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      in Energy

      Pursuing progress at the nanoscale

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      Last fall, a team of five senior undergraduate nuclear engineering students met once a week for dinners where they took turns cooking and debated how to tackle a particularly daunting challenge set forth in their program’s capstone course, 22.033 (Nuclear Systems Design Project).

      In past semesters, students had free reign to identify any real-world problem that interested them to solve through team-driven prototyping and design. This past fall worked a little differently. The team continued the trend of tackling daunting problems, but instead got an assignment to explore a particular design challenge on MIT’s campus. Rising to the challenge, the team spent the semester seeking a feasible way to introduce a highly coveted technology at MIT.

      Housed inside a big blue dome is the MIT Nuclear Reactor Laboratory (NRL). The reactor is used to conduct a wide range of science experiments, but in recent years, there have been multiple attempts to implement an instrument at the reactor that could probe the structure of materials, molecules, and devices. With this technology, researchers could model the structure of a wide range of materials and complex liquids made of polymers or containing nanoscale inhomogeneities that differ from the larger mass. On campus, researchers for the first time could conduct experiments to better understand the properties and functions of anything placed in front of a neutron beam emanating from the reactor core.

      The impact of this would be immense. If the reactor could be adapted to conduct this advanced technique, known as small-angle neutron scattering (SANS), it would open up a whole new world of research at MIT.

      “It’s essentially using the nuclear reactor as an incredibly high-performance camera that researchers from all over MIT would be very interested in using, including nuclear science and engineering, chemical engineering, biological engineering, and materials science, who currently use this tool at other institutions,” says Zachary Hartwig, Nuclear Systems Design Project professor and the MIT Robert N. Noyce Career Development Professor.

      SANS instruments have been installed at fewer than 20 facilities worldwide, and MIT researchers have previously considered implementing the capability at the reactor to help MIT expand community-wide access to SANS. Last fall, this mission went from long-time campus dream to potential reality as it became the design challenge that Hartwig’s students confronted. Despite having no experience with SANS, the team embraced the challenge, taking the first steps to figure out how to bring this technology to campus.

      “I really loved the idea that what we were doing could have a very real impact,” says Zoe Fisher, Nuclear Systems Design Project team member and now graduate nuclear engineering student.

      Each fall, Hartwig uses the course to introduce students to real-world challenges with strict constraints on solutions, and last fall’s project came with plenty of thorny design questions for students to tackle. First was the size limitation posed by the space available at MIT’s reactor. In SANS facilities around the world, the average length of the instrument is 30 meters, but at NRL, the space available is approximately 7.5 meters. Second, these instruments can cost up to $30 million, which is far outside NRL’s proposed budget of $3 million. That meant not only did students need to design an instrument that would work in a smaller space, but also one that could be built for a tenth of the typical cost.

      “The challenge was not just implementing one of these instruments,” Hartwig says. “It was whether the students could significantly innovate beyond the ‘traditional’ approach to doing SANS to meet the daunting constraints that we have at the MIT Reactor.”

      Because NRL actually wants to pursue this project, the students had to get creative, and their creative potential was precisely why the idea arose to get them involved, says Jacopo Buongiorno, the director of science and technology at NRL and Tokyo Electric Power Company Professor in Nuclear Engineering. “Involvement in real-world projects that answer questions about feasibility and cost of new technology and capabilities is a key element of a successful undergraduate education at MIT,” Buongiorno says.

      Students say it would have been impossible to tackle the problem without the help of co-instructor Boris Khaykovich, a research scientist at NRL who specializes in neutron instrumentation.

      Over the past two decades, Khaykovich has watched as SANS became the most popular technique for analyzing material structure. As the amount of available SANS beam time at the few facilities that exist became more competitive, access declined. Today only the experiments passing the most stringent review get access. What Khaykovich hopes to bring to MIT is improved access to SANS by designing an instrument that will be suitable for a majority of run-of-the-mill experiments, even if it’s not as powerful as state-of-the-art national SANS facilities. Such an instrument can still serve a wider range of researchers who currently have few opportunities to pursue SANS experiments.

      “In the U.S., we don’t have a simple, small, day-to-day SANS instrument,” Khaykovich says.

      With Khaykovich’s help, nuclear engineering undergraduate student Liam Hines says his team was able to go much further with their assessment than they would’ve starting from scratch, with no background in SANS. This project was unlike anything they’d ever been asked of as MIT students, and for students like Hines, who contributed to NRL research his entire time on campus, it was a project that hit close to home. “We were imagining this thing that might be designed at MIT,” Hines says.

      Fisher and Hines were joined by undergraduate nuclear engineering student team members Francisco Arellano, Jovier Jimenez, and Brendan Vaughan. Together, they devised a design that surprised both Khaykovich and Hartwig, identifying creative solutions that overcame all limitations and significantly reduced cost.

      Their team’s final project featured an adaptation of a conical design that was recently experimentally tested in Japan, but not generally used. The conical design allowed them to maximize precision while working within the other constraints, resulting in an instrument design that exceeded Hartwig’s expectations. The students also showed the feasibility of using an alternative type of glass-based low-cost neutron detector to calibrate the scattering data. By avoiding the need for a traditional detector based on helium-3, which is increasingly scarce and exorbitantly expensive, such a detector would dramatically reduce cost and increase availability. Their final presentation indicated the day-to-day SANS instrument could be built at only 4.5 meters long and with an estimated cost less than $1 million.

      Khaykovich credited the students for their enthusiasm, bouncing ideas off each other and exploring as much terrain as possible by interviewing experts who implemented SANS at other facilities. “They showed quite a perseverance and an ability to go deep into a very unfamiliar territory for them,” Khaykovich says.

      Hines says that Hartwig emphasized the importance of fielding expert opinions to more quickly discover optimal solutions. Fisher says that based on their research, if their design is funded, it would make SANS “more accessible to research for the sake of knowledge,” rather than dominated by industry research.

      Hartwig and Khaykovich agreed the students’ final project results showed a baseline of how MIT could pursue SANS technology cheaply, and when NRL proceeds with its own design process, Hartwig says, “The student’s work might actually change the cost of the feasibility of this at MIT in a way that if we hadn’t run the class, we would never have thought about doing.”

      Buongiorno says as they move forward with the project, NRL staff will consult students’ findings.

      “Indeed, the students developed original technical approaches, which are now being further explored by the NRL staff and may ultimately lead to the deployment of this new important capability on the MIT campus,” Buongiorno says.

      Hartwig says it’s a goal of the Nuclear Systems Design Project course to empower students to learn how to lead teams and embrace challenges, so they can be effective leaders advancing novel solutions in research and industry. “I think it helps teach people to be agile, to be flexible, to have confidence that they can actually go off and learn what they don’t know and solve problems they may think are bigger than themselves,” he says.

      It’s common for past classes of Nuclear Systems Design Project students to continue working on ideas beyond the course, and some students have even launched companies from their project research. What’s less common is for Hartwig’s students to actively serve as engineers pointed to a particular campus problem that’s expected to be resolved in the next few years.

      “In this case, they’re actually working on something real,” Hartwig says. “Their ideas are going to very much influence what we hope will be a facility that gets built at the reactor.”

      For students, it was exciting to inform a major instrument proposal that will soon be submitted to federal funding agencies, and for Hines, it became a chance to make his mark at NRL.

      “This is a lab I’ve been contributing to my entire time at MIT, and then through this project, I finished my time at MIT contributing in a much larger sense,” Hines says. More

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      in Environment

      Conversations at the front line of climate

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      The climate crisis is a novel and developing chapter in human and planetary history. As a species, humankind is still very much learning how to face this crisis, and the world’s frontline communities — those being most affected by climate change — are struggling to make their voices heard. How can communities imperiled by climate change convey the urgency of their situation to countries and organizations with the means to make a difference? And how can governments and other powerful groups provide resources to these vulnerable frontline communities?The MIT Civic Design Initiative (CDI), an interdisciplinary confluence of media studies and design expertise, emerged in 2020 to tackle just these kinds of questions. It brings together the MIT Design Lab, a program originally founded in the School of Architecture and Planning with its research practices in design, and the Comparative Media Studies program (CMS/W) with its focus on the fundamentals of human connection and communication. Drawing on these complementary sources of scholarly perspective and expertise, CDI is a suitably broad umbrella for the range of climate-related issues that humanistic research and design can potentially address. Based in the CMS/W program of the School of Humanities, Arts, and Social Sciences, the initiative is responding to the climate crises with a spirit of inquiry, listening, and solid data. Reflecting on the mission, James Paradis, the Robert M. Metcalfe Professor of CMS/W and CDI faculty director, says the core idea is to address global issues by combining new and emerging technologies with an equally keen focus on the social and cultural contexts — the human dimensions of the issue — with many of their nuances.  Working closely with Paradis on this vision are the two CDI co-directors: Yihyun Lim, an architect, urban designer, and MIT researcher; and Eric Gordon, a visiting professor of civic media in MIT CMS/W. Prior to CDI, when she was leading the MIT Design Lab research group, Lim says “At MIT Design Lab, I was working within the realm of applied research with industry partnerships, how we can apply user-centered design methods in creating connected experiences. Eric, Jim, and I wanted to shift the focus into a more civic realm, where we could bring all our collective expertise together to address tricky problems.”

      Deep listeningThe initiative’s flagship project, the Deep Listening Project, is currently working with an initial group of frontline communities in Nepal and Indigenous tribes in the United States and Canada. The work is a direct application of communication protocols: understanding how people are communicating with and often without technologies — and how technologies can be better used to help people get the help they need, when they need it, in the face of the climate crisis.

      The CDI team describes deep listening as “a form of institutional and community intake that considers diversity, tensions, and frictions, and that incorporates communities’ values in creating solutions.”

      Globally, the majority of climate response funding currently goes toward mitigation efforts — such as reducing emissions or using more eco-friendly materials. It is only in recent years that more substantial funding has been focused on climate adaptation: making adjustments that can help a community adapt to present changes and impacts and also prepare for future climate-related crises. For the millions of people in frontline communities, such adaptation can be crucial to protecting and sustaining their communities.Gordon describes the scope of the situation: “We know that over the next 10 years, climate change will drive over 100 million people to adapt where and how they live, regardless of the success of mitigation efforts. And in order for those adaptations to succeed, there must be a concerted collaborative effort between frontline communities and institutions with the resources to facilitate adaptation.“Communication between institutions and their constituents is a fundamental planning problem in any context,” Gordon continues. “In the case of climate adaptation, there will not be a surplus of time to get things right. Putting communication mechanisms in place to connect affected communities with institutional resources is already imperative.“This situation requires that we figure out, quickly, how to listen to the people who will rely on [those institutions] for their lives and livelihoods. We want to understand how institutions — from governments to universities to NGOs [nongovernmental organizations] — are adopting and adapting technologies, and how that is benefiting or hurting their constituencies.  People with direct frontline experience need to be supported in their speech and ideas, and institutions need to be able to take in the data from these communities, listen carefully to discern its significance, and then act upon it.” Sensemaking: infrastructure for connection

      One important aspect of meaningful, effective communication will be the ability of frontline and Indigenous communities to communicate likely or imagined futures, based on their own knowledge and desires. One potential tool is what the initiative calls “sensemaking:” producing and sharing data visualizations that can communicate to governments the experiences of frontline communities. The initiative also hopes to develop additional elements of the “deep listening infrastructure” — mechanisms to make sure important community voices carry and that important data isn’t lost to noise in the vast question of climate adaptability.“Oftentimes in academia, the paper gets published or the website gets developed, and everybody says, ‘OK, we’ve done our work,’” Paradis observes. “What we’re aiming to do in the CDI is the necessary work that happens after the publication of research — where research is applied to actually improve peoples’ lives.”The Deep Listening Project is also building a network of scholars and practitioners nationwide, including Henry Jenkins, co-founder and former faculty member at MIT CMS/W; Sangita Shresthova SM ’03 at the University of Southern California; and Darren Ranco at the University of Maine. Ranco, an anthropologist, Indigenous activist, and organizational leader, has been instrumental in connecting with Indigenous groups and tribal governments across North America. Meanwhile, Gordon has helped forge connections with groups like the International Red Cross/Red Crescent, the World Bank, and the UN Development. At the root of these connections is the impetus to communicate lived realities from the level of a small community to that of global relief organizations and governmental powers.

      Potential human futures

      Mona Vijaykumar, a second-year student in the SMArchS Architecture and Urbanism program in the Department of Architecture, and among the first student researcher assistants attached to the new initiative, is excited to have the chance to help build CDI from the ground up. “It’s been a great honor to be working with CDI’s amazing team for the last eight months,” she says. With her background in urban design and research interest in climate adaptation processes, Vijaykumar has been engaged in developing the Deep Listening Project’s white paper as part of MIT Climate Grand Challenges. She works alongside the initiative’s two other inaugural research assistants: Tomas Guarna, a master’s student in CMS, and Gabriela Degetau, a master’s student in the SMarchS Urbanism program, with Vijaykumar.“I was involved in analyzing the literature case study on community-based adaptation processes and co-writing the white paper,” Vijaykumar says, “and am currently working on conducting interviews with communities and institutions in India. Going forward, Gabriela and I will be presenting the white paper at gatherings such as the American Association of Geographers’ Conference in New York and the Climate and Social Impact Conference in Vancouver.”“The support and collaboration of the team have been incredibly empowering,” reflects Degetau, who will be co-presenting the white paper with Vijaykumar in New York and Vancouver, British Columbia. “Even when working from different countries and through Zoom, the experience has been unique and cohesive.”Both Degetau and Vijaykumar were selected as the first fellows of the Vuslat Foundation, organized by the MIT Transmedia Storytelling Initiative. In this one-year fellowship, they are seeking to co-design “climate imaginaries” through the Deep Listening Project. Vijaykumar’s work is also supported by the MIT Human Rights and Technology Fellowship for 2021-22, which guides her personal focus on what she refers to as the “dual sword” of technology and data colonialism in India.As the Deep Listening Project continues to develop a sustainable and balanced communication infrastructure, Lim reflects that a vital part of that is sharing how potential futures are envisioned. Both large institutions and individual communities imagine, separately — and hopefully soon together — how the human world will reshape itself to be viable in profoundly shifting climate conditions. “What are our possible futures?” asks Lim. “What are people dreaming?” 

      Story prepared by MIT SHASS CommunicationsEditorial and design director: Emily HiestandSenior communications associate: Alison Lanier More

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      in Security

      Meet the 2021-22 Accenture Fellows

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      Launched in October of 2020, the MIT and Accenture Convergence Initiative for Industry and Technology underscores the ways in which industry and technology come together to spur innovation. The five-year initiative aims to achieve its mission through research, education, and fellowships. To that end, Accenture has once again awarded five annual fellowships to MIT graduate students working on research in industry and technology convergence who are underrepresented, including by race, ethnicity, and gender.

      This year’s Accenture Fellows work across disciplines including robotics, manufacturing, artificial intelligence, and biomedicine. Their research covers a wide array of subjects, including: advancing manufacturing through computational design, with the potential to benefit global vaccine production; designing low-energy robotics for both consumer electronics and the aerospace industry; developing robotics and machine learning systems that may aid the elderly in their homes; and creating ingestible biomedical devices that can help gather medical data from inside a patient’s body.

      Student nominations from each unit within the School of Engineering, as well as from the four other MIT schools and the MIT Schwarzman College of Computing, were invited as part of the application process. Five exceptional students were selected as fellows in the initiative’s second year.

      Xinming (Lily) Liu is a PhD student in operations research at MIT Sloan School of Management. Her work is focused on behavioral and data-driven operations for social good, incorporating human behaviors into traditional optimization models, designing incentives, and analyzing real-world data. Her current research looks at the convergence of social media, digital platforms, and agriculture, with particular attention to expanding technological equity and economic opportunity in developing countries. Liu earned her BS from Cornell University, with a double major in operations research and computer science.

      Caris Moses is a PhD student in electrical engineering and computer science specializing inartificial intelligence. Moses’ research focuses on using machine learning, optimization, and electromechanical engineering to build robotics systems that are robust, flexible, intelligent, and can learn on the job. The technology she is developing holds promise for industries including flexible, small-batch manufacturing; robots to assist the elderly in their households; and warehouse management and fulfillment. Moses earned her BS in mechanical engineering from Cornell University and her MS in computer science from Northeastern University.

      Sergio Rodriguez Aponte is a PhD student in biological engineering. He is working on the convergence of computational design and manufacturing practices, which have the potential to impact industries such as biopharmaceuticals, food, and wellness/nutrition. His current research aims to develop strategies for applying computational tools, such as multiscale modeling and machine learning, to the design and production of manufacturable and accessible vaccine candidates that could eventually be available globally. Rodriguez Aponte earned his BS in industrial biotechnology from the University of Puerto Rico at Mayaguez.

      Soumya Sudhakar SM ’20 is a PhD student in aeronautics and astronautics. Her work is focused on theco-design of new algorithms and integrated circuits for autonomous low-energy robotics that could have novel applications in aerospace and consumer electronics. Her contributions bring together the emerging robotics industry, integrated circuits industry, aerospace industry, and consumer electronics industry. Sudhakar earned her BSE in mechanical and aerospace engineering from Princeton University and her MS in aeronautics and astronautics from MIT.

      So-Yoon Yang is a PhD student in electrical engineering and computer science. Her work on the development of low-power, wireless, ingestible biomedical devices for health care is at the intersection of the medical device, integrated circuit, artificial intelligence, and pharmaceutical fields. Currently, the majority of wireless biomedical devices can only provide a limited range of medical data measured from outside the body. Ingestible devices hold promise for the next generation of personal health care because they do not require surgical implantation, can be useful for detecting physiological and pathophysiological signals, and can also function as therapeutic alternatives when treatment cannot be done externally. Yang earned her BS in electrical and computer engineering from Seoul National University in South Korea and her MS in electrical engineering from Caltech. More

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      in Energy

      Design’s new frontier

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      In the 1960s, the advent of computer-aided design (CAD) sparked a revolution in design. For his PhD thesis in 1963, MIT Professor Ivan Sutherland developed Sketchpad, a game-changing software program that enabled users to draw, move, and resize shapes on a computer. Over the course of the next few decades, CAD software reshaped how everything from consumer products to buildings and airplanes were designed.

      “CAD was part of the first wave in computing in design. The ability of researchers and practitioners to represent and model designs using computers was a major breakthrough and still is one of the biggest outcomes of design research, in my opinion,” says Maria Yang, Gail E. Kendall Professor and director of MIT’s Ideation Lab.

      Innovations in 3D printing during the 1980s and 1990s expanded CAD’s capabilities beyond traditional injection molding and casting methods, providing designers even more flexibility. Designers could sketch, ideate, and develop prototypes or models faster and more efficiently. Meanwhile, with the push of a button, software like that developed by Professor Emeritus David Gossard of MIT’s CAD Lab could solve equations simultaneously to produce a new geometry on the fly.

      In recent years, mechanical engineers have expanded the computing tools they use to ideate, design, and prototype. More sophisticated algorithms and the explosion of machine learning and artificial intelligence technologies have sparked a second revolution in design engineering.

      Researchers and faculty at MIT’s Department of Mechanical Engineering are utilizing these technologies to re-imagine how the products, systems, and infrastructures we use are designed. These researchers are at the forefront of the new frontier in design.

      Computational design

      Faez Ahmed wants to reinvent the wheel, or at least the bicycle wheel. He and his team at MIT’s Design Computation & Digital Engineering Lab (DeCoDE) use an artificial intelligence-driven design method that can generate entirely novel and improved designs for a range of products — including the traditional bicycle. They create advanced computational methods to blend human-driven design with simulation-based design.

      “The focus of our DeCoDE lab is computational design. We are looking at how we can create machine learning and AI algorithms to help us discover new designs that are optimized based on specific performance parameters,” says Ahmed, an assistant professor of mechanical engineering at MIT.

      For their work using AI-driven design for bicycles, Ahmed and his collaborator Professor Daniel Frey wanted to make it easier to design customizable bicycles, and by extension, encourage more people to use bicycles over transportation methods that emit greenhouse gases.

      To start, the group gathered a dataset of 4,500 bicycle designs. Using this massive dataset, they tested the limits of what machine learning could do. First, they developed algorithms to group bicycles that looked similar together and explore the design space. They then created machine learning models that could successfully predict what components are key in identifying a bicycle style, such as a road bike versus a mountain bike.

      Once the algorithms were good enough at identifying bicycle designs and parts, the team proposed novel machine learning tools that could use this data to create a unique and creative design for a bicycle based on certain performance parameters and rider dimensions.

      Ahmed used a generative adversarial network — or GAN — as the basis of this model. GAN models utilize neural networks that can create new designs based on vast amounts of data. However, using GAN models alone would result in homogeneous designs that lack novelty and can’t be assessed in terms of performance. To address these issues in design problems, Ahmed has developed a new method which he calls “PaDGAN,” performance augmented diverse GAN.

      “When we apply this type of model, what we see is that we can get large improvements in the diversity, quality, as well as novelty of the designs,” Ahmed explains.

      Using this approach, Ahmed’s team developed an open-source computational design tool for bicycles freely available on their lab website. They hope to further develop a set of generalizable tools that can be used across industries and products.

      Longer term, Ahmed has his sights set on loftier goals. He hopes the computational design tools he develops could lead to “design democratization,” putting more power in the hands of the end user.

      “With these algorithms, you can have more individualization where the algorithm assists a customer in understanding their needs and helps them create a product that satisfies their exact requirements,” he adds.

      Using algorithms to democratize the design process is a goal shared by Stefanie Mueller, an associate professor in electrical engineering and computer science and mechanical engineering.

      Personal fabrication

      Platforms like Instagram give users the freedom to instantly edit their photographs or videos using filters. In one click, users can alter the palette, tone, and brightness of their content by applying filters that range from bold colors to sepia-toned or black-and-white. Mueller, X-Window Consortium Career Development Professor, wants to bring this concept of the Instagram filter to the physical world.

      “We want to explore how digital capabilities can be applied to tangible objects. Our goal is to bring reprogrammable appearance to the physical world,” explains Mueller, director of the HCI Engineering Group based out of MIT’s Computer Science and Artificial Intelligence Laboratory.

      Mueller’s team utilizes a combination of smart materials, optics, and computation to advance personal fabrication technologies that would allow end users to alter the design and appearance of the products they own. They tested this concept in a project they dubbed “Photo-Chromeleon.”

      First, a mix of photochromic cyan, magenta, and yellow dies are airbrushed onto an object — in this instance, a 3D sculpture of a chameleon. Using software they developed, the team sketches the exact color pattern they want to achieve on the object itself. An ultraviolet light shines on the object to activate the dyes.

      To actually create the physical pattern on the object, Mueller has developed an optimization algorithm to use alongside a normal office projector outfitted with red, green, and blue LED lights. These lights shine on specific pixels on the object for a given period of time to physically change the makeup of the photochromic pigments.

      “This fancy algorithm tells us exactly how long we have to shine the red, green, and blue light on every single pixel of an object to get the exact pattern we’ve programmed in our software,” says Mueller.

      Giving this freedom to the end user enables limitless possibilities. Mueller’s team has applied this technology to iPhone cases, shoes, and even cars. In the case of shoes, Mueller envisions a shoebox embedded with UV and LED light projectors. Users could put their shoes in the box overnight and the next day have a pair of shoes in a completely new pattern.

      Mueller wants to expand her personal fabrication methods to the clothes we wear. Rather than utilize the light projection technique developed in the PhotoChromeleon project, her team is exploring the possibility of weaving LEDs directly into clothing fibers, allowing people to change their shirt’s appearance as they wear it. These personal fabrication technologies could completely alter consumer habits.

      “It’s very interesting for me to think about how these computational techniques will change product design on a high level,” adds Mueller. “In the future, a consumer could buy a blank iPhone case and update the design on a weekly or daily basis.”

      Computational fluid dynamics and participatory design

      Another team of mechanical engineers, including Sili Deng, the Brit (1961) & Alex (1949) d’Arbeloff Career Development Professor, are developing a different kind of design tool that could have a large impact on individuals in low- and middle-income countries across the world.

      As Deng walked down the hallway of Building 1 on MIT’s campus, a monitor playing a video caught her eye. The video featured work done by mechanical engineers and MIT D-Lab on developing cleaner burning briquettes for cookstoves in Uganda. Deng immediately knew she wanted to get involved.

      “As a combustion scientist, I’ve always wanted to work on such a tangible real-world problem, but the field of combustion tends to focus more heavily on the academic side of things,” explains Deng.

      After reaching out to colleagues in MIT D-Lab, Deng joined a collaborative effort to develop a new cookstove design tool for the 3 billion people across the world who burn solid fuels to cook and heat their homes. These stoves often emit soot and carbon monoxide, leading not only to millions of deaths each year, but also worsening the world’s greenhouse gas emission problem.

      The team is taking a three-pronged approach to developing this solution, using a combination of participatory design, physical modeling, and experimental validation to create a tool that will lead to the production of high-performing, low-cost energy products.

      Deng and her team in the Deng Energy and Nanotechnology Group use physics-based modeling for the combustion and emission process in cookstoves.

      “My team is focused on computational fluid dynamics. We use computational and numerical studies to understand the flow field where the fuel is burned and releases heat,” says Deng.

      These flow mechanics are crucial to understanding how to minimize heat loss and make cookstoves more efficient, as well as learning how dangerous pollutants are formed and released in the process.

      Using computational methods, Deng’s team performs three-dimensional simulations of the complex chemistry and transport coupling at play in the combustion and emission processes. They then use these simulations to build a combustion model for how fuel is burned and a pollution model that predicts carbon monoxide emissions.

      Deng’s models are used by a group led by Daniel Sweeney in MIT D-Lab to test the experimental validation in prototypes of stoves. Finally, Professor Maria Yang uses participatory design methods to integrate user feedback, ensuring the design tool can actually be used by people across the world.

      The end goal for this collaborative team is to not only provide local manufacturers with a prototype they could produce themselves, but to also provide them with a tool that can tweak the design based on local needs and available materials.

      Deng sees wide-ranging applications for the computational fluid dynamics her team is developing.

      “We see an opportunity to use physics-based modeling, augmented with a machine learning approach, to come up with chemical models for practical fuels that help us better understand combustion. Therefore, we can design new methods to minimize carbon emissions,” she adds.

      While Deng is utilizing simulations and machine learning at the molecular level to improve designs, others are taking a more macro approach.

      Designing intelligent systems

      When it comes to intelligent design, Navid Azizan thinks big. He hopes to help create future intelligent systems that are capable of making decisions autonomously by using the enormous amounts of data emerging from the physical world. From smart robots and autonomous vehicles to smart power grids and smart cities, Azizan focuses on the analysis, design, and control of intelligent systems.

      Achieving such massive feats takes a truly interdisciplinary approach that draws upon various fields such as machine learning, dynamical systems, control, optimization, statistics, and network science, among others.

      “Developing intelligent systems is a multifaceted problem, and it really requires a confluence of disciplines,” says Azizan, assistant professor of mechanical engineering with a dual appointment in MIT’s Institute for Data, Systems, and Society (IDSS). “To create such systems, we need to go beyond standard approaches to machine learning, such as those commonly used in computer vision, and devise algorithms that can enable safe, efficient, real-time decision-making for physical systems.”

      For robot control to work in the complex dynamic environments that arise in the real world, real-time adaptation is key. If, for example, an autonomous vehicle is going to drive in icy conditions or a drone is operating in windy conditions, they need to be able to adapt to their new environment quickly.

      To address this challenge, Azizan and his collaborators at MIT and Stanford University have developed a new algorithm that combines adaptive control, a powerful methodology from control theory, with meta learning, a new machine learning paradigm.

      “This ‘control-oriented’ learning approach outperforms the existing ‘regression-oriented’ methods, which are mostly focused on just fitting the data, by a wide margin,” says Azizan.

      Another critical aspect of deploying machine learning algorithms in physical systems that Azizan and his team hope to address is safety. Deep neural networks are a crucial part of autonomous systems. They are used for interpreting complex visual inputs and making data-driven predictions of future behavior in real time. However, Azizan urges caution.

      “These deep neural networks are only as good as their training data, and their predictions can often be untrustworthy in scenarios not covered by their training data,” he says. Making decisions based on such untrustworthy predictions could lead to fatal accidents in autonomous vehicles or other safety-critical systems.

      To avoid these potentially catastrophic events, Azizan proposes that it is imperative to equip neural networks with a measure of their uncertainty. When the uncertainty is high, they can then be switched to a “safe policy.”

      In pursuit of this goal, Azizan and his collaborators have developed a new algorithm known as SCOD — Sketching Curvature of Out-of-Distribution Detection. This framework could be embedded within any deep neural network to equip them with a measure of their uncertainty.

      “This algorithm is model-agnostic and can be applied to neural networks used in various kinds of autonomous systems, whether it’s drones, vehicles, or robots,” says Azizan.

      Azizan hopes to continue working on algorithms for even larger-scale systems. He and his team are designing efficient algorithms to better control supply and demand in smart energy grids. According to Azizan, even if we create the most efficient solar panels and batteries, we can never achieve a sustainable grid powered by renewable resources without the right control mechanisms.

      Mechanical engineers like Ahmed, Mueller, Deng, and Azizan serve as the key to realizing the next revolution of computing in design.

      “MechE is in a unique position at the intersection of the computational and physical worlds,” Azizan says. “Mechanical engineers build a bridge between theoretical, algorithmic tools and real, physical world applications.”

      Sophisticated computational tools, coupled with the ground truth mechanical engineers have in the physical world, could unlock limitless possibilities for design engineering, well beyond what could have been imagined in those early days of CAD. More

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      in Environment

      Elsa Olivetti wins 2021 MIT Bose Award for Excellence in Teaching

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      This year’s Bose Award for Excellence in Teaching has been presented to MIT Associate Professor Elsa Olivetti. Olivetti’s zest for enhancing the student experience is evident in the innovative and creative flare she brings to all aspects of her work.

      “Professor Olivetti’s dedication to teaching is truly inspiring,” says Anantha P. Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “She has an extraordinary ability to engage her students, and has developed transformational approaches to curriculum and mentoring.”

      Olivetti is the Esther and Harold E. Edgerton Associate Professor in Materials Science and Engineering, and co-director of the MIT Climate and Sustainability Consortium. Her passion for addressing issues related to climate change frames the focus of her research, which centers on improving the environmental and economic sustainability of materials in the context of growing global demand. Her work focuses on reducing the significant burden of materials production and consumption through increased use of recycled and waste materials; informing the early-stage design of new materials for effective scale-up; and understanding the implications of policy, new technology development, and manufacturing processes on materials supply chains. 

      Olivetti has made significant contributions on education within the Department of Materials Science and Engineering since she came on board in 2014, including designing and implementing a subject on industrial ecology and materials, co-design of the Advanced Materials Machines NEET program, and developing a new undergraduate curriculum. Underscoring the care she has for her students’ success and well-being, Olivetti also cultivated the Course 3 Industry Seminars, pairing undergraduates with individuals working in careers related to 3D printing, environmental consulting, and manufacturing, with the aim of assisting her students with employment opportunities.

      “Professor Olivetti is a brilliant teacher and a creative educator, who engages the classroom with an uncanny ability to keep students on the edge of their seats combined with a remarkable and signature style that creates learning moments they remember years later,” says Jeff Grossman, head of the Department of Materials Science and Engineering. “I am proud to have Elsa as a colleague, and I am delighted that her excellence has been recognized with the Bose Award.”

      Olivetti received her PhD in materials science and engineering from MIT in 2007; shortly after, she joined the department as a postdoc. She subsequently worked as a research scientist in the Materials Systems Lab from 2009 to 2013 and joined the DMSE faculty in 2014. She was recently named a 2021 MacVicar Faculty Fellow in recognition of her exceptional commitment to curricular innovation, scientific research, and improving the student experience through teaching, mentoring, and advising. Previously, she has received the Earll M. Murman Award for Excellence in Undergraduate Advising in 2017, the award for “best DMSE advisor” in 2019, and the Paul Gray Award for Public Service in 2020.

      The Bose Award for Excellence in Teaching is given annually to a faculty member whose contributions to education have been characterized by dedication, care, and creativity. Established in 1990 by the School of Engineering, the award stands as a tribute to the late Amar Bose, a professor of electrical engineering and computer science and the founder of the Bose Corporation, to recognize outstanding contributions to undergraduate education by members of its faculty. More