Energy

The long-term goals of the Paris Agreement — keeping global warming well below 2 degrees Celsius and ideally 1.5 C in order to avert the worst impacts of climate change — may not be achievable by greenhouse gas emissions-reduction measures alone. Most scenarios for meeting these targets also require the deployment of negative emissions technologies (NETs) that remove carbon dioxide (CO2) from the atmosphere.

A leading NET candidate is bioenergy with carbon capture and storage (BECCS), which extracts energy from CO2-absorbing plants, captures CO2 that’s released into the atmosphere when the extracted plant matter is combusted, and stores it underground. The end-to-end process entails securing available land, cultivating and transporting crops, converting biomass into electricity with carbon capture, and transporting and storing the captured CO2.

On first glance, it may seem like a no-brainer to ramp up BECCS technology around the world to ensure that the international effort to stabilize the climate will succeed. But the prospect of cultivating plants for BECCS on a massive scale has raised concerns about adverse, unintended consequences. These include environmental impacts that range from soil erosion to biodiversity loss, and economic impacts, especially higher food prices that could result from redirecting vast tracts of agricultural land to draw down carbon emissions.

A new study in the journal Global Environmental Change focuses squarely on the economic implications of BECCS. Representing all major components of BECCS in the MIT Economic Projection and Policy Analysis (EPPA) model, researchers at the MIT Joint Program on the Science and Policy of Global Change and Imperial College London estimate the likely impacts of the technology on the global economy under climate policy scenarios that keep global warming below 1.5 C and 2 C, respectively.

They find that while it’s economically feasible to implement such policies without relying on BECCS, large-scale deployment of the technology in the second half of the century significantly lowers the overall implementation costs. Moreover, the inclusion of BECCS in these policies prevents widespread economic damages: in the 1.5 C scenario, global consumption decreases by almost 20 percent by 2100 without BECCS, but only by 5 percent with BECCS.

“Our modeling suggests that the benefits of BECCS far outweigh the costs,” says Howard Herzog, senior research engineer at the MIT Energy Initiative and co-author of the study. “In terms of costs, BECCS fares better than direct air capture, the other major negative emissions technology that uses carbon dioxide capture and storage (CCS).”

BECCS also significantly reduces the carbon prices associated with cap-and-trade policies designed to reduce emissions sufficiently to keep global warming below 1.5 C and 2 C. By creating negative emissions, the technology relieves pressure from the emissions cap and therefore lowers the price of emissions permits. At the same time, BECCS is compensated for its negative emissions through the carbon price, which is a substantial source of revenue.

“We conduct a series of experiments which robustly demonstrate that revenue from carbon permits is really driving the deployment of BECCS,” says Jennifer Morris, study co-author and research scientist at the MIT Joint Program and MIT Energy Initiative. “We find that the value of CO2 removal is far greater than the value of the electricity generation. Electricity is essentially a byproduct.”

Finally, the study concludes that while BECCS deployment results in major changes in land use to accommodate bioenergy crop cultivation consistent with meeting the 1.5 C and 2 C climate targets, it drives up the prices of food, livestock, and crops by less than 5 percent on average by 2100 (up to 15 percent in selected regions). Most notably, food prices rise by just 1.5 percent globally.

These results suggest that, in concert with dramatic emissions-reduction measures, BECCS could be an economically effective tool in the global effort to stabilize the climate.

“We have shown that large-scale deployment of BECCS could dramatically lower the costs of implementing policies aimed at meeting the long-term climate goals of the Paris Agreement, and avoid major price increases in agricultural commodities,” says MIT Joint Program deputy director and MITEI Senior Research Scientist Sergey Paltsev, who co-authored the study. “Further research is needed, however, to provide a more granular assessment of food supply chains and BECCS components, and to ensure that such deployment is politically viable.” More

In a September 2020 essay in Nature Energy, three scientists posed several “grand challenges” — one of which was to find suitable materials for thermal energy storage devices that could be used in concert with solar energy systems. Fortuitously, Mingda Li — the Norman C. Rasmussen Assistant Professor of Nuclear Science and Engineering at MIT, who heads the department’s Quantum Matter Group — was already thinking along similar lines. In fact, Li and nine collaborators (from MIT, Lawrence Berkeley National Laboratory, and Argonne National Laboratory) were developing a new methodology, involving a novel machine-learning approach, that would make it faster and easier to identify materials with favorable properties for thermal energy storage and other uses.

The results of their investigation appear this month in a paper for Advanced Science. “This is a revolutionary approach that promises to accelerate the design of new functional materials,” comments physicist Jaime Fernandez-Baca, a distinguished staff member at Oak Ridge National Laboratory.

A central challenge in materials science, Li and his coauthors write, is to “establish structure-property relationships” — to figure out the characteristics a material with a given atomic structure would have. Li’s team focused, in particular, on using structural knowledge to predict the “phonon density of states,” which has a critical bearing on thermal properties.

To understand that term, it’s best to start with the word phonon. “A crystalline material is composed of atoms arranged in a lattice structure,” explains Nina Andrejevic, a PhD student in materials science and engineering. “We can think of these atoms as spheres connected by springs, and thermal energy causes the springs to vibrate. And those vibrations, which only occur at discrete [quantized] frequencies or energies, are what we call phonons.”

The phonon density of states is simply the number of vibrational modes, or phonons, found within a given frequency or energy range. Knowing the phonon density of states, one can determine a material’s heat-carrying capacity as well as its thermal conductivity, which relates to how readily heat passes through a material, and even the superconducting transition temperature in a superconductor. “For thermal energy storage purposes, you want a material with a high specific heat, which means it can take in heat without a sharp rise in temperature,” Li says. “You also want a material with low thermal conductivity so that it retains its heat longer.”

The phonon density of states, however, is a difficult term to measure experimentally or to compute theoretically. “For a measurement like this, one has to go to a national laboratory to use a large instrument, about 10 meters long, in order to get the energy resolution you need,” Li says. “That’s because the signal we’re looking for is very weak.”

“And if you want to calculate the phonon density of states, the most accurate way of doing so relies on density functional perturbation theory (DFPT),” notes Zhantao Chen, a mechanical engineering PhD student. “But those calculations scale with the fourth order of the number of atoms in the crystal’s basic building block, which could require days of computing time on a CPU cluster.” For alloys, which contain two or more elements, the calculations become much harder, possibly taking weeks or even longer.

The new method, says Li, could reduce those computational demands to a few seconds on a PC. Rather than trying to calculate the phonon density of states from first principles, which is clearly a laborious task, his team employed a neural network approach, utilizing artificial intelligence algorithms that enable a computer to learn from example. The idea was to present the neural network with enough data on a material’s atomic structure and its associated phonon density of states that the network could discern the key patterns connecting the two. After “training” in this fashion, the network would hopefully make reliable density of states predictions for a substance with a given atomic structure.

Predictions are difficult, Li explains, because the phonon density of states cannot by described by a single number but rather by a curve (analogous to the spectrum of light given off at different wavelengths by a luminous object). “Another challenge is that we only have trustworthy [density of states] data for about 1,500 materials. When we first tried machine learning, the dataset was too small to support accurate predictions.”

His group then teamed up with Lawrence Berkeley physicist Tess Smidt ’12, a co-inventor of so-called Euclidean neural networks. “Training a conventional neural network normally requires datasets containing hundreds of thousands to millions of examples,” Smidt says. A significant part of that data demand stems from the fact that a conventional neural network does not understand that a 3D pattern and a rotated version of the same pattern are related and actually represent the same thing. Before it can recognize 3D patterns — in this case, the precise geometric arrangement of atoms in a crystal — a conventional neural network first needs to be shown the same pattern in hundreds of different orientations.

“Because Euclidean neural networks understand geometry — and recognize that rotated patterns still ‘mean’ the same thing — they can extract the maximal amount of information from a single sample,” Smidt adds. As a result, a Euclidean neural network trained on 1,500 examples can outperform a conventional neural network trained on 500 times more data.

Using the Euclidean neural network, the team predicted phonon density of states for 4,346 crystalline structures. They then selected the materials with the 20 highest heat capacities, comparing the predicted density of states values with those obtained through time-consuming DFPT calculations. The agreement was remarkably close.

The approach can be used to pick out promising thermal energy storage materials, in keeping with the aforementioned “grand challenge,” Li says. “But it could also greatly facilitate alloy design, because we can now determine the density of states for alloys just as easily as for crystals. That, in turn, offers a huge expansion in possible materials we could consider for thermal storage, as well as many other applications.”

Some applications have, in fact, already begun. Computer code from the MIT group has been installed on machines at Oak Ridge, enabling researchers to predict the phonon density of states of a given material based on its atomic structure.

Andrejevic points out, moreover, that Euclidean neural networks have even broader potential that is as-of-yet untapped. “They can help us figure out important material properties besides the phonon density of states. So this could open up the field in a big way.”

This research was funded by the U.S. Department of Energy Office of Science, National Science Foundation, and Lawrence Berkeley National Laboratory. More

More than 73 million households in remote areas of the world get electricity not from a conventional power grid but rather from sources such as solar lanterns, solar home systems (SHSs) that can power several devices, and local solar-based microgrids. Such off-grid devices and systems provide life-changing services to people who are off centralized electricity grids, and they help spread the use of renewable energy. As a result, international aid organizations and nongovernmental organizations (NGOs) are working hard to encourage their adoption.

To expedite the spread of solar technologies, such organizations need to understand the barriers and incentives for households to adopt them. Scholars have assumed that as household income increases, people will adopt newer, “higher-order” technologies and abandon older, “lower-order ones,” such as those that burn fossil fuels. But there’s clear evidence that in remote places people don’t easily abandon the energy sources they have — including their kerosene lanterns.

What motivates people in remote communities to decide to buy and use a particular energy source? What encourages them to choose a certain solar lantern? And why do they then hang onto some of their older devices after acquiring new sources such as a microgrid or even access to the state-run electric grid?

Three years ago, David Hsu, an associate professor of urban and environmental planning, and then-graduate student Elise Harrington PhD ’20, both of the Department of Urban Studies and Planning, decided to investigate those questions in remote villages in India. From preliminary work in the region, they knew that many households use a range of energy sources. If they were to figure out what had prompted a household to adopt and use particular technologies, they’d need to interview the whole decision-making group — a prospect they knew would be difficult. In the past, when Hsu and his colleagues knocked on doors to ask about interest in microgrid power, a crowd of villagers would quickly gather, the person with the highest status would respond, and everybody else would nod. For this study, he and Harrington needed to go into the home, determine what energy systems and appliances were present, and then get the family members to remember — together — how they had decided to purchase them and perhaps abandon previous systems.

The first challenge would be to get in the door. “There are many different social norms that govern access to private spaces,” says Harrington. “But as a woman, I was allowed into interior living spaces. So I got to see firsthand the appliances and lights and so on that were installed or in use.” In addition, she had learned to speak some basic Hindi so she could introduce herself, refer to appliances, and ask basic questions.

The second challenge was to get the group to remember decisions made in the past and what had motivated them — a process that could be both tedious and confusing. For help, the researchers engaged Ameya Athavankar of twobythree, a company based in Mumbai, India, that specializes in creating techniques using elements of game-playing for applications ranging from building and product design to marketing research. Athavankar quickly became an integral member of the research team, working to explore and test possible game formats and field protocols, helping to communicate in both Hindi and the local dialect, and leading the interviews.

Game-playing reveals choices

The United Nations recognizes six steps, or “tiers,” in the transition from having no electricity to being able to run high-power appliances. In their work, Hsu and Harrington decided to focus on the transition from no access to focused task lighting plus phone charging (tier 1), and then the move to general lighting, phone charging, and appliance use (tier 2). “Going from just kerosene to having electricity that provides you with basic lighting and charging can be a really transformative step for households,” says Harrington.

In consultation with a local microgrid company and an NGO with a local office, the researchers selected three villages in the Gumla District of Jharkhand, India, for their study. Two of the villages — Bartoli and Neech Kobja — had access to the state-run electricity grid. The third village — Ramda Bhinjpur — had access to a private microgrid but not to the state grid. Within those three villages, the team selected a total of 22 households that represented a range of experience with solar technologies and fuels used for basic household lighting and charging.

The photo below shows the result of using the researchers’ game-based protocol in one interview. In the game, colored playing cards represent five energy sources for lighting: a kerosene lantern, a solar lantern, an SHS, a microgrid, and the state grid. The layout of cards here shows the respondents’ choices at a series of decision points, moving in time from left to right. Each column shows the result of one decision, with cards in the top row representing “primary sources,” cards in the second row “backup sources,” and cards in the third row sources that have been eliminated for lighting use.

The layout of cards shown here records what happened when people being interviewed in one household recalled making a series of decisions about their energy sources.

Photo: Ameya Athavankar

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In this interview, respondents started with a kerosene lantern (green card) — the initial lighting source in most households. Next they added a black card representing the state-run grid in the top position and moved the kerosene lantern down a row, indicating that they retained it in their household “stack” of energy sources but used it less. They then added a solar lantern (red), using it in tandem with the state grid such that both were primary sources. The solar lantern then broke — as indicated by the red card with the crossed-out image. Finally, they added a solar home system (orange) that they used along with the state grid, while retaining their kerosene lantern.

Purchase and use patterns

Following the same protocol, the researchers performed interviews at 22 households across the three villages. They then added up the sources cited as primary and as backup at each decision point across two groups: at microgrid households and at households connected to the state grid.

The two groups show some marked differences in behavior, beginning with their move away from their kerosene lanterns. The microgrid households moved kerosene lanterns to backup as soon as they had other options available, whereas the state grid group continued to use their kerosene lanterns, only gradually shifting them to a backup position.

Households in both groups adopted solar lanterns, and many continued to use them as a primary source even after being hooked up to a microgrid or the state grid. One reason cited was that solar lanterns can provide lighting for outdoor activities after dark. Perhaps more important, a government program was providing discounted solar lanterns through schools in all three villages.

SHSs were also adopted by both groups. Indeed, many in the microgrid group went directly to an SHS, essentially leapfrogging over the solar lantern option. Once the two groups got grid access, their treatment of their SHSs differed: The microgrid households soon moved much of their SHS use into a backup position, while the state grid households continued to use their SHS as a primary source.

The researchers stress that these interviews offer insight into household use patterns for solar power: Although the sample may be small, it provides rich qualitative data for understanding household decisions. And they did observe some interesting trends. For example, when households connected to a microgrid, they often shifted their existing sources to a backup position, using them on occasion to help defray the cost of the microgrid.

In contrast, households that got access to the state-run grid frequently added both a solar lantern and an SHS, and continued to use them — even increasing their use over time. Moreover, they kept using their kerosene lanterns, only gradually moving them into a backup position. The state grid is notoriously unreliable, so people need to maintain good alternatives for use during blackouts.

Explaining the choices

To delve deeper into what influences technology choice, the researchers asked at each decision point why changes had been made. Using a second set of cards, they asked respondents about the possible importance of five factors: awareness, availability and access, capacity, unit pricing, and quality.

The adoption of every energy technology — but especially the SHS and microgrid — was intended to increase system capacity to meet more end uses, including additional appliances. People cited pricing and payment options as influencing their decisions to acquire solar lanterns and SHSs. Decisions to connect to the state grid were totally dependent on access, whereas decisions to connect to a solar microgrid were more heavily influenced by awareness of the technology.

Notably, failures in the quality of higher-order sources often influenced the retention of lower-order sources. Fully 90 percent of respondents mentioned capacity as influencing their decision to retain their SHS, citing its ability to provide brighter light and greater coverage than other sources. Solar lanterns were retained for their portability and ability to provide better-quality light for studying and other indoor activities. Most households retained kerosene and solar lanterns as well as SHSs to provide coverage during state grid or microgrid outages.

The researchers cite several responses as unexpected. For example, when purchasing an SHS, respondents were initially interested in financing — until they learned about the interest rate and the monthly payments. In general, respondents said that they preferred to make cash payments all at once because their household income varies with the season. Interestingly, other areas of the world with growing off-grid solar markets often have strong programs of pay-as-you-go financing for solar products.

Even more surprising to Harrington was finding that the people interviewed typically paid little attention to warranties or quality labels when making purchases. “There are important efforts in India, and internationally, that focus on setting technical quality standards and providing labeling and certification to communicate those quality standards to consumers,” she says. “But we found that what matters to people is their personal relationship with a shop owner or with the person or organization that introduces them to a solar product.”

Powering appliances

Finally, the researchers looked at what appliances and activities people supported with an SHS, microgrid, and grid. They grouped households into three categories by income and compared end uses across those three electricity sources.

For the high- and middle-income groups, an SHS permitted the use of high-watt devices such as fans, televisions, and laptop computers along with mobile phones and lights. Connection to either the state grid or a microgrid enabled those income groups to undertake income-generating enterprises such as operating a convenience store or running an electronics repair shop. That finding is notable because many aid organizations and microgrid operators emphasize the importance of enabling productive activities when providing electricity to underserved populations.

For the lowest income group, an SHS made possible the first move in electricity access — getting mobile phones and lights. But once on the state-run grid, even some of the most financially constrained households could run televisions and fans as well. “For all the discussion about the challenges with grid reliability and quality, you also see this amazing opportunity that the grid provides to those in our study with the lowest income,” says Harrington.

Policy implications and plans

The researchers’ findings demonstrate the value of introducing SHSs and solar lanterns to provide basic lighting and charging capability before the grid is available. In some cases, supporting adoption of those technologies is the most cost-effective approach to spreading electrification, at least in the short term.

The study also shows that people tend to buy solar devices and services in response to interactions with those whom they trust. In one case, a village decided to participate in a microgrid after an NGO well-known to the community organized a trip to see a microgrid in another village. More such efforts at consumer education and engagement may be needed to support off-grid solar.

Finally, the research confirms the value of the card-based interview technique for data collection and subsequent analysis. Taking a photograph of the laid-out cards at the end of each interview proved important to remembering and then analyzing the timeline and key factors influencing the decisions made at each step. “If we had just done interviews and transcriptions, I don’t think we ever would have made sense of what people’s decision process was,” says Hsu. “People don’t always remember the sequence or rationale for their energy adoption choices until you give them a way to record their experience.”

The researchers also see another potential application of the technique. Setting up a microgrid to provide different levels of service to households in a village requires a high degree of collective decision-making. Perhaps a version of their card-playing interview technique could support that decision-making, ensuring that every household is heard and gets what it needs from the proposed microgrid.

This research was supported by MIT’s Tata Center for Technology and Design, which is part of the MIT Energy Initiative.

This article appears in the Autumn 2020 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

Materials called perovskites are widely heralded as a likely replacement for silicon as the material of choice for solar cells, but their greatest drawback is their tendency to degrade relatively rapidly. Over recent years, the usable lifetime of perovskite-based cells has gradually improved from minutes to months, but it still lags far behind the decades expected from silicon, the material currently used for virtually all commercial solar panels.

Now, an international interdisciplinary team led by MIT has come up with a new approach to narrowing the search for the best candidates for long-lasting perovskite formulations, out of a vast number of potential combinations. Already, their system has zeroed in on one composition that in the lab has improved on existing versions more than tenfold. Even under real-world conditions at full solar cell level, beyond just a small sample in a lab, this type of perovskite has performed three times better than the state-of-the-art formulations.

The findings appear in the journal Matter, in a paper by MIT research scientist Shijing Sun, MIT professors, Moungi Bawendi,  John Fisher, and Tonio Buonassisi, who is also a principal investigator at the Singapore-MIT Alliance for Research and Technology (SMART), and 16 others from MIT, Germany, Singapore, Colorado, and New York.

Perovskites are a broad class of materials characterized by the way atoms are arranged in their layered crystal lattice. These layers, described by convention as A, B, and X, can each consist of a variety of different atoms or compounds. So, searching through the entire universe of such combinations to find the best candidates to meet specific goals — longevity, efficiency, manufacturability, and availability of source materials — is a slow and painstaking process, and largely one without any map for guidance.

“If you consider even just three elements, the most common ones in perovskites that people sub in and out are on the A site of the perovskite crystal structure,” which can each easily be varied by 1-percent increments in their relative composition, Buonassisi says. “The number of steps becomes just preposterous. It becomes very, very large” and thus impractical to search through systematically. Each step involves the complex synthesis process of creating a new material and then testing its degradation, which even under accelerated aging conditions is a time-consuming process.

The key to the team’s success is what they describe as a data fusion approach. This iterative method uses an automated system to guide the production and testing of a variety of formulations, then uses machine learning to go through the results of those tests, combined again with first-principles physical modeling, to guide the next round of experiments. The system keeps repeating that process, refining the results each time.

Buonassisi likes to compare the vast realm of possible compositions to an ocean, and he says most researchers have stayed very close to the shores of known formulations that have achieved high efficiencies, for example, by tinkering just slightly with those atomic configurations. However, “once in a while, somebody makes a mistake or has a stroke of genius and departs from that and lands somewhere else in composition space, and hey, it works better! A happy bit of serendipity, and then everybody moves over there” in their research. “But it’s not usually a structured thought process.”

This new approach, he says, provides a way to explore far offshore areas in search of better properties, in a more systematic and efficient way. In their work so far, by synthesizing and testing less than 2 percent of the possible combinations among three components, the researchers were able to zero in on what seems to be the most durable formulation of a perovskite solar cell material found to date.

“This story is really about the fusion of all the different sets of tools” used to find the new formulation, says Sun, who coordinated the international team that carried out the work, including the development of a high-throughput automated degradation test system that monitors the breakdown of the material through its changes in color as it darkens. To confirm the results, the team went beyond making a tiny chip in the lab and incorporated the material into a working solar cell.

“Another point of this work is that we actually demonstrate, all the way from the chemical selection until we actually make a solar cell in the end,” she says. “And it tells us that the machine-learning-suggested chemical is not only stable in its own freestanding form. They can also be translated into real-life solar cells, and they lead to improved reliability.” Some of their lab-scale demonstrations achieved longevity as much as 17 times greater than the baseline formula they started with, but even the full-cell demonstration, which includes the necessary interconnections, outlasted the existing materials by more than three times, she says.

Buonassisi says the method the team developed could also be applied to other areas of materials research involving similarly large ranges of choice in composition. “It really opens the door for a mode of research where you can have these short, quick loops of innovation happening, maybe at a subcomponent or a material level. And then once you zero in on the right composition, you bump it up into a longer loop that involves device fabrication, and you test it out” at that next level.

“It’s one of the big promises of the field to be able to do this type of work,” he says. “To see it actually happen was one of those [highly memorable] moments. I remember the exact place I was when I received the call from Shijing about these results — when you start to actually see these ideas come to life. It was really stunning.”

“What is particularly exciting about [this] advance is that the authors use physics to guide the intuition of the [optimization] process, rather than limiting the search space with hard constraints,” says University Professor Edward Sargent of the University of Toronto, a specialist in nanotechnology who was not connected with this research. “This approach will see widespread exploitation as machine learning continues to move toward solving real problems in materials science.”

The team included researchers at MIT, the Helmholz Intitute in Germany, the Colorado School of Mines, Brookhaven National Laboratory in New York, the Singapore-MIT Alliance for Research and Technology, and the Institute of Materials for Electronics and Energy Technology in Erlangen, Germany. The work was supported by DARPA, Total SA, the National Science Foundation, and the Skoltech NGP program. More

Arnav Patel is a self-described sustainability enthusiast. Working on solutions related to climate change has been a central thread woven throughout his time at MIT.  As a first-year student, he was initially drawn to mechanical engineering because he wanted to keep his options open.

“I felt like mechanical engineering is that perfect niche where there’s so much exposure to so many different fields. It has taught me more than just how to build things, it has changed how I think. It was honestly the best decision I ever made,” says Patel, now a senior studying mechanical engineering.

Class 2.00C (Design for Complex Environmental Issues), which is offered through the departments of Mechanical Engineering, Civil and Environmental Engineering, and MIT D-Lab, was the first class to expose him to how engineers are developing solutions to promote sustainability. Part of the Terrascope program for first-year students, the class focused on the theme “climate resiliency” the year Patel took it. Patel and his classmates traveled to the Netherlands for the class to see the infrastructure that has been built to mitigate damage from climate change-related flooding. 

The class and trip were a turning point for Patel.

“From then on, I have approached sustainability in pretty much every direction I could at MIT,” he says.

Advocating for fossil fuel divestment

The summer after his sophomore year, Patel became a founding member of a group called MIT Divest. The student-led group advocates for MIT to divest or remove investments in any companies that “develop fossil fuel resources beyond the 2 degrees Celsius carbon emissions limit, spread climate disinformation, and engage in anti-climate lobbying.”

The group also asks that any money divested from the fossil fuel industry be reinvested into carbon-free energy enterprises. For Patel, who is now co-chair of MIT Divest along with physics major Jessica Cohen, the group was his first foray into activism.

“Our work at MIT Divest is really exploring the climate activism side of things,” says Patel. “As a young person, I don’t have a lot of power on a government scale besides how I vote, but with MIT Divest I felt empowered to fight for change within the MIT community.”

Since launching, the group engaged in a number of activities to encourage fellow students and faculty to consider divestiture, including surveys, articles in MIT’s student newspaper The Tech, and meetings with members of MIT’s administration.

Patel is also the MIT Divest representative on MIT’s Climate Action Advisory Committee. He and the MIT Divest team hope to make divestments a central talking point as MIT shapes its Climate Action Plan, to be released this spring.

While MIT Divest has afforded Patel the opportunity to explore climate activism, his academic work has helped him develop sustainable solutions both on MIT’s campus and places further afield, like the Himalaya.

Reusable utensils on campusAs with most seniors this year, the fall 2020 semester looked different than Patel had envisioned. He was able to live on campus with his classmates, following various Covid-19 protocols put in place to keep the campus community safe.  

In class 2.S885 (Exploring Sustainability at Different Scales), Patel and his classmate Sheila Kennedy-Moore examined how to make on-campus dining during the pandemic more sustainable. For their final project in the class, Patel and Kennedy-Moore compared the energy use and carbon emissions associated with a variety of disposable utensils, containers, and cups.

They did a quantitative analysis of the materials used in the disposables provided to students eating in their dorm rooms by MIT Dining and made recommendations based on which materials had the smallest carbon footprint.

The pair also examined the effectiveness of the Reusable Utensil Pilot, launched by the Student Sustainability Coalition during the fall semester. They took into account the energy used to wash reusable utensils in warm water after each use.“What we found was that shifting from fully disposable utensils to reusable utensils could halve carbon emissions for the utensils during the semester,” says Patel.

Their work was referenced in a recommendation made by Waste Watchers, UA Sustain, and MIT SSC for MIT to provide reusable utensils to students. This spring, MIT Dining decided to include reusable utensils in students’ “back-to-campus” tote bag to promote the use of reusable utensils.

Sustainable Homes in the HimalayaFor his senior thesis, Patel is working with a team at MIT D-Lab in collaboration with Institute of Chemical Technology (ICT)-Mumbai and University of Petroleum and Energy Studies (UPES) on developing home energy solutions for communities in the Himalayan region. During the cold winter months, many Himalayan communities rely on inefficient and ineffective home heating methods. Some of these methods, in addition to open fires used to cook meals, are hazardous to people’s health.

“People often walk long distances to collect wood, suffer from fine particulate pollution from indoor fires and heating and cooking devices, and lack the ability to adequately provide heat during cold months and cook safely throughout the year,” says Patel.

The research team has conducted surveys to better understand the difficulties these communities face. Patel will conduct an analysis of this data and analyze user needs and preferences. His analysis will help to guide the team on which solutions may be suitable for problems associated with household energy in the region.

“Arnav has used his engineering intuition and user research skills that he learned in D-Lab courses to design and analyze a household needs assessment for our project on Livable Himalayan Homes,” says Daniel Sweeney, a research scientist at MIT D-Lab. “This project will result in affordable home energy solutions that meet the unique needs of these families and can be scaled across communities in the Himalayan region.”

According to Sweeney, Patel has become an integral part of MIT D-Lab over the years. “Arnav has a unique mix of MIT-nerdiness along with great care, dedication, and respect for the many collaborators he has worked with around the world. He has been a valuable member of the D-Lab family,” Sweeney adds.

In addition to working on his thesis, this semester Patel is participating in an MIT Experiential Learning Opportunity (ELO) with Beth Israel Deaconess Medical Center to help assess how their real estate decisions affect their carbon emissions. 

Sustainability in consultingAfter graduation in June, Patel will join management consulting firm Bain and Company as an associate consultant. While the move to management consulting may seem like a divergence from his passion for sustainability, Patel sees an opportunity to approach problems associated with climate change from a different angle.

“I landed in the management consulting realm because I wanted to understand the business world a little bit better,” he says. “That’s another area where I feel like I could play my part in pushing sustainability.” More

“The overall question for me is how to decarbonize society in the most affordable way,” says Nestor Sepulveda SM ’16, PhD ’20. As a postdoc at MIT and a researcher with the MIT Energy Initiative (MITEI), he worked with a team over several years to investigate what mix of energy sources might best accomplish this goal. The group’s initial studies suggested the “need to develop energy storage technologies that can be cost-effectively deployed for much longer durations than lithium-ion batteries,” says Dharik Mallapragada, a research scientist with MITEI.  

In a new paper published in Nature Energy, Sepulveda, Mallapragada, and colleagues from MIT and Princeton University offer a comprehensive cost and performance evaluation of the role of long-duration energy storage (LDES) technologies in transforming energy systems. LDES, a term that covers a class of diverse, emerging technologies, can respond to the variable output of renewables, discharging electrons for days and even weeks, providing resilience to an electric grid poised to deploy solar and wind power on a large scale.

“If we want to rely overwhelmingly on wind and solar power for electricity — increasingly the most affordable way to decrease carbon emissions — we have to deal with their intermittency,” says Jesse Jenkins SM ’14, PhD ’18, an assistant professor of mechanical and aerospace engineering and the Andlinger Center for Energy and the Environment at Princeton University and former researcher at MITEI.

In their paper, the researchers analyzed whether LDES paired with renewable energy sources and short-duration energy storage options like lithium-ion batteries could indeed power a massive and cost-effective transition to a decarbonized grid. They also investigated whether LDES might even eliminate the need for available-on-demand, or firm, low-carbon energy sources such as nuclear power and natural gas with carbon capture and sequestration.

“The message here is that innovative and low-cost LDES technologies could potentially have a big impact, making a deeply decarbonized electricity system more affordable and reliable,” says lead author Sepulveda, who now works as a consultant with McKinsey and Company.  But, he notes, “We will still be better off retaining firm low-carbon energy sources among our options.”

In addition to Jenkins and Mallapragada, the paper’s coauthors include Aurora Edington SM ’19, a MITEI research assistant at the time of this research and now a consultant at The Cadmus Group; and Richard K. Lester, the Japan Steel Industry Professor and associate provost at MIT, and former head of the Department of Nuclear Science and Engineering.

“As the world begins to focus more seriously on how to achieve deep decarbonization goals in the coming decades, the insights from these system-level studies are essential,” says Lester. “Researchers, innovators, investors, and policymakers will all benefit from knowledge of the cost and technical performance targets that are suggested by this work.” 

Performance and cost

The team set out to assess the impacts of LDES solutions in hypothetical electric systems that reflect real-world conditions, where technologies are scrutinized not merely by their standalone attributes, but by their relative value when matched against other energy sources.

“We need to decarbonize at an affordable cost to society, and we wanted to know if LDES can increase our probability of success while also reducing overall system cost, given the other technologies competing in the space,” says Sepulveda.

In pursuit of this goal, the team deployed an electricity system capacity expansion model, GenX, earlier developed by Jenkins and Sepulveda while at MIT. This simulation tool made it possible to evaluate the potential system impact of utilizing LDES technologies, including technologies currently being developed and others that could potentially be developed, for different future low-carbon electric grid scenarios characterized by cost and performance attributes of renewable generation, different types of firm generation, as well as alternative electricity demand projections. The study, says Jenkins, was “the first extensive use of this sort of experimental method of applying wide-scale parametric uncertainty and long-term systems-level analysis to evaluate and identify target goals regarding cost and performance for emerging long-duration energy storage technologies.”

For their study, the researchers surveyed a range of long-duration technologies — some backed by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E) program — to define the plausible cost and performance attributes of future LDES systems based on five key parameters that encompass a range of mechanical, chemical, electrochemical, and thermal approaches. These include pumped hydropower storage, vanadium redox flow batteries, aqueous sulfur flow batteries, and firebrick resistance-heated thermal storage, among others.

“Think of a bathtub, where the parameter of energy storage capacity is analogous to the volume of the tub,” explains Jenkins. Continuing the analogy, another important parameter, charge power capacity, is the size of the faucet filling the tub, and discharge power capacity, the size of the drain. In the most generalized version of an LDES technology, each attribute of the system can be independently sized. In optimizing an energy system where LDES technology functions as “an economically attractive contributor to a lower-cost, carbon-free grid,” says Jenkins, the researchers found that the parameter that matters the most is energy storage capacity cost.

“For a comprehensive assessment of LDES technology design and its economic value to decarbonized grids, we evaluated nearly 18,000 distinctive cases,” Edington explains, “spanning variations in load and renewable resource availability, northern and southern latitude climates, different combinations of LDES technologies and LDES design parameters, and choice of competing firm low-carbon generation resources.”

Some of the key takeaways from the researchers’ rigorous analysis:

LDES technologies can offer more than a 10 percent reduction in the costs of deeply decarbonized electricity systems if the storage energy capacity cost (the cost to increase the size of the bathtub) remains under the threshold of $20/kilowatt-hour. This value could increase to 40 percent if energy capacity cost of future technologies is reduced to $1/kWh and to as much as 50 percent for the best combinations of parameters modeled in the space. For purposes of comparison, the current storage energy capacity cost of batteries is around $200/kWh.
Given today’s prevailing electricity demand patterns, the LDES energy capacity cost must fall below $10/kWh to replace nuclear power; for LDES to replace all firm power options entirely, the cost must fall below $1/kWh.
In scenarios with extensive electrification of transportation and other end-uses to meet economy-wide deep decarbonization goals, it will be more challenging in northern latitudes to displace firm generation under any likely future combination of costs and efficiency performance range for known LDES technologies. This is primarily due to greater peak electricity demand resulting from heating needs in colder climates.

Actionable insights

While breakthroughs in fusion energy, next-generation nuclear power, or carbon capture could well shake up their models, the researchers believe that insights from their study can make an impact right now.

“People working with LDES can see where their technology fits in to the future electricity mix and ask: ‘Does it make economic sense from a system perspective?’” says Mallapragada. “And it’s a call for action in policy and investment in innovation, because we show where the technology gaps lie and where we see the greatest value for research breakthroughs in LDES technology development.”

Not all LDES technologies can clear the bar in this design space, nor can there be reliance on LDES as the exclusive means to expand wind and solar swiftly in the near term, or to enable a complete transition to a zero-carbon economy by 2050.

“We show how promising LDES technologies could be,” says Sepulveda. “But we also show that these technologies are not the one solution, and that we are still better off with them complementing firm resources.”

Jenkins spies niche market opportunities for LDES immediately, such as places with a lot of wind and solar deployed and limits on transmission to export that power. In such locations, storage could fill up when transmission is at its limit, and export power later while maximizing use of the power line capacity. But LDES technologies must be ready to make a major impact by the late 2030s and 2040s, he believes, by which time economies might need to be weaned completely off of natural gas dependency if decarbonization is to succeed.

“We must develop and deploy LDES and improve other low-carbon technologies this decade, so we can present real alternatives to policymakers and power system operators,” he says.

In light of this urgent need, Jenkins at Princeton and Mallapragada at MIT are now working to evaluate and advance technologies with the greatest potential in the storage and energy fields to hasten the zero-carbon goal. With help from ARPA-E and MITEI, they are making the state-of-the-art GenX electricity system planning model an open-source tool for public use as well. If their research and modeling approach can show developers and policymakers what kind of designs are most impactful, says Sepulveda, “We could have a decarbonized system that’s less expensive than today’s system if we do things right.”

This research was supported by a grant from the National Science Foundation, and by MITEI’s Low-Carbon Energy Center for Electric Power Systems. More

As incomes in developing countries continue to rise, demand for air conditioners is expected to triple by 2050. The surge will multiply what is already a major source of greenhouse gas emissions: Air conditioning is currently responsible for almost 20 percent of electricity use in buildings around the world.

Now the startup Transaera is working to curb those energy demands with a more efficient air conditioner that uses safer refrigerants to cool homes. The company believes its machine could have one-fifth the impact on the climate when compared to traditional ACs.

“The thing about air conditioning is the basic technology hasn’t changed much since it was invented 100 years ago,” says Transaera chief engineer Ross Bonner SM ’20.

That will change rapidly if Transaera’s small team is successful. The company is currently a finalist in a global competition to redesign the air conditioner. The winner of the competition, named the Global Cooling Prize, will get $1 million to commercialize their machines.

At the heart of Transaera’s design is a class of highly porous materials called metal organic frameworks, or MOFs, that passively pull moisture from the air as the machine works. Co-founder Mircea Dincă, the W.M. Keck Professor of Energy in MIT’s Department of Chemistry, has done pioneering research on MOFs, and the company’s team members see the materials’ commercial advancement as an important part of their mission.

“MOFs have a lot of potential applications, but the thing that’s held them back is unit economics and the inability to make them in a cost-effective way at scale,” says Bonner. “What Transaera aims to do is be the first to commercialize MOFs at scale and lead the breakthrough that brings MOFs into the public domain.”

Dincă’s co-founders are Transaera CEO Sorin Grama SM ’07, who is also a lecturer at MIT D-Lab, and CTO Matt Dorson, a mechanical engineer who worked with Grama on a previous startup.

“I’m just incentivized by this idea of creating something revolutionary,” says Grama. “We’ve designed these new devices, but we’re also bringing this material knowledge, with Mircea and our collaborators, and blending the two to create something really new and different.”

A material of opportunity

Grama and Dorson previously collaborated at Promethean Power Systems, which develops off-grid refrigeration solutions for farmers in India. To date, the company has installed 1,800 refrigeration systems that serve roughly 60,000 farmers each day. After stepping down as CEO in 2015, Grama returned to the Institute to teach at MIT D-Lab and serve as an entrepreneur-in-residence at the Martin Trust Center for MIT Entrepreneurship.

During that time Grama was introduced to MOFs by Rob Stoner, the MIT Energy Initiative’s deputy director for science and technology and a founding director of the MIT Tata Center.

Stoner introduced Grama to Dincă, who had been studying MOFs since he joined MIT’s faculty in 2010 and grew up 10 miles from Grama’s hometown in Romania.

MOF’s intriguing properties come from their large internal surface area and the ability to finely tune the size of the tiny chambers that run through them. Dincă previously developed MOFs with chambers just big enough to trap water molecules from the air. He described them as “sponges on steroids.”

Grama began thinking about using the material for refrigeration, but another application soon presented itself. Most people think air conditioners only cool the air in a space, but they also dry the air they’re cooling. Traditional machines use something called an evaporator, a cold coil to pull water out of the air through condensation. The cold coil must be made much colder than the desired temperature in the room in order to collect moisture. Dorson says pulling moisture out of the air takes up about half of the electricity used by traditional air conditioners.

Transaera’s MOFs passively collect moisture as air enters the system. The machine’s waste heat is then used to dry the MOF material for continuous reuse.

Transaera was formally founded in the beginning of 2018, and the Global Cooling Prize was announced later that year. Hundreds of teams expressed interest, and Transaera was ultimately selected as one of eight finalists and given $200,000 to deliver prototypes to competition organizers.

Bonner joined the company in 2019 after exploring paths to carbon neutral ACs as part of a mechanical engineering class at MIT.

When Covid-19 began sweeping through countries around the world, it was decided the Cooling Prize’s trials in India would be run remotely. Adding to the challenge, the co-founders didn’t have access to their lab in Somerville due to restrictions and were using their own tools and garages to complete the prototypes. After shipping off their prototypes, Transaera had to help Prize organizers install them through a live video feed for field trials in multiple locations in India. The team says the results validated Transaera’s approach and showed the system had a significantly lower climate impact than baseline units.

Transaera’s system also used a refrigerant known as R-32 with zero ozone depleting potential (ODP) and a global warming potential about three times lower than another commonly used refrigerant.

The milestone further convinced Transaera’s small team they were onto something.

“This air conditioning problem can have a real, material impact on people’s quality of life,” Dorson says.

Pushing a field forward

The Global Cooling Prize will announce its winner next month. Regardless of what happens, Transaera will be growing the team this year and running additional trials in Boston. The company has been working with large manufacturers that have supplied equipment for prototypes and shown the founders how they might integrate their devices with existing technologies.

The company’s foundational work with MOFs has continued even as Transaera’s air conditioner gets closer to commercialization. In fact, Transaera recently received a grant from the National Science Foundation to explore more efficient paths to MOF production with a lab at MIT.

“MOFs open up so many possibilities for all kinds of revolutionary devices, not just in air conditioning, but in water harvesting, energy storage, and super capacitors,” Grama says. “This knowledge we’re developing can apply to so many other applications down the road, and I feel like we’re pioneering this field and pushing the edge of the technology.”

Still, Transaera’s founders remain focused on bringing their AC to market first, acknowledging the problem they’re trying to tackle is big enough to keep them busy for a while.

“It’s clear when you look at the swath of the world that’s in the hot, humid tropics, there’s a growing middle class, and one of the first thing they’ll want to buy is an air conditioner,” Dorson says. “Developing more efficient air conditioning systems is critical for the health of people and of our planet’s environment.” More

Lithium-ion batteries have made possible the lightweight electronic devices whose portability we now take for granted, as well as the rapid expansion of electric vehicle production. But researchers around the world are continuing to push limits to achieve ever-greater energy densities — the amount of energy that can be stored in a given mass of material — in order to improve the performance of existing devices and potentially enable new applications such as long-range drones and robots.

One promising approach is the use of metal electrodes in place of the conventional graphite, with a higher charging voltage in the cathode. Those efforts have been hampered, however, by a variety of unwanted chemical reactions that take place with the electrolyte that separates the electrodes. Now, a team of researchers at MIT and elsewhere has found a novel electrolyte that overcomes these problems and could enable a significant leap in the power-per-weight of next-generation batteries, without sacrificing the cycle life.

The research is reported today in the journal Nature Energy in a paper by MIT professors Ju Li, Yang Shao-Horn, and Jeremiah Johnson; postdoc Weijiang Xue; and 19 others at MIT, two national laboratories, and elsewhere. The researchers say the finding could make it possible for lithium-ion batteries, which now typically can store about 260 watt-hours per kilogram, to store about 420 watt-hours per kilogram. That would translate into longer ranges for electric cars and longer-lasting changes on portable devices.

The basic raw materials for this electrolyte are inexpensive (though one of the intermediate compounds is still costly because it’s in limited use), and the process to make it is simple. So, this advance could be implemented relatively quickly, the researchers say.

The electrolyte itself is not new, explains Johnson, a professor of chemistry. It was developed a few years ago by some members of this research team, but for a different application. It was part of an effort to develop lithium-air batteries, which are seen as the ultimate long-term solution for maximizing battery energy density. But there are many obstacles still facing the development of such batteries, and that technology may still be years away. In the meantime, applying that electrolyte to lithium-ion batteries with metal electrodes turns out to be something that can be achieved much more quickly.

The new application of this electrode material was found “somewhat serendipitously,” after it had initially been developed a few years ago by Shao-Horn, Johnson, and others, in a collaborative venture aimed at lithium-air battery development.

“There’s still really nothing that allows a good rechargeable lithium-air battery,” Johnson says. However, “we designed these organic molecules that we hoped might confer stability, compared to the existing liquid electrolytes that are used.” They developed three different sulfonamide-based formulations, which they found were quite resistant to oxidation and other degradation effects. Then, working with Li’s group, postdoc Xue decided to try this material with more standard cathodes instead.

The type of battery electrode they have now used with this electrolyte, a nickel oxide containing some cobalt and manganese, “is the workhorse of today’s electric vehicle industry,” says Li, who is a professor of nuclear science and engineering and materials science and engineering.  

Because the electrode material expands and contracts anisotropically as it gets charged and discharged, this can lead to cracking and a breakdown in performance when used with conventional electrolytes. But in experiments in collaboration with Brookhaven National Laboratory, the researchers found that using the new electrolyte drastically reduced these stress-corrosion cracking degradations.

The problem was that the metal atoms in the alloy tended to dissolve into the liquid electrolyte, losing mass and leading to cracking of the metal. By contrast, the new electrolyte is extremely resistant to such dissolution. Looking at the data from the Brookhaven tests, Li says, it was “sort of shocking to see that, if you just change the electrolyte, then all these cracks are gone.” They found that the morphology of the electrolyte material is much more robust, and the transition metals “just don’t have as much solubility” in these new electrolytes.

That was a surprising combination, he says, because the material still readily allows lithium ions to pass through — the essential mechanism by which batteries get charged and discharged — while blocking the other cations, known as transition metals, from entering. The accumulation of unwanted compounds on the electrode surface after many charging-discharging cycles was reduced more than tenfold compared to the standard electrolyte.

“The electrolyte is chemically resistant against oxidation of high-energy nickel-rich materials, preventing particle fracture and stabilizing the positive electrode during cycling,” says Shao-Horn, a professor of mechanical engineering and materials science and engineering. “The electrolyte also enables stable and reversible stripping and plating of lithium metal, an important step toward enabling rechargeable lithium-metal batteries with energy two times that of the state-the-art lithium-ion batteries. This finding will catalyze further electrolyte search and designs of liquid electrolytes for lithium-metal batteries rivaling those with solid state electrolytes.”

The next step is to scale the production to make it affordable. “We make it in one very easy reaction from readily available commercial starting materials,” Johnson says. Right now, the precursor compound used to synthesize the electrolyte is expensive, but he says,  “I think if we can show the world that this is a great electrolyte for consumer electronics, the motivation to further scale up will help to drive the price down.”

Because this is essentially a “drop in” replacement for an existing electrolyte and doesn’t require redesign of the entire battery system, Li says, it could be implemented quickly and could be commercialized within a couple of years. “There’s no expensive elements, it’s just carbon and fluorine. So it’s not limited by resources, it’s just the process,” he says.

The research was supported by the U.S. Department of Energy and the National Science Foundation, and made use of facilities at Brookhaven National Laboratory and Argonne National Laboratory. More