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    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 Environment

      AI stirs up the recipe for concrete in MIT study

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      For weeks, the whiteboard in the lab was crowded with scribbles, diagrams, and chemical formulas. A research team across the Olivetti Group and the MIT Concrete Sustainability Hub (CSHub) was working intensely on a key problem: How can we reduce the amount of cement in concrete to save on costs and emissions? The question was certainly not new; materials like fly ash, a byproduct of coal production, and slag, a byproduct of steelmaking, have long been used to replace some of the cement in concrete mixes. However, the demand for these products is outpacing supply as industry looks to reduce its climate impacts by expanding their use, making the search for alternatives urgent. The challenge that the team discovered wasn’t a lack of candidates; the problem was that there were too many to sort through.On May 17, the team, led by postdoc Soroush Mahjoubi, published an open-access paper in Nature’s Communications Materials outlining their solution. “We realized that AI was the key to moving forward,” notes Mahjoubi. “There is so much data out there on potential materials — hundreds of thousands of pages of scientific literature. Sorting through them would have taken many lifetimes of work, by which time more materials would have been discovered!”With large language models, like the chatbots many of us use daily, the team built a machine-learning framework that evaluates and sorts candidate materials based on their physical and chemical properties. “First, there is hydraulic reactivity. The reason that concrete is strong is that cement — the ‘glue’ that holds it together — hardens when exposed to water. So, if we replace this glue, we need to make sure the substitute reacts similarly,” explains Mahjoubi. “Second, there is pozzolanicity. This is when a material reacts with calcium hydroxide, a byproduct created when cement meets water, to make the concrete harder and stronger over time.  We need to balance the hydraulic and pozzolanic materials in the mix so the concrete performs at its best.”Analyzing scientific literature and over 1 million rock samples, the team used the framework to sort candidate materials into 19 types, ranging from biomass to mining byproducts to demolished construction materials. Mahjoubi and his team found that suitable materials were available globally — and, more impressively, many could be incorporated into concrete mixes just by grinding them. This means it’s possible to extract emissions and cost savings without much additional processing. “Some of the most interesting materials that could replace a portion of cement are ceramics,” notes Mahjoubi. “Old tiles, bricks, pottery — all these materials may have high reactivity. That’s something we’ve observed in ancient Roman concrete, where ceramics were added to help waterproof structures. I’ve had many interesting conversations on this with Professor Admir Masic, who leads a lot of the ancient concrete studies here at MIT.”The potential of everyday materials like ceramics and industrial materials like mine tailings is an example of how materials like concrete can help enable a circular economy. By identifying and repurposing materials that would otherwise end up in landfills, researchers and industry can help to give these materials a second life as part of our buildings and infrastructure.Looking ahead, the research team is planning to upgrade the framework to be capable of assessing even more materials, while experimentally validating some of the best candidates. “AI tools have gotten this research far in a short time, and we are excited to see how the latest developments in large language models enable the next steps,” says Professor Elsa Olivetti, senior author on the work and member of the MIT Department of Materials Science and Engineering. She serves as an MIT Climate Project mission director, a CSHub principal investigator, and the leader of the Olivetti Group.“Concrete is the backbone of the built environment,” says Randolph Kirchain, co-author and CSHub director. “By applying data science and AI tools to material design, we hope to support industry efforts to build more sustainably, without compromising on strength, safety, or durability.In addition to Mahjoubi, Olivetti, and Kirchain, co-authors on the work include MIT postdoc Vineeth Venugopal, Ipek Bensu Manav SM ’21, PhD ’24; and CSHub Deputy Director Hessam AzariJafari. More

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      in Energy

      Smart carbon dioxide removal yields economic and environmental benefits

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      Last year the Earth exceeded 1.5 degrees Celsius of warming above preindustrial times, a threshold beyond which wildfires, droughts, floods, and other climate impacts are expected to escalate in frequency, intensity, and lethality. To cap global warming at 1.5 C and avert that scenario, the nearly 200 signatory nations of the Paris Agreement on climate change will need to not only dramatically lower their greenhouse gas emissions, but also take measures to remove carbon dioxide (CO2) from the atmosphere and durably store it at or below the Earth’s surface.Past analyses of the climate mitigation potential, costs, benefits, and drawbacks of different carbon dioxide removal (CDR) options have focused primarily on three strategies: bioenergy with carbon capture and storage (BECCS), in which CO2-absorbing plant matter is converted into fuels or directly burned to generate energy, with some of the plant’s carbon content captured and then stored safely and permanently; afforestation/reforestation, in which CO2-absorbing trees are planted in large numbers; and direct air carbon capture and storage (DACCS), a technology that captures and separates CO2 directly from ambient air, and injects it into geological reservoirs or incorporates it into durable products. To provide a more comprehensive and actionable analysis of CDR, a new study by researchers at the MIT Center for Sustainability Science and Strategy (CS3) first expands the option set to include biochar (charcoal produced from plant matter and stored in soil) and enhanced weathering (EW) (spreading finely ground rock particles on land to accelerate storage of CO2 in soil and water). The study then evaluates portfolios of all five options — in isolation and in combination — to assess their capability to meet the 1.5 C goal, and their potential impacts on land, energy, and policy costs.The study appears in the journal Environmental Research Letters. Aided by their global multi-region, multi-sector Economic Projection and Policy Analysis (EPPA) model, the MIT CS3 researchers produce three key findings.First, the most cost-effective, low-impact strategy that policymakers can take to achieve global net-zero emissions — an essential step in meeting the 1.5 C goal — is to diversify their CDR portfolio, rather than rely on any single option. This approach minimizes overall cropland and energy consumption, and negative impacts such as increased food insecurity and decreased energy supplies.By diversifying across multiple CDR options, the highest CDR deployment of around 31.5 gigatons of CO2 per year is achieved in 2100, while also proving the most cost-effective net-zero strategy. The study identifies BECCS and biochar as most cost-competitive in removing CO2 from the atmosphere, followed by EW, with DACCS as uncompetitive due to high capital and energy requirements. While posing logistical and other challenges, biochar and EW have the potential to improve soil quality and productivity across 45 percent of all croplands by 2100.“Diversifying CDR portfolios is the most cost-effective net-zero strategy because it avoids relying on a single CDR option, thereby reducing and redistributing negative impacts on agriculture, forestry, and other land uses, as well as on the energy sector,” says Solene Chiquier, lead author of the study who was a CS3 postdoc during its preparation.The second finding: There is no optimal CDR portfolio that will work well at global and national levels. The ideal CDR portfolio for a particular region will depend on local technological, economic, and geophysical conditions. For example, afforestation and reforestation would be of great benefit in places like Brazil, Latin America, and Africa, by not only sequestering carbon in more acreage of protected forest but also helping to preserve planetary well-being and human health.“In designing a sustainable, cost-effective CDR portfolio, it is important to account for regional availability of agricultural, energy, and carbon-storage resources,” says Sergey Paltsev, CS3 deputy director, MIT Energy Initiative senior research scientist, and supervising co-author of the study. “Our study highlights the need for enhancing knowledge about local conditions that favor some CDR options over others.”Finally, the MIT CS3 researchers show that delaying large-scale deployment of CDR portfolios could be very costly, leading to considerably higher carbon prices across the globe — a development sure to deter the climate mitigation efforts needed to achieve the 1.5 C goal. They recommend near-term implementation of policy and financial incentives to help fast-track those efforts. More

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      in Energy

      The multifaceted challenge of powering AI

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      Artificial intelligence has become vital in business and financial dealings, medical care, technology development, research, and much more. Without realizing it, consumers rely on AI when they stream a video, do online banking, or perform an online search. Behind these capabilities are more than 10,000 data centers globally, each one a huge warehouse containing thousands of computer servers and other infrastructure for storing, managing, and processing data. There are now over 5,000 data centers in the United States, and new ones are being built every day — in the U.S. and worldwide. Often dozens are clustered together right near where people live, attracted by policies that provide tax breaks and other incentives, and by what looks like abundant electricity.And data centers do consume huge amounts of electricity. U.S. data centers consumed more than 4 percent of the country’s total electricity in 2023, and by 2030 that fraction could rise to 9 percent, according to the Electric Power Research Institute. A single large data center can consume as much electricity as 50,000 homes.The sudden need for so many data centers presents a massive challenge to the technology and energy industries, government policymakers, and everyday consumers. Research scientists and faculty members at the MIT Energy Initiative (MITEI) are exploring multiple facets of this problem — from sourcing power to grid improvement to analytical tools that increase efficiency, and more. Data centers have quickly become the energy issue of our day.Unexpected demand brings unexpected solutionsSeveral companies that use data centers to provide cloud computing and data management services are announcing some surprising steps to deliver all that electricity. Proposals include building their own small nuclear plants near their data centers and even restarting one of the undamaged nuclear reactors at Three Mile Island, which has been shuttered since 2019. (A different reactor at that plant partially melted down in 1979, causing the nation’s worst nuclear power accident.) Already the need to power AI is causing delays in the planned shutdown of some coal-fired power plants and raising prices for residential consumers. Meeting the needs of data centers is not only stressing power grids, but also setting back the transition to clean energy needed to stop climate change.There are many aspects to the data center problem from a power perspective. Here are some that MIT researchers are focusing on, and why they’re important.An unprecedented surge in the demand for electricity“In the past, computing was not a significant user of electricity,” says William H. Green, director of MITEI and the Hoyt C. Hottel Professor in the MIT Department of Chemical Engineering. “Electricity was used for running industrial processes and powering household devices such as air conditioners and lights, and more recently for powering heat pumps and charging electric cars. But now all of a sudden, electricity used for computing in general, and by data centers in particular, is becoming a gigantic new demand that no one anticipated.”Why the lack of foresight? Usually, demand for electric power increases by roughly half-a-percent per year, and utilities bring in new power generators and make other investments as needed to meet the expected new demand. But the data centers now coming online are creating unprecedented leaps in demand that operators didn’t see coming. In addition, the new demand is constant. It’s critical that a data center provides its services all day, every day. There can be no interruptions in processing large datasets, accessing stored data, and running the cooling equipment needed to keep all the packed-together computers churning away without overheating.Moreover, even if enough electricity is generated, getting it to where it’s needed may be a problem, explains Deepjyoti Deka, a MITEI research scientist. “A grid is a network-wide operation, and the grid operator may have sufficient generation at another location or even elsewhere in the country, but the wires may not have sufficient capacity to carry the electricity to where it’s wanted.” So transmission capacity must be expanded — and, says Deka, that’s a slow process.Then there’s the “interconnection queue.” Sometimes, adding either a new user (a “load”) or a new generator to an existing grid can cause instabilities or other problems for everyone else already on the grid. In that situation, bringing a new data center online may be delayed. Enough delays can result in new loads or generators having to stand in line and wait for their turn. Right now, much of the interconnection queue is already filled up with new solar and wind projects. The delay is now about five years. Meeting the demand from newly installed data centers while ensuring that the quality of service elsewhere is not hampered is a problem that needs to be addressed.Finding clean electricity sourcesTo further complicate the challenge, many companies — including so-called “hyperscalers” such as Google, Microsoft, and Amazon — have made public commitments to having net-zero carbon emissions within the next 10 years. Many have been making strides toward achieving their clean-energy goals by buying “power purchase agreements.” They sign a contract to buy electricity from, say, a solar or wind facility, sometimes providing funding for the facility to be built. But that approach to accessing clean energy has its limits when faced with the extreme electricity demand of a data center.Meanwhile, soaring power consumption is delaying coal plant closures in many states. There are simply not enough sources of renewable energy to serve both the hyperscalers and the existing users, including individual consumers. As a result, conventional plants fired by fossil fuels such as coal are needed more than ever.As the hyperscalers look for sources of clean energy for their data centers, one option could be to build their own wind and solar installations. But such facilities would generate electricity only intermittently. Given the need for uninterrupted power, the data center would have to maintain energy storage units, which are expensive. They could instead rely on natural gas or diesel generators for backup power — but those devices would need to be coupled with equipment to capture the carbon emissions, plus a nearby site for permanently disposing of the captured carbon.Because of such complications, several of the hyperscalers are turning to nuclear power. As Green notes, “Nuclear energy is well matched to the demand of data centers, because nuclear plants can generate lots of power reliably, without interruption.”In a much-publicized move in September, Microsoft signed a deal to buy power for 20 years after Constellation Energy reopens one of the undamaged reactors at its now-shuttered nuclear plant at Three Mile Island, the site of the much-publicized nuclear accident in 1979. If approved by regulators, Constellation will bring that reactor online by 2028, with Microsoft buying all of the power it produces. Amazon also reached a deal to purchase power produced by another nuclear plant threatened with closure due to financial troubles. And in early December, Meta released a request for proposals to identify nuclear energy developers to help the company meet their AI needs and their sustainability goals.Other nuclear news focuses on small modular nuclear reactors (SMRs), factory-built, modular power plants that could be installed near data centers, potentially without the cost overruns and delays often experienced in building large plants. Google recently ordered a fleet of SMRs to generate the power needed by its data centers. The first one will be completed by 2030 and the remainder by 2035.Some hyperscalers are betting on new technologies. For example, Google is pursuing next-generation geothermal projects, and Microsoft has signed a contract to purchase electricity from a startup’s fusion power plant beginning in 2028 — even though the fusion technology hasn’t yet been demonstrated.Reducing electricity demandOther approaches to providing sufficient clean electricity focus on making the data center and the operations it houses more energy efficient so as to perform the same computing tasks using less power. Using faster computer chips and optimizing algorithms that use less energy are already helping to reduce the load, and also the heat generated.Another idea being tried involves shifting computing tasks to times and places where carbon-free energy is available on the grid. Deka explains: “If a task doesn’t have to be completed immediately, but rather by a certain deadline, can it be delayed or moved to a data center elsewhere in the U.S. or overseas where electricity is more abundant, cheaper, and/or cleaner? This approach is known as ‘carbon-aware computing.’” We’re not yet sure whether every task can be moved or delayed easily, says Deka. “If you think of a generative AI-based task, can it easily be separated into small tasks that can be taken to different parts of the country, solved using clean energy, and then be brought back together? What is the cost of doing this kind of division of tasks?”That approach is, of course, limited by the problem of the interconnection queue. It’s difficult to access clean energy in another region or state. But efforts are under way to ease the regulatory framework to make sure that critical interconnections can be developed more quickly and easily.What about the neighbors?A major concern running through all the options for powering data centers is the impact on residential energy consumers. When a data center comes into a neighborhood, there are not only aesthetic concerns but also more practical worries. Will the local electricity service become less reliable? Where will the new transmission lines be located? And who will pay for the new generators, upgrades to existing equipment, and so on? When new manufacturing facilities or industrial plants go into a neighborhood, the downsides are generally offset by the availability of new jobs. Not so with a data center, which may require just a couple dozen employees.There are standard rules about how maintenance and upgrade costs are shared and allocated. But the situation is totally changed by the presence of a new data center. As a result, utilities now need to rethink their traditional rate structures so as not to place an undue burden on residents to pay for the infrastructure changes needed to host data centers.MIT’s contributionsAt MIT, researchers are thinking about and exploring a range of options for tackling the problem of providing clean power to data centers. For example, they are investigating architectural designs that will use natural ventilation to facilitate cooling, equipment layouts that will permit better airflow and power distribution, and highly energy-efficient air conditioning systems based on novel materials. They are creating new analytical tools for evaluating the impact of data center deployments on the U.S. power system and for finding the most efficient ways to provide the facilities with clean energy. Other work looks at how to match the output of small nuclear reactors to the needs of a data center, and how to speed up the construction of such reactors.MIT teams also focus on determining the best sources of backup power and long-duration storage, and on developing decision support systems for locating proposed new data centers, taking into account the availability of electric power and water and also regulatory considerations, and even the potential for using what can be significant waste heat, for example, for heating nearby buildings. Technology development projects include designing faster, more efficient computer chips and more energy-efficient computing algorithms.In addition to providing leadership and funding for many research projects, MITEI is acting as a convenor, bringing together companies and stakeholders to address this issue. At MITEI’s 2024 Annual Research Conference, a panel of representatives from two hyperscalers and two companies that design and construct data centers together discussed their challenges, possible solutions, and where MIT research could be most beneficial.As data centers continue to be built, and computing continues to create an unprecedented increase in demand for electricity, Green says, scientists and engineers are in a race to provide the ideas, innovations, and technologies that can meet this need, and at the same time continue to advance the transition to a decarbonized energy system. More

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      in Energy

      Q&A: The climate impact of generative AI

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      Vijay Gadepally, a senior staff member at MIT Lincoln Laboratory, leads a number of projects at the Lincoln Laboratory Supercomputing Center (LLSC) to make computing platforms, and the artificial intelligence systems that run on them, more efficient. Here, Gadepally discusses the increasing use of generative AI in everyday tools, its hidden environmental impact, and some of the ways that Lincoln Laboratory and the greater AI community can reduce emissions for a greener future.Q: What trends are you seeing in terms of how generative AI is being used in computing?A: Generative AI uses machine learning (ML) to create new content, like images and text, based on data that is inputted into the ML system. At the LLSC we design and build some of the largest academic computing platforms in the world, and over the past few years we’ve seen an explosion in the number of projects that need access to high-performance computing for generative AI. We’re also seeing how generative AI is changing all sorts of fields and domains — for example, ChatGPT is already influencing the classroom and the workplace faster than regulations can seem to keep up.We can imagine all sorts of uses for generative AI within the next decade or so, like powering highly capable virtual assistants, developing new drugs and materials, and even improving our understanding of basic science. We can’t predict everything that generative AI will be used for, but I can certainly say that with more and more complex algorithms, their compute, energy, and climate impact will continue to grow very quickly.Q: What strategies is the LLSC using to mitigate this climate impact?A: We’re always looking for ways to make computing more efficient, as doing so helps our data center make the most of its resources and allows our scientific colleagues to push their fields forward in as efficient a manner as possible.As one example, we’ve been reducing the amount of power our hardware consumes by making simple changes, similar to dimming or turning off lights when you leave a room. In one experiment, we reduced the energy consumption of a group of graphics processing units by 20 percent to 30 percent, with minimal impact on their performance, by enforcing a power cap. This technique also lowered the hardware operating temperatures, making the GPUs easier to cool and longer lasting.Another strategy is changing our behavior to be more climate-aware. At home, some of us might choose to use renewable energy sources or intelligent scheduling. We are using similar techniques at the LLSC — such as training AI models when temperatures are cooler, or when local grid energy demand is low.We also realized that a lot of the energy spent on computing is often wasted, like how a water leak increases your bill but without any benefits to your home. We developed some new techniques that allow us to monitor computing workloads as they are running and then terminate those that are unlikely to yield good results. Surprisingly, in a number of cases we found that the majority of computations could be terminated early without compromising the end result.Q: What’s an example of a project you’ve done that reduces the energy output of a generative AI program?A: We recently built a climate-aware computer vision tool. Computer vision is a domain that’s focused on applying AI to images; so, differentiating between cats and dogs in an image, correctly labeling objects within an image, or looking for components of interest within an image.In our tool, we included real-time carbon telemetry, which produces information about how much carbon is being emitted by our local grid as a model is running. Depending on this information, our system will automatically switch to a more energy-efficient version of the model, which typically has fewer parameters, in times of high carbon intensity, or a much higher-fidelity version of the model in times of low carbon intensity.By doing this, we saw a nearly 80 percent reduction in carbon emissions over a one- to two-day period. We recently extended this idea to other generative AI tasks such as text summarization and found the same results. Interestingly, the performance sometimes improved after using our technique!Q: What can we do as consumers of generative AI to help mitigate its climate impact?A: As consumers, we can ask our AI providers to offer greater transparency. For example, on Google Flights, I can see a variety of options that indicate a specific flight’s carbon footprint. We should be getting similar kinds of measurements from generative AI tools so that we can make a conscious decision on which product or platform to use based on our priorities.We can also make an effort to be more educated on generative AI emissions in general. Many of us are familiar with vehicle emissions, and it can help to talk about generative AI emissions in comparative terms. People may be surprised to know, for example, that one image-generation task is roughly equivalent to driving four miles in a gas car, or that it takes the same amount of energy to charge an electric car as it does to generate about 1,500 text summarizations.There are many cases where customers would be happy to make a trade-off if they knew the trade-off’s impact.Q: What do you see for the future?A: Mitigating the climate impact of generative AI is one of those problems that people all over the world are working on, and with a similar goal. We’re doing a lot of work here at Lincoln Laboratory, but its only scratching at the surface. In the long term, data centers, AI developers, and energy grids will need to work together to provide “energy audits” to uncover other unique ways that we can improve computing efficiencies. We need more partnerships and more collaboration in order to forge ahead.If you’re interested in learning more, or collaborating with Lincoln Laboratory on these efforts, please contact Vijay Gadepally.

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      in Environment

      Surface-based sonar system could rapidly map the ocean floor at high resolution

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      On June 18, 2023, the Titan submersible was about an hour-and-a-half into its two-hour descent to the Titanic wreckage at the bottom of the Atlantic Ocean when it lost contact with its support ship. This cease in communication set off a frantic search for the tourist submersible and five passengers onboard, located about two miles below the ocean’s surface.Deep-ocean search and recovery is one of the many missions of military services like the U.S. Coast Guard Office of Search and Rescue and the U.S. Navy Supervisor of Salvage and Diving. For this mission, the longest delays come from transporting search-and-rescue equipment via ship to the area of interest and comprehensively surveying that area. A search operation on the scale of that for Titan — which was conducted 420 nautical miles from the nearest port and covered 13,000 square kilometers, an area roughly twice the size of Connecticut — could take weeks to complete. The search area for Titan is considered relatively small, focused on the immediate vicinity of the Titanic. When the area is less known, operations could take months. (A remotely operated underwater vehicle deployed by a Canadian vessel ended up finding the debris field of Titan on the seafloor, four days after the submersible had gone missing.)A research team from MIT Lincoln Laboratory and the MIT Department of Mechanical Engineering’s Ocean Science and Engineering lab is developing a surface-based sonar system that could accelerate the timeline for small- and large-scale search operations to days. Called the Autonomous Sparse-Aperture Multibeam Echo Sounder, the system scans at surface-ship rates while providing sufficient resolution to find objects and features in the deep ocean, without the time and expense of deploying underwater vehicles. The echo sounder — which features a large sonar array using a small set of autonomous surface vehicles (ASVs) that can be deployed via aircraft into the ocean — holds the potential to map the seabed at 50 times the coverage rate of an underwater vehicle and 100 times the resolution of a surface vessel.

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      Autonomous Sparse-Aperture Multibeam Echo SounderVideo: MIT Lincoln Laboratory

      “Our array provides the best of both worlds: the high resolution of underwater vehicles and the high coverage rate of surface ships,” says co–principal investigator Andrew March, assistant leader of the laboratory’s Advanced Undersea Systems and Technology Group. “Though large surface-based sonar systems at low frequency have the potential to determine the materials and profiles of the seabed, they typically do so at the expense of resolution, particularly with increasing ocean depth. Our array can likely determine this information, too, but at significantly enhanced resolution in the deep ocean.”Underwater unknownOceans cover 71 percent of Earth’s surface, yet more than 80 percent of this underwater realm remains undiscovered and unexplored. Humans know more about the surface of other planets and the moon than the bottom of our oceans. High-resolution seabed maps would not only be useful to find missing objects like ships or aircraft, but also to support a host of other scientific applications: understanding Earth’s geology, improving forecasting of ocean currents and corresponding weather and climate impacts, uncovering archaeological sites, monitoring marine ecosystems and habitats, and identifying locations containing natural resources such as mineral and oil deposits.Scientists and governments worldwide recognize the importance of creating a high-resolution global map of the seafloor; the problem is that no existing technology can achieve meter-scale resolution from the ocean surface. The average depth of our oceans is approximately 3,700 meters. However, today’s technologies capable of finding human-made objects on the seabed or identifying person-sized natural features — these technologies include sonar, lidar, cameras, and gravitational field mapping — have a maximum range of less than 1,000 meters through water.Ships with large sonar arrays mounted on their hull map the deep ocean by emitting low-frequency sound waves that bounce off the seafloor and return as echoes to the surface. Operation at low frequencies is necessary because water readily absorbs high-frequency sound waves, especially with increasing depth; however, such operation yields low-resolution images, with each image pixel representing a football field in size. Resolution is also restricted because sonar arrays installed on large mapping ships are already using all of the available hull space, thereby capping the sonar beam’s aperture size. By contrast, sonars on autonomous underwater vehicles (AUVs) that operate at higher frequencies within a few hundred meters of the seafloor generate maps with each pixel representing one square meter or less, resulting in 10,000 times more pixels in that same football field–sized area. However, this higher resolution comes with trade-offs: AUVs are time-consuming and expensive to deploy in the deep ocean, limiting the amount of seafloor that can be mapped; they have a maximum range of about 1,000 meters before their high-frequency sound gets absorbed; and they move at slow speeds to conserve power. The area-coverage rate of AUVs performing high-resolution mapping is about 8 square kilometers per hour; surface vessels map the deep ocean at more than 50 times that rate.A solution surfacesThe Autonomous Sparse-Aperture Multibeam Echo Sounder could offer a cost-effective approach to high-resolution, rapid mapping of the deep seafloor from the ocean’s surface. A collaborative fleet of about 20 ASVs, each hosting a small sonar array, effectively forms a single sonar array 100 times the size of a large sonar array installed on a ship. The large aperture achieved by the array (hundreds of meters) produces a narrow beam, which enables sound to be precisely steered to generate high-resolution maps at low frequency. Because very few sonars are installed relative to the array’s overall size (i.e., a sparse aperture), the cost is tractable.However, this collaborative and sparse setup introduces some operational challenges. First, for coherent 3D imaging, the relative position of each ASV’s sonar subarray must be accurately tracked through dynamic ocean-induced motions. Second, because sonar elements are not placed directly next to each other without any gaps, the array suffers from a lower signal-to-noise ratio and is less able to reject noise coming from unintended or undesired directions. To mitigate these challenges, the team has been developing a low-cost precision-relative navigation system and leveraging acoustic signal processing tools and new ocean-field estimation algorithms. The MIT campus collaborators are developing algorithms for data processing and image formation, especially to estimate depth-integrated water-column parameters. These enabling technologies will help account for complex ocean physics, spanning physical properties like temperature, dynamic processes like currents and waves, and acoustic propagation factors like sound speed.Processing for all required control and calculations could be completed either remotely or onboard the ASVs. For example, ASVs deployed from a ship or flying boat could be controlled and guided remotely from land via a satellite link or from a nearby support ship (with direct communications or a satellite link), and left to map the seabed for weeks or months at a time until maintenance is needed. Sonar-return health checks and coarse seabed mapping would be conducted on board, while full, high-resolution reconstruction of the seabed would require a supercomputing infrastructure on land or on a support ship.”Deploying vehicles in an area and letting them map for extended periods of time without the need for a ship to return home to replenish supplies and rotate crews would significantly simplify logistics and operating costs,” says co–principal investigator Paul Ryu, a researcher in the Advanced Undersea Systems and Technology Group.Since beginning their research in 2018, the team has turned their concept into a prototype. Initially, the scientists built a scale model of a sparse-aperture sonar array and tested it in a water tank at the laboratory’s Autonomous Systems Development Facility. Then, they prototyped an ASV-sized sonar subarray and demonstrated its functionality in Gloucester, Massachusetts. In follow-on sea tests in Boston Harbor, they deployed an 8-meter array containing multiple subarrays equivalent to 25 ASVs locked together; with this array, they generated 3D reconstructions of the seafloor and a shipwreck. Most recently, the team fabricated, in collaboration with Woods Hole Oceanographic Institution, a first-generation, 12-foot-long, all-electric ASV prototype carrying a sonar array underneath. With this prototype, they conducted preliminary relative navigation testing in Woods Hole, Massachusetts and Newport, Rhode Island. Their full deep-ocean concept calls for approximately 20 such ASVs of a similar size, likely powered by wave or solar energy.This work was funded through Lincoln Laboratory’s internally administered R&D portfolio on autonomous systems. The team is now seeking external sponsorship to continue development of their ocean floor–mapping technology, which was recognized with a 2024 R&D 100 Award.  More

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      in Environment

      In a unique research collaboration, students make the case for less e-waste

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      Brought together as part of the Social and Ethical Responsibilities of Computing (SERC) initiative within the MIT Schwarzman College of Computing, a community of students known as SERC Scholars is collaborating to examine the most urgent problems humans face in the digital landscape.Each semester, students from all levels from across MIT are invited to join a different topical working group led by a SERC postdoctoral associate. Each group delves into a specific issue — such as surveillance or data ownership — culminating in a final project presented at the end of the term.Typically, students complete the program with hands-on experience conducting research in a new cross-disciplinary field. However, one group of undergraduate and graduate students recently had the unique opportunity to enhance their resume by becoming published authors of a case study about the environmental and climate justice implications of the electronics hardware life cycle.Although it’s not uncommon for graduate students to co-author case studies, it’s unusual for undergraduates to earn this opportunity — and for their audience to be other undergraduates around the world.“Our team was insanely interdisciplinary,” says Anastasia Dunca, a junior studying computer science and one of the co-authors. “I joined the SERC Scholars Program because I liked the idea of being part of a cohort from across MIT working on a project that utilized all of our skillsets. It also helps [undergraduates] learn the ins and outs of computing ethics research.”Case study co-author Jasmin Liu, an MBA student in the MIT Sloan School of Management, sees the program as a platform to learn about the intersection of technology, society, and ethics: “I met team members spanning computer science, urban planning, to art/culture/technology. I was excited to work with a diverse team because I know complex problems must be approached with many different perspectives. Combining my background in humanities and business with the expertise of others allowed us to be more innovative and comprehensive.”Christopher Rabe, a former SERC postdoc who facilitated the group, says, “I let the students take the lead on identifying the topic and conducting the research.” His goal for the group was to challenge students across disciplines to develop a working definition of climate justice.From mining to e-wasteThe SERC Scholars’ case study, “From Mining to E-waste: The Environmental and Climate Justice Implications of the Electronics Hardware Life Cycle,” was published by the MIT Case Studies in Social and Ethical Responsibilities of Computing.The ongoing case studies series, which releases new issues twice a year on an open-source platform, is enabling undergraduate instructors worldwide to incorporate research-based education materials on computing ethics into their existing class syllabi.This particular case study broke down the electronics life cycle from mining to manufacturing, usage, and disposal. It offered an in-depth look at how this cycle promotes inequity in the Global South. Mining for the average of 60 minerals that power everyday devices lead to illegal deforestation, compromising air quality in the Amazon, and triggering armed conflict in Congo. Manufacturing leads to proven health risks for both formal and informal workers, some of whom are child laborers.Life cycle assessment and circular economy are proposed as mechanisms for analyzing environmental and climate justice issues in the electronics life cycle. Rather than posing solutions, the case study offers readers entry points for further discussion and for assessing their own individual responsibility as producers of e-waste.Crufting and crafting a case studyDunca joined Rabe’s working group, intrigued by the invitation to conduct a rigorous literature review examining issues like data center resource and energy use, manufacturing waste, ethical issues with AI, and climate change. Rabe quickly realized that a common thread among all participants was an interest in understanding and reducing e-waste and its impact on the environment.“I came in with the idea of us co-authoring a case study,” Rabe said. However, the writing-intensive process was initially daunting to those students who were used to conducting applied research. Once Rabe created sub-groups with discrete tasks, the steps for researching, writing, and iterating a case study became more approachable.For Ellie Bultena, an undergraduate student studying linguistics and philosophy and a contributor to the study, that meant conducting field research on the loading dock of MIT’s Stata Center, where students and faculty go “crufting” through piles of clunky printers, broken computers, and used lab equipment discarded by the Institute’s labs, departments, and individual users.Although not a formally sanctioned activity on-campus, “crufting” is the act of gleaning usable parts from these junk piles to be repurposed into new equipment or art. Bultena’s respondents, who opted to be anonymous, said that MIT could do better when it comes to the amount of e-waste generated and suggested that formal strategies could be implemented to encourage community members to repair equipment more easily or recycle more formally.Rabe, now an education program director at the MIT Environmental Solutions Initiative, is hopeful that through the Zero-Carbon Campus Initiative, which commits MIT to eliminating all direct emissions by 2050, MIT will ultimately become a model for other higher education institutions.Although the group lacked the time and resources to travel to communities in the Global South that they profiled in their case study, members leaned into exhaustive secondary research, collecting data on how some countries are irresponsibly dumping e-waste. In contrast, others have developed alternative solutions that can be duplicated elsewhere and scaled.“We source materials, manufacture them, and then throw them away,” Lelia Hampton says. A PhD candidate in electrical engineering and computer science and another co-author, Hampton jumped at the opportunity to serve in a writing role, bringing together the sub-groups research findings. “I’d never written a case study, and it was exciting. Now I want to write 10 more.”The content directly informed Hampton’s dissertation research, which “looks at applying machine learning to climate justice issues such as urban heat islands.” She said that writing a case study that is accessible to general audiences upskilled her for the non-profit organization she’s determined to start. “It’s going to provide communities with free resources and data needed to understand how they are impacted by climate change and begin to advocate against injustice,” Hampton explains.Dunca, Liu, Rabe, Bultena, and Hampton are joined on the case study by fellow authors Mrinalini Singha, a graduate student in the Art, Culture, and Technology program; Sungmoon Lim, a graduate student in urban studies and planning and EECS; Lauren Higgins, an undergraduate majoring in political science; and Madeline Schlegal, a Northeastern University co-op student.Taking the case study to classrooms around the worldAlthough PhD candidates have contributed to previous case studies in the series, this publication is the first to be co-authored with MIT undergraduates. Like any other peer-reviewed journal, before publication, the SERC Scholars’ case study was anonymously reviewed by senior scholars drawn from various fields.The series editor, David Kaiser, also served as one of SERC’s inaugural associate deans and helped shape the program. “The case studies, by design, are short, easy to read, and don’t take up lots of time,” Kaiser explained. “They are gateways for students to explore, and instructors can cover a topic that has likely already been on their mind.” This semester, Kaiser, the Germeshausen Professor of the History of Science and a professor of physics, is teaching STS.004 (Intersections: Science, Technology, and the World), an undergraduate introduction to the field of science, technology, and society. The last month of the semester has been dedicated wholly to SERC case studies, one of which is: “From Mining to E-Waste.”Hampton was visibly moved to hear that the case study is being used at MIT but also by some of the 250,000 visitors to the SERC platform, many of whom are based in the Global South and directly impacted by the issues she and her cohort researched. “Many students are focused on climate, whether through computer science, data science, or mechanical engineering. I hope that this case study educates them on environmental and climate aspects of e-waste and computing.” More

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      in Environment

      3 Questions: Can we secure a sustainable supply of nickel?

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      As the world strives to cut back on carbon emissions, demand for minerals and metals needed for clean energy technologies is growing rapidly, sometimes straining existing supply chains and harming local environments. In a new study published today in Joule, Elsa Olivetti, a professor of materials science and engineering and director of the Decarbonizing Energy and Industry mission within MIT’s Climate Project, along with recent graduates Basuhi Ravi PhD ’23 and Karan Bhuwalka PhD ’24 and nine others, examine the case of nickel, which is an essential element for some electric vehicle batteries and parts of some solar panels and wind turbines.How robust is the supply of this vital metal, and what are the implications of its extraction for the local environments, economies, and communities in the places where it is mined? MIT News asked Olivetti, Ravi, and Bhuwalka to explain their findings.Q: Why is nickel becoming more important in the clean energy economy, and what are some of the potential issues in its supply chain?Olivetti: Nickel is increasingly important for its role in EV batteries, as well as other technologies such as wind and solar. For batteries, high-purity nickel sulfate is a key input to the cathodes of EV batteries, which enables high energy density in batteries and increased driving range for EVs. As the world transitions away from fossil fuels, the demand for EVs, and consequently for nickel, has increased dramatically and is projected to continue to do so.The nickel supply chain for battery-grade nickel sulfate includes mining nickel from ore deposits, processing it to a suitable nickel intermediary, and refining it to nickel sulfate. The potential issues in the supply chain can be broadly described as land use concerns in the mining stage, and emissions concerns in the processing stage. This is obviously oversimplified, but as a basic structure for our inquiry we thought about it this way. Nickel mining is land-intensive, leading to deforestation, displacement of communities, and potential contamination of soil and water resources from mining waste. In the processing step, the use of fossil fuels leads to direct emissions including particulate matter and sulfur oxides. In addition, some emerging processing pathways are particularly energy-intensive, which can double the carbon footprint of nickel-rich batteries compared to the current average.Q: What is Indonesia’s role in the global nickel supply, and what are the consequences of nickel extraction there and in other major supply countries?Ravi: Indonesia plays a critical role in nickel supply, holding the world’s largest nickel reserves and supplying nearly half of the globally mined nickel in 2023. The country’s nickel production has seen a remarkable tenfold increase since 2016. This production surge has fueled economic growth in some regions, but also brought notable environmental and social impacts to nickel mining and processing areas.Nickel mining expansion in Indonesia has been linked to health impacts due to air pollution in the islands where nickel processing is prominent, as well as deforestation in some of the most biodiversity-rich locations on the planet. Reports of displacement of indigenous communities, land grabbing, water rights issues, and inadequate job quality in and around mines further highlight the social concerns and unequal distribution of burdens and benefits in Indonesia. Similar concerns exist in other major nickel-producing countries, where mining activities can negatively impact the environment, disrupt livelihoods, and exacerbate inequalities.On a global scale, Indonesia’s reliance on coal-based energy for nickel processing, particularly in energy-intensive smelting and leaching of a clay-like material called laterite, results in a high carbon intensity for nickel produced in the region, compared to other major producing regions such as Australia.Q: What role can industry and policymakers play in helping to meet growing demand while improving environmental safety?Bhuwalka: In consuming countries, policies can foster “discerning demand,” which means creating incentives for companies to source nickel from producers that prioritize sustainability. This can be achieved through regulations that establish acceptable environmental footprints for imported materials, such as limits on carbon emissions from nickel production. For example, the EU’s Critical Raw Materials Act and the U.S. Inflation Reduction Act could be leveraged to promote responsible sourcing. Additionally, governments can use their purchasing power to favor sustainably produced nickel in public procurement, which could influence industry practices and encourage the adoption of sustainability standards.On the supply side, nickel-producing countries like Indonesia can implement policies to mitigate the adverse environmental and social impacts of nickel extraction. This includes strengthening environmental regulations and enforcement to reduce the footprint of mining and processing, potentially through stricter pollution limits and responsible mine waste management. In addition, supporting community engagement, implementing benefit-sharing mechanisms, and investing in cleaner nickel processing technologies are also crucial.Internationally, harmonizing sustainability standards and facilitating capacity building and technology transfer between developed and developing countries can create a level playing field and prevent unsustainable practices. Responsible investment practices by international financial institutions, favoring projects that meet high environmental and social standards, can also contribute to a stable and sustainable nickel supply chain. More

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      in Energy

      Celebrating the people behind Kendall Square’s innovation ecosystem

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      While it’s easy to be amazed by the constant drumbeat of innovations coming from Kendall Square in Cambridge, Massachusetts, sometimes overlooked are the dedicated individuals working to make those scientific and technological breakthroughs a reality. Every day, people in the neighborhood tackle previously intractable problems and push the frontiers of their fields.This year’s Kendall Square Association (KSA) Annual Meeting centered around celebrating the people behind the area’s prolific innovation ecosystem. That included a new slate of awards and recognitions for community members and a panel discussion featuring MIT President Sally Kornbluth.“It’s truly inspiring to be surrounded by all of you: people who seem to share an exuberant curiosity, a pervasive ethic of service, and the baseline expectation that we’re all interested in impact — in making a difference for people and the planet,” Kornbluth said.The gathering took place in MIT’s Walker Memorial (Building 50) on Memorial Drive and attracted entrepreneurs, life science workers, local students, restaurant and retail shop owners, and leaders of nonprofits.The KSA itself is a nonprofit organization made up of over 150 organizations across the greater Kendall Square region, from large companies to universities like MIT and Harvard, along with the independent shops and restaurants that give Kendall Square its distinct character.New to this year’s event were two Founder Awards, which were given to Sangeeta Bhatia, the the John and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science at MIT, and Michal Preminger, head of Johnson and Johnson Innovation, for their work bringing people together to achieve hard things that benefit humanity.The KSA will donate $2,500 to the Science Club for Girls in Bhatia’s honor and $2,500 to Innovators for Purpose in honor of Preminger.Recognition was also given to Alex Cheung of the Cambridge Innovation Center and Shazia Mir of LabCentral for their work bringing Kendall Square’s community members together.Cambridge Mayor Denise Simmons also spoke at the event, noting the vital role the Kendall Square community has played in things like Covid-19 vaccine development and in the fight against climate change.“As many of you know, Cambridge has a long and proud history of innovation, with the presence of MIT and the remarkable growth of the tech and life science industry examples of that,” Simmons said. “We are leaving a lasting, positive impact in our city. This community has made and continues to make enormous contributions, not just to our city but to the world.”In her talk, Kornbluth also introduced the Kendall Square community to her plans for The Climate Project at MIT, which is designed to focus the Institute’s talent and resources to achieve real-world impact on climate change faster. The project will provide funding and catalyze partnerships around six climate “missions,” or broad areas where MIT researchers will seek to identify gaps in the global climate response that MIT can help fill.“The Climate Project is a whole-of-MIT mobilization that’s mission driven, solution focused, and outward looking,” Kornbluth explained. “If you want to make progress, faster and at scale, that’s the way!”After mingling with Kendall community members, Kornbluth said she still considers herself a newbie to the area but is coming to see the success of Kendall Square and MIT as more than a coincidence.“The more time I spend here, the more I come to understand the incredible synergies between MIT and Kendall Square,” Kornbluth said. “We know, for example, that proximity is an essential ingredient in our collective and distinctive recipe for impact. That proximity, and the cross-fertilization that comes with it, helps us churn out new technologies and patents, found startups, and course-correct our work as we try to keep pace with the world’s challenges. We can’t do any of this separately. Our work together — all of us in this thriving, wildly entrepreneurial community — is what drives the success of our innovation ecosystem.” More