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      MIT expands research collaboration with Commonwealth Fusion Systems to build net energy fusion machine, SPARC

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      MIT’s Plasma Science and Fusion Center (PSFC) will substantially expand its fusion energy research and education activities under a new five-year agreement with Institute spinout Commonwealth Fusion Systems (CFS).

      “This expanded relationship puts MIT and PSFC in a prime position to be an even stronger academic leader that can help deliver the research and education needs of the burgeoning fusion energy industry, in part by utilizing the world’s first burning plasma and net energy fusion machine, SPARC,” says PSFC director Dennis Whyte. “CFS will build SPARC and develop a commercial fusion product, while MIT PSFC will focus on its core mission of cutting-edge research and education.”

      Commercial fusion energy has the potential to play a significant role in combating climate change, and there is a concurrent increase in interest from the energy sector, governments, and foundations. The new agreement, administered by the MIT Energy Initiative (MITEI), where CFS is a startup member, will help PSFC expand its fusion technology efforts with a wider variety of sponsors. The collaboration enables rapid execution at scale and technology transfer into the commercial sector as soon as possible.

      This new agreement doubles CFS’ financial commitment to PSFC, enabling greater recruitment and support of students, staff, and faculty. “We’ll significantly increase the number of graduate students and postdocs, and just as important they will be working on a more diverse set of fusion science and technology topics,” notes Whyte. It extends the collaboration between PSFC and CFS that resulted in numerous advances toward fusion power plants, including last fall’s demonstration of a high-temperature superconducting (HTS) fusion electromagnet with record-setting field strength of 20 tesla.

      The combined magnetic fusion efforts at PSFC will surpass those in place during the operations of the pioneering Alcator C-Mod tokamak device that operated from 1993 to 2016. This increase in activity reflects a moment when multiple fusion energy technologies are seeing rapidly accelerating development worldwide, and the emergence of a new fusion energy industry that would require thousands of trained people.

      MITEI director Robert Armstrong adds, “Our goal from the beginning was to create a membership model that would allow startups who have specific research challenges to leverage the MITEI ecosystem, including MIT faculty, students, and other MITEI members. The team at the PSFC and MITEI have worked seamlessly to support CFS, and we are excited for this next phase of the relationship.”

      PSFC is supporting CFS’ efforts toward realizing the SPARC fusion platform, which facilitates rapid development and refinement of elements (including HTS magnets) needed to build ARC, a compact, modular, high-field fusion power plant that would set the stage for commercial fusion energy production. The concepts originated in Whyte’s nuclear science and engineering class 22.63 (Principles of Fusion Engineering) and have been carried forward by students and PSFC staff, many of whom helped found CFS; the new activity will expand research into advanced technologies for the envisioned pilot plant.

      “This has been an incredibly effective collaboration that has resulted in a major breakthrough for commercial fusion with the successful demonstration of revolutionary fusion magnet technology that will enable the world’s first commercially relevant net energy fusion device, SPARC, currently under construction,” says Bob Mumgaard SM ’15, PhD ’15, CEO of Commonwealth Fusion Systems. “We look forward to this next phase in the collaboration with MIT as we tackle the critical research challenges ahead for the next steps toward fusion power plant development.”

      In the push for commercial fusion energy, the next five years are critical, requiring intensive work on materials longevity, heat transfer, fuel recycling, maintenance, and other crucial aspects of power plant development. It will need innovation from almost every engineering discipline. “Having great teams working now, it will cut the time needed to move from SPARC to ARC, and really unleash the creativity. And the thing MIT does so well is cut across disciplines,” says Whyte.

      “To address the climate crisis, the world needs to deploy existing clean energy solutions as widely and as quickly as possible, while at the same time developing new technologies — and our goal is that those new technologies will include fusion power,” says Maria T. Zuber, MIT’s vice president for research. “To make new climate solutions a reality, we need focused, sustained collaborations like the one between MIT and Commonwealth Fusion Systems. Delivering fusion power onto the grid is a monumental challenge, and the combined capabilities of these two organizations are what the challenge demands.”

      On a strategic level, climate change and the imperative need for widely implementable carbon-free energy have helped orient the PSFC team toward scalability. “Building one or 10 fusion plants doesn’t make a difference — we have to build thousands,” says Whyte. “The design decisions we make will impact the ability to do that down the road. The real enemy here is time, and we want to remove as many impediments as possible and commit to funding a new generation of scientific leaders. Those are critically important in a field with as much interdisciplinary integration as fusion.” More

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      Absent legislative victory, the president can still meet US climate goals

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      The most recent United Nations climate change report indicates that without significant action to mitigate global warming, the extent and magnitude of climate impacts — from floods to droughts to the spread of disease — could outpace the world’s ability to adapt to them. The latest effort to introduce meaningful climate legislation in the United States Congress, the Build Back Better bill, has stalled. The climate package in that bill — $555 billion in funding for climate resilience and clean energy — aims to reduce U.S. greenhouse gas emissions by about 50 percent below 2005 levels by 2030, the nation’s current Paris Agreement pledge. With prospects of passing a standalone climate package in the Senate far from assured, is there another pathway to fulfilling that pledge?

      Recent detailed legal analysis shows that there is at least one viable option for the United States to achieve the 2030 target without legislative action. Under Section 115 on International Air Pollution of the Clean Air Act, the U.S. Environmental Protection Agency (EPA) could assign emissions targets to the states that collectively meet the national goal. The president could simply issue an executive order to empower the EPA to do just that. But would that be prudent?

      A new study led by researchers at the MIT Joint Program on the Science and Policy of Global Change explores how, under a federally coordinated carbon dioxide emissions cap-and-trade program aligned with the U.S. Paris Agreement pledge and implemented through Section 115 of the Clean Air Act, the EPA might allocate emissions cuts among states. Recognizing that the Biden or any future administration considering this strategy would need to carefully weigh its benefits against its potential political risks, the study highlights the policy’s net economic benefits to the nation.

      The researchers calculate those net benefits by combining the estimated total cost of carbon dioxide emissions reduction under the policy with the corresponding estimated expenditures that would be avoided as a result of the policy’s implementation — expenditures on health care due to particulate air pollution, and on society at large due to climate impacts.

      Assessing three carbon dioxide emissions allocation strategies (each with legal precedent) for implementing Section 115 to return cap-and-trade program revenue to the states and distribute it to state residents on an equal per-capita basis, the study finds that at the national level, the economic net benefits are substantial, ranging from $70 to $150 billion in 2030. The results appear in the journal Environmental Research Letters.

      “Our findings not only show significant net gains to the U.S. economy under a national emissions policy implemented through the Clean Air Act’s Section 115,” says Mei Yuan, a research scientist at the MIT Joint Program and lead author of the study. “They also show the policy impact on consumer costs may differ across states depending on the choice of allocation strategy.”

      The national price on carbon needed to achieve the policy’s emissions target, as well as the policy’s ultimate cost to consumers, are substantially lower than those found in studies a decade earlier, although in line with other recent studies. The researchers speculate that this is largely due to ongoing expansion of ambitious state policies in the electricity sector and declining renewable energy costs. The policy is also progressive, consistent with earlier studies, in that equal lump-sum distribution of allowance revenue to state residents generally leads to net benefits to lower-income households. Regional disparities in consumer costs can be moderated by the allocation of allowances among states.

      State-by-state emissions estimates for the study are derived from MIT’s U.S. Regional Energy Policy model, with electricity sector detail of the Renewable Energy Development System model developed by the U.S. National Renewable Energy Laboratory; air quality benefits are estimated using U.S. EPA and other models; and the climate benefits estimate is based on the social cost of carbon, the U.S. federal government’s assessment of the economic damages that would result from emitting one additional ton of carbon dioxide into the atmosphere (currently $51/ton, adjusted for inflation). 

      “In addition to illustrating the economic, health, and climate benefits of a Section 115 implementation, our study underscores the advantages of a policy that imposes a uniform carbon price across all economic sectors,” says John Reilly, former co-director of the MIT Joint Program and a study co-author. “A national carbon price would serve as a major incentive for all sectors to decarbonize.” More

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      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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      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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      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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      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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      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