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      in Energy

      Team creates map for production of eco-friendly metals

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      In work that could usher in more efficient, eco-friendly processes for producing important metals like lithium, iron, and cobalt, researchers from MIT and the SLAC National Accelerator Laboratory have mapped what is happening at the atomic level behind a particularly promising approach called metal electrolysis.

      By creating maps for a wide range of metals, they not only determined which metals should be easiest to produce using this approach, but also identified fundamental barriers behind the efficient production of others. As a result, the researchers’ map could become an important design tool for optimizing the production of all these metals.

      The work could also aid the development of metal-air batteries, cousins of the lithium-ion batteries used in today’s electric vehicles.

      Most of the metals key to society today are produced using fossil fuels. These fuels generate the high temperatures necessary to convert the original ore into its purified metal. But that process is a significant source of greenhouse gases — steel alone accounts for some 7 percent of carbon dioxide emissions globally. As a result, researchers from around the world are working to identify more eco-friendly ways for the production of metals.

      One promising approach is metal electrolysis, in which a metal oxide, the ore, is zapped with electricity to create pure metal with oxygen as the byproduct. That is the reaction explored at the atomic level in new research reported in the April 8 issue of the journal Chemistry of Materials.

      Donald Siegel is department chair and professor of mechanical engineering at the University of Texas at Austin. Says Siegel, who was not involved in the Chemistry of Materials study: “This work is an important contribution to improving the efficiency of metal production from metal oxides. It clarifies our understanding of low-carbon electrolysis processes by tracing the underlying thermodynamics back to elementary metal-oxygen interactions. I expect that this work will aid in the creation of design rules that will make these industrially important processes less reliant on fossil fuels.”

      Yang Shao-Horn, the JR East Professor of Engineering in MIT’s Department of Materials Science and Engineering (DMSE) and Department of Mechanical Engineering, is a leader of the current work, with Michal Bajdich of SLAC.

      “Here we aim to establish some basic understanding to predict the efficiency of electrochemical metal production and metal-air batteries from examining computed thermodynamic barriers for the conversion between metal and metal oxides,” says Shao-Horn, who is on the research team for MIT’s new Center for Electrification and Decarbonization of Industry, a winner of the Institute’s first-ever Climate Grand Challenges competition. Shao-Horn is also affiliated with MIT’s Materials Research Laboratory and Research Laboratory of Electronics.

      In addition to Shao-Horn and Bajdich, other authors of the Chemistry of Materials paper are Jaclyn R. Lunger, first author and a DMSE graduate student; mechanical engineering senior Naomi Lutz; and DMSE graduate student Jiayu Peng.

      Other applications

      The work could also aid in developing metal-air batteries such as lithium-air, aluminum-air, and zinc-air batteries. These cousins of the lithium-ion batteries used in today’s electric vehicles have the potential to electrify aviation because their energy densities are much higher. However, they are not yet on the market due to a variety of problems including inefficiency.

      Charging metal-air batteries also involves electrolysis. As a result, the new atomic-level understanding of these reactions could not only help engineers develop efficient electrochemical routes for metal production, but also design more efficient metal-air batteries.

      Learning from water splitting

      Electrolysis is also used to split water into oxygen and hydrogen, which stores the resulting energy. That hydrogen, in turn, could become an eco-friendly alternative to fossil fuels. Since much more is known about water electrolysis, the focus of Bajdich’s work at SLAC, than the electrolysis of metal oxides, the team compared the two processes for the first time.

      The result: “Slowly, we uncovered the elementary steps involved in metal electrolysis,” says Bajdich. The work was challenging, says Lunger, because “it was unclear to us what those steps are. We had to figure out how to get from A to B,” or from a metal oxide to metal and oxygen.

      All of the work was conducted with supercomputer simulations. “It’s like a sandbox of atoms, and then we play with them. It’s a little like Legos,” says Bajdich. More specifically, the team explored different scenarios for the electrolysis of several metals. Each involved different catalysts, molecules that boost the speed of a reaction.

      Says Lunger, “To optimize the reaction, you want to find the catalyst that makes it most efficient.” The team’s map is essentially a guide for designing the best catalysts for each different metal.

      What’s next? Lunger noted that the current work focused on the electrolysis of pure metals. “I’m interested in seeing what happens in more complex systems involving multiple metals. Can you make the reaction more efficient if there’s sodium and lithium present, or cadmium and cesium?”

      This work was supported by a U.S. Department of Energy Office of Science Graduate Student Research award. It was also supported by an MIT Energy Initiative fellowship, the Toyota Research Institute through the Accelerated Materials Design and Discovery Program, the Catalysis Science Program of Department of Energy, Office of Basic Energy Sciences, and by the Differentiate Program through the U.S. Advanced Research Projects Agency — Energy.  More

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      in Energy

      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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      in Energy

      Material 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

    • 163 Shares199 Views

      in Environment

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

      by

      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

      by

      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 Environment

      Five MIT PhD students awarded 2022 J-WAFS fellowships for water and food solutions

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      The Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) recently announced the selection of its 2022-23 cohort of graduate fellows. Two students were named Rasikbhai L. Meswani Fellows for Water Solutions and three students were named J-WAFS Graduate Student Fellows. All five fellows will receive full tuition and a stipend for one semester, and J-WAFS will support the students throughout the 2022-23 academic year by providing networking, mentorship, and opportunities to showcase their research.

      New this year, fellowship nominations were open not only to students pursuing water research, but food-related research as well. The five students selected were chosen for their commitment to solutions-based research that aims to alleviate problems such as water supply or purification, food security, or agriculture. Their projects exemplify the wide range of research that J-WAFS supports, from enhancing nutrition through improved methods to deliver micronutrients to developing high-performance drip irrigation technology. The strong applicant pool reflects the passion MIT students have to address the water and food crises currently facing the planet.

      “This year’s fellows are drawn from a dynamic and engaged community across the Institute whose creativity and ingenuity are pushing forward transformational water and food solutions,” says J-WAFS executive director Renee J. Robins. “We congratulate these students as we recognize their outstanding achievements and their promise as up-and-coming leaders in global water and food sectors.”

      2022-23 Rasikbhai L. Meswani Fellows for Water SolutionsThe Rasikbhai L. Meswani Fellowship for Water Solutions is a fellowship for students pursuing water-related research at MIT. The Rasikbhai L. Meswani Fellowship for Water Solutions was made possible by a generous gift from Elina and Nikhil Meswani and family.

      Aditya Ghodgaonkar is a PhD candidate in the Department of Mechanical Engineering at MIT, where he works in the Global Engineering and Research (GEAR) Lab under Professor Amos Winter. Ghodgaonkar received a bachelor’s degree in mechanical engineering from the RV College of Engineering in India. He then moved to the United States and received a master’s degree in mechanical engineering from Purdue University.Ghodgaonkar is currently designing hydraulic components for drip irrigation that could support the development of water-efficient irrigation systems that are off-grid, inexpensive, and low-maintenance. He has focused on designing drip irrigation emitters that are resistant to clogging, seeking inspiration about flow regulation from marine fauna such as manta rays, as well as turbomachinery concepts. Ghodgaonkar notes that clogging is currently an expensive technical challenge to diagnose, mitigate, and resolve. With an eye on hundreds of millions of farms in developing countries, he aims to bring the benefits of irrigation technology to even the poorest farmers.Outside of his research, Ghodgaonkar is a mentor in MIT Makerworks and has been a teaching assistant for classes such as 2.007 (Design and Manufacturing I). He also helped organize the annual MIT Water Summit last fall.

      Devashish Gokhale is a PhD candidate advised by Professor Patrick Doyle in the Department of Chemical Engineering. He received a bachelor’s degree in chemical engineering from the Indian Institute of Technology Madras, where he researched fluid flow in energy-efficient pumps. Gokhale’s commitment to global water security stemmed from his experience growing up in India, where water sources are threatened by population growth, industrialization, and climate change.As a researcher in the Doyle group, Devashish is developing sustainable and reusable materials for water treatment, with a focus on the elimination of emerging contaminants and other micropollutants from water through cost-effective processes. Many of these contaminants are carcinogens or endocrine disruptors, posing significant threats to both humans and animals. His advisor notes that Devashish was the first researcher in the Doyle group to work on water purification, bringing his passion for the topic to the lab.Gokhale’s research won an award for potential scalability in last year’s J-WAFS World Water Day competition. He also serves as the lecture series chair in the MIT Water Club.

      2022-23 J-WAFS Graduate Student FellowsThe J-WAFS Fellowship for Water and Food Solutions is funded by the J-WAFS Research Affiliate Program, which offers companies the opportunity to collaborate with MIT on water and food research. A portion of each research affiliate’s fees supports this fellowship. The program is central to J-WAFS’ efforts to engage across sector and disciplinary boundaries in solving real-world problems. Currently, there are two J-WAFS Research Affiliates: Xylem, Inc., a water technology company, and GoAigua, a company leading the digital transformation of the water industry.

      James Zhang is a PhD candidate in the Department of Mechanical Engineering at MIT, where he has worked in the NanoEngineering Laboratory with Professor Gang Chen since 2019. As an undergraduate at Carnegie Mellon University, he double majored in mechanical engineering and engineering public policy. He then received a master’s degree in mechanical engineering from MIT. In addition to working in the NanoEngineering Laboratory, James has also worked in the Zhao Laboratory and in the Boriskina Research Group at MIT.Zhang is developing a technology that uses light-induced evaporation to clean water. He is currently investigating the fundamental properties of how light interacts with brackish water surfaces. With strong theoretical as well as experimental components, his research could lead to innovations in desalinating brackish water at high energy efficiencies. Outside of his research, Zhang has served as a student moderator for the MIT International Colloquia on Thermal Innovations.

      Katharina Fransen is a PhD candidate advised by Professor Bradley Olsen in the Department of Chemical Engineering at MIT. She received a bachelor’s degree in chemical engineering from the University of Minnesota, where she was involved in the Society of Women Engineers. Fransen is motivated by the challenge of protecting the most vulnerable global communities from the large quantities of plastic waste associated with traditional food packaging materials. As a researcher in the Olsen Lab, Fransen is developing new plastics that are biologically-based and biodegradable, so they can degrade in the environment instead of polluting communities with plastic waste. These polymers are also optimized for food packaging applications to keep food fresher for longer, preventing food waste.Outside of her research, Fransen is involved in Diversity in Chemical Engineering as the coordinator for the graduate application mentorship program for underrepresented groups. She is also an active member of Graduate Womxn in ChemE and mentors an Undergraduate Research Opportunities Program student.

      Linzixuan (Rhoda) Zhang is a PhD candidate advised by Professor Robert Langer and Ana Jaklenec in the Department of Chemical Engineering at MIT. She received a bachelor’s degree in chemical engineering from the University of Illinois at Urbana-Champaign, where she researched how to genetically engineer microorganisms for the efficient production of advanced biofuels and chemicals.Zhang is currently developing a micronutrient delivery platform that fortifies foods with essential vitamins and nutrients. She has helped develop a group of biodegradable polymers that can stabilize micronutrients under harsh conditions, enabling local food companies to fortify food with essential vitamins. This work aims to tackle a hidden crisis in low- and middle-income countries, where a chronic lack of essential micronutrients affects an estimated 2 billion people.Zhang is also working on the development of self-boosting vaccines to promote more widespread vaccine access and serves as a research mentor in the Langer Lab. 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