More stories

  • in

    Bubble findings could unlock better electrode and electrolyzer designs

    Industrial electrochemical processes that use electrodes to produce fuels and chemical products are hampered by the formation of bubbles that block parts of the electrode surface, reducing the area available for the active reaction. Such blockage reduces the performance of the electrodes by anywhere from 10 to 25 percent.But new research reveals a decades-long misunderstanding about the extent of that interference. The findings show exactly how the blocking effect works and could lead to new ways of designing electrode surfaces to minimize inefficiencies in these widely used electrochemical processes.It has long been assumed that the entire area of the electrode shadowed by each bubble would be effectively inactivated. But it turns out that a much smaller area — roughly the area where the bubble actually contacts the surface — is blocked from its electrochemical activity. The new insights could lead directly to new ways of patterning the surfaces to minimize the contact area and improve overall efficiency.The findings are reported today in the journal Nanoscale, in a paper by recent MIT graduate Jack Lake PhD ’23, graduate student Simon Rufer, professor of mechanical engineering Kripa Varanasi, research scientist Ben Blaiszik, and six others at the University of Chicago and Argonne National Laboratory. The team has made available an open-source, AI-based software tool that engineers and scientists can now use to automatically recognize and quantify bubbles formed on a given surface, as a first step toward controlling the electrode material’s properties.

    Play video

    Gas-evolving electrodes, often with catalytic surfaces that promote chemical reactions, are used in a wide variety of processes, including the production of “green” hydrogen without the use of fossil fuels, carbon-capture processes that can reduce greenhouse gas emissions, aluminum production, and the chlor-alkali process that is used to make widely used chemical products.These are very widespread processes. The chlor-alkali process alone accounts for 2 percent of all U.S. electricity usage; aluminum production accounts for 3 percent of global electricity; and both carbon capture and hydrogen production are likely to grow rapidly in coming years as the world strives to meet greenhouse-gas reduction targets. So, the new findings could make a real difference, Varanasi says.“Our work demonstrates that engineering the contact and growth of bubbles on electrodes can have dramatic effects” on how bubbles form and how they leave the surface, he says. “The knowledge that the area under bubbles can be significantly active ushers in a new set of design rules for high-performance electrodes to avoid the deleterious effects of bubbles.”“The broader literature built over the last couple of decades has suggested that not only that small area of contact but the entire area under the bubble is passivated,” Rufer says. The new study reveals “a significant difference between the two models because it changes how you would develop and design an electrode to minimize these losses.”To test and demonstrate the implications of this effect, the team produced different versions of electrode surfaces with patterns of dots that nucleated and trapped bubbles at different sizes and spacings. They were able to show that surfaces with widely spaced dots promoted large bubble sizes but only tiny areas of surface contact, which helped to make clear the difference between the expected and actual effects of bubble coverage.Developing the software to detect and quantify bubble formation was necessary for the team’s analysis, Rufer explains. “We wanted to collect a lot of data and look at a lot of different electrodes and different reactions and different bubbles, and they all look slightly different,” he says. Creating a program that could deal with different materials and different lighting and reliably identify and track the bubbles was a tricky process, and machine learning was key to making it work, he says.Using that tool, he says, they were able to collect “really significant amounts of data about the bubbles on a surface, where they are, how big they are, how fast they’re growing, all these different things.” The tool is now freely available for anyone to use via the GitHub repository.By using that tool to correlate the visual measures of bubble formation and evolution with electrical measurements of the electrode’s performance, the researchers were able to disprove the accepted theory and to show that only the area of direct contact is affected. Videos further proved the point, revealing new bubbles actively evolving directly under parts of a larger bubble.The researchers developed a very general methodology that can be applied to characterize and understand the impact of bubbles on any electrode or catalyst surface. They were able to quantify the bubble passivation effects in a new performance metric they call BECSA (Bubble-induced electrochemically active surface), as opposed to ECSA (electrochemically active surface area), that is used in the field. “The BECSA metric was a concept we defined in an earlier study but did not have an effective method to estimate until this work,” says Varanasi.The knowledge that the area under bubbles can be significantly active ushers in a new set of design rules for high-performance electrodes. This means that electrode designers should seek to minimize bubble contact area rather than simply bubble coverage, which can be achieved by controlling the morphology and chemistry of the electrodes. Surfaces engineered to control bubbles can not only improve the overall efficiency of the processes and thus reduce energy use, they can also save on upfront materials costs. Many of these gas-evolving electrodes are coated with catalysts made of expensive metals like platinum or iridium, and the findings from this work can be used to engineer electrodes to reduce material wasted by reaction-blocking bubbles.Varanasi says that “the insights from this work could inspire new electrode architectures that not only reduce the usage of precious materials, but also improve the overall electrolyzer performance,” both of which would provide large-scale environmental benefits.The research team included Jim James, Nathan Pruyne, Aristana Scourtas, Marcus Schwarting, Aadit Ambalkar, Ian Foster, and Ben Blaiszik at the University of Chicago and Argonne National Laboratory. The work was supported by the U.S. Department of Energy under the ARPA-E program. More

  • in

    Proton-conducting materials could enable new green energy technologies

    As the name suggests, most electronic devices today work through the movement of electrons. But materials that can efficiently conduct protons — the nucleus of the hydrogen atom — could be key to a number of important technologies for combating global climate change.Most proton-conducting inorganic materials available now require undesirably high temperatures to achieve sufficiently high conductivity. However, lower-temperature alternatives could enable a variety of technologies, such as more efficient and durable fuel cells to produce clean electricity from hydrogen, electrolyzers to make clean fuels such as hydrogen for transportation, solid-state proton batteries, and even new kinds of computing devices based on iono-electronic effects.In order to advance the development of proton conductors, MIT engineers have identified certain traits of materials that give rise to fast proton conduction. Using those traits quantitatively, the team identified a half-dozen new candidates that show promise as fast proton conductors. Simulations suggest these candidates will perform far better than existing materials, although they still need to be conformed experimentally. In addition to uncovering potential new materials, the research also provides a deeper understanding at the atomic level of how such materials work.The new findings are described in the journal Energy and Environmental Sciences, in a paper by MIT professors Bilge Yildiz and Ju Li, postdocs Pjotrs Zguns and Konstantin Klyukin, and their collaborator Sossina Haile and her students from Northwestern University. Yildiz is the Breene M. Kerr Professor in the departments of Nuclear Science and Engineering, and Materials Science and Engineering.“Proton conductors are needed in clean energy conversion applications such as fuel cells, where we use hydrogen to produce carbon dioxide-free electricity,” Yildiz explains. “We want to do this process efficiently, and therefore we need materials that can transport protons very fast through such devices.”Present methods of producing hydrogen, for example steam methane reforming, emit a great deal of carbon dioxide. “One way to eliminate that is to electrochemically produce hydrogen from water vapor, and that needs very good proton conductors,” Yildiz says. Production of other important industrial chemicals and potential fuels, such as ammonia, can also be carried out through efficient electrochemical systems that require good proton conductors.But most inorganic materials that conduct protons can only operate at temperatures of 200 to 600 degrees Celsius (roughly 450 to 1,100 Fahrenheit), or even higher. Such temperatures require energy to maintain and can cause degradation of materials. “Going to higher temperatures is not desirable because that makes the whole system more challenging, and the material durability becomes an issue,” Yildiz says. “There is no good inorganic proton conductor at room temperature.” Today, the only known room-temperature proton conductor is a polymeric material that is not practical for applications in computing devices because it can’t easily be scaled down to the nanometer regime, she says.To tackle the problem, the team first needed to develop a basic and quantitative understanding of exactly how proton conduction works, taking a class of inorganic proton conductors, called solid acids. “One has to first understand what governs proton conduction in these inorganic compounds,” she says. While looking at the materials’ atomic configurations, the researchers identified a pair of characteristics that directly relates to the materials’ proton-carrying potential.As Yildiz explains, proton conduction first involves a proton “hopping from a donor oxygen atom to an acceptor oxygen. And then the environment has to reorganize and take the accepted proton away, so that it can hop to another neighboring acceptor, enabling long-range proton diffusion.” This process happens in many inorganic solids, she says. Figuring out how that last part works — how the atomic lattice gets reorganized to take the accepted proton away from the original donor atom — was a key part of this research, she says.The researchers used computer simulations to study a class of materials called solid acids that become good proton conductors above 200 degrees Celsius. This class of materials has a substructure called the polyanion group sublattice, and these groups have to rotate and take the proton away from its original site so it can then transfer to other sites. The researchers were able to identify the phonons that contribute to the flexibility of this sublattice, which is essential for proton conduction. Then they used this information to comb through vast databases of theoretically and experimentally possible compounds, in search of better proton conducting materials.As a result, they found solid acid compounds that are promising proton conductors and that have been developed and produced for a variety of different applications but never before studied as proton conductors; these compounds turned out to have just the right characteristics of lattice flexibility. The team then carried out computer simulations of how the specific materials they identified in their initial screening would perform under relevant temperatures, to confirm their suitability as proton conductors for fuel cells or other uses. Sure enough, they found six promising materials, with predicted proton conduction speeds faster than the best existing solid acid proton conductors.“There are uncertainties in these simulations,” Yildiz cautions. “I don’t want to say exactly how much higher the conductivity will be, but these look very promising. Hopefully this motivates the experimental field to try to synthesize them in different forms and make use of these compounds as proton conductors.”Translating these theoretical findings into practical devices could take some years, she says. The likely first applications would be for electrochemical cells to produce fuels and chemical feedstocks such as hydrogen and ammonia, she says.The work was supported by the U.S. Department of Energy, the Wallenberg Foundation, and the U.S. National Science Foundation. More

  • in

    AI method radically speeds predictions of materials’ thermal properties

    It is estimated that about 70 percent of the energy generated worldwide ends up as waste heat.If scientists could better predict how heat moves through semiconductors and insulators, they could design more efficient power generation systems. However, the thermal properties of materials can be exceedingly difficult to model.The trouble comes from phonons, which are subatomic particles that carry heat. Some of a material’s thermal properties depend on a measurement called the phonon dispersion relation, which can be incredibly hard to obtain, let alone utilize in the design of a system.A team of researchers from MIT and elsewhere tackled this challenge by rethinking the problem from the ground up. The result of their work is a new machine-learning framework that can predict phonon dispersion relations up to 1,000 times faster than other AI-based techniques, with comparable or even better accuracy. Compared to more traditional, non-AI-based approaches, it could be 1 million times faster.This method could help engineers design energy generation systems that produce more power, more efficiently. It could also be used to develop more efficient microelectronics, since managing heat remains a major bottleneck to speeding up electronics.“Phonons are the culprit for the thermal loss, yet obtaining their properties is notoriously challenging, either computationally or experimentally,” says Mingda Li, associate professor of nuclear science and engineering and senior author of a paper on this technique.Li is joined on the paper by co-lead authors Ryotaro Okabe, a chemistry graduate student; and Abhijatmedhi Chotrattanapituk, an electrical engineering and computer science graduate student; Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering and Computer Science at MIT; as well as others at MIT, Argonne National Laboratory, Harvard University, the University of South Carolina, Emory University, the University of California at Santa Barbara, and Oak Ridge National Laboratory. The research appears in Nature Computational Science.Predicting phononsHeat-carrying phonons are tricky to predict because they have an extremely wide frequency range, and the particles interact and travel at different speeds.A material’s phonon dispersion relation is the relationship between energy and momentum of phonons in its crystal structure. For years, researchers have tried to predict phonon dispersion relations using machine learning, but there are so many high-precision calculations involved that models get bogged down.“If you have 100 CPUs and a few weeks, you could probably calculate the phonon dispersion relation for one material. The whole community really wants a more efficient way to do this,” says Okabe.The machine-learning models scientists often use for these calculations are known as graph neural networks (GNN). A GNN converts a material’s atomic structure into a crystal graph comprising multiple nodes, which represent atoms, connected by edges, which represent the interatomic bonding between atoms.While GNNs work well for calculating many quantities, like magnetization or electrical polarization, they are not flexible enough to efficiently predict an extremely high-dimensional quantity like the phonon dispersion relation. Because phonons can travel around atoms on X, Y, and Z axes, their momentum space is hard to model with a fixed graph structure.To gain the flexibility they needed, Li and his collaborators devised virtual nodes.They create what they call a virtual node graph neural network (VGNN) by adding a series of flexible virtual nodes to the fixed crystal structure to represent phonons. The virtual nodes enable the output of the neural network to vary in size, so it is not restricted by the fixed crystal structure.Virtual nodes are connected to the graph in such a way that they can only receive messages from real nodes. While virtual nodes will be updated as the model updates real nodes during computation, they do not affect the accuracy of the model.“The way we do this is very efficient in coding. You just generate a few more nodes in your GNN. The physical location doesn’t matter, and the real nodes don’t even know the virtual nodes are there,” says Chotrattanapituk.Cutting out complexitySince it has virtual nodes to represent phonons, the VGNN can skip many complex calculations when estimating phonon dispersion relations, which makes the method more efficient than a standard GNN. The researchers proposed three different versions of VGNNs with increasing complexity. Each can be used to predict phonons directly from a material’s atomic coordinates.Because their approach has the flexibility to rapidly model high-dimensional properties, they can use it to estimate phonon dispersion relations in alloy systems. These complex combinations of metals and nonmetals are especially challenging for traditional approaches to model.The researchers also found that VGNNs offered slightly greater accuracy when predicting a material’s heat capacity. In some instances, prediction errors were two orders of magnitude lower with their technique.A VGNN could be used to calculate phonon dispersion relations for a few thousand materials in just a few seconds with a personal computer, Li says.This efficiency could enable scientists to search a larger space when seeking materials with certain thermal properties, such as superior thermal storage, energy conversion, or superconductivity.Moreover, the virtual node technique is not exclusive to phonons, and could also be used to predict challenging optical and magnetic properties.In the future, the researchers want to refine the technique so virtual nodes have greater sensitivity to capture small changes that can affect phonon structure.“Researchers got too comfortable using graph nodes to represent atoms, but we can rethink that. Graph nodes can be anything. And virtual nodes are a very generic approach you could use to predict a lot of high-dimensional quantities,” Li says.“The authors’ innovative approach significantly augments the graph neural network description of solids by incorporating key physics-informed elements through virtual nodes, for instance, informing wave-vector dependent band-structures and dynamical matrices,” says Olivier Delaire, associate professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University, who was not involved with this work. “I find that the level of acceleration in predicting complex phonon properties is amazing, several orders of magnitude faster than a state-of-the-art universal machine-learning interatomic potential. Impressively, the advanced neural net captures fine features and obeys physical rules. There is great potential to expand the model to describe other important material properties: Electronic, optical, and magnetic spectra and band structures come to mind.”This work is supported by the U.S. Department of Energy, National Science Foundation, a Mathworks Fellowship, a Sow-Hsin Chen Fellowship, the Harvard Quantum Initiative, and the Oak Ridge National Laboratory. More

  • in

    How to increase the rate of plastics recycling

    While recycling systems and bottle deposits have become increasingly widespread in the U.S., actual rates of recycling are “abysmal,” according to a team of MIT researchers who studied the rates for recycling of PET, the plastic commonly used in beverage bottles. However, their findings suggest some ways to change this.The present rate of recycling for PET, or polyethylene terephthalate, bottles nationwide is about 24 percent and has remained stagnant for a decade, the researchers say. But their study indicates that with a nationwide bottle deposit program, the rates could increase to 82 percent, with nearly two-thirds of all PET bottles being recycled into new bottles, at a net cost of just a penny a bottle when demand is robust. At the same time, they say, policies would be needed to ensure a sufficient demand for the recycled material.The findings are being published today in the Journal of Industrial Ecology, in a paper by MIT professor of materials science and engineering Elsa Olivetti, graduate students Basuhi Ravi and Karan Bhuwalka, and research scientist Richard Roth.The team looked at PET bottle collection and recycling rates in different states as well as other nations with and without bottle deposit policies, and with or without curbside recycling programs, as well as the inputs and outputs of various recycling companies and methods. The researchers say this study is the first to look in detail at the interplay between public policies and the end-to-end realities of the packaging production and recycling market.They found that bottle deposit programs are highly effective in the areas where they are in place, but at present there is not nearly enough collection of used bottles to meet the targets set by the packaging industry. Their analysis suggests that a uniform nationwide bottle deposit policy could achieve the levels of recycling that have been mandated by proposed legislation and corporate commitments.The recycling of PET is highly successful in terms of quality, with new products made from all-recycled material virtually matching the qualities of virgin material. And brands have shown that new bottles can be safely made with 100 percent postconsumer waste. But the team found that collection of the material is a crucial bottleneck that leaves processing plants unable to meet their needs. However, with the right policies in place, “one can be optimistic,” says Olivetti, who is the Jerry McAfee Professor in Engineering and the associate dean of the School of Engineering.“A message that we have found in a number of cases in the recycling space is that if you do the right work to support policies that think about both the demand but also the supply,” then significant improvements are possible, she says. “You have to think about the response and the behavior of multiple actors in the system holistically to be viable,” she says. “We are optimistic, but there are many ways to be pessimistic if we’re not thinking about that in a holistic way.”For example, the study found that it is important to consider the needs of existing municipal waste-recovery facilities. While expanded bottle deposit programs are essential to increase recycling rates and provide the feedstock to companies recycling PET into new products, the current facilities that process material from curbside recycling programs will lose revenue from PET bottles, which are a relatively high-value product compared to the other materials in the recycled waste stream. These companies would lose a source of their income if the bottles are collected through deposit programs, leaving them with only the lower-value mixed plastics.The researchers developed economic models based on rates of collection found in the states with deposit programs, recycled-content requirements, and other policies, and used these models to extrapolate to the nation as a whole. Overall, they found that the supply needs of packaging producers could be met through a nationwide bottle deposit system with a 10-cent deposit per bottle — at a net cost of about 1 cent per bottle produced when demand is strong. This need not be a federal program, but rather one where the implementation would be left up to the individual states, Olivetti says.Other countries have been much more successful in implementing deposit systems that result in very high participation rates. Several European countries manage to collect more than 90 percent of PET bottles for recycling, for example. But in the U.S., less than 29 percent are collected, and after losses in the recycling chain about 24 percent actually get recycled, the researchers found. Whereas 73 percent of Americans have access to curbside recycling, presently only 10 states have bottle deposit systems in place.Yet the demand is there so far. “There is a market for this material,” says Olivetti. While bottles collected through mixed-waste collection can still be recycled to some extent, those collected through deposit systems tend to be much cleaner and require less processing, and so are more economical to recycle into new bottles, or into textiles.To be effective, policies need to not just focus on increasing rates of recycling, but on the whole cycle of supply and demand and the different players involved, Olivetti says. Safeguards would need to be in place to protect existing recycling facilities from the lost revenues they would suffer as a result of bottle deposits, perhaps in the form of subsidies funded by fees on the bottle producers, to avoid putting these essential parts of the processing chain out of business. And other policies may be needed to ensure the continued market for the material that gets collected, including recycled content requirements and extended producer responsibility regulations, the team found.At this stage, it’s important to focus on the specific waste streams that can most effectively be recycled, and PET, along with many metals, clearly fit that category. “When we start to think about mixed plastic streams, that’s much more challenging from an environmental perspective,” she says. “Recycling systems need to be pursuing extended producers’ responsibility, or specifically thinking about materials designed more effectively toward recycled content,” she says.It’s also important to address “what the right metrics are to design for sustainably managed materials streams,” she says. “It could be energy use, could be circularity [for example, making old bottles into new bottles], could be around waste reduction, and making sure those are all aligned. That’s another kind of policy coordination that’s needed.” More

  • in

    Researchers develop a detector for continuously monitoring toxic gases

    Most systems used to detect toxic gases in industrial or domestic settings can be used only once, or at best a few times. Now, researchers at MIT have developed a detector that could provide continuous monitoring for the presence of these gases, at low cost.The new system combines two existing technologies, bringing them together in a way that preserves the advantages of each while avoiding their limitations. The team used a material called a metal-organic framework, or MOF, which is highly sensitive to tiny traces of gas but whose performance quickly degrades, and combined it with a polymer material that is highly durable and easier to process, but much less sensitive.The results are reported today in the journal Advanced Materials, in a paper by MIT professors Aristide Gumyusenge, Mircea Dinca, Heather Kulik, and Jesus del Alamo, graduate student Heejung Roh, and postdocs Dong-Ha Kim, Yeongsu Cho, and Young-Moo Jo.Highly porous and with large surface areas, MOFs come in a variety of compositions. Some can be insulators, but the ones used for this work are highly electrically conductive. With their sponge-like form, they are effective at capturing molecules of various gases, and the sizes of their pores can be tailored to make them selective for particular kinds of gases. “If you are using them as a sensor, you can recognize if the gas is there if it has an effect on the resistivity of the MOF,” says Gumyusenge, the paper’s senior author and the Merton C. Flemings Career Development Assistant Professor of Materials Science and Engineering.The drawback for these materials’ use as detectors for gases is that they readily become saturated, and then can no longer detect and quantify new inputs. “That’s not what you want. You want to be able to detect and reuse,” Gumyusenge says. “So, we decided to use a polymer composite to achieve this reversibility.”The team used a class of conductive polymers that Gumyusenge and his co-workers had previously shown can respond to gases without permanently binding to them. “The polymer, even though it doesn’t have the high surface area that the MOFs do, will at least provide this recognize-and-release type of phenomenon,” he says.The team combined the polymers in a liquid solution along with the MOF material in powdered form, and deposited the mixture on a substrate, where they dry into a uniform, thin coating. By combining the polymer, with its quick detection capability, and the more sensitive MOFs, in a one-to-one ratio, he says, “suddenly we get a sensor that has both the high sensitivity we get from the MOF and the reversibility that is enabled by the presence of the polymer.”The material changes its electrical resistance when molecules of the gas are temporarily trapped in the material. These changes in resistance can be continuously monitored by simply attaching an ohmmeter to track the resistance over time. Gumyusenge and his students demonstrated the composite material’s ability to detect nitrogen dioxide, a toxic gas produced by many kinds of combustion, in a small lab-scale device. After 100 cycles of detection, the material was still maintaining its baseline performance within a margin of about 5 to 10 percent, demonstrating its long-term use potential.In addition, this material has far greater sensitivity than most presently used detectors for nitrogen dioxide, the team reports. This gas is often detected after the use of stove ovens. And, with this gas recently linked to many asthma cases in the U.S., reliable detection in low concentrations is important. The team demonstrated that this new composite could detect, reversibly, the gas at concentrations as low as 2 parts per million.While their demonstration was specifically aimed at nitrogen dioxide, Gumyusenge says, “we can definitely tailor the chemistry to target other volatile molecules,” as long as they are small polar analytes, “which tend to be most of the toxic gases.”Besides being compatible with a simple hand-held detector or a smoke-alarm type of device, one advantage of the material is that the polymer allows it to be deposited as an extremely thin uniform film, unlike regular MOFs, which are generally in an inefficient powder form. Because the films are so thin, there is little material needed and production material costs could be low; the processing methods could be typical of those used for industrial coating processes. “So, maybe the limiting factor will be scaling up the synthesis of the polymers, which we’ve been synthesizing in small amounts,” Gumyusenge says.“The next steps will be to evaluate these in real-life settings,” he says. For example, the material could be applied as a coating on chimneys or exhaust pipes to continuously monitor gases through readings from an attached resistance monitoring device. In such settings, he says, “we need tests to check if we truly differentiate it from other potential contaminants that we might have overlooked in the lab setting. Let’s put the sensors out in real-world scenarios and see how they do.”The work was supported by the MIT Climate and Sustainability Consortium (MCSC), the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) at MIT, and the U.S. Department of Energy. More

  • in

    Scientists develop an affordable sensor for lead contamination

    Engineers at MIT, Nanytang Technological University, and several companies have developed a compact and inexpensive technology for detecting and measuring lead concentrations in water, potentially enabling a significant advance in tackling this persistent global health issue.The World Health Organization estimates that 240 million people worldwide are exposed to drinking water that contains unsafe amounts of toxic lead, which can affect brain development in children, cause birth defects, and produce a variety of neurological, cardiac, and other damaging effects. In the United States alone, an estimated 10 million households still get drinking water delivered through lead pipes.“It’s an unaddressed public health crisis that leads to over 1 million deaths annually,” says Jia Xu Brian Sia, an MIT postdoc and the senior author of the paper describing the new technology.But testing for lead in water requires expensive, cumbersome equipment and typically requires days to get results. Or, it uses simple test strips that simply reveal a yes-or-no answer about the presence of lead but no information about its concentration. Current EPA regulations require drinking water to contain no more that 15 parts per billion of lead, a concentration so low it is difficult to detect.The new system, which could be ready for commercial deployment within two or three years, could detect lead concentrations as low as 1 part per billion, with high accuracy, using a simple chip-based detector housed in a handheld device. The technology gives nearly instant quantitative measurements and requires just a droplet of water.The findings are described in a paper appearing today in the journal Nature Communications, by Sia, MIT graduate student and lead author Luigi Ranno, Professor Juejun Hu, and 12 others at MIT and other institutions in academia and industry.The team set out to find a simple detection method based on the use of photonic chips, which use light to perform measurements. The challenging part was finding a way to attach to the photonic chip surface certain ring-shaped molecules known as crown ethers, which can capture specific ions such as lead. After years of effort, they were able to achieve that attachment via a chemical process known as Fischer esterification. “That is one of the essential breakthroughs we have made in this technology,” Sia says.In testing the new chip, the researchers showed that it can detect lead in water at concentrations as low as one part per billion. At much higher concentrations, which may be relevant for testing environmental contamination such as mine tailings, the accuracy is within 4 percent.The device works in water with varying levels of acidity, ranging from pH values of 6 to 8, “which covers most environmental samples,” Sia says. They have tested the device with seawater as well as tap water, and verified the accuracy of the measurements.In order to achieve such levels of accuracy, current testing requires a device called an inductive coupled plasma mass spectrometer. “These setups can be big and expensive,” Sia says. The sample processing can take days and requires experienced technical personnel.While the new chip system they developed is “the core part of the innovation,” Ranno says, further work will be needed to develop this into an integrated, handheld device for practical use. “For making an actual product, you would need to package it into a usable form factor,” he explains. This would involve having a small chip-based laser coupled to the photonic chip. “It’s a matter of mechanical design, some optical design, some chemistry, and figuring out the supply chain,” he says. While that takes time, he says, the underlying concepts are straightforward.The system can be adapted to detect other similar contaminants in water, including cadmium, copper, lithium, barium, cesium, and radium, Ranno says. The device could be used with simple cartridges that can be swapped out to detect different elements, each using slightly different crown ethers that can bind to a specific ion.“There’s this problem that people don’t measure their water enough, especially in the developing countries,” Ranno says. “And that’s because they need to collect the water, prepare the sample, and bring it to these huge instruments that are extremely expensive.” Instead, “having this handheld device, something compact that even untrained personnel can just bring to the source for on-site monitoring, at low costs,” could make regular, ongoing widespread testing feasible.Hu, who is the John F. Elliott Professor of Materials Science and Engineering, says, “I’m hoping this will be quickly implemented, so we can benefit human society. This is a good example of a technology coming from a lab innovation where it may actually make a very tangible impact on society, which is of course very fulfilling.”“If this study can be extended to simultaneous detection of multiple metal elements, especially the presently concerning radioactive elements, its potential would be immense,” says Hou Wang, an associate professor of environmental science and engineering at Hunan University in China, who was not associated with this work.Wang adds, “This research has engineered a sensor capable of instantaneously detecting lead concentration in water. This can be utilized in real-time to monitor the lead pollution concentration in wastewater discharged from industries such as battery manufacturing and lead smelting, facilitating the establishment of industrial wastewater monitoring systems. I think the innovative aspects and developmental potential of this research are quite commendable.”Wang Qian, a principal research scientist at the Institute of Materials Research in Singapore, who also was not affiliated with this work, says, “The ability for the pervasive, portable, and quantitative detection of lead has proved to be challenging primarily due to cost concerns. This work demonstrates the potential to do so in a highly integrated form factor and is compatible with large-scale, low-cost manufacturing.”The team included researchers at MIT, at Nanyang Technological University and Temasek Laboratories in Singapore, at the University of Southampton in the U.K., and at companies Fingate Technologies, in Singapore, and Vulcan Photonics, headquartered in Malaysia. The work used facilities at MIT.nano, the Harvard University Center for Nanoscale Systems, NTU’s Center for Micro- and Nano-Electronics, and the Nanyang Nanofabrication Center. More

  • in

    Two MIT teams selected for NSF sustainable materials grants

    Two teams led by MIT researchers were selected in December 2023 by the U.S. National Science Foundation (NSF) Convergence Accelerator, a part of the TIP Directorate, to receive awards of $5 million each over three years, to pursue research aimed at helping to bring cutting-edge new sustainable materials and processes from the lab into practical, full-scale industrial production. The selection was made after 16 teams from around the country were chosen last year for one-year grants to develop detailed plans for further research aimed at solving problems of sustainability and scalability for advanced electronic products.

    Of the two MIT-led teams chosen for this current round of funding, one team, Topological Electric, is led by Mingda Li, an associate professor in the Department of Nuclear Science and Engineering. This team will be finding pathways to scale up sustainable topological materials, which have the potential to revolutionize next-generation microelectronics by showing superior electronic performance, such as dissipationless states or high-frequency response. The other team, led by Anuradha Agarwal, a principal research scientist at MIT’s Materials Research Laboratory, will be focusing on developing new materials, devices, and manufacturing processes for microchips that minimize energy consumption using electronic-photonic integration, and that detect and avoid the toxic or scarce materials used in today’s production methods.

    Scaling the use of topological materials

    Li explains that some materials based on quantum effects have achieved successful transitions from lab curiosities to successful mass production, such as blue-light LEDs, and giant magnetorestance (GMR) devices used for magnetic data storage. But he says there are a variety of equally promising materials that have shown promise but have yet to make it into real-world applications.

    “What we really wanted to achieve is to bring newer-generation quantum materials into technology and mass production, for the benefit of broader society,” he says. In particular, he says, “topological materials are really promising to do many different things.”

    Topological materials are ones whose electronic properties are fundamentally protected against disturbance. For example, Li points to the fact that just in the last two years, it has been shown that some topological materials are even better electrical conductors than copper, which are typically used for the wires interconnecting electronic components. But unlike the blue-light LEDs or the GMR devices, which have been widely produced and deployed, when it comes to topological materials, “there’s no company, no startup, there’s really no business out there,” adds Tomas Palacios, the Clarence J. Lebel Professor in Electrical Engineering at MIT and co-principal investigator on Li’s team. Part of the reason is that many versions of such materials are studied “with a focus on fundamental exotic physical properties with little or no consideration on the sustainability aspects,” says Liang Fu, an MIT professor of physics and also a co-PI. Their team will be looking for alternative formulations that are more amenable to mass production.

    One possible application of these topological materials is for detecting terahertz radiation, explains Keith Nelson, an MIT professor of chemistry and co-PI. This extremely high-frequency electronics can carry far more information than conventional radio or microwaves, but at present there are no mature electronic devices available that are scalable at this frequency range. “There’s a whole range of possibilities for topological materials” that could work at these frequencies, he says. In addition, he says, “we hope to demonstrate an entire prototype system like this in a single, very compact solid-state platform.”

    Li says that among the many possible applications of topological devices for microelectronics devices of various kinds, “we don’t know which, exactly, will end up as a product, or will reach real industrial scaleup. That’s why this opportunity from NSF is like a bridge, which is precious, to allow us to dig deeper to unleash the true potential.”

    In addition to Li, Palacios, Fu, and Nelson, the Topological Electric team includes Qiong Ma, assistant professor of physics in Boston College; Farnaz Niroui, assistant professor of electrical engineering and computer science at MIT; Susanne Stemmer, professor of materials at the University of California at Santa Barbara; Judy Cha, professor of materials science and engineering at Cornell University; industrial partners including IBM, Analog Devices, and Raytheon; and professional consultants. “We are taking this opportunity seriously,” Li says. “We really want to see if the topological materials are as good as we show in the lab when being scaled up, and how far we can push to broadly industrialize them.”

    Toward sustainable microchip production and use

    The microchips behind everything from smartphones to medical imaging are associated with a significant percentage of greenhouse gas emissions today, and every year the world produces more than 50 million metric tons of electronic waste, the equivalent of about 5,000 Eiffel Towers. Further, the data centers necessary for complex computations and huge amount of data transfer — think AI and on-demand video — are growing and will require 10 percent of the world’s electricity by 2030.

    “The current microchip manufacturing supply chain, which includes production, distribution, and use, is neither scalable nor sustainable, and cannot continue. We must innovate our way out of this crisis,” says Agarwal.

    The name of Agarwal’s team, FUTUR-IC, is a reference to the future of the integrated circuits, or chips, through a global alliance for sustainable microchip manufacturing. Says Agarwal, “We bring together stakeholders from industry, academia, and government to co-optimize across three dimensions: technology, ecology, and workforce. These were identified as key interrelated areas by some 140 stakeholders. With FUTUR-IC we aim to cut waste and CO2-equivalent emissions associated with electronics by 50 percent every 10 years.”

    The market for microelectronics in the next decade is predicted to be on the order of a trillion dollars, but most of the manufacturing for the industry occurs only in limited geographical pockets around the world. FUTUR-IC aims to diversify and strengthen the supply chain for manufacturing and packaging of electronics. The alliance has 26 collaborators and is growing. Current external collaborators include the International Electronics Manufacturing Initiative (iNEMI), Tyndall National Institute, SEMI, Hewlett Packard Enterprise, Intel, and the Rochester Institute of Technology.

    Agarwal leads FUTUR-IC in close collaboration with others, including, from MIT, Lionel Kimerling, the Thomas Lord Professor of Materials Science and Engineering; Elsa Olivetti, the Jerry McAfee Professor in Engineering; Randolph Kirchain, principal research scientist in the Materials Research Laboratory; and Greg Norris, director of MIT’s Sustainability and Health Initiative for NetPositive Enterprise (SHINE). All are affiliated with the Materials Research Laboratory. They are joined by Samuel Serna, an MIT visiting professor and assistant professor of physics at Bridgewater State University. Other key personnel include Sajan Saini, education director for the Initiative for Knowledge and Innovation in Manufacturing in MIT’s Department of Materials Science and Engineering; Peter O’Brien, a professor from Tyndall National Institute; and Shekhar Chandrashekhar, CEO of iNEMI.

    “We expect the integration of electronics and photonics to revolutionize microchip manufacturing, enhancing efficiency, reducing energy consumption, and paving the way for unprecedented advancements in computing speed and data-processing capabilities,” says Serna, who is the co-lead on the project’s technology “vector.”

    Common metrics for these efforts are needed, says Norris, co-lead for the ecology vector, adding, “The microchip industry must have transparent and open Life Cycle Assessment (LCA) models and data, which are being developed by FUTUR-IC.” This is especially important given that microelectronics production transcends industries. “Given the scale and scope of microelectronics, it is critical for the industry to lead in the transition to sustainable manufacture and use,” says Kirchain, another co-lead and the co-director of the Concrete Sustainability Hub at MIT. To bring about this cross-fertilization, co-lead Olivetti, also co-director of the MIT Climate and Sustainability Consortium (MCSC), will collaborate with FUTUR-IC to enhance the benefits from microchip recycling, leveraging the learning across industries.

    Saini, the co-lead for the workforce vector, stresses the need for agility. “With a workforce that adapts to a practice of continuous upskilling, we can help increase the robustness of the chip-manufacturing supply chain, and validate a new design for a sustainability curriculum,” he says.

    “We have become accustomed to the benefits forged by the exponential growth of microelectronic technology performance and market size,” says Kimerling, who is also director of MIT’s Materials Research Laboratory and co-director of the MIT Microphotonics Center. “The ecological impact of this growth in terms of materials use, energy consumption and end-of-life disposal has begun to push back against this progress. We believe that concurrently engineered solutions for these three dimensions will build a common learning curve to power the next 40 years of progress in the semiconductor industry.”

    The MIT teams are two of six that received awards addressing sustainable materials for global challenges through phase two of the NSF Convergence Accelerator program. Launched in 2019, the program targets solutions to especially compelling challenges at an accelerated pace by incorporating a multidisciplinary research approach. More

  • in

    Reducing pesticide use while increasing effectiveness

    Farming can be a low-margin, high-risk business, subject to weather and climate patterns, insect population cycles, and other unpredictable factors. Farmers need to be savvy managers of the many resources they deal, and chemical fertilizers and pesticides are among their major recurring expenses.

    Despite the importance of these chemicals, a lack of technology that monitors and optimizes sprays has forced farmers to rely on personal experience and rules of thumb to decide how to apply these chemicals. As a result, these chemicals tend to be over-sprayed, leading to their runoff into waterways and buildup up in the soil.

    That could change, thanks to a new approach of feedback-optimized spraying, invented by AgZen, an MIT spinout founded in 2020 by Professor Kripa Varanasi and Vishnu Jayaprakash SM ’19, PhD ’22.

    Play video

    AgZen has developed a system for farming that can monitor exactly how much of the sprayed chemicals adheres to plants, in real time, as the sprayer drives through a field. Built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray.

    Over the past decade, AgZen’s founders have developed products and technologies to control the interactions of droplets and sprays with plant surfaces. The Boston-based venture-backed company launched a new commercial product in 2024 and is currently piloting another related product. Field tests of both have shown the products can help farmers spray more efficiently and effectively, using fewer chemicals overall.

    “Worldwide, farms spend approximately $60 billion a year on pesticides. Our objective is to reduce the number of pesticides sprayed and lighten the financial burden on farms without sacrificing effective pest management,” Varanasi says.

    Getting droplets to stick

    While the world pesticide market is growing rapidly, a lot of the pesticides sprayed don’t reach their target. A significant portion bounces off the plant surfaces, lands on the ground, and becomes part of the runoff that flows to streams and rivers, often causing serious pollution. Some of these pesticides can be carried away by wind over very long distances.

    “Drift, runoff, and poor application efficiency are well-known, longstanding problems in agriculture, but we can fix this by controlling and monitoring how sprayed droplets interact with leaves,” Varanasi says.

    With support from MIT Tata Center and the Abdul Latif Jameel Water and Food Systems Lab, Varanasi and his team analyzed how droplets strike plant surfaces, and explored ways to increase application efficiency. This research led them to develop a novel system of nozzles that cloak droplets with compounds that enhance the retention of droplets on the leaves, a product they call EnhanceCoverage.

    Field studies across regions — from Massachusetts to California to Italy and France —showed that this droplet-optimization system could allow farmers to cut the amount of chemicals needed by more than half because more of the sprayed substances would stick to the leaves.

    Measuring coverage

    However, in trying to bring this technology to market, the researchers faced a sticky problem: Nobody knew how well pesticide sprays were adhering to the plants in the first place, so how could AgZen say that the coverage was better with its new EnhanceCoverage system?

    “I had grown up spraying with a backpack on a small farm in India, so I knew this was an issue,” Jayaprakash says. “When we spoke to growers, they told me how complicated spraying is when you’re on a large machine. Whenever you spray, there are so many things that can influence how effective your spray is. How fast do you drive the sprayer? What flow rate are you using for the chemicals? What chemical are you using? What’s the age of the plants, what’s the nozzle you’re using, what is the weather at the time? All these things influence agrochemical efficiency.”

    Agricultural spraying essentially comes down to dissolving a chemical in water and then spraying droplets onto the plants. “But the interaction between a droplet and the leaf is complex,” Varanasi says. “We were coming in with ways to optimize that, but what the growers told us is, hey, we’ve never even really looked at that in the first place.”

    Although farmers have been spraying agricultural chemicals on a large scale for about 80 years, they’ve “been forced to rely on general rules of thumb and pick all these interlinked parameters, based on what’s worked for them in the past. You pick a set of these parameters, you go spray, and you’re basically praying for outcomes in terms of how effective your pest control is,” Varanasi says.

    Before AgZen could sell farmers on the new system to improve droplet coverage, the company had to invent a way to measure precisely how much spray was adhering to plants in real-time.

    Comparing before and after

    The system they came up with, which they tested extensively on farms across the country last year, involves a unit that can be bolted onto the spraying arm of virtually any sprayer. It carries two sensor stacks, one just ahead of the sprayer nozzles and one behind. Then, built-in software running on a tablet shows the operator exactly how much of each leaf has been covered by the spray. It also computes how much those droplets will spread out or evaporate, leading to a precise estimate of the final coverage.

    “There’s a lot of physics that governs how droplets spread and evaporate, and this has been incorporated into software that a farmer can use,” Varanasi says. “We bring a lot of our expertise into understanding droplets on leaves. All these factors, like how temperature and humidity influence coverage, have always been nebulous in the spraying world. But now you have something that can be exact in determining how well your sprays are doing.”

    “We’re not only measuring coverage, but then we recommend how to act,” says Jayaprakash, who is AgZen’s CEO. “With the information we collect in real-time and by using AI, RealCoverage tells operators how to optimize everything on their sprayer, from which nozzle to use, to how fast to drive, to how many gallons of spray is best for a particular chemical mix on a particular acre of a crop.”

    The tool was developed to prove how much AgZen’s EnhanceCoverage nozzle system (which will be launched in 2025) improves coverage. But it turns out that monitoring and optimizing droplet coverage on leaves in real-time with this system can itself yield major improvements.

    “We worked with large commercial farms last year in specialty and row crops,” Jayaprakash says. “When we saved our pilot customers up to 50 percent of their chemical cost at a large scale, they were very surprised.” He says the tool has reduced chemical costs and volume in fallow field burndowns, weed control in soybeans, defoliation in cotton, and fungicide and insecticide sprays in vegetables and fruits. Along with data from commercial farms, field trials conducted by three leading agricultural universities have also validated these results.

    “Across the board, we were able to save between 30 and 50 percent on chemical costs and increase crop yields by enabling better pest control,” Jayaprakash says. “By focusing on the droplet-leaf interface, our product can help any foliage spray throughout the year, whereas most technological advancements in this space recently have been focused on reducing herbicide use alone.” The company now intends to lease the system across thousands of acres this year.

    And these efficiency gains can lead to significant returns at scale, he emphasizes: In the U.S., farmers currently spend $16 billion a year on chemicals, to protect about $200 billion of crop yields.

    The company launched its first product, the coverage optimization system called RealCoverage, this year, reaching a wide variety of farms with different crops and in different climates. “We’re going from proof-of-concept with pilots in large farms to a truly massive scale on a commercial basis with our lease-to-own program,” Jayaprakash says.

    “We’ve also been tapped by the USDA to help them evaluate practices to minimize pesticides in watersheds,” Varanasi says, noting that RealCoverage can also be useful for regulators, chemical companies, and agricultural equipment manufacturers.

    Once AgZen has proven the effectiveness of using coverage as a decision metric, and after the RealCoverage optimization system is widely in practice, the company will next roll out its second product, EnhanceCoverage, designed to maximize droplet adhesion. Because that system will require replacing all the nozzles on a sprayer, the researchers are doing pilots this year but will wait for a full rollout in 2025, after farmers have gained experience and confidence with their initial product.

    “There is so much wastage,” Varanasi says. “Yet farmers must spray to protect crops, and there is a lot of environmental impact from this. So, after all this work over the years, learning about how droplets stick to surfaces and so on, now the culmination of it in all these products for me is amazing, to see all this come alive, to see that we’ll finally be able to solve the problem we set out to solve and help farmers.” More