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      in Environment

      Students dive into research with the MIT Climate and Sustainability Consortium

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      Throughout the fall 2021 semester, the MIT Climate and Sustainability Consortium (MCSC) supported several research projects with a climate-and-sustainability topic related to the consortium, through the MIT Undergraduate Research Opportunities Program (UROP). These students, who represent a range of disciplines, had the opportunity to work with MCSC Impact Fellows on topics related directly to the ongoing work and collaborations with MCSC member companies and the broader MIT community, from carbon capture to value-chain resilience to biodegradables. Many of these students are continuing their work this spring semester.

      Hannah Spilman, who is studying chemical engineering, worked with postdoc Glen Junor, an MCSC Impact Fellow, to investigate carbon capture, utilization, and storage (CCUS), with the goal of facilitating CCUS on a gigaton scale, a much larger capacity than what currently exists. “Scientists agree CCUS will be an important tool in combating climate change, but the largest CCUS facility only captures CO2 on a megaton scale, and very few facilities are actually operating,” explains Spilman. 

      Throughout her UROP, she worked on analyzing the currently deployed technology in the CCUS field, using National Carbon Capture Center post-combustion project reports to synthesize the results and outline those technologies. Examining projects like the RTI-NAS experiment, which showcased innovation with carbon capture technology, was especially helpful. “We must first understand where we are, and as we continue to conduct analyses, we will be able to understand the field’s current state and path forward,” she concludes.

      Fellow chemical engineering students Claire Kim and Alfonso Restrepo are working with postdoc and MCSC Impact Fellow Xiangkun (Elvis) Cao, also on investigating CCUS technology. Kim’s focus is on life cycle assessment (LCA), while Restrepo’s focus is on techno-economic assessment (TEA). They have been working together to use the two tools to evaluate multiple CCUS technologies. While LCA and TEA are not new tools themselves, their application in CCUS has not been comprehensively defined and described. “CCUS can play an important role in the flexible, low-carbon energy systems,” says Kim, which was part of the motivation behind her project choice.

      Through TEA, Restrepo has been investigating how various startups and larger companies are incorporating CCUS technology in their processes. “In order to reduce CO2 emissions before it’s too late to act, there is a strong need for resources that effectively evaluate CCUS technology, to understand the effectiveness and viability of emerging technology for future implementation,” he explains. For their next steps, Kim and Restrepo will apply LCA and TEA to the analysis of a specific capture (for example, direct ocean capture) or conversion (for example, CO2-to-fuel conversion) process​ in CCUS.

      Cameron Dougal, a first-year student, and James Santoro, studying management, both worked with postdoc and MCSC Impact Fellow Paloma Gonzalez-Rojas on biodegradable materials. Dougal explored biodegradable packaging film in urban systems. “I have had a longstanding interest in sustainability, with a newer interest in urban planning and design, which motivated me to work on this project,” Dougal says. “Bio-based plastics are a promising step for the future.”

      Dougal spent time conducting internet and print research, as well as speaking with faculty on their relevant work. From these efforts, Dougal has identified important historical context for the current recycling landscape — as well as key case studies and cities around the world to explore further. In addition to conducting more research, Dougal plans to create a summary and statistic sheet.

      Santoro dove into the production angle, working on evaluating the economic viability of the startups that are creating biodegradable materials. “Non-renewable plastics (created with fossil fuels) continue to pollute and irreparably damage our environment,” he says. “As we look for innovative solutions, a key question to answer is how can we determine a more effective way to evaluate the economic viability and probability of success for new startups and technologies creating biodegradable plastics?” The project aims to develop an effective framework to begin to answer this.

      At this point, Santoro has been understanding the overall ecosystem, understanding how these biodegradable materials are developed, and analyzing the economics side of things. He plans to have conversations with company founders, investors, and experts, and identify major challenges for biodegradable technology startups in creating high performance products with attractive unit economics. There is also still a lot to research about new technologies and trends in the industry, the profitability of different products, as well as specific individual companies doing this type of work.

      Tess Buchanan, who is studying materials science and engineering, is working with Katharina Fransen and Sarah Av-Ron, MIT graduate students in the Department of Chemical Engineering, and principal investigator Professor Bradley Olsen, to also explore biodegradables by looking into their development from biomass “This is critical work, given the current plastics sustainability crisis, and the potential of bio-based polymers,” Buchanan says.

      The objective of the project is to explore new sustainable polymers through a biodegradation assay using clear zone growth analysis to yield degradation rates. For next steps, Buchanan is diving into synthesis expansion and using machine learning to understand the relationship between biodegradation and polymer chemistry.

      Kezia Hector, studying chemical engineering, and Tamsin Nottage, a first-year student, working with postdoc and MCSC Impact Fellow Sydney Sroka, explored advancing and establishing sustainable solutions for value chain resilience. Hector’s focus was understanding how wildfires can affect supply chains, specifically identifying sources of economic loss. She reviewed academic literature and news articles, and looked at the Amazon, California, Siberia, and Washington, finding that wildfires cause millions of dollars in damage every year and impact supply chains by cutting off or slowing down freight activity. She will continue to identify ways to make supply chains more resilient and sustainable.

      Nottage focused on the economic impact of typhoons, closely studying Typhoon Mangkhut, a powerful and catastrophic tropical cyclone that caused extensive damages of $593 million in Guam, the Philippines, and South China in September 2018. “As a Bahamian, I’ve witnessed the ferocity of hurricanes and challenges of rebuilding after them,” says Nottage. “I used this project to identify the tropical cyclones that caused the most extensive damage for further investigation.”She compiled the causes of damage and their costs to inform targets of supply chain resiliency reform (shipping, building materials, power supply, etc.). As a next step, Nottage will focus on modeling extreme events like Mangkunt to develop frameworks that companies can learn from and utilize to build more sustainable supply chains in the future.

      Ellie Vaserman, a first-year student working with postdoc and MCSC Impact Fellow Poushali Maji, also explored a topic related to value chains: unlocking circularity across the entire value chain through quality improvement, inclusive policy, and behavior to improve materials recovery. Specifically, her objectives have been to learn more about methods of chemolysis and the viability of their products, to compare methods of chemical recycling of polyethylene terephthalate (PET) using quantitative metrics, and to design qualitative visuals to make the steps in PET chemical recycling processes more understandable.

      To do so, she conducted a literature review to identify main methods of chemolysis that are utilized in the field (and collect data about these methods) and created graphics for some of the more common processes. Moving forward, she hopes to compare the processes using other metrics and research the energy intensity of the monomer purification processes.

      The work of these students, as well as many others, continued over MIT’s Independent Activities Period in January. More

    • 100 Shares179 Views

      in Environment

      Selective separation could help alleviate critical metals shortage

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      New processing methods developed by MIT researchers could help ease looming shortages of the essential metals that power everything from phones to automotive batteries, by making it easier to separate these rare metals from mining ores and recycled materials.

      Selective adjustments within a chemical process called sulfidation allowed professor of metallurgy Antoine Allanore and his graduate student Caspar Stinn to successfully target and separate rare metals, such as the cobalt in a lithium-ion battery, from mixed-metal materials.

      As they report in the journal Nature, their processing techniques allow the metals to remain in solid form and be separated without dissolving the material. This avoids traditional but costly liquid separation methods that require significant energy. The researchers developed processing conditions for 56 elements and tested these conditions on 15 elements.

      Their sulfidation approach, they write in the paper, could reduce the capital costs of metal separation between 65 and 95 percent from mixed-metal oxides. Their selective processing could also reduce greenhouse gas emissions by 60 to 90 percent compared to traditional liquid-based separation.

      “We were excited to find replacements for processes that had really high levels of water usage and greenhouse gas emissions, such as lithium-ion battery recycling, rare-earth magnet recycling, and rare-earth separation,” says Stinn. “Those are processes that make materials for sustainability applications, but the processes themselves are very unsustainable.”

      The findings offer one way to alleviate a growing demand for minor metals like cobalt, lithium, and rare earth elements that are used in “clean” energy products like electric cars, solar cells, and electricity-generating windmills. According to a 2021 report by the International Energy Agency, the average amount of minerals needed for a new unit of power generation capacity has risen by 50 percent since 2010, as renewable energy technologies using these metals expand their reach.

      Opportunity for selectivity

      For more than a decade, the Allanore group has been studying the use of sulfide materials in developing new electrochemical routes for metal production. Sulfides are common materials, but the MIT scientists are experimenting with them under extreme conditions like very high temperatures — from 800 to 3,000 degrees Fahrenheit — that are used in manufacturing plants but not in a typical university lab.

      “We are looking at very well-established materials in conditions that are uncommon compared to what has been done before,” Allanore explains, “and that is why we are finding new applications or new realities.”

      In the process of synthetizing high-temperature sulfide materials to support electrochemical production, Stinn says, “we learned we could be very selective and very controlled about what products we made. And it was with that understanding that we realized, ‘OK, maybe there’s an opportunity for selectivity in separation here.’”

      The chemical reaction exploited by the researchers reacts a material containing a mix of metal oxides to form new metal-sulfur compounds or sulfides. By altering factors like temperature, gas pressure, and the addition of carbon in the reaction process, Stinn and Allanore found that they could selectively create a variety of sulfide solids that can be physically separated by a variety of methods, including crushing the material and sorting different-sized sulfides or using magnets to separate different sulfides from one another.

      Current methods of rare metal separation rely on large quantities of energy, water, acids, and organic solvents which have costly environmental impacts, says Stinn. “We are trying to use materials that are abundant, economical, and readily available for sustainable materials separation, and we have expanded that domain to now include sulfur and sulfides.”

      Stinn and Allanore used selective sulfidation to separate out economically important metals like cobalt in recycled lithium-ion batteries. They also used their techniques to separate dysprosium — a rare-earth element used in applications ranging from data storage devices to optoelectronics — from rare-earth-boron magnets, or from the typical mixture of oxides available from mining minerals such as bastnaesite.

      Leveraging existing technology

      Metals like cobalt and rare earths are only found in small amounts in mined materials, so industries must process large volumes of material to retrieve or recycle enough of these metals to be economically viable, Allanore explains. “It’s quite clear that these processes are not efficient. Most of the emissions come from the lack of selectivity and the low concentration at which they operate.”

      By eliminating the need for liquid separation and the extra steps and materials it requires to dissolve and then reprecipitate individual elements, the MIT researchers’ process significantly reduces the costs incurred and emissions produced during separation.

      “One of the nice things about separating materials using sulfidation is that a lot of existing technology and process infrastructure can be leveraged,” Stinn says. “It’s new conditions and new chemistries in established reactor styles and equipment.”

      The next step is to show that the process can work for large amounts of raw material — separating out 16 elements from rare-earth mining streams, for example. “Now we have shown that we can handle three or four or five of them together, but we have not yet processed an actual stream from an existing mine at a scale to match what’s required for deployment,” Allanore says.

      Stinn and colleagues in the lab have built a reactor that can process about 10 kilograms of raw material per day, and the researchers are starting conversations with several corporations about the possibilities.

      “We are discussing what it would take to demonstrate the performance of this approach with existing mineral and recycling streams,” Allanore says.

      This research was supported by the U.S. Department of Energy and the U.S. National Science Foundation. More

    • 75 Shares119 Views

      in Environment

      Q&A: More-sustainable concrete with machine learning

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      As a building material, concrete withstands the test of time. Its use dates back to early civilizations, and today it is the most popular composite choice in the world. However, it’s not without its faults. Production of its key ingredient, cement, contributes 8-9 percent of the global anthropogenic CO2 emissions and 2-3 percent of energy consumption, which is only projected to increase in the coming years. With aging United States infrastructure, the federal government recently passed a milestone bill to revitalize and upgrade it, along with a push to reduce greenhouse gas emissions where possible, putting concrete in the crosshairs for modernization, too.

      Elsa Olivetti, the Esther and Harold E. Edgerton Associate Professor in the MIT Department of Materials Science and Engineering, and Jie Chen, MIT-IBM Watson AI Lab research scientist and manager, think artificial intelligence can help meet this need by designing and formulating new, more sustainable concrete mixtures, with lower costs and carbon dioxide emissions, while improving material performance and reusing manufacturing byproducts in the material itself. Olivetti’s research improves environmental and economic sustainability of materials, and Chen develops and optimizes machine learning and computational techniques, which he can apply to materials reformulation. Olivetti and Chen, along with their collaborators, have recently teamed up for an MIT-IBM Watson AI Lab project to make concrete more sustainable for the benefit of society, the climate, and the economy.

      Q: What applications does concrete have, and what properties make it a preferred building material?

      Olivetti: Concrete is the dominant building material globally with an annual consumption of 30 billion metric tons. That is over 20 times the next most produced material, steel, and the scale of its use leads to considerable environmental impact, approximately 5-8 percent of global greenhouse gas (GHG) emissions. It can be made locally, has a broad range of structural applications, and is cost-effective. Concrete is a mixture of fine and coarse aggregate, water, cement binder (the glue), and other additives.

      Q: Why isn’t it sustainable, and what research problems are you trying to tackle with this project?

      Olivetti: The community is working on several ways to reduce the impact of this material, including alternative fuels use for heating the cement mixture, increasing energy and materials efficiency and carbon sequestration at production facilities, but one important opportunity is to develop an alternative to the cement binder.

      While cement is 10 percent of the concrete mass, it accounts for 80 percent of the GHG footprint. This impact is derived from the fuel burned to heat and run the chemical reaction required in manufacturing, but also the chemical reaction itself releases CO2 from the calcination of limestone. Therefore, partially replacing the input ingredients to cement (traditionally ordinary Portland cement or OPC) with alternative materials from waste and byproducts can reduce the GHG footprint. But use of these alternatives is not inherently more sustainable because wastes might have to travel long distances, which adds to fuel emissions and cost, or might require pretreatment processes. The optimal way to make use of these alternate materials will be situation-dependent. But because of the vast scale, we also need solutions that account for the huge volumes of concrete needed. This project is trying to develop novel concrete mixtures that will decrease the GHG impact of the cement and concrete, moving away from the trial-and-error processes towards those that are more predictive.

      Chen: If we want to fight climate change and make our environment better, are there alternative ingredients or a reformulation we could use so that less greenhouse gas is emitted? We hope that through this project using machine learning we’ll be able to find a good answer.

      Q: Why is this problem important to address now, at this point in history?

      Olivetti: There is urgent need to address greenhouse gas emissions as aggressively as possible, and the road to doing so isn’t necessarily straightforward for all areas of industry. For transportation and electricity generation, there are paths that have been identified to decarbonize those sectors. We need to move much more aggressively to achieve those in the time needed; further, the technological approaches to achieve that are more clear. However, for tough-to-decarbonize sectors, such as industrial materials production, the pathways to decarbonization are not as mapped out.

      Q: How are you planning to address this problem to produce better concrete?

      Olivetti: The goal is to predict mixtures that will both meet performance criteria, such as strength and durability, with those that also balance economic and environmental impact. A key to this is to use industrial wastes in blended cements and concretes. To do this, we need to understand the glass and mineral reactivity of constituent materials. This reactivity not only determines the limit of the possible use in cement systems but also controls concrete processing, and the development of strength and pore structure, which ultimately control concrete durability and life-cycle CO2 emissions.

      Chen: We investigate using waste materials to replace part of the cement component. This is something that we’ve hypothesized would be more sustainable and economic — actually waste materials are common, and they cost less. Because of the reduction in the use of cement, the final concrete product would be responsible for much less carbon dioxide production. Figuring out the right concrete mixture proportion that makes endurable concretes while achieving other goals is a very challenging problem. Machine learning is giving us an opportunity to explore the advancement of predictive modeling, uncertainty quantification, and optimization to solve the issue. What we are doing is exploring options using deep learning as well as multi-objective optimization techniques to find an answer. These efforts are now more feasible to carry out, and they will produce results with reliability estimates that we need to understand what makes a good concrete.

      Q: What kinds of AI and computational techniques are you employing for this?

      Olivetti: We use AI techniques to collect data on individual concrete ingredients, mix proportions, and concrete performance from the literature through natural language processing. We also add data obtained from industry and/or high throughput atomistic modeling and experiments to optimize the design of concrete mixtures. Then we use this information to develop insight into the reactivity of possible waste and byproduct materials as alternatives to cement materials for low-CO2 concrete. By incorporating generic information on concrete ingredients, the resulting concrete performance predictors are expected to be more reliable and transformative than existing AI models.

      Chen: The final objective is to figure out what constituents, and how much of each, to put into the recipe for producing the concrete that optimizes the various factors: strength, cost, environmental impact, performance, etc. For each of the objectives, we need certain models: We need a model to predict the performance of the concrete (like, how long does it last and how much weight does it sustain?), a model to estimate the cost, and a model to estimate how much carbon dioxide is generated. We will need to build these models by using data from literature, from industry, and from lab experiments.

      We are exploring Gaussian process models to predict the concrete strength, going forward into days and weeks. This model can give us an uncertainty estimate of the prediction as well. Such a model needs specification of parameters, for which we will use another model to calculate. At the same time, we also explore neural network models because we can inject domain knowledge from human experience into them. Some models are as simple as multi-layer perceptions, while some are more complex, like graph neural networks. The goal here is that we want to have a model that is not only accurate but also robust — the input data is noisy, and the model must embrace the noise, so that its prediction is still accurate and reliable for the multi-objective optimization.

      Once we have built models that we are confident with, we will inject their predictions and uncertainty estimates into the optimization of multiple objectives, under constraints and under uncertainties.

      Q: How do you balance cost-benefit trade-offs?

      Chen: The multiple objectives we consider are not necessarily consistent, and sometimes they are at odds with each other. The goal is to identify scenarios where the values for our objectives cannot be further pushed simultaneously without compromising one or a few. For example, if you want to further reduce the cost, you probably have to suffer the performance or suffer the environmental impact. Eventually, we will give the results to policymakers and they will look into the results and weigh the options. For example, they may be able to tolerate a slightly higher cost under a significant reduction in greenhouse gas. Alternatively, if the cost varies little but the concrete performance changes drastically, say, doubles or triples, then this is definitely a favorable outcome.

      Q: What kinds of challenges do you face in this work?

      Chen: The data we get either from industry or from literature are very noisy; the concrete measurements can vary a lot, depending on where and when they are taken. There are also substantial missing data when we integrate them from different sources, so, we need to spend a lot of effort to organize and make the data usable for building and training machine learning models. We also explore imputation techniques that substitute missing features, as well as models that tolerate missing features, in our predictive modeling and uncertainty estimate.

      Q: What do you hope to achieve through this work?

      Chen: In the end, we are suggesting either one or a few concrete recipes, or a continuum of recipes, to manufacturers and policymakers. We hope that this will provide invaluable information for both the construction industry and for the effort of protecting our beloved Earth.

      Olivetti: We’d like to develop a robust way to design cements that make use of waste materials to lower their CO2 footprint. Nobody is trying to make waste, so we can’t rely on one stream as a feedstock if we want this to be massively scalable. We have to be flexible and robust to shift with feedstocks changes, and for that we need improved understanding. Our approach to develop local, dynamic, and flexible alternatives is to learn what makes these wastes reactive, so we know how to optimize their use and do so as broadly as possible. We do that through predictive model development through software we have developed in my group to automatically extract data from literature on over 5 million texts and patents on various topics. We link this to the creative capabilities of our IBM collaborators to design methods that predict the final impact of new cements. If we are successful, we can lower the emissions of this ubiquitous material and play our part in achieving carbon emissions mitigation goals.

      Other researchers involved with this project include Stefanie Jegelka, the X-Window Consortium Career Development Associate Professor in the MIT Department of Electrical Engineering and Computer Science; Richard Goodwin, IBM principal researcher; Soumya Ghosh, MIT-IBM Watson AI Lab research staff member; and Kristen Severson, former research staff member. Collaborators included Nghia Hoang, former research staff member with MIT-IBM Watson AI Lab and IBM Research; and Jeremy Gregory, research scientist in the MIT Department of Civil and Environmental Engineering and executive director of the MIT Concrete Sustainability Hub.

      This research is supported by the MIT-IBM Watson AI Lab. More

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      in Energy

      An energy-storage solution that flows like soft-serve ice cream

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      Batteries made from an electrically conductive mixture the consistency of molasses could help solve a critical piece of the decarbonization puzzle. An interdisciplinary team from MIT has found that an electrochemical technology called a semisolid flow battery can be a cost-competitive form of energy storage and backup for variable renewable energy (VRE) sources such as wind and solar. The group’s research is described in a paper published in Joule.

      “The transition to clean energy requires energy storage systems of different durations for when the sun isn’t shining and the wind isn’t blowing,” says Emre Gençer, a research scientist with the MIT Energy Initiative (MITEI) and a member of the team. “Our work demonstrates that a semisolid flow battery could be a lifesaving as well as economical option when these VRE sources can’t generate power for a day or longer — in the case of natural disasters, for instance.”

      The rechargeable zinc-manganese dioxide (Zn-MnO2) battery the researchers created beat out other long-duration energy storage contenders. “We performed a comprehensive, bottom-up analysis to understand how the battery’s composition affects performance and cost, looking at all the trade-offs,” says Thaneer Malai Narayanan SM ’18, PhD ’21. “We showed that our system can be cheaper than others, and can be scaled up.”

      Narayanan, who conducted this work at MIT as part of his doctorate in mechanical engineering, is the lead author of the paper. Additional authors include Gençer, Yunguang Zhu, a postdoc in the MIT Electrochemical Energy Lab; Gareth McKinley, the School of Engineering Professor of Teaching Innovation and professor of mechanical engineering at MIT; and Yang Shao-Horn, the JR East Professor of Engineering, a professor of mechanical engineering and of materials science and engineering, and a member of the Research Laboratory of Electronics (RLE), who directs the MIT Electrochemical Energy Lab.

      Going with the flow

      In 2016, Narayanan began his graduate studies, joining the Electrochemical Energy Lab, a hotbed of research and exploration of solutions to mitigate climate change, which is centered on innovative battery chemistry and decarbonizing fuels and chemicals. One exciting opportunity for the lab: developing low- and no-carbon backup energy systems suitable for grid-scale needs when VRE generation flags.                                                  

      While the lab cast a wide net, investigating energy conversion and storage using solid oxide fuel cells, lithium-ion batteries, and metal-air batteries, among others, Narayanan took a particular interest in flow batteries. In these systems, two different chemical (electrolyte) solutions with either negative or positive ions are pumped from separate tanks, meeting across a membrane (called the stack). Here, the ion streams react, converting electrical energy to chemical energy — in effect, charging the battery. When there is demand for this stored energy, the solution gets pumped back to the stack to convert chemical energy into electrical energy again.

      The duration of time that flow batteries can discharge, releasing the stored electricity, is determined by the volume of positively and negatively charged electrolyte solutions streaming through the stack. In theory, as long as these solutions keep flowing, reacting, and converting the chemical energy to electrical energy, the battery systems can provide electricity.

      “For backup lasting more than a day, the architecture of flow batteries suggests they can be a cheap option,” says Narayanan. “You recharge the solution in the tanks from sun and wind power sources.” This renders the entire system carbon free.

      But while the promise of flow battery technologies has beckoned for at least a decade, the uneven performance and expense of materials required for these battery systems has slowed their implementation. So, Narayanan set out on an ambitious journey: to design and build a flow battery that could back up VRE systems for a day or more, storing and discharging energy with the same or greater efficiency than backup rivals; and to determine, through rigorous cost analysis, whether such a system could prove economically viable as a long-duration energy option.

      Multidisciplinary collaborators

      To attack this multipronged challenge, Narayanan’s project brought together, in his words, “three giants, scientists all well-known in their fields”:  Shao-Horn, who specializes in chemical physics and electrochemical science, and design of materials; Gençer, who creates detailed economic models of emergent energy systems at MITEI; and McKinley, an expert in rheology, the physics of flow. These three also served as his thesis advisors.

      “I was excited to work in such an interdisciplinary team, which offered a unique opportunity to create a novel battery architecture by designing charge transfer and ion transport within flowable semi-solid electrodes, and to guide battery engineering using techno-economics of such flowable batteries,” says Shao-Horn.

      While other flow battery systems in contention, such as the vanadium redox flow battery, offer the storage capacity and energy density to back up megawatt and larger power systems, they depend on expensive chemical ingredients that make them bad bets for long duration purposes. Narayanan was on the hunt for less-pricey chemical components that also feature rich energy potential.

      Through a series of bench experiments, the researchers came up with a novel electrode (electrical conductor) for the battery system: a mixture containing dispersed manganese dioxide (MnO2) particles, shot through with an electrically conductive additive, carbon black. This compound reacts with a conductive zinc solution or zinc plate at the stack, enabling efficient electrochemical energy conversion. The fluid properties of this battery are far removed from the watery solutions used by other flow batteries.

      “It’s a semisolid — a slurry,” says Narayanan. “Like thick, black paint, or perhaps a soft-serve ice cream,” suggests McKinley. The carbon black adds the pigment and the electric punch. To arrive at the optimal electrochemical mix, the researchers tweaked their formula many times.

      “These systems have to be able to flow under reasonable pressures, but also have a weak yield stress so that the active MnO2 particles don’t sink to the bottom of the flow tanks when the system isn’t being used, as well as not separate into a battery/oily clear fluid phase and a dense paste of carbon particles and MnO2,” says McKinley.

      This series of experiments informed the technoeconomic analysis. By “connecting the dots between composition, performance, and cost,” says Narayanan, he and Gençer were able to make system-level cost and efficiency calculations for the Zn-MnO2 battery.

      “Assessing the cost and performance of early technologies is very difficult, and this was an example of how to develop a standard method to help researchers at MIT and elsewhere,” says Gençer. “One message here is that when you include the cost analysis at the development stage of your experimental work, you get an important early understanding of your project’s cost implications.”

      In their final round of studies, Gençer and Narayanan compared the Zn-MnO2 battery to a set of equivalent electrochemical battery and hydrogen backup systems, looking at the capital costs of running them at durations of eight, 24, and 72 hours. Their findings surprised them: For battery discharges longer than a day, their semisolid flow battery beat out lithium-ion batteries and vanadium redox flow batteries. This was true even when factoring in the heavy expense of pumping the MnO2 slurry from tank to stack. “I was skeptical, and not expecting this battery would be competitive, but once I did the cost calculation, it was plausible,” says Gençer.

      But carbon-free battery backup is a very Goldilocks-like business: Different situations require different-duration solutions, whether an anticipated overnight loss of solar power, or a longer-term, climate-based disruption in the grid. “Lithium-ion is great for backup of eight hours and under, but the materials are too expensive for longer periods,” says Gençer. “Hydrogen is super expensive for very short durations, and good for very long durations, and we will need all of them.” This means it makes sense to continue working on the Zn-MnO2 system to see where it might fit in.

      “The next step is to take our battery system and build it up,” says Narayanan, who is working now as a battery engineer. “Our research also points the way to other chemistries that could be developed under the semi-solid flow battery platform, so we could be seeing this kind of technology used for energy storage in our lifetimes.”

      This research was supported by Eni S.p.A. through MITEI. Thaneer Malai Narayanan received an Eni-sponsored MIT Energy Fellowship during his work on the project. More

    • 138 Shares169 Views

      in Environment

      Making catalytic surfaces more active to help decarbonize fuels and chemicals

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      Electrochemical reactions that are accelerated using catalysts lie at the heart of many processes for making and using fuels, chemicals, and materials — including storing electricity from renewable energy sources in chemical bonds, an important capability for decarbonizing transportation fuels. Now, research at MIT could open the door to ways of making certain catalysts more active, and thus enhancing the efficiency of such processes.

      A new production process yielded catalysts that increased the efficiency of the chemical reactions by fivefold, potentially enabling useful new processes in biochemistry, organic chemistry, environmental chemistry, and electrochemistry. The findings are described today in the journal Nature Catalysis, in a paper by Yang Shao-Horn, an MIT professor of mechanical engineering and of materials science and engineering, and a member of the Research Lab of Electronics (RLE); Tao Wang, a postdoc in RLE; Yirui Zhang, a graduate student in the Department of Mechanical Engineering; and five others.

      The process involves adding a layer of what’s called an ionic liquid in between a gold or platinum catalyst and a chemical feedstock. Catalysts produced with this method could potentially enable much more efficient conversion of hydrogen fuel to power devices such as fuel cells, or more efficient conversion of carbon dioxide into fuels.

      “There is an urgent need to decarbonize how we power transportation beyond light-duty vehicles, how we make fuels, and how we make materials and chemicals,” says Shao-Horn, emphasizing the pressing call to reduce carbon emissions highlighted in the latest IPCC report on climate change. This new approach to enhancing catalytic activity could provide an important step in that direction, she says.

      Using hydrogen in electrochemical devices such as fuel cells is one promising approach to decarbonizing fields such as aviation and heavy-duty vehicles, and the new process may help to make such uses practical. At present, the oxygen reduction reaction that powers such fuel cells is limited by its inefficiency. Previous attempts to improve that efficiency have focused on choosing different catalyst materials or modifying their surface compositions and structure.

      In this research, however, instead of modifying the solid surfaces, the team added a thin layer in between the catalyst and the electrolyte, the active material that participates in the chemical reaction. The ionic liquid layer, they found, regulates the activity of protons that help to increase the rate of the chemical reactions taking place on the interface.

      Because there is a great variety of such ionic liquids to choose from, it’s possible to “tune” proton activity and the reaction rates to match the energetics needed for processes involving proton transfer, which can be used to make fuels and chemicals through reactions with oxygen.

      “The proton activity and the barrier for proton transfer is governed by the ionic liquid layer, and so there’s a great tuneability in terms of catalytic activity for reactions involving proton and electron transfer,” Shao-Horn says. And the effect is produced by a vanishingly thin layer of the liquid, just a few nanometers thick, above which is a much thicker layer of the liquid that is to undergo the reaction.

      “I think this concept is novel and important,” says Wang, the paper’s first author, “because people know the proton activity is important in many electrochemistry reactions, but it’s very challenging to study.” That’s because in a water environment, there are so many interactions between neighboring water molecules involved that it’s very difficult to separate out which reactions are taking place. By using an ionic liquid, whose ions can each only form a single bond with the intermediate material, it became possible to study the reactions in detail, using infrared spectroscopy.

      As a result, Wang says, “Our finding highlights the critical role that interfacial electrolytes, in particular the intermolecular hydrogen bonding, can play in enhancing the activity of the electro-catalytic process. It also provides fundamental insights into proton transfer mechanisms at a quantum mechanical level, which can push the frontiers of knowing how protons and electrons interact at catalytic interfaces.”

      “The work is also exciting because it gives people a design principle for how they can tune the catalysts,” says Zhang. “We need some species right at a ‘sweet spot’ — not too active or too inert — to enhance the reaction rate.”

      With some of these techniques, says Reshma Rao, a recent doctoral graduate from MIT and now a postdoc at Imperial College, London, who is also a co-author of the paper, “we see up to a five-times increase in activity. I think the most exciting part of this research is the way it opens up a whole new dimension in the way we think about catalysis.” The field had hit “a kind of roadblock,” she says, in finding ways to design better materials. By focusing on the liquid layer rather than the surface of the material, “that’s kind of a whole different way of looking at this problem, and opens up a whole new dimension, a whole new axis along which we can change things and optimize some of these reaction rates.”

      The team also included Botao Huang, Bin Cai, and Livia Giordano in the MIT’s Research Laboratory of Electronics, and Shi-Gang Sun at Xiamen University in China. The work was supported by the Toyota Research Institute, and used the National Science Foundation’s Extreme Science and Engineering Environment. More

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      Designing better batteries for electric vehicles

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      The urgent need to cut carbon emissions is prompting a rapid move toward electrified mobility and expanded deployment of solar and wind on the electric grid. If those trends escalate as expected, the need for better methods of storing electrical energy will intensify.

      “We need all the strategies we can get to address the threat of climate change,” says Elsa Olivetti PhD ’07, the Esther and Harold E. Edgerton Associate Professor in Materials Science and Engineering. “Obviously, developing technologies for grid-based storage at a large scale is critical. But for mobile applications — in particular, transportation — much research is focusing on adapting today’s lithium-ion battery to make versions that are safer, smaller, and can store more energy for their size and weight.”

      Traditional lithium-ion batteries continue to improve, but they have limitations that persist, in part because of their structure. A lithium-ion battery consists of two electrodes — one positive and one negative — sandwiched around an organic (carbon-containing) liquid. As the battery is charged and discharged, electrically charged particles (or ions) of lithium pass from one electrode to the other through the liquid electrolyte.

      One problem with that design is that at certain voltages and temperatures, the liquid electrolyte can become volatile and catch fire. “Batteries are generally safe under normal usage, but the risk is still there,” says Kevin Huang PhD ’15, a research scientist in Olivetti’s group.

      Another problem is that lithium-ion batteries are not well-suited for use in vehicles. Large, heavy battery packs take up space and increase a vehicle’s overall weight, reducing fuel efficiency. But it’s proving difficult to make today’s lithium-ion batteries smaller and lighter while maintaining their energy density — that is, the amount of energy they store per gram of weight.

      To solve those problems, researchers are changing key features of the lithium-ion battery to make an all-solid, or “solid-state,” version. They replace the liquid electrolyte in the middle with a thin, solid electrolyte that’s stable at a wide range of voltages and temperatures. With that solid electrolyte, they use a high-capacity positive electrode and a high-capacity, lithium metal negative electrode that’s far thinner than the usual layer of porous carbon. Those changes make it possible to shrink the overall battery considerably while maintaining its energy-storage capacity, thereby achieving a higher energy density.

      “Those features — enhanced safety and greater energy density — are probably the two most-often-touted advantages of a potential solid-state battery,” says Huang. He then quickly clarifies that “all of these things are prospective, hoped-for, and not necessarily realized.” Nevertheless, the possibility has many researchers scrambling to find materials and designs that can deliver on that promise.

      Thinking beyond the lab

      Researchers have come up with many intriguing options that look promising — in the lab. But Olivetti and Huang believe that additional practical considerations may be important, given the urgency of the climate change challenge. “There are always metrics that we researchers use in the lab to evaluate possible materials and processes,” says Olivetti. Examples might include energy-storage capacity and charge/discharge rate. When performing basic research — which she deems both necessary and important — those metrics are appropriate. “But if the aim is implementation, we suggest adding a few metrics that specifically address the potential for rapid scaling,” she says.

      Based on industry’s experience with current lithium-ion batteries, the MIT researchers and their colleague Gerbrand Ceder, the Daniel M. Tellep Distinguished Professor of Engineering at the University of California at Berkeley, suggest three broad questions that can help identify potential constraints on future scale-up as a result of materials selection. First, with this battery design, could materials availability, supply chains, or price volatility become a problem as production scales up? (Note that the environmental and other concerns raised by expanded mining are outside the scope of this study.) Second, will fabricating batteries from these materials involve difficult manufacturing steps during which parts are likely to fail? And third, do manufacturing measures needed to ensure a high-performance product based on these materials ultimately lower or raise the cost of the batteries produced?

      To demonstrate their approach, Olivetti, Ceder, and Huang examined some of the electrolyte chemistries and battery structures now being investigated by researchers. To select their examples, they turned to previous work in which they and their collaborators used text- and data-mining techniques to gather information on materials and processing details reported in the literature. From that database, they selected a few frequently reported options that represent a range of possibilities.

      Materials and availability

      In the world of solid inorganic electrolytes, there are two main classes of materials — the oxides, which contain oxygen, and the sulfides, which contain sulfur. Olivetti, Ceder, and Huang focused on one promising electrolyte option in each class and examined key elements of concern for each of them.

      The sulfide they considered was LGPS, which combines lithium, germanium, phosphorus, and sulfur. Based on availability considerations, they focused on the germanium, an element that raises concerns in part because it’s not generally mined on its own. Instead, it’s a byproduct produced during the mining of coal and zinc.

      To investigate its availability, the researchers looked at how much germanium was produced annually in the past six decades during coal and zinc mining and then at how much could have been produced. The outcome suggested that 100 times more germanium could have been produced, even in recent years. Given that supply potential, the availability of germanium is not likely to constrain the scale-up of a solid-state battery based on an LGPS electrolyte.

      The situation looked less promising with the researchers’ selected oxide, LLZO, which consists of lithium, lanthanum, zirconium, and oxygen. Extraction and processing of lanthanum are largely concentrated in China, and there’s limited data available, so the researchers didn’t try to analyze its availability. The other three elements are abundantly available. However, in practice, a small quantity of another element — called a dopant — must be added to make LLZO easy to process. So the team focused on tantalum, the most frequently used dopant, as the main element of concern for LLZO.

      Tantalum is produced as a byproduct of tin and niobium mining. Historical data show that the amount of tantalum produced during tin and niobium mining was much closer to the potential maximum than was the case with germanium. So the availability of tantalum is more of a concern for the possible scale-up of an LLZO-based battery.

      But knowing the availability of an element in the ground doesn’t address the steps required to get it to a manufacturer. So the researchers investigated a follow-on question concerning the supply chains for critical elements — mining, processing, refining, shipping, and so on. Assuming that abundant supplies are available, can the supply chains that deliver those materials expand quickly enough to meet the growing demand for batteries?

      In sample analyses, they looked at how much supply chains for germanium and tantalum would need to grow year to year to provide batteries for a projected fleet of electric vehicles in 2030. As an example, an electric vehicle fleet often cited as a goal for 2030 would require production of enough batteries to deliver a total of 100 gigawatt hours of energy. To meet that goal using just LGPS batteries, the supply chain for germanium would need to grow by 50 percent from year to year — a stretch, since the maximum growth rate in the past has been about 7 percent. Using just LLZO batteries, the supply chain for tantalum would need to grow by about 30 percent — a growth rate well above the historical high of about 10 percent.

      Those examples demonstrate the importance of considering both materials availability and supply chains when evaluating different solid electrolytes for their scale-up potential. “Even when the quantity of a material available isn’t a concern, as is the case with germanium, scaling all the steps in the supply chain to match the future production of electric vehicles may require a growth rate that’s literally unprecedented,” says Huang.

      Materials and processing

      In assessing the potential for scale-up of a battery design, another factor to consider is the difficulty of the manufacturing process and how it may impact cost. Fabricating a solid-state battery inevitably involves many steps, and a failure at any step raises the cost of each battery successfully produced. As Huang explains, “You’re not shipping those failed batteries; you’re throwing them away. But you’ve still spent money on the materials and time and processing.”

      As a proxy for manufacturing difficulty, Olivetti, Ceder, and Huang explored the impact of failure rate on overall cost for selected solid-state battery designs in their database. In one example, they focused on the oxide LLZO. LLZO is extremely brittle, and at the high temperatures involved in manufacturing, a large sheet that’s thin enough to use in a high-performance solid-state battery is likely to crack or warp.

      To determine the impact of such failures on cost, they modeled four key processing steps in assembling LLZO-based batteries. At each step, they calculated cost based on an assumed yield — that is, the fraction of total units that were successfully processed without failing. With the LLZO, the yield was far lower than with the other designs they examined; and, as the yield went down, the cost of each kilowatt-hour (kWh) of battery energy went up significantly. For example, when 5 percent more units failed during the final cathode heating step, cost increased by about $30/kWh — a nontrivial change considering that a commonly accepted target cost for such batteries is $100/kWh. Clearly, manufacturing difficulties can have a profound impact on the viability of a design for large-scale adoption.

      Materials and performance

      One of the main challenges in designing an all-solid battery comes from “interfaces” — that is, where one component meets another. During manufacturing or operation, materials at those interfaces can become unstable. “Atoms start going places that they shouldn’t, and battery performance declines,” says Huang.

      As a result, much research is devoted to coming up with methods of stabilizing interfaces in different battery designs. Many of the methods proposed do increase performance; and as a result, the cost of the battery in dollars per kWh goes down. But implementing such solutions generally involves added materials and time, increasing the cost per kWh during large-scale manufacturing.

      To illustrate that trade-off, the researchers first examined their oxide, LLZO. Here, the goal is to stabilize the interface between the LLZO electrolyte and the negative electrode by inserting a thin layer of tin between the two. They analyzed the impacts — both positive and negative — on cost of implementing that solution. They found that adding the tin separator increases energy-storage capacity and improves performance, which reduces the unit cost in dollars/kWh. But the cost of including the tin layer exceeds the savings so that the final cost is higher than the original cost.

      In another analysis, they looked at a sulfide electrolyte called LPSCl, which consists of lithium, phosphorus, and sulfur with a bit of added chlorine. In this case, the positive electrode incorporates particles of the electrolyte material — a method of ensuring that the lithium ions can find a pathway through the electrolyte to the other electrode. However, the added electrolyte particles are not compatible with other particles in the positive electrode — another interface problem. In this case, a standard solution is to add a “binder,” another material that makes the particles stick together.

      Their analysis confirmed that without the binder, performance is poor, and the cost of the LPSCl-based battery is more than $500/kWh. Adding the binder improves performance significantly, and the cost drops by almost $300/kWh. In this case, the cost of adding the binder during manufacturing is so low that essentially all the of the cost decrease from adding the binder is realized. Here, the method implemented to solve the interface problem pays off in lower costs.

      The researchers performed similar studies of other promising solid-state batteries reported in the literature, and their results were consistent: The choice of battery materials and processes can affect not only near-term outcomes in the lab but also the feasibility and cost of manufacturing the proposed solid-state battery at the scale needed to meet future demand. The results also showed that considering all three factors together — availability, processing needs, and battery performance — is important because there may be collective effects and trade-offs involved.

      Olivetti is proud of the range of concerns the team’s approach can probe. But she stresses that it’s not meant to replace traditional metrics used to guide materials and processing choices in the lab. “Instead, it’s meant to complement those metrics by also looking broadly at the sorts of things that could get in the way of scaling” — an important consideration given what Huang calls “the urgent ticking clock” of clean energy and climate change.

      This research was supported by the Seed Fund Program of the MIT Energy Initiative (MITEI) Low-Carbon Energy Center for Energy Storage; by Shell, a founding member of MITEI; and by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, under the Advanced Battery Materials Research Program. The text mining work was supported by the National Science Foundation, the Office of Naval Research, and MITEI.

      This article appears in the Spring 2021 issue of Energy Futures, the magazine of the MIT Energy Initiative. More

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      in Energy

      Using aluminum and water to make clean hydrogen fuel — when and where it’s needed

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      As the world works to move away from fossil fuels, many researchers are investigating whether clean hydrogen fuel can play an expanded role in sectors from transportation and industry to buildings and power generation. It could be used in fuel cell vehicles, heat-producing boilers, electricity-generating gas turbines, systems for storing renewable energy, and more.

      But while using hydrogen doesn’t generate carbon emissions, making it typically does. Today, almost all hydrogen is produced using fossil fuel-based processes that together generate more than 2 percent of all global greenhouse gas emissions. In addition, hydrogen is often produced in one location and consumed in another, which means its use also presents logistical challenges.

      A promising reaction

      Another option for producing hydrogen comes from a perhaps surprising source: reacting aluminum with water. Aluminum metal will readily react with water at room temperature to form aluminum hydroxide and hydrogen. That reaction doesn’t typically take place because a layer of aluminum oxide naturally coats the raw metal, preventing it from coming directly into contact with water.

      Using the aluminum-water reaction to generate hydrogen doesn’t produce any greenhouse gas emissions, and it promises to solve the transportation problem for any location with available water. Simply move the aluminum and then react it with water on-site. “Fundamentally, the aluminum becomes a mechanism for storing hydrogen — and a very effective one,” says Douglas P. Hart, professor of mechanical engineering at MIT. “Using aluminum as our source, we can ‘store’ hydrogen at a density that’s 10 times greater than if we just store it as a compressed gas.”

      Two problems have kept aluminum from being employed as a safe, economical source for hydrogen generation. The first problem is ensuring that the aluminum surface is clean and available to react with water. To that end, a practical system must include a means of first modifying the oxide layer and then keeping it from re-forming as the reaction proceeds.

      The second problem is that pure aluminum is energy-intensive to mine and produce, so any practical approach needs to use scrap aluminum from various sources. But scrap aluminum is not an easy starting material. It typically occurs in an alloyed form, meaning that it contains other elements that are added to change the properties or characteristics of the aluminum for different uses. For example, adding magnesium increases strength and corrosion-resistance, adding silicon lowers the melting point, and adding a little of both makes an alloy that’s moderately strong and corrosion-resistant.

      Despite considerable research on aluminum as a source of hydrogen, two key questions remain: What’s the best way to prevent the adherence of an oxide layer on the aluminum surface, and how do alloying elements in a piece of scrap aluminum affect the total amount of hydrogen generated and the rate at which it is generated?

      “If we’re going to use scrap aluminum for hydrogen generation in a practical application, we need to be able to better predict what hydrogen generation characteristics we’re going to observe from the aluminum-water reaction,” says Laureen Meroueh PhD ’20, who earned her doctorate in mechanical engineering.

      Since the fundamental steps in the reaction aren’t well understood, it’s been hard to predict the rate and volume at which hydrogen forms from scrap aluminum, which can contain varying types and concentrations of alloying elements. So Hart, Meroueh, and Thomas W. Eagar, a professor of materials engineering and engineering management in the MIT Department of Materials Science and Engineering, decided to examine — in a systematic fashion — the impacts of those alloying elements on the aluminum-water reaction and on a promising technique for preventing the formation of the interfering oxide layer.

      To prepare, they had experts at Novelis Inc. fabricate samples of pure aluminum and of specific aluminum alloys made of commercially pure aluminum combined with either 0.6 percent silicon (by weight), 1 percent magnesium, or both — compositions that are typical of scrap aluminum from a variety of sources. Using those samples, the MIT researchers performed a series of tests to explore different aspects of the aluminum-water reaction.

      Pre-treating the aluminum

      The first step was to demonstrate an effective means of penetrating the oxide layer that forms on aluminum in the air. Solid aluminum is made up of tiny grains that are packed together with occasional boundaries where they don’t line up perfectly. To maximize hydrogen production, researchers would need to prevent the formation of the oxide layer on all those interior grain surfaces.

      Research groups have already tried various ways of keeping the aluminum grains “activated” for reaction with water. Some have crushed scrap samples into particles so tiny that the oxide layer doesn’t adhere. But aluminum powders are dangerous, as they can react with humidity and explode. Another approach calls for grinding up scrap samples and adding liquid metals to prevent oxide deposition. But grinding is a costly and energy-intensive process.

      To Hart, Meroueh, and Eagar, the most promising approach — first introduced by Jonathan Slocum ScD ’18 while he was working in Hart’s research group — involved pre-treating the solid aluminum by painting liquid metals on top and allowing them to permeate through the grain boundaries.

      To determine the effectiveness of that approach, the researchers needed to confirm that the liquid metals would reach the internal grain surfaces, with and without alloying elements present. And they had to establish how long it would take for the liquid metal to coat all of the grains in pure aluminum and its alloys.

      They started by combining two metals — gallium and indium — in specific proportions to create a “eutectic” mixture; that is, a mixture that would remain in liquid form at room temperature. They coated their samples with the eutectic and allowed it to penetrate for time periods ranging from 48 to 96 hours. They then exposed the samples to water and monitored the hydrogen yield (the amount formed) and flow rate for 250 minutes. After 48 hours, they also took high-magnification scanning electron microscope (SEM) images so they could observe the boundaries between adjacent aluminum grains.

      Based on the hydrogen yield measurements and the SEM images, the MIT team concluded that the gallium-indium eutectic does naturally permeate and reach the interior grain surfaces. However, the rate and extent of penetration vary with the alloy. The permeation rate was the same in silicon-doped aluminum samples as in pure aluminum samples but slower in magnesium-doped samples.

      Perhaps most interesting were the results from samples doped with both silicon and magnesium — an aluminum alloy often found in recycling streams. Silicon and magnesium chemically bond to form magnesium silicide, which occurs as solid deposits on the internal grain surfaces. Meroueh hypothesized that when both silicon and magnesium are present in scrap aluminum, those deposits can act as barriers that impede the flow of the gallium-indium eutectic.

      The experiments and images confirmed her hypothesis: The solid deposits did act as barriers, and images of samples pre-treated for 48 hours showed that permeation wasn’t complete. Clearly, a lengthy pre-treatment period would be critical for maximizing the hydrogen yield from scraps of aluminum containing both silicon and magnesium.

      Meroueh cites several benefits to the process they used. “You don’t have to apply any energy for the gallium-indium eutectic to work its magic on aluminum and get rid of that oxide layer,” she says. “Once you’ve activated your aluminum, you can drop it in water, and it’ll generate hydrogen — no energy input required.” Even better, the eutectic doesn’t chemically react with the aluminum. “It just physically moves around in between the grains,” she says. “At the end of the process, I could recover all of the gallium and indium I put in and use it again” — a valuable feature as gallium and (especially) indium are costly and in relatively short supply.

      Impacts of alloying elements on hydrogen generation

      The researchers next investigated how the presence of alloying elements affects hydrogen generation. They tested samples that had been treated with the eutectic for 96 hours; by then, the hydrogen yield and flow rates had leveled off in all the samples.

      The presence of 0.6 percent silicon increased the hydrogen yield for a given weight of aluminum by 20 percent compared to pure aluminum — even though the silicon-containing sample had less aluminum than the pure aluminum sample. In contrast, the presence of 1 percent magnesium produced far less hydrogen, while adding both silicon and magnesium pushed the yield up, but not to the level of pure aluminum.

      The presence of silicon also greatly accelerated the reaction rate, producing a far higher peak in the flow rate but cutting short the duration of hydrogen output. The presence of magnesium produced a lower flow rate but allowed the hydrogen output to remain fairly steady over time. And once again, aluminum with both alloying elements produced a flow rate between that of magnesium-doped and pure aluminum.

      Those results provide practical guidance on how to adjust the hydrogen output to match the operating needs of a hydrogen-consuming device. If the starting material is commercially pure aluminum, adding small amounts of carefully selected alloying elements can tailor the hydrogen yield and flow rate. If the starting material is scrap aluminum, careful choice of the source can be key. For high, brief bursts of hydrogen, pieces of silicon-containing aluminum from an auto junkyard could work well. For lower but longer flows, magnesium-containing scraps from the frame of a demolished building might be better. For results somewhere in between, aluminum containing both silicon and magnesium should work well; such material is abundantly available from scrapped cars and motorcycles, yachts, bicycle frames, and even smartphone cases.

      It should also be possible to combine scraps of different aluminum alloys to tune the outcome, notes Meroueh. “If I have a sample of activated aluminum that contains just silicon and another sample that contains just magnesium, I can put them both into a container of water and let them react,” she says. “So I get the fast ramp-up in hydrogen production from the silicon and then the magnesium takes over and has that steady output.”

      Another opportunity for tuning: Reducing grain size

      Another practical way to affect hydrogen production could be to reduce the size of the aluminum grains — a change that should increase the total surface area available for reactions to occur.

      To investigate that approach, the researchers requested specially customized samples from their supplier. Using standard industrial procedures, the Novelis experts first fed each sample through two rollers, squeezing it from the top and bottom so that the internal grains were flattened. They then heated each sample until the long, flat grains had reorganized and shrunk to a targeted size.

      In a series of carefully designed experiments, the MIT team found that reducing the grain size increased the efficiency and decreased the duration of the reaction to varying degrees in the different samples. Again, the presence of particular alloying elements had a major effect on the outcome.

      Needed: A revised theory that explains observations

      Throughout their experiments, the researchers encountered some unexpected results. For example, standard corrosion theory predicts that pure aluminum will generate more hydrogen than silicon-doped aluminum will — the opposite of what they observed in their experiments.

      To shed light on the underlying chemical reactions, Hart, Meroueh, and Eagar investigated hydrogen “flux,” that is, the volume of hydrogen generated over time on each square centimeter of aluminum surface, including the interior grains. They examined three grain sizes for each of their four compositions and collected thousands of data points measuring hydrogen flux.

      Their results show that reducing grain size has significant effects. It increases the peak hydrogen flux from silicon-doped aluminum as much as 100 times and from the other three compositions by 10 times. With both pure aluminum and silicon-containing aluminum, reducing grain size also decreases the delay before the peak flux and increases the rate of decline afterward. With magnesium-containing aluminum, reducing the grain size brings about an increase in peak hydrogen flux and results in a slightly faster decline in the rate of hydrogen output. With both silicon and magnesium present, the hydrogen flux over time resembles that of magnesium-containing aluminum when the grain size is not manipulated. When the grain size is reduced, the hydrogen output characteristics begin to resemble behavior observed in silicon-containing aluminum. That outcome was unexpected because when silicon and magnesium are both present, they react to form magnesium silicide, resulting in a new type of aluminum alloy with its own properties.

      The researchers stress the benefits of developing a better fundamental understanding of the underlying chemical reactions involved. In addition to guiding the design of practical systems, it might help them find a replacement for the expensive indium in their pre-treatment mixture. Other work has shown that gallium will naturally permeate through the grain boundaries of aluminum. “At this point, we know that the indium in our eutectic is important, but we don’t really understand what it does, so we don’t know how to replace it,” says Hart.

      But already Hart, Meroueh, and Eagar have demonstrated two practical ways of tuning the hydrogen reaction rate: by adding certain elements to the aluminum and by manipulating the size of the interior aluminum grains. In combination, those approaches can deliver significant results. “If you go from magnesium-containing aluminum with the largest grain size to silicon-containing aluminum with the smallest grain size, you get a hydrogen reaction rate that differs by two orders of magnitude,” says Meroueh. “That’s huge if you’re trying to design a real system that would use this reaction.”

      This research was supported through the MIT Energy Initiative by ExxonMobil-MIT Energy Fellowships awarded to Laureen Meroueh PhD ’20 from 2018 to 2020.

      This article appears in the Spring 2021 issue of Energy Futures, the magazine of the MIT Energy Initiative.  More

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      Elsa Olivetti wins 2021 MIT Bose Award for Excellence in Teaching

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      This year’s Bose Award for Excellence in Teaching has been presented to MIT Associate Professor Elsa Olivetti. Olivetti’s zest for enhancing the student experience is evident in the innovative and creative flare she brings to all aspects of her work.

      “Professor Olivetti’s dedication to teaching is truly inspiring,” says Anantha P. Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “She has an extraordinary ability to engage her students, and has developed transformational approaches to curriculum and mentoring.”

      Olivetti is the Esther and Harold E. Edgerton Associate Professor in Materials Science and Engineering, and co-director of the MIT Climate and Sustainability Consortium. Her passion for addressing issues related to climate change frames the focus of her research, which centers on improving the environmental and economic sustainability of materials in the context of growing global demand. Her work focuses on reducing the significant burden of materials production and consumption through increased use of recycled and waste materials; informing the early-stage design of new materials for effective scale-up; and understanding the implications of policy, new technology development, and manufacturing processes on materials supply chains. 

      Olivetti has made significant contributions on education within the Department of Materials Science and Engineering since she came on board in 2014, including designing and implementing a subject on industrial ecology and materials, co-design of the Advanced Materials Machines NEET program, and developing a new undergraduate curriculum. Underscoring the care she has for her students’ success and well-being, Olivetti also cultivated the Course 3 Industry Seminars, pairing undergraduates with individuals working in careers related to 3D printing, environmental consulting, and manufacturing, with the aim of assisting her students with employment opportunities.

      “Professor Olivetti is a brilliant teacher and a creative educator, who engages the classroom with an uncanny ability to keep students on the edge of their seats combined with a remarkable and signature style that creates learning moments they remember years later,” says Jeff Grossman, head of the Department of Materials Science and Engineering. “I am proud to have Elsa as a colleague, and I am delighted that her excellence has been recognized with the Bose Award.”

      Olivetti received her PhD in materials science and engineering from MIT in 2007; shortly after, she joined the department as a postdoc. She subsequently worked as a research scientist in the Materials Systems Lab from 2009 to 2013 and joined the DMSE faculty in 2014. She was recently named a 2021 MacVicar Faculty Fellow in recognition of her exceptional commitment to curricular innovation, scientific research, and improving the student experience through teaching, mentoring, and advising. Previously, she has received the Earll M. Murman Award for Excellence in Undergraduate Advising in 2017, the award for “best DMSE advisor” in 2019, and the Paul Gray Award for Public Service in 2020.

      The Bose Award for Excellence in Teaching is given annually to a faculty member whose contributions to education have been characterized by dedication, care, and creativity. Established in 1990 by the School of Engineering, the award stands as a tribute to the late Amar Bose, a professor of electrical engineering and computer science and the founder of the Bose Corporation, to recognize outstanding contributions to undergraduate education by members of its faculty. More