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      in Environment

      MADMEC winner identifies sustainable greenhouse-cooling materials

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      The winners of this year’s MADMEC competition identified a class of materials that could offer a more efficient way to keep greenhouses cool.

      After Covid-19 put the materials science competition on pause for two years, on Tuesday SmartClime, a team made up of three MIT graduate students, took home the first place, $10,000 prize.

      The team showed that a type of material that changes color in response to an electric voltage could reduce energy usage and save money if coated onto the panes of glass in greenhouses.

      “This project came out of our love of gardening,” said SmartClime team member and PhD candidate Isabella Caruso in the winning presentation. “Greenhouses let you grow things year-round, even in New England, but even greenhouse pros need to use heating furnaces in the winter and ventilation in the summer. All of that can be very labor- and energy-intensive.”

      Current options to keep greenhouses cool include traditional air conditioning units, venting and fans, and simple cloth. To develop a better solution, the team looked through scientific papers to find materials with the right climate control properties.

      Two classes of materials that looked promising were thermochromic coatings, which change color based on temperature, and electrochromic solutions, which change color based on electric voltage.

      Creating both the thermochromic and electrochromic solutions required the team to assemble nanoparticles and spin-coat them onto glass substrates. In lab tests, the electrochromic material performed well, turning a deep bluish hue to reduce the heat coming into the greenhouse while also letting in enough light for plants. Specifically, the electrochromic cell kept its test box about 1 to 3 degrees Celsius cooler than the test box coated in regular glass.

      The team estimated that greenhouse owners could make back the added costs of the electrochromic paneling through savings on other climate-control measures. Additional benefits of using the material include reducing heat-related crop losses, increasing crop yields, and reducing water requirements.

      Hosted by MIT’s Department of Materials Science and Engineering (DMSE), the competition was the culmination of team projects that began last spring and included a series of design challenges throughout the summer. Each team received guidance, access to equipment and labs, and up to $1,000 in funding to build and test their prototypes.

      “It’s great to be back and to have everyone here in person,” Mike Tarkanian, a senior lecturer in DMSE and coordinator of MADMEC, said at the event. “I’ve enjoyed getting back to normal, doing the design challenges over the summer and celebrating with everyone here today.”

      The second-place prize was split between YarnZ, which identified a nanofiber yarn that is more sustainable than traditional textile fibers, and WasteAway, which has developed a waste bin monitoring device that can identify the types of items thrown into trash and recycling bins and flag misplaced items.

      YarnZ (which stands for Yarns Are Really NanofiberZ), developed a nanofiber yarn that is more degradable than traditional microfiber yarns without sacrificing on performance.

      A large chunk of the waste and emissions in the clothing industry come from polyester, a slow-degrading polymer that requires an energy-intensive melt spinning process before it’s spun into the fibers of our clothes.

      “The biggest thing I want to impress upon you today is that the textile industry is a major greenhouse gas-producing entity and also produces a huge amount of waste,” YarnZ member and PhD candidate Natalie Mamrol said in the presentation.

      To replace polyester, the team developed a continuous process in which a type of nanofiber film collects in a water bath before being twisted into yarn. In subsequent tests, the nanofiber-based yarn degraded more quicky than traditional microfibers and showed comparable durability. YarnZ believes this early data should encourage others to explore nanofibers as a viable replacement in the clothing industry and to invest in scaling the approach for industrial settings.

      WasteAway’s system includes a camera that sits on top of trash bins and uses artificial intelligence to recognize items that people throw away.

      Of the 300 million tons of waste generated in the U.S. each year, more than half ends up in landfills. A lot of that waste could have been composted or recycled but was misplaced during disposal.

      “When someone throws something into the bin, our sensor detects the motion and captures an image,” explains WasteAway’s Melissa Stok, an undergraduate at MIT. “Those images are then processed by our machine-learning algorithm to find contamination.”

      Each device costs less than $30, and the team says that cost could go down as parts are bought at larger scales. The insights gleaned from the device could help waste management officials identify contaminated trash piles as well as inform education efforts by revealing common mistakes people make.

      Overall, Tarkanian believes the competition was a success not only because of the final results, but because of the experience the students got throughout the MADMEC program, which included several smaller, hands-on competitions involving laser cutters, 3-D printers, soldering irons, and other equipment many students said they had never used before.

      “They end up getting into the lab through these design challenges, which have them compete in various engineering tasks,” Tarkanian says. “It helps them get comfortable designing and prototyping, and they often end up using those tools in their research later.” More

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      in Energy

      Simulating neutron behavior in nuclear reactors

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      Amelia Trainer applied to MIT because she lost a bet.

      As part of what the fourth-year nuclear science and engineering (NSE) doctoral student labels her “teenage rebellious phase,” Trainer was quite convinced she would just be wasting the application fee were she to submit an application. She wasn’t even “super sure” she wanted to go to college. But a high-school friend was convinced Trainer would get into a “top school” if she only applied. A bet followed: If Trainer lost, she would have to apply to MIT. Trainer lost — and is glad she did.

      Growing up in Daytona Beach, Florida, good grades were Trainer’s thing. Seeing friends participate in interschool math competitions, Trainer decided she would tag along and soon found she loved them. She remembers being adept at reading the room: If teams were especially struggling over a problem, Trainer figured the answer had to be something easy, like zero or one. “The hardest problems would usually have the most goofball answers,” she laughs.

      Simulating neutron behavior

      As a doctoral student, hard problems in math, specifically computational reactor physics, continue to be Trainer’s forte.

      Her research, under the guidance of Professor Benoit Forget in MIT NSE’s Computational Reactor Physics Group (CRPG), focuses on modeling complicated neutron behavior in reactors. Simulation helps forecast the behavior of reactors before millions of dollars sink into development of a potentially uneconomical unit. Using simulations, Trainer can see “where the neutrons are going, how much heat is being produced, and how much power the reactor can generate.” Her research helps form the foundation for the next generation of nuclear power plants.

      To simulate neutron behavior inside of a nuclear reactor, you first need to know how neutrons will interact with the various materials inside the system. These neutrons can have wildly different energies, thereby making them susceptible to different physical phenomena. For the entirety of her graduate studies, Trainer has been primarily interested in the physics regarding slow-moving neutrons and their scattering behavior.

      When a slow neutron scatters off of a material, it can induce or cancel out molecular vibrations between the material’s atoms. The effect that material vibrations can have on neutron energies, and thereby on reactor behavior, has been heavily approximated over the years. Trainer is primarily interested in chipping away at these approximations by creating scattering data for materials that have historically been misrepresented and by exploring new techniques for preparing slow-neutron scattering data.

      Trainer remembers waiting for a simulation to complete in the early days of the Covid-19 pandemic, when she discovered a way to predict neutron behavior with limited input data. Traditionally, “people have to store large tables of what neutrons will do under specific circumstances,” she says. “I’m really happy about it because it’s this really cool method of sampling what your neutron does from very little information,” Trainer says.

      Amelia Trainer — Modeling complicated neutron behavior in nuclear reactors

      As part of her research, Trainer often works closely with two software packages: OpenMC and NJOY. OpenMC is a Monte Carlo neutron transport simulation code that was developed in the CRPG and is used to simulate neutron behavior in reactor systems. NJOY is a nuclear data processing tool, and is used to create, augment, and prepare material data that is fed into tools like OpenMC. By editing both these codes to her specifications, Trainer is able to observe the effect that “upstream” material data has on the “downstream” reactor calculations. Through this, she hopes to identify additional problems: approximations that could lead to a noticeable misrepresentation of the physics.

      A love of geometry and poetry

      Trainer discovered the coolness of science as a child. Her mother, who cares for indoor plants and runs multiple greenhouses, and her father, a blacksmith and farrier, who explored materials science through his craft, were self-taught inspirations.

      Trainer’s father urged his daughter to learn and pursue any topics that she found exciting and encouraged her to read poems from “Calvin and Hobbes” out loud when she struggled with a speech impediment in early childhood. Reading the same passages every day helped her memorize them. “The natural manifestation of that extended into [a love of] poetry,” Trainer says.

      A love of poetry, combined with Trainer’s propensity for fun, led her to compose an ode to pi as part of an MIT-sponsored event for alumni. “I was really only in it for the cupcake,” she laughs. (Participants received an indulgent treat).

      Play video

      MIT Matters: A Love Poem to Pi

      Computations and nuclear science

      After being accepted at MIT, Trainer knew she wanted to study in a field that would take her skills at the levels they were at — “my math skills were pretty underdeveloped in the grand scheme of things,” she says. An open-house weekend at MIT, where she met with faculty from the NSE department, and the opportunity to contribute to a discipline working toward clean energy, cemented Trainer’s decision to join NSE.

      As a high schooler, Trainer won a scholarship to Embry-Riddle Aeronautical University to learn computer coding and knew computational physics might be more aligned with her interests. After she joined MIT as an undergraduate student in 2014, she realized that the CRPG, with its focus on coding and modeling, might be a good fit. Fortunately, a graduate student from Forget’s team welcomed Trainer’s enthusiasm for research even as an undergraduate first-year. She has stayed with the lab ever since. 

      Research internships at Los Alamos National Laboratory, the creators of NJOY, have furthered Trainer’s enthusiasm for modeling and computational physics. She met a Los Alamos scientist after he presented a talk at MIT and it snowballed into a collaboration where she could work on parts of the NJOY code. “It became a really cool collaboration which led me into a deep dive into physics and data preparation techniques, which was just so fulfilling,” Trainer says. As for what’s next, Trainer was awarded the Rickover fellowship in nuclear engineering by the the Department of Energy’s Naval Reactors Division and will join the program in Pittsburgh after she graduates.

      For many years, Trainer’s cats, Jacques and Monster, have been a constant companion. “Neutrons, computers, and cats, that’s my personality,” she laughs. Work continues to fuel her passion. To borrow a favorite phrase from Spaceman Spiff, Trainer’s favorite “Calvin” avatar, Trainer’s approach to research has invariably been: “Another day, another mind-boggling adventure.” More

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      in Energy

      Building better batteries, faster

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      To help combat climate change, many car manufacturers are racing to add more electric vehicles in their lineups. But to convince prospective buyers, manufacturers need to improve how far these cars can go on a single charge. One of their main challenges? Figuring out how to make extremely powerful but lightweight batteries.

      Typically, however, it takes decades for scientists to thoroughly test new battery materials, says Pablo Leon, an MIT graduate student in materials science. To accelerate this process, Leon is developing a machine-learning tool for scientists to automate one of the most time-consuming, yet key, steps in evaluating battery materials.

      With his tool in hand, Leon plans to help search for new materials to enable the development of powerful and lightweight batteries. Such batteries would not only improve the range of EVs, but they could also unlock potential in other high-power systems, such as solar energy systems that continuously deliver power, even at night.

      From a young age, Leon knew he wanted to pursue a PhD, hoping to one day become a professor of engineering, like his father. Growing up in College Station, Texas, home to Texas A&M University, where his father worked, many of Leon’s friends also had parents who were professors or affiliated with the university. Meanwhile, his mom worked outside the university, as a family counselor in a neighboring city.

      In college, Leon followed in his father’s and older brother’s footsteps to become a mechanical engineer, earning his bachelor’s degree at Texas A&M. There, he learned how to model the behaviors of mechanical systems, such as a metal spring’s stiffness. But he wanted to delve deeper, down to the level of atoms, to understand exactly where these behaviors come from.

      So, when Leon applied to graduate school at MIT, he switched fields to materials science, hoping to satisfy his curiosity. But the transition to a different field was “a really hard process,” Leon says, as he rushed to catch up to his peers.

      To help with the transition, Leon sought out a congenial research advisor and found one in Rafael Gómez-Bombarelli, an assistant professor in the Department of Materials Science and Engineering (DMSE). “Because he’s from Spain and my parents are Peruvian, there’s a cultural ease with the way we talk,” Leon says. According to Gómez-Bombarelli, sometimes the two of them even discuss research in Spanish — a “rare treat.” That connection has empowered Leon to freely brainstorm ideas or talk through concerns with his advisor, enabling him to make significant progress in his research.

      Leveraging machine learning to research battery materials

      Scientists investigating new battery materials generally use computer simulations to understand how different combinations of materials perform. These simulations act as virtual microscopes for batteries, zooming in to see how materials interact at an atomic level. With these details, scientists can understand why certain combinations do better, guiding their search for high-performing materials.

      But building accurate computer simulations is extremely time-intensive, taking years and sometimes even decades. “You need to know how every atom interacts with every other atom in your system,” Leon says. To create a computer model of these interactions, scientists first make a rough guess at a model using complex quantum mechanics calculations. They then compare the model with results from real-life experiments, manually tweaking different parts of the model, including the distances between atoms and the strength of chemical bonds, until the simulation matches real life.

      With well-studied battery materials, the simulation process is somewhat easier. Scientists can buy simulation software that includes pre-made models, Leon says, but these models often have errors and still require additional tweaking.

      To build accurate computer models more quickly, Leon is developing a machine-learning-based tool that can efficiently guide the trial-and-error process. “The hope with our machine learning framework is to not have to rely on proprietary models or do any hand-tuning,” he says. Leon has verified that for well-studied materials, his tool is as accurate as the manual method for building models.

      With this system, scientists will have a single, standardized approach for building accurate models in lieu of the patchwork of approaches currently in place, Leon says.

      Leon’s tool comes at an opportune time, when many scientists are investigating a new paradigm of batteries: solid-state batteries. Compared to traditional batteries, which contain liquid electrolytes, solid-state batteries are safer, lighter, and easier to manufacture. But creating versions of these batteries that are powerful enough for EVs or renewable energy storage is challenging.

      This is largely because in battery chemistry, ions dislike flowing through solids and instead prefer liquids, in which atoms are spaced further apart. Still, scientists believe that with the right combination of materials, solid-state batteries can provide enough electricity for high-power systems, such as EVs. 

      Leon plans to use his machine-learning tool to help look for good solid-state battery materials more quickly. After he finds some powerful candidates in simulations, he’ll work with other scientists to test out the new materials in real-world experiments.

      Helping students navigate graduate school

      To get to where he is today, doing exciting and impactful research, Leon credits his community of family and mentors. Because of his upbringing, Leon knew early on which steps he would need to take to get into graduate school and work toward becoming a professor. And he appreciates the privilege of his position, even more so as a Peruvian American, given that many Latino students are less likely to have access to the same resources. “I understand the academic pipeline in a way that I think a lot of minority groups in academia don’t,” he says.

      Now, Leon is helping prospective graduate students from underrepresented backgrounds navigate the pipeline through the DMSE Application Assistance Program. Each fall, he mentors applicants for the DMSE PhD program at MIT, providing feedback on their applications and resumes. The assistance program is student-run and separate from the admissions process.

      Knowing firsthand how invaluable mentorship is from his relationship with his advisor, Leon is also heavily involved in mentoring junior PhD students in his department. This past year, he served as the academic chair on his department’s graduate student organization, the Graduate Materials Council. With MIT still experiencing disruptions from Covid-19, Leon noticed a problem with student cohesiveness. “I realized that traditional [informal] modes of communication across [incoming class] years had been cut off,” he says, making it harder for junior students to get advice from their senior peers. “They didn’t have any community to fall back on.”

      To help fix this problem, Leon served as a go-to mentor for many junior students. He helped second-year PhD students prepare for their doctoral qualification exam, an often-stressful rite of passage. He also hosted seminars for first-year students to teach them how to make the most of their classes and help them acclimate to the department’s fast-paced classes. For fun, Leon organized an axe-throwing event to further facilitate student cameraderie.

      Leon’s efforts were met with success. Now, “newer students are building back the community,” he says, “so I feel like I can take a step back” from being academic chair. He will instead continue mentoring junior students through other programs within the department. He also plans to extend his community-building efforts among faculty and students, facilitating opportunities for students to find good mentors and work on impactful research. With these efforts, Leon hopes to help others along the academic pipeline that he’s become familiar with, journeying together over their PhDs. More

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      in Environment

      From bridges to DNA: civil engineering across disciplines

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      How is DNA like a bridge? This question is not a riddle or logic game, it is a concern of Johannes Kalliauer’s doctoral thesis.

      As a student at TU Wien in Austria, Kalliauer was faced with a monumental task: combining approaches from civil engineering and theoretical physics to better understand the forces that act on DNA.

      Kalliauer, now a postdoc at the MIT Concrete Sustainability Hub, says he modeled DNA as though it were a beam, using molecular dynamics principles to understand its structural properties.

      “The mechanics of very small objects, like DNA helices, and large ones, like bridges, are quite similar. Each may be understood in terms of Newtonian mechanics. Forces and moments act on each system, subjecting each to deformations like twisting, stretching, and warping,” says Kalliauer.

      As a 2020 article from TU Wien noted, Kalliauer observed a counterintuitive behavior when examining DNA at an atomic level. Unlike a typical spring which becomes less coiled as it is stretched, DNA was observed to become more wound as its length was increased. 

      In situations like these where conventional logic appears to break down, Kalliauer relies on the intuition he has gained as an engineer.

      “To understand this strange behavior in DNA, I turned to a fundamental approach: I examined what was the same about DNA and macroscopic structures and what was different. Civil engineers use methods and calculations which have been developed over centuries and which are very similar to the ones I employed for my thesis,” Kalliauer explains. 

      As Kalliauer continues, “Structural engineering is an incredibly versatile discipline. If you understand it, you can understand atomistic objects like DNA strands and very large ones like galaxies. As a researcher, I rely on it to help me bring new viewpoints to fields like biology. Other civil engineers can and should do the same.”

      Kalliauer, who grew up in a small town in Austria, has spent his life applying unconventional approaches like this across disciplines. “I grew up in a math family. While none of us were engineers, my parents instilled an appreciation for the discipline in me and my two older sisters.”

      After middle school, Kalliauer attended a technical school for civil engineering, where he discovered a fascination for mechanics. He also worked on a construction site to gain practical experience and see engineering applied in a real-world context.

      Kalliauer studied out of interest intensely, working upwards of 100 hours per week to better understand coursework in university. “I asked teachers and professors many questions, often challenging their ideas. Above everything else, I needed to understand things for myself. Doing well on exams was a secondary concern.”

      In university, he studied topics ranging from car crash testing to concrete hinges to biology. As a new member of the CSHub, he is studying how floods may be modeled with the statistical physics-based model provided by lattice density functional theory.

      In doing this, he builds on the work of past and present CSHub researchers like Elli Vartziotis and Katerina Boukin. 

      “It’s important to me that this research has a real impact in the world. I hope my approach to engineering can help researchers and stakeholders understand how floods propagate in urban contexts, so that we may make cities more resilient,” he says. More

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      in Environment

      Four researchers with MIT ties earn Schmidt Science Fellowships

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      Four researchers with MIT ties — Juncal Arbelaiz, Xiangkun (Elvis) Cao, Sandya Subramanian, and Heather Zlotnick ’17 — have been honored with competitive Schmidt Science Fellowships.

      Created in 2017, the fellows program aims to bring together the world’s brightest minds “to solve society’s toughest challenges.”

      The four MIT-affiliated researchers are among 29 Schmidt Science Fellows from around the world who will receive postdoctoral support for either one or two years with an annual stipend of $100,000, along with individualized mentoring and participation in the program’s Global Meeting Series. The fellows will also have opportunities to engage with thought-leaders from science, business, policy, and society. According to the award announcement, the fellows are expected to pursue research that shifts from the focus of their PhDs, to help expand and enhance their futures as scientific leaders.

      Juncal Arbelaiz is a PhD candidate in applied mathematics at MIT, who is completing her doctorate this summer. Her doctoral research at MIT is advised by Ali Jadbabaie, the JR East Professor of Engineering and head of the Department of Civil and Environmental Engineering; Anette Hosoi, the Neil and Jane Pappalardo Professor of Mechanical Engineering and associate dean of the School of Engineering; and Bassam Bamieh, professor of mechanical engineering and associate director of the Center for Control, Dynamical Systems, and Computation at the University of California at Santa Barbara. Arbelaiz’s research revolves around the design of optimal decentralized intelligence for spatially-distributed dynamical systems.

      “I cannot think of a better way to start my independent scientific career. I feel very excited and grateful for this opportunity,” says Arbelaiz. With her fellowship, she will enlist systems biology to explore how the nervous system encodes and processes sensory information to address future safety-critical artificial intelligence applications. “The Schmidt Science Fellowship will provide me with a unique opportunity to work at the intersection of biological and machine intelligence for two years and will be a steppingstone towards my longer-term objective of becoming a researcher in bio-inspired machine intelligence,” she says.

      Xiangkun (Elvis) Cao is currently a postdoc in the lab of T. Alan Hatton, the Ralph Landau Professor in Chemical Engineering, and an Impact Fellow at the MIT Climate and Sustainability Consortium. Cao received his PhD in mechanical engineering from Cornell University in 2021, during which he focused on microscopic precision in the simultaneous delivery of light and fluids by optofluidics, with advances relevant to health and sustainability applications. As a Schmidt Science Fellow, he plans to be co-advised by Hatton on carbon capture, and Ted Sargent, professor of chemistry at Northwestern University, on carbon utilization. Cao is passionate about integrated carbon capture and utilization (CCU) from molecular to process levels, machine learning to inspire smart CCU, and the nexus of technology, business, and policy for CCU.

      “The Schmidt Science Fellowship provides the perfect opportunity for me to work across disciplines to study integrated carbon capture and utilization from molecular to process levels,” Cao explains. “My vision is that by integrating carbon capture and utilization, we can concurrently make scientific discoveries and unlock economic opportunities while mitigating global climate change. This way, we can turn our carbon liability into an asset.”

      Sandya Subramanian, a 2021 PhD graduate of the Harvard-MIT Program in Health Sciences and Technology (HST) in the area of medical engineering and medical physics, is currently a postdoc at Stanford Data Science. She is focused on the topics of biomedical engineering, statistics, machine learning, neuroscience, and health care. Her research is on developing new technologies and methods to study the interactions between the brain, the autonomic nervous system, and the gut. “I’m extremely honored to receive the Schmidt Science Fellowship and to join the Schmidt community of leaders and scholars,” says Subramanian. “I’ve heard so much about the fellowship and the fact that it can open doors and give people confidence to pursue challenging or unique paths.”

      According to Subramanian, the autonomic nervous system and its interactions with other body systems are poorly understood but thought to be involved in several disorders, such as functional gastrointestinal disorders, Parkinson’s disease, diabetes, migraines, and eating disorders. The goal of her research is to improve our ability to monitor and quantify these physiologic processes. “I’m really interested in understanding how we can use physiological monitoring technologies to inform clinical decision-making, especially around the autonomic nervous system, and I look forward to continuing the work that I’ve recently started at Stanford as Schmidt Science Fellow,” she says. “A huge thank you to all of the mentors, colleagues, friends, and leaders I had the pleasure of meeting and working with at HST and MIT; I couldn’t have done this without everything I learned there.”

      Hannah Zlotnick ’17 attended MIT for her undergraduate studies, majoring in biological engineering with a minor in mechanical engineering. At MIT, Zlotnick was a student-athlete on the women’s varsity soccer team, a UROP student in Alan Grodzinsky’s laboratory, and a member of Pi Beta Phi. For her PhD, Zlotnick attended the University of Pennsylvania, and worked in Robert Mauck’s laboratory within the departments of Bioengineering and Orthopaedic Surgery.

      Zlotnick’s PhD research focused on harnessing remote forces, such as magnetism or gravity, to enhance engineered cartilage and osteochondral repair both in vitro and in large animal models. Zlotnick now plans to pivot to the field of biofabrication to create tissue models of the knee joint to assess potential therapeutics for osteoarthritis. “I am humbled to be a part of the Schmidt Science Fellows community, and excited to venture into the field of biofabrication,” Zlotnick says. “Hopefully this work uncovers new therapies for patients with inflammatory joint diseases.” More

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      in Energy

      Evan Leppink: Seeking a way to better stabilize the fusion environment

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      “Fusion energy was always one of those kind-of sci-fi technologies that you read about,” says nuclear science and engineering PhD candidate Evan Leppink. He’s recalling the time before fusion became a part of his daily hands-on experience at MIT’s Plasma Science and Fusion Center, where he is studying a unique way to drive current in a tokamak plasma using radiofrequency (RF) waves. 

      Now, an award from the U.S. Department of Energy’s (DOE) Office of Science Graduate Student Research (SCGSR) Program will support his work with a 12-month residency at the DIII-D National Fusion Facility in San Diego, California.

      Like all tokamaks, DIII-D generates hot plasma inside a doughnut-shaped vacuum chamber wrapped with magnets. Because plasma will follow magnetic field lines, tokamaks are able to contain the turbulent plasma fuel as it gets hotter and denser, keeping it away from the edges of the chamber where it could damage the wall materials. A key part of the tokamak concept is that part of the magnetic field is created by electrical currents in the plasma itself, which helps to confine and stabilize the configuration. Researchers often launch high-power RF waves into tokamaks to drive that current.

      Leppink will be contributing to research, led by his MIT advisor Steve Wukitch, that pursues launching RF waves in DIII-D using a unique compact antenna placed on the tokamak center column. Typically, antennas are placed inside the tokamak on the outer edge of the doughnut, farthest from the central hole (or column), primarily because access and installation are easier there. This is known as the “low-field side,” because the magnetic field is lower there than at the central column, the “high-field side.” This MIT-led experiment, for the first time, will mount an antenna on the high-field side. There is some theoretical evidence that placing the wave launcher there could improve power penetration and current drive efficiency. And because the plasma environment is less harsh on this side, the antenna will survive longer, a factor important for any future power-producing tokamak.

      Leppink’s work on DIII-D focuses specifically on measuring the density of plasmas generated in the tokamak, for which he developed a “reflectometer.” This small antenna launches microwaves into the plasma, which reflect back to the antenna to be measured. The time that it takes for these microwaves to traverse the plasma provides information about the plasma density, allowing researchers to build up detailed density profiles, data critical for injecting RF power into the plasma.

      “Research shows that when we try to inject these waves into the plasma to drive the current, they can lose power as they travel through the edge region of the tokamak, and can even have problems entering the core of the plasma, where we would most like to direct them,” says Leppink. “My diagnostic will measure that edge region on the high-field side near the launcher in great detail, which provides us a way to directly verify calculations or compare actual results with simulation results.”

      Although focused on his own research, Leppink has excelled at priming other students for success in their studies and research. In 2021 he received the NSE Outstanding Teaching Assistant and Mentorship Award.

      “The highlights of TA’ing for me were the times when I could watch students go from struggling with a difficult topic to fully understanding it, often with just a nudge in the right direction and then allowing them to follow their own intuition the rest of the way,” he says.

      The right direction for Leppink points toward San Diego and RF current drive experiments on DIII-D. He is grateful for the support from the SCGSR, a program created to prepare graduate students like him for science, technology, engineering, or mathematics careers important to the DOE Office of Science mission. It provides graduate thesis research opportunities through extended residency at DOE national laboratories. He has already made several trips to DIII-D, in part to install his reflectometer, and has been impressed with the size of the operation.

      “It takes a little while to kind of compartmentalize everything and say, ‘OK, well, here’s my part of the machine. This is what I’m doing.’ It can definitely be overwhelming at times. But I’m blessed to be able to work on what has been the workhorse tokamak of the United States for the past few decades.” More

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      in Environment

      Helping renewable energy projects succeed in local communities

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      Jungwoo Chun makes surprising discoveries about sustainability initiatives by zooming in on local communities.

      His discoveries lie in understanding how renewable energy infrastructure develops at a local level. With so many stakeholders in a community — citizens, government officials, businesses, and other organizations — the development process gets complicated very quickly. Chun works to unpack stakeholder relationships to help local renewable energy projects move forward.

      While his interests today are in local communities around the U.S., Chun comes from a global background. Growing up, his family moved frequently due to his dad’s work. He lived in Seoul, South Korea until elementary school and then hopped from city to city around Asia, spending time in China, Hong Kong, and Singapore. When it was time for college, he returned to South Korea, majoring in international studies at Korea University and later completing his master’s there in the same field.

      After graduating, Chun wanted to leverage his international expertise to tackle climate change. So, he pursued a second master’s in international environmental policy with William Moomaw at Tufts University.

      During that time, Chun came across an article on climate change by David Victor, a professor in public policy at the University of California at San Diego. Victor argued that while international efforts to fight climate change are necessary, more tangible progress can be made through local efforts catered to each country. That prompted Chun to think a step further: “What can we do in the local community to make a little bit of a difference, which could add up to something big in the long term?”

      With a renewed direction for his goals, Chun arrived at the MIT Department of Urban Studies and Planning, specializing in environmental policy and planning. But he was still missing that final inspirational spark to proactively pursue his goals — until he began working with his primary advisor, Lawrence Susskind, the Ford Professor of Urban and Environmental Planning and director of the Science Impact Collaborative.

      For previous research projects, “I would just do what I was told,” Chun says, but his new advisor “really opened [his] eyes” to being an active member of the community. From the start, Susskind has encouraged Chun to share his research ideas and has shown him how to leverage his research skills for public service. Over the past few years, Chun has also taught several classes with Susskind, learning to approach education thoughtfully for an engaging and equitable classroom. Because of their relationship, Chun now always searches for ways to make a difference through research, teaching, and public service.

      Understanding renewable energy projects at a local level

      For his main dissertation project with Susskind, Chun is studying community-owned solar energy projects, working to understand what makes them successful.

      Often, communities don’t have the required expertise to carry out these projects on their own and instead look to advisory organizations for help. But little research has been done on these organizations and the roles that they play in developing solar energy infrastructure.

      Through over 200 surveys and counting, Chun has discovered that these organizations act as life-long collaborators to communities and are critical in getting community-owned solar projects up and running. At the start of these projects, they walk communities through a mountain of logistics for setting up solar energy infrastructure, including permit applications, budgeting, and contractor employment. After the infrastructure is in place, the organizations stay involved, serving as consultants when needed and sometimes even becoming partners.

      Because of these roles, Chun calls these organizations “intermediaries,” drawing a parallel with roles in in conflict resolution. “But it’s much more than that,” he adds. Intermediaries help local communities “build a movement [for community-owned solar energy projects] … and empower them to be independent and self-sustaining.”

      Chun is also working on another project with Susskind, looking at situations where communities are opposed to renewable energy infrastructure. For this project, Chun is supervising and mentoring a group of five undergraduates. Together, they are trying to pinpoint the reasons behind local opposition to renewable energy projects.

      The idea for this project emerged two years ago, when Chun heard in the news that many solar and wind projects were being delayed or cancelled due to local opposition. But the reasons for this opposition weren’t thoroughly researched.

      “When we started to dig a little deeper, [we found that] communities oppose these projects even though they aren’t opposed to renewable energy,” Chun says. The primary reasons for opposition lie in land use concerns, including financial challenges, health and safety concerns, and ironically, environmental consequences. By better understanding these concerns, Chun hopes to help more renewable energy projects succeed and bring society closer to a sustainable future.

      Bringing research to the classroom and community

      Right now, Chun is looking to bring his research insights on renewable energy infrastructure into the classroom. He’s developing a course on renewable energy that will act as a “clinic” where students will work with communities to understand their concerns for potential renewable energy projects. The students’ findings will then be passed onto project leaders to help them address these concerns.

      This new course is modeled after 11.074/11.274 (Cybersecurity Clinic), which Chun has helped develop over the past few years. In this clinic, students work with local governments in New England to assess potential cybersecurity vulnerabilities in their digital systems. At first, “a lot of city governments were very skeptical, like ‘students doing service for us…?’” Chun says. “But in the end, they were all very satisfied with the outcome” and found the assessments “impactful.”

      Since the Cybersecurity Clinic has kicked off, other universities have approached Chun and his co-instructors about developing their own regional clinics. Now, there are cybersecurity clinics operating around the world. “That’s been a huge success,” Chun says. Going forward, “we’d like to expand the benefit of this clinic [to address] communities opposing renewable energy [projects].” The new course will be a philosophical trifecta for Chun, combining his commitments to research, teaching, and public service.

      Chun plans to wrap up his PhD at the end of this summer and is currently writing his dissertation on community-owned solar energy projects. “I’m done with all the background work — working the soil and throwing the seeds in the right place,” he says, “It’s now time to gather all the crops and present the work.” More

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      in Energy

      Solar-powered desalination device wins MIT $100K competition

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      The winner of this year’s MIT $100K Entrepreneurship Competition is commercializing a new water desalination technology.

      Nona Desalination says it has developed a device capable of producing enough drinking water for 10 people at half the cost and with 1/10th the power of other water desalination devices. The device is roughly the size and weight of a case of bottled water and is powered by a small solar panel.

      “Our mission is to make portable desalination sustainable and easy,” said Nona CEO and MIT MBA candidate Bruce Crawford in the winning pitch, delivered to an audience in the Kresge Auditorium and online.

      The traditional approach for water desalination relies on a power-intensive process called reverse osmosis. In contrast, Nona uses a technology developed in MIT’s Research Laboratory of Electronics that removes salt and bacteria from seawater using an electrical current.

      “Because we can do all this at super low pressure, we don’t need the high-pressure pump [used in reverse osmosis], so we don’t need a lot of electricity,” says Crawford, who co-founded the company with MIT Research Scientist Junghyo Yoon. “Our device runs on less power than a cell phone charger.”

      The founders cited problems like tropical storms, drought, and infrastructure crises like the one in Flint, Michigan, to underscore that clean water access is not just a problem in developing countries. In Houston, after Hurricane Harvey caused catastrophic flooding in 2017, some residents were advised not to drink their tap water for months.

      The company has already developed a small prototype that produces clean drinking water. With its winnings, Nona will build more prototypes to give to early customers.

      The company plans to sell its first units to sailors before moving into the emergency preparedness space in the U.S., which it estimates to be a $5 billion industry. From there, it hopes to scale globally to help with disaster relief. The technology could also possibly be used for hydrogen production, oil and gas separation, and more.

      The MIT $100K is MIT’s largest entrepreneurship competition. It began in 1989 and is organized by students with support from the Martin Trust Center for MIT Entrepreneurship and the MIT Sloan School of Management. Each team must include at least one current MIT student.

      The second-place $25,000 prize went to Inclusive.ly, a company helping people and organizations create a more inclusive environment.

      The company uses conversational artificial intelligence and natural language processing to detect words and phrases that contain bias, and can measure the level of bias or inclusivity in communication.

      “We’re here to create a world where everyone feels invited to the conversation,” said MBA candidate Yeti Khim, who co-founded the company with fellow MBA candidates Joyce Chen and Priya Bhasin.

      Inclusive.ly can scan a range of communications and make suggestions for improvement. The algorithm can detect discrimination, microaggression, and condescension, and the founders say it analyzes language in a more nuanced way than tools like Grammarly.

      The company is currently developing a plugin for web browsers and is hoping to partner with large enterprise customers later this year. It will work with internal communications like emails as well as external communications like sales and marketing material.

      Inclusive.ly plans to sell to organizations on a subscription model and notes that diversity and inclusion is becoming a higher priority in many companies. Khim cited studies showing that lack of inclusion hinders employee productivity, retention, and recruiting.

      “We could all use a little bit of help to create the most inclusive version of ourselves,” Khim said.

      The third-place prize went to RTMicrofluidics, which is building at-home tests for a range of diseases including strep throat, tuberculosis, and mononucleosis. The test is able to detect a host of bacterial and viral pathogens in saliva and provide accurate test results in less than 30 minutes.

      The audience choice award went to Sparkle, which has developed a molecular dye technology that can illuminate tumors, making them easier to remove during surgery.

      This year’s $100K event was the culmination of a process that began last March, when 60 teams applied for the program. Out of that pool, 20 semifinalists were given additional mentoring and support before eight finalists were selected to pitch.

      The other finalist teams were:

      Astrahl, which is developing high resolution and affordable X-ray systems by integrating nanotechnologies with scintillators;

      Encreto Therapeutics, which is discovering medications to satiate appetite for people with obesity;

      Iridence, which has patented a biomaterial to replace minerals like mica as a way to make the beauty industry more sustainable; and

      Mantel, which is developing a liquid material for more efficient carbon removal that operates at high temperatures. More