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      in Environment

      Researchers return to Arctic to test integrated sensor nodes

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      Shimmering ice extends in all directions as far as the eye can see. Air temperatures plunge to minus 40 degrees Fahrenheit and colder with wind chills. Ocean currents drag large swaths of ice floating at sea. Polar bears, narwhals, and other iconic Arctic species roam wild.For a week this past spring, MIT Lincoln Laboratory researchers Ben Evans and Dave Whelihan called this place — drifting some 200 nautical miles offshore from Prudhoe Bay, Alaska, on the frozen Beaufort Sea in the Arctic Circle — home. Two ice runways for small aircraft provided their only way in and out of this remote wilderness; heated tents provided their only shelter from the bitter cold.

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      Here, in the northernmost region on Earth, Evans and Whelihan joined other groups conducting fieldwork in the Arctic as part of Operation Ice Camp (OIC) 2024, an operational exercise run by the U.S. Navy’s Arctic Submarine Laboratory (ASL). Riding on snowmobiles and helicopters, the duo deployed a small set of integrated sensor nodes that measure everything from atmospheric conditions to ice properties to the structure of water deep below the surface.Ultimately, they envision deploying an unattended network of these low-cost sensor nodes across the Arctic to increase scientific understanding of the trending loss in sea ice extent and thickness. Warming much faster than the rest of the world, the Arctic is a ground zero for climate change, with cascading impacts across the planet that include rising sea levels and extreme weather. Openings in the sea ice cover, or leads, are concerning not only for climate change but also for global geopolitical competition over transit routes and natural resources. A synoptic view of the physical processes happening above, at, and below sea ice is key to determining why the ice is diminishing. In turn, this knowledge can help predict when and where fractures will occur, to inform planning and decision-making.Winter “camp”Every two years, OIC, previously called Ice Exercise (ICEX), provides a way for the international community to access the Arctic for operational readiness exercises and scientific research, with the focus switching back and forth; this year’s focus was scientific research. Coordination, planning, and execution of the month-long operation is led by ASL, a division of the U.S. Navy’s Undersea Warfighting Development Center responsible for ensuring the submarine force can effectively operate in the Arctic Ocean.Making this inhospitable and unforgiving environment safe for participants takes considerable effort. The critical first step is determining where to set up camp. In the weeks before the first participants arrived for OIC 2024, ASL — with assistance from the U.S. National Ice Center, University of Alaska Fairbanks Geophysical Institute, and UIC Science — flew over large sheets of floating ice (ice floes) identified via satellite imagery, landed on some they thought might be viable sites, and drilled through the ice to check its thickness. The ice floe must not only be large enough to accommodate construction of a camp and two runways but also feature both multiyear ice and first-year ice. Multiyear ice is thick and strong but rough, making it ideal for camp setup, while the smooth but thinner first-year ice is better suited for building runways. Once the appropriate ice floe was selected, ASL began to haul in equipment and food, build infrastructure like lodging and a command center, and fly in a small group before fully operationalizing the site. They also identified locations near the camp for two Navy submarines to surface through the ice.The more than 200 participants represented U.S. and allied forces and scientists from research organizations and universities. Distinguished visitors from government offices also attended OIC to see the unique Arctic environment and unfolding challenges firsthand.“Our ASL hosts do incredible work to build this camp from scratch and keep us alive,” Evans says.Evans and Whelihan, part of the laboratory’s Advanced Undersea Systems and Technology Group, first trekked to the Arctic in March 2022 for ICEX 2022. (The laboratory in general has been participating since 2016 in these events, the first iteration of which occurred in 1946.) There, they deployed a suite of commercial off-the-shelf sensors for detecting acoustic (sound) and seismic (vibration) events created by ice fractures or collisions, and for measuring salinity, temperature, and pressure in the water below the ice. They also deployed a prototype fiber-based temperature sensor array developed by the laboratory and research partners for precisely measuring temperature across the entire water column at one location, and a University of New Hampshire (UNH)−supplied echosounder to investigate the different layers present in the water column. In this maiden voyage, their goals were to assess how these sensors fared in the harsh Arctic conditions and to collect a dataset from which characteristic signatures of ice-fracturing events could begin to be identified. These events would be correlated with weather and water conditions to eventually offer a predictive capability.“We saw real phenomenology in our data,” Whelihan says. “But, we’re not ice experts. What we’re good at here at the laboratory is making and deploying sensors. That’s our place in the world of climate science: to be a data provider. In fact, we hope to open source all of our data this year so that ice scientists can access and analyze them and then we can make enhanced sensors and collect more data.”Interim iceIn the two years since that expedition, they and their colleagues have been modifying their sensor designs and deployment strategies. As Evans and Whelihan learned at ICEX 2022, to be resilient in the Arctic, a sensor must not only be kept warm and dry during deployment but also be deployed in a way to prevent breaking. Moreover, sufficient power and data links are needed to collect and access sensor data.“We can make cold-weather electronics, no problem,” Whelihan says. “The two drivers are operating the sensors in an energy-starved environment — the colder it is, the worse batteries perform — and keeping them from getting destroyed when ice floes crash together as leads in the ice open up.”Their work in the interim to OIC 2024 involved integrating the individual sensors into hardened sensor nodes and practicing deploying these nodes in easier-to-access locations. To facilitate incorporating additional sensors into a node, Whelihan spearheaded the development of an open-source, easily extensible hardware and software architecture.In March 2023, the Lincoln Laboratory team deployed three sensor nodes for a week on Huron Bay off Lake Superior through Michigan Tech’s Great Lakes Research Center (GLRC). Engineers from GLRC helped the team safely set up an operations base on the ice. They demonstrated that the sensor integration worked, and the sensor nodes proved capable of surviving for at least a week in relatively harsh conditions. The researchers recorded seismic activity on all three nodes, corresponding to some ice breaking further up the bay.“Proving our sensor node in an Arctic surrogate environment provided a stepping stone for testing in the real Arctic,” Evans says.Evans then received an invitation from Ignatius Rigor, the coordinator of the International Arctic Buoy Program (IABP), to join him on an upcoming trip to Utqiaġvik (formerly Barrow), Alaska, and deploy one of their seismic sensor nodes on the ice there (with support from UIC Science). The IABP maintains a network of Arctic buoys equipped with meteorological and oceanic sensors. Data collected by these buoys are shared with the operational and research communities to support real-time operations (e.g., forecasting sea ice conditions for coastal Alaskans) and climate research. However, these buoys are typically limited in the frequency at which they collect data, so phenomenology on shorter time scales important to climate change may be missed. Moreover, these buoys are difficult and expensive to deploy because they are designed to survive in the harshest environments for years at a time.  The laboratory-developed sensor nodes could offer an inexpensive, easier-to-deploy option for collecting more data over shorter periods of time. In April 2023, Evans placed a sensor node in Utqiaġvik on landfast sea ice, which is stationary ice anchored to the seabed just off the coast. During the sensor node’s week-long deployment, a big piece of drift ice (ice not attached to the seabed or other fixed object) broke off and crashed into the landfast ice. The event was recorded by a radar maintained by the University of Alaska Fairbanks that monitors sea ice movement in near real time to warn of any instability. Though this phenomenology is not exactly the same as that expected for Arctic sea ice, the researchers were encouraged to see seismic activity recorded by their sensor node.In December 2023, Evans and Whelihan headed to New Hampshire, where they conducted echosounder testing in UNH’s engineering test tank and on the Piscataqua River. Together with their UNH partners, they sought to determine whether a low-cost, hobby-grade echosounder could detect the same phenomenology of interest as the high-fidelity UNH echosounder, which would be far too costly to deploy in sensor nodes across the Arctic. In the test tank and on the river, the low-cost echosounder proved capable of detecting masses of water moving in the water column, but with considerably less structural detail than afforded by the higher-cost option. Seeing such dynamics is important to inferring where water comes from and understanding how it affects sea ice breakup — for example, how warm water moving in from the Pacific Ocean is coming into contact with and melting the ice. So, the laboratory researchers and UNH partners have been building a medium-fidelity, medium-cost echosounder.In January 2024, Evans and Whelihan — along with Jehan Diaz, a fellow staff member in their research group — returned to GLRC. With logistical support from their GLRC hosts, they snowmobiled across the ice on Portage Lake, where they practiced several activities to prepare for OIC 2024: augering (drilling) six-inch holes in the ice, albeit in thinner ice than that in the Arctic; placing their long, pipe-like sensor nodes through these holes; operating cold-hardened drones to interact with the nodes; and retrieving the nodes. They also practiced sensor calibration by hitting the ice with an iron bar some distance away from the nodes and correlating this distance with the resulting measured acoustic and seismic intensity.“Our time at GLRC helped us mitigate a lot of risks and prepare to deploy these complex systems in the Arctic,” Whelihan says.Arctic againTo get to OIC, Evans and Whelihan first flew to Prudhoe Bay and reacclimated to the frigid temperatures. They spent the next two days at the Deadhorse Aviation Center hangar inspecting their equipment for transit-induced damage, which included squashed cables and connectors that required rejiggering.“That’s part of the adventure story,” Evans says. “Getting stuff to Prudhoe Bay is not your standard shipping; it’s ice-road trucking.”From there, they boarded a small aircraft to the ice camp.“Even though this trip marked our second time coming here, it was still disorienting,” Evans continues. “You land in the middle of nowhere on a small aircraft after a couple-hour flight. You get out bundled in all of your Arctic gear in this remote, pristine environment.”After unloading and rechecking their equipment for any damage, calibrating their sensors, and attending safety briefings, they were ready to begin their experiments.An icy situationInside the project tent, Evans and Whelihan deployed the UNH-supplied echosounder and a suite of ground-truth sensors on an automated winch to profile water conductivity, temperature, and depth (CTD). Echosounder data needed to be validated with associated CTD data to determine the source of the water in the water column. Ocean properties change as a function of depth, and these changes are important to capture, in part because masses of water coming in from the Atlantic and Pacific oceans arrive at different depths. Though masses of warm water have always existed, climate change–related mechanisms are now bringing them into contact with the ice.  “As ice breaks up, wind can directly interact with the ocean because it’s lacking that barrier of ice cover,” Evans explains. “Kinetic energy from the wind causes mixing in the ocean; all the warm water that used to stay at depth instead gets brought up and interacts with the ice.”They also deployed four of their sensor nodes several miles outside of camp. To access this deployment site, they rode on a sled pulled via a snowmobile driven by Ann Hill, an ASL field party leader trained in Arctic survival and wildlife encounters. The temperature that day was -55 F. At such a dangerously cold temperature, frostnip and frostbite are all too common. To avoid removal of gloves or other protective clothing, the researchers enabled the nodes with WiFi capability (the nodes also have a satellite communications link to transmit low-bandwidth data). Large amounts of data are automatically downloaded over WiFi to an arm-wearable haptic (touch-based) system when a user walks up to a node.“It was so cold that the holes we were drilling in the ice to reach the water column were freezing solid,” Evans explains. “We realized it was going to be quite an ordeal to get our sensor nodes out of the ice.”So, after drilling a big hole in the ice, they deployed only one central node with all the sensor components: a commercial echosounder, an underwater microphone, a seismometer, and a weather station. They deployed the other three nodes, each with a seismometer and weather station, atop the ice.“One of our design considerations was flexibility,” Whelihan says. “Each node can integrate as few or as many sensors as desired.”The small sensor array was only collecting data for about a day when Evans and Whelihan, who were at the time on a helicopter, saw that their initial field site had become completely cut off from camp by a 150-meter-wide ice lead. They quickly returned to camp to load the tools needed to pull the nodes, which were no longer accessible by snowmobile. Two recently arrived staff members from the Ted Stevens Center for Arctic Security Studies offered to help them retrieve their nodes. The helicopter landed on the ice floe near a crack, and the pilot told them they had half an hour to complete their recovery mission. By the time they had retrieved all four sensors, the crack had increased from thumb to fist size.“When we got home, we analyzed the collected sensor data and saw a spike in seismic activity corresponding to what could be the major ice-fracturing event that necessitated our node recovery mission,” Whelihan says.  The researchers also conducted experiments with their Arctic-hardened drones to evaluate their utility for retrieving sensor node data and to develop concepts of operations for future capabilities.“The idea is to have some autonomous vehicle land next to the node, download data, and come back, like a data mule, rather than having to expend energy getting data off the system, say via high-speed satellite communications,” Whelihan says. “We also started testing whether the drone is capable on its own of finding sensors that are constantly moving and getting close enough to them. Even flying in 25-mile-per-hour winds, and at very low temperatures, the drone worked well.”Aside from carrying out their experiments, the researchers had the opportunity to interact with other participants. Their “roommates” were ice scientists from Norway and Finland. They met other ice and water scientists conducting chemistry experiments on the salt content of ice taken from different depths in the ice sheet (when ocean water freezes, salt tends to get pushed out of the ice). One of their collaborators — Nicholas Schmerr, an ice seismologist from the University of Maryland — placed high-quality geophones (for measuring vibrations in the ice) alongside their nodes deployed on the camp field site. They also met with junior enlisted submariners, who temporarily came to camp to open up spots on the submarine for distinguished visitors.“Part of what we’ve been doing over the last three years is building connections within the Arctic community,” Evans says. “Every time I start to get a handle on the phenomenology that exists out here, I learn something new. For example, I didn’t know that sometimes a layer of ice forms a little bit deeper than the primary ice sheet, and you can actually see fish swimming in between the layers.”“One day, we were out with our field party leader, who saw fog while she was looking at the horizon and said the ice was breaking up,” Whelihan adds. “I said, ‘Wait, what?’ As she explained, when an ice lead forms, fog comes out of the ocean. Sure enough, within 30 minutes, we had quarter-mile visibility, whereas beforehand it was unlimited.”Back to solid groundBefore leaving, Whelihan and Evans retrieved and packed up all the remaining sensor nodes, adopting the “leave no trace” philosophy of preserving natural places.“Only a limited number of people get access to this special environment,” Whelihan says. “We hope to grow our footprint at these events in future years, giving opportunities to other laboratory staff members to attend.”In the meantime, they will analyze the collected sensor data and refine their sensor node design. One design consideration is how to replenish the sensors’ battery power. A potential path forward is to leverage the temperature difference between water and air, and harvest energy from the water currents moving under ice floes. Wind energy may provide another viable solution. Solar power would only work for part of the year because the Arctic Circle undergoes periods of complete darkness.The team is also seeking external sponsorship to continue their work engineering sensing systems that advance the scientific community’s understanding of changes to Arctic ice; this work is currently funded through Lincoln Laboratory’s internally administered R&D portfolio on climate change. And, in learning more about this changing environment and its critical importance to strategic interests, they are considering other sensing problems that they could tackle using their Arctic engineering expertise.“The Arctic is becoming a more visible and important region because of how it’s changing,” Evans concludes. “Going forward as a country, we must be able to operate there.” More

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      in Energy

      Proton-conducting materials could enable new green energy technologies

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      As the name suggests, most electronic devices today work through the movement of electrons. But materials that can efficiently conduct protons — the nucleus of the hydrogen atom — could be key to a number of important technologies for combating global climate change.Most proton-conducting inorganic materials available now require undesirably high temperatures to achieve sufficiently high conductivity. However, lower-temperature alternatives could enable a variety of technologies, such as more efficient and durable fuel cells to produce clean electricity from hydrogen, electrolyzers to make clean fuels such as hydrogen for transportation, solid-state proton batteries, and even new kinds of computing devices based on iono-electronic effects.In order to advance the development of proton conductors, MIT engineers have identified certain traits of materials that give rise to fast proton conduction. Using those traits quantitatively, the team identified a half-dozen new candidates that show promise as fast proton conductors. Simulations suggest these candidates will perform far better than existing materials, although they still need to be conformed experimentally. In addition to uncovering potential new materials, the research also provides a deeper understanding at the atomic level of how such materials work.The new findings are described in the journal Energy and Environmental Sciences, in a paper by MIT professors Bilge Yildiz and Ju Li, postdocs Pjotrs Zguns and Konstantin Klyukin, and their collaborator Sossina Haile and her students from Northwestern University. Yildiz is the Breene M. Kerr Professor in the departments of Nuclear Science and Engineering, and Materials Science and Engineering.“Proton conductors are needed in clean energy conversion applications such as fuel cells, where we use hydrogen to produce carbon dioxide-free electricity,” Yildiz explains. “We want to do this process efficiently, and therefore we need materials that can transport protons very fast through such devices.”Present methods of producing hydrogen, for example steam methane reforming, emit a great deal of carbon dioxide. “One way to eliminate that is to electrochemically produce hydrogen from water vapor, and that needs very good proton conductors,” Yildiz says. Production of other important industrial chemicals and potential fuels, such as ammonia, can also be carried out through efficient electrochemical systems that require good proton conductors.But most inorganic materials that conduct protons can only operate at temperatures of 200 to 600 degrees Celsius (roughly 450 to 1,100 Fahrenheit), or even higher. Such temperatures require energy to maintain and can cause degradation of materials. “Going to higher temperatures is not desirable because that makes the whole system more challenging, and the material durability becomes an issue,” Yildiz says. “There is no good inorganic proton conductor at room temperature.” Today, the only known room-temperature proton conductor is a polymeric material that is not practical for applications in computing devices because it can’t easily be scaled down to the nanometer regime, she says.To tackle the problem, the team first needed to develop a basic and quantitative understanding of exactly how proton conduction works, taking a class of inorganic proton conductors, called solid acids. “One has to first understand what governs proton conduction in these inorganic compounds,” she says. While looking at the materials’ atomic configurations, the researchers identified a pair of characteristics that directly relates to the materials’ proton-carrying potential.As Yildiz explains, proton conduction first involves a proton “hopping from a donor oxygen atom to an acceptor oxygen. And then the environment has to reorganize and take the accepted proton away, so that it can hop to another neighboring acceptor, enabling long-range proton diffusion.” This process happens in many inorganic solids, she says. Figuring out how that last part works — how the atomic lattice gets reorganized to take the accepted proton away from the original donor atom — was a key part of this research, she says.The researchers used computer simulations to study a class of materials called solid acids that become good proton conductors above 200 degrees Celsius. This class of materials has a substructure called the polyanion group sublattice, and these groups have to rotate and take the proton away from its original site so it can then transfer to other sites. The researchers were able to identify the phonons that contribute to the flexibility of this sublattice, which is essential for proton conduction. Then they used this information to comb through vast databases of theoretically and experimentally possible compounds, in search of better proton conducting materials.As a result, they found solid acid compounds that are promising proton conductors and that have been developed and produced for a variety of different applications but never before studied as proton conductors; these compounds turned out to have just the right characteristics of lattice flexibility. The team then carried out computer simulations of how the specific materials they identified in their initial screening would perform under relevant temperatures, to confirm their suitability as proton conductors for fuel cells or other uses. Sure enough, they found six promising materials, with predicted proton conduction speeds faster than the best existing solid acid proton conductors.“There are uncertainties in these simulations,” Yildiz cautions. “I don’t want to say exactly how much higher the conductivity will be, but these look very promising. Hopefully this motivates the experimental field to try to synthesize them in different forms and make use of these compounds as proton conductors.”Translating these theoretical findings into practical devices could take some years, she says. The likely first applications would be for electrochemical cells to produce fuels and chemical feedstocks such as hydrogen and ammonia, she says.The work was supported by the U.S. Department of Energy, the Wallenberg Foundation, and the U.S. National Science Foundation. More

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      in Environment

      China-based emissions of three potent climate-warming greenhouse gases spiked in past decade

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      When it comes to heating up the planet, not all greenhouse gases are created equal. They vary widely in their global warming potential (GWP), a measure of how much infrared thermal radiation a greenhouse gas would absorb over a given time frame once it enters the atmosphere. For example, measured over a 100-year period, the GWP of methane is about 28 times that of carbon dioxide (CO2), and the GWPs of a class of greenhouse gases known as perfluorocarbons (PFCs) are thousands of times that of CO2. The lifespans in the atmosphere of different greenhouse gases also vary widely. Methane persists in the atmosphere for around 10 years; CO2 for over 100 years, and PFCs for up to tens of thousands of years.Given the high GWPs and lifespans of PFCs, their emissions could pose a major roadblock to achieving the aspirational goal of the Paris Agreement on climate change — to limit the increase in global average surface temperature to 1.5 degrees Celsius above preindustrial levels. Now, two new studies based on atmospheric observations inside China and high-resolution atmospheric models show a rapid rise in Chinese emissions over the last decade (2011 to 2020 or 2021) of three PFCs: tetrafluoromethane (PFC-14) and hexafluoroethane (PFC-116) (results in PNAS), and perfluorocyclobutane (PFC-318) (results in Environmental Science & Technology).Both studies find that Chinese emissions have played a dominant role in driving up global emission levels for all three PFCs.The PNAS study identifies substantial PFC-14 and PFC-116 emission sources in the less-populated western regions of China from 2011 to 2021, likely due to the large amount of aluminum industry in these regions. The semiconductor industry also contributes to some of the emissions detected in the more economically developed eastern regions. These emissions are byproducts from aluminum smelting, or occur during the use of the two PFCs in the production of semiconductors and flat panel displays. During the observation period, emissions of both gases in China rose by 78 percent, accounting for most of the increase in global emissions of these gases.The ES&T study finds that during 2011-20, a 70 percent increase in Chinese PFC-318 emissions (contributing more than half of the global emissions increase of this gas) — originated primarily in eastern China. The regions with high emissions of PFC-318 in China overlap with geographical areas densely populated with factories that produce polytetrafluoroethylene (PTFE, commonly used for nonstick cookware coatings), implying that PTFE factories are major sources of PFC-318 emissions in China. In these factories, PFC-318 is formed as a byproduct.“Using atmospheric observations from multiple monitoring sites, we not only determined the magnitudes of PFC emissions, but also pinpointed the possible locations of their sources,” says Minde An, a postdoc at the MIT Center for Global Change Science (CGCS), and corresponding author of both studies. “Identifying the actual source industries contributing to these PFC emissions, and understanding the reasons for these largely byproduct emissions, can provide guidance for developing region- or industry-specific mitigation strategies.”“These three PFCs are largely produced as unwanted byproducts during the manufacture of otherwise widely used industrial products,” says MIT professor of atmospheric sciences Ronald Prinn, director of both the MIT Joint Program on the Science and Policy of Global Change and CGCS, and a co-author of both studies. “Phasing out emissions of PFCs as early as possible is highly beneficial for achieving global climate mitigation targets and is likely achievable by recycling programs and targeted technological improvements in these industries.”Findings in both studies were obtained, in part, from atmospheric observations collected from nine stations within a Chinese network, including one station from the Advanced Global Atmospheric Gases Experiment (AGAGE) network. For comparison, global total emissions were determined from five globally distributed, relatively unpolluted “background” AGAGE stations, as reported in the latest United Nations Environment Program and World Meteorological Organization Ozone Assessment report. More

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      in Energy

      AI method radically speeds predictions of materials’ thermal properties

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      It is estimated that about 70 percent of the energy generated worldwide ends up as waste heat.If scientists could better predict how heat moves through semiconductors and insulators, they could design more efficient power generation systems. However, the thermal properties of materials can be exceedingly difficult to model.The trouble comes from phonons, which are subatomic particles that carry heat. Some of a material’s thermal properties depend on a measurement called the phonon dispersion relation, which can be incredibly hard to obtain, let alone utilize in the design of a system.A team of researchers from MIT and elsewhere tackled this challenge by rethinking the problem from the ground up. The result of their work is a new machine-learning framework that can predict phonon dispersion relations up to 1,000 times faster than other AI-based techniques, with comparable or even better accuracy. Compared to more traditional, non-AI-based approaches, it could be 1 million times faster.This method could help engineers design energy generation systems that produce more power, more efficiently. It could also be used to develop more efficient microelectronics, since managing heat remains a major bottleneck to speeding up electronics.“Phonons are the culprit for the thermal loss, yet obtaining their properties is notoriously challenging, either computationally or experimentally,” says Mingda Li, associate professor of nuclear science and engineering and senior author of a paper on this technique.Li is joined on the paper by co-lead authors Ryotaro Okabe, a chemistry graduate student; and Abhijatmedhi Chotrattanapituk, an electrical engineering and computer science graduate student; Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering and Computer Science at MIT; as well as others at MIT, Argonne National Laboratory, Harvard University, the University of South Carolina, Emory University, the University of California at Santa Barbara, and Oak Ridge National Laboratory. The research appears in Nature Computational Science.Predicting phononsHeat-carrying phonons are tricky to predict because they have an extremely wide frequency range, and the particles interact and travel at different speeds.A material’s phonon dispersion relation is the relationship between energy and momentum of phonons in its crystal structure. For years, researchers have tried to predict phonon dispersion relations using machine learning, but there are so many high-precision calculations involved that models get bogged down.“If you have 100 CPUs and a few weeks, you could probably calculate the phonon dispersion relation for one material. The whole community really wants a more efficient way to do this,” says Okabe.The machine-learning models scientists often use for these calculations are known as graph neural networks (GNN). A GNN converts a material’s atomic structure into a crystal graph comprising multiple nodes, which represent atoms, connected by edges, which represent the interatomic bonding between atoms.While GNNs work well for calculating many quantities, like magnetization or electrical polarization, they are not flexible enough to efficiently predict an extremely high-dimensional quantity like the phonon dispersion relation. Because phonons can travel around atoms on X, Y, and Z axes, their momentum space is hard to model with a fixed graph structure.To gain the flexibility they needed, Li and his collaborators devised virtual nodes.They create what they call a virtual node graph neural network (VGNN) by adding a series of flexible virtual nodes to the fixed crystal structure to represent phonons. The virtual nodes enable the output of the neural network to vary in size, so it is not restricted by the fixed crystal structure.Virtual nodes are connected to the graph in such a way that they can only receive messages from real nodes. While virtual nodes will be updated as the model updates real nodes during computation, they do not affect the accuracy of the model.“The way we do this is very efficient in coding. You just generate a few more nodes in your GNN. The physical location doesn’t matter, and the real nodes don’t even know the virtual nodes are there,” says Chotrattanapituk.Cutting out complexitySince it has virtual nodes to represent phonons, the VGNN can skip many complex calculations when estimating phonon dispersion relations, which makes the method more efficient than a standard GNN. The researchers proposed three different versions of VGNNs with increasing complexity. Each can be used to predict phonons directly from a material’s atomic coordinates.Because their approach has the flexibility to rapidly model high-dimensional properties, they can use it to estimate phonon dispersion relations in alloy systems. These complex combinations of metals and nonmetals are especially challenging for traditional approaches to model.The researchers also found that VGNNs offered slightly greater accuracy when predicting a material’s heat capacity. In some instances, prediction errors were two orders of magnitude lower with their technique.A VGNN could be used to calculate phonon dispersion relations for a few thousand materials in just a few seconds with a personal computer, Li says.This efficiency could enable scientists to search a larger space when seeking materials with certain thermal properties, such as superior thermal storage, energy conversion, or superconductivity.Moreover, the virtual node technique is not exclusive to phonons, and could also be used to predict challenging optical and magnetic properties.In the future, the researchers want to refine the technique so virtual nodes have greater sensitivity to capture small changes that can affect phonon structure.“Researchers got too comfortable using graph nodes to represent atoms, but we can rethink that. Graph nodes can be anything. And virtual nodes are a very generic approach you could use to predict a lot of high-dimensional quantities,” Li says.“The authors’ innovative approach significantly augments the graph neural network description of solids by incorporating key physics-informed elements through virtual nodes, for instance, informing wave-vector dependent band-structures and dynamical matrices,” says Olivier Delaire, associate professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University, who was not involved with this work. “I find that the level of acceleration in predicting complex phonon properties is amazing, several orders of magnitude faster than a state-of-the-art universal machine-learning interatomic potential. Impressively, the advanced neural net captures fine features and obeys physical rules. There is great potential to expand the model to describe other important material properties: Electronic, optical, and magnetic spectra and band structures come to mind.”This work is supported by the U.S. Department of Energy, National Science Foundation, a Mathworks Fellowship, a Sow-Hsin Chen Fellowship, the Harvard Quantum Initiative, and the Oak Ridge National Laboratory. More

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      in Environment

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

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

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      Study: Weaker ocean circulation could enhance CO2 buildup in the atmosphere

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      As climate change advances, the ocean’s overturning circulation is predicted to weaken substantially. With such a slowdown, scientists estimate the ocean will pull down less carbon dioxide from the atmosphere. However, a slower circulation should also dredge up less carbon from the deep ocean that would otherwise be released back into the atmosphere. On balance, the ocean should maintain its role in reducing carbon emissions from the atmosphere, if at a slower pace.However, a new study by an MIT researcher finds that scientists may have to rethink the relationship between the ocean’s circulation and its long-term capacity to store carbon. As the ocean gets weaker, it could release more carbon from the deep ocean into the atmosphere instead.The reason has to do with a previously uncharacterized feedback between the ocean’s available iron, upwelling carbon and nutrients, surface microorganisms, and a little-known class of molecules known generally as “ligands.” When the ocean circulates more slowly, all these players interact in a self-perpetuating cycle that ultimately increases the amount of carbon that the ocean outgases back to the atmosphere.“By isolating the impact of this feedback, we see a fundamentally different relationship between ocean circulation and atmospheric carbon levels, with implications for the climate,” says study author Jonathan Lauderdale, a research scientist in MIT’s Department of Earth, Atmospheric, and Planetary Sciences. “What we thought is going on in the ocean is completely overturned.”Lauderdale says the findings show that “we can’t count on the ocean to store carbon in the deep ocean in response to future changes in circulation. We must be proactive in cutting emissions now, rather than relying on these natural processes to buy us time to mitigate climate change.”His study appears today in the journal Nature Communications.Box flowIn 2020, Lauderdale led a study that explored ocean nutrients, marine organisms, and iron, and how their interactions influence the growth of phytoplankton around the world. Phytoplankton are microscopic, plant-like organisms that live on the ocean surface and consume a diet of carbon and nutrients that upwell from the deep ocean and iron that drifts in from desert dust.The more phytoplankton that can grow, the more carbon dioxide they can absorb from the atmosphere via photosynthesis, and this plays a large role in the ocean’s ability to sequester carbon.For the 2020 study, the team developed a simple “box” model, representing conditions in different parts of the ocean as general boxes, each with a different balance of nutrients, iron, and ligands — organic molecules that are thought to be byproducts of phytoplankton. The team modeled a general flow between the boxes to represent the ocean’s larger circulation — the way seawater sinks, then is buoyed back up to the surface in different parts of the world.This modeling revealed that, even if scientists were to “seed” the oceans with extra iron, that iron wouldn’t have much of an effect on global phytoplankton growth. The reason was due to a limit set by ligands. It turns out that, if left on its own, iron is insoluble in the ocean and therefore unavailable to phytoplankton. Iron only becomes soluble at “useful” levels when linked with ligands, which keep iron in a form that plankton can consume. Lauderdale found that adding iron to one ocean region to consume additional nutrients robs other regions of nutrients that phytoplankton there need to grow. This lowers the production of ligands and the supply of iron back to the original ocean region, limiting the amount of extra carbon that would be taken up from the atmosphere.Unexpected switchOnce the team published their study, Lauderdale worked the box model into a form that he could make publicly accessible, including ocean and atmosphere carbon exchange and extending the boxes to represent more diverse environments, such as conditions similar to the Pacific, the North Atlantic, and the Southern Ocean. In the process, he tested other interactions within the model, including the effect of varying ocean circulation.He ran the model with different circulation strengths, expecting to see less atmospheric carbon dioxide with weaker ocean overturning — a relationship that previous studies have supported, dating back to the 1980s. But what he found instead was a clear and opposite trend: The weaker the ocean’s circulation, the more CO2 built up in the atmosphere.“I thought there was some mistake,” Lauderdale recalls. “Why were atmospheric carbon levels trending the wrong way?”When he checked the model, he found that the parameter describing ocean ligands had been left “on” as a variable. In other words, the model was calculating ligand concentrations as changing from one ocean region to another.On a hunch, Lauderdale turned this parameter “off,” which set ligand concentrations as constant in every modeled ocean environment, an assumption that many ocean models typically make. That one change reversed the trend, back to the assumed relationship: A weaker circulation led to reduced atmospheric carbon dioxide. But which trend was closer to the truth?Lauderdale looked to the scant available data on ocean ligands to see whether their concentrations were more constant or variable in the actual ocean. He found confirmation in GEOTRACES, an international study that coordinates measurements of trace elements and isotopes across the world’s oceans, that scientists can use to compare concentrations from region to region. Indeed, the molecules’ concentrations varied. If ligand concentrations do change from one region to another, then his surprise new result was likely representative of the real ocean: A weaker circulation leads to more carbon dioxide in the atmosphere.“It’s this one weird trick that changed everything,” Lauderdale says. “The ligand switch has revealed this completely different relationship between ocean circulation and atmospheric CO2 that we thought we understood pretty well.”Slow cycleTo see what might explain the overturned trend, Lauderdale analyzed biological activity and carbon, nutrient, iron, and ligand concentrations from the ocean model under different circulation strengths, comparing scenarios where ligands were variable or constant across the various boxes.This revealed a new feedback: The weaker the ocean’s circulation, the less carbon and nutrients the ocean pulls up from the deep. Any phytoplankton at the surface would then have fewer resources to grow and would produce fewer byproducts (including ligands) as a result. With fewer ligands available, less iron at the surface would be usable, further reducing the phytoplankton population. There would then be fewer phytoplankton available to absorb carbon dioxide from the atmosphere and consume upwelled carbon from the deep ocean.“My work shows that we need to look more carefully at how ocean biology can affect the climate,” Lauderdale points out. “Some climate models predict a 30 percent slowdown in the ocean circulation due to melting ice sheets, particularly around Antarctica. This huge slowdown in overturning circulation could actually be a big problem: In addition to a host of other climate issues, not only would the ocean take up less anthropogenic CO2 from the atmosphere, but that could be amplified by a net outgassing of deep ocean carbon, leading to an unanticipated increase in atmospheric CO2 and unexpected further climate warming.”  More

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      in Environment

      How to increase the rate of plastics recycling

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      While recycling systems and bottle deposits have become increasingly widespread in the U.S., actual rates of recycling are “abysmal,” according to a team of MIT researchers who studied the rates for recycling of PET, the plastic commonly used in beverage bottles. However, their findings suggest some ways to change this.The present rate of recycling for PET, or polyethylene terephthalate, bottles nationwide is about 24 percent and has remained stagnant for a decade, the researchers say. But their study indicates that with a nationwide bottle deposit program, the rates could increase to 82 percent, with nearly two-thirds of all PET bottles being recycled into new bottles, at a net cost of just a penny a bottle when demand is robust. At the same time, they say, policies would be needed to ensure a sufficient demand for the recycled material.The findings are being published today in the Journal of Industrial Ecology, in a paper by MIT professor of materials science and engineering Elsa Olivetti, graduate students Basuhi Ravi and Karan Bhuwalka, and research scientist Richard Roth.The team looked at PET bottle collection and recycling rates in different states as well as other nations with and without bottle deposit policies, and with or without curbside recycling programs, as well as the inputs and outputs of various recycling companies and methods. The researchers say this study is the first to look in detail at the interplay between public policies and the end-to-end realities of the packaging production and recycling market.They found that bottle deposit programs are highly effective in the areas where they are in place, but at present there is not nearly enough collection of used bottles to meet the targets set by the packaging industry. Their analysis suggests that a uniform nationwide bottle deposit policy could achieve the levels of recycling that have been mandated by proposed legislation and corporate commitments.The recycling of PET is highly successful in terms of quality, with new products made from all-recycled material virtually matching the qualities of virgin material. And brands have shown that new bottles can be safely made with 100 percent postconsumer waste. But the team found that collection of the material is a crucial bottleneck that leaves processing plants unable to meet their needs. However, with the right policies in place, “one can be optimistic,” says Olivetti, who is the Jerry McAfee Professor in Engineering and the associate dean of the School of Engineering.“A message that we have found in a number of cases in the recycling space is that if you do the right work to support policies that think about both the demand but also the supply,” then significant improvements are possible, she says. “You have to think about the response and the behavior of multiple actors in the system holistically to be viable,” she says. “We are optimistic, but there are many ways to be pessimistic if we’re not thinking about that in a holistic way.”For example, the study found that it is important to consider the needs of existing municipal waste-recovery facilities. While expanded bottle deposit programs are essential to increase recycling rates and provide the feedstock to companies recycling PET into new products, the current facilities that process material from curbside recycling programs will lose revenue from PET bottles, which are a relatively high-value product compared to the other materials in the recycled waste stream. These companies would lose a source of their income if the bottles are collected through deposit programs, leaving them with only the lower-value mixed plastics.The researchers developed economic models based on rates of collection found in the states with deposit programs, recycled-content requirements, and other policies, and used these models to extrapolate to the nation as a whole. Overall, they found that the supply needs of packaging producers could be met through a nationwide bottle deposit system with a 10-cent deposit per bottle — at a net cost of about 1 cent per bottle produced when demand is strong. This need not be a federal program, but rather one where the implementation would be left up to the individual states, Olivetti says.Other countries have been much more successful in implementing deposit systems that result in very high participation rates. Several European countries manage to collect more than 90 percent of PET bottles for recycling, for example. But in the U.S., less than 29 percent are collected, and after losses in the recycling chain about 24 percent actually get recycled, the researchers found. Whereas 73 percent of Americans have access to curbside recycling, presently only 10 states have bottle deposit systems in place.Yet the demand is there so far. “There is a market for this material,” says Olivetti. While bottles collected through mixed-waste collection can still be recycled to some extent, those collected through deposit systems tend to be much cleaner and require less processing, and so are more economical to recycle into new bottles, or into textiles.To be effective, policies need to not just focus on increasing rates of recycling, but on the whole cycle of supply and demand and the different players involved, Olivetti says. Safeguards would need to be in place to protect existing recycling facilities from the lost revenues they would suffer as a result of bottle deposits, perhaps in the form of subsidies funded by fees on the bottle producers, to avoid putting these essential parts of the processing chain out of business. And other policies may be needed to ensure the continued market for the material that gets collected, including recycled content requirements and extended producer responsibility regulations, the team found.At this stage, it’s important to focus on the specific waste streams that can most effectively be recycled, and PET, along with many metals, clearly fit that category. “When we start to think about mixed plastic streams, that’s much more challenging from an environmental perspective,” she says. “Recycling systems need to be pursuing extended producers’ responsibility, or specifically thinking about materials designed more effectively toward recycled content,” she says.It’s also important to address “what the right metrics are to design for sustainably managed materials streams,” she says. “It could be energy use, could be circularity [for example, making old bottles into new bottles], could be around waste reduction, and making sure those are all aligned. That’s another kind of policy coordination that’s needed.” More

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      in Environment

      Making climate models relevant for local decision-makers

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      Climate models are a key technology in predicting the impacts of climate change. By running simulations of the Earth’s climate, scientists and policymakers can estimate conditions like sea level rise, flooding, and rising temperatures, and make decisions about how to appropriately respond. But current climate models struggle to provide this information quickly or affordably enough to be useful on smaller scales, such as the size of a city. Now, authors of a new open-access paper published in the Journal of Advances in Modeling Earth Systems have found a method to leverage machine learning to utilize the benefits of current climate models, while reducing the computational costs needed to run them. “It turns the traditional wisdom on its head,” says Sai Ravela, a principal research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS) who wrote the paper with EAPS postdoc Anamitra Saha. Traditional wisdomIn climate modeling, downscaling is the process of using a global climate model with coarse resolution to generate finer details over smaller regions. Imagine a digital picture: A global model is a large picture of the world with a low number of pixels. To downscale, you zoom in on just the section of the photo you want to look at — for example, Boston. But because the original picture was low resolution, the new version is blurry; it doesn’t give enough detail to be particularly useful. “If you go from coarse resolution to fine resolution, you have to add information somehow,” explains Saha. Downscaling attempts to add that information back in by filling in the missing pixels. “That addition of information can happen two ways: Either it can come from theory, or it can come from data.” Conventional downscaling often involves using models built on physics (such as the process of air rising, cooling, and condensing, or the landscape of the area), and supplementing it with statistical data taken from historical observations. But this method is computationally taxing: It takes a lot of time and computing power to run, while also being expensive. A little bit of both In their new paper, Saha and Ravela have figured out a way to add the data another way. They’ve employed a technique in machine learning called adversarial learning. It uses two machines: One generates data to go into our photo. But the other machine judges the sample by comparing it to actual data. If it thinks the image is fake, then the first machine has to try again until it convinces the second machine. The end-goal of the process is to create super-resolution data. Using machine learning techniques like adversarial learning is not a new idea in climate modeling; where it currently struggles is its inability to handle large amounts of basic physics, like conservation laws. The researchers discovered that simplifying the physics going in and supplementing it with statistics from the historical data was enough to generate the results they needed. “If you augment machine learning with some information from the statistics and simplified physics both, then suddenly, it’s magical,” says Ravela. He and Saha started with estimating extreme rainfall amounts by removing more complex physics equations and focusing on water vapor and land topography. They then generated general rainfall patterns for mountainous Denver and flat Chicago alike, applying historical accounts to correct the output. “It’s giving us extremes, like the physics does, at a much lower cost. And it’s giving us similar speeds to statistics, but at much higher resolution.” Another unexpected benefit of the results was how little training data was needed. “The fact that that only a little bit of physics and little bit of statistics was enough to improve the performance of the ML [machine learning] model … was actually not obvious from the beginning,” says Saha. It only takes a few hours to train, and can produce results in minutes, an improvement over the months other models take to run. Quantifying risk quicklyBeing able to run the models quickly and often is a key requirement for stakeholders such as insurance companies and local policymakers. Ravela gives the example of Bangladesh: By seeing how extreme weather events will impact the country, decisions about what crops should be grown or where populations should migrate to can be made considering a very broad range of conditions and uncertainties as soon as possible.“We can’t wait months or years to be able to quantify this risk,” he says. “You need to look out way into the future and at a large number of uncertainties to be able to say what might be a good decision.”While the current model only looks at extreme precipitation, training it to examine other critical events, such as tropical storms, winds, and temperature, is the next step of the project. With a more robust model, Ravela is hoping to apply it to other places like Boston and Puerto Rico as part of a Climate Grand Challenges project.“We’re very excited both by the methodology that we put together, as well as the potential applications that it could lead to,” he says.  More