solution?

    A: Our project seeks to demonstrate how a scalable surface ocean observing network can be launched and operated, and to illustrate how this can reduce uncertainties in estimates of air-sea carbon dioxide exchange. With an initial high-impact goal of substantially eliminating the vast uncertainties that plague our understanding of ocean uptake of carbon dioxide, we will gather critical measurements for improving extended weather and climate forecast models and reducing climate impact uncertainty. The results have the potential to more accurately identify trillions of dollars worth of economic activity. More

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    Improving predictions of sea level rise for the next century

    When we think of climate change, one of the most dramatic images that comes to mind is the loss of glacial ice. As the Earth warms, these enormous rivers of ice become a casualty of the rising temperatures. But, as ice sheets retreat, they also become an important contributor to one the more dangerous outcomes of climate change: sea-level rise. At MIT, an interdisciplinary team of scientists is determined to improve sea level rise predictions for the next century, in part by taking a closer look at the physics of ice sheets.

    Last month, two research proposals on the topic, led by Brent Minchew, the Cecil and Ida Green Career Development Professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS), were announced as finalists in the MIT Climate Grand Challenges initiative. Launched in July 2020, Climate Grand Challenges fielded almost 100 project proposals from collaborators across the Institute who heeded the bold charge: to develop research and innovations that will deliver game-changing advances in the world’s efforts to address the climate challenge.

    As finalists, Minchew and his collaborators from the departments of Urban Studies and Planning, Economics, Civil and Environmental Engineering, the Haystack Observatory, and external partners, received $100,000 to develop their research plans. A subset of the 27 proposals tapped as finalists will be announced next month, making up a portfolio of multiyear “flagship” projects receiving additional funding and support.

    One goal of both Minchew proposals is to more fully understand the most fundamental processes that govern rapid changes in glacial ice, and to use that understanding to build next-generation models that are more predictive of ice sheet behavior as they respond to, and influence, climate change.

    “We need to develop more accurate and computationally efficient models that provide testable projections of sea-level rise over the coming decades. To do so quickly, we want to make better and more frequent observations and learn the physics of ice sheets from these data,” says Minchew. “For example, how much stress do you have to apply to ice before it breaks?”

    Currently, Minchew’s Glacier Dynamics and Remote Sensing group uses satellites to observe the ice sheets on Greenland and Antarctica primarily with interferometric synthetic aperture radar (InSAR). But the data are often collected over long intervals of time, which only gives them “before and after” snapshots of big events. By taking more frequent measurements on shorter time scales, such as hours or days, they can get a more detailed picture of what is happening in the ice.

    “Many of the key unknowns in our projections of what ice sheets are going to look like in the future, and how they’re going to evolve, involve the dynamics of glaciers, or our understanding of how the flow speed and the resistances to flow are related,” says Minchew.

    At the heart of the two proposals is the creation of SACOS, the Stratospheric Airborne Climate Observatory System. The group envisions developing solar-powered drones that can fly in the stratosphere for months at a time, taking more frequent measurements using a new lightweight, low-power radar and other high-resolution instrumentation. They also propose air-dropping sensors directly onto the ice, equipped with seismometers and GPS trackers to measure high-frequency vibrations in the ice and pinpoint the motions of its flow.

    How glaciers contribute to sea level rise

    Current climate models predict an increase in sea levels over the next century, but by just how much is still unclear. Estimates are anywhere from 20 centimeters to two meters, which is a large difference when it comes to enacting policy or mitigation. Minchew points out that response measures will be different, depending on which end of the scale it falls toward. If it’s closer to 20 centimeters, coastal barriers can be built to protect low-level areas. But with higher surges, such measures become too expensive and inefficient to be viable, as entire portions of cities and millions of people would have to be relocated.

    “If we’re looking at a future where we could get more than a meter of sea level rise by the end of the century, then we need to know about that sooner rather than later so that we can start to plan and to do our best to prepare for that scenario,” he says.

    There are two ways glaciers and ice sheets contribute to rising sea levels: direct melting of the ice and accelerated transport of ice to the oceans. In Antarctica, warming waters melt the margins of the ice sheets, which tends to reduce the resistive stresses and allow ice to flow more quickly to the ocean. This thinning can also cause the ice shelves to be more prone to fracture, facilitating the calving of icebergs — events which sometimes cause even further acceleration of ice flow.

    Using data collected by SACOS, Minchew and his group can better understand what material properties in the ice allow for fracturing and calving of icebergs, and build a more complete picture of how ice sheets respond to climate forces. 

    “What I want is to reduce and quantify the uncertainties in projections of sea level rise out to the year 2100,” he says.

    From that more complete picture, the team — which also includes economists, engineers, and urban planning specialists — can work on developing predictive models and methods to help communities and governments estimate the costs associated with sea level rise, develop sound infrastructure strategies, and spur engineering innovation.

    Understanding glacier dynamics

    More frequent radar measurements and the collection of higher-resolution seismic and GPS data will allow Minchew and the team to develop a better understanding of the broad category of glacier dynamics — including calving, an important process in setting the rate of sea level rise which is currently not well understood.  

    “Some of what we’re doing is quite similar to what seismologists do,” he says. “They measure seismic waves following an earthquake, or a volcanic eruption, or things of this nature and use those observations to better understand the mechanisms that govern these phenomena.”

    Air-droppable sensors will help them collect information about ice sheet movement, but this method comes with drawbacks — like installation and maintenance, which is difficult to do out on a massive ice sheet that is moving and melting. Also, the instruments can each only take measurements at a single location. Minchew equates it to a bobber in water: All it can tell you is how the bobber moves as the waves disturb it.

    But by also taking continuous radar measurements from the air, Minchew’s team can collect observations both in space and in time. Instead of just watching the bobber in the water, they can effectively make a movie of the waves propagating out, as well as visualize processes like iceberg calving happening in multiple dimensions.

    Once the bobbers are in place and the movies recorded, the next step is developing machine learning algorithms to help analyze all the new data being collected. While this data-driven kind of discovery has been a hot topic in other fields, this is the first time it has been applied to glacier research.

    “We’ve developed this new methodology to ingest this huge amount of data,” he says, “and from that create an entirely new way of analyzing the system to answer these fundamental and critically important questions.”  More

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    New program bolsters innovation in next-generation artificial intelligence hardware

    The MIT AI Hardware Program is a new academia and industry collaboration aimed at defining and developing translational technologies in hardware and software for the AI and quantum age. A collaboration between the MIT School of Engineering and MIT Schwarzman College of Computing, involving the Microsystems Technologies Laboratories and programs and units in the college, the cross-disciplinary effort aims to innovate technologies that will deliver enhanced energy efficiency systems for cloud and edge computing.

    “A sharp focus on AI hardware manufacturing, research, and design is critical to meet the demands of the world’s evolving devices, architectures, and systems,” says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Knowledge-sharing between industry and academia is imperative to the future of high-performance computing.”

    Based on use-inspired research involving materials, devices, circuits, algorithms, and software, the MIT AI Hardware Program convenes researchers from MIT and industry to facilitate the transition of fundamental knowledge to real-world technological solutions. The program spans materials and devices, as well as architecture and algorithms enabling energy-efficient and sustainable high-performance computing.

    “As AI systems become more sophisticated, new solutions are sorely needed to enable more advanced applications and deliver greater performance,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “Our aim is to devise real-world technological solutions and lead the development of technologies for AI in hardware and software.”

    The inaugural members of the program are companies from a wide range of industries including chip-making, semiconductor manufacturing equipment, AI and computing services, and information systems R&D organizations. The companies represent a diverse ecosystem, both nationally and internationally, and will work with MIT faculty and students to help shape a vibrant future for our planet through cutting-edge AI hardware research.

    The five inaugural members of the MIT AI Hardware Program are:  

    Amazon, a global technology company whose hardware inventions include the Kindle, Amazon Echo, Fire TV, and Astro; 
    Analog Devices, a global leader in the design and manufacturing of analog, mixed signal, and DSP integrated circuits; 
    ASML, an innovation leader in the semiconductor industry, providing chipmakers with hardware, software, and services to mass produce patterns on silicon through lithography; 
    NTT Research, a subsidiary of NTT that conducts fundamental research to upgrade reality in game-changing ways that improve lives and brighten our global future; and 
    TSMC, the world’s leading dedicated semiconductor foundry.

    The MIT AI Hardware Program will create a roadmap of transformative AI hardware technologies. Leveraging MIT.nano, the most advanced university nanofabrication facility anywhere, the program will foster a unique environment for AI hardware research.  

    “We are all in awe at the seemingly superhuman capabilities of today’s AI systems. But this comes at a rapidly increasing and unsustainable energy cost,” says Jesús del Alamo, the Donner Professor in MIT’s Department of Electrical Engineering and Computer Science. “Continued progress in AI will require new and vastly more energy-efficient systems. This, in turn, will demand innovations across the entire abstraction stack, from materials and devices to systems and software. The program is in a unique position to contribute to this quest.”

    The program will prioritize the following topics:

    analog neural networks;
    new roadmap CMOS designs;
    heterogeneous integration for AI systems;
    onolithic-3D AI systems;
    analog nonvolatile memory devices;
    software-hardware co-design;
    intelligence at the edge;
    intelligent sensors;
    energy-efficient AI;
    intelligent internet of things (IIoT);
    neuromorphic computing;
    AI edge security;
    quantum AI;
    wireless technologies;
    hybrid-cloud computing; and
    high-performance computation.

    “We live in an era where paradigm-shifting discoveries in hardware, systems communications, and computing have become mandatory to find sustainable solutions — solutions that we are proud to give to the world and generations to come,” says Aude Oliva, senior research scientist in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and director of strategic industry engagement in the MIT Schwarzman College of Computing.

    The new program is co-led by Jesús del Alamo and Aude Oliva, and Anantha Chandrakasan serves as chair. More

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    Finding her way to fusion

    “I catch myself startling people in public.”

    Zoe Fisher’s animated hands carry part of the conversation as she describes how her naturally loud and expressive laughter turned heads in the streets of Yerevan. There during MIT’s Independent Activities period (IAP), she was helping teach nuclear science at the American University of Armenia, before returning to MIT to pursue fusion research at the Plasma Science and Fusion Center (PSFC).

    Startling people may simply be in Fisher’s DNA. She admits that when she first arrived at MIT, knowing nothing about nuclear science and engineering (NSE), she chose to join that department’s Freshman Pre-Orientation Program (FPOP) “for the shock value.” It was a choice unexpected by family, friends, and mostly herself. Now in her senior year, a 2021 recipient of NSE’s Irving Kaplan Award for academic achievements by a junior and entering a fifth-year master of science program in nuclear fusion, Fisher credits that original spontaneous impulse for introducing her to a subject she found so compelling that, after exploring multiple possibilities, she had to return to it.

    Fisher’s venture to Armenia, under the guidance of NSE associate professor Areg Danagoulian, is not the only time she has taught oversees with MISTI’s Global Teaching Labs, though it is the first time she has taught nuclear science, not to mention thermodynamics and materials science. During IAP 2020 she was a student teacher at a German high school, teaching life sciences, mathematics, and even English to grades five through 12. And after her first year she explored the transportation industry with a mechanical engineering internship in Tuscany, Italy.

    By the time she was ready to declare her NSE major she had sampled the alternatives both overseas and at home, taking advantage of MIT’s Undergraduate Research Opportunities Program (UROP). Drawn to fusion’s potential as an endless source of carbon-free energy on earth, she decided to try research at the PSFC, to see if the study was a good fit. 

    Much fusion research at MIT has favored heating hydrogen fuel inside a donut-shaped device called a tokamak, creating plasma that is hot and dense enough for fusion to occur. Because plasma will follow magnetic field lines, these devices are wrapped with magnets to keep the hot fuel from damaging the chamber walls.

    Fisher was assigned to SPARC, the PSFC’s new tokamak collaboration with MIT startup Commonwealth Fusion Systems (CSF), which uses a game-changing high-temperature superconducting (HTS) tape to create fusion magnets that minimize tokamak size and maximize performance. Working on a database reference book for SPARC materials, she was finding purpose even in the most repetitive tasks. “Which is how I knew I wanted to stay in fusion,” she laughs.

    Fisher’s latest UROP assignment takes her — literally — deeper into SPARC research. She works in a basement laboratory in building NW13 nicknamed “The Vault,” on a proton accelerator whose name conjures an underworld: DANTE. Supervised by PSFC Director Dennis Whyte and postdoc David Fischer, she is exploring the effects of radiation damage on the thin HTS tape that is key to SPARC’s design, and ultimately to the success of ARC, a prototype working fusion power plant.

    Because repetitive bombardment with neutrons produced during the fusion process can diminish the superconducting properties of the HTS, it is crucial to test the tape repeatedly. Fisher assists in assembling and testing the experimental setups for irradiating the HTS samples. Fisher recalls her first project was installing a “shutter” that would allow researchers to control exactly how much radiation reached the tape without having to turn off the entire experiment.

    “You could just push the button — block the radiation — then unblock it. It sounds super simple, but it took many trials. Because first I needed the right size solenoid, and then I couldn’t find a piece of metal that was small enough, and then we needed cryogenic glue…. To this day the actual final piece is made partially of paper towels.”

    She shrugs and laughs. “It worked, and it was the cheapest option.”

    Fisher is always ready to find the fun in fusion. Referring to DANTE as “A really cool dude,” she admits, “He’s perhaps a bit fickle. I may or may not have broken him once.” During a recent IAP seminar, she joined other PSFC UROP students to discuss her research, and expanded on how a mishap can become a gateway to understanding.

    “The grad student I work with and I got to repair almost the entire internal circuit when we blew the fuse — which originally was a really bad thing. But it ended up being great because we figured out exactly how it works.”

    Fisher’s upbeat spirit makes her ideal not only for the challenges of fusion research, but for serving the MIT community. As a student representative for NSE’s Diversity, Equity and Inclusion Committee, she meets monthly with the goal of growing and supporting diversity within the department.

    “This opportunity is impactful because I get my voice, and the voices of my peers, taken seriously,” she says. “Currently, we are spending most of our efforts trying to identify and eliminate hurdles based on race, ethnicity, gender, and income that prevent people from pursuing — and applying to — NSE.”

    To break from the lab and committees, she explores the Charles River as part of MIT’s varsity sailing team, refusing to miss a sunset. She also volunteers as an FPOP mentor, seeking to provide incoming first-years with the kind of experience that will make them want to return to the topic, as she did.

    She looks forward to continuing her studies on the HTS tapes she has been irradiating, proposing to send a current pulse above the critical current through the tape, to possibly anneal any defects from radiation, which would make repairs on future fusion power plants much easier.

    Fisher credits her current path to her UROP mentors and their infectious enthusiasm for the carbon-free potential of fusion energy.

    “UROPing around the PSFC showed me what I wanted to do with my life,” she says. “Who doesn’t want to save the world?” More

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    Tuning in to invisible waves on the JET tokamak

    Research scientist Alex Tinguely is readjusting to Cambridge and Boston.

    As a postdoc with the Plasma Science and Fusion Center (PSFC), the MIT graduate spent the last two years in Oxford, England, a city he recalls can be traversed entirely “in the time it takes to walk from MIT to Harvard.” With its ancient stone walls, cathedrals, cobblestone streets, and winding paths, that small city was his home base for a big project: JET, a tokamak that is currently the largest operating magnetic fusion energy experiment in the world.

    Located at the Culham Center for Fusion Energy (CCFE), part of the U.K. Atomic Energy Authority, this key research center of the European Fusion Program has recently announced historic success. Using a 50-50 deuterium-tritium fuel mixture for the first time since 1997, JET established a fusion power record of 10 megawatts output over five seconds. It produced 59 megajoules of fusion energy, more than doubling the 22 megajoule record it set in 1997. As a member of the JET Team, Tinguely has overseen the measurement and instrumentation systems (diagnostics) contributed by the MIT group.

    A lucky chance

    The postdoctoral opportunity arose just as Tinguely was graduating with a PhD in physics from MIT. Managed by Professor Miklos Porkolab as the principal investigator for over 20 years, this postdoctoral program has prepared multiple young researchers for careers in fusion facilities around the world. The collaborative research provided Tinguely the chance to work on a fusion device that would be adding tritium to the usual deuterium fuel.

    Fusion, the process that fuels the sun and other stars, could provide a long-term source of carbon-free power on Earth, if it can be harnessed. For decades researchers have tried to create an artificial star in a doughnut-shaped bottle, or “tokamak,” using magnetic fields to keep the turbulent plasma fuel confined and away from the walls of its container long enough for fusion to occur.

    In his graduate student days at MIT, Tinguely worked on the PSFC’s Alcator C-Mod tokamak, now decommissioned, which, like most magnetic fusion devices, used deuterium to create the plasmas for experiments. JET, since beginning operation in 1983, has done the same, later joining a small number of facilities that added tritium, a radioactive isotope of hydrogen. While this addition increases the amount of fusion, it also creates much more radiation and activation.

    Tinguely considers himself fortunate to have been placed at JET.

    “There aren’t that many operating tokamaks in the U.S. right now,” says Tinguely, “not to mention one that would be running deuterium-tritium (DT), which hasn’t been run for over 20 years, and which would be making some really important measurements. I got a very lucky spot where I was an MIT postdoc, but I lived in Oxford, working on a very international project.”

    Strumming magnetic field lines

    The measurements that interest Tinguely are of low-frequency electromagnetic waves in tokamak plasmas. Tinguely uses an antenna diagnostic developed by MIT, EPFL Swiss Plasma Center, and CCFE to probe the so-called Alfvén eigenmodes when they are stable, before the energetic alpha particles produced by DT fusion plasmas can drive them toward instability.

    What makes MIT’s “Alfvén Eigenmode Active Diagnostic” essential is that without it researchers cannot see, or measure, stable eigenmodes. Unstable modes show up clearly as magnetic fluctuations in the data, but stable waves are invisible without prompting from the antenna. These measurements help researchers understand the physics of Alfvén waves and their potential for degrading fusion performance, providing insights that will be increasingly important for future DT fusion devices.

    Tinguely likens the diagnostic to fingers on guitar strings.

    “The magnetic field lines in the tokamak are like guitar strings. If you have nothing to give energy to the strings — or give energy to the waves of the magnetic field lines — they just sit there, they don’t do anything. The energetic plasma particles can essentially ‘play the guitar strings,’ strum the magnetic field lines of the plasma, and that’s when you can see the waves in your plasma. But if the energetic particle drive of the waves is not strong enough you won’t see them, so you need to come along and ‘pluck the strings’ with our antenna. And that’s how you learn some information about the waves.”

    Much of Tinguely’s experience on JET took place during the Covid-19 pandemic, when off-site operation and analysis were the norm. However, because the MIT diagnostic needed to be physically turned on and off, someone from Tinguely’s team needed to be on site twice a day, a routine that became even less convenient when tritium was introduced.

    “When you have deuterium and tritium, you produce a lot of neutrons. So, some of the buildings became off-limits during operation, which meant they had to be turned on really early in the morning, like 6:30 a.m., and then turned off very late at night, around 10:30 p.m.”

    Looking to the future

    Now a research scientist at the PSFC, Tinguely continues to work at JET remotely. He sometimes wishes he could again ride that train from Oxford to Culham — which he fondly remembers for its clean, comfortable efficiency — to see work colleagues and to visit local friends. The life he created for himself in England included practice and performance with the 125-year-old Oxford Bach Choir, as well as weekly dinner service at The Gatehouse, a facility that offers free support for the local homeless and low-income communities.

    “Being back is exciting too,” he says. “It’s fun to see how things have changed, how people and projects have grown, what new opportunities have arrived.”

    He refers specifically to a project that is beginning to take up more of his time: SPARC, the tokamak the PSFC supports in collaboration with Commonwealth Fusion Systems. Designed to use deuterium-tritium to make net fusion gains, SPARC will be able to use the latest research on JET to advantage. Tinguely is already exploring how his expertise with Alfvén eigenmodes can support the experiment.

    “I actually had an opportunity to do my PhD — or DPhil as they would call it — at Oxford University, but I went to MIT for grad school instead,” Tinguely reveals. “So, this is almost like closure, in a sense. I got to have my Oxford experience in the end, just in a different way, and have the MIT experience too.”

    He adds, “And I see myself being here at MIT for some time.” More