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      in Environment

      Surface coating designed to improve power plant efficiency wins 2022 Water Innovation Prize

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      The winner of this year’s Water Innovation Prize is a company commercializing a material that could dramatically improve the efficiency of power plants.

      The company, Mesophase, is developing a more efficient power plant steam condenser that leverages a surface coating developed in the lab of Evelyn Wang, MIT’s Ford Professor of Engineering and the head of the Department of Mechanical Engineering. Such condensers, which convert steam into water, sit at the heart of the energy extraction process in most of the world’s power plants.

      In the winning pitch, company founders said they believe their low-cost, durable coating will improve the heat transfer performance of such condensers.

      “What makes us excited about this technology is that in the condenser field, this is the first time we’ve seen a coating that can last long enough for industrial applications and be made with a high potential to scale up,” said Yajing Zhao SM ’18, who is currently a PhD candidate in mechanical engineering at MIT. “When compared to what’s available in academia and industry, we believe you’ll see record performance in terms of both heat transfer and lifetime.”

      In most power plants, condensers cool steam to turn it into water. The pressure change caused by that conversion creates a vacuum that pulls steam through a turbine. Mesophase’s patent-pending surface coating improves condensers’ ability to transfer heat, thus allowing operators to extract power more efficiently.

      Based on lab tests, the company predicts it can increase power plant output by up to 7 percent using existing infrastructure. Because steam condensers are used around the world, this advance could help increase global electricity production by 500 terawatt hours per year, which is equivalent to the electricity supply for about 1 billion people.

      The efficiency gains will also lead to less water use. Water sent from cooling towers is a common means of keeping condensers cool. The company estimates its system could reduce fresh water withdrawals by the equivalent of what is used by 50 million people per year.

      After running pilots, the company believes the new material could be installed in power plants during the regularly scheduled maintenance that occurs every two to five years. The company is also planning to work with existing condenser manufacturers to get to market faster.

      “This all works because a condenser with our technology in it has significantly more attractive economics than what you find in the market today,” says Mesophase’s Michael Gangemi, an MBA candidate at MIT’s Sloan School of Management.

      The company plans to start in the U.S. geothermal space, where Mesophase estimates its technology is worth about $800 million a year.

      “Much of the geothermal capacity in the U.S. was built in the ’50s and ’60s,” Gangemi said. “That means most of these plants are operating way below capacity, and they invest frequently in technology like ours just to maintain their power output.”

      The company will use the prize money, in part, to begin testing in a real power plant environment.

      “We are excited about these developments, but we know that they are only first steps as we move toward broader energy applications,” Gangemi said.

      MIT’s Water Innovation Prize helps translate water-related research and ideas into businesses and impact. Each year, student-led finalist teams pitch their innovations to students, faculty, investors, and people working in various water-related industries.

      This year’s event, held in a virtual hybrid format in MIT’s Media Lab, included five finalist teams. The second-place $15,000 award was given to Livingwater Systems, which provides portable rainwater collection and filtration systems to displaced and off-grid communities.

      The company’s product consists of a low-cost mesh that goes on roofs to collect the water and a collapsible storage unit that incorporates a sediment filter. The water becomes drinkable after applying chlorine tablets to the storage unit.

      “Perhaps the single greatest attraction of our units is their elegance and simplicity,” Livingwater CEO Joshua Kao said in the company’s pitch. “Anyone can take advantage of their easy, do-it-yourself setup without any preexisting knowhow.”

      The company says the system works on the pitched roofs used in many off-grid settlements, refugee camps, and slums. The entire unit fits inside a backpack.

      The team also notes existing collection systems cost thousands of dollars, require expert installation, and can’t be attached to surfaces like tents. Livingwater is aiming to partner with nongovernmental organizations and nonprofit entities to sell its systems for $60 each, which would represent significant cost savings when compared to alternatives like busing water into settlements.

      The company will be running a paid pilot with the World Food Program this fall.

      “Support from MIT will be crucial for building the core team on the ground,” said Livingwater’s Gabriela Saade, a master’s student in public policy at the University of Chicago. “Let’s begin to realize a new era of water security in Latin America and across the globe.”

      The third-place $10,000 prize went to Algeon Materials, which is creating sustainable and environmentally friendly bioplastics from kelp. Algeon also won the $5,000 audience choice award for its system, which doesn’t require water, fertilizer, or land to produce.

      The other finalists were:

      Flowless, which uses artificial intelligence and an internet of things (IoT) platform to detect leaks and optimize water-related processes to reduce waste;
      Hydrologistics Africa Ltd, a platform to help consumers and utilities manage their water consumption; and
      Watabot, which is developing autonomous, artificial intelligence-powered systems to monitor harmful algae in real time and predict algae activity.

      Each year the Water Innovation Prize, hosted by the MIT Water Club, awards up to $50,000 in grants to teams from around the world. This year’s program received over 50 applications. A group of 20 semifinalist teams spent one month working with mentors to refine their pitches and business plans, and the final field of finalists received another month of mentorship.

      The Water Innovation Prize started in 2015 and has awarded more than $275,000 to 24 different teams to date. More

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      in Energy

      How can we reduce the carbon footprint of global computing?

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      The voracious appetite for energy from the world’s computers and communications technology presents a clear threat for the globe’s warming climate. That was the blunt assessment from presenters in the intensive two-day Climate Implications of Computing and Communications workshop held on March 3 and 4, hosted by MIT’s Climate and Sustainability Consortium (MCSC), MIT-IBM Watson AI Lab, and the Schwarzman College of Computing.

      The virtual event featured rich discussions and highlighted opportunities for collaboration among an interdisciplinary group of MIT faculty and researchers and industry leaders across multiple sectors — underscoring the power of academia and industry coming together.

      “If we continue with the existing trajectory of compute energy, by 2040, we are supposed to hit the world’s energy production capacity. The increase in compute energy and demand has been increasing at a much faster rate than the world energy production capacity increase,” said Bilge Yildiz, the Breene M. Kerr Professor in the MIT departments of Nuclear Science and Engineering and Materials Science and Engineering, one of the workshop’s 18 presenters. This computing energy projection draws from the Semiconductor Research Corporations’s decadal report.To cite just one example: Information and communications technology already account for more than 2 percent of global energy demand, which is on a par with the aviation industries emissions from fuel.“We are the very beginning of this data-driven world. We really need to start thinking about this and act now,” said presenter Evgeni Gousev, senior director at Qualcomm.  Innovative energy-efficiency optionsTo that end, the workshop presentations explored a host of energy-efficiency options, including specialized chip design, data center architecture, better algorithms, hardware modifications, and changes in consumer behavior. Industry leaders from AMD, Ericsson, Google, IBM, iRobot, NVIDIA, Qualcomm, Tertill, Texas Instruments, and Verizon outlined their companies’ energy-saving programs, while experts from across MIT provided insight into current research that could yield more efficient computing.Panel topics ranged from “Custom hardware for efficient computing” to “Hardware for new architectures” to “Algorithms for efficient computing,” among others.

      Visual representation of the conversation during the workshop session entitled “Energy Efficient Systems.”

      Image: Haley McDevitt

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      The goal, said Yildiz, is to improve energy efficiency associated with computing by more than a million-fold.“I think part of the answer of how we make computing much more sustainable has to do with specialized architectures that have very high level of utilization,” said Darío Gil, IBM senior vice president and director of research, who stressed that solutions should be as “elegant” as possible.  For example, Gil illustrated an innovative chip design that uses vertical stacking to reduce the distance data has to travel, and thus reduces energy consumption. Surprisingly, more effective use of tape — a traditional medium for primary data storage — combined with specialized hard drives (HDD), can yield a dramatic savings in carbon dioxide emissions.Gil and presenters Bill Dally, chief scientist and senior vice president of research of NVIDIA; Ahmad Bahai, CTO of Texas Instruments; and others zeroed in on storage. Gil compared data to a floating iceberg in which we can have fast access to the “hot data” of the smaller visible part while the “cold data,” the large underwater mass, represents data that tolerates higher latency. Think about digital photo storage, Gil said. “Honestly, are you really retrieving all of those photographs on a continuous basis?” Storage systems should provide an optimized mix of of HDD for hot data and tape for cold data based on data access patterns.Bahai stressed the significant energy saving gained from segmenting standby and full processing. “We need to learn how to do nothing better,” he said. Dally spoke of mimicking the way our brain wakes up from a deep sleep, “We can wake [computers] up much faster, so we don’t need to keep them running in full speed.”Several workshop presenters spoke of a focus on “sparsity,” a matrix in which most of the elements are zero, as a way to improve efficiency in neural networks. Or as Dally said, “Never put off till tomorrow, where you could put off forever,” explaining efficiency is not “getting the most information with the fewest bits. It’s doing the most with the least energy.”Holistic and multidisciplinary approaches“We need both efficient algorithms and efficient hardware, and sometimes we need to co-design both the algorithm and the hardware for efficient computing,” said Song Han, a panel moderator and assistant professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT.Some presenters were optimistic about innovations already underway. According to Ericsson’s research, as much as 15 percent of the carbon emissions globally can be reduced through the use of existing solutions, noted Mats Pellbäck Scharp, head of sustainability at Ericsson. For example, GPUs are more efficient than CPUs for AI, and the progression from 3G to 5G networks boosts energy savings.“5G is the most energy efficient standard ever,” said Scharp. “We can build 5G without increasing energy consumption.”Companies such as Google are optimizing energy use at their data centers through improved design, technology, and renewable energy. “Five of our data centers around the globe are operating near or above 90 percent carbon-free energy,” said Jeff Dean, Google’s senior fellow and senior vice president of Google Research.Yet, pointing to the possible slowdown in the doubling of transistors in an integrated circuit — or Moore’s Law — “We need new approaches to meet this compute demand,” said Sam Naffziger, AMD senior vice president, corporate fellow, and product technology architect. Naffziger spoke of addressing performance “overkill.” For example, “we’re finding in the gaming and machine learning space we can make use of lower-precision math to deliver an image that looks just as good with 16-bit computations as with 32-bit computations, and instead of legacy 32b math to train AI networks, we can use lower-energy 8b or 16b computations.”

      Visual representation of the conversation during the workshop session entitled “Wireless, networked, and distributed systems.”

      Image: Haley McDevitt

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      Other presenters singled out compute at the edge as a prime energy hog.“We also have to change the devices that are put in our customers’ hands,” said Heidi Hemmer, senior vice president of engineering at Verizon. As we think about how we use energy, it is common to jump to data centers — but it really starts at the device itself, and the energy that the devices use. Then, we can think about home web routers, distributed networks, the data centers, and the hubs. “The devices are actually the least energy-efficient out of that,” concluded Hemmer.Some presenters had different perspectives. Several called for developing dedicated silicon chipsets for efficiency. However, panel moderator Muriel Medard, the Cecil H. Green Professor in EECS, described research at MIT, Boston University, and Maynooth University on the GRAND (Guessing Random Additive Noise Decoding) chip, saying, “rather than having obsolescence of chips as the new codes come in and in different standards, you can use one chip for all codes.”Whatever the chip or new algorithm, Helen Greiner, CEO of Tertill (a weeding robot) and co-founder of iRobot, emphasized that to get products to market, “We have to learn to go away from wanting to get the absolute latest and greatest, the most advanced processor that usually is more expensive.” She added, “I like to say robot demos are a dime a dozen, but robot products are very infrequent.”Greiner emphasized consumers can play a role in pushing for more energy-efficient products — just as drivers began to demand electric cars.Dean also sees an environmental role for the end user.“We have enabled our cloud customers to select which cloud region they want to run their computation in, and they can decide how important it is that they have a low carbon footprint,” he said, also citing other interfaces that might allow consumers to decide which air flights are more efficient or what impact installing a solar panel on their home would have.However, Scharp said, “Prolonging the life of your smartphone or tablet is really the best climate action you can do if you want to reduce your digital carbon footprint.”Facing increasing demandsDespite their optimism, the presenters acknowledged the world faces increasing compute demand from machine learning, AI, gaming, and especially, blockchain. Panel moderator Vivienne Sze, associate professor in EECS, noted the conundrum.“We can do a great job in making computing and communication really efficient. But there is this tendency that once things are very efficient, people use more of it, and this might result in an overall increase in the usage of these technologies, which will then increase our overall carbon footprint,” Sze said.Presenters saw great potential in academic/industry partnerships, particularly from research efforts on the academic side. “By combining these two forces together, you can really amplify the impact,” concluded Gousev.Presenters at the Climate Implications of Computing and Communications workshop also included: Joel Emer, professor of the practice in EECS at MIT; David Perreault, the Joseph F. and Nancy P. Keithley Professor of EECS at MIT; Jesús del Alamo, MIT Donner Professor and professor of electrical engineering in EECS at MIT; Heike Riel, IBM Fellow and head science and technology at IBM; and Takashi Ando, principal research staff member at IBM Research. The recorded workshop sessions are available on YouTube. More

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      in Energy

      Machine learning, harnessed to extreme computing, aids fusion energy development

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      MIT research scientists Pablo Rodriguez-Fernandez and Nathan Howard have just completed one of the most demanding calculations in fusion science — predicting the temperature and density profiles of a magnetically confined plasma via first-principles simulation of plasma turbulence. Solving this problem by brute force is beyond the capabilities of even the most advanced supercomputers. Instead, the researchers used an optimization methodology developed for machine learning to dramatically reduce the CPU time required while maintaining the accuracy of the solution.

      Fusion energyFusion offers the promise of unlimited, carbon-free energy through the same physical process that powers the sun and the stars. It requires heating the fuel to temperatures above 100 million degrees, well above the point where the electrons are stripped from their atoms, creating a form of matter called plasma. On Earth, researchers use strong magnetic fields to isolate and insulate the hot plasma from ordinary matter. The stronger the magnetic field, the better the quality of the insulation that it provides.

      Rodriguez-Fernandez and Howard have focused on predicting the performance expected in the SPARC device, a compact, high-magnetic-field fusion experiment, currently under construction by the MIT spin-out company Commonwealth Fusion Systems (CFS) and researchers from MIT’s Plasma Science and Fusion Center. While the calculation required an extraordinary amount of computer time, over 8 million CPU-hours, what was remarkable was not how much time was used, but how little, given the daunting computational challenge.

      The computational challenge of fusion energyTurbulence, which is the mechanism for most of the heat loss in a confined plasma, is one of the science’s grand challenges and the greatest problem remaining in classical physics. The equations that govern fusion plasmas are well known, but analytic solutions are not possible in the regimes of interest, where nonlinearities are important and solutions encompass an enormous range of spatial and temporal scales. Scientists resort to solving the equations by numerical simulation on computers. It is no accident that fusion researchers have been pioneers in computational physics for the last 50 years.

      One of the fundamental problems for researchers is reliably predicting plasma temperature and density given only the magnetic field configuration and the externally applied input power. In confinement devices like SPARC, the external power and the heat input from the fusion process are lost through turbulence in the plasma. The turbulence itself is driven by the difference in the extremely high temperature of the plasma core and the relatively cool temperatures of the plasma edge (merely a few million degrees). Predicting the performance of a self-heated fusion plasma therefore requires a calculation of the power balance between the fusion power input and the losses due to turbulence.

      These calculations generally start by assuming plasma temperature and density profiles at a particular location, then computing the heat transported locally by turbulence. However, a useful prediction requires a self-consistent calculation of the profiles across the entire plasma, which includes both the heat input and turbulent losses. Directly solving this problem is beyond the capabilities of any existing computer, so researchers have developed an approach that stitches the profiles together from a series of demanding but tractable local calculations. This method works, but since the heat and particle fluxes depend on multiple parameters, the calculations can be very slow to converge.

      However, techniques emerging from the field of machine learning are well suited to optimize just such a calculation. Starting with a set of computationally intensive local calculations run with the full-physics, first-principles CGYRO code (provided by a team from General Atomics led by Jeff Candy) Rodriguez-Fernandez and Howard fit a surrogate mathematical model, which was used to explore and optimize a search within the parameter space. The results of the optimization were compared to the exact calculations at each optimum point, and the system was iterated to a desired level of accuracy. The researchers estimate that the technique reduced the number of runs of the CGYRO code by a factor of four.

      New approach increases confidence in predictionsThis work, described in a recent publication in the journal Nuclear Fusion, is the highest fidelity calculation ever made of the core of a fusion plasma. It refines and confirms predictions made with less demanding models. Professor Jonathan Citrin, of the Eindhoven University of Technology and leader of the fusion modeling group for DIFFER, the Dutch Institute for Fundamental Energy Research, commented: “The work significantly accelerates our capabilities in more routinely performing ultra-high-fidelity tokamak scenario prediction. This algorithm can help provide the ultimate validation test of machine design or scenario optimization carried out with faster, more reduced modeling, greatly increasing our confidence in the outcomes.” 

      In addition to increasing confidence in the fusion performance of the SPARC experiment, this technique provides a roadmap to check and calibrate reduced physics models, which run with a small fraction of the computational power. Such models, cross-checked against the results generated from turbulence simulations, will provide a reliable prediction before each SPARC discharge, helping to guide experimental campaigns and improving the scientific exploitation of the device. It can also be used to tweak and improve even simple data-driven models, which run extremely quickly, allowing researchers to sift through enormous parameter ranges to narrow down possible experiments or possible future machines.

      The research was funded by CFS, with computational support from the National Energy Research Scientific Computing Center, a U.S. Department of Energy Office of Science User Facility. More

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      in Energy

      Using excess heat to improve electrolyzers and fuel cells

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      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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      in Energy

      What choices does the world need to make to keep global warming below 2 C?

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      When the 2015 Paris Agreement set a long-term goal of keeping global warming “well below 2 degrees Celsius, compared to pre-industrial levels” to avoid the worst impacts of climate change, it did not specify how its nearly 200 signatory nations could collectively achieve that goal. Each nation was left to its own devices to reduce greenhouse gas emissions in alignment with the 2 C target. Now a new modeling strategy developed at the MIT Joint Program on the Science and Policy of Global Change that explores hundreds of potential future development pathways provides new insights on the energy and technology choices needed for the world to meet that target.

      Described in a study appearing in the journal Earth’s Future, the new strategy combines two well-known computer modeling techniques to scope out the energy and technology choices needed over the coming decades to reduce emissions sufficiently to achieve the Paris goal.

      The first technique, Monte Carlo analysis, quantifies uncertainty levels for dozens of energy and economic indicators including fossil fuel availability, advanced energy technology costs, and population and economic growth; feeds that information into a multi-region, multi-economic-sector model of the world economy that captures the cross-sectoral impacts of energy transitions; and runs that model hundreds of times to estimate the likelihood of different outcomes. The MIT study focuses on projections through the year 2100 of economic growth and emissions for different sectors of the global economy, as well as energy and technology use.

      The second technique, scenario discovery, uses machine learning tools to screen databases of model simulations in order to identify outcomes of interest and their conditions for occurring. The MIT study applies these tools in a unique way by combining them with the Monte Carlo analysis to explore how different outcomes are related to one another (e.g., do low-emission outcomes necessarily involve large shares of renewable electricity?). This approach can also identify individual scenarios, out of the hundreds explored, that result in specific combinations of outcomes of interest (e.g., scenarios with low emissions, high GDP growth, and limited impact on electricity prices), and also provide insight into the conditions needed for that combination of outcomes.

      Using this unique approach, the MIT Joint Program researchers find several possible patterns of energy and technology development under a specified long-term climate target or economic outcome.

      “This approach shows that there are many pathways to a successful energy transition that can be a win-win for the environment and economy,” says Jennifer Morris, an MIT Joint Program research scientist and the study’s lead author. “Toward that end, it can be used to guide decision-makers in government and industry to make sound energy and technology choices and avoid biases in perceptions of what ’needs’ to happen to achieve certain outcomes.”

      For example, while achieving the 2 C goal, the global level of combined wind and solar electricity generation by 2050 could be less than three times or more than 12 times the current level (which is just over 2,000 terawatt hours). These are very different energy pathways, but both can be consistent with the 2 C goal. Similarly, there are many different energy mixes that can be consistent with maintaining high GDP growth in the United States while also achieving the 2 C goal, with different possible roles for renewables, natural gas, carbon capture and storage, and bioenergy. The study finds renewables to be the most robust electricity investment option, with sizable growth projected under each of the long-term temperature targets explored.

      The researchers also find that long-term climate targets have little impact on economic output for most economic sectors through 2050, but do require each sector to significantly accelerate reduction of its greenhouse gas emissions intensity (emissions per unit of economic output) so as to reach near-zero levels by midcentury.

      “Given the range of development pathways that can be consistent with meeting a 2 degrees C goal, policies that target only specific sectors or technologies can unnecessarily narrow the solution space, leading to higher costs,” says former MIT Joint Program Co-Director John Reilly, a co-author of the study. “Our findings suggest that policies designed to encourage a portfolio of technologies and sectoral actions can be a wise strategy that hedges against risks.”

      The research was supported by the U.S. Department of Energy Office of Science. More

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      in Energy

      At Climate Grand Challenges showcase event, an exploration of how to accelerate breakthrough solutions

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      On the eve of Earth Day, more than 300 faculty, researchers, students, government officials, and industry leaders gathered in the Samberg Conference Center, along with thousands more who tuned in online, to celebrate MIT’s first-ever Climate Grand Challenges and the five most promising concepts to emerge from the two-year competition.

      The event began with a climate policy conversation between MIT President L. Rafael Reif and Special Presidential Envoy for Climate John Kerry, followed by presentations from each of the winning flagship teams, and concluded with an expert panel that explored pathways for moving from ideas to impact at scale as quickly as possible.

      “In 2020, when we launched the Climate Grand Challenges, we wanted to focus the daring creativity and pioneering expertise of the MIT community on the urgent problem of climate change,” said President Reif in kicking off the event. “Together these flagship projects will define a transformative new research agenda at MIT, one that has the potential to make meaningful contributions to the global climate response.”

      Reif and Kerry discussed multiple aspects of the climate crisis, including mitigation, adaptation, and the policies and strategies that can help the world avert the worst consequences of climate change and make the United States a leader again in bringing technology into commercial use. Referring to the accelerated wartime research effort that helped turn the tide in World War II, which included work conducted at MIT, Kerry said, “We need about five Manhattan Projects, frankly.”

      “People are now sensing a much greater urgency to finding solutions — new technology — and taking to scale some of the old technologies,” Kerry said. “There are things that are happening that I think are exciting, but the problem is it’s not happening fast enough.”

      Strategies for taking technology from the lab to the marketplace were the basis for the final portion of the event. The panel was moderated by Alicia Barton, president and CEO of FirstLight Power, and included Manish Bapna, president and CEO of the Natural Resources Defense Council; Jack Little, CEO and co-founder of MathWorks; Arati Prabhakar, president of Actuate and former head of the Defense Advanced Research Projects Agency; and Katie Rae, president and managing director of The Engine. The discussion touched upon the importance of marshaling the necessary resources and building the cross-sector partnerships required to scale the technologies being developed by the flagship teams and to deliver them to the world in time to make a difference. 

      “MIT doesn’t sit on its hands ever, and innovation is central to its founding,” said Rae. “The students coming out of MIT at every level, along with the professors, have been committed to these challenges for a long time and therefore will have a big impact. These flagships have always been in process, but now we have an extraordinary moment to commercialize these projects.”

      The panelists weighed in on how to change the mindset around finance, policy, business, and community adoption to scale massive shifts in energy generation, transportation, and other major carbon-emitting industries. They stressed the importance of policies that address the economic, equity, and public health impacts of climate change and of reimagining supply chains and manufacturing to grow and distribute these technologies quickly and affordably. 

      “We are embarking on five adventures, but we do not know yet, cannot know yet, where these projects will take us,” said Maria Zuber, MIT’s vice president for research. “These are powerful and promising ideas. But each one will require focused effort, creative and interdisciplinary teamwork, and sustained commitment and support if they are to become part of the climate and energy revolution that the world urgently needs. This work begins now.” 

      Zuber called for investment from philanthropists and financiers, and urged companies, governments, and others to join this all-of-humanity effort. Associate Provost for International Activities Richard Lester echoed this message in closing the event. 

      “Every one of us needs to put our shoulder to the wheel at the points where our leverage is maximized — where we can do what we’re best at,” Lester said. “For MIT, Climate Grand Challenges is one of those maximum leverage points.” More

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      in Energy

      Developing electricity-powered, low-emissions alternatives to carbon-intensive industrial processes

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      On April 11, 2022, MIT announced five multiyear flagship projects in the first-ever Climate Grand Challenges, a new initiative to tackle complex climate problems and deliver breakthrough solutions to the world as quickly as possible. This is the second article in a five-part series highlighting the most promising concepts to emerge from the competition, and the interdisciplinary research teams behind them.

      One of the biggest leaps that humankind could take to drastically lower greenhouse gas emissions globally would be the complete decarbonization of industry. But without finding low-cost, environmentally friendly substitutes for industrial materials, the traditional production of steel, cement, ammonia, and ethylene will continue pumping out billions of tons of carbon annually; these sectors alone are responsible for at least one third of society’s global greenhouse gas emissions. 

      A major problem is that industrial manufacturers, whose success depends on reliable, cost-efficient, and large-scale production methods, are too heavily invested in processes that have historically been powered by fossil fuels to quickly switch to new alternatives. It’s a machine that kicked on more than 100 years ago, and which MIT electrochemical engineer Yet-Ming Chiang says we can’t shut off without major disruptions to the world’s massive supply chain of these materials. What’s needed, Chiang says, is a broader, collaborative clean energy effort that takes “targeted fundamental research, all the way through to pilot demonstrations that greatly lowers the risk for adoption of new technology by industry.”

      This would be a new approach to decarbonization of industrial materials production that relies on largely unexplored but cleaner electrochemical processes. New production methods could be optimized and integrated into the industrial machine to make it run on low-cost, renewable electricity in place of fossil fuels. 

      Recognizing this, Chiang, the Kyocera Professor in the Department of Materials Science and Engineering, teamed with research collaborator Bilge Yildiz, the Breene M. Kerr Professor of Nuclear Science and Engineering and professor of materials science and engineering, with key input from Karthish Manthiram, visiting professor in the Department of Chemical Engineering, to submit a project proposal to the MIT Climate Grand Challenges. Their plan: to create an innovation hub on campus that would bring together MIT researchers individually investigating decarbonization of steel, cement, ammonia, and ethylene under one roof, combining research equipment and directly collaborating on new methods to produce these four key materials.

      Many researchers across MIT have already signed on to join the effort, including Antoine Allanore, associate professor of metallurgy, who specializes in the development of sustainable materials and manufacturing processes, and Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in the Department of Materials Science and Engineering, who is an expert in materials economics and sustainability. Other MIT faculty currently involved include Fikile Brushett, Betar Gallant, Ahmed Ghoniem, William Green, Jeffrey Grossman, Ju Li, Yuriy Román-Leshkov, Yang Shao-Horn, Robert Stoner, Yogesh Surendranath, Timothy Swager, and Kripa Varanasi.

      “The team we brought together has the expertise needed to tackle these challenges, including electrochemistry — using electricity to decarbonize these chemical processes — and materials science and engineering, process design and scale-up technoeconomic analysis, and system integration, which is all needed for this to go out from our labs to the field,” says Yildiz.

      Selected from a field of more than 100 proposals, their Center for Electrification and Decarbonization of Industry (CEDI) will be the first such institute worldwide dedicated to testing and scaling the most innovative and promising technologies in sustainable chemicals and materials. CEDI will work to facilitate rapid translation of lab discoveries into affordable, scalable industry solutions, with potential to offset as much as 15 percent of greenhouse gas emissions. The team estimates that some CEDI projects already underway could be commercialized within three years.

      “The real timeline is as soon as possible,” says Chiang.

      To achieve CEDI’s ambitious goals, a physical location is key, staffed with permanent faculty, as well as undergraduates, graduate students, and postdocs. Yildiz says the center’s success will depend on engaging student researchers to carry forward with research addressing the biggest ongoing challenges to decarbonization of industry.

      “We are training young scientists, students, on the learned urgency of the problem,” says Yildiz. “We empower them with the skills needed, and even if an individual project does not find the implementation in the field right away, at least, we would have trained the next generation that will continue to go after them in the field.”

      Chiang’s background in electrochemistry showed him how the efficiency of cement production could benefit from adopting clean electricity sources, and Yildiz’s work on ethylene, the source of plastic and one of industry’s most valued chemicals, has revealed overlooked cost benefits to switching to electrochemical processes with less expensive starting materials. With industry partners, they hope to continue these lines of fundamental research along with Allanore, who is focused on electrifying steel production, and Manthiram, who is developing new processes for ammonia. Olivetti will focus on understanding risks and barriers to implementation. This multilateral approach aims to speed up the timeline to industry adoption of new technologies at the scale needed for global impact.

      “One of the points of emphasis in this whole center is going to be applying technoeconomic analysis of what it takes to be successful at a technical and economic level, as early in the process as possible,” says Chiang.

      The impact of large-scale industry adoption of clean energy sources in these four key areas that CEDI plans to target first would be profound, as these sectors are currently responsible for 7.5 billion tons of emissions annually. There is the potential for even greater impact on emissions as new knowledge is applied to other industrial products beyond the initial four targets of steel, cement, ammonia, and ethylene. Meanwhile, the center will stand as a hub to attract new industry, government stakeholders, and research partners to collaborate on urgently needed solutions, both newly arising and long overdue.

      When Chiang and Yildiz first met to discuss ideas for MIT Climate Grand Challenges, they decided they wanted to build a climate research center that functioned unlike any other to help pivot large industry toward decarbonization. Beyond considering how new solutions will impact industry’s bottom line, CEDI will also investigate unique synergies that could arise from the electrification of industry, like processes that would create new byproducts that could be the feedstock to other industry processes, reducing waste and increasing efficiencies in the larger system. And because industry is so good at scaling, those added benefits would be widespread, finally replacing century-old technologies with critical updates designed to improve production and markedly reduce industry’s carbon footprint sooner rather than later.

      “Everything we do, we’re going to try to do with urgency,” Chiang says. “The fundamental research will be done with urgency, and the transition to commercialization, we’re going to do with urgency.” More

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      in Energy

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

      by

      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