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    Study finds health risks in switching ships from diesel to ammonia fuel

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    As container ships the size of city blocks cross the oceans to deliver cargo, their huge diesel engines emit large quantities of air pollutants that drive climate change and have human health impacts. It has been estimated that maritime shipping accounts for almost 3 percent of global carbon dioxide emissions and the industry’s negative impacts on air quality cause about 100,000 premature deaths each year.Decarbonizing shipping to reduce these detrimental effects is a goal of the International Maritime Organization, a U.N. agency that regulates maritime transport. One potential solution is switching the global fleet from fossil fuels to sustainable fuels such as ammonia, which could be nearly carbon-free when considering its production and use.But in a new study, an interdisciplinary team of researchers from MIT and elsewhere caution that burning ammonia for maritime fuel could worsen air quality further and lead to devastating public health impacts, unless it is adopted alongside strengthened emissions regulations.Ammonia combustion generates nitrous oxide (N2O), a greenhouse gas that is about 300 times more potent than carbon dioxide. It also emits nitrogen in the form of nitrogen oxides (NO and NO2, referred to as NOx), and unburnt ammonia may slip out, which eventually forms fine particulate matter in the atmosphere. These tiny particles can be inhaled deep into the lungs, causing health problems like heart attacks, strokes, and asthma.The new study indicates that, under current legislation, switching the global fleet to ammonia fuel could cause up to about 600,000 additional premature deaths each year. However, with stronger regulations and cleaner engine technology, the switch could lead to about 66,000 fewer premature deaths than currently caused by maritime shipping emissions, with far less impact on global warming.“Not all climate solutions are created equal. There is almost always some price to pay. We have to take a more holistic approach and consider all the costs and benefits of different climate solutions, rather than just their potential to decarbonize,” says Anthony Wong, a postdoc in the MIT Center for Global Change Science and lead author of the study.His co-authors include Noelle Selin, an MIT professor in the Institute for Data, Systems, and Society and the Department of Earth, Atmospheric and Planetary Sciences (EAPS); Sebastian Eastham, a former principal research scientist who is now a senior lecturer at Imperial College London; Christine Mounaïm-Rouselle, a professor at the University of Orléans in France; Yiqi Zhang, a researcher at the Hong Kong University of Science and Technology; and Florian Allroggen, a research scientist in the MIT Department of Aeronautics and Astronautics. The research appears this week in Environmental Research Letters.Greener, cleaner ammoniaTraditionally, ammonia is made by stripping hydrogen from natural gas and then combining it with nitrogen at extremely high temperatures. This process is often associated with a large carbon footprint. The maritime shipping industry is betting on the development of “green ammonia,” which is produced by using renewable energy to make hydrogen via electrolysis and to generate heat.“In theory, if you are burning green ammonia in a ship engine, the carbon emissions are almost zero,” Wong says.But even the greenest ammonia generates nitrous oxide (N2O), nitrogen oxides (NOx) when combusted, and some of the ammonia may slip out, unburnt. This nitrous oxide would escape into the atmosphere, where the greenhouse gas would remain for more than 100 years. At the same time, the nitrogen emitted as NOx and ammonia would fall to Earth, damaging fragile ecosystems. As these emissions are digested by bacteria, additional N2O  is produced.NOx and ammonia also mix with gases in the air to form fine particulate matter. A primary contributor to air pollution, fine particulate matter kills an estimated 4 million people each year.“Saying that ammonia is a ‘clean’ fuel is a bit of an overstretch. Just because it is carbon-free doesn’t necessarily mean it is clean and good for public health,” Wong says.A multifaceted modelThe researchers wanted to paint the whole picture, capturing the environmental and public health impacts of switching the global fleet to ammonia fuel. To do so, they designed scenarios to measure how pollutant impacts change under certain technology and policy assumptions.From a technological point of view, they considered two ship engines. The first burns pure ammonia, which generates higher levels of unburnt ammonia but emits fewer nitrogen oxides. The second engine technology involves mixing ammonia with hydrogen to improve combustion and optimize the performance of a catalytic converter, which controls both nitrogen oxides and unburnt ammonia pollution.They also considered three policy scenarios: current regulations, which only limit NOx emissions in some parts of the world; a scenario that adds ammonia emission limits over North America and Western Europe; and a scenario that adds global limits on ammonia and NOx emissions.The researchers used a ship track model to calculate how pollutant emissions change under each scenario and then fed the results into an air quality model. The air quality model calculates the impact of ship emissions on particulate matter and ozone pollution. Finally, they estimated the effects on global public health.One of the biggest challenges came from a lack of real-world data, since no ammonia-powered ships are yet sailing the seas. Instead, the researchers relied on experimental ammonia combustion data from collaborators to build their model.“We had to come up with some clever ways to make that data useful and informative to both the technology and regulatory situations,” he says.A range of outcomesIn the end, they found that with no new regulations and ship engines that burn pure ammonia, switching the entire fleet would cause 681,000 additional premature deaths each year.“While a scenario with no new regulations is not very realistic, it serves as a good warning of how dangerous ammonia emissions could be. And unlike NOx, ammonia emissions from shipping are currently unregulated,” Wong says.However, even without new regulations, using cleaner engine technology would cut the number of premature deaths down to about 80,000, which is about 20,000 fewer than are currently attributed to maritime shipping emissions. With stronger global regulations and cleaner engine technology, the number of people killed by air pollution from shipping could be reduced by about 66,000.“The results of this study show the importance of developing policies alongside new technologies,” Selin says. “There is a potential for ammonia in shipping to be beneficial for both climate and air quality, but that requires that regulations be designed to address the entire range of potential impacts, including both climate and air quality.”Ammonia’s air quality impacts would not be felt uniformly across the globe, and addressing them fully would require coordinated strategies across very different contexts. Most premature deaths would occur in East Asia, since air quality regulations are less stringent in this region. Higher levels of existing air pollution cause the formation of more particulate matter from ammonia emissions. In addition, shipping volume over East Asia is far greater than elsewhere on Earth, compounding these negative effects.In the future, the researchers want to continue refining their analysis. They hope to use these findings as a starting point to urge the marine industry to share engine data they can use to better evaluate air quality and climate impacts. They also hope to inform policymakers about the importance and urgency of updating shipping emission regulations.This research was funded by the MIT Climate and Sustainability Consortium. More

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      School of Engineering welcomes new faculty

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      The School of Engineering welcomes 15 new faculty members across six of its academic departments. This new cohort of faculty members, who have either recently started their roles at MIT or will start within the next year, conduct research across a diverse range of disciplines.Many of these new faculty specialize in research that intersects with multiple fields. In addition to positions in the School of Engineering, a number of these faculty have positions at other units across MIT. Faculty with appointments in the Department of Electrical Engineering and Computer Science (EECS) report into both the School of Engineering and the MIT Stephen A. Schwarzman College of Computing. This year, new faculty also have joint appointments between the School of Engineering and the School of Humanities, Arts, and Social Sciences and the School of Science.“I am delighted to welcome this cohort of talented new faculty to the School of Engineering,” says Anantha Chandrakasan, chief innovation and strategy officer, dean of engineering, and Vannevar Bush Professor of Electrical Engineering and Computer Science. “I am particularly struck by the interdisciplinary approach many of these new faculty take in their research. They are working in areas that are poised to have tremendous impact. I look forward to seeing them grow as researchers and educators.”The new engineering faculty include:Stephen Bates joined the Department of Electrical Engineering and Computer Science as an assistant professor in September 2023. He is also a member of the Laboratory for Information and Decision Systems (LIDS). Bates uses data and AI for reliable decision-making in the presence of uncertainty. In particular, he develops tools for statistical inference with AI models, data impacted by strategic behavior, and settings with distribution shift. Bates also works on applications in life sciences and sustainability. He previously worked as a postdoc in the Statistics and EECS departments at the University of California at Berkeley (UC Berkeley). Bates received a BS in statistics and mathematics at Harvard University and a PhD from Stanford University.Abigail Bodner joined the Department of EECS and Department of Earth, Atmospheric and Planetary Sciences as an assistant professor in January. She is also a member of the LIDS. Bodner’s research interests span climate, physical oceanography, geophysical fluid dynamics, and turbulence. Previously, she worked as a Simons Junior Fellow at the Courant Institute of Mathematical Sciences at New York University. Bodner received her BS in geophysics and mathematics and MS in geophysics from Tel Aviv University, and her SM in applied mathematics and PhD from Brown University.Andreea Bobu ’17 will join the Department of Aeronautics and Astronautics as an assistant professor in July. Her research sits at the intersection of robotics, mathematical human modeling, and deep learning. Previously, she was a research scientist at the Boston Dynamics AI Institute, focusing on how robots and humans can efficiently arrive at shared representations of their tasks for more seamless and reliable interactions. Bobu earned a BS in computer science and engineering from MIT and a PhD in electrical engineering and computer science from UC Berkeley.Suraj Cheema will join the Department of Materials Science and Engineering, with a joint appointment in the Department of EECS, as an assistant professor in July. His research explores atomic-scale engineering of electronic materials to tackle challenges related to energy consumption, storage, and generation, aiming for more sustainable microelectronics. This spans computing and energy technologies via integrated ferroelectric devices. He previously worked as a postdoc at UC Berkeley. Cheema earned a BS in applied physics and applied mathematics from Columbia University and a PhD in materials science and engineering from UC Berkeley.Samantha Coday joins the Department of EECS as an assistant professor in July. She will also be a member of the MIT Research Laboratory of Electronics. Her research interests include ultra-dense power converters enabling renewable energy integration, hybrid electric aircraft and future space exploration. To enable high-performance converters for these critical applications her research focuses on the optimization, design, and control of hybrid switched-capacitor converters. Coday earned a BS in electrical engineering and mathematics from Southern Methodist University and an MS and a PhD in electrical engineering and computer science from UC Berkeley.Mitchell Gordon will join the Department of EECS as an assistant professor in July. He will also be a member of the MIT Computer Science and Artificial Intelligence Laboratory. In his research, Gordon designs interactive systems and evaluation approaches that bridge principles of human-computer interaction with the realities of machine learning. He currently works as a postdoc at the University of Washington. Gordon received a BS from the University of Rochester, and MS and PhD from Stanford University, all in computer science.Kaiming He joined the Department of EECS as an associate professor in February. He will also be a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His research interests cover a wide range of topics in computer vision and deep learning. He is currently focused on building computer models that can learn representations and develop intelligence from and for the complex world. Long term, he hopes to augment human intelligence with improved artificial intelligence. Before joining MIT, He was a research scientist at Facebook AI. He earned a BS from Tsinghua University and a PhD from the Chinese University of Hong Kong.Anna Huang SM ’08 will join the departments of EECS and Music and Theater Arts as assistant professor in September. She will help develop graduate programming focused on music technology. Previously, she spent eight years with Magenta at Google Brain and DeepMind, spearheading efforts in generative modeling, reinforcement learning, and human-computer interaction to support human-AI partnerships in music-making. She is the creator of Music Transformer and Coconet (which powered the Bach Google Doodle). She was a judge and organizer for the AI Song Contest. Anna holds a Canada CIFAR AI Chair at Mila, a BM in music composition, and BS in computer science from the University of Southern California, an MS from the MIT Media Lab, and a PhD from Harvard University.Yael Kalai PhD ’06 will join the Department of EECS as a professor in September. She is also a member of CSAIL. Her research interests include cryptography, the theory of computation, and security and privacy. Kalai currently focuses on both the theoretical and real-world applications of cryptography, including work on succinct and easily verifiable non-interactive proofs. She received her bachelor’s degree from the Hebrew University of Jerusalem, a master’s degree at the Weizmann Institute of Science, and a PhD from MIT.Sendhil Mullainathan will join the departments of EECS and Economics as a professor in July. His research uses machine learning to understand complex problems in human behavior, social policy, and medicine. Previously, Mullainathan spent five years at MIT before joining the faculty at Harvard in 2004, and then the University of Chicago in 2018. He received his BA in computer science, mathematics, and economics from Cornell University and his PhD from Harvard University.Alex Rives will join the Department of EECS as an assistant professor in September, with a core membership in the Broad Institute of MIT and Harvard. In his research, Rives is focused on AI for scientific understanding, discovery, and design for biology. Rives worked with Meta as a New York University graduate student, where he founded and led the Evolutionary Scale Modeling team that developed large language models for proteins. Rives received his BS in philosophy and biology from Yale University and is completing his PhD in computer science at NYU.Sungho Shin will join the Department of Chemical Engineering as an assistant professor in July. His research interests include control theory, optimization algorithms, high-performance computing, and their applications to decision-making in complex systems, such as energy infrastructures. Shin is a postdoc at the Mathematics and Computer Science Division at Argonne National Laboratory. He received a BS in mathematics and chemical engineering from Seoul National University and a PhD in chemical engineering from the University of Wisconsin-Madison.Jessica Stark joined the Department of Biological Engineering as an assistant professor in January. In her research, Stark is developing technologies to realize the largely untapped potential of cell-surface sugars, called glycans, for immunological discovery and immunotherapy. Previously, Stark was an American Cancer Society postdoc at Stanford University. She earned a BS in chemical and biomolecular engineering from Cornell University and a PhD in chemical and biological engineering at Northwestern University.Thomas John “T.J.” Wallin joined the Department of Materials Science and Engineering as an assistant professor in January. As a researcher, Wallin’s interests lay in advanced manufacturing of functional soft matter, with an emphasis on soft wearable technologies and their applications in human-computer interfaces. Previously, he was a research scientist at Meta’s Reality Labs Research working in their haptic interaction team. Wallin earned a BS in physics and chemistry from the College of William and Mary, and an MS and PhD in materials science and engineering from Cornell University.Gioele Zardini joined the Department of Civil and Environmental Engineering as an assistant professor in September. He will also join LIDS and the Institute for Data, Systems, and Society. Driven by societal challenges, Zardini’s research interests include the co-design of sociotechnical systems, compositionality in engineering, applied category theory, decision and control, optimization, and game theory, with society-critical applications to intelligent transportation systems, autonomy, and complex networks and infrastructures. He received his BS, MS, and PhD in mechanical engineering with a focus on robotics, systems, and control from ETH Zurich, and spent time at MIT, Stanford University, and Motional. More

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      in Environment

      Shining a light on oil fields to make them more sustainable

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      Operating an oil field is complex and there is a staggeringly long list of things that can go wrong.

      One of the most common problems is spills of the salty brine that’s a toxic byproduct of pumping oil. Another is over- or under-pumping that can lead to machine failure and methane leaks. (The oil and gas industry is the largest industrial emitter of methane in the U.S.) Then there are extreme weather events, which range from winter frosts to blazing heat, that can put equipment out of commission for months. One of the wildest problems Sebastien Mannai SM ’14, PhD ’18 has encountered are hogs that pop open oil tanks with their snouts to enjoy on-demand oil baths.

      Mannai helps oil field owners detect and respond to these problems while optimizing the operation of their machinery to prevent the issues from occurring in the first place. He is the founder and CEO of Amplified Industries, a company selling oil field monitoring and control tools that help make the industry more efficient and sustainable.

      Amplified Industries’ sensors and analytics give oil well operators real-time alerts when things go wrong, allowing them to respond to issues before they become disasters.

      “We’re able to find 99 percent of the issues affecting these machines, from mechanical failures to human errors, including issues happening thousands of feet underground,” Mannai explains. “With our AI solution, operators can put the wells on autopilot, and the system automatically adjusts or shuts the well down as soon as there’s an issue.”

      Amplified currently works with private companies in states spanning from Texas to Wyoming, that own and operate as many as 3,000 wells. Such companies make up the majority of oil well operators in the U.S. and operate both new and older, more failure-prone equipment that has been in the field for decades.

      Such operators also have a harder time responding to environmental regulations like the Environmental Protection Agency’s new methane guidelines, which seek to dramatically reduce emissions of the potent greenhouse gas in the industry over the next few years.

      “These operators don’t want to be releasing methane,” Mannai explains. “Additionally, when gas gets into the pumping equipment, it leads to premature failures. We can detect gas and slow the pump down to prevent it. It’s the best of both worlds: The operators benefit because their machines are working better, saving them money while also giving them a smaller environmental footprint with fewer spills and methane leaks.”

      Leveraging “every MIT resource I possibly could”

      Mannai learned about the cutting-edge technology used in the space and aviation industries as he pursued his master’s degree at the Gas Turbine Laboratory in MIT’s Department of Aeronautics and Astronautics. Then, during his PhD at MIT, he worked with an oil services company and discovered the oil and gas industry was still relying on decades-old technologies and equipment.

      “When I first traveled to the field, I could not believe how old-school the actual operations were,” says Mannai, who has previously worked in rocket engine and turbine factories. “A lot of oil wells have to be adjusted by feel and rules of thumb. The operators have been let down by industrial automation and data companies.”

      Monitoring oil wells for problems typically requires someone in a pickup truck to drive hundreds of miles between wells looking for obvious issues, Mannai says. The sensors that are deployed are expensive and difficult to replace. Over time, they’re also often damaged in the field to the point of being unusable, forcing technicians to make educated guesses about the status of each well.

      “We often see that equipment unplugged or programmed incorrectly because it is incredibly over-complicated and ill-designed for the reality of the field,” Mannai says. “Workers on the ground often have to rip it out and bypass the control system to pump by hand. That’s how you end up with so many spills and wells pumping at suboptimal levels.”

      To build a better oil field monitoring system, Mannai received support from the MIT Sandbox Innovation Fund and the Venture Mentoring Service (VMS). He also participated in the delta V summer accelerator at the Martin Trust Center for MIT Entrepreneurship, the fuse program during IAP, and the MIT I-Corps program, and took a number of classes at the MIT Sloan School of Management. In 2019, Amplified Industries — which operated under the name Acoustic Wells until recently — won the MIT $100K Entrepreneurship competition.

      “My approach was to sign up to every possible entrepreneurship related program and to leverage every MIT resource I possibly could,” Mannai says. “MIT was amazing for us.”

      Mannai officially launched the company after his postdoc at MIT, and Amplified raised its first round of funding in early 2020. That year, Amplified’s small team moved into the Greentown Labs startup incubator in Somerville.

      Mannai says building the company’s battery-powered, low-cost sensors was a huge challenge. The sensors run machine-learning inference models and their batteries last for 10 years. They also had to be able to handle extreme conditions, from the scorching hot New Mexico desert to the swamps of Louisiana and the freezing cold winters in North Dakota.

      “We build very rugged, resilient hardware; it’s a must in those environments” Mannai says. “But it’s also very simple to deploy, so if a device does break, it’s like changing a lightbulb: We ship them a new one and it takes them a couple of minutes to swap it out.”

      Customers equip each well with four or five of Amplified’s sensors, which attach to the well’s cables and pipes to measure variables like tension, pressure, and amps. Vast amounts of data are then sent to Amplified’s cloud and processed by their analytics engine. Signal processing methods and AI models are used to diagnose problems and control the equipment in real-time, while generating notifications for the operators when something goes wrong. Operators can then remotely adjust the well or shut it down.

      “That’s where AI is important, because if you just record everything and put it in a giant dashboard, you create way more work for people,” Mannai says. “The critical part is the ability to process and understand this newly recorded data and make it readily usable in the real world.”

      Amplified’s dashboard is customized for different people in the company, so field technicians can quickly respond to problems and managers or owners can get a high-level view of how everything is running.

      Mannai says often when Amplified’s sensors are installed, they’ll immediately start detecting problems that were unknown to engineers and technicians in the field. To date, Amplified has prevented hundreds of thousands of gallons worth of brine water spills, which are particularly damaging to surrounding vegetation because of their high salt and sulfur content.

      Preventing those spills is only part of Amplified’s positive environmental impact; the company is now turning its attention toward the detection of methane leaks.

      Helping a changing industry

      The EPA’s proposed new Waste Emissions Charge for oil and gas companies would start at $900 per metric ton of reported methane emissions in 2024 and increase to $1,500 per metric ton in 2026 and beyond.

      Mannai says Amplified is well-positioned to help companies comply with the new rules. Its equipment has already showed it can detect various kinds of leaks across the field, purely based on analytics of existing data.

      “Detecting methane leaks typically requires someone to walk around every valve and piece of piping with a thermal camera or sniffer, but these operators often have thousands of valves and hundreds of miles of pipes,” Mannai says. “What we see in the field is that a lot of times people don’t know where the pipes are because oil wells change owners so frequently, or they will miss an intermittent leak.”

      Ultimately Mannai believes a strong data backend and modernized sensing equipment will become the backbone of the industry, and is a necessary prerequisite to both improving efficiency and cleaning up the industry.

      “We’re selling a service that ensures your equipment is working optimally all the time,” Mannai says. “That means a lot fewer fines from the EPA, but it also means better-performing equipment. There’s a mindset change happening across the industry, and we’re helping make that transition as easy and affordable as possible.” More

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      in Environment

      Researchers release open-source space debris model

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      MIT’s Astrodynamics, Space Robotics, and Controls Laboratory (ARCLab) announced the public beta release of the MIT Orbital Capacity Assessment Tool (MOCAT) during the 2023 Organization for Economic Cooperation and Development (OECD) Space Forum Workshop on Dec. 14. MOCAT enables users to model the long-term future space environment to understand growth in space debris and assess the effectiveness of debris-prevention mechanisms.

      With the escalating congestion in low Earth orbit, driven by a surge in satellite deployments, the risk of collisions and space debris proliferation is a pressing concern. Conducting thorough space environment studies is critical for developing effective strategies for fostering responsible and sustainable use of space resources. 

      MOCAT stands out among orbital modeling tools for its capability to model individual objects, diverse parameters, orbital characteristics, fragmentation scenarios, and collision probabilities. With the ability to differentiate between object categories, generalize parameters, and offer multi-fidelity computations, MOCAT emerges as a versatile and powerful tool for comprehensive space environment analysis and management.

      MOCAT is intended to provide an open-source tool to empower stakeholders including satellite operators, regulators, and members of the public to make data-driven decisions. The ARCLab team has been developing these models for the last several years, recognizing that the lack of open-source implementation of evolutionary modeling tools limits stakeholders’ ability to develop consensus on actions to help improve space sustainability. This beta release is intended to allow users to experiment with the tool and provide feedback to help guide further development.

      Richard Linares, the principal investigator for MOCAT and an MIT associate professor of aeronautics and astronautics, expresses excitement about the tool’s potential impact: “MOCAT represents a significant leap forward in orbital capacity assessment. By making it open-source and publicly available, we hope to engage the global community in advancing our understanding of satellite orbits and contributing to the sustainable use of space.”

      MOCAT consists of two main components. MOCAT-MC evaluates space environment evolution with individual trajectory simulation and Monte Carlo parameter analysis, providing both a high-level overall view for the environment and a fidelity analysis into the individual space objects evolution. MOCAT Source Sink Evolutionary Model (MOCAT-SSEM), meanwhile, uses a lower-fidelity modeling approach that can run on personal computers within seconds to minutes. MOCAT-MC and MOCAT-SSEM can be accessed separately via GitHub.

      MOCAT’s initial development has been supported by the Defense Advanced Research Projects Agency (DARPA) and NASA’s Office of Technology and Strategy.

      “We are thrilled to support this groundbreaking orbital debris modeling work and the new knowledge it created,” says Charity Weeden, associate administrator for the Office of Technology, Policy, and Strategy at NASA headquarters in Washington. “This open-source modeling tool is a public good that will advance space sustainability, improve evidence-based policy analysis, and help all users of space make better decisions.” More

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      in Environment

      Forging climate connections across the Institute

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      Climate change is the ultimate cross-cutting issue: Not limited to any one discipline, it ranges across science, technology, policy, culture, human behavior, and well beyond. The response to it likewise requires an all-of-MIT effort.

      Now, to strengthen such an effort, a new grant program spearheaded by the Climate Nucleus, the faculty committee charged with the oversight and implementation of Fast Forward: MIT’s Climate Action Plan for the Decade, aims to build up MIT’s climate leadership capacity while also supporting innovative scholarship on diverse climate-related topics and forging new connections across the Institute.

      Called the Fast Forward Faculty Fund (F^4 for short), the program has named its first cohort of six faculty members after issuing its inaugural call for proposals in April 2023. The cohort will come together throughout the year for climate leadership development programming and networking. The program provides financial support for graduate students who will work with the faculty members on the projects — the students will also participate in leadership-building activities — as well as $50,000 in flexible, discretionary funding to be used to support related activities. 

      “Climate change is a crisis that truly touches every single person on the planet,” says Noelle Selin, co-chair of the nucleus and interim director of the Institute for Data, Systems, and Society. “It’s therefore essential that we build capacity for every member of the MIT community to make sense of the problem and help address it. Through the Fast Forward Faculty Fund, our aim is to have a cohort of climate ambassadors who can embed climate everywhere at the Institute.”

      F^4 supports both faculty who would like to begin doing climate-related work, as well as faculty members who are interested in deepening their work on climate. The program has the core goal of developing cohorts of F^4 faculty and graduate students who, in addition to conducting their own research, will become climate leaders at MIT, proactively looking for ways to forge new climate connections across schools, departments, and disciplines.

      One of the projects, “Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies,” led by Professor Siqi Zheng of the MIT Center for Real Estate in collaboration with colleagues from the MIT Sloan School of Management, focuses on the roughly 40 percent of carbon dioxide emissions that come from the buildings and real estate sector. Zheng notes that this sector has been slow to respond to climate change, but says that is starting to change, thanks in part to the rising awareness of climate risks and new local regulations aimed at reducing emissions from buildings.

      Using a data-driven approach, the project seeks to understand the efficient and equitable market incentives, technology solutions, and public policies that are most effective at transforming the real estate industry. Johnattan Ontiveros, a graduate student in the Technology and Policy Program, is working with Zheng on the project.

      “We were thrilled at the incredible response we received from the MIT faculty to our call for proposals, which speaks volumes about the depth and breadth of interest in climate at MIT,” says Anne White, nucleus co-chair and vice provost and associate vice president for research. “This program makes good on key commitments of the Fast Forward plan, supporting cutting-edge new work by faculty and graduate students while helping to deepen the bench of climate leaders at MIT.”

      During the 2023-24 academic year, the F^4 faculty and graduate student cohorts will come together to discuss their projects, explore opportunities for collaboration, participate in climate leadership development, and think proactively about how to deepen interdisciplinary connections among MIT community members interested in climate change.

      The six inaugural F^4 awardees are:

      Professor Tristan Brown, History Section: Humanistic Approaches to the Climate Crisis  

      With this project, Brown aims to create a new community of practice around narrative-centric approaches to environmental and climate issues. Part of a broader humanities initiative at MIT, it brings together a global working group of interdisciplinary scholars, including Serguei Saavedra (Department of Civil and Environmental Engineering) and Or Porath (Tel Aviv University; Religion), collectively focused on examining the historical and present links between sacred places and biodiversity for the purposes of helping governments and nongovernmental organizations formulate better sustainability goals. Boyd Ruamcharoen, a PhD student in the History, Anthropology, and Science, Technology, and Society (HASTS) program, will work with Brown on this project.

      Professor Kerri Cahoy, departments of Aeronautics and Astronautics and Earth, Atmospheric, and Planetary Sciences (AeroAstro): Onboard Autonomous AI-driven Satellite Sensor Fusion for Coastal Region Monitoring

      The motivation for this project is the need for much better data collection from satellites, where technology can be “20 years behind,” says Cahoy. As part of this project, Cahoy will pursue research in the area of autonomous artificial intelligence-enabled rapid sensor fusion (which combines data from different sensors, such as radar and cameras) onboard satellites to improve understanding of the impacts of climate change, specifically sea-level rise and hurricanes and flooding in coastal regions. Graduate students Madeline Anderson, a PhD student in electrical engineering and computer science (EECS), and Mary Dahl, a PhD student in AeroAstro, will work with Cahoy on this project.

      Professor Priya Donti, Department of Electrical Engineering and Computer Science: Robust Reinforcement Learning for High-Renewables Power Grids 

      With renewables like wind and solar making up a growing share of electricity generation on power grids, Donti’s project focuses on improving control methods for these distributed sources of electricity. The research will aim to create a realistic representation of the characteristics of power grid operations, and eventually inform scalable operational improvements in power systems. It will “give power systems operators faith that, OK, this conceptually is good, but it also actually works on this grid,” says Donti. PhD candidate Ana Rivera from EECS is the F^4 graduate student on the project.

      Professor Jason Jackson, Department of Urban Studies and Planning (DUSP): Political Economy of the Climate Crisis: Institutions, Power and Global Governance

      This project takes a political economy approach to the climate crisis, offering a distinct lens to examine, first, the political governance challenge of mobilizing climate action and designing new institutional mechanisms to address the global and intergenerational distributional aspects of climate change; second, the economic challenge of devising new institutional approaches to equitably finance climate action; and third, the cultural challenge — and opportunity — of empowering an adaptive socio-cultural ecology through traditional knowledge and local-level social networks to achieve environmental resilience. Graduate students Chen Chu and Mrinalini Penumaka, both PhD students in DUSP, are working with Jackson on the project.

      Professor Haruko Wainwright, departments of Nuclear Science and Engineering (NSE) and Civil and Environmental Engineering: Low-cost Environmental Monitoring Network Technologies in Rural Communities for Addressing Climate Justice 

      This project will establish a community-based climate and environmental monitoring network in addition to a data visualization and analysis infrastructure in rural marginalized communities to better understand and address climate justice issues. The project team plans to work with rural communities in Alaska to install low-cost air and water quality, weather, and soil sensors. Graduate students Kay Whiteaker, an MS candidate in NSE, and Amandeep Singh, and MS candidate in System Design and Management at Sloan, are working with Wainwright on the project, as is David McGee, professor in earth, atmospheric, and planetary sciences.

      Professor Siqi Zheng, MIT Center for Real Estate and DUSP: Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies 

      See the text above for the details on this project. More

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      in Environment

      Transatlantic connections make the difference for MIT Portugal

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      Successful relationships take time to develop, with both parties investing energy and resources and fostering mutual trust and understanding. The MIT Portugal Program (MPP), a strategic partnership between MIT, Portuguese universities and research institutions, and the Portuguese government, is a case in point.

      Portugal’s inaugural partnership with a U.S. university, MPP was established in 2006 as a collaboration between MIT and the Portuguese Science and Technology Foundation (Fundação para a Ciência e Tecnologia, or FCT). Since then, the program has developed research platforms in areas such as bioengineering, sustainable energy, transportation systems, engineering design, and advanced manufacturing. Now halfway through its third phase (MPP2030, begun in 2018), the program owes much of its success to the bonds connecting institutions and people across the Atlantic over the past 17 years.

      “When you look at the successes and the impact, these things don’t happen overnight,” says John Hansman, the T. Wilson Professor of Aeronautics and Astronautics at MIT and co-director of MPP, noting, in particular, MPP’s achievements in the areas of energy and ocean research, as well as bioengineering. “This has been a longstanding relationship that we have and want to continue. I think it’s been beneficial to Portugal and to MIT. I think you can argue it has made substantial contributions to the success that Portugal is currently experiencing both in its technical capabilities and also its energy policy.”

      With research often aimed at climate and sustainability solutions, one of MPP’s key strengths is its education of future leaders in science, technology, and entrepreneurship. And the program’s impacts carry forward, as several former MPP students are now on the faculty at participating Portuguese universities.

      “The original intent of working together with Portugal was to try to establish collaboration between universities and to instill some of the MIT culture with the culture in Portugal, and I think that’s been hugely successful,” says Douglas Hart, MPP co-director and professor of mechanical engineering at MIT. “It has had a lot of impacts in terms of the research, but also the people.”

      One of those people is André Pina, associate director of H2 strategy and origination at the company EDP, who was in residence at MIT in 2014 as part of the MPP Sustainable Energy Systems Doctoral Program. He says the competencies and experiences he acquired have been critical to his professional development in energy system planning, have influenced his approach to problem solving, and have allowed him to bring “holistic thinking” to business endeavors.

      “The MIT Portugal Program has created a collaborative ecosystem between Portuguese universities, companies, and MIT that enabled the training of highly qualified professionals, while contributing to the positioning of Portuguese companies in new cutting-edge fields,” he says.

      Building on MPP’s previous successes, MPP2030 focuses on advancing research in four strategic areas: climate science and climate change; earth systems from oceans to near space; digital transformation in manufacturing; and sustainable cities — all involving data science-intensive approaches and methodologies. Within these broad scientific areas, FCT funding has enabled seven collaborative large-scale “flagship” projects between Portuguese and MIT researchers during the current phase, as well as dozens of smaller projects.

      Flagship projects currently underway include:

      ·   AEROS Constellation

      ·   C-Tech: Climate Driven Technologies for Low Carbon Cities

      ·   K2D: Knowledge and Data from the Deep to Space

      ·   NEWSAT

      ·   Operator: Digital Transformation in Industry with a Focus on the Operator 4.0

      ·   SNOB-5G: Scalable Network Backhauling for 5G

      ·   Transformer 4.0: Digital Revolution of Power Transformers

      Sustainability plays a significant role in MPP — reflective of the value both Portugal and MIT place on environmental, energy, and climate solutions. Projects under the Sustainable Cities strategic area, for example, are “helping cities in Portugal to become more efficient and more sustainable,” Hansman says, noting that MPP’s influence is being felt in cities across the country and it is “having a big impact in terms of local city planning activities.”

      Regarding energy, Hansman points to a previous MPP phase that focused on the Azores as an isolated energy ecosystem and investigated its ability to minimize energy use and become energy independent.

      “That view of system-level energy use helped to stimulate activity on the mainland in Portugal, which has helped Portugal become a leader in various energy sources and made them less vulnerable in the last year or two,” Hansman says.

      In the Oceans to Near Space strategic area, the K2D flagship project also emphasizes research into sustainability solutions, as well as resilience to environmental change. Over the past few years, K2D researchers in Portugal and MIT have worked together to develop components that permit cost-effective gathering of chemical, physical, biological, and environmental data from the ocean depths. One current project investigates the integration of autonomous underwater vehicles with subsea cables to enhance both environmental monitoring and hazard warning systems.

      “The program has been very successful,” Hart says. “They are now deploying a 2-kilometer cable just south of Lisbon, which will be in place in another month or so. Portugal has been hit with tsunamis that caused tremendous devastation, and one of the objectives of these cables is to sense tsunamis. So, it’s an early warning system.”

      As a leader in ocean technology with a long history of maritime discovery, Portugal provides many opportunities for MIT’s ocean researchers. Hart notes that the Portuguese military invites international researchers on board its ships, providing MIT with research opportunities that would be financially difficult otherwise.

      Hansman adds that partnering with researchers in the Azores provides MIT with unique access to facilities and labs in the middle of the Atlantic Ocean. For example, Hart will be teaching at a marine robotics summer school in the Azores this July.

      Cadence Payne, an MIT PhD candidate, is among those planning to attend. Through MPP’s AEROS project, Payne has helped develop a modular “cubesat” that will orbit over Portugal’s Exclusive Economic Zone collecting images and radio data to help define the ecological health of the country’s coastal waters. The nanosatellite is expected to launch in late 2023 or early 2024, says Payne, adding that it will be Portugal’s first cubesat mission.

      “In monitoring the ocean, you’re monitoring the climate,” Payne says. “If you want to do work on detecting climate change and developing methods of mitigating climate change … it helps to integrate international collaboration,” she says, adding that, for students, “it’s been a really beautiful opportunity for us to see the benefits of collaboration.”

      “I would say one of the main benefits of working with Portugal is that we share many interests in research in the sense that they’re very interested in climate change, sustainability, environmental impacts and those kinds of things,” says Hart. “They have turned out to be a very good strategic partner for MIT, and, hopefully, MIT for them.” More

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      in Environment

      Megawatt electrical motor designed by MIT engineers could help electrify aviation

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      Aviation’s huge carbon footprint could shrink significantly with electrification. To date, however, only small all-electric planes have gotten off the ground. Their electric motors generate hundreds of kilowatts of power. To electrify larger, heavier jets, such as commercial airliners, megawatt-scale motors are required. These would be propelled by hybrid or turbo-electric propulsion systems where an electrical machine is coupled with a gas turbine aero-engine.

      To meet this need, a team of MIT engineers is now creating a 1-megawatt motor that could be a key stepping stone toward electrifying larger aircraft. The team has designed and tested the major components of the motor, and shown through detailed computations that the coupled components can work as a whole to generate one megawatt of power, at a weight and size competitive with current small aero-engines.

      For all-electric applications, the team envisions the motor could be paired with a source of electricity such as a battery or a fuel cell. The motor could then turn the electrical energy into mechanical work to power a plane’s propellers. The electrical machine could also be paired with a traditional turbofan jet engine to run as a hybrid propulsion system, providing electric propulsion during certain phases of a flight.

      “No matter what we use as an energy carrier — batteries, hydrogen, ammonia, or sustainable aviation fuel — independent of all that, megawatt-class motors will be a key enabler for greening aviation,” says Zoltan Spakovszky, the T. Wilson Professor in Aeronautics and the Director of the Gas Turbine Laboratory (GTL) at MIT, who leads the project.

      Spakovszky and members of his team, along with industry collaborators, will present their work at a special session of the American Institute of Aeronautics and Astronautics – Electric Aircraft Technologies Symposium (EATS) at the Aviation conference in June.

      The MIT team is composed of faculty, students, and research staff from GTL and the MIT Laboratory for Electromagnetic and Electronic Systems: Henry Andersen Yuankang Chen, Zachary Cordero, David Cuadrado,  Edward Greitzer, Charlotte Gump, James Kirtley, Jr., Jeffrey Lang, David Otten, David Perreault, and Mohammad Qasim,  along with Marc Amato of Innova-Logic LLC. The project is sponsored by Mitsubishi Heavy Industries (MHI).

      Heavy stuff

      To prevent the worst impacts from human-induced climate change, scientists have determined that global emissions of carbon dioxide must reach net zero by 2050. Meeting this target for aviation, Spakovszky says, will require “step-change achievements” in the design of unconventional aircraft, smart and flexible fuel systems, advanced materials, and safe and efficient electrified propulsion. Multiple aerospace companies are focused on electrified propulsion and the design of megawatt-scale electric machines that are powerful and light enough to propel passenger aircraft.

      “There is no silver bullet to make this happen, and the devil is in the details,” Spakovszky says. “This is hard engineering, in terms of co-optimizing individual components and making them compatible with each other while maximizing overall performance. To do this means we have to push the boundaries in materials, manufacturing, thermal management, structures and rotordynamics, and power electronics”

      Broadly speaking, an electric motor uses electromagnetic force to generate motion. Electric motors, such as those that power the fan in your laptop, use electrical energy — from a battery or power supply — to generate a magnetic field, typically through copper coils. In response, a magnet, set near the coils, then spins in the direction of the generated field and can then drive a fan or propeller.

      Electric machines have been around for over 150 years, with the understanding that, the bigger the appliance or vehicle, the larger the copper coils  and the magnetic rotor, making the machine heavier. The more power the electrical machine generates, the more heat it produces, which requires additional elements to keep the components cool — all of which can take up space and add significant weight to the system, making it challenging for airplane applications.

      “Heavy stuff doesn’t go on airplanes,” Spakovszky says. “So we had to come up with a compact, lightweight, and powerful architecture.”

      Good trajectory

      As designed, the MIT electric motor and power electronics are each about the size of a checked suitcase weighing less than an adult passenger.

      The motor’s main components are: a high-speed rotor, lined with an array of magnets with varying orientation of polarity; a compact low-loss stator that fits inside the rotor and contains an intricate array of copper windings; an advanced heat exchanger that keeps the components cool while transmitting the torque of the machine; and a distributed power electronics system, made from 30 custom-built circuit boards, that precisely change the currents running through each of the stator’s copper windings, at high frequency.

      “I believe this is the first truly co-optimized integrated design,” Spakovszky says. “Which means we did a very extensive design space exploration where all considerations from thermal management, to rotor dynamics, to power electronics and electrical machine architecture were assessed in an integrated way to find out what is the best possible combination to get the required specific power at one megawatt.”

      As a whole system, the motor is designed such that the distributed circuit boards are close coupled with the electrical machine to minimize transmission loss and to allow effective air cooling through the integrated heat exchanger.

      “This is a high-speed machine, and to keep it rotating while creating torque, the magnetic fields have to be traveling very quickly, which we can do through our circuit boards switching at high frequency,” Spakovszky says.

      To mitigate risk, the team has built and tested each of the major components individually, and shown that they can operate as designed and at conditions exceeding normal operational demands. The researchers plan to assemble the first fully working electric motor, and start testing it in the fall.

      “The electrification of aircraft has been on a steady rise,” says Phillip Ansell, director of the Center for Sustainable Aviation at the University of Illinois Urbana-Champaign, who was not involved in the project. “This group’s design uses a wonderful combination of conventional and cutting-edge methods for electric machine development, allowing it to offer both robustness and efficiency to meet the practical needs of aircraft of the future.”

      Once the MIT team can demonstrate the electric motor as a whole, they say the design could power regional aircraft and could also be a companion to conventional jet engines, to enable hybrid-electric propulsion systems. The team also envision that multiple one-megawatt motors could power multiple fans distributed along the wing on future aircraft configurations. Looking ahead, the foundations of the one-megawatt electrical machine design could potentially be scaled up to multi-megawatt motors, to power larger passenger planes.

      “I think we’re on a good trajectory,” says Spakovszky, whose group and research have focused on more than just gas turbines. “We are not electrical engineers by training, but addressing the 2050 climate grand challenge is of utmost importance; working with electrical engineering faculty, staff and students for this goal can draw on MIT’s breadth of technologies so the whole is greater than the sum of the parts. So we are reinventing ourselves in new areas. And MIT gives you the opportunity to do that.” More

    • 175 Shares189 Views

      in Energy

      Computers that power self-driving cars could be a huge driver of global carbon emissions

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      In the future, the energy needed to run the powerful computers on board a global fleet of autonomous vehicles could generate as many greenhouse gas emissions as all the data centers in the world today.

      That is one key finding of a new study from MIT researchers that explored the potential energy consumption and related carbon emissions if autonomous vehicles are widely adopted.

      The data centers that house the physical computing infrastructure used for running applications are widely known for their large carbon footprint: They currently account for about 0.3 percent of global greenhouse gas emissions, or about as much carbon as the country of Argentina produces annually, according to the International Energy Agency. Realizing that less attention has been paid to the potential footprint of autonomous vehicles, the MIT researchers built a statistical model to study the problem. They determined that 1 billion autonomous vehicles, each driving for one hour per day with a computer consuming 840 watts, would consume enough energy to generate about the same amount of emissions as data centers currently do.

      The researchers also found that in over 90 percent of modeled scenarios, to keep autonomous vehicle emissions from zooming past current data center emissions, each vehicle must use less than 1.2 kilowatts of power for computing, which would require more efficient hardware. In one scenario — where 95 percent of the global fleet of vehicles is autonomous in 2050, computational workloads double every three years, and the world continues to decarbonize at the current rate — they found that hardware efficiency would need to double faster than every 1.1 years to keep emissions under those levels.

      “If we just keep the business-as-usual trends in decarbonization and the current rate of hardware efficiency improvements, it doesn’t seem like it is going to be enough to constrain the emissions from computing onboard autonomous vehicles. This has the potential to become an enormous problem. But if we get ahead of it, we could design more efficient autonomous vehicles that have a smaller carbon footprint from the start,” says first author Soumya Sudhakar, a graduate student in aeronautics and astronautics.

      Sudhakar wrote the paper with her co-advisors Vivienne Sze, associate professor in the Department of Electrical Engineering and Computer Science (EECS) and a member of the Research Laboratory of Electronics (RLE); and Sertac Karaman, associate professor of aeronautics and astronautics and director of the Laboratory for Information and Decision Systems (LIDS). The research appears today in the January-February issue of IEEE Micro.

      Modeling emissions

      The researchers built a framework to explore the operational emissions from computers on board a global fleet of electric vehicles that are fully autonomous, meaning they don’t require a back-up human driver.

      The model is a function of the number of vehicles in the global fleet, the power of each computer on each vehicle, the hours driven by each vehicle, and the carbon intensity of the electricity powering each computer.

      “On its own, that looks like a deceptively simple equation. But each of those variables contains a lot of uncertainty because we are considering an emerging application that is not here yet,” Sudhakar says.

      For instance, some research suggests that the amount of time driven in autonomous vehicles might increase because people can multitask while driving and the young and the elderly could drive more. But other research suggests that time spent driving might decrease because algorithms could find optimal routes that get people to their destinations faster.

      In addition to considering these uncertainties, the researchers also needed to model advanced computing hardware and software that doesn’t exist yet.

      To accomplish that, they modeled the workload of a popular algorithm for autonomous vehicles, known as a multitask deep neural network because it can perform many tasks at once. They explored how much energy this deep neural network would consume if it were processing many high-resolution inputs from many cameras with high frame rates, simultaneously.

      When they used the probabilistic model to explore different scenarios, Sudhakar was surprised by how quickly the algorithms’ workload added up.

      For example, if an autonomous vehicle has 10 deep neural networks processing images from 10 cameras, and that vehicle drives for one hour a day, it will make 21.6 million inferences each day. One billion vehicles would make 21.6 quadrillion inferences. To put that into perspective, all of Facebook’s data centers worldwide make a few trillion inferences each day (1 quadrillion is 1,000 trillion).

      “After seeing the results, this makes a lot of sense, but it is not something that is on a lot of people’s radar. These vehicles could actually be using a ton of computer power. They have a 360-degree view of the world, so while we have two eyes, they may have 20 eyes, looking all over the place and trying to understand all the things that are happening at the same time,” Karaman says.

      Autonomous vehicles would be used for moving goods, as well as people, so there could be a massive amount of computing power distributed along global supply chains, he says. And their model only considers computing — it doesn’t take into account the energy consumed by vehicle sensors or the emissions generated during manufacturing.

      Keeping emissions in check

      To keep emissions from spiraling out of control, the researchers found that each autonomous vehicle needs to consume less than 1.2 kilowatts of energy for computing. For that to be possible, computing hardware must become more efficient at a significantly faster pace, doubling in efficiency about every 1.1 years.

      One way to boost that efficiency could be to use more specialized hardware, which is designed to run specific driving algorithms. Because researchers know the navigation and perception tasks required for autonomous driving, it could be easier to design specialized hardware for those tasks, Sudhakar says. But vehicles tend to have 10- or 20-year lifespans, so one challenge in developing specialized hardware would be to “future-proof” it so it can run new algorithms.

      In the future, researchers could also make the algorithms more efficient, so they would need less computing power. However, this is also challenging because trading off some accuracy for more efficiency could hamper vehicle safety.

      Now that they have demonstrated this framework, the researchers want to continue exploring hardware efficiency and algorithm improvements. In addition, they say their model can be enhanced by characterizing embodied carbon from autonomous vehicles — the carbon emissions generated when a car is manufactured — and emissions from a vehicle’s sensors.

      While there are still many scenarios to explore, the researchers hope that this work sheds light on a potential problem people may not have considered.

      “We are hoping that people will think of emissions and carbon efficiency as important metrics to consider in their designs. The energy consumption of an autonomous vehicle is really critical, not just for extending the battery life, but also for sustainability,” says Sze.

      This research was funded, in part, by the National Science Foundation and the MIT-Accenture Fellowship. More

    • 125 Shares169 Views

      in Energy

      With new heat treatment, 3D-printed metals can withstand extreme conditions

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      A new MIT-developed heat treatment transforms the microscopic structure of 3D-printed metals, making the materials stronger and more resilient in extreme thermal environments. The technique could make it possible to 3D print high-performance blades and vanes for power-generating gas turbines and jet engines, which would enable new designs with improved fuel consumption and energy efficiency.

      Today’s gas turbine blades are manufactured through conventional casting processes in which molten metal is poured into complex molds and directionally solidified. These components are made from some of the most heat-resistant metal alloys on Earth, as they are designed to rotate at high speeds in extremely hot gas, extracting work to generate electricity in power plants and thrust in jet engines.

      There is growing interest in manufacturing turbine blades through 3D-printing, which, in addition to its environmental and cost benefits, could allow manufacturers to quickly produce more intricate, energy-efficient blade geometries. But efforts to 3D-print turbine blades have yet to clear a big hurdle: creep.

      In metallurgy, creep refers to a metal’s tendency to permanently deform in the face of persistent mechanical stress and high temperatures. While researchers have explored printing turbine blades, they have found that the printing process produces fine grains on the order of tens to hundreds of microns in size — a microstructure that is especially vulnerable to creep.

      “In practice, this would mean a gas turbine would have a shorter life or less fuel efficiency,” says Zachary Cordero, the Boeing Career Development Professor in Aeronautics and Astronautics at MIT. “These are costly, undesirable outcomes.”

      Cordero and his colleagues found a way to improve the structure of 3D-printed alloys by adding an additional heat-treating step, which transforms the as-printed material’s fine grains into much larger “columnar” grains — a sturdier microstructure that should minimize the material’s creep potential, since the “columns” are aligned with the axis of greatest stress. The researchers say the method, outlined today in Additive Manufacturing, clears the way for industrial 3D-printing of gas turbine blades.

      “In the near future, we envision gas turbine manufacturers will print their blades and vanes at large-scale additive manufacturing plants, then post-process them using our heat treatment,” Cordero says. “3D-printing will enable new cooling architectures that can improve the thermal efficiency of a turbine, so that it produces the same amount of power while burning less fuel and ultimately emits less carbon dioxide.”

      Cordero’s co-authors on the study are lead author Dominic Peachey, Christopher Carter, and Andres Garcia-Jimenez at MIT, Anugrahaprada Mukundan and Marie-Agathe Charpagne of the University of Illinois at Urbana-Champaign, and Donovan Leonard of Oak Ridge National Laboratory.

      Triggering a transformation

      The team’s new method is a form of directional recrystallization — a heat treatment that passes a material through a hot zone at a precisely controlled speed to meld a material’s many microscopic grains into larger, sturdier, and more uniform crystals.

      Directional recrystallization was invented more than 80 years ago and has been applied to wrought materials. In their new study, the MIT team adapted directional recrystallization for 3D-printed superalloys.

      The team tested the method on 3D-printed nickel-based superalloys — metals that are typically cast and used in gas turbines. In a series of experiments, the researchers placed 3D-printed samples of rod-shaped superalloys in a room-temperature water bath placed just below an induction coil. They slowly drew each rod out of the water and through the coil at various speeds, dramatically heating the rods to temperatures varying between 1,200 and 1,245 degrees Celsius.

      They found that drawing the rods at a particular speed (2.5 millimeters per hour) and through a specific temperature (1,235 degrees Celsius) created a steep thermal gradient that triggered a transformation in the material’s printed, fine-grained microstructure.

      “The material starts as small grains with defects called dislocations, that are like a mangled spaghetti,” Cordero explains. “When you heat this material up, those defects can annihilate and reconfigure, and the grains are able to grow. We’re continuously elongating the grains by consuming the defective material and smaller grains — a process termed recrystallization.”

      Creep away

      After cooling the heat-treated rods, the researchers examined their microstructure using optical and electron microscopy, and found that the material’s printed microscopic grains were replaced with “columnar” grains, or long crystal-like regions that were significantly larger than the original grains.

      “We’ve completely transformed the structure,” says lead author Dominic Peachey. “We show we can increase the grain size by orders of magnitude, to massive columnar grains, which theoretically should lead to dramatic improvements in creep properties.”

      The team also showed they could manipulate the draw speed and temperature of the rod samples to tailor the material’s growing grains, creating regions of specific grain size and orientation. This level of control, Cordero says, can enable manufacturers to print turbine blades with site-specific microstructures that are resilient to specific operating conditions.

      Cordero plans to test the heat treatment on 3D-printed geometries that more closely resemble turbine blades. The team is also exploring ways to speed up the draw rate, as well as test a heat-treated structure’s resistance to creep. Then, they envision that the heat treatment could enable the practical application of 3D-printing to produce industrial-grade turbine blades, with more complex shapes and patterns.

      “New blade and vane geometries will enable more energy-efficient land-based gas turbines, as well as, eventually, aeroengines,” Cordero notes. “This could from a baseline perspective lead to lower carbon dioxide emissions, just through improved efficiency of these devices.”

      This research was supported, in part, by the U.S. Office of Naval Research. More