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    MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16

    For the first time, MIT sent an organized engagement to the global Conference of the Parties for the Convention on Biological Diversity, which this year was held Oct. 21 to Nov. 1 in Cali, Colombia.The 10 delegates to COP16 included faculty, researchers, and students from the MIT Environmental Solutions Initiative (ESI), the Department of Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL), the Department of Urban Studies and Planning (DUSP), the Institute for Data, Systems, and Society (IDSS), and the Center for Sustainability Science and Strategy.In previous years, MIT faculty had participated sporadically in the discussions. This organized engagement, led by the ESI, is significant because it brought representatives from many of the groups working on biodiversity across the Institute; showcased the breadth of MIT’s research in more than 15 events including panels, roundtables, and keynote presentations across the Blue and Green Zones of the conference (with the Blue Zone representing the primary venue for the official negotiations and discussions and the Green Zone representing public events); and created an experiential learning opportunity for students who followed specific topics in the negotiations and throughout side events.The conference also gathered attendees from governments, nongovernmental organizations, businesses, other academic institutions, and practitioners focused on stopping global biodiversity loss and advancing the 23 goals of the Kunming-Montreal Global Biodiversity Framework (KMGBF), an international agreement adopted in 2022 to guide global efforts to protect and restore biodiversity through 2030.MIT’s involvement was particularly pronounced when addressing goals related to building coalitions of sub-national governments (targets 11, 12, 14); technology and AI for biodiversity conservation (targets 20 and 21); shaping equitable markets (targets 3, 11, and 19); and informing an action plan for Afro-descendant communities (targets 3, 10, and 22).Building coalitions of sub-national governmentsThe ESI’s Natural Climate Solutions (NCS) Program was able to support two separate coalitions of Latin American cities, namely the Coalition of Cities Against Illicit Economies in the Biogeographic Chocó Region and the Colombian Amazonian Cities coalition, who successfully signed declarations to advance specific targets of the KMGBF (the aforementioned targets 11, 12, 14).This was accomplished through roundtables and discussions where team members — including Marcela Angel, research program director at the MIT ESI; Angelica Mayolo, ESI Martin Luther King Fellow 2023-25; and Silvia Duque and Hannah Leung, MIT Master’s in City Planning students — presented a set of multi-scale actions including transnational strategies, recommendations to strengthen local and regional institutions, and community-based actions to promote the conservation of the Biogeographic Chocó as an ecological corridor.“There is an urgent need to deepen the relationship between academia and local governments of cities located in biodiversity hotspots,” said Angel. “Given the scale and unique conditions of Amazonian cities, pilot research projects present an opportunity to test and generate a proof of concept. These could generate catalytic information needed to scale up climate adaptation and conservation efforts in socially and ecologically sensitive contexts.”ESI’s research also provided key inputs for the creation of the Fund for the Biogeographic Chocó Region, a multi-donor fund launched within the framework of COP16 by a coalition composed of Colombia, Ecuador, Panamá, and Costa Rica. The fund aims to support biodiversity conservation, ecosystem restoration, climate change mitigation and adaptation, and sustainable development efforts across the region.Technology and AI for biodiversity conservationData, technology, and artificial intelligence are playing an increasing role in how we understand biodiversity and ecosystem change globally. Professor Sara Beery’s research group at MIT focuses on this intersection, developing AI methods that enable species and environmental monitoring at previously unprecedented spatial, temporal, and taxonomic scales.During the International Union of Biological Diversity Science-Policy Forum, the high-level COP16 segment focused on outlining recommendations from scientific and academic community, Beery spoke on a panel alongside María Cecilia Londoño, scientific information manager of the Humboldt Institute and co-chair of the Global Biodiversity Observations Network, and Josh Tewksbury, director of the Smithsonian Tropical Research Institute, among others, about how these technological advancements will help humanity achieve our biodiversity targets. The panel emphasized that AI innovation was needed, but with emphasis on direct human-AI partnership, AI capacity building, and the need for data and AI policy to ensure equity of access and benefit from these technologies.As a direct outcome of the session, for the first time, AI was emphasized in the statement on behalf of science and academia delivered by Hernando Garcia, director of the Humboldt Institute, and David Skorton, secretary general of the Smithsonian Institute, to the high-level segment of the COP16.That statement read, “To effectively address current and future challenges, urgent action is required in equity, governance, valuation, infrastructure, decolonization and policy frameworks around biodiversity data and artificial intelligence.”Beery also organized a panel at the GEOBON pavilion in the Blue Zone on Scaling Biodiversity Monitoring with AI, which brought together global leaders from AI research, infrastructure development, capacity and community building, and policy and regulation. The panel was initiated and experts selected from the participants at the recent Aspen Global Change Institute Workshop on Overcoming Barriers to Impact in AI for Biodiversity, co-organized by Beery.Shaping equitable marketsIn a side event co-hosted by the ESI with CAF-Development Bank of Latin America, researchers from ESI’s Natural Climate Solutions Program — including Marcela Angel; Angelica Mayolo; Jimena Muzio, ESI research associate; and Martin Perez Lara, ESI research affiliate and director for Forest Climate Solutions Impact and Monitoring at World Wide Fund for Nature of the U.S. — presented results of a study titled “Voluntary Carbon Markets for Social Impact: Comprehensive Assessment of the Role of Indigenous Peoples and Local Communities (IPLC) in Carbon Forestry Projects in Colombia.” The report highlighted the structural barriers that hinder effective participation of IPLC, and proposed a conceptual framework to assess IPLC engagement in voluntary carbon markets.Communicating these findings is important because the global carbon market has experienced a credibility crisis since 2023, influenced by critical assessments in academic literature, journalism questioning the quality of mitigation results, and persistent concerns about the engagement of private actors with IPLC. Nonetheless, carbon forestry projects have expanded rapidly in Indigenous, Afro-descendant, and local communities’ territories, and there is a need to assess the relationships between private actors and IPLC and to propose pathways for equitable participation. 

    Panelists pose at the equitable markets side event at the Latin American Pavilion in the Blue Zone.

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    The research presentation and subsequent panel with representatives of the association for Carbon Project Developers in Colombia Asocarbono, Fondo Acción, and CAF further discussed recommendations for all actors in the value chain of carbon certificates — including those focused on promoting equitable benefit-sharing and safeguarding compliance, increased accountability, enhanced governance structures, strengthened institutionality, and regulatory frameworks  — necessary to create an inclusive and transparent market.Informing an action plan for Afro-descendant communitiesThe Afro-Interamerican Forum on Climate Change (AIFCC), an international network working to highlight the critical role of Afro-descendant peoples in global climate action, was also present at COP16.At the Afro Summit, Mayolo presented key recommendations prepared collectively by the members of AIFCC to the technical secretariat of the Convention on Biological Diversity (CBD). The recommendations emphasize:creating financial tools for conservation and supporting Afro-descendant land rights;including a credit guarantee fund for countries that recognize Afro-descendant collective land titling and research on their contributions to biodiversity conservation;calling for increased representation of Afro-descendant communities in international policy forums;capacity-building for local governments; andstrategies for inclusive growth in green business and energy transition.These actions aim to promote inclusive and sustainable development for Afro-descendant populations.“Attending COP16 with a large group from MIT contributing knowledge and informed perspectives at 15 separate events was a privilege and honor,” says MIT ESI Director John E. Fernández. “This demonstrates the value of the ESI as a powerful research and convening body at MIT. Science is telling us unequivocally that climate change and biodiversity loss are the two greatest challenges that we face as a species and a planet. MIT has the capacity, expertise, and passion to address not only the former, but also the latter, and the ESI is committed to facilitating the very best contributions across the institute for the critical years that are ahead of us.”A fuller overview of the conference is available via The MIT Environmental Solutions Initiative’s Primer of COP16. More

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    A new catalyst can turn methane into something useful

    Although it is less abundant than carbon dioxide, methane gas contributes disproportionately to global warming because it traps more heat in the atmosphere than carbon dioxide, due to its molecular structure.MIT chemical engineers have now designed a new catalyst that can convert methane into useful polymers, which could help reduce greenhouse gas emissions.“What to do with methane has been a longstanding problem,” says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT and the senior author of the study. “It’s a source of carbon, and we want to keep it out of the atmosphere but also turn it into something useful.”The new catalyst works at room temperature and atmospheric pressure, which could make it easier and more economical to deploy at sites of methane production, such as power plants and cattle barns.Daniel Lundberg PhD ’24 and MIT postdoc Jimin Kim are the lead authors of the study, which appears today in Nature Catalysis. Former postdoc Yu-Ming Tu and postdoc Cody Ritt also authors of the paper.Capturing methaneMethane is produced by bacteria known as methanogens, which are often highly concentrated in landfills, swamps, and other sites of decaying biomass. Agriculture is a major source of methane, and methane gas is also generated as a byproduct of transporting, storing, and burning natural gas. Overall, it is believed to account for about 15 percent of global temperature increases.At the molecular level, methane is made of a single carbon atom bound to four hydrogen atoms. In theory, this molecule should be a good building block for making useful products such as polymers. However, converting methane to other compounds has proven difficult because getting it to react with other molecules usually requires high temperature and high pressures.To achieve methane conversion without that input of energy, the MIT team designed a hybrid catalyst with two components: a zeolite and a naturally occurring enzyme. Zeolites are abundant, inexpensive clay-like minerals, and previous work has found that they can be used to catalyze the conversion of methane to carbon dioxide.In this study, the researchers used a zeolite called iron-modified aluminum silicate, paired with an enzyme called alcohol oxidase. Bacteria, fungi, and plants use this enzyme to oxidize alcohols.This hybrid catalyst performs a two-step reaction in which zeolite converts methane to methanol, and then the enzyme converts methanol to formaldehyde. That reaction also generates hydrogen peroxide, which is fed back into the zeolite to provide a source of oxygen for the conversion of methane to methanol.This series of reactions can occur at room temperature and doesn’t require high pressure. The catalyst particles are suspended in water, which can absorb methane from the surrounding air. For future applications, the researchers envision that it could be painted onto surfaces.“Other systems operate at high temperature and high pressure, and they use hydrogen peroxide, which is an expensive chemical, to drive the methane oxidation. But our enzyme produces hydrogen peroxide from oxygen, so I think our system could be very cost-effective and scalable,” Kim says.Creating a system that incorporates both enzymes and artificial catalysts is a “smart strategy,” says Damien Debecker, a professor at the Institute of Condensed Matter and Nanosciences at the University of Louvain, Belgium.“Combining these two families of catalysts is challenging, as they tend to operate in rather distinct operation conditions. By unlocking this constraint and mastering the art of chemo-enzymatic cooperation, hybrid catalysis becomes key-enabling: It opens new perspectives to run complex reaction systems in an intensified way,” says Debecker, who was not involved in the research.Building polymersOnce formaldehyde is produced, the researchers showed they could use that molecule to generate polymers by adding urea, a nitrogen-containing molecule found in urine. This resin-like polymer, known as urea-formaldehyde, is now used in particle board, textiles and other products.The researchers envision that this catalyst could be incorporated into pipes used to transport natural gas. Within those pipes, the catalyst could generate a polymer that could act as a sealant to heal cracks in the pipes, which are a common source of methane leakage. The catalyst could also be applied as a film to coat surfaces that are exposed to methane gas, producing polymers that could be collected for use in manufacturing, the researchers say.Strano’s lab is now working on catalysts that could be used to remove carbon dioxide from the atmosphere and combine it with nitrate to produce urea. That urea could then be mixed with the formaldehyde produced by the zeolite-enzyme catalyst to produce urea-formaldehyde.The research was funded by the U.S. Department of Energy. More

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    An inflatable gastric balloon could help people lose weight

    Gastric balloons — silicone balloons filled with air or saline and placed in the stomach — can help people lose weight by making them feel too full to overeat. However, this effect eventually can wear off as the stomach becomes used to the sensation of fullness.To overcome that limitation, MIT engineers have designed a new type of gastric balloon that can be inflated and deflated as needed. In an animal study, they showed that inflating the balloon before a meal caused the animals to reduce their food intake by 60 percent.This type of intervention could offer an alternative for people who don’t want to undergo more invasive treatments such as gastric bypass surgery, or people who don’t respond well to weight-loss drugs, the researchers say.“The basic concept is we can have this balloon that is dynamic, so it would be inflated right before a meal and then you wouldn’t feel hungry. Then it would be deflated in between meals,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and the senior author of the study.Neil Zixun Jia, who received a PhD from MIT in 2023, is the lead author of the paper, which appears today in the journal Device.An inflatable balloonGastric balloons filled with saline are currently approved for use in the United States. These balloons stimulate a sense of fullness in the stomach, and studies have shown that they work well, but the benefits are often temporary.“Gastric balloons do work initially. Historically, what has been seen is that the balloon is associated with weight loss. But then in general, the weight gain resumes the same trajectory,” Traverso says. “What we reasoned was perhaps if we had a system that simulates that fullness in a transient way, meaning right before a meal, that could be a way of inducing weight loss.”To achieve a longer-lasting effect in patients, the researchers set out to design a device that could expand and contract on demand. They created two prototypes: One is a traditional balloon that inflates and deflates, and the other is a mechanical device with four arms that expand outward, pushing out an elastic polymer shell that presses on the stomach wall.In animal tests, the researchers found that the mechanical-arm device could effectively expand to fill the stomach, but they ended up deciding to pursue the balloon option instead.“Our sense was that the balloon probably distributed the force better, and down the line, if you have balloon that is applying the pressure, that is probably a safer approach in the long run,” Traverso says.The researchers’ new balloon is similar to a traditional gastric balloon, but it is inserted into the stomach through an incision in the abdominal wall. The balloon is connected to an external controller that can be attached to the skin and contains a pump that inflates and deflates the balloon when needed. Inserting this device would be similar to the procedure used to place a feeding tube into a patient’s stomach, which is commonly done for people who are unable to eat or drink.“If people, for example, are unable to swallow, they receive food through a tube like this. We know that we can keep tubes in for years, so there is already precedent for other systems that can stay in the body for a very long time. That gives us some confidence in the longer-term compatibility of this system,” Traverso says.Reduced food intakeIn tests in animals, the researchers found that inflating the balloon before meals led to a 60 percent reduction in the amount of food consumed. These studies were done over the course of a month, but the researchers now plan to do longer-term studies to see if this reduction leads to weight loss.“The deployment for traditional gastric balloons is usually six months, if not more, and only then you will see good amount of weight loss. We will have to evaluate our device in a similar or longer time span to prove it really works better,” Jia says.If developed for use in humans, the new gastric balloon could offer an alternative to existing obesity treatments. Other treatments for obesity include gastric bypass surgery, “stomach stapling” (a surgical procedure in which the stomach capacity is reduced), and drugs including GLP-1 receptor agonists such as semaglutide.The gastric balloon could be an option for patients who are not good candidates for surgery or don’t respond well to weight-loss drugs, Traverso says.“For certain patients who are higher-risk, who cannot undergo surgery, or did not tolerate the medication or had some other contraindication, there are limited options,” he says. “Traditional gastric balloons are still being used, but they come with a caveat that eventually the weight loss can plateau, so this is a way of trying to address that fundamental limitation.”The research was funded by MIT’s Department of Mechanical Engineering, the Karl van Tassel Career Development Professorship, the Whitaker Health Sciences Fund Fellowship, the T.S. Lin Fellowship, the MIT Undergraduate Research Opportunities Program, and the Boston University Yawkey Funded Internship Program.  More

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    Q&A: Transforming research through global collaborations

    The MIT Global Seed Funds (GSF) program fosters global research collaborations with MIT faculty and their peers abroad — creating partnerships that tackle complex global issues, from climate change to health-care challenges and beyond. Administered by the MIT Center for International Studies (CIS), the GSF program has awarded more than $26 million to over 1,200 faculty research projects since its inception in 2008. Through its unique funding structure — comprising a general fund for unrestricted geographical use and several specific funds within individual countries, regions, and universities — GSF supports a wide range of projects. The current call for proposals from MIT faculty and researchers with principal investigator status is open until Dec. 10. CIS recently sat down with faculty recipients Josephine Carstensen and David McGee to discuss the value and impact GSF added to their research. Carstensen, the Gilbert W. Winslow Career Development Associate Professor of Civil and Environmental Engineering, generates computational designs for large-scale structures with the intent of designing novel low-carbon solutions. McGee, the William R. Kenan, Jr. Professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS), reconstructs the patterns, pace, and magnitudes of past hydro-climate changes.Q: How did the Global Seed Funds program connect you with global partnerships related to your research?Carstensen: One of the projects my lab is working on is to unlock the potential of complex cast-glass structures. Through our GSF partnership with researchers at TUDelft (Netherlands), my group was able to leverage our expertise in generative design algorithms alongside the TUDelft team, who are experts in the physical casting and fabrication of glass structures. Our initial connection to TUDelft was actually through one of my graduate students who was at a conference and met TUDelft researchers. He was inspired by their work and felt there could be synergy between our labs. The question then became: How do we connect with TUDelft? And that was what led us to the Global Seed Funds program. McGee: Our research is based in fieldwork conducted in partnership with experts who have a rich understanding of local environments. These locations range from lake basins in Chile and Argentina to caves in northern Mexico, Vietnam, and Madagascar. GSF has been invaluable for helping foster partnerships with collaborators and universities in these different locations, enabling the pilot work and relationship-building necessary to establish longer-term, externally funded projects.Q: Tell us more about your GSF-funded work.Carstensen: In my research group at MIT, we live mainly in a computational regime, and we do very little proof-of-concept testing. To that point, we do not even have the facilities nor experience to physically build large-scale structures, or even specialized structures. GSF has enabled us to connect with the researchers at TUDelft who do much more experimental testing than we do. Being able to work with the experts at TUDelft within their physical realm provided valuable insights into their way of approaching problems. And, likewise, the researchers at TUDelft benefited from our expertise. It has been fruitful in ways we couldn’t have imagined within our lab at MIT.McGee: The collaborative work supported by the GSF has focused on reconstructing how past climate changes impacted rainfall patterns around the world, using natural archives like lake sediments and cave formations. One particularly successful project has been our work in caves in northeastern Mexico, which has been conducted in partnership with researchers from the National Autonomous University of Mexico (UNAM) and a local caving group. This project has involved several MIT undergraduate and graduate students, sponsored a research symposium in Mexico City, and helped us obtain funding from the National Science Foundation for a longer-term project.Q: You both mentioned the involvement of your graduate students. How exactly has the GSF augmented the research experience of your students?Carstensen: The collaboration has especially benefited the graduate students from both the MIT and TUDelft teams. The opportunity presented through this project to engage in research at an international peer institution has been extremely beneficial for their academic growth and maturity. It has facilitated training in new and complementary technical areas that they would not have had otherwise and allowed them to engage with leading world experts. An example of this aspect of the project’s success is that the collaboration has inspired one of my graduate students to actively pursue postdoc opportunities in Europe (including at TU Delft) after his graduation.McGee: MIT students have traveled to caves in northeastern Mexico and to lake basins in northern Chile to conduct fieldwork and build connections with local collaborators. Samples enabled by GSF-supported projects became the focus of two graduate students’ PhD theses, two EAPS undergraduate senior theses, and multiple UROP [Undergraduate Research Opportunity Program] projects.Q: Were there any unexpected benefits to the work funded by GSF?Carstensen: The success of this project would not have been possible without this specific international collaboration. Both the Delft and MIT teams bring highly different essential expertise that has been necessary for the successful project outcome. It allowed both the Delft and MIT teams to gain an in-depth understanding of the expertise areas and resources of the other collaborators. Both teams have been deeply inspired. This partnership has fueled conversations about potential future projects and provided multiple outcomes, including a plan to publish two journal papers on the project outcome. The first invited publication is being finalized now.McGee: GSF’s focus on reciprocal exchange has enabled external collaborators to spend time at MIT, sharing their work and exchanging ideas. Other funding is often focused on sending MIT researchers and students out, but GSF has helped us bring collaborators here, making the relationship more equal. A GSF-supported visit by Argentinian researchers last year made it possible for them to interact not just with my group, but with students and faculty across EAPS. More

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    Decarbonizing heavy industry with thermal batteries

    Whether you’re manufacturing cement, steel, chemicals, or paper, you need a large amount of heat. Almost without exception, manufacturers around the world create that heat by burning fossil fuels.In an effort to clean up the industrial sector, some startups are changing manufacturing processes for specific materials. Some are even changing the materials themselves. Daniel Stack SM ’17, PhD ’21 is trying to address industrial emissions across the board by replacing the heat source.Since coming to MIT in 2014, Stack has worked to develop thermal batteries that use electricity to heat up a conductive version of ceramic firebricks, which have been used as heat stores and insulators for centuries. In 2021, Stack co-founded Electrified Thermal Solutions, which has since demonstrated that its firebricks can store heat efficiently for hours and discharge it by heating air or gas up to 3,272 degrees Fahrenheit — hot enough to power the most demanding industrial applications.Achieving temperatures north of 3,000 F represents a breakthrough for the electric heating industry, as it enables some of the world’s hardest-to-decarbonize sectors to utilize renewable energy for the first time. It also unlocks a new, low-cost model for using electricity when it’s at its cheapest and cleanest.“We have a global perspective at Electrified Thermal, but in the U.S. over the last five years, we’ve seen an incredible opportunity emerge in energy prices that favors flexible offtake of electricity,” Stack says. “Throughout the middle of the country, especially in the wind belt, electricity prices in many places are negative for more than 20 percent of the year, and the trend toward decreasing electricity pricing during off-peak hours is a nationwide phenomenon. Technologies like our Joule Hive Thermal Battery will enable us to access this inexpensive, clean electricity and compete head to head with fossil fuels on price for industrial heating needs, without even factoring in the positive climate impact.”A new approach to an old technologyStack’s research plans changed quickly when he joined MIT’s Department of Nuclear Science and Engineering as a master’s student in 2014.“I went to MIT excited to work on the next generation of nuclear reactors, but what I focused on almost from day one was how to heat up bricks,” Stack says. “It wasn’t what I expected, but when I talked to my advisor, [Principal Research Scientist] Charles Forsberg, about energy storage and why it was valuable to not just nuclear power but the entire energy transition, I realized there was no project I would rather work on.”Firebricks are ubiquitous, inexpensive clay bricks that have been used for millennia in fireplaces and ovens. In 2017, Forsberg and Stack co-authored a paper showing firebricks’ potential to store heat from renewable resources, but the system still used electric resistance heaters — like the metal coils in toasters and space heaters — which limited its temperature output.For his doctoral work, Stack worked with Forsberg to make firebricks that were electrically conductive, replacing the resistance heaters so the bricks produced the heat directly.“Electric heaters are your biggest limiter: They burn out too fast, they break down, they don’t get hot enough,” Stack explains. “The idea was to skip the heaters because firebricks themselves are really cheap, abundant materials that can go to flame-like temperatures and hang out there for days.”Forsberg and Stacks were able to create conductive firebricks by tweaking the chemical composition of traditional firebricks. Electrified Thermal’s bricks are 98 percent similar to existing firebricks and are produced using the same processes, allowing existing manufacturers to make them inexpensively.Toward the end of his PhD program, Stack realized the invention could be commercialized. He started taking classes at the MIT Sloan School of Management and spending time at the Martin Trust Center for MIT Entrepreneurship. He also entered the StartMIT program and the I-Corps program, and received support from the U.S. Department of Energy and MIT’s Venture Mentoring Service (VMS).“Through the Boston ecosystem, the MIT ecosystem, and with help from the Department of Energy, we were able to launch this from the lab at MIT,” Stack says. “What we spun out was an electrically conductive firebrick, or what we refer to as an e-Brick.”Electrified Thermal contains its firebrick arrays in insulated, off-the-shelf metal boxes. Although the system is highly configurable depending on the end use, the company’s standard system can collect and release about 5 megawatts of energy and store about 25 megawatt-hours.The company has demonstrated its system’s ability to produce high temperatures and has been cycling its system at its headquarters in Medford, Massachusetts. That work has collectively earned Electrified Thermal $40 million from various the Department of Energy offices to scale the technology and work with manufacturers.“Compared to other electric heating, we can run hotter and last longer than any other solution on the market,” Stack says. “That means replacing fossil fuels at a lot of industrial sites that couldn’t otherwise decarbonize.”Scaling to solve a global problemElectrified Thermal is engaging with hundreds of industrial companies, including manufacturers of cement, steel, glass, basic and specialty chemicals, food and beverage, and pulp and paper.“The industrial heating challenge affects everyone under the sun,” Stack says. “They all have fundamentally the same problem, which is getting their heat in a way that is affordable and zero carbon for the energy transition.”The company is currently building a megawatt-scale commercial version of its system, which it expects to be operational in the next seven months.“Next year will be a huge proof point to the industry,” Stack says. “We’ll be using the commercial system to showcase a variety of operating points that customers need to see, and we’re hoping to be running systems on customer sites by the end of the year. It’ll be a huge achievement and a first for electric heating because no other solution in the market can put out the kind of temperatures that we can put out.”By working with manufacturers to produce its firebricks and casings, Electrified Thermal hopes to be able to deploy its systems rapidly and at low cost across a massive industry.“From the very beginning, we engineered these e-bricks to be rapidly scalable and rapidly producible within existing supply chains and manufacturing processes,” Stack says. “If you want to decarbonize heavy industry, there will be no cheaper way than turning electricity into heat from zero-carbon electricity assets. We’re seeking to be the premier technology that unlocks those capabilities, with double digit percentages of global energy flowing through our system as we accomplish the energy transition.” More

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    To design better water filters, MIT engineers look to manta rays

    Filter feeders are everywhere in the animal world, from tiny crustaceans and certain types of coral and krill, to various molluscs, barnacles, and even massive basking sharks and baleen whales. Now, MIT engineers have found that one filter feeder has evolved to sift food in ways that could improve the design of industrial water filters.In a paper appearing this week in the Proceedings of the National Academy of Sciences, the team characterizes the filter-feeding mechanism of the mobula ray — a family of aquatic rays that includes two manta species and seven devil rays. Mobula rays feed by swimming open-mouthed through plankton-rich regions of the ocean and filtering plankton particles into their gullet as water streams into their mouths and out through their gills.The floor of the mobula ray’s mouth is lined on either side with parallel, comb-like structures, called plates, that siphon water into the ray’s gills. The MIT team has shown that the dimensions of these plates may allow for incoming plankton to bounce all the way across the plates and further into the ray’s cavity, rather than out through the gills. What’s more, the ray’s gills absorb oxygen from the outflowing water, helping the ray to simultaneously breathe while feeding.“We show that the mobula ray has evolved the geometry of these plates to be the perfect size to balance feeding and breathing,” says study author Anette “Peko” Hosoi, the Pappalardo Professor of Mechanical Engineering at MIT.The engineers fabricated a simple water filter modeled after the mobula ray’s plankton-filtering features. They studied how water flowed through the filter when it was fitted with 3D-printed plate-like structures. The team took the results of these experiments and drew up a blueprint, which they say designers can use to optimize industrial cross-flow filters, which are broadly similar in configuration to that of the mobula ray.“We want to expand the design space of traditional cross-flow filtration with new knowledge from the manta ray,” says lead author and MIT postdoc Xinyu Mao PhD ’24. “People can choose a parameter regime of the mobula ray so they could potentially improve overall filter performance.”Hosoi and Mao co-authored the new study with Irmgard Bischofberger, associate professor of mechanical engineering at MIT.A better trade-offThe new study grew out of the group’s focus on filtration during the height of the Covid pandemic, when the researchers were designing face masks to filter out the virus. Since then, Mao has shifted focus to study filtration in animals and how certain filter-feeding mechanisms might improve filters used in industry, such as in water treatment plants.Mao observed that any industrial filter must strike a balance between permeability (how easily fluid can flow through a filter), and selectivity (how successful a filter is at keeping out particles of a target size). For instance, a membrane that is studded with large holes might be highly permeable, meaning a lot of water can be pumped through using very little energy. However, the membrane’s large holes would let many particles through, making it very low in selectivity. Likewise, a membrane with much smaller pores would be more selective yet also require more energy to pump the water through the smaller openings.“We asked ourselves, how do we do better with this tradeoff between permeability and selectivity?” Hosoi says.As Mao looked into filter-feeding animals, he found that the mobula ray has struck an ideal balance between permeability and selectivity: The ray is highly permeable, in that it can let water into its mouth and out through its gills quickly enough to capture oxygen to breathe. At the same time, it is highly selective, filtering and feeding on plankton rather than letting the particles stream out through the gills.The researchers realized that the ray’s filtering features are broadly similar to that of industrial cross-flow filters. These filters are designed such that fluid flows across a permeable membrane that lets through most of the fluid, while any polluting particles continue flowing across the membrane and eventually out into a reservoir of waste.The team wondered whether the mobula ray might inspire design improvements to industrial cross-flow filters. For that, they took a deeper dive into the dynamics of mobula ray filtration.A vortex keyAs part of their new study, the team fabricated a simple filter inspired by the mobula ray. The filter’s design is what engineers refer to as a “leaky channel” — effectively, a pipe with holes along its sides. In this case, the team’s “channel” consists of two flat, transparent acrylic plates that are glued together at the edges, with a slight opening between the plates through which fluid can be pumped. At one end of the channel, the researchers inserted 3D-printed structures resembling the grooved plates that run along the floor of the mobula ray’s mouth.The team then pumped water through the channel at various rates, along with colored dye to visualize the flow. They took images across the channel and observed an interesting transition: At slow pumping rates, the flow was “very peaceful,” and fluid easily slipped through the grooves in the printed plates and out into a reservoir. When the researchers increased the pumping rate, the faster-flowing fluid did not slip through, but appeared to swirl at the mouth of each groove, creating a vortex, similar to a small knot of hair between the tips of a comb’s teeth.“This vortex is not blocking water, but it is blocking particles,” Hosoi explains. “Whereas in a slower flow, particles go through the filter with the water, at higher flow rates, particles try to get through the filter but are blocked by this vortex and are shot down the channel instead. The vortex is helpful because it prevents particles from flowing out.”The team surmised that vortices are the key to mobula rays’ filter-feeding ability. The ray is able to swim at just the right speed that water, streaming into its mouth, can form vortices between the grooved plates. These vortices effectively block any plankton particles — even those that are smaller than the space between plates. The particles then bounce across the plates and head further into the ray’s cavity, while the rest of the water can still flow between the plates and out through the gills.The researchers used the results of their experiments, along with dimensions of the filtering features of mobula rays, to develop a blueprint for cross-flow filtration.“We have provided practical guidance on how to actually filter as the mobula ray does,” Mao offers.“You want to design a filter such that you’re in the regime where you generate vortices,” Hosoi says. “Our guidelines tell you: If you want your plant to pump at a certain rate, then your filter has to have a particular pore diameter and spacing to generate vortices that will filter out particles of this size. The mobula ray is giving us a really nice rule of thumb for rational design.”This work was supported, in part, by the U.S. National Institutes of Health, and the Harvey P. Greenspan Fellowship Fund.  More

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    New AI tool generates realistic satellite images of future flooding

    Visualizing the potential impacts of a hurricane on people’s homes before it hits can help residents prepare and decide whether to evacuate.MIT scientists have developed a method that generates satellite imagery from the future to depict how a region would look after a potential flooding event. The method combines a generative artificial intelligence model with a physics-based flood model to create realistic, birds-eye-view images of a region, showing where flooding is likely to occur given the strength of an oncoming storm.As a test case, the team applied the method to Houston and generated satellite images depicting what certain locations around the city would look like after a storm comparable to Hurricane Harvey, which hit the region in 2017. The team compared these generated images with actual satellite images taken of the same regions after Harvey hit. They also compared AI-generated images that did not include a physics-based flood model.The team’s physics-reinforced method generated satellite images of future flooding that were more realistic and accurate. The AI-only method, in contrast, generated images of flooding in places where flooding is not physically possible.The team’s method is a proof-of-concept, meant to demonstrate a case in which generative AI models can generate realistic, trustworthy content when paired with a physics-based model. In order to apply the method to other regions to depict flooding from future storms, it will need to be trained on many more satellite images to learn how flooding would look in other regions.“The idea is: One day, we could use this before a hurricane, where it provides an additional visualization layer for the public,” says Björn Lütjens, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences, who led the research while he was a doctoral student in MIT’s Department of Aeronautics and Astronautics (AeroAstro). “One of the biggest challenges is encouraging people to evacuate when they are at risk. Maybe this could be another visualization to help increase that readiness.”To illustrate the potential of the new method, which they have dubbed the “Earth Intelligence Engine,” the team has made it available as an online resource for others to try.The researchers report their results today in the journal IEEE Transactions on Geoscience and Remote Sensing. The study’s MIT co-authors include Brandon Leshchinskiy; Aruna Sankaranarayanan; and Dava Newman, professor of AeroAstro and director of the MIT Media Lab; along with collaborators from multiple institutions.Generative adversarial imagesThe new study is an extension of the team’s efforts to apply generative AI tools to visualize future climate scenarios.“Providing a hyper-local perspective of climate seems to be the most effective way to communicate our scientific results,” says Newman, the study’s senior author. “People relate to their own zip code, their local environment where their family and friends live. Providing local climate simulations becomes intuitive, personal, and relatable.”For this study, the authors use a conditional generative adversarial network, or GAN, a type of machine learning method that can generate realistic images using two competing, or “adversarial,” neural networks. The first “generator” network is trained on pairs of real data, such as satellite images before and after a hurricane. The second “discriminator” network is then trained to distinguish between the real satellite imagery and the one synthesized by the first network.Each network automatically improves its performance based on feedback from the other network. The idea, then, is that such an adversarial push and pull should ultimately produce synthetic images that are indistinguishable from the real thing. Nevertheless, GANs can still produce “hallucinations,” or factually incorrect features in an otherwise realistic image that shouldn’t be there.“Hallucinations can mislead viewers,” says Lütjens, who began to wonder whether such hallucinations could be avoided, such that generative AI tools can be trusted to help inform people, particularly in risk-sensitive scenarios. “We were thinking: How can we use these generative AI models in a climate-impact setting, where having trusted data sources is so important?”Flood hallucinationsIn their new work, the researchers considered a risk-sensitive scenario in which generative AI is tasked with creating satellite images of future flooding that could be trustworthy enough to inform decisions of how to prepare and potentially evacuate people out of harm’s way.Typically, policymakers can get an idea of where flooding might occur based on visualizations in the form of color-coded maps. These maps are the final product of a pipeline of physical models that usually begins with a hurricane track model, which then feeds into a wind model that simulates the pattern and strength of winds over a local region. This is combined with a flood or storm surge model that forecasts how wind might push any nearby body of water onto land. A hydraulic model then maps out where flooding will occur based on the local flood infrastructure and generates a visual, color-coded map of flood elevations over a particular region.“The question is: Can visualizations of satellite imagery add another level to this, that is a bit more tangible and emotionally engaging than a color-coded map of reds, yellows, and blues, while still being trustworthy?” Lütjens says.The team first tested how generative AI alone would produce satellite images of future flooding. They trained a GAN on actual satellite images taken by satellites as they passed over Houston before and after Hurricane Harvey. When they tasked the generator to produce new flood images of the same regions, they found that the images resembled typical satellite imagery, but a closer look revealed hallucinations in some images, in the form of floods where flooding should not be possible (for instance, in locations at higher elevation).To reduce hallucinations and increase the trustworthiness of the AI-generated images, the team paired the GAN with a physics-based flood model that incorporates real, physical parameters and phenomena, such as an approaching hurricane’s trajectory, storm surge, and flood patterns. With this physics-reinforced method, the team generated satellite images around Houston that depict the same flood extent, pixel by pixel, as forecasted by the flood model.“We show a tangible way to combine machine learning with physics for a use case that’s risk-sensitive, which requires us to analyze the complexity of Earth’s systems and project future actions and possible scenarios to keep people out of harm’s way,” Newman says. “We can’t wait to get our generative AI tools into the hands of decision-makers at the local community level, which could make a significant difference and perhaps save lives.”The research was supported, in part, by the MIT Portugal Program, the DAF-MIT Artificial Intelligence Accelerator, NASA, and Google Cloud. 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    Advancing urban tree monitoring with AI-powered digital twins

    The Irish philosopher George Berkely, best known for his theory of immaterialism, once famously mused, “If a tree falls in a forest and no one is around to hear it, does it make a sound?”What about AI-generated trees? They probably wouldn’t make a sound, but they will be critical nonetheless for applications such as adaptation of urban flora to climate change. To that end, the novel “Tree-D Fusion” system developed by researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Google, and Purdue University merges AI and tree-growth models with Google’s Auto Arborist data to create accurate 3D models of existing urban trees. The project has produced the first-ever large-scale database of 600,000 environmentally aware, simulation-ready tree models across North America.“We’re bridging decades of forestry science with modern AI capabilities,” says Sara Beery, MIT electrical engineering and computer science (EECS) assistant professor, MIT CSAIL principal investigator, and a co-author on a new paper about Tree-D Fusion. “This allows us to not just identify trees in cities, but to predict how they’ll grow and impact their surroundings over time. We’re not ignoring the past 30 years of work in understanding how to build these 3D synthetic models; instead, we’re using AI to make this existing knowledge more useful across a broader set of individual trees in cities around North America, and eventually the globe.”Tree-D Fusion builds on previous urban forest monitoring efforts that used Google Street View data, but branches it forward by generating complete 3D models from single images. While earlier attempts at tree modeling were limited to specific neighborhoods, or struggled with accuracy at scale, Tree-D Fusion can create detailed models that include typically hidden features, such as the back side of trees that aren’t visible in street-view photos.The technology’s practical applications extend far beyond mere observation. City planners could use Tree-D Fusion to one day peer into the future, anticipating where growing branches might tangle with power lines, or identifying neighborhoods where strategic tree placement could maximize cooling effects and air quality improvements. These predictive capabilities, the team says, could change urban forest management from reactive maintenance to proactive planning.A tree grows in Brooklyn (and many other places)The researchers took a hybrid approach to their method, using deep learning to create a 3D envelope of each tree’s shape, then using traditional procedural models to simulate realistic branch and leaf patterns based on the tree’s genus. This combo helped the model predict how trees would grow under different environmental conditions and climate scenarios, such as different possible local temperatures and varying access to groundwater.Now, as cities worldwide grapple with rising temperatures, this research offers a new window into the future of urban forests. In a collaboration with MIT’s Senseable City Lab, the Purdue University and Google team is embarking on a global study that re-imagines trees as living climate shields. Their digital modeling system captures the intricate dance of shade patterns throughout the seasons, revealing how strategic urban forestry could hopefully change sweltering city blocks into more naturally cooled neighborhoods.“Every time a street mapping vehicle passes through a city now, we’re not just taking snapshots — we’re watching these urban forests evolve in real-time,” says Beery. “This continuous monitoring creates a living digital forest that mirrors its physical counterpart, offering cities a powerful lens to observe how environmental stresses shape tree health and growth patterns across their urban landscape.”AI-based tree modeling has emerged as an ally in the quest for environmental justice: By mapping urban tree canopy in unprecedented detail, a sister project from the Google AI for Nature team has helped uncover disparities in green space access across different socioeconomic areas. “We’re not just studying urban forests — we’re trying to cultivate more equity,” says Beery. The team is now working closely with ecologists and tree health experts to refine these models, ensuring that as cities expand their green canopies, the benefits branch out to all residents equally.It’s a breezeWhile Tree-D fusion marks some major “growth” in the field, trees can be uniquely challenging for computer vision systems. Unlike the rigid structures of buildings or vehicles that current 3D modeling techniques handle well, trees are nature’s shape-shifters — swaying in the wind, interweaving branches with neighbors, and constantly changing their form as they grow. The Tree-D fusion models are “simulation-ready” in that they can estimate the shape of the trees in the future, depending on the environmental conditions.“What makes this work exciting is how it pushes us to rethink fundamental assumptions in computer vision,” says Beery. “While 3D scene understanding techniques like photogrammetry or NeRF [neural radiance fields] excel at capturing static objects, trees demand new approaches that can account for their dynamic nature, where even a gentle breeze can dramatically alter their structure from moment to moment.”The team’s approach of creating rough structural envelopes that approximate each tree’s form has proven remarkably effective, but certain issues remain unsolved. Perhaps the most vexing is the “entangled tree problem;” when neighboring trees grow into each other, their intertwined branches create a puzzle that no current AI system can fully unravel.The scientists see their dataset as a springboard for future innovations in computer vision, and they’re already exploring applications beyond street view imagery, looking to extend their approach to platforms like iNaturalist and wildlife camera traps.“This marks just the beginning for Tree-D Fusion,” says Jae Joong Lee, a Purdue University PhD student who developed, implemented and deployed the Tree-D-Fusion algorithm. “Together with my collaborators, I envision expanding the platform’s capabilities to a planetary scale. Our goal is to use AI-driven insights in service of natural ecosystems — supporting biodiversity, promoting global sustainability, and ultimately, benefiting the health of our entire planet.”Beery and Lee’s co-authors are Jonathan Huang, Scaled Foundations head of AI (formerly of Google); and four others from Purdue University: PhD students Jae Joong Lee and Bosheng Li, Professor and Dean’s Chair of Remote Sensing Songlin Fei, Assistant Professor Raymond Yeh, and Professor and Associate Head of Computer Science Bedrich Benes. Their work is based on efforts supported by the United States Department of Agriculture’s (USDA) Natural Resources Conservation Service and is directly supported by the USDA’s National Institute of Food and Agriculture. The researchers presented their findings at the European Conference on Computer Vision this month.  More