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    Using excess heat to improve electrolyzers and fuel cells

    Reducing the use of fossil fuels will have unintended consequences for the power-generation industry and beyond. For example, many industrial chemical processes use fossil-fuel byproducts as precursors to things like asphalt, glycerine, and other important chemicals. One solution to reduce the impact of the loss of fossil fuels on industrial chemical processes is to store and use the heat that nuclear fission produces. New MIT research has dramatically improved a way to put that heat toward generating chemicals through a process called electrolysis. 

    Electrolyzers are devices that use electricity to split water (H2O) and generate molecules of hydrogen (H2) and oxygen (O2). Hydrogen is used in fuel cells to generate electricity and drive electric cars or drones or in industrial operations like the production of steel, ammonia, and polymers. Electrolyzers can also take in water and carbon dioxide (CO2) and produce oxygen and ethylene (C2H4), a chemical used in polymers and elsewhere.

    There are three main types of electrolyzers. One type works at room temperature, but has downsides; they’re inefficient and require rare metals, such as platinum. A second type is more efficient but runs at high temperatures, above 700 degrees Celsius. But metals corrode at that temperature, and the devices need expensive sealing and insulation. The third type would be a Goldilocks solution for nuclear heat if it were perfected, running at 300-600 C and requiring mostly cheap materials like stainless steel. These cells have never been operated as efficiently as theory says they should. The new work, published this month in Nature, both illuminates the problem and offers a solution.

    A sandwich mystery

    The intermediate-temperature devices use what are called protonic ceramic electrochemical cells. Each cell is a sandwich, with a dense electrolyte layered between two porous electrodes. Water vapor is pumped into the top electrode. A wire on the side connects the two electrodes, and externally generated electricity runs from the top to the bottom. The voltage pulls electrons out of the water, which splits the molecule, releasing oxygen. A hydrogen atom without an electron is just a proton. The protons get pulled through the electrolyte to rejoin with the electrons at the bottom electrode and form H2 molecules, which are then collected.

    On its own, the electrolyte in the middle, made mainly of barium, cerium, and zirconium, conducts protons very well. “But when we put the same material into this three-layer device, the proton conductivity of the full cell is pretty bad,” says Yanhao Dong, a postdoc in MIT’s Department of Nuclear Science and Engineering and a paper co-author. “Its conductivity is only about 50 percent of the bulk form’s. We wondered why there’s an inconsistency here.”

    A couple of clues pointed them in the right direction. First, if they don’t prepare the cell very carefully, the top layer, only about 20 microns (.02 millimeters) thick, doesn’t stay attached. “Sometimes if you use just Scotch tape, it will peel off,” Dong says. Second, when they looked at a cross section of a device using a scanning electron microscope, they saw that the top surface of the electrolyte layer was flat, whereas the bottom surface of the porous electrode sitting on it was bumpy, and the two came into contact in only a few places. They didn’t bond well. That precarious interface leads to both structural de-lamination and poor proton passage from the electrode to the electrolyte.

    Acidic solution

    The solution turned out to be simple: researchers roughed up the top of the electrolyte. Specifically, they applied acid for 10 minutes, which etched grooves into the surface. Ju Li, the Battelle Energy Alliance Professor in Nuclear Engineering and professor of materials science and engineering at MIT, and a paper co-author, likens it to sandblasting a surface before applying paint to increase adhesion. Their acid-treated cells produced about 200 percent more hydrogen per area at 1.5 volts at 600 C than did any previous cell of its type, and worked well down to 350 C with very little performance decay over extended operation. 

    “The authors reported a surprisingly simple yet highly effective surface treatment to dramatically improve the interface,” says Liangbing Hu, the director of the Center for Materials Innovation at the Maryland Energy Innovation Institute, who was not involved in the work. He calls the cell performance “exceptional.”

    “We are excited and surprised” by the results, Dong says. “The engineering solution seems quite simple. And that’s actually good, because it makes it very applicable to real applications.” In a practical product, many such cells would be stacked together to form a module. MIT’s partner in the project, Idaho National Laboratory, is very strong in engineering and prototyping, so Li expects to see electrolyzers based on this technology at scale before too long. “At the materials level, this is a breakthrough that shows that at a real-device scale you can work at this sweet spot of temperature of 350 to 600 degrees Celsius for nuclear fission and fusion reactors,” he says.

    “Reduced operating temperature enables cheaper materials for the large-scale assembly, including the stack,” says Idaho National Laboratory researcher and paper co-author Dong Ding. “The technology operates within the same temperature range as several important, current industrial processes, including ammonia production and CO2 reduction. Matching these temperatures will expedite the technology’s adoption within the existing industry.”

    “This is very significant for both Idaho National Lab and us,” Li adds, “because it bridges nuclear energy and renewable electricity.” He notes that the technology could also help fuel cells, which are basically electrolyzers run in reverse, using green hydrogen or hydrocarbons to generate electricity. According to Wei Wu, a materials scientist at Idaho National Laboratory and a paper co-author, “this technique is quite universal and compatible with other solid electrochemical devices.”

    Dong says it’s rare for a paper to advance both science and engineering to such a degree. “We are happy to combine those together and get both very good scientific understanding and also very good real-world performance.”

    This work, done in collaboration with Idaho National Laboratory, New Mexico State University, and the University of Nebraska–Lincoln, was funded, in part, by the U.S. Department of Energy. More

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    A new heat engine with no moving parts is as efficient as a steam turbine

    Engineers at MIT and the National Renewable Energy Laboratory (NREL) have designed a heat engine with no moving parts. Their new demonstrations show that it converts heat to electricity with over 40 percent efficiency — a performance better than that of traditional steam turbines.

    The heat engine is a thermophotovoltaic (TPV) cell, similar to a solar panel’s photovoltaic cells, that passively captures high-energy photons from a white-hot heat source and converts them into electricity. The team’s design can generate electricity from a heat source of between 1,900 to 2,400 degrees Celsius, or up to about 4,300 degrees Fahrenheit.

    The researchers plan to incorporate the TPV cell into a grid-scale thermal battery. The system would absorb excess energy from renewable sources such as the sun and store that energy in heavily insulated banks of hot graphite. When the energy is needed, such as on overcast days, TPV cells would convert the heat into electricity, and dispatch the energy to a power grid.

    With the new TPV cell, the team has now successfully demonstrated the main parts of the system in separate, small-scale experiments. They are working to integrate the parts to demonstrate a fully operational system. From there, they hope to scale up the system to replace fossil-fuel-driven power plants and enable a fully decarbonized power grid, supplied entirely by renewable energy.

    “Thermophotovoltaic cells were the last key step toward demonstrating that thermal batteries are a viable concept,” says Asegun Henry, the Robert N. Noyce Career Development Professor in MIT’s Department of Mechanical Engineering. “This is an absolutely critical step on the path to proliferate renewable energy and get to a fully decarbonized grid.”

    Henry and his collaborators have published their results today in the journal Nature. Co-authors at MIT include Alina LaPotin, Kevin Schulte, Kyle Buznitsky, Colin Kelsall, Andrew Rohskopf, and Evelyn Wang, the Ford Professor of Engineering and head of the Department of Mechanical Engineering, along with collaborators at NREL in Golden, Colorado.

    Jumping the gap

    More than 90 percent of the world’s electricity comes from sources of heat such as coal, natural gas, nuclear energy, and concentrated solar energy. For a century, steam turbines have been the industrial standard for converting such heat sources into electricity.

    On average, steam turbines reliably convert about 35 percent of a heat source into electricity, with about 60 percent representing the highest efficiency of any heat engine to date. But the machinery depends on moving parts that are temperature- limited. Heat sources higher than 2,000 degrees Celsius, such as Henry’s proposed thermal battery system, would be too hot for turbines.

    In recent years, scientists have looked into solid-state alternatives — heat engines with no moving parts, that could potentially work efficiently at higher temperatures.

    “One of the advantages of solid-state energy converters are that they can operate at higher temperatures with lower maintenance costs because they have no moving parts,” Henry says. “They just sit there and reliably generate electricity.”

    Thermophotovoltaic cells offered one exploratory route toward solid-state heat engines. Much like solar cells, TPV cells could be made from semiconducting materials with a particular bandgap — the gap between a material’s valence band and its conduction band. If a photon with a high enough energy is absorbed by the material, it can kick an electron across the bandgap, where the electron can then conduct, and thereby generate electricity — doing so without moving rotors or blades.

    To date, most TPV cells have only reached efficiencies of around 20 percent, with the record at 32 percent, as they have been made of relatively low-bandgap materials that convert lower-temperature, low-energy photons, and therefore convert energy less efficiently.

    Catching light

    In their new TPV design, Henry and his colleagues looked to capture higher-energy photons from a higher-temperature heat source, thereby converting energy more efficiently. The team’s new cell does so with higher-bandgap materials and multiple junctions, or material layers, compared with existing TPV designs.

    The cell is fabricated from three main regions: a high-bandgap alloy, which sits over a slightly lower-bandgap alloy, underneath which is a mirror-like layer of gold. The first layer captures a heat source’s highest-energy photons and converts them into electricity, while lower-energy photons that pass through the first layer are captured by the second and converted to add to the generated voltage. Any photons that pass through this second layer are then reflected by the mirror, back to the heat source, rather than being absorbed as wasted heat.

    The team tested the cell’s efficiency by placing it over a heat flux sensor — a device that directly measures the heat absorbed from the cell. They exposed the cell to a high-temperature lamp and concentrated the light onto the cell. They then varied the bulb’s intensity, or temperature, and observed how the cell’s power efficiency — the amount of power it produced, compared with the heat it absorbed — changed with temperature. Over a range of 1,900 to 2,400 degrees Celsius, the new TPV cell maintained an efficiency of around 40 percent.

    “We can get a high efficiency over a broad range of temperatures relevant for thermal batteries,” Henry says.

    The cell in the experiments is about a square centimeter. For a grid-scale thermal battery system, Henry envisions the TPV cells would have to scale up to about 10,000 square feet (about a quarter of a football field), and would operate in climate-controlled warehouses to draw power from huge banks of stored solar energy. He points out that an infrastructure exists for making large-scale photovoltaic cells, which could also be adapted to manufacture TPVs.

    “There’s definitely a huge net positive here in terms of sustainability,” Henry says. “The technology is safe, environmentally benign in its life cycle, and can have a tremendous impact on abating carbon dioxide emissions from electricity production.”

    This research was supported, in part, by the U.S. Department of Energy. More

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    A better way to separate gases

    Industrial processes for chemical separations, including natural gas purification and the production of oxygen and nitrogen for medical or industrial uses, are collectively responsible for about 15 percent of the world’s energy use. They also contribute a corresponding amount to the world’s greenhouse gas emissions. Now, researchers at MIT and Stanford University have developed a new kind of membrane for carrying out these separation processes with roughly 1/10 the energy use and emissions.

    Using membranes for separation of chemicals is known to be much more efficient than processes such as distillation or absorption, but there has always been a tradeoff between permeability — how fast gases can penetrate through the material — and selectivity — the ability to let the desired molecules pass through while blocking all others. The new family of membrane materials, based on “hydrocarbon ladder” polymers, overcomes that tradeoff, providing both high permeability and extremely good selectivity, the researchers say.

    The findings are reported today in the journal Science, in a paper by Yan Xia, an associate professor of chemistry at Stanford; Zachary Smith, an assistant professor of chemical engineering at MIT; Ingo Pinnau, a professor at King Abdullah University of Science and Technology, and five others.

    Gas separation is an important and widespread industrial process whose uses include removing impurities and undesired compounds from natural gas or biogas, separating oxygen and nitrogen from air for medical and industrial purposes, separating carbon dioxide from other gases for carbon capture, and producing hydrogen for use as a carbon-free transportation fuel. The new ladder polymer membranes show promise for drastically improving the performance of such separation processes. For example, separating carbon dioxide from methane, these new membranes have five times the selectivity and 100 times the permeability of existing cellulosic membranes for that purpose. Similarly, they are 100 times more permeable and three times as selective for separating hydrogen gas from methane.

    The new type of polymers, developed over the last several years by the Xia lab, are referred to as ladder polymers because they are formed from double strands connected by rung-like bonds, and these linkages provide a high degree of rigidity and stability to the polymer material. These ladder polymers are synthesized via an efficient and selective chemistry the Xia lab developed called CANAL, an acronym for catalytic arene-norbornene annulation, which stitches readily available chemicals into ladder structures with hundreds or even thousands of rungs. The polymers are synthesized in a solution, where they form rigid and kinked ribbon-like strands that can easily be made into a thin sheet with sub-nanometer-scale pores by using industrially available polymer casting processes. The sizes of the resulting pores can be tuned through the choice of the specific hydrocarbon starting compounds. “This chemistry and choice of chemical building blocks allowed us to make very rigid ladder polymers with different configurations,” Xia says.

    To apply the CANAL polymers as selective membranes, the collaboration made use of Xia’s expertise in polymers and Smith’s specialization in membrane research. Holden Lai, a former Stanford doctoral student, carried out much of the development and exploration of how their structures impact gas permeation properties. “It took us eight years from developing the new chemistry to finding the right polymer structures that bestow the high separation performance,” Xia says.

    The Xia lab spent the past several years varying the structures of CANAL polymers to understand how their structures affect their separation performance. Surprisingly, they found that adding additional kinks to their original CANAL polymers significantly improved the mechanical robustness of their membranes and boosted their selectivity  for molecules of similar sizes, such as oxygen and nitrogen gases, without losing permeability of the more permeable gas. The selectivity actually improves as the material ages. The combination of high selectivity and high permeability makes these materials outperform all other polymer materials in many gas separations, the researchers say.

    Today, 15 percent of global energy use goes into chemical separations, and these separation processes are “often based on century-old technologies,” Smith says. “They work well, but they have an enormous carbon footprint and consume massive amounts of energy. The key challenge today is trying to replace these nonsustainable processes.” Most of these processes require high temperatures for boiling and reboiling solutions, and these often are the hardest processes to electrify, he adds.

    For the separation of oxygen and nitrogen from air, the two molecules only differ in size by about 0.18 angstroms (ten-billionths of a meter), he says. To make a filter capable of separating them efficiently “is incredibly difficult to do without decreasing throughput.” But the new ladder polymers, when manufactured into membranes produce tiny pores that achieve high selectivity, he says. In some cases, 10 oxygen molecules permeate for every nitrogen, despite the razor-thin sieve needed to access this type of size selectivity. These new membrane materials have “the highest combination of permeability and selectivity of all known polymeric materials for many applications,” Smith says.

    “Because CANAL polymers are strong and ductile, and because they are soluble in certain solvents, they could be scaled for industrial deployment within a few years,” he adds. An MIT spinoff company called Osmoses, led by authors of this study, recently won the MIT $100K entrepreneurship competition and has been partly funded by The Engine to commercialize the technology.

    There are a variety of potential applications for these materials in the chemical processing industry, Smith says, including the separation of carbon dioxide from other gas mixtures as a form of emissions reduction. Another possibility is the purification of biogas fuel made from agricultural waste products in order to provide carbon-free transportation fuel. Hydrogen separation for producing a fuel or a chemical feedstock, could also be carried out efficiently, helping with the transition to a hydrogen-based economy.

    The close-knit team of researchers is continuing to refine the process to facilitate the development from laboratory to industrial scale, and to better understand the details on how the macromolecular structures and packing result in the ultrahigh selectivity. Smith says he expects this platform technology to play a role in multiple decarbonization pathways, starting with hydrogen separation and carbon capture, because there is such a pressing need for these technologies in order to transition to a carbon-free economy.

    “These are impressive new structures that have outstanding gas separation performance,” says Ryan Lively, am associate professor of chemical and biomolecular engineering at Georgia Tech, who was not involved in this work. “Importantly, this performance is improved during membrane aging and when the membranes are challenged with concentrated gas mixtures. … If they can scale these materials and fabricate membrane modules, there is significant potential practical impact.”

    The research team also included Jun Myun Ahn and Ashley Robinson at Stanford, Francesco Benedetti at MIT, now the chief executive officer at Osmoses, and Yingge Wang at King Abdullah University of Science and Technology in Saudi Arabia. The work was supported by the Stanford Natural Gas Initiative, the Sloan Research Fellowship, the U.S. Department of Energy Office of Basic Energy Sciences, and the National Science Foundation. More

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    Using artificial intelligence to find anomalies hiding in massive datasets

    Identifying a malfunction in the nation’s power grid can be like trying to find a needle in an enormous haystack. Hundreds of thousands of interrelated sensors spread across the U.S. capture data on electric current, voltage, and other critical information in real time, often taking multiple recordings per second.

    Researchers at the MIT-IBM Watson AI Lab have devised a computationally efficient method that can automatically pinpoint anomalies in those data streams in real time. They demonstrated that their artificial intelligence method, which learns to model the interconnectedness of the power grid, is much better at detecting these glitches than some other popular techniques.

    Because the machine-learning model they developed does not require annotated data on power grid anomalies for training, it would be easier to apply in real-world situations where high-quality, labeled datasets are often hard to come by. The model is also flexible and can be applied to other situations where a vast number of interconnected sensors collect and report data, like traffic monitoring systems. It could, for example, identify traffic bottlenecks or reveal how traffic jams cascade.

    “In the case of a power grid, people have tried to capture the data using statistics and then define detection rules with domain knowledge to say that, for example, if the voltage surges by a certain percentage, then the grid operator should be alerted. Such rule-based systems, even empowered by statistical data analysis, require a lot of labor and expertise. We show that we can automate this process and also learn patterns from the data using advanced machine-learning techniques,” says senior author Jie Chen, a research staff member and manager of the MIT-IBM Watson AI Lab.

    The co-author is Enyan Dai, an MIT-IBM Watson AI Lab intern and graduate student at the Pennsylvania State University. This research will be presented at the International Conference on Learning Representations.

    Probing probabilities

    The researchers began by defining an anomaly as an event that has a low probability of occurring, like a sudden spike in voltage. They treat the power grid data as a probability distribution, so if they can estimate the probability densities, they can identify the low-density values in the dataset. Those data points which are least likely to occur correspond to anomalies.

    Estimating those probabilities is no easy task, especially since each sample captures multiple time series, and each time series is a set of multidimensional data points recorded over time. Plus, the sensors that capture all that data are conditional on one another, meaning they are connected in a certain configuration and one sensor can sometimes impact others.

    To learn the complex conditional probability distribution of the data, the researchers used a special type of deep-learning model called a normalizing flow, which is particularly effective at estimating the probability density of a sample.

    They augmented that normalizing flow model using a type of graph, known as a Bayesian network, which can learn the complex, causal relationship structure between different sensors. This graph structure enables the researchers to see patterns in the data and estimate anomalies more accurately, Chen explains.

    “The sensors are interacting with each other, and they have causal relationships and depend on each other. So, we have to be able to inject this dependency information into the way that we compute the probabilities,” he says.

    This Bayesian network factorizes, or breaks down, the joint probability of the multiple time series data into less complex, conditional probabilities that are much easier to parameterize, learn, and evaluate. This allows the researchers to estimate the likelihood of observing certain sensor readings, and to identify those readings that have a low probability of occurring, meaning they are anomalies.

    Their method is especially powerful because this complex graph structure does not need to be defined in advance — the model can learn the graph on its own, in an unsupervised manner.

    A powerful technique

    They tested this framework by seeing how well it could identify anomalies in power grid data, traffic data, and water system data. The datasets they used for testing contained anomalies that had been identified by humans, so the researchers were able to compare the anomalies their model identified with real glitches in each system.

    Their model outperformed all the baselines by detecting a higher percentage of true anomalies in each dataset.

    “For the baselines, a lot of them don’t incorporate graph structure. That perfectly corroborates our hypothesis. Figuring out the dependency relationships between the different nodes in the graph is definitely helping us,” Chen says.

    Their methodology is also flexible. Armed with a large, unlabeled dataset, they can tune the model to make effective anomaly predictions in other situations, like traffic patterns.

    Once the model is deployed, it would continue to learn from a steady stream of new sensor data, adapting to possible drift of the data distribution and maintaining accuracy over time, says Chen.

    Though this particular project is close to its end, he looks forward to applying the lessons he learned to other areas of deep-learning research, particularly on graphs.

    Chen and his colleagues could use this approach to develop models that map other complex, conditional relationships. They also want to explore how they can efficiently learn these models when the graphs become enormous, perhaps with millions or billions of interconnected nodes. And rather than finding anomalies, they could also use this approach to improve the accuracy of forecasts based on datasets or streamline other classification techniques.

    This work was funded by the MIT-IBM Watson AI Lab and the U.S. Department of Energy. More

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    “Vigilant inclusion” central to combating climate change

    “To turbocharge work on saving the planet, we need effective, innovative, localized solutions, and diverse perspectives and experience at the table,” said U.S. Secretary of Energy Jennifer M. Granholm, the keynote speaker at the 10th annual U.S. Clean Energy Education and Empowerment (C3E) Women in Clean Energy Symposium and Awards.

    This event, convened virtually over Nov. 3-4 and engaging more than 1,000 participants, was devoted to the themes of justice and equity in clean energy. In panels and presentations, speakers hammered home the idea that the benefits of a zero-carbon future must be shared equitably, especially among groups historically neglected or marginalized. To ensure this outcome, the speakers concluded, these same groups must help drive the clean-energy transition, and women, who stand to bear enormous burdens as the world warms, should be central to the effort. This means “practicing vigilant inclusion,” said Granholm.

    The C3E symposium, which is dedicated to celebrating the leadership of women in the field of clean energy and inspiring the next generation of women leaders, featured professionals from government, industry, research, and other sectors. Some of them spoke from experience, and from the heart, on issues of environmental justice.

    “I grew up in a trailer park in northern Utah, where it was so cold at night a sheet of ice formed on the inside of the door,” said Melanie Santiago-Mosier, the deputy director of the Clean Energy Group and Clean Energy States Alliance. Santiago-Mosier, who won a 2018 C3E award for advocacy, has devoted her career “to bringing the benefits of clean energy to families like mine, and to preventing mistakes of the past that result in a deeply unjust energy system.”

    Tracey A. LeBeau, a member of the Cheyenne River Sioux Tribe who grew up in South Dakota, described the flooding of her community’s land to create a hydroelectric dam, forcing the dislocation of many people. Today, as administrator and CEO of the Western Area Power Administration, LeBeau manages distribution of hydropower across 15 states, and has built an organization in which the needs of disadvantaged communities are top of mind. “I stay true to my indigenous point of view,” she said.

    The C3E Symposium was launched in 2012 to increase gender diversity in the energy sector and provide awards to outstanding women in the field. It is part of the C3E Initiative, a collaboration between the U.S. Department of Energy (DOE), the MIT Energy Initiative (MITEI), Texas A&M Energy Institute, and Stanford Precourt Institute for Energy, which hosted the event this year.

    Connecting global rich and poor

    As the COP26 climate summit unfolded in Glasgow, highlighting the sharp divide between rich and poor nations, C3E panelists pursued a related agenda. One panel focused on paths for collaboration between industrialized nations and nations with developing economies to build a sustainable, carbon-neutral global economy.

    Radhika Thakkar, the vice president of corporate affairs at solar home energy provider Greenlight Planet and a 2019 C3E international award winner, believes that small partnerships with women at the community level can lead to large impacts. When her company introduced solar lamp home systems to Rwanda, “Women abandoned selling bananas to sell our lamps, making enough money to purchase land, cows, even putting their families through school,” she said.

    Sudeshna Banerjee, the practice manager for Europe and Central Asia and the energy and extractives global practice at the World Bank, talked about impacts of a bank-supported electrification program in Nairobi slums where gang warfare kept girls confined at home. “Once the lights came on, girls felt more empowered to go around in dark hours,” she said. “This is what development is: creating opportunities for young women to do something with their lives, giving them educational opportunities and creating instances for them to generate income.”

    In another session, panelists focused on ways to enable disadvantaged communities in the United States to take full advantage of clean energy opportunities.

    Amy Glasmeier, a professor of economic geography and regional planning at MIT, believes remote, rural communities require broadband and other information channels in order to chart their own clean-energy journeys. “We must provide access to more than energy, so people can educate themselves and imagine how the energy transition can work for them.”

    Santiago-Mosier described the absence of rooftop solar in underprivileged neighborhoods of the nation’s cities and towns as the result of a kind of clean-energy redlining. “Clean energy and the solar industry are falling into 400-year-old traps of systemic racism,” she said. “This is no accident: senior executives in solar are white and male.” The answer is “making sure that providers and companies are elevating people of color and women in industries,” otherwise “solar is leaving potential growth on the table.”

    Data for equitable outcomes

    Jessica Granderson, the director of building technology at the White House Council on Environmental Quality and the 2015 C3E research award winner, is measuring and remediating greenhouse gas emissions from the nation’s hundred-million-plus homes and commercial structures. In a panel exploring data-driven solutions for advancing equitable energy outcomes, Granderson described using new building performance standards that improve the energy efficiency and material performance of construction in a way that does not burden building owners with modest resources. “We are emphasizing engagements at the community level, bringing in a local workforce, and addressing the needs of local programs, in a way that hasn’t necessarily been present in the past,” she said.

    To facilitate her studies on how people in these communities use and experience public transportation systems, Tierra Bills, an assistant professor in civil and environmental engineering at Wayne State University, is developing a community-based approach for collecting data. “Not everyone who is eager to contribute to a study can participate in an online survey and upload data, so we need to find ways of overcoming these barriers,” she said.

    Corporate efforts to advance social and environmental justice turn on community engagement as well. Paula Gold-Williams, a C3E ambassador and the president and CEO of CPS Energy, with 1 million customers in San Antonio, Texas, described a weatherization campaign to better insulate homes that involved “looking for as many places to go as possible in parts of town where people wouldn’t normally raise their hands.”

    Carla Peterman, the executive vice president for corporate affairs and chief of sustainability at Pacific Gas & Electric, and the 2015 C3E government award winner, was deliberating about raising rates some years ago. “My ‘aha’ moment was in a community workshop where I realized that a $5 increase is too much,” she said. “It may be the cost of a latte, but these folks aren’t buying lattes, and it’s a choice between electricity and food or shelter.”

    A call to arms

    Humanity cannot win the all-out race to achieve a zero-carbon future without a vast new cohort of participants, symposium speakers agreed. A number of the 2021 C3E award winners who have committed their careers to clean energy invoked the moral imperative of the moment and issued a call to arms.

    “Seven-hundred-and-fifty million people around the world live without reliable energy, and 70 percent of schools lack power,” said Rhonda Jordan-Antoine PhD ’12, a senior energy specialist at the World Bank who received this year’s international award. By laboring to bring smart grids, battery technologies, and regional integration to even the most remote communities, she said, we open up opportunities for education and jobs. “Energy access is not just about energy, but development,” said Antoine, “and I hope you are encouraged to advance clean energy efforts around the globe.”

    Faith Corneille, who won the government award, works in the U.S. Department of State’s Bureau of Energy Resources. “We need innovators and scientists to design solutions; energy efficiency experts and engineers to build; lawyers to review, and bankers to invest, and insurance agents to protect against risk; and we need problem-solvers to thread these together,” she said. “Whatever your path, there’s a role for you: energy and climate intersect with whatever you do.”

    “We know the cause of climate change and how to reverse it, but to make that happen we need passionate and brilliant minds, all pulling in the same direction,” said Megan Nutting, the executive vice president of government and regulatory affairs at Sunnova Energy Corporation, and winner of the business award. “The clean-energy transition needs women,” she said. “If you are not working in clean energy, then why not?” More