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    How to reduce greenhouse gas emissions from ammonia production

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    Ammonia is one of the most widely produced chemicals in the world, used mostly as fertilizer, but also for the production of some plastics, textiles, and other applications. Its production, through processes that require high heat and pressure, accounts for up to 20 percent of all the greenhouse gases from the entire chemical industry, so efforts have been underway worldwide to find ways to reduce those emissions.Now, researchers at MIT have come up with a clever way of combining two different methods of producing the compound that minimizes waste products, that, when combined with some other simple upgrades, could reduce the greenhouse emissions from production by as much as 63 percent, compared to the leading “low-emissions” approach being used today.The new approach is described in the journal Energy & Fuels, in a paper by MIT Energy Initiative (MITEI) Director William H. Green, graduate student Sayandeep Biswas, MITEI Director of Research Randall Field, and two others.“Ammonia has the most carbon dioxide emissions of any kind of chemical,” says Green, who is the Hoyt C. Hottel Professor in Chemical Engineering. “It’s a very important chemical,” he says, because its use as a fertilizer is crucial to being able to feed the world’s population.Until late in the 19th century, the most widely used source of nitrogen fertilizer was mined deposits of bat or bird guano, mostly from Chile, but that source was beginning to run out, and there were predictions that the world would soon be running short of food to sustain the population. But then a new chemical process, called the Haber-Bosch process after its inventors, made it possible to make ammonia out of nitrogen from the air and hydrogen, which was mostly derived from methane. But both the burning of fossil fuels to provide the needed heat and the use of methane to make the hydrogen led to massive climate-warming emissions from the process.To address this, two newer variations of ammonia production have been developed: so-called “blue ammonia,” where the greenhouse gases are captured right at the factory and then sequestered deep underground, and “green ammonia,” produced by a different chemical pathway, using electricity instead of fossil fuels to hydrolyze water to make hydrogen.Blue ammonia is already beginning to be used, with a few plants operating now in Louisiana, Green says, and the ammonia mostly being shipped to Japan, “so that’s already kind of commercial.” Other parts of the world are starting to use green ammonia, especially in places that have lots of hydropower, solar, or wind to provide inexpensive electricity, including a giant plant now under construction in Saudi Arabia.But in most places, both blue and green ammonia are still more expensive than the traditional fossil-fuel-based version, so many teams around the world have been working on ways to cut these costs as much as possible so that the difference is small enough to be made up through tax subsidies or other incentives.The problem is growing, because as the population grows, and as wealth increases, there will be ever-increasing demands for nitrogen fertilizer. At the same time, ammonia is a promising substitute fuel to power hard-to-decarbonize transportation such as cargo ships and heavy trucks, which could lead to even greater needs for the chemical.“It definitely works” as a transportation fuel, by powering fuel cells that have been demonstrated for use by everything from drones to barges and tugboats and trucks, Green says. “People think that the most likely market of that type would be for shipping,” he says, “because the downside of ammonia is it’s toxic and it’s smelly, and that makes it slightly dangerous to handle and to ship around.” So its best uses may be where it’s used in high volume and in relatively remote locations, like the high seas. In fact, the International Maritime Organization will soon be voting on new rules that might give a strong boost to the ammonia alternative for shipping.The key to the new proposed system is to combine the two existing approaches in one facility, with a blue ammonia factory next to a green ammonia factory. The process of generating hydrogen for the green ammonia plant leaves a lot of leftover oxygen that just gets vented to the air. Blue ammonia, on the other hand, uses a process called autothermal reforming that requires a source of pure oxygen, so if there’s a green ammonia plant next door, it can use that excess oxygen.“Putting them next to each other turns out to have significant economic value,” Green says. This synergy could help hybrid “blue-green ammonia” facilities serve as an important bridge toward a future where eventually green ammonia, the cleanest version, could finally dominate. But that future is likely decades away, Green says, so having the combined plants could be an important step along the way.“It might be a really long time before [green ammonia] is actually attractive” economically, he says. “Right now, it’s nowhere close, except in very special situations.” But the combined plants “could be a really appealing concept, and maybe a good way to start the industry,” because so far only small, standalone demonstration plants of the green process are being built.“If green or blue ammonia is going to become the new way of making ammonia, you need to find ways to make it relatively affordable in a lot of countries, with whatever resources they’ve got,” he says. This new proposed combination, he says, “looks like a really good idea that can help push things along. Ultimately, there’s got to be a lot of green ammonia plants in a lot of places,” and starting out with the combined plants, which could be more affordable now, could help to make that happen. The team has filed for a patent on the process.Although the team did a detailed study of both the technology and the economics that show the system has great promise, Green points out that “no one has ever built one. We did the analysis, it looks good, but surely when people build the first one, they’ll find funny little things that need some attention,” such as details of how to start up or shut down the process. “I would say there’s plenty of additional work to do to make it a real industry.” But the results of this study, which shows the costs to be much more affordable than existing blue or green plants in isolation, “definitely encourages the possibility of people making the big investments that would be needed to really make this industry feasible.”This proposed integration of the two methods “improves efficiency, reduces greenhouse gas emissions, and lowers overall cost,” says Kevin van Geem, a professor in the Center for Sustainable Chemistry at Ghent University, who was not associated with this research. “The analysis is rigorous, with validated process models, transparent assumptions, and comparisons to literature benchmarks. By combining techno-economic analysis with emissions accounting, the work provides a credible and balanced view of the trade-offs.”He adds that, “given the scale of global ammonia production, such a reduction could have a highly impactful effect on decarbonizing one of the most emissions-intensive chemical industries.”The research team also included MIT postdoc Angiras Menon and MITEI research lead Guiyan Zang. The work was supported by IHI Japan through the MIT Energy Initiative and the Martin Family Society of Fellows for Sustainability.  More

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      Secretary of Energy Chris Wright ’85 visits MIT

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      U.S. Secretary of Energy Chris Wright ’85 visited MIT on Monday, meeting Institute leaders, discussing energy innovation at a campus forum, viewing poster presentations from researchers supported through the MIT-GE Vernova Energy and Climate Alliance, and watching energy research demos in the lab where he used to work as a student. “I’ve always been in energy because I think it’s just far and away the world’s most important industry,” Wright said at the forum, which included a panel discussion with business leaders and a fireside chat with MIT Professor Ernest Moniz, who was the U.S. secretary of energy from 2013 to 2017. Wright added: “Not only is it by far the world’s most important industry, because it enables all the others, but it’s also a booming time right now. … It is an awesomely exciting time to be in energy.”Wright was greeted on campus by MIT President Sally Kornbluth, who also gave introductory remarks at the forum, held in MIT’s Samberg Center. While the Institute has added many research facilities and buildings since Wright was a student, Kornbluth observed, the core MIT ethos remains the same.“MIT is still MIT,” Kornbluth said. “It’s a community that rewards merit, boldness, and scientific rigor. And it’s a magnet for people with a drive to solve hard problems that matter in the real world, an enthusiasm for working with industry, and an ethic of national service.”When it comes to energy research, Kornbluth added, “MIT is developing transformational approaches to make American energy more secure, reliable, affordable, and clean — which in turn will strengthen both U.S. competitiveness and national security.”At the event, Wright, the 17th U.S. secretary of energy, engaged in a fireside chat with Moniz, the 13th U.S. secretary of energy, the Cecil and Ida Green Professor of Physics and Engineering Systems Post-Tenure, a special advisor to the MIT president, and the founding director of the MIT Energy Initiative (MITEI). Wright began his remarks by reflecting on Kornbluth’s description of the Institute.“Merit, boldness, and scientific rigor,” Wright said. “That is MIT … to me. That hit me hard when I got here, and frankly, it’s a good part of the reason my life has gone the way it’s gone.”On energy topics, Wright emphasized the need for continued innovation in energy across a range of technologies, including fusion, geothermal, and more, while advocating for the benefits of vigorous market-based progress. Before becoming secretary of energy, Wright most recently served as founder and CEO of Liberty Energy. He also was the founder of Pinnacle Technologies, among other enterprises. Wright was confirmed as secretary by the U.S. Senate in February.Asked to name promising areas of technological development, Wright focused on three particular areas of interest. Citing artificial intelligence, he noted that the interest in it was “overwhelming,” with many possible applications. Regarding fusion energy, Wright said, “We are going to see meaningful breakthroughs.” And quantum computing, he added, was going to be a “game-changer” as well.Wright also emphasized the value of federal support for fundamental research, including projects in the national laboratories the Department of Energy oversees.“The 17 national labs we have in this country are absolute jewels. They are gems of this country,” Wright said. He later noted, “There are things, like this foundational research, that are just an essential part of our country and an essential part of our future.”Moniz asked Wright a range of questions in the fireside chat, while adding his own perspective at times about the many issues connected to energy abundance globally.“Climate, energy, security, equity, affordability, have to be recognized as one conversation, and not separate conversations,” Moniz said. “That’s what’s at stake in my view.”Wright’s appearance was part of the Energy Freedom Tour developed by the American Conservation Coalition (ACC), in coordination with the Hamm Institute for American Energy at Oklahoma State University. Later stops are planned for Stanford University and Texas A&M University.Ann Bluntzer Pullin, executive director of the Hamm Institute, gave remarks at the forum as well, noting the importance of making students aware of the energy industry and helping to “get them excited about the impact this career can make.” She also praised MIT’s advances in the field, adding, “This is where so many ideas were born and executed that have allowed America to really thrive in this energy abundance in our country that we have [had] for so long.”The forum also featured remarks from Roger Martella, chief corporate officer, chief sustainability officer, and head of government affairs at GE Vernova. In March, MIT and GE Vernova announced a new five-year joint program, the MIT-GE Vernova Energy and Climate Alliance, featuring research projects, education programs, and career opportunities for MIT students.“That’s what we’re about, electrification as the lifeblood of prosperity,” Martella said, describing GE Vernova’s work. “When we’re here at MIT we feel like we’re living history every moment when we’re walking down the halls, because no institution has [contributed] to innovation and technology more, doing it every single day to advance prosperity for all people around the world.”A panel discussion at the forum featured Wright speaking along with three MIT alumni who are active in the energy business: Carlos Araque ’01, SM ’02, CEO of Quaise Energy, a leading-edge firm in geothermal energy solutions; Bob Mumgaard SM ’15, PhD ’15, CEO of Commonwealth Fusion Systems, a leading fusion energy firm and an MIT spinout; and Milo Werner SM ’07, MBA ’07, a general partner at DCVC and expert in energy and climate investments. The panel was moderated by Chris Barnard, president of the ACC.Mumgaard noted that Commonwealth Fusion Systems launched in 2018 with “an explicit mission, working with MIT still today, of putting fusion onto an industrial trajectory,” although there is “plenty left to do, still, at that intersection of science, technology, innovation, and business.”Araque said he believes geothermal is “metric-by-metric” more powerful and profitable than many other forms of energy. “This is not a stop-gap,” he added. Quaise is currently developing its first power-plant-scale facility in the U.S.Werner noted that the process of useful innovation only begins in the lab; making an advance commercially viable is the critical next step. The biggest impact “is not in the breakthrough,” she said. “It’s not in the discovery that you make in the lab. It’s actually once you’ve built a billion of them. That’s when you actually change the world.”After the forum, Wright took a tour of multiple research centers on the MIT campus, including the MIT.nano facility, guided by Vladimir Bulović, faculty director of MIT.nano and the Fariborz Maseeh Chair in Emerging Technology.At MIT.nano, Bulović showed Wright the Titan Krios G3i, a nearly room-size electron microscope that enables researchers to take a high-resolution look at the structure of tiny particles, with a variety of research applications. The tour also viewed one of MIT.nano’s cleanrooms, a shared fabrication facility used by both MIT researchers and users outside of MIT, including many in industry.On a different note, in an MIT.nano hallway, Bulović showed Wright the One.MIT mosaics, which contain the names of all MIT students and employees past and present — well over 300,000 in all. First etched on a 6-inch wafer, the mosaics are a visual demonstration of the power of nanotechnology — and a searchable display, so Bulović located Wright’s name, which is printed near the chin of one of the figures on the MIT seal.The tour ended in the basement of Building 10, in what is now the refurbished Grainger Energy Machine Facility, where Wright used to conduct research. After earning his undergraduate degree in mechanical engineering, Wright entered into graduate studies at MIT before leaving, as he recounted at the forum, to pursue business opportunities.At the lab, Wright met with David Perreault, the Ford Foundation Professor of Engineering; and Steven Leeb, the Emanuel Landsman Professor, a specialist in power systems. A half-dozen MIT graduate students gave Wright demos of their research projects, all involving energy-generation innovations. Wright readily engaged with all the graduate students about the technologies and the parameters of the devices, and asked the students about their own careers.Wright was accompanied on the lab tour by MIT Provost Anantha Chandrakasan, himself an expert in developing energy-efficient systems. Chandrakasan delivered closing remarks at the forum in the Samberg Center, noting MIT’s “strong partnership with the Department of Energy” and its “long and proud history of engaging industry.”As such, Chandrakasan said, MIT has a “role as a resource in service of the nation, so please don’t hesitate to call on us.” More

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      MIT OpenCourseWare is “a living testament to the nobility of open, unbounded learning”

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      Mostafa Fawzy became interested in physics in high school. It was the “elegance and paradox” of quantum theory that got his attention and led to his studies at the undergraduate and graduate level. But even with a solid foundation of coursework and supportive mentors, Fawzy wanted more. MIT Open Learning’s OpenCourseWare was just the thing he was looking for.  Now a doctoral candidate in atomic physics at Alexandria University and an assistant lecturer of physics at Alamein International University in Egypt, Fawzy reflects on how MIT OpenCourseWare bolstered his learning early in his graduate studies in 2019.  Part of MIT Open Learning, OpenCourseWare offers free, online, open educational resources from more than 2,500 courses that span the MIT undergraduate and graduate curriculum. Fawzy was looking for advanced resources to supplement his research in quantum mechanics and theoretical physics, and he was immediately struck by the quality, accessibility, and breadth of MIT’s resources. “OpenCourseWare was transformative in deepening my understanding of advanced physics,” Fawzy says. “I found the structured lectures and assignments in quantum physics particularly valuable. They enhanced both my theoretical insight and practical problem-solving skills — skills I later applied in research on atomic systems influenced by magnetic fields and plasma environments.”  He completed educational resources including Quantum Physics I and Quantum Physics II, calling them “dense and mathematically sophisticated.” He met the challenge by engaging with the content in different ways: first, by simply listening to lectures, then by taking detailed notes, and finally by working though problem sets. Although initially he struggled to keep up, this methodical approach paid off, he says. He is grateful to his undergraduate mentors, professors M. Sakr and T. Bahy of Alexandria University, as well as to MIT OpenCourseWare, calling it a “steadfast companion through countless solitary nights of study, a beacon in times when formal resources were scarce, and a living testament to the nobility of open, unbounded learning.”  Recognizing the power of mentorship and teaching, Fawzy serves as an academic mentor with the African Academy of Sciences, supporting early-career researchers across the continent in theoretical and atomic physics.  “Many of these mentees lack access to advanced academic resources,” he explains. “I regularly incorporate OpenCourseWare into our mentorship sessions, using it as a foundational teaching and reference tool. It’s an equalizer, providing the same high-caliber content to students regardless of geographical or institutional limitations.” As he looks toward the future, Fawzy has big plans, influenced by MIT. “I aspire to establish a regional center for excellence in atomic and plasma physics, blending cutting-edge research with open-access education in the Global South,” he says. As he continues his research and teaching, he also hopes to influence science policy and contribute to international partnerships that shine the spotlight on research and science in emerging nations.  Along the way, he says, “OpenCourseWare remains a cornerstone resource that I will return to again and again.”  Fawzy says he’s also interested in MIT Open Learning resources in computational physics and energy and sustainability. He’s following MIT’s Energy Initiative, calling it increasingly relevant to his current work and future plans.  Fawzy is a proponent of open learning and a testament to its power. “The intellectual seeds sown by Open Learning resources such as MIT OpenCourseWare have flourished within me, shaping my identity as a physicist and affirming my deep belief in the transformative power of knowledge shared freely, without barriers,” he says.  More

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      Responding to the climate impact of generative AI

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      In part 2 of our two-part series on generative artificial intelligence’s environmental impacts, MIT News explores some of the ways experts are working to reduce the technology’s carbon footprint.The energy demands of generative AI are expected to continue increasing dramatically over the next decade.For instance, an April 2025 report from the International Energy Agency predicts that the global electricity demand from data centers, which house the computing infrastructure to train and deploy AI models, will more than double by 2030, to around 945 terawatt-hours. While not all operations performed in a data center are AI-related, this total amount is slightly more than the energy consumption of Japan.Moreover, an August 2025 analysis from Goldman Sachs Research forecasts that about 60 percent of the increasing electricity demands from data centers will be met by burning fossil fuels, increasing global carbon emissions by about 220 million tons. In comparison, driving a gas-powered car for 5,000 miles produces about 1 ton of carbon dioxide.These statistics are staggering, but at the same time, scientists and engineers at MIT and around the world are studying innovations and interventions to mitigate AI’s ballooning carbon footprint, from boosting the efficiency of algorithms to rethinking the design of data centers.Considering carbon emissionsTalk of reducing generative AI’s carbon footprint is typically centered on “operational carbon” — the emissions used by the powerful processors, known as GPUs, inside a data center. It often ignores “embodied carbon,” which are emissions created by building the data center in the first place, says Vijay Gadepally, senior scientist at MIT Lincoln Laboratory, who leads research projects in the Lincoln Laboratory Supercomputing Center.Constructing and retrofitting a data center, built from tons of steel and concrete and filled with air conditioning units, computing hardware, and miles of cable, consumes a huge amount of carbon. In fact, the environmental impact of building data centers is one reason companies like Meta and Google are exploring more sustainable building materials. (Cost is another factor.)Plus, data centers are enormous buildings — the world’s largest, the China Telecomm-Inner Mongolia Information Park, engulfs roughly 10 million square feet — with about 10 to 50 times the energy density of a normal office building, Gadepally adds. “The operational side is only part of the story. Some things we are working on to reduce operational emissions may lend themselves to reducing embodied carbon, too, but we need to do more on that front in the future,” he says.Reducing operational carbon emissionsWhen it comes to reducing operational carbon emissions of AI data centers, there are many parallels with home energy-saving measures. For one, we can simply turn down the lights.“Even if you have the worst lightbulbs in your house from an efficiency standpoint, turning them off or dimming them will always use less energy than leaving them running at full blast,” Gadepally says.In the same fashion, research from the Supercomputing Center has shown that “turning down” the GPUs in a data center so they consume about three-tenths the energy has minimal impacts on the performance of AI models, while also making the hardware easier to cool.Another strategy is to use less energy-intensive computing hardware.Demanding generative AI workloads, such as training new reasoning models like GPT-5, usually need many GPUs working simultaneously. The Goldman Sachs analysis estimates that a state-of-the-art system could soon have as many as 576 connected GPUs operating at once.But engineers can sometimes achieve similar results by reducing the precision of computing hardware, perhaps by switching to less powerful processors that have been tuned to handle a specific AI workload.There are also measures that boost the efficiency of training power-hungry deep-learning models before they are deployed.Gadepally’s group found that about half the electricity used for training an AI model is spent to get the last 2 or 3 percentage points in accuracy. Stopping the training process early can save a lot of that energy.“There might be cases where 70 percent accuracy is good enough for one particular application, like a recommender system for e-commerce,” he says.Researchers can also take advantage of efficiency-boosting measures.For instance, a postdoc in the Supercomputing Center realized the group might run a thousand simulations during the training process to pick the two or three best AI models for their project.By building a tool that allowed them to avoid about 80 percent of those wasted computing cycles, they dramatically reduced the energy demands of training with no reduction in model accuracy, Gadepally says.Leveraging efficiency improvementsConstant innovation in computing hardware, such as denser arrays of transistors on semiconductor chips, is still enabling dramatic improvements in the energy efficiency of AI models.Even though energy efficiency improvements have been slowing for most chips since about 2005, the amount of computation that GPUs can do per joule of energy has been improving by 50 to 60 percent each year, says Neil Thompson, director of the FutureTech Research Project at MIT’s Computer Science and Artificial Intelligence Laboratory and a principal investigator at MIT’s Initiative on the Digital Economy.“The still-ongoing ‘Moore’s Law’ trend of getting more and more transistors on chip still matters for a lot of these AI systems, since running operations in parallel is still very valuable for improving efficiency,” says Thomspon.Even more significant, his group’s research indicates that efficiency gains from new model architectures that can solve complex problems faster, consuming less energy to achieve the same or better results, is doubling every eight or nine months.Thompson coined the term “negaflop” to describe this effect. The same way a “negawatt” represents electricity saved due to energy-saving measures, a “negaflop” is a computing operation that doesn’t need to be performed due to algorithmic improvements.These could be things like “pruning” away unnecessary components of a neural network or employing compression techniques that enable users to do more with less computation.“If you need to use a really powerful model today to complete your task, in just a few years, you might be able to use a significantly smaller model to do the same thing, which would carry much less environmental burden. Making these models more efficient is the single-most important thing you can do to reduce the environmental costs of AI,” Thompson says.Maximizing energy savingsWhile reducing the overall energy use of AI algorithms and computing hardware will cut greenhouse gas emissions, not all energy is the same, Gadepally adds.“The amount of carbon emissions in 1 kilowatt hour varies quite significantly, even just during the day, as well as over the month and year,” he says.Engineers can take advantage of these variations by leveraging the flexibility of AI workloads and data center operations to maximize emissions reductions. For instance, some generative AI workloads don’t need to be performed in their entirety at the same time.Splitting computing operations so some are performed later, when more of the electricity fed into the grid is from renewable sources like solar and wind, can go a long way toward reducing a data center’s carbon footprint, says Deepjyoti Deka, a research scientist in the MIT Energy Initiative.Deka and his team are also studying “smarter” data centers where the AI workloads of multiple companies using the same computing equipment are flexibly adjusted to improve energy efficiency.“By looking at the system as a whole, our hope is to minimize energy use as well as dependence on fossil fuels, while still maintaining reliability standards for AI companies and users,” Deka says.He and others at MITEI are building a flexibility model of a data center that considers the differing energy demands of training a deep-learning model versus deploying that model. Their hope is to uncover the best strategies for scheduling and streamlining computing operations to improve energy efficiency.The researchers are also exploring the use of long-duration energy storage units at data centers, which store excess energy for times when it is needed.With these systems in place, a data center could use stored energy that was generated by renewable sources during a high-demand period, or avoid the use of diesel backup generators if there are fluctuations in the grid.“Long-duration energy storage could be a game-changer here because we can design operations that really change the emission mix of the system to rely more on renewable energy,” Deka says.In addition, researchers at MIT and Princeton University are developing a software tool for investment planning in the power sector, called GenX, which could be used to help companies determine the ideal place to locate a data center to minimize environmental impacts and costs.Location can have a big impact on reducing a data center’s carbon footprint. For instance, Meta operates a data center in Lulea, a city on the coast of northern Sweden where cooler temperatures reduce the amount of electricity needed to cool computing hardware.Thinking farther outside the box (way farther), some governments are even exploring the construction of data centers on the moon where they could potentially be operated with nearly all renewable energy.AI-based solutionsCurrently, the expansion of renewable energy generation here on Earth isn’t keeping pace with the rapid growth of AI, which is one major roadblock to reducing its carbon footprint, says Jennifer Turliuk MBA ’25, a short-term lecturer, former Sloan Fellow, and former practice leader of climate and energy AI at the Martin Trust Center for MIT Entrepreneurship.The local, state, and federal review processes required for a new renewable energy projects can take years.Researchers at MIT and elsewhere are exploring the use of AI to speed up the process of connecting new renewable energy systems to the power grid.For instance, a generative AI model could streamline interconnection studies that determine how a new project will impact the power grid, a step that often takes years to complete.And when it comes to accelerating the development and implementation of clean energy technologies, AI could play a major role.“Machine learning is great for tackling complex situations, and the electrical grid is said to be one of the largest and most complex machines in the world,” Turliuk adds.For instance, AI could help optimize the prediction of solar and wind energy generation or identify ideal locations for new facilities.It could also be used to perform predictive maintenance and fault detection for solar panels or other green energy infrastructure, or to monitor the capacity of transmission wires to maximize efficiency.By helping researchers gather and analyze huge amounts of data, AI could also inform targeted policy interventions aimed at getting the biggest “bang for the buck” from areas such as renewable energy, Turliuk says.To help policymakers, scientists, and enterprises consider the multifaceted costs and benefits of AI systems, she and her collaborators developed the Net Climate Impact Score.The score is a framework that can be used to help determine the net climate impact of AI projects, considering emissions and other environmental costs along with potential environmental benefits in the future.At the end of the day, the most effective solutions will likely result from collaborations among companies, regulators, and researchers, with academia leading the way, Turliuk adds.“Every day counts. We are on a path where the effects of climate change won’t be fully known until it is too late to do anything about it. This is a once-in-a-lifetime opportunity to innovate and make AI systems less carbon-intense,” she says. More

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      Confronting the AI/energy conundrum

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      The explosive growth of AI-powered computing centers is creating an unprecedented surge in electricity demand that threatens to overwhelm power grids and derail climate goals. At the same time, artificial intelligence technologies could revolutionize energy systems, accelerating the transition to clean power.“We’re at a cusp of potentially gigantic change throughout the economy,” said William H. Green, director of the MIT Energy Initiative (MITEI) and Hoyt C. Hottel Professor in the MIT Department of Chemical Engineering, at MITEI’s Spring Symposium, “AI and energy: Peril and promise,” held on May 13. The event brought together experts from industry, academia, and government to explore solutions to what Green described as both “local problems with electric supply and meeting our clean energy targets” while seeking to “reap the benefits of AI without some of the harms.” The challenge of data center energy demand and potential benefits of AI to the energy transition is a research priority for MITEI.AI’s startling energy demandsFrom the start, the symposium highlighted sobering statistics about AI’s appetite for electricity. After decades of flat electricity demand in the United States, computing centers now consume approximately 4 percent of the nation’s electricity. Although there is great uncertainty, some projections suggest this demand could rise to 12-15 percent by 2030, largely driven by artificial intelligence applications.Vijay Gadepally, senior scientist at MIT’s Lincoln Laboratory, emphasized the scale of AI’s consumption. “The power required for sustaining some of these large models is doubling almost every three months,” he noted. “A single ChatGPT conversation uses as much electricity as charging your phone, and generating an image consumes about a bottle of water for cooling.”Facilities requiring 50 to 100 megawatts of power are emerging rapidly across the United States and globally, driven both by casual and institutional research needs relying on large language programs such as ChatGPT and Gemini. Gadepally cited congressional testimony by Sam Altman, CEO of OpenAI, highlighting how fundamental this relationship has become: “The cost of intelligence, the cost of AI, will converge to the cost of energy.”“The energy demands of AI are a significant challenge, but we also have an opportunity to harness these vast computational capabilities to contribute to climate change solutions,” said Evelyn Wang, MIT vice president for energy and climate and the former director at the Advanced Research Projects Agency-Energy (ARPA-E) at the U.S. Department of Energy.Wang also noted that innovations developed for AI and data centers — such as efficiency, cooling technologies, and clean-power solutions — could have broad applications beyond computing facilities themselves.Strategies for clean energy solutionsThe symposium explored multiple pathways to address the AI-energy challenge. Some panelists presented models suggesting that while artificial intelligence may increase emissions in the short term, its optimization capabilities could enable substantial emissions reductions after 2030 through more efficient power systems and accelerated clean technology development.Research shows regional variations in the cost of powering computing centers with clean electricity, according to Emre Gençer, co-founder and CEO of Sesame Sustainability and former MITEI principal research scientist. Gençer’s analysis revealed that the central United States offers considerably lower costs due to complementary solar and wind resources. However, achieving zero-emission power would require massive battery deployments — five to 10 times more than moderate carbon scenarios — driving costs two to three times higher.“If we want to do zero emissions with reliable power, we need technologies other than renewables and batteries, which will be too expensive,” Gençer said. He pointed to “long-duration storage technologies, small modular reactors, geothermal, or hybrid approaches” as necessary complements.Because of data center energy demand, there is renewed interest in nuclear power, noted Kathryn Biegel, manager of R&D and corporate strategy at Constellation Energy, adding that her company is restarting the reactor at the former Three Mile Island site, now called the “Crane Clean Energy Center,” to meet this demand. “The data center space has become a major, major priority for Constellation,” she said, emphasizing how their needs for both reliability and carbon-free electricity are reshaping the power industry.Can AI accelerate the energy transition?Artificial intelligence could dramatically improve power systems, according to Priya Donti, assistant professor and the Silverman Family Career Development Professor in MIT’s Department of Electrical Engineering and Computer Science and the Laboratory for Information and Decision Systems. She showcased how AI can accelerate power grid optimization by embedding physics-based constraints into neural networks, potentially solving complex power flow problems at “10 times, or even greater, speed compared to your traditional models.”AI is already reducing carbon emissions, according to examples shared by Antonia Gawel, global director of sustainability and partnerships at Google. Google Maps’ fuel-efficient routing feature has “helped to prevent more than 2.9 million metric tons of GHG [greenhouse gas] emissions reductions since launch, which is the equivalent of taking 650,000 fuel-based cars off the road for a year,” she said. Another Google research project uses artificial intelligence to help pilots avoid creating contrails, which represent about 1 percent of global warming impact.AI’s potential to speed materials discovery for power applications was highlighted by Rafael Gómez-Bombarelli, the Paul M. Cook Career Development Associate Professor in the MIT Department of Materials Science and Engineering. “AI-supervised models can be trained to go from structure to property,” he noted, enabling the development of materials crucial for both computing and efficiency.Securing growth with sustainabilityThroughout the symposium, participants grappled with balancing rapid AI deployment against environmental impacts. While AI training receives most attention, Dustin Demetriou, senior technical staff member in sustainability and data center innovation at IBM, quoted a World Economic Forum article that suggested that “80 percent of the environmental footprint is estimated to be due to inferencing.” Demetriou emphasized the need for efficiency across all artificial intelligence applications.Jevons’ paradox, where “efficiency gains tend to increase overall resource consumption rather than decrease it” is another factor to consider, cautioned Emma Strubell, the Raj Reddy Assistant Professor in the Language Technologies Institute in the School of Computer Science at Carnegie Mellon University. Strubell advocated for viewing computing center electricity as a limited resource requiring thoughtful allocation across different applications.Several presenters discussed novel approaches for integrating renewable sources with existing grid infrastructure, including potential hybrid solutions that combine clean installations with existing natural gas plants that have valuable grid connections already in place. These approaches could provide substantial clean capacity across the United States at reasonable costs while minimizing reliability impacts.Navigating the AI-energy paradoxThe symposium highlighted MIT’s central role in developing solutions to the AI-electricity challenge.Green spoke of a new MITEI program on computing centers, power, and computation that will operate alongside the comprehensive spread of MIT Climate Project research. “We’re going to try to tackle a very complicated problem all the way from the power sources through the actual algorithms that deliver value to the customers — in a way that’s going to be acceptable to all the stakeholders and really meet all the needs,” Green said.Participants in the symposium were polled about priorities for MIT’s research by Randall Field, MITEI director of research. The real-time results ranked “data center and grid integration issues” as the top priority, followed by “AI for accelerated discovery of advanced materials for energy.”In addition, attendees revealed that most view AI’s potential regarding power as a “promise,” rather than a “peril,” although a considerable portion remain uncertain about the ultimate impact. When asked about priorities in power supply for computing facilities, half of the respondents selected carbon intensity as their top concern, with reliability and cost following. More

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      in Energy

      Decarbonizing steel is as tough as steel

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      The long-term aspirational goal of the Paris Agreement on climate change is to cap global warming at 1.5 degrees Celsius above preindustrial levels, and thereby reduce the frequency and severity of floods, droughts, wildfires, and other extreme weather events. Achieving that goal will require a massive reduction in global carbon dioxide (CO2) emissions across all economic sectors. A major roadblock, however, could be the industrial sector, which accounts for roughly 25 percent of global energy- and process-related CO2 emissions — particularly within the iron and steel sector, industry’s largest emitter of CO2.Iron and steel production now relies heavily on fossil fuels (coal or natural gas) for heat, converting iron ore to iron, and making steel strong. Steelmaking could be decarbonized by a combination of several methods, including carbon capture technology, the use of low- or zero-carbon fuels, and increased use of recycled steel. Now a new study in the Journal of Cleaner Production systematically explores the viability of different iron-and-steel decarbonization strategies.Today’s strategy menu includes improving energy efficiency, switching fuels and technologies, using more scrap steel, and reducing demand. Using the MIT Economic Projection and Policy Analysis model, a multi-sector, multi-region model of the world economy, researchers at MIT, the University of Illinois at Urbana-Champaign, and ExxonMobil Technology and Engineering Co. evaluate the decarbonization potential of replacing coal-based production processes with electric arc furnaces (EAF), along with either scrap steel or “direct reduced iron” (DRI), which is fueled by natural gas with carbon capture and storage (NG CCS DRI-EAF) or by hydrogen (H2 DRI-EAF).Under a global climate mitigation scenario aligned with the 1.5 C climate goal, these advanced steelmaking technologies could result in deep decarbonization of the iron and steel sector by 2050, as long as technology costs are low enough to enable large-scale deployment. Higher costs would favor the replacement of coal with electricity and natural gas, greater use of scrap steel, and reduced demand, resulting in a more-than-50-percent reduction in emissions relative to current levels. Lower technology costs would enable massive deployment of NG CCS DRI-EAF or H2 DRI-EAF, reducing emissions by up to 75 percent.Even without adoption of these advanced technologies, the iron-and-steel sector could significantly reduce its CO2 emissions intensity (how much CO2 is released per unit of production) with existing steelmaking technologies, primarily by replacing coal with gas and electricity (especially if it is generated by renewable energy sources), using more scrap steel, and implementing energy efficiency measures.“The iron and steel industry needs to combine several strategies to substantially reduce its emissions by mid-century, including an increase in recycling, but investing in cost reductions in hydrogen pathways and carbon capture and sequestration will enable even deeper emissions mitigation in the sector,” says study supervising author Sergey Paltsev, deputy director of the MIT Center for Sustainability Science and Strategy (MIT CS3) and a senior research scientist at the MIT Energy Initiative (MITEI).This study was supported by MIT CS3 and ExxonMobil through its membership in MITEI. More

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      in Energy

      Recovering from the past and transitioning to a better energy future

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      As the frequency and severity of extreme weather events grow, it may become increasingly necessary to employ a bolder approach to climate change, warned Emily A. Carter, the Gerhard R. Andlinger Professor in Energy and the Environment at Princeton University. Carter made her case for why the energy transition is no longer enough in the face of climate change while speaking at the MIT Energy Initiative (MITEI) Presents: Advancing the Energy Transition seminar on the MIT campus.“If all we do is take care of what we did in the past — but we don’t change what we do in the future — then we’re still going to be left with very serious problems,” she said. Our approach to climate change mitigation must comprise transformation, intervention, and adaption strategies, said Carter. Transitioning to a decarbonized electricity system is one piece of the puzzle. Growing amounts of solar and wind energy — along with nuclear, hydropower, and geothermal — are slowly transforming the energy electricity landscape, but Carter noted that there are new technologies farther down the pipeline.  “Advanced geothermal may come on in the next couple of decades. Fusion will only really start to play a role later in the century, but could provide firm electricity such that we can start to decommission nuclear,” said Carter, who is also a senior strategic advisor and associate laboratory director at the Department of Energy’s Princeton Plasma Physics Laboratory. Taking this a step further, Carter outlined how this carbon-free electricity should then be used to electrify everything we can. She highlighted the industrial sector as a critical area for transformation: “The energy transition is about transitioning off of fossil fuels. If you look at the manufacturing industries, they are driven by fossil fuels right now. They are driven by fossil fuel-driven thermal processes.” Carter noted that thermal energy is much less efficient than electricity and highlighted electricity-driven strategies that could replace heat in manufacturing, such as electrolysis, plasmas, light-emitting diodes (LEDs) for photocatalysis, and joule heating. The transportation sector is also a key area for electrification, Carter said. While electric vehicles have become increasingly common in recent years, heavy-duty transportation is not as easily electrified. The solution? “Carbon-neutral fuels for heavy-duty aviation and shipping,” she said, emphasizing that these fuels will need to become part of the circular economy. “We know that when we burn those fuels, they’re going to produce CO2 [carbon dioxide] again. They need to come from a source of CO2 that is not fossil-based.” The next step is intervention in the form of carbon dioxide removal, which then necessitates methods of storage and utilization, according to Carter. “There’s a lot of talk about building large numbers of pipelines to capture the CO2 — from fossil fuel-driven power plants, cement plants, steel plants, all sorts of industrial places that emit CO2 — and then piping it and storing it in underground aquifers,” she explained. Offshore pipelines are much more expensive than those on land, but can mitigate public concerns over their safety. Europe is exclusively focusing their efforts offshore for this very reason, and the same could be true for the United States, Carter said.  Once carbon dioxide is captured, commercial utilization may provide economic leverage to accelerate sequestration, even if only a few gigatons are used per year, Carter noted. Through mineralization, CO2 can be converted into carbonates, which could be used in building materials such as concrete and road-paving materials.  There is another form of intervention that Carter currently views as a last resort: solar geoengineering, sometimes known as solar radiation management or SRM. In 1991, Mount Pinatubo in the Philippines erupted and released sulfur dioxide into the stratosphere, which caused a temporary cooling of the Earth by approximately 0.5 degree Celsius for over a year. SRM seeks to recreate that cooling effect by injecting particles into the atmosphere that reflect sunlight. According to Carter, there are three main strategies: stratospheric aerosol injection, cirrus cloud thinning (thinning clouds to let more infrared radiation emitted by the earth escape to space), and marine cloud brightening (brightening clouds with sea salt so they reflect more light).  “My view is, I hope we don’t ever have to do it, but I sure think we should understand what would happen in case somebody else just decides to do it. It’s a global security issue,” said Carter. “In principle, it’s not so difficult technologically, so we’d like to really understand and to be able to predict what would happen if that happened.” With any technology, stakeholder and community engagement is essential for deployment, Carter said. She emphasized the importance of both respectfully listening to concerns and thoroughly addressing them, stating, “Hopefully, there’s enough information given to assuage their fears. We have to gain the trust of people before any deployment can be considered.” A crucial component of this trust starts with the responsibility of the scientific community to be transparent and critique each other’s work, Carter said. “Skepticism is good. You should have to prove your proof of principle.” MITEI Presents: Advancing the Energy Transition is an MIT Energy Initiative speaker series highlighting energy experts and leaders at the forefront of the scientific, technological, and policy solutions needed to transform our energy systems. The series will continue in fall 2025. For more information on this and additional events, visit the MITEI website. More

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      in Environment

      Study helps pinpoint areas where microplastics will accumulate

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      The accumulation of microplastics in the environment, and within our bodies, is an increasingly worrisome issue. But predicting where these ubiquitous particles will accumulate, and therefore where remediation efforts should be focused, has been difficult because of the many factors that contribute to their dispersal and deposition.New research from MIT shows that one key factor in determining where microparticles are likely to build up has to do with the presence of biofilms. These thin, sticky biopolymer layers are shed by microorganisms and can accumulate on surfaces, including along sandy riverbeds or seashores. The study found that, all other conditions being equal, microparticles are less likely to accumulate in sediment infused with biofilms, because if they land there, they are more likely to be resuspended by flowing water and carried away.The open-access findings appear in the journal Geophysical Research Letters, in a paper by MIT postdoc Hyoungchul Park and professor of civil and environmental engineering Heidi Nepf. “Microplastics are definitely in the news a lot,” Nepf says, “and we don’t fully understand where the hotspots of accumulation are likely to be. This work gives a little bit of guidance” on some of the factors that can cause these particles, and small particles in general, to accumulate in certain locations.Most experiments looking at the ways microparticles are transported and deposited have been conducted over bare sand, Park says. “But in nature, there are a lot of microorganisms, such as bacteria, fungi, and algae, and when they adhere to the stream bed they generate some sticky things.” These substances are known as extracellular polymeric substances, or EPS, and they “can significantly affect the channel bed characteristics,” he says. The new research focused on determining exactly how these substances affected the transport of microparticles, including microplastics.The research involved a flow tank with a bottom lined with fine sand, and sometimes with vertical plastic tubes simulating the presence of mangrove roots. In some experiments the bed consisted of pure sand, and in others the sand was mixed with a biological material to simulate the natural biofilms found in many riverbed and seashore environments.Water mixed with tiny plastic particles was pumped through the tank for three hours, and then the bed surface was photographed under ultraviolet light that caused the plastic particles to fluoresce, allowing a quantitative measurement of their concentration.The results revealed two different phenomena that affected how much of the plastic accumulated on the different surfaces. Immediately around the rods that stood in for above-ground roots, turbulence prevented particle deposition. In addition, as the amount of simulated biofilms in the sediment bed increased, the accumulation of particles also decreased.Nepf and Park concluded that the biofilms filled up the spaces between the sand grains, leaving less room for the microparticles to fit in. The particles were more exposed because they penetrated less deeply in between the sand grains, and as a result they were much more easily resuspended and carried away by the flowing water.“These biological films fill the pore spaces between the sediment grains,” Park explains, “and that makes the deposited particles — the particles that land on the bed — more exposed to the forces generated by the flow, which makes it easier for them to be resuspended. What we found was that in a channel with the same flow conditions and the same vegetation and the same sand bed, if one is without EPS and one is with EPS, then the one without EPS has a much higher deposition rate than the one with EPS.”Nepf adds: “The biofilm is blocking the plastics from accumulating in the bed because they can’t go deep into the bed. They just stay right on the surface, and then they get picked up and moved elsewhere. So, if I spilled a large amount of microplastic in two rivers, and one had a sandy or gravel bottom, and one was muddier with more biofilm, I would expect more of the microplastics to be retained in the sandy or gravelly river.”All of this is complicated by other factors, such as the turbulence of the water or the roughness of the bottom surface, she says. But it provides a “nice lens” to provide some suggestions for people who are trying to study the impacts of microplastics in the field. “They’re trying to determine what kinds of habitats these plastics are in, and this gives a framework for how you might categorize those habitats,” she says. “It gives guidance to where you should go to find more plastics versus less.”As an example, Park suggests, in mangrove ecosystems, microplastics may preferentially accumulate in the outer edges, which tend to be sandy, while the interior zones have sediment with more biofilm. Thus, this work suggests “the sandy outer regions may be potential hotspots for microplastic accumulation,” he says, and can make this a priority zone for monitoring and protection.“This is a highly relevant finding,” says Isabella Schalko, a research scientist at ETH Zurich, who was not associated with this research. “It suggests that restoration measures such as re-vegetation or promoting biofilm growth could help mitigate microplastic accumulation in aquatic systems. It highlights the powerful role of biological and physical features in shaping particle transport processes.”The work was supported by Shell International Exploration and Production through the MIT Energy Initiative. More

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      in Energy

      A new approach could fractionate crude oil using much less energy

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      Separating crude oil into products such as gasoline, diesel, and heating oil is an energy-intensive process that accounts for about 6 percent of the world’s CO2 emissions. Most of that energy goes into the heat needed to separate the components by their boiling point.In an advance that could dramatically reduce the amount of energy needed for crude oil fractionation, MIT engineers have developed a membrane that filters the components of crude oil by their molecular size.“This is a whole new way of envisioning a separation process. Instead of boiling mixtures to purify them, why not separate components based on shape and size? The key innovation is that the filters we developed can separate very small molecules at an atomistic length scale,” says Zachary P. Smith, an associate professor of chemical engineering at MIT and the senior author of the new study.The new filtration membrane can efficiently separate heavy and light components from oil, and it is resistant to the swelling that tends to occur with other types of oil separation membranes. The membrane is a thin film that can be manufactured using a technique that is already widely used in industrial processes, potentially allowing it to be scaled up for widespread use.Taehoon Lee, a former MIT postdoc who is now an assistant professor at Sungkyunkwan University in South Korea, is the lead author of the paper, which appears today in Science.Oil fractionationConventional heat-driven processes for fractionating crude oil make up about 1 percent of global energy use, and it has been estimated that using membranes for crude oil separation could reduce the amount of energy needed by about 90 percent. For this to succeed, a separation membrane needs to allow hydrocarbons to pass through quickly, and to selectively filter compounds of different sizes.Until now, most efforts to develop a filtration membrane for hydrocarbons have focused on polymers of intrinsic microporosity (PIMs), including one known as PIM-1. Although this porous material allows the fast transport of hydrocarbons, it tends to excessively absorb some of the organic compounds as they pass through the membrane, leading the film to swell, which impairs its size-sieving ability.To come up with a better alternative, the MIT team decided to try modifying polymers that are used for reverse osmosis water desalination. Since their adoption in the 1970s, reverse osmosis membranes have reduced the energy consumption of desalination by about 90 percent — a remarkable industrial success story.The most commonly used membrane for water desalination is a polyamide that is manufactured using a method known as interfacial polymerization. During this process, a thin polymer film forms at the interface between water and an organic solvent such as hexane. Water and hexane do not normally mix, but at the interface between them, a small amount of the compounds dissolved in them can react with each other.In this case, a hydrophilic monomer called MPD, which is dissolved in water, reacts with a hydrophobic monomer called TMC, which is dissolved in hexane. The two monomers are joined together by a connection known as an amide bond, forming a polyamide thin film (named MPD-TMC) at the water-hexane interface.While highly effective for water desalination, MPD-TMC doesn’t have the right pore sizes and swelling resistance that would allow it to separate hydrocarbons.To adapt the material to separate the hydrocarbons found in crude oil, the researchers first modified the film by changing the bond that connects the monomers from an amide bond to an imine bond. This bond is more rigid and hydrophobic, which allows hydrocarbons to quickly move through the membrane without causing noticeable swelling of the film compared to the polyamide counterpart.“The polyimine material has porosity that forms at the interface, and because of the cross-linking chemistry that we have added in, you now have something that doesn’t swell,” Smith says. “You make it in the oil phase, react it at the water interface, and with the crosslinks, it’s now immobilized. And so those pores, even when they’re exposed to hydrocarbons, no longer swell like other materials.”The researchers also introduced a monomer called triptycene. This shape-persistent, molecularly selective molecule further helps the resultant polyimines to form pores that are the right size for hydrocarbons to fit through.This approach represents “an important step toward reducing industrial energy consumption,” says Andrew Livingston, a professor of chemical engineering at Queen Mary University of London, who was not involved in the study.“This work takes the workhorse technology of the membrane desalination industry, interfacial polymerization, and creates a new way to apply it to organic systems such as hydrocarbon feedstocks, which currently consume large chunks of global energy,” Livingston says. “The imaginative approach using an interfacial catalyst coupled to hydrophobic monomers leads to membranes with high permeance and excellent selectivity, and the work shows how these can be used in relevant separations.”Efficient separationWhen the researchers used the new membrane to filter a mixture of toluene and triisopropylbenzene (TIPB) as a benchmark for evaluating separation performance, it was able to achieve a concentration of toluene 20 times greater than its concentration in the original mixture. They also tested the membrane with an industrially relevant mixture consisting of naphtha, kerosene, and diesel, and found that it could efficiently separate the heavier and lighter compounds by their molecular size.If adapted for industrial use, a series of these filters could be used to generate a higher concentration of the desired products at each step, the researchers say.“You can imagine that with a membrane like this, you could have an initial stage that replaces a crude oil fractionation column. You could partition heavy and light molecules and then you could use different membranes in a cascade to purify complex mixtures to isolate the chemicals that you need,” Smith says.Interfacial polymerization is already widely used to create membranes for water desalination, and the researchers believe it should be possible to adapt those processes to mass produce the films they designed in this study.“The main advantage of interfacial polymerization is it’s already a well-established method to prepare membranes for water purification, so you can imagine just adopting these chemistries into existing scale of manufacturing lines,” Lee says.The research was funded, in part, by ExxonMobil through the MIT Energy Initiative.  More