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    Assay determines the percentage of Omicron, other variants in Covid wastewater

    Wastewater monitoring emerged amid the Covid-19 pandemic as an effective and noninvasive way to track a viral outbreak, and advances in the technology have enabled researchers to not only identify but also quantify the presence of particular variants of concern (VOCs) in wastewater samples.

    Last year, researchers with the Singapore-MIT Alliance for Research and Technology (SMART) made the news for developing a quantitative assay for the Alpha variant of SARS-CoV-2 in wastewater, while also working on a similar assay for the Delta variant. Previously, conventional wastewater detection methods could only detect the presence of SARS-CoV-2 viral material in a sample, without identifying the variant of the virus.

    Now, a team at SMART has developed a quantitative RT-qPCR assay that can detect the Omicron variant of SARS-CoV-2. This type of assay enables wastewater surveillance to accurately trace variant dynamics in any given community or population, and support and inform the implementation of appropriate public health measures tailored according to the specific traits of a particular viral pathogen.

    The capacity to count and assess particular VOCs is unique to SMART’s open-source assay, and allows researchers to accurately determine displacement trends in a community. Hence, the new assay can reveal what proportion of SARS-CoV-2 virus circulating in a community belongs to a particular variant. This is particularly significant, as different SARS-CoV-2 VOCs — Alpha, Delta, Omicron, and their offshoots — have emerged at various points throughout the pandemic, each causing a new wave of infections to which the population was more susceptible.

    The team’s new allele-specific RT-qPCR assay is described in a paper, “Rapid displacement of SARS-CoV-2 variant Delta by Omicron revealed by allele-specific PCR in wastewater,” published this month in Water Research. Senior author on the work is Eric Alm, professor of biological engineering at MIT and a principal investigator in the Antimicrobial Resistance (AMR) interdisciplinary research group within SMART, MIT’s research enterprise in Singapore. Co-authors include researchers from Nanyang Technological University (NTU), Singapore National University (NUS), MIT, Singapore Centre for Environmental Life Sciences Engineering (SCELSE), and Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia Romagna (IZSLER) in Italy.

    Omicron overtakes delta within three weeks in Italy study

    In their study, SMART researchers found that the increase in booster vaccine population coverage in Italy concurred with the complete displacement of the Delta variant by the Omicron variant in wastewater samples obtained from the Torbole Casaglia wastewater treatment plant, with a catchment size of 62,722 people. Taking less than three weeks, the rapid pace of this displacement can be attributed to Omicron’s infection advantage over the previously dominant Delta in vaccinated individuals, which may stem from Omicron’s more efficient evasion of vaccination-induced immunity.

    “In a world where Covid-19 is endemic, the monitoring of VOCs through wastewater surveillance will be an effective tool for the tracking of variants circulating in the community and will play an increasingly important role in guiding public health response,” says paper co-author Federica Armas, a senior postdoc at SMART AMR. “This work has demonstrated that wastewater surveillance can be used to quickly and quantitatively trace VOCs present in a community.”

    Wastewater surveillance vital for future pandemic responses

    As the global population becomes increasingly vaccinated and exposed to prior infections, nations have begun transitioning toward the classification of SARS-CoV-2 as an endemic disease, rolling back active clinical surveillance toward decentralized antigen rapid tests, and consequently reducing sequencing of patient samples. However, SARS-CoV-2 has been shown to produce novel VOCs that can swiftly emerge and spread rapidly across populations, displacing previously dominant variants of the virus. This was observed when Delta displaced Alpha across the globe after the former’s emergence in India in December 2020, and again when Omicron displaced Delta at an even faster rate following its discovery in South Africa in November 2021. The continuing emergence of novel VOCs therefore necessitates continued vigilance on the monitoring of circulating SARS-CoV-2 variants in communities.

    In a separate review paper on wastewater surveillance titled “Making Waves: Wastewater Surveillance of SARS-CoV-2 in an Endemic Future,” published in the journal Water Research, SMART researchers and collaborators found that the utility of wastewater surveillance in the near future could include 1) monitoring the trend of viral loads in wastewater for quantified viral estimates circulating in a community; 2) sampling of wastewater at the source — e.g., taking samples from particular neighborhoods or buildings — for pinpointing infections in neighborhoods and at the building level; 3) integrating wastewater and clinical surveillance for cost-efficient population surveillance; and 4) genome sequencing wastewater samples to track circulating and emerging variants in the population.

    “Our experience with SARS-CoV-2 has shown that clinical testing can often only paint a limited picture of the true extent of an outbreak or pandemic. With Covid-19 becoming prevalent and with the anticipated emergence of further variants of concern, qualitative and quantitative data from wastewater surveillance will be an integral component of a cost- and resource-efficient public health surveillance program, empowering authorities to make more informed policy decisions,” adds corresponding author Janelle Thompson, associate professor at SCELSE and NTU. “Our review provides a roadmap for the wider deployment of wastewater surveillance, with opportunities and challenges that, if addressed, will enable us to not only better manage Covid-19, but also future-proof societies for other viral pathogens and future pandemics.”

    In addition, the review suggests that future wastewater research should comply with a set of standardized wastewater processing methods to reduce inconsistencies in wastewater data toward improving epidemiological inference. Methods developed in the context of SARS-CoV-2 and its analyses could be of invaluable benefit for future wastewater monitoring work on discovering emerging zoonotic pathogens — pathogens that can be transmitted from animals to humans — and for early detection of future pandemics.

    Furthermore, far from being confined to SARS-CoV-2, wastewater surveillance has already been adapted for use in combating other viral pathogens. Another paper from September 2021 described an advance in the development of effective wastewater surveillance for dengue, Zika, and yellow fever viruses, with SMART researchers successfully measuring decay rates of these medically significant arboviruses in wastewater. This was followed by another review paper by SMART published in July 2022 that explored current progress and future challenges and opportunities in wastewater surveillance for arboviruses. These developments represent an important first step toward establishing arbovirus wastewater surveillance, which would help policymakers in Singapore and beyond make better informed and more targeted public health measures in controlling arbovirus outbreaks such as dengue, which is a significant public health concern in Singapore.

    “Our learnings from using wastewater surveillance as a key tool over the course of Covid-19 will be crucial in helping researchers develop similar methods to monitor and tackle other viral pathogens and future pandemics,” says Lee Wei Lin, first author of the latest SMART paper and research scientist at SMART AMR. “Wastewater surveillance has already shown promising utility in helping to fight other viral pathogens, including some of the world’s most prevalent mosquito-borne diseases, and there is significant potential for the technology to be adapted for use against other infectious viral diseases.”

    The research is carried out by SMART and its collaborators at SCELSE, NTU, and NUS, co-led by Professor Eric Alm (SMART and MIT) and Associate Professor Janelle Thompson (SCELSE and NTU), and is supported by Singapore’sNational Research Foundation (NRF) under its Campus for Research Excellence And Technological Enterprise (CREATE) program. The research is part of an initiative funded by the NRF to develop sewage-based surveillance for rapid outbreak detection and intervention in Singapore.

    SMART was established by MIT in partnership with the NRF in 2007. SMART is the first entity in CREATE developed by NRF and serves as an intellectual and innovation hub for research interactions between MIT and Singapore, undertaking cutting-edge research projects in areas of interest to both Singapore and MIT. SMART currently comprises an Innovation Centre and five interdisciplinary research groups: AMR, Critical Analytics for Manufacturing Personalized-Medicine, Disruptive & Sustainable Technologies for Agricultural Precision, Future Urban Mobility, and Low Energy Electronic Systems.

    The AMR IRG is a translational research and entrepreneurship program that tackles the growing threat of antimicrobial resistance. By leveraging talent and convergent technologies across Singapore and MIT, they tackle AMR head-on by developing multiple innovative and disruptive approaches to identify, respond to, and treat drug-resistant microbial infections. Through strong scientific and clinical collaborations, our goal is to provide transformative, holistic solutions for Singapore and the world. More

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    Using seismology for groundwater management

    As climate change increases the number of extreme weather events, such as megadroughts, groundwater management is key for sustaining water supply. But current groundwater monitoring tools are either costly or insufficient for deeper aquifers, limiting our ability to monitor and practice sustainable management in populated areas.

    Now, a new paper published in Nature Communications bridges seismology and hydrology with a pilot application that uses seismometers as a cost-effective way to monitor and map groundwater fluctuations.

    “Our measurements are independent from and complementary to traditional observations,” says Shujuan Mao PhD ’21, lead author on the paper. “It provides a new way to dictate groundwater management and evaluate the impact of human activity on shaping underground hydrologic systems.”

    Mao, currently a Thompson Postdoctoral Fellow in the Geophysics department at Stanford University, conducted most of the research during her PhD in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). Other contributors to the paper include EAPS department chair and Schlumberger Professor of Earth and Planetary Sciences Robert van der Hilst, as well as Michel Campillo and Albanne Lecointre from the Institut des Sciences de la Terre in France.

    While there are a few different methods currently used for measuring groundwater, they all come with notable drawbacks. Hydraulic heads, which drill through the ground and into the aquifers, are expensive and can only give limited information at the specific location they’re placed. Noninvasive techniques based on satellite- or airborne-sensing lack the sensitivity and resolution needed to observe deeper depths.

    Mao proposes using seismometers, which are instruments used to measure ground vibrations such as the waves produced by earthquakes. They can measure seismic velocity, which is the propagation speed of seismic waves. Seismic velocity measurements are unique to the mechanical state of rocks, or the ways rocks respond to their physical environment, and can tell us a lot about them.

    The idea of using seismic velocity to characterize property changes in rocks has long been used in laboratory-scale analysis, but only recently have scientists been able to measure it continuously in realistic-scale geological settings. For aquifer monitoring, Mao and her team associate the seismic velocity with the hydraulic property, or the water content, in the rocks.

    Seismic velocity measurements make use of ambient seismic fields, or background noise, recorded by seismometers. “The Earth’s surface is always vibrating, whether due to ocean waves, winds, or human activities,” she explains. “Most of the time those vibrations are really small and are considered ‘noise’ by traditional seismologists. But in recent years scientists have shown that the continuous noise records in fact contain a wealth of information about the properties and structures of the Earth’s interior.”

    To extract useful information from the noise records, Mao and her team used a technique called seismic interferometry, which analyzes wave interference to calculate the seismic velocity of the medium the waves pass through. For their pilot application, Mao and her team applied this analysis to basins in the Metropolitan Los Angeles region, an area suffering from worsening drought and a growing population.

    By doing this, Mao and her team were able to see how the aquifers changed physically over time at a high resolution. Their seismic velocity measurements verified measurements taken by hydraulic heads over the last 20 years, and the images matched very well with satellite data. They could also see differences in how the storage areas changed between counties in the area that used different water pumping practices, which is important for developing water management protocol.

    Mao also calls using the seismometers a “buy-one get-one free” deal, since seismometers are already in use for earthquake and tectonic studies not just across California, but worldwide, and could help “avoid the expensive cost of drilling and maintaining dedicated groundwater monitoring wells,” she says.

    Mao emphasizes that this study is just the beginning of exploring possible applications of seismic noise interferometry in this way. It can be used to monitor other near-surface systems, such as geothermal or volcanic systems, and Mao is currently applying it to oil and gas fields. But in places like California currently experiencing megadroughts, and who rely on groundwater for a large portion of their water needs, this kind of information is key for sustainable water management.

    “It’s really important, especially now, to characterize these changes in groundwater storage so that we can promote data-informed policymaking to help them thrive under increasing water stress,” she says.

    This study was funded, in part, by the European Research Council, with additional support from the Thompson Fellowship at Stanford University. More

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    Making hydropower plants more sustainable

    Growing up on a farm in Texas, there was always something for siblings Gia Schneider ’99 and Abe Schneider ’02, SM ’03 to do. But every Saturday at 2 p.m., no matter what, the family would go down to a local creek to fish, build rock dams and rope swings, and enjoy nature.

    Eventually the family began going to a remote river in Colorado each summer. The river forked in two; one side was managed by ranchers who destroyed natural features like beaver dams, while the other side remained untouched. The family noticed the fishing was better on the preserved side, which led Abe to try measuring the health of the two river ecosystems. In high school, he co-authored a study showing there were more beneficial insects in the bed of the river with the beaver dams.

    The experience taught both siblings a lesson that has stuck. Today they are the co-founders of Natel Energy, a company attempting to mimic natural river ecosystems with hydropower systems that are more sustainable than conventional hydro plants.

    “The big takeaway for us, and what we’ve been doing all this time, is thinking of ways that infrastructure can help increase the health of our environment — and beaver dams are a good example of infrastructure that wouldn’t otherwise be there that supports other populations of animals,” Abe says. “It’s a motivator for the idea that hydropower can help improve the environment rather than destroy the environment.”

    Through new, fish-safe turbines and other features designed to mimic natural river conditions, the founders say their plants can bridge the gap between power-plant efficiency and environmental sustainability. By retrofitting existing hydropower plants and developing new projects, the founders believe they can supercharge a hydropower industry that is by far the largest source of renewable electricity in the world but has not grown in energy generation as much as wind and solar in recent years.

    “Hydropower plants are built today with only power output in mind, as opposed to the idea that if we want to unlock growth, we have to solve for both efficiency and river sustainability,” Gia says.

    A life’s mission

    The origins of Natel came not from a single event but from a lifetime of events. Abe and Gia’s father was an inventor and renewable energy enthusiast who designed and built the log cabin they grew up in. With no television, the kids’ preferred entertainment was reading books or being outside. The water in their house was pumped by power generated using a mechanical windmill on the north side of the house.

    “We grew up hanging clothes on a line, and it wasn’t because we were too poor to own a dryer, but because everything about our existence and our use of energy was driven by the idea that we needed to make conscious decisions about sustainability,” Abe says.

    One of the things that fascinated both siblings was hydropower. In high school, Abe recalls bugging his friend who was good at math to help him with designs for new hydro turbines.

    Both siblings admit coming to MIT was a major culture shock, but they loved the atmosphere of problem solving and entrepreneurship that permeated the campus. Gia came to MIT in 1995 and majored in chemical engineering while Abe followed three years later and majored in mechanical engineering for both his bachelor’s and master’s degrees.

    All the while, they never lost sight of hydropower. In the 1998 MIT $100K Entrepreneurship Competitions (which was the $50K at the time), they pitched an idea for hydropower plants based on a linear turbine design. They were named finalists in the competition, but still wanted more industry experience before starting a company. After graduation, Abe worked as a mechanical engineer and did some consulting work with the operators of small hydropower plants while Gia worked at the energy desks of a few large finance companies.

    In 2009, the siblings, along with their late father, Daniel, received a small business grant of $200,000 and formally launched Natel Energy.

    Between 2009 and 2019, the founders worked on a linear turbine design that Abe describes as turbines on a conveyor belt. They patented and deployed the system on a few sites, but the problem of ensuring safe fish passage remained.

    Then the founders were doing some modeling that suggested they could achieve high power plant efficiency using an extremely rounded edge on a turbine blade — as opposed to the sharp blades typically used for hydropower turbines. The insight made them realize if they didn’t need sharp blades, perhaps they didn’t need a complex new turbine.

    “It’s so counterintuitive, but we said maybe we can achieve the same results with a propeller turbine, which is the most common kind,” Abe says. “It started out as a joke — or a challenge — and I did some modeling and rapidly realized, ‘Holy cow, this actually could work!’ Instead of having a powertrain with a decade’s worth of complexity, you have a powertrain that has one moving part, and almost no change in loading, in a form factor that the whole industry is used to.”

    The turbine Natel developed features thick blades that allow more than 99 percent of fish to pass through safely, according to third-party tests. Natel’s turbines also allow for the passage of important river sediment and can be coupled with structures that mimic natural features of rivers like log jams, beaver dams, and rock arches.

    “We want the most efficient machine possible, but we also want the most fish-safe machine possible, and that intersection has led to our unique intellectual property,” Gia says.

    Supercharging hydropower

    Natel has already installed two versions of its latest turbine, what it calls the Restoration Hydro Turbine, at existing plants in Maine and Oregon. The company hopes that by the end of this year, two more will be deployed, including one in Europe, a key market for Natel because of its stronger environmental regulations for hydropower plants.

    Since their installation, the founders say the first two turbines have converted more than 90 percent of the energy available in the water into energy at the turbine, a comparable efficiency to conventional turbines.

    Looking forward, Natel believes its systems have a significant role to play in boosting the hydropower industry, which is facing increasing scrutiny and environmental regulation that could otherwise close down many existing plants. For example, the founders say that hydropower plants the company could potentially retrofit across the U.S. and Europe have a total capacity of about 30 gigawatts, enough to power millions of homes.

    Natel also has ambitions to build entirely new plants on the many nonpowered dams around the U.S. and Europe. (Currently only 3 percent of the United States’ 80,000 dams are powered.) The founders estimate their systems could generate about 48 gigawatts of new electricity across the U.S. and Europe — the equivalent of more than 100 million solar panels.

    “We’re looking at numbers that are pretty meaningful,” Gia says. “We could substantially add to the existing installed base while also modernizing the existing base to continue to be productive while meeting modern environmental requirements.”

    Overall, the founders see hydropower as a key technology in our transition to sustainable energy, a sentiment echoed by recent MIT research.

    “Hydro today supplies the bulk of electricity reliability services in a lot of these areas — things like voltage regulation, frequency regulation, storage,” Gia says. “That’s key to understand: As we transition to a zero-carbon grid, we need a reliable grid, and hydro has a very important role in supporting that. Particularly as we think about making this transition as quickly as we can, we’re going to need every bit of zero-emission resources we can get.” More

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    Could used beer yeast be the solution to heavy metal contamination in water?

    A new analysis by researchers at MIT’s Center for Bits and Atoms (CBA) has found that inactive yeast could be effective as an inexpensive, abundant, and simple material for removing lead contamination from drinking water supplies. The study shows that this approach can be efficient and economic, even down to part-per-billion levels of contamination. Serious damage to human health is known to occur even at these low levels.

    The method is so efficient that the team has calculated that waste yeast discarded from a single brewery in Boston would enough to treat the city’s entire water supply. Such a fully sustainable system would not only purify the water but also divert what would otherwise be a waste stream needing disposal.

    The findings are detailed today in the journal Nature Communications Earth and Environment, in a paper by MIT Research Scientist Patritsia Statathou; Brown University postdoc and MIT Visiting Scholar Christos Athanasiou; MIT Professor Neil Gershenfeld, the director of CBA; and nine others at MIT, Brown, Wellesley College, Nanyang Technological University, and National Technical University of Athens.

    Lead and other heavy metals in water are a significant global problem that continues to grow because of electronic waste and discharges from mining operations. In the U.S. alone, more than 12,000 miles of waterways are impacted by acidic mine-drainage-water rich in heavy metals, the country’s leading source of water pollution. And unlike organic pollutants, most of which can be eventually broken down, heavy metals don’t biodegrade, but persist indefinitely and bioaccumulate. They are either impossible or very expensive to completely remove by conventional methods such as chemical precipitation or membrane filtration.

    Lead is highly toxic, even at tiny concentrations, especially affecting children as they grow. The European Union has reduced its standard for allowable lead in drinking water from 10 parts per billion to 5 parts per billion. In the U.S., the Environmental Protection Agency has declared that no level at all in water supplies is safe. And average levels in bodies of surface water globally are 10 times higher than they were 50 years ago, ranging from 10 parts per billion in Europe to hundreds of parts per billion in South America.

    “We don’t just need to minimize the existence of lead; we need to eliminate it in drinking water,” says Stathatou. “And the fact is that the conventional treatment processes are not doing this effectively when the initial concentrations they have to remove are low, in the parts-per-billion scale and below. They either fail to completely remove these trace amounts, or in order to do so they consume a lot of energy and they produce toxic byproducts.”

    The solution studied by the MIT team is not a new one — a process called biosorption, in which inactive biological material is used to remove heavy metals from water, has been known for a few decades. But the process has been studied and characterized only at much higher concentrations, at more than one part-per-million levels. “Our study demonstrates that the process can indeed work efficiently at the much lower concentrations of typical real-world water supplies, and investigates in detail the mechanisms involved in the process,” Athanasiou says.

    The team studied the use of a type of yeast widely used in brewing and in industrial processes, called S. cerevisiae, on pure water spiked with trace amounts of lead. They demonstrated that a single gram of the inactive, dried yeast cells can remove up to 12 milligrams of lead in aqueous solutions with initial lead concentrations below 1 part per million. They also showed that the process is very rapid, taking less than five minutes to complete.

    Because the yeast cells used in the process are inactive and desiccated, they require no particular care, unlike other processes that rely on living biomass to perform such functions which require nutrients and sunlight to keep the materials active. What’s more, yeast is abundantly available already, as a waste product from beer brewing and from various other fermentation-based industrial processes.

    Stathatou has estimated that to clean a water supply for a city the size of Boston, which uses about 200 million gallons a day, would require about 20 tons of yeast per day, or about 7,000 tons per year. By comparison, one single brewery, the Boston Beer Company, generates 20,000 tons a year of surplus yeast that is no longer useful for fermentation.

    The researchers also performed a series of tests to determine that the yeast cells are responsible for biosorption. Athanasiou says that “exploring biosorption mechanisms at such challenging concentrations is a tough problem. We were the first to use a mechanics perspective to unravel biosorption mechanisms, and we discovered that the mechanical properties of the yeast cells change significantly after lead uptake. This provides fundamentally new insights for the process.”

    Devising a practical system for processing the water and retrieving the yeast, which could then be separated from the lead for reuse, is the next stage of the team’s research, they say.

    “To scale up the process and actually put it in place, you need to embed these cells in a kind of filter, and this is the work that’s currently ongoing,” Stathatou says. They are also looking at ways of recovering both the cells and the lead. “We need to conduct further experiments, but there is the option to get both back,” she says.

    The same material can potentially be used to remove other heavy metals, such as cadmium and copper, but that will require further research to quantify the effective rates for those processes, the researchers say.

    “This research revealed a very promising, inexpensive, and environmentally friendly solution for lead removal,” says Sivan Zamir, vice president of Xylem Innovation Labs, a water technology research firm, who was not associated with this research. “It also deepened our understanding of the biosorption process, paving the way for the development of materials tailored to removal of other heavy metals.”

    The team also included Marios Tsezos at the National Technical University of Athens, in Greece; John Gross at Wellesley College; Camron Blackburn, Filippos Tourlomousis, and Andreas Mershin at MIT’s CBA; Brian Sheldon, Nitin Padture, Eric Darling at Brown University; and Huajian Gao at Brown University and Nanyang Technological University, in Singapore. More

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    MIT J-WAFS announces 2022 seed grant recipients

    The Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) at MIT has awarded eight MIT principal investigators with 2022 J-WAFS seed grants. The grants support innovative MIT research that has the potential to have significant impact on water- and food-related challenges.

    The only program at MIT that is dedicated to water- and food-related research, J-WAFS has offered seed grant funding to MIT principal investigators and their teams for the past eight years. The grants provide up to $75,000 per year, overhead-free, for two years to support new, early-stage research in areas such as water and food security, safety, supply, and sustainability. Past projects have spanned many diverse disciplines, including engineering, science, technology, and business innovation, as well as social science and economics, architecture, and urban planning. 

    Seven new projects led by eight researchers will be supported this year. With funding going to four different MIT departments, the projects address a range of challenges by employing advanced materials, technology innovations, and new approaches to resource management. The new projects aim to remove harmful chemicals from water sources, develop drought monitoring systems for farmers, improve management of the shellfish industry, optimize water purification materials, and more.

    “Climate change, the pandemic, and most recently the war in Ukraine have exacerbated and put a spotlight on the serious challenges facing global water and food systems,” says J-WAFS director John H. Lienhard. He adds, “The proposals chosen this year have the potential to create measurable, real-world impacts in both the water and food sectors.”  

    The 2022 J-WAFS seed grant researchers and their projects are:

    Gang Chen, the Carl Richard Soderberg Professor of Power Engineering in MIT’s Department of Mechanical Engineering, is using sunlight to desalinate water. The use of solar energy for desalination is not a new idea, particularly solar thermal evaporation methods. However, the solar thermal evaporation process has an overall low efficiency because it relies on breaking hydrogen bonds among individual water molecules, which is very energy-intensive. Chen and his lab recently discovered a photomolecular effect that dramatically lowers the energy required for desalination. 

    The bonds among water molecules inside a water cluster in liquid water are mostly hydrogen bonds. Chen discovered that a photon with energy larger than the bonding energy between the water cluster and the remaining water liquids can cleave off the water cluster at the water-air interface, colliding with air molecules and disintegrating into 60 or even more individual water molecules. This effect has the potential to significantly boost clean water production via new desalination technology that produces a photomolecular evaporation rate that exceeds pure solar thermal evaporation by at least ten-fold. 

    John E. Fernández is the director of the MIT Environmental Solutions Initiative (ESI) and a professor in the Department of Architecture, and also affiliated with the Department of Urban Studies and Planning. Fernández is working with Scott D. Odell, a postdoc in the ESI, to better understand the impacts of mining and climate change in water-stressed regions of Chile.

    The country of Chile is one of the world’s largest exporters of both agricultural and mineral products; however, little research has been done on climate change effects at the intersection of these two sectors. Fernández and Odell will explore how desalination is being deployed by the mining industry to relieve pressure on continental water supplies in Chile, and with what effect. They will also research how climate change and mining intersect to affect Andean glaciers and agricultural communities dependent upon them. The researchers intend for this work to inform policies to reduce social and environmental harms from mining, desalination, and climate change.

    Ariel L. Furst is the Raymond (1921) and Helen St. Laurent Career Development Professor of Chemical Engineering at MIT. Her 2022 J-WAFS seed grant project seeks to effectively remove dangerous and long-lasting chemicals from water supplies and other environmental areas. 

    Perfluorooctanoic acid (PFOA), a component of Teflon, is a member of a group of chemicals known as per- and polyfluoroalkyl substances (PFAS). These human-made chemicals have been extensively used in consumer products like nonstick cooking pans. Exceptionally high levels of PFOA have been measured in water sources near manufacturing sites, which is problematic as these chemicals do not readily degrade in our bodies or the environment. The majority of humans have detectable levels of PFAS in their blood, which can lead to significant health issues including cancer, liver damage, and thyroid effects, as well as developmental effects in infants. Current remediation methods are limited to inefficient capture and are mostly confined to laboratory settings. Furst’s proposed method utilizes low-energy, scaffolded enzyme materials to move beyond simple capture to degrade these hazardous pollutants.

    Heather J. Kulik is an associate professor in the Department of Chemical Engineering at MIT who is developing novel computational strategies to identify optimal materials for purifying water. Water treatment requires purification by selectively separating small ions from water. However, human-made, scalable materials for water purification and desalination are often not stable in typical operating conditions and lack precision pores for good separation. 

    Metal-organic frameworks (MOFs) are promising materials for water purification because their pores can be tailored to have precise shapes and chemical makeup for selective ion affinity. Yet few MOFs have been assessed for their properties relevant to water purification. Kulik plans to use virtual high-throughput screening accelerated by machine learning models and molecular simulation to accelerate discovery of MOFs. Specifically, Kulik will be looking for MOFs with ultra-stable structures in water that do not break down at certain temperatures. 

    Gregory C. Rutledge is the Lammot du Pont Professor of Chemical Engineering at MIT. He is leading a project that will explore how to better separate oils from water. This is an important problem to solve given that industry-generated oil-contaminated water is a major source of pollution to the environment.

    Emulsified oils are particularly challenging to remove from water due to their small droplet sizes and long settling times. Microfiltration is an attractive technology for the removal of emulsified oils, but its major drawback is fouling, or the accumulation of unwanted material on solid surfaces. Rutledge will examine the mechanism of separation behind liquid-infused membranes (LIMs) in which an infused liquid coats the surface and pores of the membrane, preventing fouling. Robustness of the LIM technology for removal of different types of emulsified oils and oil mixtures will be evaluated. César Terrer is an assistant professor in the Department of Civil and Environmental Engineering whose J-WAFS project seeks to answer the question: How can satellite images be used to provide a high-resolution drought monitoring system for farmers? 

    Drought is recognized as one of the world’s most pressing issues, with direct impacts on vegetation that threaten water resources and food production globally. However, assessing and monitoring the impact of droughts on vegetation is extremely challenging as plants’ sensitivity to lack of water varies across species and ecosystems. Terrer will leverage a new generation of remote sensing satellites to provide high-resolution assessments of plant water stress at regional to global scales. The aim is to provide a plant drought monitoring product with farmland-specific services for water and socioeconomic management.

    Michael Triantafyllou is the Henry L. and Grace Doherty Professor in Ocean Science and Engineering in the Department of Mechanical Engineering. He is developing a web-based system for natural resources management that will deploy geospatial analysis, visualization, and reporting to better manage and facilitate aquaculture data.  By providing value to commercial fisheries’ permit holders who employ significant numbers of people and also to recreational shellfish permit holders who contribute to local economies, the project has attracted support from the Massachusetts Division of Marine Fisheries as well as a number of local resource management departments.

    Massachusetts shell fisheries generated roughly $339 million in 2020, accounting for 17 percent of U.S. East Coast production. Managing such a large industry is a time-consuming process, given there are thousands of acres of coastal areas grouped within over 800 classified shellfish growing areas. Extreme climate events present additional challenges. Triantafyllou’s research will help efforts to enforce environmental regulations, support habitat restoration efforts, and prevent shellfish-related food safety issues. More

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    Engineers use artificial intelligence to capture the complexity of breaking waves

    Waves break once they swell to a critical height, before cresting and crashing into a spray of droplets and bubbles. These waves can be as large as a surfer’s point break and as small as a gentle ripple rolling to shore. For decades, the dynamics of how and when a wave breaks have been too complex to predict.

    Now, MIT engineers have found a new way to model how waves break. The team used machine learning along with data from wave-tank experiments to tweak equations that have traditionally been used to predict wave behavior. Engineers typically rely on such equations to help them design resilient offshore platforms and structures. But until now, the equations have not been able to capture the complexity of breaking waves.

    The updated model made more accurate predictions of how and when waves break, the researchers found. For instance, the model estimated a wave’s steepness just before breaking, and its energy and frequency after breaking, more accurately than the conventional wave equations.

    Their results, published today in the journal Nature Communications, will help scientists understand how a breaking wave affects the water around it. Knowing precisely how these waves interact can help hone the design of offshore structures. It can also improve predictions for how the ocean interacts with the atmosphere. Having better estimates of how waves break can help scientists predict, for instance, how much carbon dioxide and other atmospheric gases the ocean can absorb.

    “Wave breaking is what puts air into the ocean,” says study author Themis Sapsis, an associate professor of mechanical and ocean engineering and an affiliate of the Institute for Data, Systems, and Society at MIT. “It may sound like a detail, but if you multiply its effect over the area of the entire ocean, wave breaking starts becoming fundamentally important to climate prediction.”

    The study’s co-authors include lead author and MIT postdoc Debbie Eeltink, Hubert Branger and Christopher Luneau of Aix-Marseille University, Amin Chabchoub of Kyoto University, Jerome Kasparian of the University of Geneva, and T.S. van den Bremer of Delft University of Technology.

    Learning tank

    To predict the dynamics of a breaking wave, scientists typically take one of two approaches: They either attempt to precisely simulate the wave at the scale of individual molecules of water and air, or they run experiments to try and characterize waves with actual measurements. The first approach is computationally expensive and difficult to simulate even over a small area; the second requires a huge amount of time to run enough experiments to yield statistically significant results.

    The MIT team instead borrowed pieces from both approaches to develop a more efficient and accurate model using machine learning. The researchers started with a set of equations that is considered the standard description of wave behavior. They aimed to improve the model by “training” the model on data of breaking waves from actual experiments.

    “We had a simple model that doesn’t capture wave breaking, and then we had the truth, meaning experiments that involve wave breaking,” Eeltink explains. “Then we wanted to use machine learning to learn the difference between the two.”

    The researchers obtained wave breaking data by running experiments in a 40-meter-long tank. The tank was fitted at one end with a paddle which the team used to initiate each wave. The team set the paddle to produce a breaking wave in the middle of the tank. Gauges along the length of the tank measured the water’s height as waves propagated down the tank.

    “It takes a lot of time to run these experiments,” Eeltink says. “Between each experiment you have to wait for the water to completely calm down before you launch the next experiment, otherwise they influence each other.”

    Safe harbor

    In all, the team ran about 250 experiments, the data from which they used to train a type of machine-learning algorithm known as a neural network. Specifically, the algorithm is trained to compare the real waves in experiments with the predicted waves in the simple model, and based on any differences between the two, the algorithm tunes the model to fit reality.

    After training the algorithm on their experimental data, the team introduced the model to entirely new data — in this case, measurements from two independent experiments, each run at separate wave tanks with different dimensions. In these tests, they found the updated model made more accurate predictions than the simple, untrained model, for instance making better estimates of a breaking wave’s steepness.

    The new model also captured an essential property of breaking waves known as the “downshift,” in which the frequency of a wave is shifted to a lower value. The speed of a wave depends on its frequency. For ocean waves, lower frequencies move faster than higher frequencies. Therefore, after the downshift, the wave will move faster. The new model predicts the change in frequency, before and after each breaking wave, which could be especially relevant in preparing for coastal storms.

    “When you want to forecast when high waves of a swell would reach a harbor, and you want to leave the harbor before those waves arrive, then if you get the wave frequency wrong, then the speed at which the waves are approaching is wrong,” Eeltink says.

    The team’s updated wave model is in the form of an open-source code that others could potentially use, for instance in climate simulations of the ocean’s potential to absorb carbon dioxide and other atmospheric gases. The code can also be worked into simulated tests of offshore platforms and coastal structures.

    “The number one purpose of this model is to predict what a wave will do,” Sapsis says. “If you don’t model wave breaking right, it would have tremendous implications for how structures behave. With this, you could simulate waves to help design structures better, more efficiently, and without huge safety factors.”

    This research is supported, in part, by the Swiss National Science Foundation, and by the U.S. Office of Naval Research. More

  • in

    Material designed to improve power plant efficiency wins 2022 Water Innovation Prize

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The other finalists were:

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

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

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

  • in

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    The other finalists were:

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

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

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