Aurelia Butler

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    J-PAL North America announces five new partnerships with state and local governments

    J-PAL North America, a research center in MIT’s Department of Economics, has announced five new partnerships with state and local governments across the United States after a call for proposals in early February. Over the next year, these partners will work with J-PAL North America’s State and Local Innovation Initiative to evaluate policy-relevant questions critical to alleviating poverty in the United States.

    J-PAL North America will work with the Colorado Department of Higher Education, Ohio’s Franklin County Department of Job and Family Services, the New Mexico Public Education Department, Puerto Rico’s Department of Economic Development and Commerce, and Oregon’s Jackson County Fire District 3. Each partner will leverage support from J-PAL North America to develop randomized evaluations, which have the potential to reveal widely applicable lessons about which programs and policies are most effective. 

    State and local leaders are vital stakeholders in developing rigorous evidence in order to understand which policies and programs work to reduce poverty, and why. By supporting each government partner in developing these five evaluation projects, the voice of policymakers and practitioners will remain a central part of the research process. Each of this year’s selected projects seeks to address policy concerns that have been identified by state and local governments in J-PAL North America’s State and Local Learning Agenda as key areas for addressing barriers to mobility from poverty, including environment, education, economic security, and housing stability. 

    One project looks to mitigate the emission of carbon co-pollutants, which cause disproportionately high rates of health problems among communities experiencing poverty. 

    Oregon’s Jackson County Fire District 3 will investigate the impact of subsidies on the uptake of wildfire risk reduction activities in a county severely affected by wildfires. “Wildfires have become more prevalent, longer lasting, and more destructive in Oregon and across the western United States. We also know that wildfire is disproportionately impacting our most vulnerable populations,” says Bob Horton, fire chief of Jackson County Fire District 3. “With technical support from JPAL North America’s staff and this grant funding, we will devise the most current and effective strategy, deeply rooted in the evidence, to drive the take-up of home-hardening behaviors — methods to increase a home’s resistance to fire — and lower the risk to homes when faced with wildfire.” 

    This project is in alignment with the priorities of J-PAL’s Environment, Energy, and Climate Change sector and its agenda for catalyzing more policy-relevant research on adaptation strategies. 

    Policymakers and researchers have also identified programs aimed at increasing opportunity within education as a key priority for evaluation. In partnering with J-PAL North America, the Colorado Department of Higher Education will assess the impact of My Colorado Journey, an online platform available to all Coloradans that provides information on education, training, and career pathways. 

    “As Colorado builds back stronger from the pandemic, we know that education and workforce development are at the center of Colorado’s recovery agenda,” shares Executive Director Angie Paccione of the Colorado Department of Education. “Platforms like My Colorado Journey are key to supporting the education, training, and workforce exploration of Coloradans of any age. With support from J-PAL North America, we can better understand how to effectively serve Coloradans, further enhance this vital platform, and continue to build a Colorado for all.”

    Similarly, the New Mexico Public Education Department proposes their intervention within the context of New Mexico’s community school state initiative. They will look at the impact of case management and cash transfers on students at risk of multiple school transfers throughout their education, which include children who are experiencing homelessness, migrant children, children in the foster care system, and military-connected children, among others. “New Mexico is delighted to partner with J-PAL North America to explore visionary pathways to success for highly mobile students,” says New Mexico Public Education Secretary (Designate) Kurt Steinhaus. “We look forward to implementing and testing innovative solutions, such as cash transfers, that can expand our current nationally recognized community schools strategy. Together, we aim to find solutions that meet the needs of highly mobile students and families who lack stable housing.”

    Another key priority for the intersection of policy and research is economic security — fostering upward mobility by providing individuals with resources to promote stable incomes and increase standards of living. By adjusting caseworker employment services to better align with local needs, Puerto Rico’s Department of Economic Development and Commerce (DEDC) looks to understand how individualized services can impact employment and earnings. 

    “The commitment of the government of Puerto Rico is to develop human resources to the highest quality standards,” says DEDC Secretary Cidre Miranda, whose statement was provided in Spanish and translated. “For the DEDC, it is fundamental to contribute to the development of initiatives like this one, because they have the objective of forging the future professionals that Puerto Rico requires and needs.” J-PAL North America’s partnership with DEDC has the potential to provide valuable lessons for other state and local programs also seeking to promote economic security. 

    Finally, Ohio’s Franklin County Department of Job and Family Services seeks to understand the impact of an eviction prevention workshop in a county with eviction rates that are higher than both the state and national average. “Stable housing should not be a luxury, but for far too many Franklin County families it has become one,” Deputy Franklin County Administrator Joy Bivens says. “We need to view our community’s affordable housing crisis through both a social determinants of health and racial equity lens. We are grateful for the opportunity to partner with J-PAL North America to ensure we are pursuing research-based interventions that, yes, address immediate housing needs, but also provide long-term stability so they can climb the economic ladder.”

    Franklin County Department of Job and Family Services’ evaluation aligns with policymaker and researcher interests to ensure safe and affordable housing. This partnership will have great potential to not only improve resources local to Franklin County, but, along with each of the other four agencies, can also provide a useful model for other government agencies facing similar challenges.For more information on state and local policy priorities, see J-PAL North America’s State and Local Learning Agenda. To learn more about the State and Local Innovation Initiative, please visit the Initiative webpage or contact Initiative Manager Louise Geraghty. More

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    Selective separation could help alleviate critical metals shortage

    New processing methods developed by MIT researchers could help ease looming shortages of the essential metals that power everything from phones to automotive batteries, by making it easier to separate these rare metals from mining ores and recycled materials.

    Selective adjustments within a chemical process called sulfidation allowed professor of metallurgy Antoine Allanore and his graduate student Caspar Stinn to successfully target and separate rare metals, such as the cobalt in a lithium-ion battery, from mixed-metal materials.

    As they report in the journal Nature, their processing techniques allow the metals to remain in solid form and be separated without dissolving the material. This avoids traditional but costly liquid separation methods that require significant energy. The researchers developed processing conditions for 56 elements and tested these conditions on 15 elements.

    Their sulfidation approach, they write in the paper, could reduce the capital costs of metal separation between 65 and 95 percent from mixed-metal oxides. Their selective processing could also reduce greenhouse gas emissions by 60 to 90 percent compared to traditional liquid-based separation.

    “We were excited to find replacements for processes that had really high levels of water usage and greenhouse gas emissions, such as lithium-ion battery recycling, rare-earth magnet recycling, and rare-earth separation,” says Stinn. “Those are processes that make materials for sustainability applications, but the processes themselves are very unsustainable.”

    The findings offer one way to alleviate a growing demand for minor metals like cobalt, lithium, and rare earth elements that are used in “clean” energy products like electric cars, solar cells, and electricity-generating windmills. According to a 2021 report by the International Energy Agency, the average amount of minerals needed for a new unit of power generation capacity has risen by 50 percent since 2010, as renewable energy technologies using these metals expand their reach.

    Opportunity for selectivity

    For more than a decade, the Allanore group has been studying the use of sulfide materials in developing new electrochemical routes for metal production. Sulfides are common materials, but the MIT scientists are experimenting with them under extreme conditions like very high temperatures — from 800 to 3,000 degrees Fahrenheit — that are used in manufacturing plants but not in a typical university lab.

    “We are looking at very well-established materials in conditions that are uncommon compared to what has been done before,” Allanore explains, “and that is why we are finding new applications or new realities.”

    In the process of synthetizing high-temperature sulfide materials to support electrochemical production, Stinn says, “we learned we could be very selective and very controlled about what products we made. And it was with that understanding that we realized, ‘OK, maybe there’s an opportunity for selectivity in separation here.’”

    The chemical reaction exploited by the researchers reacts a material containing a mix of metal oxides to form new metal-sulfur compounds or sulfides. By altering factors like temperature, gas pressure, and the addition of carbon in the reaction process, Stinn and Allanore found that they could selectively create a variety of sulfide solids that can be physically separated by a variety of methods, including crushing the material and sorting different-sized sulfides or using magnets to separate different sulfides from one another.

    Current methods of rare metal separation rely on large quantities of energy, water, acids, and organic solvents which have costly environmental impacts, says Stinn. “We are trying to use materials that are abundant, economical, and readily available for sustainable materials separation, and we have expanded that domain to now include sulfur and sulfides.”

    Stinn and Allanore used selective sulfidation to separate out economically important metals like cobalt in recycled lithium-ion batteries. They also used their techniques to separate dysprosium — a rare-earth element used in applications ranging from data storage devices to optoelectronics — from rare-earth-boron magnets, or from the typical mixture of oxides available from mining minerals such as bastnaesite.

    Leveraging existing technology

    Metals like cobalt and rare earths are only found in small amounts in mined materials, so industries must process large volumes of material to retrieve or recycle enough of these metals to be economically viable, Allanore explains. “It’s quite clear that these processes are not efficient. Most of the emissions come from the lack of selectivity and the low concentration at which they operate.”

    By eliminating the need for liquid separation and the extra steps and materials it requires to dissolve and then reprecipitate individual elements, the MIT researchers’ process significantly reduces the costs incurred and emissions produced during separation.

    “One of the nice things about separating materials using sulfidation is that a lot of existing technology and process infrastructure can be leveraged,” Stinn says. “It’s new conditions and new chemistries in established reactor styles and equipment.”

    The next step is to show that the process can work for large amounts of raw material — separating out 16 elements from rare-earth mining streams, for example. “Now we have shown that we can handle three or four or five of them together, but we have not yet processed an actual stream from an existing mine at a scale to match what’s required for deployment,” Allanore says.

    Stinn and colleagues in the lab have built a reactor that can process about 10 kilograms of raw material per day, and the researchers are starting conversations with several corporations about the possibilities.

    “We are discussing what it would take to demonstrate the performance of this approach with existing mineral and recycling streams,” Allanore says.

    This research was supported by the U.S. Department of Energy and the U.S. National Science Foundation. More

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    Expanding the conversation about sustainability

    Stacy Godfreey-Igwe sat in her dorm room at MIT, staring frantically at her phone. An unprecedented snowstorm had hit her hometown of Richardson, Texas, and she was having difficulty contacting her family. She felt worried and frustrated, aware that nearby neighborhoods hadn’t lost power during the storm but that her family home had suffered significant damage. She finally got a hold of her parents, who had taken refuge in a nearby office building, but the experience left her shaken and more determined than ever to devote herself to addressing climate injustice.

    Godfreey-Igwe, the daughter of Nigerian immigrants, has long been concerned about how marginalized communities can shoulder a disproportionately heavy environmental burden. At MIT, she chose a double major in mechanical engineering with a concentration in global and sustainable development, and in African and African diaspora studies, a major she helped establish and became the first student to declare. Initially seeing the two fields as separate, she now embraces their intersectionality in her work in and out of the classroom.

    Through an Undergraduate Research Opportunity Program (UROP) project with Amah Edoh, the Homer A. Burnell Assistant Professor of Anthropology and African Studies at MIT, Godfreey-Igwe has learned more about her Igbo cultural heritage and hopes to understand what the future of climate change poses for the culture’s sustainability. Godfreey-Igwe herself is the “Ada” – or eldest child – in her family, a role that carries a responsibility for keeping her family’s culture alive. That sense of responsibility, to her community and to future generations, has stayed with her at MIT.

    For Independent Activities Period during her first year at the Institute, Godfreey-Igwe traveled to Kazakhstan through MIT’s Global Teaching Labs. As a student teacher, she taught Kazakh high school chemistry students about polymers and the impact plastic materials can have on the Earth’s climate. She was also an MIT International Science and Technology Initiatives (MISTI) Identity X Ambassador during her time there, blogging about her experiences as a Black woman in the country. She saw the role as an opportunity to shed light on the challenges of navigating her identity abroad, with hopes of fostering community through her posts.

    The following summer, Godfreey-Igwe interned for the Saathi Biodegradable Sanitary Napkins Startup in Ahmedabad, India. During her time there, she researched and wrote articles focused on educating the public about the benefits eco-friendly sanitary pads posed to public health and the environment. She also interviewed a director for the city’s Center for Environmental Education, about the importance of uplifting and supporting marginalized communities hit hardest by climate change. The conversation was eye-opening for Godfreey-Igwe; she saw not only how complex the process of mitigating climate change was, but also how diverse the solutions needed to be.

    She has also pursued her interest in plastics and sustainability through summer research projects. In of the summer of 2020, Godfreey-Igwe worked under a lab in Stanford University’s civil and environmental engineering department to create and design models maximizing the efficiency of bacterial processes leading to the creation of bioplastics. The project’s goal was to find a sustainable form of plastic breakdown for future applications in the environment.  She presented her research at the Harvard National Collegiate Research Conference and received a presentation award during the MIT Mechanical Engineering Research Exhibition. This past summer, she was awarded a grant through the NSF Center for Sustainable Polymers at the University of Minnesota to work on a research project seeking to understand microplastic generation.

    Ultimately, Godfreey-Igwe recognizes that to propose thoughtful solutions to climate issues, the people hit hardest must be a part of the conversation. For her, a key way to bring more people into conversations about sustainability and inclusion is through mentorship. This role is especially meaningful to Godfreey-Igwe because she knows firsthand how important for members of underrepresented groups to feel supported at a place like MIT. “The experience of coming to an institution like MIT, as someone who is low-income or of color, can be isolating. Especially if you feel like there are people who can’t relate to your background,” she says.

    Godfreey-Igwe is a member of Active Community Engagement FPOP (ACE), a social action group on campus that engages with local communities through public service work. Initially joining as a participant, Godfreey-Igwe became a counselor and then coordinator; she facilitates social action workshops and introduces students to service opportunities both at MIT and around Boston. She says her time in ACE has helped build her confidence in her abilities as a leader, mentor, and cultivator of inclusionary spaces. She is also a member of iHouse (International Development House), where she served for three years as the housing and service co-chair.

    Godfreey-Igwe also tutors one-on-one for Tutoring Plus in Cambridge, where since her first year she has provided mentorship and STEM tutoring to a low-income, high school student of color. Last spring, she was awarded the Tutoring Plus of Cambridge Unwavering Service Award for her service and commitment to the program.

    Looking ahead, Godfreey-Igwe hopes to use the skills learned from her mentorship and leadership roles to establish greater structures for collaboration on climate mitigation technologies, ideas, and practices. Focusing on mentoring young scientists of color, she wants to build up underprivileged groups and institutions for sustainable climate change research, ensuring everyone has a voice in the ongoing conversation.

    “In all this work, I’m hoping to make sure that globally marginalized communities are more visible in climate-related spaces, both in terms of who is doing the engineering and who the engineering works for,” she says. More

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    The power of economics to explain and shape the world

    Nobel Prize-winning economist Esther Duflo sympathizes with students who have no interest in her field. She was such a student herself — until an undergraduate research post gave her the chance to learn first-hand that economists address many of the major issues facing human and planetary well-being.“Most people have a wrong view of what economics is. They just see economists on television discussing what’s going to happen to the stock market,” says Duflo, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics. “But what people do in the field is very broad. Economists grapple with the real world and with the complexity that goes with it.”

    That’s why this year Duflo has teamed up with Professor Abhijit Banerjee to offer 14.009 (Economics and Society’s Greatest Problems), a first-year discovery subject — a class type designed to give undergraduates a low-pressure, high-impact way to explore a field. In this case, they are exploring the range of issues that economists engage with every day: the economic dimensions of climate change, international trade, racism, justice, education, poverty, health care, social preferences, and economic growth are just a few of the topics the class covers.“We think it’s pretty important that the first exposure to economics is via issues,” Duflo says. “If you first get exposed to economics via models, these models necessarily have to be very simplified, and then students get the idea that economics is a simplistic view of the world that can’t explain much.”Arguably, Duflo and Banerjee have been disproving that view throughout their careers. In 2003, the pair founded MIT’s Abdul Latif Jameel Poverty Action Lab, a leading antipoverty research network that provides scientific evidence on what methods actually work to alleviate poverty — which enables governments and nongovernmental organizations to implement truly effective programs and social policies. And, in 2019 they won the Nobel Prize in economics (together with Michael Kremer of the University of Chicago) for their innovative work applying laboratory-style randomized, controlled trials to research a wide range of topics implicated in global poverty.“Super cool”

    First-year Jean Billa, one of the students in 14.009, says, “Economics isn’t just about how money flows, but about how people react to certain events. That was an interesting discovery for me.”

    It’s also precisely the lesson Banerjee and Duflo hoped students would take away from 14.009, a class that centers on weekly in-person discussions of the professors’ recorded lectures — many of which align with chapters in Banerjee and Duflo’s book “Good Economics for Hard Times” (Public Affairs, 2019).Classes typically start with a poll in which the roughly 100 enrolled students can register their views on that week’s topic. Then, students get to discuss the issue, says senior Dina Atia, teaching assistant for the class. Noting that she finds it “super cool” that Nobelists are teaching MIT’s first-year students, Atia points out that both Duflo and Banerjee have also made themselves available to chat with students after class. “They’re definitely extending themselves,” she says.“We want the students to get excited about economics so they want to know more,” says Banerjee, the Ford Foundation International Professor of Economics, “because this is a field that can help us address some of the biggest problems society faces.” Using natural experiments to test theories

    Early in the term, for example, the topic was migration. In the lecture, Duflo points out that migration policies are often impacted by the fear that unskilled migrants will overwhelm a region, taking jobs from residents and demanding social services. Yet, migrant flows in normal years represent just 3 percent of the world population. “There is no flood. There is no vast movement of migrants,” she says.Duflo then explains that economists were able to learn a lot about migration thanks to a “natural experiment,” the Mariel boat lift. This 1980 event brought roughly 125,000 unskilled Cubans to Florida over a matter a months, enabling economists to study the impacts of a sudden wave of migration. Duflo says a look at real wages before and after the migration showed no significant impacts.“It was interesting to see that most theories about immigrants were not justified,” Billa says. “That was a real-life situation, and the results showed that even a massive wave of immigration didn’t change work in the city [Miami].”

    Question assumptions, find the facts in dataSince this is a broad survey course, there is always more to unpack. The goal, faculty say, is simply to help students understand the power of economics to explain and shape the world. “We are going so fast from topic to topic, I don’t expect them to retain all the information,” Duflo says. Instead, students are expected to gain an appreciation for a way of thinking. “Economics is about questioning everything — questioning assumptions you don’t even know are assumptions and being sophisticated about looking at data to uncover the facts.”To add impact, Duflo says she and Banerjee tie lessons to current events and dive more deeply into a few economic studies. One class, for example, focused on the unequal burden the Covid-19 pandemic has placed on different demographic groups and referenced research by Harvard University professor Marcella Alsan, who won a MacArthur Fellowship this fall for her work studying the impact of racism on health disparities.

    Duflo also revealed that at the beginning of the pandemic, she suspected that mistrust of the health-care system could prevent Black Americans from taking certain measures to protect themselves from the virus. What she discovered when she researched the topic, however, was that political considerations outweighed racial influences as a predictor of behavior. “The lesson for you is, it’s good to question your assumptions,” she told the class.“Students should ideally understand, by the end of class, why it’s important to ask questions and what they can teach us about the effectiveness of policy and economic theory,” Banerjee says. “We want people to discover the range of economics and to understand how economists look at problems.”

    Story by MIT SHASS CommunicationsEditorial and design director: Emily HiestandSenior writer: Kathryn O’Neill More

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    New visions for better transportation

    We typically experience transportation problems from the ground up. Waiting for a delayed bus, packing ourselves into a subway car, or crawling along in traffic, it is common to see such systems struggling at close range.

    Yet sometimes transportation solutions come from a high-level, top-down approach. That was the theme of the final talk in MIT’s Mobility Forum series, delivered on Friday by MIT Professor Thomas Magnanti, which centered on applying to transportation the same overarching analytical framework used in other domains, such as bioengineering.

    Magnanti’s remarks focused on a structured approach to problem-solving known as the 4M method — which stands for measuring, mining, modeling, and manipulating. In urban transportation planning, for instance, measuring and mining might involve understanding traffic flows. Modeling might simulate those traffic flows, and manipulating would mean engineering interventions: tolls, one-way streets, or other changes.

    “These are four things that interact quite a bit with each other,” said Magnanti, who is an Institute Professor — MIT’s highest faculty distinction — and a professor of operations research at the MIT Sloan School of Management. “And they provide us with a sense of how you can gather data and understand a system, but also how you can improve it.”

    Magnanti, a leading expert in operations research, pointed out that the 4M method can be applied to systems from physics to biomedical research. He outlined how it might be used to analyze transportations-related systems such as supply chains and warehouse movements.

    In all cases, he noted, applying the 4M concept to a system is an iterative process: Making changes to a system will likely produce new flows — of traffic and goods — and thus be subject to a new set of measurements.

    “One thing to notice here, once you manipulate the system, it changes the data,” Magnanti observed. “You’re doing this so you can hopefully improve operations, but it creates new data. So, you want to measure that new data again, you want to mine it, you want to model it again, and then manipulate it. … This is a continuing loop that we use in these systems.”

    Magnanti’s talk, “Understanding and Improving Transportation Systems,” was delivered online to a public audience of about 175 people. It was the 12th and final event of the MIT Mobility Forum in the fall 2021 semester. The event series is organized by the MIT Mobility Initiative, an Institute-wide effort to research and accelerate the evolution of transportation, at a time when decarbonization in the sector is critical.

    Other MIT Mobility Forum talks have focused on topics such as zero-environmental-impact aviation, measuring pedestrian flows in cities, autonomous vehicles, the impact of high-speed rail and subways on cities, values and equity in mobility design, and more.

    Overall, the forum “offers an opportunity to showcase the groundbreaking transportation research occurring across the Institute,” says Jinhua Zhao, an associate professor of transportation and city planning in MIT’s Department of Urban Studies and Planning, and director of the MIT Mobility Initiative.

    The initiative has held 39 such talks since it launched in 2020, and the series will continue again in the spring semester of 2022.

    One of the principal features of the forum, like the MIT Mobility Initiative in general, is that it “facilitates cross-disciplinary exchanges both within MIT and without,” Zhao says. Faculty and students from every school at MIT have participated in the forum, lending intellectual and methodological diversity to a broad field.

    For his part, Magnanti, who is both an engineer and operations researcher by training, embraced that interdisciplinary approach in his remarks, fielding a variety of audience questions after his talk, about research methods and other issues. Magnanti, who served from 2009 to 2017 as the founding president of the Singapore University of Technology and Design (with which MIT has had research collaborations), noted that the setting can heavily influence transportation research and progress.

    In Singapore, he noted, “They measure everything. They measure how people access the subway … and they use their data.” Of course, Singapore’s status as a city-state of modest size, among other factors, makes comprehensive transportation planning more feasible there. Still, Magnanti also noted that the infrastructure bill recently passed by the U.S. federal government is “going to provide lots of opportunities” for transportation improvements.

    And in general, Magnanti added, one of the best things academic leaders and research communities can do is to “continue to create a sense of excitement. Even when things are tough, the problems are going to be interesting.” More

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    A tool to speed development of new solar cells

    In the ongoing race to develop ever-better materials and configurations for solar cells, there are many variables that can be adjusted to try to improve performance, including material type, thickness, and geometric arrangement. Developing new solar cells has generally been a tedious process of making small changes to one of these parameters at a time. While computational simulators have made it possible to evaluate such changes without having to actually build each new variation for testing, the process remains slow.

    Now, researchers at MIT and Google Brain have developed a system that makes it possible not just to evaluate one proposed design at a time, but to provide information about which changes will provide the desired improvements. This could greatly increase the rate for the discovery of new, improved configurations.

    The new system, called a differentiable solar cell simulator, is described in a paper published today in the journal Computer Physics Communications, written by MIT junior Sean Mann, research scientist Giuseppe Romano of MIT’s Institute for Soldier Nanotechnologies, and four others at MIT and at Google Brain.

    Traditional solar cell simulators, Romano explains, take the details of a solar cell configuration and produce as their output a predicted efficiency — that is, what percentage of the energy of incoming sunlight actually gets converted to an electric current. But this new simulator both predicts the efficiency and shows how much that output is affected by any one of the input parameters. “It tells you directly what happens to the efficiency if we make this layer a little bit thicker, or what happens to the efficiency if we for example change the property of the material,” he says.

    In short, he says, “we didn’t discover a new device, but we developed a tool that will enable others to discover more quickly other higher performance devices.” Using this system, “we are decreasing the number of times that we need to run a simulator to give quicker access to a wider space of optimized structures.” In addition, he says, “our tool can identify a unique set of material parameters that has been hidden so far because it’s very complex to run those simulations.”

    While traditional approaches use essentially a random search of possible variations, Mann says, with his tool “we can follow a trajectory of change because the simulator tells you what direction you want to be changing your device. That makes the process much faster because instead of exploring the entire space of opportunities, you can just follow a single path” that leads directly to improved performance.

    Since advanced solar cells often are composed of multiple layers interlaced with conductive materials to carry electric charge from one to the other, this computational tool reveals how changing the relative thicknesses of these different layers will affect the device’s output. “This is very important because the thickness is critical. There is a strong interplay between light propagation and the thickness of each layer and the absorption of each layer,” Mann explains.

    Other variables that can be evaluated include the amount of doping (the introduction of atoms of another element) that each layer receives, or the dielectric constant of insulating layers, or the bandgap, a measure of the energy levels of photons of light that can be captured by different materials used in the layers.

    This simulator is now available as an open-source tool that can be used immediately to help guide research in this field, Romano says. “It is ready, and can be taken up by industry experts.” To make use of it, researchers would couple this device’s computations with an optimization algorithm, or even a machine learning system, to rapidly assess a wide variety of possible changes and home in quickly on the most promising alternatives.

    At this point, the simulator is based on just a one-dimensional version of the solar cell, so the next step will be to expand its capabilities to include two- and three-dimensional configurations. But even this 1D version “can cover the majority of cells that are currently under production,” Romano says. Certain variations, such as so-called tandem cells using different materials, cannot yet be simulated directly by this tool, but “there are ways to approximate a tandem solar cell by simulating each of the individual cells,” Mann says.

    The simulator is “end-to-end,” Romano says, meaning it computes the sensitivity of the efficiency, also taking into account light absorption. He adds: “An appealing future direction is composing our simulator with advanced existing differentiable light-propagation simulators, to achieve enhanced accuracy.”

    Moving forward, Romano says, because this is an open-source code, “that means that once it’s up there, the community can contribute to it. And that’s why we are really excited.” Although this research group is “just a handful of people,” he says, now anyone working in the field can make their own enhancements and improvements to the code and introduce new capabilities.

    “Differentiable physics is going to provide new capabilities for the simulations of engineered systems,” says Venkat Viswanathan, an associate professor of mechanical engineering at Carnegie Mellon University, who was not associated with this work. “The  differentiable solar cell simulator is an incredible example of differentiable physics, that can now provide new capabilities to optimize solar cell device performance,” he says, calling the study “an exciting step forward.”

    In addition to Mann and Romano, the team included Eric Fadel and Steven Johnson at MIT, and Samuel Schoenholz and Ekin Cubuk at Google Brain. The work was supported in part by Eni S.p.A. and the MIT Energy Initiative, and the MIT Quest for Intelligence. More

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    Q&A: More-sustainable concrete with machine learning

    As a building material, concrete withstands the test of time. Its use dates back to early civilizations, and today it is the most popular composite choice in the world. However, it’s not without its faults. Production of its key ingredient, cement, contributes 8-9 percent of the global anthropogenic CO2 emissions and 2-3 percent of energy consumption, which is only projected to increase in the coming years. With aging United States infrastructure, the federal government recently passed a milestone bill to revitalize and upgrade it, along with a push to reduce greenhouse gas emissions where possible, putting concrete in the crosshairs for modernization, too.

    Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in the MIT Department of Materials Science and Engineering, and Jie Chen, MIT-IBM Watson AI Lab research scientist and manager, think artificial intelligence can help meet this need by designing and formulating new, more sustainable concrete mixtures, with lower costs and carbon dioxide emissions, while improving material performance and reusing manufacturing byproducts in the material itself. Olivetti’s research improves environmental and economic sustainability of materials, and Chen develops and optimizes machine learning and computational techniques, which he can apply to materials reformulation. Olivetti and Chen, along with their collaborators, have recently teamed up for an MIT-IBM Watson AI Lab project to make concrete more sustainable for the benefit of society, the climate, and the economy.

    Q: What applications does concrete have, and what properties make it a preferred building material?

    Olivetti: Concrete is the dominant building material globally with an annual consumption of 30 billion metric tons. That is over 20 times the next most produced material, steel, and the scale of its use leads to considerable environmental impact, approximately 5-8 percent of global greenhouse gas (GHG) emissions. It can be made locally, has a broad range of structural applications, and is cost-effective. Concrete is a mixture of fine and coarse aggregate, water, cement binder (the glue), and other additives.

    Q: Why isn’t it sustainable, and what research problems are you trying to tackle with this project?

    Olivetti: The community is working on several ways to reduce the impact of this material, including alternative fuels use for heating the cement mixture, increasing energy and materials efficiency and carbon sequestration at production facilities, but one important opportunity is to develop an alternative to the cement binder.

    While cement is 10 percent of the concrete mass, it accounts for 80 percent of the GHG footprint. This impact is derived from the fuel burned to heat and run the chemical reaction required in manufacturing, but also the chemical reaction itself releases CO2 from the calcination of limestone. Therefore, partially replacing the input ingredients to cement (traditionally ordinary Portland cement or OPC) with alternative materials from waste and byproducts can reduce the GHG footprint. But use of these alternatives is not inherently more sustainable because wastes might have to travel long distances, which adds to fuel emissions and cost, or might require pretreatment processes. The optimal way to make use of these alternate materials will be situation-dependent. But because of the vast scale, we also need solutions that account for the huge volumes of concrete needed. This project is trying to develop novel concrete mixtures that will decrease the GHG impact of the cement and concrete, moving away from the trial-and-error processes towards those that are more predictive.

    Chen: If we want to fight climate change and make our environment better, are there alternative ingredients or a reformulation we could use so that less greenhouse gas is emitted? We hope that through this project using machine learning we’ll be able to find a good answer.

    Q: Why is this problem important to address now, at this point in history?

    Olivetti: There is urgent need to address greenhouse gas emissions as aggressively as possible, and the road to doing so isn’t necessarily straightforward for all areas of industry. For transportation and electricity generation, there are paths that have been identified to decarbonize those sectors. We need to move much more aggressively to achieve those in the time needed; further, the technological approaches to achieve that are more clear. However, for tough-to-decarbonize sectors, such as industrial materials production, the pathways to decarbonization are not as mapped out.

    Q: How are you planning to address this problem to produce better concrete?

    Olivetti: The goal is to predict mixtures that will both meet performance criteria, such as strength and durability, with those that also balance economic and environmental impact. A key to this is to use industrial wastes in blended cements and concretes. To do this, we need to understand the glass and mineral reactivity of constituent materials. This reactivity not only determines the limit of the possible use in cement systems but also controls concrete processing, and the development of strength and pore structure, which ultimately control concrete durability and life-cycle CO2 emissions.

    Chen: We investigate using waste materials to replace part of the cement component. This is something that we’ve hypothesized would be more sustainable and economic — actually waste materials are common, and they cost less. Because of the reduction in the use of cement, the final concrete product would be responsible for much less carbon dioxide production. Figuring out the right concrete mixture proportion that makes endurable concretes while achieving other goals is a very challenging problem. Machine learning is giving us an opportunity to explore the advancement of predictive modeling, uncertainty quantification, and optimization to solve the issue. What we are doing is exploring options using deep learning as well as multi-objective optimization techniques to find an answer. These efforts are now more feasible to carry out, and they will produce results with reliability estimates that we need to understand what makes a good concrete.

    Q: What kinds of AI and computational techniques are you employing for this?

    Olivetti: We use AI techniques to collect data on individual concrete ingredients, mix proportions, and concrete performance from the literature through natural language processing. We also add data obtained from industry and/or high throughput atomistic modeling and experiments to optimize the design of concrete mixtures. Then we use this information to develop insight into the reactivity of possible waste and byproduct materials as alternatives to cement materials for low-CO2 concrete. By incorporating generic information on concrete ingredients, the resulting concrete performance predictors are expected to be more reliable and transformative than existing AI models.

    Chen: The final objective is to figure out what constituents, and how much of each, to put into the recipe for producing the concrete that optimizes the various factors: strength, cost, environmental impact, performance, etc. For each of the objectives, we need certain models: We need a model to predict the performance of the concrete (like, how long does it last and how much weight does it sustain?), a model to estimate the cost, and a model to estimate how much carbon dioxide is generated. We will need to build these models by using data from literature, from industry, and from lab experiments.

    We are exploring Gaussian process models to predict the concrete strength, going forward into days and weeks. This model can give us an uncertainty estimate of the prediction as well. Such a model needs specification of parameters, for which we will use another model to calculate. At the same time, we also explore neural network models because we can inject domain knowledge from human experience into them. Some models are as simple as multi-layer perceptions, while some are more complex, like graph neural networks. The goal here is that we want to have a model that is not only accurate but also robust — the input data is noisy, and the model must embrace the noise, so that its prediction is still accurate and reliable for the multi-objective optimization.

    Once we have built models that we are confident with, we will inject their predictions and uncertainty estimates into the optimization of multiple objectives, under constraints and under uncertainties.

    Q: How do you balance cost-benefit trade-offs?

    Chen: The multiple objectives we consider are not necessarily consistent, and sometimes they are at odds with each other. The goal is to identify scenarios where the values for our objectives cannot be further pushed simultaneously without compromising one or a few. For example, if you want to further reduce the cost, you probably have to suffer the performance or suffer the environmental impact. Eventually, we will give the results to policymakers and they will look into the results and weigh the options. For example, they may be able to tolerate a slightly higher cost under a significant reduction in greenhouse gas. Alternatively, if the cost varies little but the concrete performance changes drastically, say, doubles or triples, then this is definitely a favorable outcome.

    Q: What kinds of challenges do you face in this work?

    Chen: The data we get either from industry or from literature are very noisy; the concrete measurements can vary a lot, depending on where and when they are taken. There are also substantial missing data when we integrate them from different sources, so, we need to spend a lot of effort to organize and make the data usable for building and training machine learning models. We also explore imputation techniques that substitute missing features, as well as models that tolerate missing features, in our predictive modeling and uncertainty estimate.

    Q: What do you hope to achieve through this work?

    Chen: In the end, we are suggesting either one or a few concrete recipes, or a continuum of recipes, to manufacturers and policymakers. We hope that this will provide invaluable information for both the construction industry and for the effort of protecting our beloved Earth.

    Olivetti: We’d like to develop a robust way to design cements that make use of waste materials to lower their CO2 footprint. Nobody is trying to make waste, so we can’t rely on one stream as a feedstock if we want this to be massively scalable. We have to be flexible and robust to shift with feedstocks changes, and for that we need improved understanding. Our approach to develop local, dynamic, and flexible alternatives is to learn what makes these wastes reactive, so we know how to optimize their use and do so as broadly as possible. We do that through predictive model development through software we have developed in my group to automatically extract data from literature on over 5 million texts and patents on various topics. We link this to the creative capabilities of our IBM collaborators to design methods that predict the final impact of new cements. If we are successful, we can lower the emissions of this ubiquitous material and play our part in achieving carbon emissions mitigation goals.

    Other researchers involved with this project include Stefanie Jegelka, the X-Window Consortium Career Development Associate Professor in the MIT Department of Electrical Engineering and Computer Science; Richard Goodwin, IBM principal researcher; Soumya Ghosh, MIT-IBM Watson AI Lab research staff member; and Kristen Severson, former research staff member. Collaborators included Nghia Hoang, former research staff member with MIT-IBM Watson AI Lab and IBM Research; and Jeremy Gregory, research scientist in the MIT Department of Civil and Environmental Engineering and executive director of the MIT Concrete Sustainability Hub.

    This research is supported by the MIT-IBM Watson AI Lab. More

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    in Environment

    3 Questions: Tolga Durak on building a safety culture at MIT

    Environment, Health, and Safety Managing Director Tolga Durak heads a team working to build a strong safety culture at the Institute and to implement systems that lead to successful lab and makerspace operations. EHS is also pursuing new opportunities in the areas of safe and sustainable labs and applied makerspace research. 

    Durak holds a BS in mechanical engineering, a MS in industrial and systems engineering, and a PhD in building construction/environmental design and planning. He has over 20 years of experience in engineering and EHS in higher education, having served in such roles as authority having jurisdiction, responsible official, fire marshal, risk manager, radiation safety officer, laser safety officer, safety engineer, project manager, and emergency manager for government agencies, as well as universities with extensive health-care and research facilities.

    Q: What “words of wisdom” regarding lab/shop health and safety would you like to share with the research community? 

    A: EHS staff always strive to help maintain the safety and well-being of the MIT community. When it comes to lab/shop safety or any areas with hazards, first and foremost, we encourage wearing the appropriate personal protective equipment (PPE) when handling potentially hazardous materials. While PPE needs depend on the hazards and the space, common PPE includes safety glasses, lab coats, gloves, clothes that cover your skin, and closed-toe shoes. Shorts and open-toe shoes have no place in the lab/shop setting when hazardous materials are stored or used. Accidents will and do happen. The severity of injuries due to accidental exposures can be minimized when researchers are wearing PPE. Remember, there is only one you!   

    Overall, be aware of your surroundings, be knowledgeable about the hazards of the materials and equipment you are using, and be prepared for the unexpected. Ask yourself, “What’s the worst thing that can happen during this experiment or procedure?” Prepare by doing a thorough risk assessment, ask others who may be knowledgeable for their ideas and help, and standardize procedures where possible. Be prepared to respond appropriately when an emergency arises. 

    Safety in our classrooms, labs, and makerspaces is paramount and requires a collaborative effort. 

    Q: What are the established programs within EHS that students and researchers should be aware of, and what opportunities and challenges do you face trying to advance a healthy safety culture at MIT? 

    A: The EHS program staff in Biosafety, Industrial Hygiene, Environmental Management, Occupational and Construction Safety, and Radiation Protection are ready to assist with risk assessments, chemical safety, physical hazards, hazard-specific training, materials management, and hazardous waste disposal and reuse/recycling. Locally, each department, laboratory, and center has an EHS coordinator, as well as an assigned EHS team, to assist in the implementation of required EHS programs. Each lab/shop also has a designated EHS representative — someone who has local knowledge of your lab/shop and can help you with safety requirements specific to your work area.  

    One of the biggest challenges we face is that due to the decentralized nature of the Institute, no one size fits all when it comes to implementing successful safety practices. We also view this as an opportunity to enhance our safety culture. A strong safety culture is reflected at MIT when all lab and makerspace members are willing to look out for each other, challenge the status quo when necessary, and do the right thing even when no one is looking. In labs/shops with a strong safety culture, faculty and researchers discuss safety topics at group meetings, group members remind each other to wear the appropriate PPE (lab coats, safety glasses, etc.), more experienced team members mentor the newcomers, and riskier operations are reviewed and assessed to make them as safe as possible.  

    Q: Can you describe the new Safe and Sustainable Laboratories (S2L) efforts and the makerspace operational research programs envisioned for the future? 

    A: The MIT EHS Office has a plan for renewing its dedication to sustainability and climate action. We are dedicated to doing our part to promote a research environment that assures the highest level of health and safety but also strives to reduce energy, water, and waste through educating and supporting faculty, students, and researchers. With the goal of integrating sustainability across the lab sector of campus and bridging that with the Institute’s climate action goals, EHS has partnered with the MIT Office of Sustainability, Department of Facilities, vice president for finance, and vice president for campus services and stewardship to relaunch the “green” labs sustainability efforts under a new Safe and Sustainable Labs program.

    Part of that plan is to implement a Sustainable Labs Certification program. The process is designed to be as easy as possible for the lab groups. We are starting with simple actions like promoting the use of equipment timers in certain locations to conserve energy, fume hood/ventilation management, preventative maintenance for ultra-low-temperature freezers, increasing recycling, and helping labs update their central chemical inventory system, which can help forecast MIT’s potential waste streams. 

    EHS has also partnered with Project Manus to build a test-bed lab to study potential health and environmental exposures present in makerspaces as a result of specialized equipment and processes with our new Applied Makerspace Research Initiative.   More