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    How light can vaporize water without the need for heat

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    It’s the most fundamental of processes — the evaporation of water from the surfaces of oceans and lakes, the burning off of fog in the morning sun, and the drying of briny ponds that leaves solid salt behind. Evaporation is all around us, and humans have been observing it and making use of it for as long as we have existed.

    And yet, it turns out, we’ve been missing a major part of the picture all along.

    In a series of painstakingly precise experiments, a team of researchers at MIT has demonstrated that heat isn’t alone in causing water to evaporate. Light, striking the water’s surface where air and water meet, can break water molecules away and float them into the air, causing evaporation in the absence of any source of heat.

    The astonishing new discovery could have a wide range of significant implications. It could help explain mysterious measurements over the years of how sunlight affects clouds, and therefore affect calculations of the effects of climate change on cloud cover and precipitation. It could also lead to new ways of designing industrial processes such as solar-powered desalination or drying of materials.

    The findings, and the many different lines of evidence that demonstrate the reality of the phenomenon and the details of how it works, are described today in the journal PNAS, in a paper by Carl Richard Soderberg Professor of Power Engineering Gang Chen, postdocs Guangxin Lv and Yaodong Tu, and graduate student James Zhang.

    The authors say their study suggests that the effect should happen widely in nature— everywhere from clouds to fogs to the surfaces of oceans, soils, and plants — and that it could also lead to new practical applications, including in energy and clean water production. “I think this has a lot of applications,” Chen says. “We’re exploring all these different directions. And of course, it also affects the basic science, like the effects of clouds on climate, because clouds are the most uncertain aspect of climate models.”

    A newfound phenomenon

    The new work builds on research reported last year, which described this new “photomolecular effect” but only under very specialized conditions: on the surface of specially prepared hydrogels soaked with water. In the new study, the researchers demonstrate that the hydrogel is not necessary for the process; it occurs at any water surface exposed to light, whether it’s a flat surface like a body of water or a curved surface like a droplet of cloud vapor.

    Because the effect was so unexpected, the team worked to prove its existence with as many different lines of evidence as possible. In this study, they report 14 different kinds of tests and measurements they carried out to establish that water was indeed evaporating — that is, molecules of water were being knocked loose from the water’s surface and wafted into the air — due to the light alone, not by heat, which was long assumed to be the only mechanism involved.

    One key indicator, which showed up consistently in four different kinds of experiments under different conditions, was that as the water began to evaporate from a test container under visible light, the air temperature measured above the water’s surface cooled down and then leveled off, showing that thermal energy was not the driving force behind the effect.

    Other key indicators that showed up included the way the evaporation effect varied depending on the angle of the light, the exact color of the light, and its polarization. None of these varying characteristics should happen because at these wavelengths, water hardly absorbs light at all — and yet the researchers observed them.

    The effect is strongest when light hits the water surface at an angle of 45 degrees. It is also strongest with a certain type of polarization, called transverse magnetic polarization. And it peaks in green light — which, oddly, is the color for which water is most transparent and thus interacts the least.

    Chen and his co-researchers have proposed a physical mechanism that can explain the angle and polarization dependence of the effect, showing that the photons of light can impart a net force on water molecules at the water surface that is sufficient to knock them loose from the body of water. But they cannot yet account for the color dependence, which they say will require further study.

    They have named this the photomolecular effect, by analogy with the photoelectric effect that was discovered by Heinrich Hertz in 1887 and finally explained by Albert Einstein in 1905. That effect was one of the first demonstrations that light also has particle characteristics, which had major implications in physics and led to a wide variety of applications, including LEDs. Just as the photoelectric effect liberates electrons from atoms in a material in response to being hit by a photon of light, the photomolecular effect shows that photons can liberate entire molecules from a liquid surface, the researchers say.

    “The finding of evaporation caused by light instead of heat provides new disruptive knowledge of light-water interaction,” says Xiulin Ruan, professor of mechanical engineering at Purdue University, who was not involved in the study. “It could help us gain new understanding of how sunlight interacts with cloud, fog, oceans, and other natural water bodies to affect weather and climate. It has significant potential practical applications such as high-performance water desalination driven by solar energy. This research is among the rare group of truly revolutionary discoveries which are not widely accepted by the community right away but take time, sometimes a long time, to be confirmed.”

    Solving a cloud conundrum

    The finding may solve an 80-year-old mystery in climate science. Measurements of how clouds absorb sunlight have often shown that they are absorbing more sunlight than conventional physics dictates possible. The additional evaporation caused by this effect could account for the longstanding discrepancy, which has been a subject of dispute since such measurements are difficult to make.

    “Those experiments are based on satellite data and flight data,“ Chen explains. “They fly an airplane on top of and below the clouds, and there are also data based on the ocean temperature and radiation balance. And they all conclude that there is more absorption by clouds than theory could calculate. However, due to the complexity of clouds and the difficulties of making such measurements, researchers have been debating whether such discrepancies are real or not. And what we discovered suggests that hey, there’s another mechanism for cloud absorption, which was not accounted for, and this mechanism might explain the discrepancies.”

    Chen says he recently spoke about the phenomenon at an American Physical Society conference, and one physicist there who studies clouds and climate said they had never thought about this possibility, which could affect calculations of the complex effects of clouds on climate. The team conducted experiments using LEDs shining on an artificial cloud chamber, and they observed heating of the fog, which was not supposed to happen since water does not absorb in the visible spectrum. “Such heating can be explained based on the photomolecular effect more easily,” he says.

    Lv says that of the many lines of evidence, “the flat region in the air-side temperature distribution above hot water will be the easiest for people to reproduce.” That temperature profile “is a signature” that demonstrates the effect clearly, he says.

    Zhang adds: “It is quite hard to explain how this kind of flat temperature profile comes about without invoking some other mechanism” beyond the accepted theories of thermal evaporation. “It ties together what a whole lot of people are reporting in their solar desalination devices,” which again show evaporation rates that cannot be explained by the thermal input.

    The effect can be substantial. Under the optimum conditions of color, angle, and polarization, Lv says, “the evaporation rate is four times the thermal limit.”

    Already, since publication of the first paper, the team has been approached by companies that hope to harness the effect, Chen says, including for evaporating syrup and drying paper in a paper mill. The likeliest first applications will come in the areas of solar desalinization systems or other industrial drying processes, he says. “Drying consumes 20 percent of all industrial energy usage,” he points out.

    Because the effect is so new and unexpected, Chen says, “This phenomenon should be very general, and our experiment is really just the beginning.” The experiments needed to demonstrate and quantify the effect are very time-consuming. “There are many variables, from understanding water itself, to extending to other materials, other liquids and even solids,” he says.

    “The observations in the manuscript points to a new physical mechanism that foundationally alters our thinking on the kinetics of evaporation,” says Shannon Yee, an associate professor of mechanical engineering at Georgia Tech, who was not associated with this work. He adds, “Who would have thought that we are still learning about something as quotidian as water evaporating?”

    “I think this work is very significant scientifically because it presents a new mechanism,” says University of Alberta Distinguished Professor Janet A.W. Elliott, who also was not associated with this work. “It may also turn out to be practically important for technology and our understanding of nature, because evaporation of water is ubiquitous and the effect appears to deliver significantly higher evaporation rates than the known thermal mechanism. …  My overall impression is this work is outstanding. It appears to be carefully done with many precise experiments lending support for one another.”

    The work was partly supported by an MIT Bose Award. More

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      in Environment

      Advancing technology for aquaculture

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      According to the National Oceanic and Atmospheric Administration, aquaculture in the United States represents a $1.5 billion industry annually. Like land-based farming, shellfish aquaculture requires healthy seed production in order to maintain a sustainable industry. Aquaculture hatchery production of shellfish larvae — seeds — requires close monitoring to track mortality rates and assess health from the earliest stages of life. 

      Careful observation is necessary to inform production scheduling, determine effects of naturally occurring harmful bacteria, and ensure sustainable seed production. This is an essential step for shellfish hatcheries but is currently a time-consuming manual process prone to human error. 

      With funding from MIT’s Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), MIT Sea Grant is working with Associate Professor Otto Cordero of the MIT Department of Civil and Environmental Engineering, Professor Taskin Padir and Research Scientist Mark Zolotas at the Northeastern University Institute for Experiential Robotics, and others at the Aquaculture Research Corporation (ARC), and the Cape Cod Commercial Fishermen’s Alliance, to advance technology for the aquaculture industry. Located on Cape Cod, ARC is a leading shellfish hatchery, farm, and wholesaler that plays a vital role in providing high-quality shellfish seed to local and regional growers.

      Two MIT students have joined the effort this semester, working with Robert Vincent, MIT Sea Grant’s assistant director of advisory services, through the Undergraduate Research Opportunities Program (UROP). 

      First-year student Unyime Usua and sophomore Santiago Borrego are using microscopy images of shellfish seed from ARC to train machine learning algorithms that will help automate the identification and counting process. The resulting user-friendly image recognition tool aims to aid aquaculturists in differentiating and counting healthy, unhealthy, and dead shellfish larvae, improving accuracy and reducing time and effort.

      Vincent explains that AI is a powerful tool for environmental science that enables researchers, industry, and resource managers to address challenges that have long been pinch points for accurate data collection, analysis, predictions, and streamlining processes. “Funding support from programs like J-WAFS enable us to tackle these problems head-on,” he says. 

      ARC faces challenges with manually quantifying larvae classes, an important step in their seed production process. “When larvae are in their growing stages they are constantly being sized and counted,” explains Cheryl James, ARC larval/juvenile production manager. “This process is critical to encourage optimal growth and strengthen the population.” 

      Developing an automated identification and counting system will help to improve this step in the production process with time and cost benefits. “This is not an easy task,” says Vincent, “but with the guidance of Dr. Zolotas at the Northeastern University Institute for Experiential Robotics and the work of the UROP students, we have made solid progress.” 

      The UROP program benefits both researchers and students. Involving MIT UROP students in developing these types of systems provides insights into AI applications that they might not have considered, providing opportunities to explore, learn, and apply themselves while contributing to solving real challenges.

      Borrego saw this project as an opportunity to apply what he’d learned in class 6.390 (Introduction to Machine Learning) to a real-world issue. “I was starting to form an idea of how computers can see images and extract information from them,” he says. “I wanted to keep exploring that.”

      Usua decided to pursue the project because of the direct industry impacts it could have. “I’m pretty interested in seeing how we can utilize machine learning to make people’s lives easier. We are using AI to help biologists make this counting and identification process easier.” While Usua wasn’t familiar with aquaculture before starting this project, she explains, “Just hearing about the hatcheries that Dr. Vincent was telling us about, it was unfortunate that not a lot of people know what’s going on and the problems that they’re facing.”

      On Cape Cod alone, aquaculture is an $18 million per year industry. But the Massachusetts Division of Marine Fisheries estimates that hatcheries are only able to meet 70–80 percent of seed demand annually, which impacts local growers and economies. Through this project, the partners aim to develop technology that will increase seed production, advance industry capabilities, and help understand and improve the hatchery microbiome.

      Borrego explains the initial challenge of having limited data to work with. “Starting out, we had to go through and label all of the data, but going through that process helped me learn a lot.” In true MIT fashion, he shares his takeaway from the project: “Try to get the best out of what you’re given with the data you have to work with. You’re going to have to adapt and change your strategies depending on what you have.”

      Usua describes her experience going through the research process, communicating in a team, and deciding what approaches to take. “Research is a difficult and long process, but there is a lot to gain from it because it teaches you to look for things on your own and find your own solutions to problems.”

      In addition to increasing seed production and reducing the human labor required in the hatchery process, the collaborators expect this project to contribute to cost savings and technology integration to support one of the most underserved industries in the United States. 

      Borrego and Usua both plan to continue their work for a second semester with MIT Sea Grant. Borrego is interested in learning more about how technology can be used to protect the environment and wildlife. Usua says she hopes to explore more projects related to aquaculture. “It seems like there’s an infinite amount of ways to tackle these issues.” More

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      in Energy

      Extracting hydrogen from rocks

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      It’s commonly thought that the most abundant element in the universe, hydrogen, exists mainly alongside other elements — with oxygen in water, for example, and with carbon in methane. But naturally occurring underground pockets of pure hydrogen are punching holes in that notion — and generating attention as a potentially unlimited source of carbon-free power. One interested party is the U.S. Department of Energy, which last month awarded $20 million in research grants to 18 teams from laboratories, universities, and private companies to develop technologies that can lead to cheap, clean fuel from the subsurface. Geologic hydrogen, as it’s known, is produced when water reacts with iron-rich rocks, causing the iron to oxidize. One of the grant recipients, MIT Assistant Professor Iwnetim Abate’s research group, will use its $1.3 million grant to determine the ideal conditions for producing hydrogen underground — considering factors such as catalysts to initiate the chemical reaction, temperature, pressure, and pH levels. The goal is to improve efficiency for large-scale production, meeting global energy needs at a competitive cost. The U.S. Geological Survey estimates there are potentially billions of tons of geologic hydrogen buried in the Earth’s crust. Accumulations have been discovered worldwide, and a slew of startups are searching for extractable deposits. Abate is looking to jump-start the natural hydrogen production process, implementing “proactive” approaches that involve stimulating production and harvesting the gas.                                                                                                                         “We aim to optimize the reaction parameters to make the reaction faster and produce hydrogen in an economically feasible manner,” says Abate, the Chipman Development Professor in the Department of Materials Science and Engineering (DMSE). Abate’s research centers on designing materials and technologies for the renewable energy transition, including next-generation batteries and novel chemical methods for energy storage. 

      Sparking innovation

      Interest in geologic hydrogen is growing at a time when governments worldwide are seeking carbon-free energy alternatives to oil and gas. In December, French President Emmanuel Macron said his government would provide funding to explore natural hydrogen. And in February, government and private sector witnesses briefed U.S. lawmakers on opportunities to extract hydrogen from the ground. Today commercial hydrogen is manufactured at $2 a kilogram, mostly for fertilizer and chemical and steel production, but most methods involve burning fossil fuels, which release Earth-heating carbon. “Green hydrogen,” produced with renewable energy, is promising, but at $7 per kilogram, it’s expensive. “If you get hydrogen at a dollar a kilo, it’s competitive with natural gas on an energy-price basis,” says Douglas Wicks, a program director at Advanced Research Projects Agency – Energy (ARPA-E), the Department of Energy organization leading the geologic hydrogen grant program. Recipients of the ARPA-E grants include Colorado School of Mines, Texas Tech University, and Los Alamos National Laboratory, plus private companies including Koloma, a hydrogen production startup that has received funding from Amazon and Bill Gates. The projects themselves are diverse, ranging from applying industrial oil and gas methods for hydrogen production and extraction to developing models to understand hydrogen formation in rocks. The purpose: to address questions in what Wicks calls a “total white space.” “In geologic hydrogen, we don’t know how we can accelerate the production of it, because it’s a chemical reaction, nor do we really understand how to engineer the subsurface so that we can safely extract it,” Wicks says. “We’re trying to bring in the best skills of each of the different groups to work on this under the idea that the ensemble should be able to give us good answers in a fairly rapid timeframe.” Geochemist Viacheslav Zgonnik, one of the foremost experts in the natural hydrogen field, agrees that the list of unknowns is long, as is the road to the first commercial projects. But he says efforts to stimulate hydrogen production — to harness the natural reaction between water and rock — present “tremendous potential.” “The idea is to find ways we can accelerate that reaction and control it so we can produce hydrogen on demand in specific places,” says Zgonnik, CEO and founder of Natural Hydrogen Energy, a Denver-based startup that has mineral leases for exploratory drilling in the United States. “If we can achieve that goal, it means that we can potentially replace fossil fuels with stimulated hydrogen.”

      “A full-circle moment”

      For Abate, the connection to the project is personal. As a child in his hometown in Ethiopia, power outages were a usual occurrence — the lights would be out three, maybe four days a week. Flickering candles or pollutant-emitting kerosene lamps were often the only source of light for doing homework at night. “And for the household, we had to use wood and charcoal for chores such as cooking,” says Abate. “That was my story all the way until the end of high school and before I came to the U.S. for college.” In 1987, well-diggers drilling for water in Mali in Western Africa uncovered a natural hydrogen deposit, causing an explosion. Decades later, Malian entrepreneur Aliou Diallo and his Canadian oil and gas company tapped the well and used an engine to burn hydrogen and power electricity in the nearby village. Ditching oil and gas, Diallo launched Hydroma, the world’s first hydrogen exploration enterprise. The company is drilling wells near the original site that have yielded high concentrations of the gas. “So, what used to be known as an energy-poor continent now is generating hope for the future of the world,” Abate says. “Learning about that was a full-circle moment for me. Of course, the problem is global; the solution is global. But then the connection with my personal journey, plus the solution coming from my home continent, makes me personally connected to the problem and to the solution.”

      Experiments that scale

      Abate and researchers in his lab are formulating a recipe for a fluid that will induce the chemical reaction that triggers hydrogen production in rocks. The main ingredient is water, and the team is testing “simple” materials for catalysts that will speed up the reaction and in turn increase the amount of hydrogen produced, says postdoc Yifan Gao. “Some catalysts are very costly and hard to produce, requiring complex production or preparation,” Gao says. “A catalyst that’s inexpensive and abundant will allow us to enhance the production rate — that way, we produce it at an economically feasible rate, but also with an economically feasible yield.” The iron-rich rocks in which the chemical reaction happens can be found across the United States and the world. To optimize the reaction across a diversity of geological compositions and environments, Abate and Gao are developing what they call a high-throughput system, consisting of artificial intelligence software and robotics, to test different catalyst mixtures and simulate what would happen when applied to rocks from various regions, with different external conditions like temperature and pressure. “And from that we measure how much hydrogen we are producing for each possible combination,” Abate says. “Then the AI will learn from the experiments and suggest to us, ‘Based on what I’ve learned and based on the literature, I suggest you test this composition of catalyst material for this rock.’” The team is writing a paper on its project and aims to publish its findings in the coming months. The next milestones for the project, after developing the catalyst recipe, is designing a reactor that will serve two purposes. First, fitted with technologies such as Raman spectroscopy, it will allow researchers to identify and optimize the chemical conditions that lead to improved rates and yield of hydrogen production. The lab-scale device will also inform the design of a real-world reactor that can accelerate hydrogen production in the field. “That would be a plant-scale reactor that would be implanted into the subsurface,” Abate says. The cross-disciplinary project is also tapping the expertise of Yang Shao-Horn, of MIT’s Department of Mechanical Engineering and DMSE, for computational analysis of the catalyst, and Esteban Gazel, a Cornell University scientist who will lend his expertise in geology and geochemistry. He’ll focus on understanding the iron-rich ultramafic rock formations across the United States and the globe and how they react with water. For Wicks at ARPA-E, the questions Abate and the other grant recipients are asking are just the first, critical steps in uncharted energy territory. “If we can understand how to stimulate these rocks into generating hydrogen, safely getting it up, it really unleashes the potential energy source,” he says. Then the emerging industry will look to oil and gas for the drilling, piping, and gas extraction know-how. “As I like to say, this is enabling technology that we hope to, in a very short term, enable us to say, ‘Is there really something there?’” More

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      in Environment

      MIT-derived algorithm helps forecast the frequency of extreme weather

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      To assess a community’s risk of extreme weather, policymakers rely first on global climate models that can be run decades, and even centuries, forward in time, but only at a coarse resolution. These models might be used to gauge, for instance, future climate conditions for the northeastern U.S., but not specifically for Boston.

      To estimate Boston’s future risk of extreme weather such as flooding, policymakers can combine a coarse model’s large-scale predictions with a finer-resolution model, tuned to estimate how often Boston is likely to experience damaging floods as the climate warms. But this risk analysis is only as accurate as the predictions from that first, coarser climate model.

      “If you get those wrong for large-scale environments, then you miss everything in terms of what extreme events will look like at smaller scales, such as over individual cities,” says Themistoklis Sapsis, the William I. Koch Professor and director of the Center for Ocean Engineering in MIT’s Department of Mechanical Engineering.

      Sapsis and his colleagues have now developed a method to “correct” the predictions from coarse climate models. By combining machine learning with dynamical systems theory, the team’s approach “nudges” a climate model’s simulations into more realistic patterns over large scales. When paired with smaller-scale models to predict specific weather events such as tropical cyclones or floods, the team’s approach produced more accurate predictions for how often specific locations will experience those events over the next few decades, compared to predictions made without the correction scheme.

      Play video

      This animation shows the evolution of storms around the northern hemisphere, as a result of a high-resolution storm model, combined with the MIT team’s corrected global climate model. The simulation improves the modeling of extreme values for wind, temperature, and humidity, which typically have significant errors in coarse scale models. Credit: Courtesy of Ruby Leung and Shixuan Zhang, PNNL

      Sapsis says the new correction scheme is general in form and can be applied to any global climate model. Once corrected, the models can help to determine where and how often extreme weather will strike as global temperatures rise over the coming years. 

      “Climate change will have an effect on every aspect of human life, and every type of life on the planet, from biodiversity to food security to the economy,” Sapsis says. “If we have capabilities to know accurately how extreme weather will change, especially over specific locations, it can make a lot of difference in terms of preparation and doing the right engineering to come up with solutions. This is the method that can open the way to do that.”

      The team’s results appear today in the Journal of Advances in Modeling Earth Systems. The study’s MIT co-authors include postdoc Benedikt Barthel Sorensen and Alexis-Tzianni Charalampopoulos SM ’19, PhD ’23, with Shixuan Zhang, Bryce Harrop, and Ruby Leung of the Pacific Northwest National Laboratory in Washington state.

      Over the hood

      Today’s large-scale climate models simulate weather features such as the average temperature, humidity, and precipitation around the world, on a grid-by-grid basis. Running simulations of these models takes enormous computing power, and in order to simulate how weather features will interact and evolve over periods of decades or longer, models average out features every 100 kilometers or so.

      “It’s a very heavy computation requiring supercomputers,” Sapsis notes. “But these models still do not resolve very important processes like clouds or storms, which occur over smaller scales of a kilometer or less.”

      To improve the resolution of these coarse climate models, scientists typically have gone under the hood to try and fix a model’s underlying dynamical equations, which describe how phenomena in the atmosphere and oceans should physically interact.

      “People have tried to dissect into climate model codes that have been developed over the last 20 to 30 years, which is a nightmare, because you can lose a lot of stability in your simulation,” Sapsis explains. “What we’re doing is a completely different approach, in that we’re not trying to correct the equations but instead correct the model’s output.”

      The team’s new approach takes a model’s output, or simulation, and overlays an algorithm that nudges the simulation toward something that more closely represents real-world conditions. The algorithm is based on a machine-learning scheme that takes in data, such as past information for temperature and humidity around the world, and learns associations within the data that represent fundamental dynamics among weather features. The algorithm then uses these learned associations to correct a model’s predictions.

      “What we’re doing is trying to correct dynamics, as in how an extreme weather feature, such as the windspeeds during a Hurricane Sandy event, will look like in the coarse model, versus in reality,” Sapsis says. “The method learns dynamics, and dynamics are universal. Having the correct dynamics eventually leads to correct statistics, for example, frequency of rare extreme events.”

      Climate correction

      As a first test of their new approach, the team used the machine-learning scheme to correct simulations produced by the Energy Exascale Earth System Model (E3SM), a climate model run by the U.S. Department of Energy, that simulates climate patterns around the world at a resolution of 110 kilometers. The researchers used eight years of past data for temperature, humidity, and wind speed to train their new algorithm, which learned dynamical associations between the measured weather features and the E3SM model. They then ran the climate model forward in time for about 36 years and applied the trained algorithm to the model’s simulations. They found that the corrected version produced climate patterns that more closely matched real-world observations from the last 36 years, not used for training.

      “We’re not talking about huge differences in absolute terms,” Sapsis says. “An extreme event in the uncorrected simulation might be 105 degrees Fahrenheit, versus 115 degrees with our corrections. But for humans experiencing this, that is a big difference.”

      When the team then paired the corrected coarse model with a specific, finer-resolution model of tropical cyclones, they found the approach accurately reproduced the frequency of extreme storms in specific locations around the world.

      “We now have a coarse model that can get you the right frequency of events, for the present climate. It’s much more improved,” Sapsis says. “Once we correct the dynamics, this is a relevant correction, even when you have a different average global temperature, and it can be used for understanding how forest fires, flooding events, and heat waves will look in a future climate. Our ongoing work is focusing on analyzing future climate scenarios.”

      “The results are particularly impressive as the method shows promising results on E3SM, a state-of-the-art climate model,” says Pedram Hassanzadeh, an associate professor who leads the Climate Extremes Theory and Data group at the University of Chicago and was not involved with the study. “It would be interesting to see what climate change projections this framework yields once future greenhouse-gas emission scenarios are incorporated.”

      This work was supported, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      Artificial reef designed by MIT engineers could protect marine life, reduce storm damage

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      The beautiful, gnarled, nooked-and-crannied reefs that surround tropical islands serve as a marine refuge and natural buffer against stormy seas. But as the effects of climate change bleach and break down coral reefs around the world, and extreme weather events become more common, coastal communities are left increasingly vulnerable to frequent flooding and erosion.

      An MIT team is now hoping to fortify coastlines with “architected” reefs — sustainable, offshore structures engineered to mimic the wave-buffering effects of natural reefs while also providing pockets for fish and other marine life.

      The team’s reef design centers on a cylindrical structure surrounded by four rudder-like slats. The engineers found that when this structure stands up against a wave, it efficiently breaks the wave into turbulent jets that ultimately dissipate most of the wave’s total energy. The team has calculated that the new design could reduce as much wave energy as existing artificial reefs, using 10 times less material.

      The researchers plan to fabricate each cylindrical structure from sustainable cement, which they would mold in a pattern of “voxels” that could be automatically assembled, and would provide pockets for fish to explore and other marine life to settle in. The cylinders could be connected to form a long, semipermeable wall, which the engineers could erect along a coastline, about half a mile from shore. Based on the team’s initial experiments with lab-scale prototypes, the architected reef could reduce the energy of incoming waves by more than 95 percent.

      “This would be like a long wave-breaker,” says Michael Triantafyllou, the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering. “If waves are 6 meters high coming toward this reef structure, they would be ultimately less than a meter high on the other side. So, this kills the impact of the waves, which could prevent erosion and flooding.”

      Details of the architected reef design are reported today in a study appearing in the open-access journal PNAS Nexus. Triantafyllou’s MIT co-authors are Edvard Ronglan SM ’23; graduate students Alfonso Parra Rubio, Jose del Auila Ferrandis, and Erik Strand; research scientists Patricia Maria Stathatou and Carolina Bastidas; and Professor Neil Gershenfeld, director of the Center for Bits and Atoms; along with Alexis Oliveira Da Silva at the Polytechnic Institute of Paris, Dixia Fan of Westlake University, and Jeffrey Gair Jr. of Scinetics, Inc.

      Leveraging turbulence

      Some regions have already erected artificial reefs to protect their coastlines from encroaching storms. These structures are typically sunken ships, retired oil and gas platforms, and even assembled configurations of concrete, metal, tires, and stones. However, there’s variability in the types of artificial reefs that are currently in place, and no standard for engineering such structures. What’s more, the designs that are deployed tend to have a low wave dissipation per unit volume of material used. That is, it takes a huge amount of material to break enough wave energy to adequately protect coastal communities.

      The MIT team instead looked for ways to engineer an artificial reef that would efficiently dissipate wave energy with less material, while also providing a refuge for fish living along any vulnerable coast.

      “Remember, natural coral reefs are only found in tropical waters,” says Triantafyllou, who is director of the MIT Sea Grant. “We cannot have these reefs, for instance, in Massachusetts. But architected reefs don’t depend on temperature, so they can be placed in any water, to protect more coastal areas.”

      MIT researchers test the wave-breaking performance of two artificial reef structures in the MIT Towing Tank.Credit: Courtesy of the researchers

      The new effort is the result of a collaboration between researchers in MIT Sea Grant, who developed the reef structure’s hydrodynamic design, and researchers at the Center for Bits and Atoms (CBA), who worked to make the structure modular and easy to fabricate on location. The team’s architected reef design grew out of two seemingly unrelated problems. CBA researchers were developing ultralight cellular structures for the aerospace industry, while Sea Grant researchers were assessing the performance of blowout preventers in offshore oil structures — cylindrical valves that are used to seal off oil and gas wells and prevent them from leaking.

      The team’s tests showed that the structure’s cylindrical arrangement generated a high amount of drag. In other words, the structure appeared to be especially efficient in dissipating high-force flows of oil and gas. They wondered: Could the same arrangement dissipate another type of flow, in ocean waves?

      The researchers began to play with the general structure in simulations of water flow, tweaking its dimensions and adding certain elements to see whether and how waves changed as they crashed against each simulated design. This iterative process ultimately landed on an optimized geometry: a vertical cylinder flanked by four long slats, each attached to the cylinder in a way that leaves space for water to flow through the resulting structure. They found this setup essentially breaks up any incoming wave energy, causing parts of the wave-induced flow to spiral to the sides rather than crashing ahead.

      “We’re leveraging this turbulence and these powerful jets to ultimately dissipate wave energy,” Ferrandis says.

      Standing up to storms

      Once the researchers identified an optimal wave-dissipating structure, they fabricated a laboratory-scale version of an architected reef made from a series of the cylindrical structures, which they 3D-printed from plastic. Each test cylinder measured about 1 foot wide and 4 feet tall. They assembled a number of cylinders, each spaced about a foot apart, to form a fence-like structure, which they then lowered into a wave tank at MIT. They then generated waves of various heights and measured them before and after passing through the architected reef.

      “We saw the waves reduce substantially, as the reef destroyed their energy,” Triantafyllou says.

      The team has also looked into making the structures more porous, and friendly to fish. They found that, rather than making each structure from a solid slab of plastic, they could use a more affordable and sustainable type of cement.

      “We’ve worked with biologists to test the cement we intend to use, and it’s benign to fish, and ready to go,” he adds.

      They identified an ideal pattern of “voxels,” or microstructures, that cement could be molded into, in order to fabricate the reefs while creating pockets in which fish could live. This voxel geometry resembles individual egg cartons, stacked end to end, and appears to not affect the structure’s overall wave-dissipating power.

      “These voxels still maintain a big drag while allowing fish to move inside,” Ferrandis says.

      The team is currently fabricating cement voxel structures and assembling them into a lab-scale architected reef, which they will test under various wave conditions. They envision that the voxel design could be modular, and scalable to any desired size, and easy to transport and install in various offshore locations. “Now we’re simulating actual sea patterns, and testing how these models will perform when we eventually have to deploy them,” says Anjali Sinha, a graduate student at MIT who recently joined the group.

      Going forward, the team hopes to work with beach towns in Massachusetts to test the structures on a pilot scale.

      “These test structures would not be small,” Triantafyllou emphasizes. “They would be about a mile long, and about 5 meters tall, and would cost something like 6 million dollars per mile. So it’s not cheap. But it could prevent billions of dollars in storm damage. And with climate change, protecting the coasts will become a big issue.”

      This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency. More

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      in Environment

      Reducing pesticide use while increasing effectiveness

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      Farming can be a low-margin, high-risk business, subject to weather and climate patterns, insect population cycles, and other unpredictable factors. Farmers need to be savvy managers of the many resources they deal, and chemical fertilizers and pesticides are among their major recurring expenses.

      Despite the importance of these chemicals, a lack of technology that monitors and optimizes sprays has forced farmers to rely on personal experience and rules of thumb to decide how to apply these chemicals. As a result, these chemicals tend to be over-sprayed, leading to their runoff into waterways and buildup up in the soil.

      That could change, thanks to a new approach of feedback-optimized spraying, invented by AgZen, an MIT spinout founded in 2020 by Professor Kripa Varanasi and Vishnu Jayaprakash SM ’19, PhD ’22.

      Play video

      AgZen has developed a system for farming that can monitor exactly how much of the sprayed chemicals adheres to plants, in real time, as the sprayer drives through a field. Built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray.

      Over the past decade, AgZen’s founders have developed products and technologies to control the interactions of droplets and sprays with plant surfaces. The Boston-based venture-backed company launched a new commercial product in 2024 and is currently piloting another related product. Field tests of both have shown the products can help farmers spray more efficiently and effectively, using fewer chemicals overall.

      “Worldwide, farms spend approximately $60 billion a year on pesticides. Our objective is to reduce the number of pesticides sprayed and lighten the financial burden on farms without sacrificing effective pest management,” Varanasi says.

      Getting droplets to stick

      While the world pesticide market is growing rapidly, a lot of the pesticides sprayed don’t reach their target. A significant portion bounces off the plant surfaces, lands on the ground, and becomes part of the runoff that flows to streams and rivers, often causing serious pollution. Some of these pesticides can be carried away by wind over very long distances.

      “Drift, runoff, and poor application efficiency are well-known, longstanding problems in agriculture, but we can fix this by controlling and monitoring how sprayed droplets interact with leaves,” Varanasi says.

      With support from MIT Tata Center and the Abdul Latif Jameel Water and Food Systems Lab, Varanasi and his team analyzed how droplets strike plant surfaces, and explored ways to increase application efficiency. This research led them to develop a novel system of nozzles that cloak droplets with compounds that enhance the retention of droplets on the leaves, a product they call EnhanceCoverage.

      Field studies across regions — from Massachusetts to California to Italy and France —showed that this droplet-optimization system could allow farmers to cut the amount of chemicals needed by more than half because more of the sprayed substances would stick to the leaves.

      Measuring coverage

      However, in trying to bring this technology to market, the researchers faced a sticky problem: Nobody knew how well pesticide sprays were adhering to the plants in the first place, so how could AgZen say that the coverage was better with its new EnhanceCoverage system?

      “I had grown up spraying with a backpack on a small farm in India, so I knew this was an issue,” Jayaprakash says. “When we spoke to growers, they told me how complicated spraying is when you’re on a large machine. Whenever you spray, there are so many things that can influence how effective your spray is. How fast do you drive the sprayer? What flow rate are you using for the chemicals? What chemical are you using? What’s the age of the plants, what’s the nozzle you’re using, what is the weather at the time? All these things influence agrochemical efficiency.”

      Agricultural spraying essentially comes down to dissolving a chemical in water and then spraying droplets onto the plants. “But the interaction between a droplet and the leaf is complex,” Varanasi says. “We were coming in with ways to optimize that, but what the growers told us is, hey, we’ve never even really looked at that in the first place.”

      Although farmers have been spraying agricultural chemicals on a large scale for about 80 years, they’ve “been forced to rely on general rules of thumb and pick all these interlinked parameters, based on what’s worked for them in the past. You pick a set of these parameters, you go spray, and you’re basically praying for outcomes in terms of how effective your pest control is,” Varanasi says.

      Before AgZen could sell farmers on the new system to improve droplet coverage, the company had to invent a way to measure precisely how much spray was adhering to plants in real-time.

      Comparing before and after

      The system they came up with, which they tested extensively on farms across the country last year, involves a unit that can be bolted onto the spraying arm of virtually any sprayer. It carries two sensor stacks, one just ahead of the sprayer nozzles and one behind. Then, built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray. It also computes how much those droplets will spread out or evaporate, leading to a precise estimate of the final coverage.

      “There’s a lot of physics that governs how droplets spread and evaporate, and this has been incorporated into software that a farmer can use,” Varanasi says. “We bring a lot of our expertise into understanding droplets on leaves. All these factors, like how temperature and humidity influence coverage, have always been nebulous in the spraying world. But now you have something that can be exact in determining how well your sprays are doing.”

      “We’re not only measuring coverage, but then we recommend how to act,” says Jayaprakash, who is AgZen’s CEO. “With the information we collect in real-time and by using AI, RealCoverage tells operators how to optimize everything on their sprayer, from which nozzle to use, to how fast to drive, to how many gallons of spray is best for a particular chemical mix on a particular acre of a crop.”

      The tool was developed to prove how much AgZen’s EnhanceCoverage nozzle system (which will be launched in 2025) improves coverage. But it turns out that monitoring and optimizing droplet coverage on leaves in real-time with this system can itself yield major improvements.

      “We worked with large commercial farms last year in specialty and row crops,” Jayaprakash says. “When we saved our pilot customers up to 50 percent of their chemical cost at a large scale, they were very surprised.” He says the tool has reduced chemical costs and volume in fallow field burndowns, weed control in soybeans, defoliation in cotton, and fungicide and insecticide sprays in vegetables and fruits. Along with data from commercial farms, field trials conducted by three leading agricultural universities have also validated these results.

      “Across the board, we were able to save between 30 and 50 percent on chemical costs and increase crop yields by enabling better pest control,” Jayaprakash says. “By focusing on the droplet-leaf interface, our product can help any foliage spray throughout the year, whereas most technological advancements in this space recently have been focused on reducing herbicide use alone.” The company now intends to lease the system across thousands of acres this year.

      And these efficiency gains can lead to significant returns at scale, he emphasizes: In the U.S., farmers currently spend $16 billion a year on chemicals, to protect about $200 billion of crop yields.

      The company launched its first product, the coverage optimization system called RealCoverage, this year, reaching a wide variety of farms with different crops and in different climates. “We’re going from proof-of-concept with pilots in large farms to a truly massive scale on a commercial basis with our lease-to-own program,” Jayaprakash says.

      “We’ve also been tapped by the USDA to help them evaluate practices to minimize pesticides in watersheds,” Varanasi says, noting that RealCoverage can also be useful for regulators, chemical companies, and agricultural equipment manufacturers.

      Once AgZen has proven the effectiveness of using coverage as a decision metric, and after the RealCoverage optimization system is widely in practice, the company will next roll out its second product, EnhanceCoverage, designed to maximize droplet adhesion. Because that system will require replacing all the nozzles on a sprayer, the researchers are doing pilots this year but will wait for a full rollout in 2025, after farmers have gained experience and confidence with their initial product.

      “There is so much wastage,” Varanasi says. “Yet farmers must spray to protect crops, and there is a lot of environmental impact from this. So, after all this work over the years, learning about how droplets stick to surfaces and so on, now the culmination of it in all these products for me is amazing, to see all this come alive, to see that we’ll finally be able to solve the problem we set out to solve and help farmers.” More

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      in Environment

      MIT researchers remotely map crops, field by field

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      Crop maps help scientists and policymakers track global food supplies and estimate how they might shift with climate change and growing populations. But getting accurate maps of the types of crops that are grown from farm to farm often requires on-the-ground surveys that only a handful of countries have the resources to maintain.

      Now, MIT engineers have developed a method to quickly and accurately label and map crop types without requiring in-person assessments of every single farm. The team’s method uses a combination of Google Street View images, machine learning, and satellite data to automatically determine the crops grown throughout a region, from one fraction of an acre to the next. 

      The researchers used the technique to automatically generate the first nationwide crop map of Thailand — a smallholder country where small, independent farms make up the predominant form of agriculture. The team created a border-to-border map of Thailand’s four major crops — rice, cassava, sugarcane, and maize — and determined which of the four types was grown, at every 10 meters, and without gaps, across the entire country. The resulting map achieved an accuracy of 93 percent, which the researchers say is comparable to on-the-ground mapping efforts in high-income, big-farm countries.

      The team is applying their mapping technique to other countries such as India, where small farms sustain most of the population but the type of crops grown from farm to farm has historically been poorly recorded.

      “It’s a longstanding gap in knowledge about what is grown around the world,” says Sherrie Wang, the d’Arbeloff Career Development Assistant Professor in MIT’s Department of Mechanical Engineering, and the Institute for Data, Systems, and Society (IDSS). “The final goal is to understand agricultural outcomes like yield, and how to farm more sustainably. One of the key preliminary steps is to map what is even being grown — the more granularly you can map, the more questions you can answer.”

      Wang, along with MIT graduate student Jordi Laguarta Soler and Thomas Friedel of the agtech company PEAT GmbH, will present a paper detailing their mapping method later this month at the AAAI Conference on Artificial Intelligence.

      Ground truth

      Smallholder farms are often run by a single family or farmer, who subsist on the crops and livestock that they raise. It’s estimated that smallholder farms support two-thirds of the world’s rural population and produce 80 percent of the world’s food. Keeping tabs on what is grown and where is essential to tracking and forecasting food supplies around the world. But the majority of these small farms are in low to middle-income countries, where few resources are devoted to keeping track of individual farms’ crop types and yields.

      Crop mapping efforts are mainly carried out in high-income regions such as the United States and Europe, where government agricultural agencies oversee crop surveys and send assessors to farms to label crops from field to field. These “ground truth” labels are then fed into machine-learning models that make connections between the ground labels of actual crops and satellite signals of the same fields. They then label and map wider swaths of farmland that assessors don’t cover but that satellites automatically do.

      “What’s lacking in low- and middle-income countries is this ground label that we can associate with satellite signals,” Laguarta Soler says. “Getting these ground truths to train a model in the first place has been limited in most of the world.”

      The team realized that, while many developing countries do not have the resources to maintain crop surveys, they could potentially use another source of ground data: roadside imagery, captured by services such as Google Street View and Mapillary, which send cars throughout a region to take continuous 360-degree images with dashcams and rooftop cameras.

      In recent years, such services have been able to access low- and middle-income countries. While the goal of these services is not specifically to capture images of crops, the MIT team saw that they could search the roadside images to identify crops.

      Cropped image

      In their new study, the researchers worked with Google Street View (GSV) images taken throughout Thailand — a country that the service has recently imaged fairly thoroughly, and which consists predominantly of smallholder farms.

      Starting with over 200,000 GSV images randomly sampled across Thailand, the team filtered out images that depicted buildings, trees, and general vegetation. About 81,000 images were crop-related. They set aside 2,000 of these, which they sent to an agronomist, who determined and labeled each crop type by eye. They then trained a convolutional neural network to automatically generate crop labels for the other 79,000 images, using various training methods, including iNaturalist — a web-based crowdsourced  biodiversity database, and GPT-4V, a “multimodal large language model” that enables a user to input an image and ask the model to identify what the image is depicting. For each of the 81,000 images, the model generated a label of one of four crops that the image was likely depicting — rice, maize, sugarcane, or cassava.

      The researchers then paired each labeled image with the corresponding satellite data taken of the same location throughout a single growing season. These satellite data include measurements across multiple wavelengths, such as a location’s greenness and its reflectivity (which can be a sign of water). 

      “Each type of crop has a certain signature across these different bands, which changes throughout a growing season,” Laguarta Soler notes.

      The team trained a second model to make associations between a location’s satellite data and its corresponding crop label. They then used this model to process satellite data taken of the rest of the country, where crop labels were not generated or available. From the associations that the model learned, it then assigned crop labels across Thailand, generating a country-wide map of crop types, at a resolution of 10 square meters.

      This first-of-its-kind crop map included locations corresponding to the 2,000 GSV images that the researchers originally set aside, that were labeled by arborists. These human-labeled images were used to validate the map’s labels, and when the team looked to see whether the map’s labels matched the expert, “gold standard” labels, it did so 93 percent of the time.

      “In the U.S., we’re also looking at over 90 percent accuracy, whereas with previous work in India, we’ve only seen 75 percent because ground labels are limited,” Wang says. “Now we can create these labels in a cheap and automated way.”

      The researchers are moving to map crops across India, where roadside images via Google Street View and other services have recently become available.

      “There are over 150 million smallholder farmers in India,” Wang says. “India is covered in agriculture, almost wall-to-wall farms, but very small farms, and historically it’s been very difficult to create maps of India because there are very sparse ground labels.”

      The team is working to generate crop maps in India, which could be used to inform policies having to do with assessing and bolstering yields, as global temperatures and populations rise.

      “What would be interesting would be to create these maps over time,” Wang says. “Then you could start to see trends, and we can try to relate those things to anything like changes in climate and policies.” More

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      in Environment

      K. Lisa Yang Global Engineering and Research Center will prioritize innovations for resource-constrained communities

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      Billions of people worldwide face threats to their livelihood, health, and well-being due to poverty. These problems persist because solutions offered in developed countries often do not meet the requirements — related to factors like price, performance, usability, robustness, and culture — of poor or developing countries. Academic labs frequently try to tackle these challenges, but often to no avail because they lack real-world, on-the-ground knowledge from key stakeholders, and because they do not have an efficient, reliable means of converting breakthroughs to real-world impact.

      The new K. Lisa Yang Global Engineering and Research (GEAR) Center at MIT, founded with a $28 million gift from philanthropist and investor Lisa Yang, aims to rethink how products and technologies for resource-constrained communities are conceived, designed, and commercialized. A collaboration between MIT’s School of Engineering and School of Science, the Yang GEAR Center will bring together a multidisciplinary team of MIT researchers to assess today’s most pressing global challenges in three critical areas: global health, climate change mitigation and adaptation, and the water-energy-food nexus.

      “As she has shown over and over through her philanthropy, Lisa Yang shares MIT’s passion for connecting fundamental research and real-world data to create positive impact,” says MIT president Sally Kornbluth. “I’m grateful for her powerful vision and incredible generosity in founding the K. Lisa Yang GEAR Center. I can’t imagine a better use of MIT’s talents than working to improve the lives and health of people around the world.”

      Yang’s gift expands her exceptional philanthropic support of human health and basic science research at MIT over the past six years. Yang GEAR Center will join MIT’s Yang Tan Collective, an assemblage of six major research centers focused on accelerating collaboration in basic science, research, and engineering to realize translational strategies that improve human health and well-being at a global scale.

      “Billions of people face daily life-or-death challenges that could be improved with elegant technologies,” says Yang. “And yet I’ve learned how many products and tools created by top engineers don’t make it out of the lab. They may look like clever ideas during the prototype phase, but they are entirely ill-suited to the communities they were designed for. I am very excited about the potential of a deliberate and thoughtful engineering effort that will prioritize the design of technologies for use in impoverished communities.”

      Cost, material availability, cultural suitability, and other market mismatches hinder many major innovations in global health, food, and water from being translated to use in resource-constrained communities. Yang GEAR Center will support a major research and design program with its mission to strategically identify compelling challenges and associated scientific knowledge gaps in resource-constrained communities then address them through academic innovation to create and translate transformative technologies.

      The center will be led by Amos Winter, associate professor of mechanical engineering, whose lab focuses on creating technologies that marry innovative, low-cost design with an in-depth understanding of the unique socioeconomic constraints of emerging markets.

      “Academia has a key role to play in solving the historically unsolvable challenges in resource-constrained communities,” says Winter. “However, academic research is often disconnected from the real-world requirements that must be satisfied to make meaningful change. Yang GEAR Center will be a catalyst for innovation to impact by helping colleagues identify compelling problems and focus their talents on realizing real-world solutions, and by providing mechanisms for commercial dissemination. I am extremely grateful to find in Lisa a partner who shares a vision for how academic research can play a more efficient and targeted role in addressing the needs of the world’s most disadvantaged populations.”

      The backbone of the Yang GEAR Center will be a team of seasoned research scientists and engineers. These individuals will scout real-world problems and distill the relevant research questions then help assemble collaborative teams. As projects develop, center staff will mentor students, build and conduct field pilots, and foster relationships with stakeholders around the world. They will be strategically positioned to translate technology at the end of projects through licensing and startups. Center staff and collaborators will focus on creating products and services for climate-driven migrants, such as solar-powered energy and water networks; technologies for reducing atmospheric carbon and promoting the hydrogen economy; brackish water desalination and irrigation solutions; and high-performance, global health diagnostics and devices.

      For instance, a Yang GEAR Center team focused on creating water-saving and solar-powered irrigation solutions for farmers in the Middle East and North Africa will continue its work in the region. They will conduct exploratory research; build a team of stakeholders, including farmers, agricultural outreach organizations, irrigation hardware manufacturers, retailers, water and agriculture scientists, and local government officials; design, rigorously test, and iterate prototypes both in the lab and in the field; and conduct large-scale field trials to garner user feedback and pave the way to product commercialization.

      “Grounded in foundational scientific research and blended with excellence in the humanities, MIT provides a framework that integrates people, economics, research, and innovation. By incorporating multiple perspectives — and being attentive to the needs and cultures of the people who will ultimately rely on research outcomes — MIT can have the greatest impact in areas of health, climate science, and resource security,” says Nergis Mavalvala, dean of the School of Science and the Curtis and Kathleen Marble Professor of Astrophysics.

      An overarching aim for the center will be to educate graduates who are global engineers, designers, and researchers positioned for a career of addressing compelling, high-impact challenges. The center includes four endowed Hock E. Tan GEAR Center Fellowships that will support graduate students and/or postdoctoral fellows eager to enter the field of global engineering. The fellowships are named for MIT alumnus and Broadcom CEO Hock E. Tan ’75 SM ’75.

      “I am thrilled that the Yang GEAR Center is taking a leading role in training problem-solvers who will rethink how products and inventions can help communities facing the most pressing challenges of our time,” adds Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “These talented young students,  postdocs, and staff have the potential to reach across disciplines — and across the globe — to truly transform the impact engineering can have in the future.” More

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      in Energy

      The future of motorcycles could be hydrogen

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      MIT’s Electric Vehicle Team, which has a long record of building and racing innovative electric vehicles, including cars and motorcycles, in international professional-level competitions, is trying something very different this year: The team is building a hydrogen-powered electric motorcycle, using a fuel cell system, as a testbed for new hydrogen-based transportation.

      The motorcycle successfully underwent its first full test-track demonstration in October. It is designed as an open-source platform that should make it possible to swap out and test a variety of different components, and for others to try their own versions based on plans the team is making freely available online.

      Aditya Mehrotra, who is spearheading the project, is a graduate student working with mechanical engineering professor Alex Slocum, the Walter M. May  and A. Hazel May Chair in Emerging Technologies. Mehrotra was studying energy systems and happened to also really like motorcycles, he says, “so we came up with the idea of a hydrogen-powered bike. We did an evaluation study, and we thought that this could actually work. We [decided to] try to build it.”

      Team members say that while battery-powered cars are a boon for the environment, they still face limitations in range and have issues associated with the mining of lithium and resulting emissions. So, the team was interested in exploring hydrogen-powered vehicles as a clean alternative, allowing for vehicles that could be quickly refilled just like gasoline-powered vehicles.

      Unlike past projects by the team, which has been part of MIT since 2005, this vehicle will not be entering races or competitions but will be presented at a variety of conferences. The team, consisting of about a dozen students, has been working on building the prototype since January 2023. In October they presented the bike at the Hydrogen Americas Summit, and in May they will travel to the Netherlands to present it at the World Hydrogen Summit. In addition to the two hydrogen summits, the team plans to show its bike at the Consumer Electronics Show in Las Vegas this month.

      “We’re hoping to use this project as a chance to start conversations around ‘small hydrogen’ systems that could increase demand, which could lead to the development of more infrastructure,” Mehrotra says. “We hope the project can help find new and creative applications for hydrogen.” In addition to these demonstrations and the online information the team will provide, he adds, they are also working toward publishing papers in academic journals describing their project and lessons learned from it, in hopes of making “an impact on the energy industry.”

      Play video

      For the love of speed: Building a hydrogen-powered motorcycle

      The motorcycle took shape over the course of the year piece by piece. “We got a couple of industry sponsors to donate components like the fuel cell and a lot of the major components of the system,” he says. They also received support from the MIT Energy Initiative, the departments of Mechanical Engineering and Electrical Engineering and Computer Science, and the MIT Edgerton Center.

      Initial tests were conducted on a dynamometer, a kind of instrumented treadmill Mehrotra describes as “basically a mock road.” The vehicle used battery power during its development, until the fuel cell, provided by South Korean company Doosan, could be delivered and installed. The space the group has used to design and build the prototype, the home of the Electric Vehicle Team, is in MIT’s Building N51 and is well set up to do detailed testing of each of the bike’s components as it is developed and integrated.

      Elizabeth Brennan, a senior in mechanical engineering, says she joined the team in January 2023 because she wanted to gain more electrical engineering experience, “and I really fell in love with it.” She says group members “really care and are very excited to be here and work on this bike and believe in the project.”

      Brennan, who is the team’s safety lead, has been learning about the safe handling methods required for the bike’s hydrogen fuel, including the special tanks and connectors needed. The team initially used a commercially available electric motor for the prototype but is now working on an improved version, designed from scratch, she says, “which gives us a lot more flexibility.”

      As part of the project, team members are developing a kind of textbook describing what they did and how they carried out each step in the process of designing and fabricating this hydrogen electric fuel-cell bike. No such motorcycle yet exists as a commercial product, though a few prototypes have been built.

      That kind of guidebook to the process “just doesn’t exist,” Brennan says. She adds that “a lot of the technology development for hydrogen is either done in simulation or is still in the prototype stages, because developing it is expensive, and it’s difficult to test these kinds of systems.” One of the team’s goals for the project is to make everything available as an open-source design, and “we want to provide this bike as a platform for researchers and for education, where researchers can test ideas in both space- and funding-constrained environments.”

      Unlike a design built as a commercial product, Mehrotra says, “our vehicle is fully designed for research, so you can swap components in and out, and get real hardware data on how good your designs are.” That can help people work on implementing their new design ideas and help push the industry forward, he says.

      The few prototypes developed previously by some companies were inefficient and expensive, he says. “So far as we know, we are the first fully open-source, rigorously documented, tested and released-as-a-platform, [fuel cell] motorcycle in the world. No one else has made a motorcycle and tested it to the level that we have, and documented to the point that someone might actually be able to take this and scale it in the future, or use it in research.”

      He adds that “at the moment, this vehicle is affordable for research, but it’s not affordable yet for commercial production because the fuel cell is a very big, expensive component.” Doosan Fuel Cell, which provided the fuel cell for the prototype bike, produces relatively small and lightweight fuel cells mostly for use in drones. The company also produces hydrogen storage and delivery systems.

      The project will continue to evolve, says team member Annika Marschner, a sophomore in mechanical engineering. “It’s sort of an ongoing thing, and as we develop it and make changes, make it a stronger, better bike, it will just continue to grow over the years, hopefully,” she says.

      While the Electric Vehicle Team has until now focused on battery-powered vehicles, Marschner says, “Right now we’re looking at hydrogen because it seems like something that’s been less explored than other technologies for making sustainable transportation. So, it seemed like an exciting thing for us to offer our time and effort to.”

      Making it all work has been a long process. The team is using a frame from a 1999 motorcycle, with many custom-made parts added to support the electric motor, the hydrogen tank, the fuel cell, and the drive train. “Making everything fit in the frame of the bike is definitely something we’ve had to think about a lot because there’s such limited space there. So, it required trying to figure out how to mount things in clever ways so that there are not conflicts,” she says.

      Marschner says, “A lot of people don’t really imagine hydrogen energy being something that’s out there being used on the roads, but the technology does exist.” She points out that Toyota and Hyundai have hydrogen-fueled vehicles on the market, and that some hydrogen fuel stations exist, mostly in California, Japan, and some European countries. But getting access to hydrogen, “for your average consumer on the East Coast, is a huge, huge challenge. Infrastructure is definitely the biggest challenge right now to hydrogen vehicles,” she says.

      She sees a bright future for hydrogen as a clean fuel to replace fossil fuels over time. “I think it has a huge amount of potential,” she says. “I think one of the biggest challenges with moving hydrogen energy forward is getting these demonstration projects actually developed and showing that these things can work and that they can work well. So, we’re really excited to bring it along further.” More