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      How to decarbonize the world, at scale

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      The world in recent years has largely been moving on from debates about the need to curb carbon emissions and focusing more on action — the development, implementation, and deployment of the technological, economic, and policy measures to spur the scale of reductions needed by mid-century. That was the message Robert Stoner, the interim director of the MIT Energy Initiative (MITEI), gave in his opening remarks at the 2023 MITEI Annual Research Conference.

      Attendees at the two-day conference included faculty members, researchers, industry and financial leaders, government officials, and students, as well as more than 50 online participants from around the world.

      “We are at an extraordinary inflection point. We have this narrow window in time to mitigate the worst effects of climate change by transforming our entire energy system and economy,” said Jonah Wagner, the chief strategist of the U.S. Department of Energy’s (DOE) Loan Programs Office, in one of the conference’s keynote speeches.

      Yet the solutions exist, he said. “Most of the technologies that we need to deploy to stay close to the international target of 1.5 degrees Celsius warming are proven and ready to go,” he said. “We have over 80 percent of the technologies we will need through 2030, and at least half of the technologies we will need through 2050.”

      For example, Wagner pointed to the newly commissioned advanced nuclear power plant near Augusta, Georgia — the first new nuclear reactor built in the United States in a generation, partly funded through DOE loans. “It will be the largest source of clean power in America,” he said. Though implementing all the needed technologies in the United States through mid-century will cost an estimated $10 trillion, or about $300 billion a year, most of that money will come from the private sector, he said.

      As the United States faces what he describes as “a tsunami of distributed energy production,” one key example of the strategy that’s needed going forward, he said, is encouraging the development of virtual power plants (VPPs). The U.S. power grid is growing, he said, and will add 200 gigawatts of peak demand by 2030. But rather than building new, large power plants to satisfy that need, much of the increase can be accommodated by VPPs, he said — which are “aggregations of distributed energy resources like rooftop solar with batteries, like electric vehicles (EVs) and chargers, like smart appliances, commercial and industrial loads on the grid that can be used together to help balance supply and demand just like a traditional power plant.” For example, by shifting the time of demand for some applications where the timing is not critical, such as recharging EVs late at night instead of right after getting home from work when demand may be peaking, the need for extra peak power can be alleviated.

      Such programs “offer a broad range of benefits,” including affordability, reliability and resilience, decarbonization, and emissions reductions. But implementing such systems on a wide scale requires some up-front help, he explained. Payment for consumers to enroll in programs that allow such time adjustments “is the majority of the cost” of establishing VPPs, he says, “and that means most of the money spent on VPPs goes back into the pockets of American consumers.” But to make that happen, there is a need for standardization of VPP operations “so that we are not recreating the wheel every single time we deploy a pilot or an effort with a utility.”

      The conference’s other keynote speaker, Anne White, the vice provost and associate vice president for research administration at MIT, cited devastating recent floods, wildfires, and many other extreme weather-related crises around the world that have been exacerbated by climate change. “We saw in myriad ways that energy concerns and climate concerns are one and the same,” she said. “So, we must urgently develop and scale low-carbon and zero-carbon solutions to prevent future warming. And we must do this with a practical, systems-based approach that considers efficiency, affordability, equity, and sustainability for how the world will meet its energy needs.”

      White added that at MIT, “we are mobilizing everything.” People at MIT feel a strong sense of responsibility for dealing with these global issues, she said, “and I think it’s because we believe we have tools that can really make a difference.”

      Among the specific promising technologies that have sprung from MIT’s labs, she pointed out, is the rapid development of fusion technology that led to MIT spinoff company Commonwealth Fusion Systems, which aims to build a demonstration unit of a practical fusion power reactor by the decade’s end. That’s an outcome of decades of research, she emphasized — the kinds of early-stage risky work that only academic labs, with help from government grants, can carry out.

      For example, she pointed to the more than 200 projects that MITEI has provided seed funds of $150,000 each for two years, totaling over $28 million to date. Such early support is “a key part of producing the kind of transformative innovation we know we all need.” In addition, MIT’s The Engine has also helped launch not only Commonwealth Fusion Systems, but also Form Energy, a company building a plant in West Virginia to manufacture advanced iron-air batteries for renewable energy storage, and many others.

      Following that theme of supporting early innovation, the conference featured two panels that served to highlight the work of students and alumni and their energy-related startup companies. First, a startup showcase, moderated by Catarina Madeira, the director of MIT’s Startup Exchange, featured presentations about seven recent spinoff companies that are developing cutting-edge technologies that emerged from MIT research. These included:

      Aeroshield, developing a new kind of highly-insulated window using a unique aerogel material;
      Sublime, which is developing a low-emissions concrete;
      Found Energy, developing a way to use recycled aluminum as a fuel;
      Veir, developing superconducting power lines;
      Emvolom, developing inexpensive green fuels from waste gases;
      Boston Metal, developing low-emissions production processes for steel and other metals;
      Transaera, with a new kind of efficient air conditioning; and
      Carbon Recycling International, producing cheap hydrogen fuel and syngas.
      Later in the conference, a “student slam competition” featured presentations by 11 students who described results of energy projects they had been working on this past summer. The projects were as diverse as analyzing opposition to wind farms in Maine, how best to allocate EV charging stations, optimizing bioenergy production, recycling the lithium from batteries, encouraging adoption of heat pumps, and conflict analysis about energy project siting. Attendees voted on the quality of the student presentations, and electrical engineering and computer science student Tori Hagenlocker was declared first-place winner for her talk on heat pump adoption.

      Students were also featured in a first-time addition to the conference: a panel discussion among five current or recent students, giving their perspective on today’s energy issues and priorities, and how they are working toward trying to make a difference. Andres Alvarez, a recent graduate in nuclear engineering, described his work with a startup focused on identifying and supporting early-stage ideas that have potential. Graduate student Dyanna Jaye of urban studies and planning spoke about her work helping to launch a group called the Sunrise Movement to try to drive climate change as a top priority for the country, and her work helping to develop the Green New Deal.

      Peter Scott, a graduate student in mechanical engineering who is studying green hydrogen production, spoke of the need for a “very drastic and rapid phaseout of current, existing fossil fuels” and a halt on developing new sources. Amar Dayal, an MBA candidate at the MIT Sloan School of Management, talked about the interplay between technology and policy, and the crucial role that legislation like the Inflation Reduction Act can have in enabling new energy technology to make the climb to commercialization. And Shreyaa Raghavan, a doctoral student in the Institute of Data, Systems, and Society, talked about the importance of multidisciplinary approaches to climate issues, including the important role of computer science. She added that MIT does well on this compared to other institutions, and “sustainability and decarbonization is a pillar in a lot of the different departments and programs that exist here.”

      Some recent recipients of MITEI’s Seed Fund grants reported on their progress in a panel discussion moderated by MITEI Executive Director Martha Broad. Seed grant recipient Ariel Furst, a professor of chemical engineering, pointed out that access to electricity is very much concentrated in the global North and that, overall, one in 10 people worldwide lacks access to electricity and some 2.5 billion people “rely on dirty fuels to heat their homes and cook their food,” with impacts on both health and climate. The solution her project is developing involves using DNA molecules combined with catalysts to passively convert captured carbon dioxide into ethylene, a widely used chemical feedstock and fuel. Kerri Cahoy, a professor of aeronautics and astronautics, described her work on a system for monitoring methane emissions and power-line conditions by using satellite-based sensors. She and her team found that power lines often begin emitting detectable broadband radio frequencies long before they actually fail in a way that could spark fires.

      Admir Masic, an associate professor of civil and environmental engineering, described work on mining the ocean for minerals such as magnesium hydroxide to be used for carbon capture. The process can turn carbon dioxide into solid material that is stable over geological times and potentially usable as a construction material. Kripa Varanasi, a professor of mechanical engineering, said that over the years MITEI seed funding helped some of his projects that “went on to become startup companies, and some of them are thriving.” He described ongoing work on a new kind of electrolyzer for green hydrogen production. He developed a system using bubble-attracting surfaces to increase the efficiency of bioreactors that generate hydrogen fuel.

      A series of panel discussions over the two days covered a range of topics related to technologies and policies that could make a difference in combating climate change. On the technological side, one panel led by Randall Field, the executive director of MITEI’s Future Energy Systems Center, looked at large, hard-to-decarbonize industrial processes. Antoine Allanore, a professor of metallurgy, described progress in developing innovative processes for producing iron and steel, among the world’s most used commodities, in a way that drastically reduces greenhouse gas emissions. Greg Wilson of JERA Americas described the potential for ammonia produced from renewable sources to substitute for natural gas in power plants, greatly reducing emissions. Yet-Ming Chiang, a professor in materials science and engineering, described ways to decarbonize cement production using a novel low-temperature process. And Guiyan Zang, a research scientist at MITEI, spoke of efforts to reduce the carbon footprint of producing ethylene, a major industrial chemical, by using an electrochemical process.

      Another panel, led by Jacopo Buongiorno, professor of nuclear science and engineering, explored the brightening future for expansion of nuclear power, including new, small, modular reactors that are finally emerging into commercial demonstration. “There is for the first time truly here in the U.S. in at least a decade-and-a-half, a lot of excitement, a lot of attention towards nuclear,” Buongiorno said. Nuclear power currently produces 45 to 50 percent of the nation’s carbon-free electricity, the panelists said, and with the first new nuclear power plant in decades now in operation, the stage is set for significant growth.

      Carbon capture and sequestration was the subject of a panel led by David Babson, the executive director of MIT’s Climate Grand Challenges program. MIT professors Betar Gallant and Kripa Varanasi and industry representatives Elisabeth Birkeland from Equinor and Luc Huyse from Chevron Technology Ventures described significant progress in various approaches to recovering carbon dioxide from power plant emissions, from the air, and from the ocean, and converting it into fuels, construction materials, or other valuable commodities.

      Some panel discussions also addressed the financial and policy side of the climate issue. A panel on geopolitical implications of the energy transition was moderated by MITEI Deputy Director of Policy Christopher Knittel, who said “energy has always been synonymous with geopolitics.” He said that as concerns shift from where to find the oil and gas to where is the cobalt and nickel and other elements that will be needed, “not only are we worried about where the deposits of natural resources are, but we’re going to be more and more worried about how governments are incentivizing the transition” to developing this new mix of natural resources. Panelist Suzanne Berger, an Institute professor, said “we’re now at a moment of unique openness and opportunity for creating a new American production system,” one that is much more efficient and less carbon-producing.

      One panel dealt with the investor’s perspective on the possibilities and pitfalls of emerging energy technologies. Moderator Jacqueline Pless, an assistant professor in MIT Sloan, said “there’s a lot of momentum now in this space. It’s a really ripe time for investing,” but the risks are real. “Tons of investment is needed in some very big and uncertain technologies.”

      The role that large, established companies can play in leading a transition to cleaner energy was addressed by another panel. Moderator J.J. Laukatis, MITEI’s director of member services, said that “the scale of this transformation is massive, and it will also be very different from anything we’ve seen in the past. We’re going to have to scale up complex new technologies and systems across the board, from hydrogen to EVs to the electrical grid, at rates we haven’t done before.” And doing so will require a concerted effort that includes industry as well as government and academia. More

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      3 Questions: What should scientists and the public know about nuclear waste?

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      Many researchers see an expansion of nuclear power, which produces no greenhouse gas emissions from its power generation, as an essential component of strategies to combat global climate change. Yet there is still strong resistance to such expansion, and much of that is based on the issue of how to safely dispose of the resulting radioactive waste material. MIT recently convened a workshop to help nuclear engineers, policymakers, and academics learn about approaches to communicating accurate information about the management of nuclear waste to students and the public, in hopes of allaying fears and encouraging support for the development of new, safer nuclear power plants around the world.

      Organized by Haruko Wainwright, an MIT assistant professor of nuclear science and engineering and of civil and environmental engineering, the workshop included professors, researchers, industry representatives, and government officials, and was designed to emphasize the multidisciplinary nature of the issue. MIT News asked Wainwright to describe the workshop and its conclusions, which she reported on in a paper just published in the Journal of Environmental Radioactivity.

      Q: What was the main objective of the this workshop?

      A: There is a growing concern that, in spite of much excitement about new nuclear reactor deployment and nuclear energy for tackling climate change, relatively less attention is being paid to the thorny question of long-term management of the spent fuel (waste) from these reactors. The government and industry have embraced consent-based siting approaches — that is, finding sites to store and dispose nuclear waste through broad community participation with equity and environmental justice considered. However, many of us in academia feel that those in the industry are missing key facts to communicate to the public.

      Understanding and managing nuclear waste requires a multidisciplinary expertise in nuclear, civil, and chemical engineering as well as environmental and earth sciences. For example, the amount of waste per se, which is always very small for nuclear systems, is not the only factor determining the environmental impacts because some radionuclides in the waste are vastly more mobile than others, and thus can spread farther and more quickly. Nuclear engineers, environmental scientists, and others need to work together to predict the environmental impacts of radionuclides in the waste generated by the new reactors, and to develop waste isolation strategies for an extended time.

      We organized this workshop to ensure this collaborative approach is mastered from the start. A second objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste and shaping a more broadly educated group of nuclear and general engineers.

      Q: What kinds of innovative teaching practices were discussed and recommended, and are there examples of these practices in action?

       A: Some participants teach project-based or simulation-based courses of real-world situations. For example, students are divided into several groups representing various stakeholders — such as the public, policymakers, scientists, and governments — and discuss the potential siting of a nuclear waste repository in a community. Such a course helps the students to consider the perspectives of different groups, understand a plurality of points of view, and learn how to communicate their ideas and concerns effectively. Other courses may ask students to synthesize key technical facts and numbers, and to develop a Congressional testimony statement or an opinion article for newspapers. 

      Q: What are some of the biggest misconceptions people have about nuclear waste, and how do you think these misconceptions can be addressed?

      A: The workshop participants agreed that the broader and life-cycle perspectives are important. Within the nuclear energy life cycle, for example, people focus disproportionally on high-level radioactive waste or spent fuel, which has been highly regulated and well managed. Nuclear systems also produce secondary waste, including low-level waste and uranium mining waste, which gets less attention.

      The participants also believe that the nuclear industry has been exemplary in leading the environmental and waste isolation science and technologies. Nuclear waste disposal strategies were developed in the 1950s, much earlier than other hazardous waste which began to receive serious regulation only in the 1970s. In addition, current nuclear waste disposal practices consider the compliance periods of isolation for thousands of years, while other hazardous waste disposal is not required to consider beyond 30 years, although some waste has an essentially infinite longevity, for example, mercury or lead. Finally, there is relatively unregulated waste — such as CO2 from fossil energy, agricultural effluents and other sources — that is released freely into the biosphere and is already impacting our environment. Yet, many people remain more concerned about the relatively well-regulated nuclear waste than about all these unregulated sources.

      Interestingly, many engineers — even nuclear engineers — do not know these facts. We believe that we need to teach students not just cutting-edge technologies, but also broader perspectives, including the history of industries and regulations, as well as environmental science.

      At the same time, we need to move the nuclear community to think more holistically about waste and its environmental impacts from the early stages of design of nuclear systems. We should design new reactors from the “waste up.”  We believe that the nuclear industry should continue to lead waste-management technologies and strategies, and also encourage other industries to adopt lifecycle approaches about their own waste to improve the overall sustainability. More

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      MIT design would harness 40 percent of the sun’s heat to produce clean hydrogen fuel

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      MIT engineers aim to produce totally green, carbon-free hydrogen fuel with a new, train-like system of reactors that is driven solely by the sun.

      In a study appearing today in Solar Energy Journal, the engineers lay out the conceptual design for a system that can efficiently produce “solar thermochemical hydrogen.” The system harnesses the sun’s heat to directly split water and generate hydrogen — a clean fuel that can power long-distance trucks, ships, and planes, while in the process emitting no greenhouse gas emissions.

      Today, hydrogen is largely produced through processes that involve natural gas and other fossil fuels, making the otherwise green fuel more of a “grey” energy source when considered from the start of its production to its end use. In contrast, solar thermochemical hydrogen, or STCH, offers a totally emissions-free alternative, as it relies entirely on renewable solar energy to drive hydrogen production. But so far, existing STCH designs have limited efficiency: Only about 7 percent of incoming sunlight is used to make hydrogen. The results so far have been low-yield and high-cost.

      In a big step toward realizing solar-made fuels, the MIT team estimates its new design could harness up to 40 percent of the sun’s heat to generate that much more hydrogen. The increase in efficiency could drive down the system’s overall cost, making STCH a potentially scalable, affordable option to help decarbonize the transportation industry.

      “We’re thinking of hydrogen as the fuel of the future, and there’s a need to generate it cheaply and at scale,” says the study’s lead author, Ahmed Ghoniem, the Ronald C. Crane Professor of Mechanical Engineering at MIT. “We’re trying to achieve the Department of Energy’s goal, which is to make green hydrogen by 2030, at $1 per kilogram. To improve the economics, we have to improve the efficiency and make sure most of the solar energy we collect is used in the production of hydrogen.”

      Ghoniem’s study co-authors are Aniket Patankar, first author and MIT postdoc; Harry Tuller, MIT professor of materials science and engineering; Xiao-Yu Wu of the University of Waterloo; and Wonjae Choi at Ewha Womans University in South Korea.

      Solar stations

      Similar to other proposed designs, the MIT system would be paired with an existing source of solar heat, such as a concentrated solar plant (CSP) — a circular array of hundreds of mirrors that collect and reflect sunlight to a central receiving tower. An STCH system then absorbs the receiver’s heat and directs it to split water and produce hydrogen. This process is very different from electrolysis, which uses electricity instead of heat to split water.

      At the heart of a conceptual STCH system is a two-step thermochemical reaction. In the first step, water in the form of steam is exposed to a metal. This causes the metal to grab oxygen from steam, leaving hydrogen behind. This metal “oxidation” is similar to the rusting of iron in the presence of water, but it occurs much faster. Once hydrogen is separated, the oxidized (or rusted) metal is reheated in a vacuum, which acts to reverse the rusting process and regenerate the metal. With the oxygen removed, the metal can be cooled and exposed to steam again to produce more hydrogen. This process can be repeated hundreds of times.

      The MIT system is designed to optimize this process. The system as a whole resembles a train of box-shaped reactors running on a circular track. In practice, this track would be set around a solar thermal source, such as a CSP tower. Each reactor in the train would house the metal that undergoes the redox, or reversible rusting, process.

      Each reactor would first pass through a hot station, where it would be exposed to the sun’s heat at temperatures of up to 1,500 degrees Celsius. This extreme heat would effectively pull oxygen out of a reactor’s metal. That metal would then be in a “reduced” state — ready to grab oxygen from steam. For this to happen, the reactor would move to a cooler station at temperatures around 1,000 C, where it would be exposed to steam to produce hydrogen.

      Rust and rails

      Other similar STCH concepts have run up against a common obstacle: what to do with the heat released by the reduced reactor as it is cooled. Without recovering and reusing this heat, the system’s efficiency is too low to be practical.

      A second challenge has to do with creating an energy-efficient vacuum where metal can de-rust. Some prototypes generate a vacuum using mechanical pumps, though the pumps are too energy-intensive and costly for large-scale hydrogen production.

      To address these challenges, the MIT design incorporates several energy-saving workarounds. To recover most of the heat that would otherwise escape from the system, reactors on opposite sides of the circular track are allowed to exchange heat through thermal radiation; hot reactors get cooled while cool reactors get heated. This keeps the heat within the system. The researchers also added a second set of reactors that would circle around the first train, moving in the opposite direction. This outer train of reactors would operate at generally cooler temperatures and would be used to evacuate oxygen from the hotter inner train, without the need for energy-consuming mechanical pumps.

      These outer reactors would carry a second type of metal that can also easily oxidize. As they circle around, the outer reactors would absorb oxygen from the inner reactors, effectively de-rusting the original metal, without having to use energy-intensive vacuum pumps. Both reactor trains would  run continuously and would enerate separate streams of pure hydrogen and oxygen.

      The researchers carried out detailed simulations of the conceptual design, and found that it would significantly boost the efficiency of solar thermochemical hydrogen production, from 7 percent, as previous designs have demonstrated, to 40 percent.

      “We have to think of every bit of energy in the system, and how to use it, to minimize the cost,” Ghoniem says. “And with this design, we found that everything can be powered by heat coming from the sun. It is able to use 40 percent of the sun’s heat to produce hydrogen.”

      “If this can be realized, it could drastically change our energy future — namely, enabling hydrogen production, 24/7,” says Christopher Muhich, an assistant professor of chemical engineering at Arizona State University, who was not involved in the research. “The ability to make hydrogen is the linchpin to producing liquid fuels from sunlight.”

      In the next year, the team will be building a prototype of the system that they plan to test in concentrated solar power facilities at laboratories of the Department of Energy, which is currently funding the project.

      “When fully implemented, this system would be housed in a little building in the middle of a solar field,” Patankar explains. “Inside the building, there could be one or more trains each having about 50 reactors. And we think this could be a modular system, where you can add reactors to a conveyor belt, to scale up hydrogen production.”

      This work was supported by the Centers for Mechanical Engineering Research and Education at MIT and SUSTech. More

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      New tools are available to help reduce the energy that AI models devour

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      When searching for flights on Google, you may have noticed that each flight’s carbon-emission estimate is now presented next to its cost. It’s a way to inform customers about their environmental impact, and to let them factor this information into their decision-making.

      A similar kind of transparency doesn’t yet exist for the computing industry, despite its carbon emissions exceeding those of the entire airline industry. Escalating this energy demand are artificial intelligence models. Huge, popular models like ChatGPT signal a trend of large-scale artificial intelligence, boosting forecasts that predict data centers will draw up to 21 percent of the world’s electricity supply by 2030.

      The MIT Lincoln Laboratory Supercomputing Center (LLSC) is developing techniques to help data centers reel in energy use. Their techniques range from simple but effective changes, like power-capping hardware, to adopting novel tools that can stop AI training early on. Crucially, they have found that these techniques have a minimal impact on model performance.

      In the wider picture, their work is mobilizing green-computing research and promoting a culture of transparency. “Energy-aware computing is not really a research area, because everyone’s been holding on to their data,” says Vijay Gadepally, senior staff in the LLSC who leads energy-aware research efforts. “Somebody has to start, and we’re hoping others will follow.”

      Curbing power and cooling down

      Like many data centers, the LLSC has seen a significant uptick in the number of AI jobs running on its hardware. Noticing an increase in energy usage, computer scientists at the LLSC were curious about ways to run jobs more efficiently. Green computing is a principle of the center, which is powered entirely by carbon-free energy.

      Training an AI model — the process by which it learns patterns from huge datasets — requires using graphics processing units (GPUs), which are power-hungry hardware. As one example, the GPUs that trained GPT-3 (the precursor to ChatGPT) are estimated to have consumed 1,300 megawatt-hours of electricity, roughly equal to that used by 1,450 average U.S. households per month.

      While most people seek out GPUs because of their computational power, manufacturers offer ways to limit the amount of power a GPU is allowed to draw. “We studied the effects of capping power and found that we could reduce energy consumption by about 12 percent to 15 percent, depending on the model,” Siddharth Samsi, a researcher within the LLSC, says.

      The trade-off for capping power is increasing task time — GPUs will take about 3 percent longer to complete a task, an increase Gadepally says is “barely noticeable” considering that models are often trained over days or even months. In one of their experiments in which they trained the popular BERT language model, limiting GPU power to 150 watts saw a two-hour increase in training time (from 80 to 82 hours) but saved the equivalent of a U.S. household’s week of energy.

      The team then built software that plugs this power-capping capability into the widely used scheduler system, Slurm. The software lets data center owners set limits across their system or on a job-by-job basis.

      “We can deploy this intervention today, and we’ve done so across all our systems,” Gadepally says.

      Side benefits have arisen, too. Since putting power constraints in place, the GPUs on LLSC supercomputers have been running about 30 degrees Fahrenheit cooler and at a more consistent temperature, reducing stress on the cooling system. Running the hardware cooler can potentially also increase reliability and service lifetime. They can now consider delaying the purchase of new hardware — reducing the center’s “embodied carbon,” or the emissions created through the manufacturing of equipment — until the efficiencies gained by using new hardware offset this aspect of the carbon footprint. They’re also finding ways to cut down on cooling needs by strategically scheduling jobs to run at night and during the winter months.

      “Data centers can use these easy-to-implement approaches today to increase efficiencies, without requiring modifications to code or infrastructure,” Gadepally says.

      Taking this holistic look at a data center’s operations to find opportunities to cut down can be time-intensive. To make this process easier for others, the team — in collaboration with Professor Devesh Tiwari and Baolin Li at Northeastern University — recently developed and published a comprehensive framework for analyzing the carbon footprint of high-performance computing systems. System practitioners can use this analysis framework to gain a better understanding of how sustainable their current system is and consider changes for next-generation systems.  

      Adjusting how models are trained and used

      On top of making adjustments to data center operations, the team is devising ways to make AI-model development more efficient.

      When training models, AI developers often focus on improving accuracy, and they build upon previous models as a starting point. To achieve the desired output, they have to figure out what parameters to use, and getting it right can take testing thousands of configurations. This process, called hyperparameter optimization, is one area LLSC researchers have found ripe for cutting down energy waste. 

      “We’ve developed a model that basically looks at the rate at which a given configuration is learning,” Gadepally says. Given that rate, their model predicts the likely performance. Underperforming models are stopped early. “We can give you a very accurate estimate early on that the best model will be in this top 10 of 100 models running,” he says.

      In their studies, this early stopping led to dramatic savings: an 80 percent reduction in the energy used for model training. They’ve applied this technique to models developed for computer vision, natural language processing, and material design applications.

      “In my opinion, this technique has the biggest potential for advancing the way AI models are trained,” Gadepally says.

      Training is just one part of an AI model’s emissions. The largest contributor to emissions over time is model inference, or the process of running the model live, like when a user chats with ChatGPT. To respond quickly, these models use redundant hardware, running all the time, waiting for a user to ask a question.

      One way to improve inference efficiency is to use the most appropriate hardware. Also with Northeastern University, the team created an optimizer that matches a model with the most carbon-efficient mix of hardware, such as high-power GPUs for the computationally intense parts of inference and low-power central processing units (CPUs) for the less-demanding aspects. This work recently won the best paper award at the International ACM Symposium on High-Performance Parallel and Distributed Computing.

      Using this optimizer can decrease energy use by 10-20 percent while still meeting the same “quality-of-service target” (how quickly the model can respond).

      This tool is especially helpful for cloud customers, who lease systems from data centers and must select hardware from among thousands of options. “Most customers overestimate what they need; they choose over-capable hardware just because they don’t know any better,” Gadepally says.

      Growing green-computing awareness

      The energy saved by implementing these interventions also reduces the associated costs of developing AI, often by a one-to-one ratio. In fact, cost is usually used as a proxy for energy consumption. Given these savings, why aren’t more data centers investing in green techniques?

      “I think it’s a bit of an incentive-misalignment problem,” Samsi says. “There’s been such a race to build bigger and better models that almost every secondary consideration has been put aside.”

      They point out that while some data centers buy renewable-energy credits, these renewables aren’t enough to cover the growing energy demands. The majority of electricity powering data centers comes from fossil fuels, and water used for cooling is contributing to stressed watersheds. 

      Hesitancy may also exist because systematic studies on energy-saving techniques haven’t been conducted. That’s why the team has been pushing their research in peer-reviewed venues in addition to open-source repositories. Some big industry players, like Google DeepMind, have applied machine learning to increase data center efficiency but have not made their work available for others to deploy or replicate. 

      Top AI conferences are now pushing for ethics statements that consider how AI could be misused. The team sees the climate aspect as an AI ethics topic that has not yet been given much attention, but this also appears to be slowly changing. Some researchers are now disclosing the carbon footprint of training the latest models, and industry is showing a shift in energy transparency too, as in this recent report from Meta AI.

      They also acknowledge that transparency is difficult without tools that can show AI developers their consumption. Reporting is on the LLSC roadmap for this year. They want to be able to show every LLSC user, for every job, how much energy they consume and how this amount compares to others, similar to home energy reports.

      Part of this effort requires working more closely with hardware manufacturers to make getting these data off hardware easier and more accurate. If manufacturers can standardize the way the data are read out, then energy-saving and reporting tools can be applied across different hardware platforms. A collaboration is underway between the LLSC researchers and Intel to work on this very problem.

      Even for AI developers who are aware of the intense energy needs of AI, they can’t do much on their own to curb this energy use. The LLSC team wants to help other data centers apply these interventions and provide users with energy-aware options. Their first partnership is with the U.S. Air Force, a sponsor of this research, which operates thousands of data centers. Applying these techniques can make a significant dent in their energy consumption and cost.

      “We’re putting control into the hands of AI developers who want to lessen their footprint,” Gadepally says. “Do I really need to gratuitously train unpromising models? Am I willing to run my GPUs slower to save energy? To our knowledge, no other supercomputing center is letting you consider these options. Using our tools, today, you get to decide.”

      Visit this webpage to see the group’s publications related to energy-aware computing and findings described in this article. More

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      Tracking US progress on the path to a decarbonized economy

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      Investments in new technologies and infrastucture that help reduce greenhouse gas emissions — everything from electric vehicles to heat pumps — are growing rapidly in the United States. Now, a new database enables these investments to be comprehensively monitored in real-time, thereby helping to assess the efficacy of policies designed to spur clean investments and address climate change.

      The Clean Investment Monitor (CIM), developed by a team at MIT’s Center for Energy and Environmental Policy Research (CEEPR) led by Institute Innovation Fellow Brian Deese and in collaboration with the Rhodium Group, an independent research firm, provides a timely and methodologically consistent tracking of all announced public and private investments in the manufacture and deployment of clean technologies and infrastructure in the U.S. The CIM offers a means of assessing the country’s progress in transitioning to a cleaner economy and reducing greenhouse gas emissions.

      In the year from July 1, 2022, to June 30, 2023, data from the CIM show, clean investments nationwide totaled $213 billion. To put that figure in perspective, 18 states in the U.S. have GDPs each lower than $213 billion.

      “As clean technology becomes a larger and larger sector in the United States, its growth will have far-reaching implications — for our economy, for our leadership in innovation, and for reducing our greenhouse gas emissions,” says Deese, who served as the director of the White House National Economic Council from January 2021 to February 2023. “The Clean Investment Monitor is a tool designed to help us understand and assess this growth in a real-time, comprehensive way. Our hope is that the CIM will enhance research and improve public policies designed to accelerate the clean energy transition.”

      Launched on Sept. 13, the CIM shows that the $213 billion invested over the last year reflects a 37 percent increase from the $155 billion invested in the previous 12-month period. According to CIM data, the fastest growth has been in the manufacturing sector, where investment grew 125 percent year-on-year, particularly in electric vehicle and solar manufacturing.

      Beyond manufacturing, the CIM also provides data on investment in clean energy production, such as solar, wind, and nuclear; industrial decarbonization, such as sustainable aviation fuels; and retail investments by households and businesses in technologies like heat pumps and zero-emission vehicles. The CIM’s data goes back to 2018, providing a baseline before the passage of the legislation in 2021 and 2022.

      “We’re really excited to bring MIT’s analytical rigor to bear to help develop the Clean Investment Monitor,” says Christopher Knittel, the George P. Shultz Professor of Energy Economics at the MIT Sloan School of Management and CEEPR’s faculty director. “Bolstered by Brian’s keen understanding of the policy world, this tool is poised to become the go-to reference for anyone looking to understand clean investment flows and what drives them.”

      In 2021 and 2022, the U.S. federal government enacted a series of new laws that together aimed to catalyze the largest-ever national investment in clean energy technologies and related infrastructure. The Clean Investment Monitor can also be used to track how well the legislation is living up to expectations.

      The three pieces of federal legislation — the Infrastructure Investment and Jobs Act, enacted in 2021, and the Inflation Reduction Act (IRA) and the CHIPS and Science Act, both enacted in 2022 — provide grants, loans, loan guarantees, and tax incentives to spur investments in technologies that reduce greenhouse gas emissions.

      The effectiveness of the legislation in hastening the U.S. transition to a clean economy will be crucial in determining whether the country reaches its goal of reducing greenhouse gas emissions by 50 percent to 52 percent below 2005 levels in 2030. An analysis earlier this year estimated that the IRA will lead to a 43 percent to 48 percent decline in economywide emissions below 2005 levels by 2035, compared with 27 percent to 35 percent in a reference scenario without the law’s provisions, helping bring the U.S. goal closer in reach.

      The Clean Investment Monitor is available at cleaninvestmentmonitor.org. More

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      in Environment

      Desirée Plata appointed co-director of the MIT Climate and Sustainability Consortium

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      Desirée Plata, associate professor of civil and environmental engineering at MIT, has been named co-director of the MIT Climate and Sustainability Consortium (MCSC), effective Sept. 1. Plata will serve on the MCSC’s leadership team alongside Anantha P. Chandrakasan, dean of the MIT School of Engineering, the Vannevar Bush Professor of Electrical Engineering and Computer Science, and MCSC chair; Elsa Olivetti, the Jerry McAfee Professor in Engineering, a professor of materials science and engineering, and associate dean of engineering, and MCSC co-director; and Jeremy Gregory, MCSC executive director.Plata succeeds Jeffrey Grossman, the Morton and Claire Goulder and Family Professor in Environmental Systems, who has served as co-director since the MCSC’s launch in January 2021. Grossman, who played a central role in the ideation and launch of the MCSC, will continue his work with the MCSC as strategic advisor.“Professor Plata is a valued member of the MIT community. She brings a deep understanding of and commitment to climate and sustainability initiatives at MIT, as well as extensive experience working with industry, to her new role within the MCSC,” says Chandrakasan. The MIT Climate and Sustainability Consortium is an academia-industry collaboration working to accelerate implementation of large-scale solutions across sectors of the global economy. It aims to lay the groundwork for one critical aspect of MIT’s continued and intensified commitment to climate: helping large companies usher in, adapt to, and prosper in a decarbonized world.“We are thrilled to bring Professor Plata’s knowledge, vision, and passion to our leadership team,” says Olivetti. “Her experience developing sustainable technologies that have the potential to improve the environment and reduce the impacts of climate change will help move our work forward in meaningful ways. We have valued Professor Plata’s contributions to the consortium and look forward to continuing our work with her.”Plata played a pivotal role in the creation and launch of the MCSC’s Climate and Sustainability Scholars Program and its yearlong course for MIT rising juniors and seniors — an effort that she and Olivetti were recently recognized for with the Class of 1960 Innovation in Education Fellowship. She has also been a member of the MCSC’s Faculty Steering Committee since the consortium’s launch, helping to shape and guide its vision and work.Plata is a dedicated researcher, educator, and mentor. A member of MIT’s faculty since 2018, Plata and her team at the Plata Lab are helping to guide industry to more environmentally sustainable practices and develop new ways to protect the health of the planet — using chemistry to understand the impact that industrial materials and processes have on the environment. By coupling devices that simulate industrial systems with computation, she helps industry develop more environmentally friendly practices.To celebrate her work in the lab, classroom, and community, Plata has received many awards and honors. In 2020, she won MIT’s prestigious Harold E. Edgerton Faculty Achievement Award, recognizing her innovative approach to environmentally sustainable industrial practices, her inspirational teaching and mentoring, and her service to MIT and the community. She is a two-time National Academy of Sciences Kavli Frontiers of Science Fellow, a two-time National Academy of Engineers Frontiers of Engineering Fellow, and a Caltech Young Investigator Sustainability Fellow. She has also won the ACS C. Ellen Gonter Environmental Chemistry Award, an NSF CAREER award, and the 2016 Odebrecht Award for Sustainable Development.Beyond her work in the academic space, Plata is co-founder of two climate- and energy-related startups: Nth Cycle and Moxair, illustrating her commitment to translating academic innovations for real-world implementation — a core value of the MCSC.Plata received her bachelor’s degree from Union College and her PhD from the MIT and Woods Hole Oceanographic Institution (MIT-WHOI) joint program in oceanography/applied ocean science and engineering. After receiving her doctorate, Plata held positions at Mount Holyoke College, Duke University, and Yale University.  More

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      in Energy

      Jackson Jewett wants to design buildings that use less concrete

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      After three years leading biking tours through U.S. National Parks, Jackson Jewett decided it was time for a change.

      “It was a lot of fun, but I realized I missed buildings,” says Jewett. “I really wanted to be a part of that industry, learn more about it, and reconnect with my roots in the built environment.”

      Jewett grew up in California in what he describes as a “very creative household.”

      “I remember making very elaborate Halloween costumes with my parents, making fun dioramas for school projects, and building forts in the backyard, that kind of thing,” Jewett explains.

      Both of his parents have backgrounds in design; his mother studied art in college and his father is a practicing architect. From a young age, Jewett was interested in following in his father’s footsteps. But when he arrived at the University of California at Berkeley in the midst of the 2009 housing crash, it didn’t seem like the right time. Jewett graduated with a degree in cognitive science and a minor in history of architecture. And even as he led tours through Yellowstone, the Grand Canyon, and other parks, buildings were in the back of his mind.

      It wasn’t just the built environment that Jewett was missing. He also longed for the rigor and structure of an academic environment.

      Jewett arrived at MIT in 2017, initially only planning on completing the master’s program in civil and environmental engineering. It was then that he first met Josephine Carstensen, a newly hired lecturer in the department. Jewett was interested in Carstensen’s work on “topology optimization,” which uses algorithms to design structures that can achieve their performance requirements while using only a limited amount of material. He was particularly interested in applying this approach to concrete design, and he collaborated with Carstensen to help demonstrate its viability.

      After earning his master’s, Jewett spent a year and a half as a structural engineer in New York City. But when Carstensen was hired as a professor, she reached out to Jewett about joining her lab as a PhD student. He was ready for another change.

      Now in the third year of his PhD program, Jewett’s dissertation work builds upon his master’s thesis to further refine algorithms that can design building-scale concrete structures that use less material, which would help lower carbon emissions from the construction industry. It is estimated that the concrete industry alone is responsible for 8 percent of global carbon emissions, so any efforts to reduce that number could help in the fight against climate change.

      Implementing new ideas

      Topology optimization is a small field, with the bulk of the prior work being computational without any experimental verification. The work Jewett completed for his master’s thesis was just the start of a long learning process.

      “I do feel like I’m just getting to the part where I can start implementing my own ideas without as much support as I’ve needed in the past,” says Jewett. “In the last couple of months, I’ve been working on a reinforced concrete optimization algorithm that I hope will be the cornerstone of my thesis.”

      The process of fine-tuning a generative algorithm is slow going, particularly when tackling a multifaceted problem.

      “It can take days or usually weeks to take a step toward making it work as an entire integrated system,” says Jewett. “The days when that breakthrough happens and I can see the algorithm converging on a solution that makes sense — those are really exciting moments.”

      By harnessing computational power, Jewett is searching for materially efficient components that can be used to make up structures such as bridges or buildings. These are other constraints to consider as well, particularly ensuring that the cost of manufacturing isn’t too high. Having worked in the industry before starting the PhD program, Jewett has an eye toward doing work that can be feasibly implemented.

      Inspiring others

      When Jewett first visited MIT campus, he was drawn in by the collaborative environment of the institute and the students’ drive to learn. Now, he’s a part of that process as a teaching assistant and a supervisor in the Undergraduate Research Opportunities Program.  

      Working as a teaching assistant isn’t a requirement for Jewett’s program, but it’s been one of his favorite parts of his time at MIT.

      “The MIT undergrads are so gifted and just constantly impress me,” says Jewett. “Being able to teach, especially in the context of what MIT values is a lot of fun. And I learn, too. My coding practices have gotten so much better since working with undergrads here.”

      Jewett’s experiences have inspired him to pursue a career in academia after the completion of his program, which he expects to complete in the spring of 2025. But he’s making sure to take care of himself along the way. He still finds time to plan cycling trips with his friends and has gotten into running ever since moving to Boston. So far, he’s completed two marathons.

      “It’s so inspiring to be in a place where so many good ideas are just bouncing back and forth all over campus,” says Jewett. “And on most days, I remember that and it inspires me. But it’s also the case that academics is hard, PhD programs are hard, and MIT — there’s pressure being here, and sometimes that pressure can feel like it’s working against you.”

      Jewett is grateful for the mental health resources that MIT provides students. While he says it can be imperfect, it’s been a crucial part of his journey.

      “My PhD thesis will be done in 2025, but the work won’t be done. The time horizon of when these things need to be implemented is relatively short if we want to make an impact before global temperatures have already risen too high. My PhD research will be developing a framework for how that could be done with concrete construction, but I’d like to keep thinking about other materials and construction methods even after this project is finished.” More

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      in Environment

      Harnessing hydrogen’s potential to address long-haul trucking emissions

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      The transportation of goods forms the basis of today’s globally distributed supply chains, and long-haul trucking is a central and critical link in this complex system. To meet climate goals around the world, it is necessary to develop decarbonized solutions to replace diesel powertrains, but given trucking’s indispensable and vast role, these solutions must be both economically viable and practical to implement. While hydrogen-based options, as an alternative to diesel, have the potential to become a promising decarbonization strategy, hydrogen has significant limitations when it comes to delivery and refueling.These roadblocks, combined with hydrogen’s compelling decarbonization potential, are what motivated a team of MIT researchers led by William H. Green, the Hoyt Hottel Professor in Chemical Engineering, to explore a cost-effective way to transport and store hydrogen using liquid organic hydrogen carriers (LOHCs). The team is developing a disruptive technology that allows LOHCs to not only deliver the hydrogen to the trucks, but also store the hydrogen onboard.Their findings were recently published in Energy and Fuels, a peer-reviewed journal of the American Chemical Society, in a paper titled “Perspective on Decarbonizing Long-Haul Trucks Using Onboard Dehydrogenation of Liquid Organic Hydrogen Carriers.” The MIT team is led by Green, and includes graduate students Sayandeep Biswas and Kariana Moreno Sader. Their research is supported by the MIT Climate and Sustainability Consortium (MCSC) through its Seed Awards program and MathWorks, and ties into the work within the MCSC’s Tough Transportation Modes focus area.An “onboard” approachCurrently, LOHCs, which work within existing retail fuel distribution infrastructure, are used to deliver hydrogen gas to refueling stations, where it is then compressed and delivered onto trucks equipped with hydrogen fuel cell or combustion engines.“This current approach incurs significant energy loss due to endothermic hydrogen release and compression at the retail station” says Green. “To address this, our work is exploring a more efficient application, with LOHC-powered trucks featuring onboard dehydrogenation.”To implement such a design, the team aims to modify the truck’s powertrain (the system inside a vehicle that produces the energy to propel it forward) to allow onboard hydrogen release from the LOHCs, using waste heat from the engine exhaust to power the “dehydrogenation” process. 

      Proposed process flow diagram for onboard dehydrogenation. Component sizes are not to scale and have been enlarged for illustrative purposes.

      Image courtesy of the Green Group.

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      The dehydrogenation process happens within a high-temperature reactor, which continually receives hydrogen-rich LOHCs from the fuel storage tank. Hydrogen released from the reactor is fed to the engine, after passing through a separator to remove any lingering LOHC. On its way to the engine, some of the hydrogen gets diverted to a burner to heat the reactor, which helps to augment the reactor heating provided by the engine exhaust gases.Acknowledging and addressing hydrogen’s drawbacksThe team’s paper underscores that current uses of hydrogen, including LOHC systems, to decarbonize the trucking sector have drawbacks. Regardless of technical improvements, these existing options remain prohibitively expensive due to the high cost of retail hydrogen delivery.“We present an alternative option that addresses a lot of the challenges and seems to be a viable way in which hydrogen can be used in this transportation context,” says Biswas, who was recently elected to the MIT Martin Family Society of Fellows for Sustainability for his work in this area. “Hydrogen, when used through LOHCs, has clear benefits for long-hauling, such as scalability and fast refueling time. There is also an enormous potential to improve delivery and refueling to further reduce cost, and our system is working to do that.”“Utilizing hydrogen is an option that is globally accessible, and could be extended to countries like the one where I am from,” says Moreno Sader, who is originally from Colombia. “Since it synergizes with existing infrastructure, large upfront investments are not necessary. The global applicability is huge.”Moreno Sader is a MathWorks Fellow, and, along with the rest of the team, has been using MATLAB tools to develop models and simulations for this work.Different sectors coming togetherDecarbonizing transportation modes, including long-haul trucking, requires expertise and perspectives from different industries — an approach that resonates with the MCSC’s mission.The team’s groundbreaking research into LOHC-powered trucking is among several projects supported by the MCSC within its Tough Transportation Modes focus area, led by postdoc Impact Fellow Danika MacDonell. The MCSC-supported projects were chosen to tackle a complementary set of societally important and industry-relevant challenges to decarbonizing heavy-duty transportation, which span a range of sectors and solution pathways. Other projects focus, for example, on logistics optimization for electrified trucking fleets, or air quality and climate impacts of ammonia-powered shipping.The MCSC works to support and amplify the impact of these projects by engaging the research teams with industry partners from a variety of sectors. In addition, the MCSC pursues a collective multisectoral approach to decarbonizing transportation by facilitating shared learning across the different projects through regular cross-team discussion.The research led by Green celebrates this cross-sector theme by integrating industry-leading computing tools provided by MathWorks with cutting-edge developments in chemical engineering, as well as industry-leading commercial LOHC reactor demonstrations, to build a compelling vision for cost-effective LOHC-powered trucking.The review and research conducted in the Energy and Fuels article lays the groundwork for further investigations into LOHC-powered truck design. The development of such a vehicle — with a power-dense, efficient, and robust onboard hydrogen release system — requires dedicated investigations and further optimization of core components geared specifically toward the trucking application. More