The race to develop renewable energy technologies

In the early 20th century, just as electric grids were starting to transform daily life, an unlikely advocate for renewable energy voiced his concerns about burning fossil fuels. Thomas Edison expressed dismay over using combustion instead of renewable resources in a 1910 interview for Elbert Hubbard’s anthology, “Little Journeys to the Homes of the Great.”

“This scheme of combustion to get power makes me sick to think of — it is so wasteful,” Edison said. “You see, we should utilize natural forces and thus get all of our power. Sunshine is a form of energy, and the winds and the tides are manifestations of energy. Do we use them? Oh, no! We burn up wood and coal, as renters burn up the front fence for fuel.”

Over a century later, roughly 80 percent of global energy consumption still comes from burning fossil fuels. As the impact of climate change on the environment becomes increasingly drastic, there is a mounting sense of urgency for researchers and engineers to develop scalable renewable energy solutions.

“Even 100 years ago, Edison understood that we cannot replace combustion with a single alternative,” adds Reshma Rao PhD '19, a postdoc in MIT’s Electrochemical Energy Lab who included Edison’s quote in her doctoral thesis. “We must look to different solutions that might vary temporally and geographically depending on resource availability.”

Rao is one of many researchers across MIT’s Department of Mechanical Engineering who have entered the race to develop energy conversion and storage technologies from renewable sources such as wind, wave, solar, and thermal.

Harnessing energy from waves

When it comes to renewable energy, waves have other resources beat in two respects. First, unlike solar, waves offer a consistent energy source regardless of time of day. Second, waves provide much greater energy density than wind due to water’s heavier mass.

Despite these advantages, wave-energy harvesting is still in its infancy. Unlike wind and solar, there is no consensus in the field of wave hydrodynamics on how to efficiently capture and convert wave energy. Dick K.P. Yue, Philip J. Solondz Professor of Engineering, is hoping to change that.

“My group has been looking at new paradigms,” explains Yue. “Rather than tinkering with small improvements, we want to develop a new way of thinking about the wave-energy problem.”

One aspect of that paradigm is determining the optimal geometry of wave-energy converters (WECs). Graduate student Emma Edwards has been developing a systematic methodology to determine what kind of shape WECs should be.

“If we can optimize the shape of WECs for maximizing extractable power, wave energy could move significantly closer to becoming an economically viable source of renewable energy,” says Edwards. 

Another aspect of the wave-energy paradigm Yue’s team is working on is finding the optimal configuration for WECs in the water. Grgur Tokić PhD '16, an MIT alum and current postdoc working in Yue’s group, is building a case for optimal configurations of WECs in large arrays, rather than as stand-alone devices.

Before being placed in the water, WECs are tuned for their particular environment. This tuning involves considerations like predicted wave frequency and prevailing wind direction. According to Tokić and Yue, if WECs are configured in an array, this tuning could occur in real time, maximizing energy-harvesting potential.

In an array, “sentry” WECs could gather measurements about waves such as amplitude, frequency, and direction. Using wave reconstructing and forecasting, these WECs could then communicate information about conditions to other WECs in the array wirelessly, enabling them to tune minute-by-minute in response to current wave conditions.

“If an array of WECs can tune fast enough so they are optimally configured for their current environment, now we are talking serious business,” explains Yue. “Moving toward arrays opens up the possibilities of significant advances and gains many-times-over non-interacting, isolated devices.”

By examining the optimal size and configuration of WECs using theoretical and computational methods, Yue’s group hopes to develop potentially game-changing frameworks for harnessing the power of waves.

Accelerating the discovery of photovoltaics

The amount of solar energy that reaches the Earth’s surface offers a tantalizing prospect in the quest for renewable energy. Every hour, an estimated 430 quintillion joules of energy is delivered to Earth from the sun. That’s the equivalent of one year’s worth of global energy consumption by humans.

Tonio Buonassisi, professor of mechanical engineering, has dedicated his entire career to developing technologies that harness this energy and convert it into usable electricity. But time, he says, is of the essence. “When you consider what we are up against in terms of climate change, it becomes increasingly clear we are running out of time,” he says.

For solar energy to have a meaningful impact, according to Buonassisi, researchers need to develop solar cell materials that are efficient, scalable, cost-effective, and reliable. These four variables pose a challenge for engineers — rather than develop a material that satisfies just one of these factors, they need to create one that ticks off all four boxes and can be moved to market as quickly as possible. “If it takes us 75 years to get a solar cell that does all of these things to market, it’s not going to help us solve this problem. We need to get it to market in the next five years,” Buonassisi adds.

To accelerate the discovery and testing of new materials, Buonassisi’s team has developed a process that uses a combination of machine learning and high-throughput experimentation — a type of experimentation that enables a large quantity of materials to be screened at the same time. The result is a 10-fold increase in the speed of discovery and analysis for new solar cell materials.

“Machine learning is our navigational tool,” explains Buonassisi. “It can de-bottleneck the cycle of learning so we can grind through material candidates and find one that satisfies all four variables.”

Shijing Sun, a research scientist in Buonassisi’s group, used a combination of machine learning and high-throughput experiments to quickly assess and test perovskite solar cells.

“We use machine learning to accelerate the materials discovery, and developed an algorithm that directs us to the next sampling point and guides our next experiment,” Sun says. Previously, it would take three to five hours to classify a set of solar cell materials. The machine learning algorithm can classify materials in just five minutes.

Using this method, Sun and Buonassisi made 96 tested compositions. Of those, two perovskite materials hold promise and will be tested further.

By using machine learning as a tool for inverse design, the research team hopes to assess thousands of compounds that could lead to the development of a material that enables the large-scale adoption of solar energy conversion. “If in the next five years we can develop that material using the set of productivity tools we’ve developed, it can help us secure the best possible future that we can,” adds Buonassisi.

New materials to trap heat

While Buonassisi’s team is focused on developing solutions that directly convert solar energy into electricity, researchers including Gang Chen, Carl Richard Soderberg Professor of Power Engineering, are working on technologies that convert sunlight into heat. Thermal energy from the heat is then used to provide electricity.

“For the past 20 years, I’ve been working on materials that convert heat into electricity,” says Chen. While much of this materials research is on the nanoscale, Chen and his team at the NanoEngineering Group are no strangers to large-scale experimental systems. They previously built a to-scale receiver system that used concentrating solar thermal power (CSP).

In CSP, sunlight is used to heat up a thermal fluid, such as oil or molten salt. That fluid is then either used to generate electricity by running an engine, such as a steam turbine, or stored for later use.

Over the course of a four-year project funded by the U.S. Department of Energy, Chen’s team built a CSP receiver at MIT’s Bates Research and Engineering Center in Middleton, Massachusetts. They developed the Solar Thermal Aerogel Receiver — nicknamed STAR.

The system relied on mirrors known as Fresnel reflectors to direct sunlight to pipes containing thermal fluid. Typically, for fluid to effectively trap the heat generated by this reflected sunlight, it would need to be encased in a high-cost vacuum tube. In STAR, however, Chen’s team utilized a transparent aerogel that can trap heat at incredibly high temperatures — removing the need for expensive vacuum enclosures. While letting in over 95 percent of the incoming sunlight, the aerogel retains its insulating properties, preventing heat from escaping the receiver.

In addition to being more efficient than traditional vacuum receivers, the aerogel receivers enabled new configurations for the CSP solar reflectors. The reflecting mirrors were flatter and more compact than conventionally used parabolic receivers, resulting in a savings of material. 

“Cost is everything with energy applications, so the fact STAR was cheaper than most thermal energy receivers, in addition to being more efficient, was important,” adds Svetlana Boriskina, a research scientist working on Chen’s team. 

After the conclusion of the project in 2018, Chen and Wang have continued their collaboration to explore solar thermal applications for the aerogel material used in STAR. They recently used the aerogel in a device that contained a heat-absorbing material. When placed on a roof on MIT’s campus, the heat-absorbing material, which was covered by a layer of the aerogel, reached an amazingly high temperature of 220 degrees Celsius. The outside air temperature, for comparison, was a chilly 0 C. Unlike STAR, this new system doesn’t require Fresnel reflectors to direct sunlight to the thermal material.

“Our latest work using the aerogel enables sunlight concentration without focusing optics to harness thermal energy,” explains Chen. “If you aren’t using focusing optics, you can develop a system that is easier to use and cheaper than traditional receivers.”

The aerogel device could potentially be further developed into a system that powers heating and cooling systems in homes.

Solving the storage problem

While CSP receivers like STAR offer some energy storage capabilities, there is a push to develop more robust energy storage systems for renewable technologies. Storing energy for later use when resources aren’t supplying a consistent stream of energy — for example, when the sun is covered by clouds, or there is little-to-no wind — will be crucial for the adoption of renewable energy on the grid. To solve this problem, researchers are developing new storage technologies.  

Asegun Henry, Robert N. Noyce Career Development Professor, who like Chen has developed CSP technologies, has created a new storage system that has been dubbed “sun in a box.” Using two tanks, excess energy can be stored in white-hot molten silicon. When this excess energy is needed, mounted photovoltaic cells can be actuated into place to convert the white-hot light from the silicon back into electricity.

“It’s a true battery that can work with any type of energy conversion,” adds Henry.

Betar Gallant, ABS Career Development Professor, meanwhile, is exploring ways to improve the energy density of today’s electrochemical batteries by designing new storage materials that are more cost-effective and versatile for storing cleanly generated energy. Rather than develop these materials using metals that are extracted through energy-intensive mining, she aims to build batteries using more earth-abundant materials.

“Ideally, we want to create a battery that can match the irregular supply of solar or wind energy that peak at different times without degrading, as today’s batteries do” explains Gallant.

In addition to working on lithium-ion batteries, like Gallant, Yang Shao-Horn, W.M. Keck Professor of Energy, and postdoc Reshma Rao are developing technologies that can directly convert renewable energy to fuels.

“If we want to store energy at scale going beyond lithium ion batteries, we need to use resources that are abundant,” Rao explains. In their electrochemical technology, Rao and Shao-Horn utilize one of the most abundant resources — liquid water.

Using an active catalyst and electrodes, water is split into hydrogen and oxygen in a series of chemical reactions. The hydrogen becomes an energy carrier and can be stored for later use in a fuel cell. To convert the energy stored in the hydrogen back into electricity, the reactions are reversed. The only by-product of this reaction is water.  

“If we can get and store hydrogen sustainably, we can basically electrify our economy using renewables like wind, wave, or solar,” says Rao.

Rao has broken down every fundamental reaction that takes place within this process. In addition to focusing on the electrode-electrolyte interface involved, she is developing next-generation catalysts to drive these reactions.  

“This work is at the frontier of the fundamental understanding of active sites catalyzing water splitting for hydrogen-based fuels from solar and wind to decarbonize transport and industry,” adds Shao-Horn.

Securing a sustainable future

While shifting from a grid powered primarily by fossil fuels to a grid powered by renewable energy seems like a herculean task, there have been promising developments in the past decade. A report released prior to the UN Global Climate Action Summit in September showed that, thanks to $2.6 trillion of investment, renewable energy conversion has quadrupled since 2010.

In a statement after the release of the report, Inger Andersen, executive director of the UN Environment Program, stressed the correlation between investing in renewable energy and securing a sustainable future for humankind. “It is clear that we need to rapidly step up the pace of the global switch to renewables if we are to meet international climate and development goals,” Andersen said.

No single conversion or storage technology will be responsible for the shift from fossil fuels to renewable energy. It will require a tapestry of complementary solutions from researchers both here at MIT and across the globe.

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Intelligent Towing Tank propels human-robot-computer research

In its first year of operation, the Intelligent Towing Tank (ITT) conducted about 100,000 total experiments, essentially completing the equivalent of a PhD student’s five years’ worth of experiments in a matter of weeks.

The automated experimental facility, developed in the MIT Sea Grant Hydrodynamics Laboratory, automatically and adaptively performs, analyzes, and designs experiments exploring vortex-induced vibrations (VIVs). Important for engineering offshore ocean structures like marine drilling risers that connect underwater oil wells to the surface, VIVs remain somewhat of a phenomenon to researchers due to the high number of parameters involved.

Guided by active learning, the ITT conducts series of experiments wherein the parameters of each next experiment are selected by a computer. Using an “explore-and-exploit” methodology, the system dramatically reduces the number of experiments required to explore and map the complex forces governing VIVs.

What began as then-PhD candidate Dixia Fan’s quest to cut back on conducting a thousand or so laborious experiments — by hand — led to the design of the innovative system and a paper recently published in the journal Science Robotics.

Fan, now a postdoc, and a team of researchers from the MIT Sea Grant College Program and MIT’s Department of Mechanical Engineering, École Normale Supérieure de Rennes, and Brown University, reveal a potential paradigm shift in experimental research, where humans, computers, and robots can collaborate more effectively to accelerate scientific discovery.

The 33-foot whale of a tank comes alive, working without interruption or supervision on the venture at hand — in this case, exploring a canonical problem in the field of fluid-structure interactions. But the researchers envision applications of the active learning and automation approach to experimental research across disciplines, potentially leading to new insights and models in multi-input/multi-output nonlinear systems.

VIVs are inherently-nonlinear motions induced on a structure in an oncoming irregular cross-stream, which prove vexing to study. The researchers report that the number of experiments completed by the ITT is already comparable to the total number of experiments done to date worldwide on the subject of VIVs.

The reason for this is the large number of independent parameters, from flow velocity to pressure, involved in studying the complex forces at play. According to Fan, a systematic brute-force approach — blindly conducting 10 measurements per parameter in an eight-dimensional parametric space — would require 100 million experiments.

With the ITT, Fan and his collaborators have taken the problem into a wider parametric space than previously practicable to explore. “If we performed traditional techniques on the problem we studied,” he explains, “it would take 950 years to finish the experiment.” Clearly infeasible, so Fan and the team integrated a Gaussian process regression learning algorithm into the ITT. In doing so, the researchers reduced the experimental burden by several orders of magnitude, requiring only a few thousand experiments.

The robotic system automatically conducts an initial sequence of experiments, periodically towing a submerged structure along the length of the tank at a constant velocity. Then, the ITT takes partial control over the parameters of each next experiment by minimizing suitable acquisition functions of quantified uncertainties and adapting to achieve a range of objectives, like reduced drag.

Earlier this year, Fan was awarded an MIT Mechanical Engineering de Florez Award for "Outstanding Ingenuity and Creative Judgment" in the development of the ITT. “Dixia’s design of the Intelligent Towing Tank is an outstanding example of using novel methods to reinvigorate mature fields,” says Michael Triantafyllou, Henry L. and Grace Doherty Professor in Ocean Science and Engineering, who acted as Fan’s doctoral advisor.

Triantafyllou, a co-author on this paper and the director of the MIT Sea Grant College Program, says, “MIT Sea Grant has committed resources and funded projects using deep-learning methods in ocean-related problems for several years that are already paying off.” Funded by the National Oceanic and Atmospheric Administration and administered by the National Sea Grant Program, MIT Sea Grant is a federal-Institute partnership that brings the research and engineering core of MIT to bear on ocean-related challenges.

Fan’s research points to a number of others utilizing automation and artificial intelligence in science: At Caltech, a robot scientist named “Adam” generates and tests hypotheses; at the Defense Advanced Research Projects Agency, the Big Mechanism program reads tens of thousands of research papers to generate new models.

Similarly, the ITT applies human-computer-robot collaboration to accelerate experimental efforts. The system demonstrates a potential paradigm shift in conducting research, where automation and uncertainty quantification can considerably accelerate scientific discovery. The researchers assert that the machine learning methodology described in this paper can be adapted and applied in and beyond fluid mechanics, to other experimental fields.

Other contributors to the paper include George Karniadakis from Brown University, who is also affiliated with MIT Sea Grant; Gurvan Jodin from ENS Rennes; MIT PhD candidate in mechanical engineering Yu Ma; and Thomas Consi, Luca Bonfiglio, and Lily Keyes from MIT Sea Grant.

This work was supported by DARPA, Fariba Fahroo, and Jan Vandenbrande through an EQUiPS (Enabling Quantification of Uncertainty in Physical Systems) grant, as well as Shell, Subsea 7, and the MIT Sea Grant College Program.

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Understanding the impact of deep-sea mining

Resting atop Thomas Peacock’s desk is an ordinary-looking brown rock. Roughly the size of a potato, it has been at the center of decades of debate. Known as a polymetallic nodule, it spent 10 million years sitting on the deep seabed, 15,000 feet below sea level. The nodule contains nickel, cobalt, copper, and manganese — four minerals that are essential in energy storage.

“As society moves toward driving more electric vehicles and utilizing renewable energy, there will be an increased demand for these minerals, to manufacture the batteries necessary to decarbonize the economy,” says Peacock, a professor of mechanical engineering and the director of MIT’s Environmental Dynamics Lab (END Lab). He is part of an international team of researchers that has been trying to gain a better understanding the environmental impact of collecting polymetallic nodules, a process known as deep-sea mining.

The minerals found in the nodules, particularly cobalt and nickel, are key components of lithium-ion batteries. Currently, lithium-ion batteries offer the best energy density of any commercially available battery. This high energy density makes them ideal for use in everything from cellphones to electric vehicles, which require large amounts of energy within a compact space.

“Those two elements are expected to see a tremendous growth in demand due to energy storage,” says Richard Roth, director of MIT’s Materials Systems Laboratory.

While researchers are exploring alternative battery technologies such as sodium-ion batteries and flow batteries that utilize electrochemical cells, these technologies are far from commercialization.

“Few people expect any of these lithium-ion alternatives to be available in the next decade,” explains Roth. “Waiting for unknown future battery chemistries and technologies could significantly delay widespread adoption of electric vehicles.”

Vast amounts of specialty nickel will be also needed to build larger-scale batteries that will be required as societies look to shift from an electric grid powered by fossil fuels to one powered by renewable resources like solar, wind, wave, and thermal.

“The collection of nodules from the seabed is being considered as a new means for getting these materials, but before doing so it is imperative to fully understand the environmental impact of mining resources from the deep ocean and compare it to the environmental impact of mining resources on land,” explains Peacock.

After receiving seed funding from MIT’s Environmental Solutions Initiative (ESI), Peacock was able to apply his expertise in fluid dynamics to study how deep-sea mining could affect surrounding ecosystems.

Meeting the demand for energy storage

Currently, nickel and cobalt are extracted through land-based mining operations. Much of this mining occurs in the Democratic Republic of the Congo, which produces 60 percent of the world’s cobalt. These land-based mines often impact surrounding environments through the destruction of habitats, erosion, and soil and water contamination. There are also concerns that land-based mining, especially in politically unstable countries, might not be able to supply enough of these materials as the demand for batteries rises.

The swath of ocean located between Hawaii and the West Coast of the United States — also  known as the Clarion Clipperton Fracture Zone — is estimated to possess six times more cobalt and three times more nickel than all known land-based stores, as well as vast deposits of manganese and a substantial amount of copper.

While the seabed is abundant with these materials, little is known about the short- and long-term environmental effects of mining 15,000 feet below sea level. Peacock and his collaborator Professor Matthew Alford from the Scripps Institution of Oceanography and the University of California at San Diego are leading the quest to understand how the sediment plumes generated by the collection of nodules from the seabed will be carried by water currents.

“The key question is, if we decide to make a plume at site A, how far does it spread before eventually raining down on the sea floor?” explains Alford. “That ability to map the geography of the impact of sea floor mining is a crucial unknown right now.”

The research Peacock and Alford are conducting will help inform stakeholders about the potential environmental effects of deep-sea mining. One pressing matter is that draft exploitation regulations for deep-sea mining in areas beyond national jurisdiction are currently being negotiated by the International Seabed Authority (ISA), an independent organization established by the United Nations that regulates all mining activities on the sea floor. Peacock and Alford’s research will help guide the development of environmental standards and guidelines to be issued under those regulations.

“We have a unique opportunity to help regulators and other concerned parties to assess draft regulations using our data and modeling, before operations start and we regret the impact of our activity,” says Carlos Munoz Royo, a PhD student in MIT’s END Lab.

Tracking plumes in the water

In deep-sea mining, a collector vehicle would be deployed from a ship. The collector vehicle then travels 15,000 feet down to the seabed, where it vacuums up the top four inches of the seabed. This process creates a plume known as a collector plume.

“As the collector moves across the seabed floor, it stirs up sediment and creates a sediment cloud, or plume, that’s carried away and distributed by ocean currents,” explains Peacock.

The collector vehicle picks up the nodules, which are pumped through a pipe back to the ship. On the ship, usable nodules are separated from unwanted sediment. That sediment is piped back into the ocean, creating a second plume, known as a discharge plume.

Peacock collaborated with Pierre Lermusiaux, professor of mechanical engineering and of ocean science and engineering, and Glenn Flierl, professor of Earth, atmospheric, and planetary sciences, to create mathematical models that predict how these two plumes travel through the water.

To test these models, Peacock set out to track actual plumes created by mining the floor of the Pacific Ocean. With funding from MIT ESI, he embarked on the first-ever field study of such plumes. He was joined by Alford and Eric Adams, senior research engineer at MIT, as well as other researchers and engineers from MIT, Scripps, and the United States Geological Survey.

With funding from the UC Ship Funds Program, the team conducted experiments in consultation with the ISA during a weeklong expedition in the Pacific Ocean aboard the U.S. Navy R/V Sally Ride in March 2018. The researchers mixed sediment with a tracer dye that they were able to track using sensors on the ship developed by Alford’s Multiscale Ocean Dynamics group. In doing so, they created a map of the plumes’ journeys.

The field experiments demonstrated that the models Peacock and Lermusiaux developed can be used to predict how plumes will travel through the water — and could help give a clearer picture of how surrounding biology might be affected.

Impact on deep-sea organisms

Life on the ocean floor moves at a glacial pace. Sediment accumulates at a rate of 1 millimeter every millennium. With such a slow rate of growth, areas disturbed by deep-sea mining would be unlikely to recover on a reasonable timescale.

“The concern is that if there is a biological community specific to the area, it might be irretrievably impacted by mining,” explains Peacock. 

According to Cindy Van Dover, professor of biological oceanography at Duke University, in addition to organisms that live in or around the nodules, other organisms elsewhere in the water column could be affected as the plumes travel.

“There could be clogging of filter feeding structures of, for example, gelatinous organisms in the water column, and burial of organisms on the sediment,” she explains. “There could also be some metals that get into the water column, so there are concerns about toxicology.”

Peacock’s research on plumes could help biologists like Van Dover assess collateral damage from deep-sea mining operations in surrounding ecosystems.

Drafting regulations for mining the sea

Through connections with MIT’s Policy Lab, the Institute is one of only two research universities with observer status at the ISA.

“The plume research is very important, and MIT is helping with the experimentation and developing plume models, which is vital to inform the current work of the International Seabed Authority and its stakeholder base,” explains Chris Brown, a consultant at the ISA. Brown was one of dozens of experts who convened on MIT’s campus last fall at a workshop discussing the risks of deep-sea mining.

To date, the field research Peacock and Alford conducted is the only ocean dataset on midwater plumes that exists to help guide decision-making. The next step in understanding how plumes move through the water will be to track plumes generated by a prototype collector vehicle. Peacock and his team in the END Lab are preparing to participate in a major field study using a prototype vehicle in 2020.

Thanks to recent funding provided by the 11th Hour Project, Peacock and Lermusiaux hope to develop models that give increasingly accurate predictions about how deep-sea mining plumes will travel through the ocean. They will continue to interact with academic colleagues, international agencies, NGOs, and contractors to develop a clearer picture of deep-sea mining’s environmental impact.

“It’s important to have input from all stakeholders early in the conversation to help make informed decisions, so we can fully understand the environmental impact of mining resources from the ocean and compare it to the environmental impact of mining resources on land,” says Peacock.

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Autonomous system improves environmental sampling at sea

An autonomous robotic system invented by researchers at MIT and the Woods Hole Oceanographic Institution (WHOI) efficiently sniffs out the most scientifically interesting — but hard-to-find — sampling spots in vast, unexplored waters.

Environmental scientists are often interested in gathering samples at the most interesting locations, or “maxima,” in an environment. One example could be a source of leaking chemicals, where the concentration is the highest and mostly unspoiled by external factors. But a maximum can be any quantifiable value that researchers want to measure, such as water depth or parts of coral reef most exposed to air.

Efforts to deploy maximum-seeking robots suffer from efficiency and accuracy issues. Commonly, robots will move back and forth like lawnmowers to cover an area, which is time-consuming and collects many uninteresting samples. Some robots sense and follow high-concentration trails to their leak source. But they can be misled. For example, chemicals can get trapped and accumulate in crevices far from a source. Robots may identify those high-concentration spots as the source yet be nowhere close.

In a paper being presented at the International Conference on Intelligent Robots and Systems (IROS), the researchers describe “PLUMES,” a system that enables autonomous mobile robots to zero in on a maximum far faster and more efficiently. PLUMES leverages probabilistic techniques to predict which paths are likely to lead to the maximum, while navigating obstacles, shifting currents, and other variables. As it collects samples, it weighs what it’s learned to determine whether to continue down a promising path or search the unknown — which may harbor more valuable samples.

Importantly, PLUMES reaches its destination without ever getting trapped in those tricky high-concentration spots. “That’s important, because it’s easy to think you’ve found gold, but really you’ve found fool’s gold,” says co-first author Victoria Preston, a PhD student in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and in the MIT-WHOI Joint Program.

The researchers built a PLUMES-powered robotic boat that successfully detected the most exposed coral head in the Bellairs Fringing Reef in Barbados — meaning, it was located in the shallowest spot — which is useful for studying how sun exposure impacts coral organisms. In 100 simulated trials in diverse underwater environments, a virtual PLUMES robot also consistently collected seven to eight times more samples of maxima than traditional coverage methods in allotted time frames.

“PLUMES does the minimal amount of exploration necessary to find the maximum and then concentrates quickly on collecting valuable samples there,” says co-first author Genevieve Flaspohler, a PhD student and in CSAIL and the MIT-WHOI Joint Program.

Joining Preston and Flaspohler on the paper are: Anna P.M. Michel and Yogesh Girdhar, both scientists in the Department of Applied Ocean Physics and Engineering at the WHOI; and Nicholas Roy, a professor in CSAIL and in the Department of Aeronautics and Astronautics.  

Navigating an exploit-explore tradeoff

A key insight of PLUMES was using techniques from probability to reason about navigating the notoriously complex tradeoff between exploiting what’s learned about the environment and exploring unknown areas that may be more valuable.

“The major challenge in maximum-seeking is allowing the robot to balance exploiting information from places it already knows to have high concentrations and exploring places it doesn’t know much about,” Flaspohler says. “If the robot explores too much, it won’t collect enough valuable samples at the maximum. If it doesn’t explore enough, it may miss the maximum entirely.”

Dropped into a new environment, a PLUMES-powered robot uses a probabilistic statistical model called a Gaussian process to make predictions about environmental variables, such as chemical concentrations, and estimate sensing uncertainties. PLUMES then generates a distribution of possible paths the robot can take, and uses the estimated values and uncertainties to rank each path by how well it allows the robot to explore and exploit.

At first, PLUMES will choose paths that randomly explore the environment. Each sample, however, provides new information about the targeted values in the surrounding environment — such as spots with highest concentrations of chemicals or shallowest depths. The Gaussian process model exploits that data to narrow down possible paths the robot can follow from its given position to sample from locations with even higher value. PLUMES uses a novel objective function — commonly used in machine-learning to maximize a reward — to make the call of whether the robot should exploit past knowledge or explore the new area.

“Hallucinating” paths

The decision where to collect the next sample relies on the system’s ability to “hallucinate” all possible future action from its current location. To do so, it leverages a modified version of Monte Carlo Tree Search (MCTS), a path-planning technique popularized for powering artificial-intelligence systems that master complex games, such as Go and Chess.

MCTS uses a decision tree — a map of connected nodes and lines — to simulate a path, or sequence of moves, needed to reach a final winning action. But in games, the space for possible paths is finite. In unknown environments, with real-time changing dynamics, the space is effectively infinite, making planning extremely difficult. The researchers designed “continuous-observation MCTS,” which leverages the Gaussian process and the novel objective function to search over this unwieldy space of possible real paths.

The root of this MCTS decision tree starts with a “belief” node, which is the next immediate step the robot can take. This node contains the entire history of the robot’s actions and observations up until that point. Then, the system expands the tree from the root into new lines and nodes, looking over several steps of future actions that lead to explored and unexplored areas.

Then, the system simulates what would happen if it took a sample from each of those newly generated nodes, based on some patterns it has learned from previous observations. Depending on the value of the final simulated node, the entire path receives a reward score, with higher values equaling more promising actions. Reward scores from all paths are rolled back to the root node. The robot selects the highest-scoring path, takes a step, and collects a real sample. Then, it uses the real data to update its Gaussian process model and repeats the “hallucination” process.

“As long as the system continues to hallucinate that there may be a higher value in unseen parts of the world, it must keep exploring,” Flaspohler says. “When it finally converges on a spot it estimates to be the maximum, because it can’t hallucinate a higher value along the path, it then stops exploring.”

Now, the researchers are collaborating with scientists at WHOI to use PLUMES-powered robots to localize chemical plumes at volcanic sites and study methane releases in melting coastal estuaries in the Arctic. Scientists are interested in the source of chemical gases released into the atmosphere, but these test sites can span hundreds of square miles.

“They can [use PLUMES to] spend less time exploring that huge area and really concentrate on collecting scientifically valuable samples,” Preston says.

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MIT alumna addresses the world’s mounting plastic waste problem

It’s been nearly 10 years since Priyanka Bakaya MBA ’11 founded Renewlogy to develop a system that converts plastic waste into fuel. Today, that system is being used to profitably turn even nonrecyclable plastic into high-value fuels like diesel, as well as the precursors to new plastics.

Since its inception, Bakaya has guided Renewlogy through multiple business and product transformations to maximize its impact. During the company’s evolution from a garage-based startup to a global driver of sustainability, it has licensed its technology to waste management companies in the U.S. and Canada, created community-driven supply chains for processing nonrecycled plastic, and started a nonprofit, Renew Oceans, to reduce the flow of plastic into the world’s oceans.

The latter project has brought Bakaya and her team to one of the most polluted rivers in the world, the Ganges. With an effort based in Varanasi, a city of much religious, political, and cultural significance in India, Renew Oceans hopes to transform the river basin by incentivizing residents to dispose of omnipresent plastic waste in its “reverse vending machines,” which provide coupons in exchange for certain plastics.

Each of Renewlogy’s initiatives has brought challenges Bakaya never could have imagined during her early days tinkering with the system. But she’s approached those hurdles with a creative determination, driven by her belief in the transformative power of the company.

“It’s important to focus on big problems you’re really passionate about,” Bakaya says. “The only reason we’ve stuck with it over the years is because it’s extremely meaningful, and I couldn’t imagine working this hard and long on something if it wasn’t deeply meaningful.”

A system for sustainability

Bakaya began working on a plastic-conversion system with Renewlogy co-founder and Chief Technology Officer Benjamin Coates after coming to MIT’s Sloan School of Management in 2009. While pursuing his PhD at the University of Utah, Coates had been developing continuously operating systems to create fuels from things like wood waste and algae conversion.

One of Renewlogy’s key innovations is using a continuous system on plastics, which saves energy by eliminating the need to reheat the system to the high temperatures necessary for conversion.

Today, plastics entering Renewlogy’s system are first shredded, then put through a chemical reformer, where a catalyst degrades their long carbon chains.

Roughly 15 to 20 percent of those chains are converted into hydrocarbon gas that Renewlogy recycles to heat the system. Five percent turns into char, and the remaining 75 percent is converted into high-value fuels. Bakaya says the system can create about 60 barrels of fuel for every 10 tons of plastic it processes, and it has a 75 percent lower carbon footprint when compared to traditional methods for extracting and distilling diesel fuel.

In 2014, the company began running a large-scale plant in Salt Lake City, where it continues to iterate its processes and hold demonstrations.

Since then, Renewlogy has set up another commercial-scale facility in Nova Scotia, Canada, where the waste management company Sustane uses it to process about 10 tons of plastic a day, representing 5 percent of the total amount of solid waste the company collects. Renewlogy is also building a similar-sized facility in Phoenix, Arizona, that will be breaking ground next year. That project focuses on processing specific types of plastics (identified by international resin codes 3 through 7) that are less easily recycled.

In addition to its licensing strategy, the company is spearheading grassroots efforts to gather and process plastic that’s not normally collected for recycling, as part of the Hefty Energy Bag Program.

Through the program, residents in cities including Boise, Idaho, Omaha, Nebraska, and Lincoln, Nebraska, can put plastics numbered 4 through 6 into their regular recycling bins using special orange bags. The bags are separated at the recycling facility and sent to Renewlogy’s Salt Lake City plant for processing.

The projects have positioned Renewlogy to continue scaling and have earned Bakaya entrepreneurial honors from the likes of Forbes, Fortune, and the World Economic Forum. But a growing crisis in the world’s oceans has drawn her halfway across the world, to the site of the company’s most ambitious project yet.

Renewing the planet’s oceans

Of the millions of tons of plastic waste flowing through rivers into the world’s oceans each year, roughly 90 percent comes from just 10 rivers. The worsening environmental conditions of these rivers represents a growing global crisis that state governments have put billions of dollars toward, often with discouraging results.

Bakaya believes she can help.

“Most of these plastics tend to be what are referred to as soft plastics, which are typically much more challenging to recycle, but are a good feedstock for Renewlogy’s process,” she says.

Bakaya started Renew Oceans as a separate, nonprofit arm of Renewlogy last year. Since then, Renew Oceans has designed fence-like structures to collect river waste that can then be brought to its scaled down machines for processing. These machines can process between 0.1 and 1 ton of plastic a day.

Renew Oceans has already built its first machine, and Bakaya says deciding where to put it was easy.

From its origins in the Himalayas, the Ganges River flows over 1,500 miles through India and Bangladesh, serving as a means of transportation, irrigation, energy, and as a sacred monument to millions of people who refer to it as Mother Ganges.

Renewlogy’s first machine is currently undergoing local commissioning in the Indian city of Varanasi. Bakaya says the project is designed to scale.

“The aim is to take this to other major polluted rivers where we can have maximum impact,” Bakaya says. “We’ve started with the Ganges, but we want to go to other regions, especially around Asia, and find circular economies that can support this in the long term so locals can derive value from these plastics.”

Scaling down their system was another unforeseen project for Bakaya and Coates, who remember scaling up prototypes during the early days of the company. Throughout the years, Renewlogy has also adjusted its chemical processes in response to changing markets, having begun by producing crude oil, then moving to diesel as oil prices plummeted, and now exploring ways to create high-value petrochemicals like naphtha, which can be used to make new plastics.

Indeed, the company’s approach has featured almost as many twists and turns as the Ganges itself. Bakaya says she wouldn’t have it any other way.

“I’d really encourage entrepreneurs to not just go down that easy road but to really challenge themselves and try to solve big problems — especially students from MIT. The world is kind of depending on MIT students to push us forward and challenge the realm of possibility. We all should feel that sense of responsibility to solve bigger problems.”

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A battery-free sensor for underwater exploration

To investigate the vastly unexplored oceans covering most our planet, researchers aim to build a submerged network of interconnected sensors that send data to the surface — an underwater “internet of things.” But how to supply constant power to scores of sensors designed to stay for long durations in the ocean’s deep?

MIT researchers have an answer: a battery-free underwater communication system that uses near-zero power to transmit sensor data. The system could be used to monitor sea temperatures to study climate change and track marine life over long periods — and even sample waters on distant planets. They are presenting the system at the SIGCOMM conference this week, in a paper that has won the conference’s “best paper” award.

The system makes use of two key phenomena. One, called the “piezoelectric effect,” occurs when vibrations in certain materials generate an electrical charge. The other is “backscatter,” a communication technique commonly used for RFID tags, that transmits data by reflecting modulated wireless signals off a tag and back to a reader.

In the researchers’ system, a transmitter sends acoustic waves through water toward a piezoelectric sensor that has stored data. When the wave hits the sensor, the material vibrates and stores the resulting electrical charge. Then the sensor uses the stored energy to reflect a wave back to a receiver — or it doesn’t reflect one at all. Alternating between reflection in that way corresponds to the bits in the transmitted data: For a reflected wave, the receiver decodes a 1; for no reflected wave, the receiver decodes a 0.

“Once you have a way to transmit 1s and 0s, you can send any information,” says co-author Fadel Adib, an assistant professor in the MIT Media Lab and the Department of Electrical Engineering and Computer Science and founding director of the Signal Kinetics Research Group. “Basically, we can communicate with underwater sensors based solely on the incoming sound signals whose energy we are harvesting.”

The researchers demonstrated their Piezo-Acoustic Backscatter System in an MIT pool, using it to collect water temperature and pressure measurements. The system was able to transmit 3 kilobytes per second of accurate data from two sensors simultaneously at a distance of 10 meters between sensor and receiver.

Applications go beyond our own planet. The system, Adib says, could be used to collect data in the recently discovered subsurface ocean on Saturn’s largest moon, Titan. In June, NASA announced the Dragonfly mission to send a rover in 2026 to explore the moon, sampling water reservoirs and other sites.

“How can you put a sensor under the water on Titan that lasts for long periods of time in a place that’s difficult to get energy?” says Adib, who co-wrote the paper with Media Lab researcher JunSu Jang. “Sensors that communicate without a battery open up possibilities for sensing in extreme environments.”

Preventing deformation

Inspiration for the system hit while Adib was watching “Blue Planet,” a nature documentary series exploring various aspects of sea life. Oceans cover about 72 percent of Earth’s surface. “It occurred to me how little we know of the ocean and how marine animals evolve and procreate,” he says. Internet-of-things (IoT) devices could aid that research, “but underwater you can’t use Wi-Fi or Bluetooth signals … and you don’t want to put batteries all over the ocean, because that raises issues with pollution.”

That led Adib to piezoelectric materials, which have been around and used in microphones and other devices for about 150 years. They produce a small voltage in response to vibrations. But that effect is also reversible: Applying voltage causes the material to deform. If placed underwater, that effect produces a pressure wave that travels through the water. They’re often used to detect sunken vessels, fish, and other underwater objects.

“That reversibility is what allows us to develop a very powerful underwater backscatter communication technology,” Adib says.

Communicating relies on preventing the piezoelectric resonator from naturally deforming in response to strain. At the heart of the system is a submerged node, a circuit board that houses a piezoelectric resonator, an energy-harvesting unit, and a microcontroller. Any type of sensor can be integrated into the node by programming the microcontroller. An acoustic projector (transmitter) and underwater listening device, called a hydrophone (receiver), are placed some distance away.

Say the sensor wants to send a 0 bit. When the transmitter sends its acoustic wave at the node, the piezoelectric resonator absorbs the wave and naturally deforms, and the energy harvester stores a little charge from the resulting vibrations. The receiver then sees no reflected signal and decodes a 0.

However, when the sensor wants to send a 1 bit, the nature changes. When the transmitter sends a wave, the microcontroller uses the stored charge to send a little voltage to the piezoelectric resonator. That voltage reorients the material’s structure in a way that stops it from deforming, and instead reflects the wave. Sensing a reflected wave, the receiver decodes a 1.

Long-term deep-sea sensing

The transmitter and receiver must have power but can be planted on ships or buoys, where batteries are easier to replace, or connected to outlets on land. One transmitter and one receiver can gather information from many sensors covering one area or many areas.

“When you’re tracking a marine animal, for instance, you want to track it over a long range and want to keep the sensor on them for a long period of time. You don’t want to worry about the battery running out,” Adib says. “Or, if you want to track temperature gradients in the ocean, you can get information from sensors covering a number of different places.”

Another interesting application is monitoring brine pools, large areas of brine that sit in pools in ocean basins, and are difficult to monitor long-term. They exist, for instance, on the Antarctic Shelf, where salt settles during the formation of sea ice, and could aid in studying melting ice and marine life interaction with the pools. “We could sense what’s happening down there, without needing to keep hauling sensors up when their batteries die,” Adib says.

Polly Huang, a professor of electrical engineering at Taiwan National University, praised the work for its technical novelty and potential impact on environmental science. “This is a cool idea,” Huang says. “It's not news one uses piezoelectric crystals to harvest energy … [but is the] first time to see it being used as a radio at the same time [which] is unheard of to the sensor network/system research community. Also interesting and unique is the hardware design and fabrication. The circuit and the design of the encapsulation are both sound and interesting.”

While noting that the system still needs more experimentation, especially in sea water, Huang adds that “this might be the ultimate solution for researchers in marine biography, oceanography, or even meteorology — those in need of long-term, low-human-effort underwater sensing.”

Next, the researchers aim to demonstrate that the system can work at farther distances and communicate with more sensors simultaneously. They’re also hoping to test if the system can transmit sound and low-resolution images.

The work is sponsored, in part, by the U.S Office of Naval Research.

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Tuna are spawning in marine protected areas

Marine protected areas are large swaths of coastal seas or open ocean that are protected by governments from activities such as commercial fishing and mining. Such marine sanctuaries have had rehabilitating effects on at-risk species living within their borders. But it’s been less clear how they benefit highly migratory species such as tuna.

Now researchers at MIT and the Woods Hole Oceanographic Institution have found evidence that tuna are spawning in the Phoenix Islands Protected Area (PIPA), one of the largest marine protected areas in the world, covering an area of the central Pacific as large as Argentina.

The researchers observed multiple species of tuna larvae throughout this protected expanse, suggesting that several migratory species are using these protected waters as a reproductive stopover, over several consecutive years, and even during a particularly strong El Niño season, where PIPA may have provided a critical refuge.

The results, published this week in the journal Scientific Reports, suggest that marine protected areas may be ocean oases for migratory fish, with plentiful nutrients and clean, clear waters that encourage tuna and other migratory species to linger, and spawn often. The study supports the notion that marine protected areas can provide protection to adult fish during spawning, and in this way, help to bolster fish populations — particularly those that, outside protected areas, are in danger of overfishing.

“We have proven that tuna are spawning in this protected area, and that it’s worth protecting,” says Christina Hernández, a graduate student in MIT’s Department of Earth, Atmospheric, and Planetary Sciences. “There are various types of protection for marine areas around the world, and all those measures allow us to preserve populations better, and in some cases protect highly migratory species.”

Sea change in conservation

The Phoenix Islands Protected Area is part of the territorial waters of the Republic of Kiribati (pronounced Keer-ee-bahs), a sovereign state in Micronesia made up of three island chains in the central Pacific. The islands, if stitched together, would amount to no more than the land area of Cape Cod. However, Kiribati’s ocean territory is vast, extending 200 nautical miles from each of its 32 atolls. The people of Kiribati rely heavily on revenue from tuna licenses that they mete out to commercial fishers. In 2008, however, the republic designated 11 percent of its waters as a mixed-use marine protected area, with limited fishing. Officials ultimately banned all fishing activities in the region starting in 2015, in a conservation effort that — among other things — protected many endangered species, such as giant clams and coconut crab, along with birds, mammals, and sea turtles living within its boundaries.

While fishing vessels have respected the protected territory, keeping their activities outside PIPA’s boundaries, legal fishing efforts surrounding PIPA caused the researchers to wonder whether PIPA might eventually provide an economic gain in the form of “spillover effects.” In other words, if an ecological region is preserved over long periods of time, it might produce more fish that, once full-grown, might cross the territory’s boundaries, benefiting both Kiribati and the regional fishing community.

Hernández’ colleague, Randi Rotjan of Boston University, had been working with the Republic of Kiribati on ways to scientifically monitor PIPA, and wanted to assess whether the protected region might also serve as protected spawning grounds for migratory tuna.

In 2014, the team began yearly expeditions to the central Pacific, to sample within PIPA for tuna larvae, fish younger than 4 weeks old, that would suggest recent spawning activity in the region. The researchers embarked on a 140-foot-long student sailing vessel, owned and operated by Sea Education Association, which also collaborated on this study. Sailing from Hawaii, the ship reached the edges of PIPA after about a 10-day journey. Once within the protected area, the team began sampling the waters for tiny fish, using three different nets, each designed to collect at 100 meters, 50 meters, and skimming the surface.

The team pulled up nets teeming with ocean plankton, including tuna larvae, along with tiny crustaceans, jellyfish, pelagic worms, and anchovies, all of which they preserved and transported back to Massachusetts, where they carried out analyses to extract and identify the number and type of tuna larvae amid the rest of the catch.

From 2015 to 2017, the three years included in the current paper, the researchers analyzed samples from over 175 net tows, and identified more than 600 tuna larvae, covering a distance within PIPA of more than 650 nautical miles, or 1,200 kilometers. Compared with a handful of previous studies on tuna larvae populations, Hernández says the number and density of larvae they found is “pretty on track for what we expect for this part of the Pacific.”

“Larval populations can’t really control how they move, and they get mixed around by ocean currents and dispersed away from each other,” Hernández explains. “As they continue to grow, they start to school and are in denser aggregations. But as larvae, they live at low densities.”

The tuna larvae appeared in about similar abundances over all three years, and even in 2015, when a strong El Niño season dramatically altered ocean conditions.

“That’s something that’s relatively good news, that the protected area seems to be pretty good habitat across environmental conditions,” Hernández says.

The team identified tuna larvae in their samples as species of skipjack, big-eye, and yellowfin.

“These particular fish are not so picky about where they spawn, and they can spawn every two to three days, for a couple of months,” Hernández says. “If they’re thinking the food is pretty good in PIPA, they may stay inside its boundaries for a few weeks, and might have additional spawning events that they wouldn’t have if they were outside the protected area, where they could get caught before they spawn.”

The results are the first evidence that highly migratory species spawn in marine protected areas. But whether such regions encourage species to reproduce more than in other, unprotected waters will require studies over a longer period of time.

“We have to protect these areas long enough to figure out if they are causing an increase in tuna populations,” Hernández says. “The amount of information we have about the Pacific tuna is paltry. And it’s critically important that we study the early life stages of fishes, and that we monitor protected areas, and populations of tuna, as the ocean changes.”

This work was supported in part by the PIPA Trust, Sea Education Association, the Prince Albert of Monaco Foundation II, New England Aquarium, and Boston University.

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