New approach improves right whale distribution models

Bigelow Laboratory for Ocean Sciences

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Right whales “Arpeggio” (#2753) and #4617 pass by each other while feeding in the Great South Channel off Cape Cod in February 2024 (Credit: New England Aquarium, NMFS permit #25739).

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Credit: New England Aquarium (NMFS permit #25739)

Despite being one of the largest animals on the planet, the limited population and vast territory of the North Atlantic right whale make tracking these behemoths challenging. Yet, accurate predictions of their distribution — and preferred habitat at different times of year — is essential for effective conservation.

New research led by scientists at Bigelow Laboratory outlines a modeling approach that incorporates information on the abundance of the whale’s favorite zooplankton prey species, considering their actual daily energy needs, or “feeding threshold,” to more effectively predict where the right whales congregate at different times of year.

The findings highlight the value of including nuanced and detailed prey information in right whale models to improve their predictive power for management and conservation. They also suggest that secondary prey species may have a more important and complex role in the right whale diet than previously thought.

“This work is exciting because it confirms that realistically representing prey is an important factor in models accurately predicting where right whales gather," said the study’s lead author, Camille Ross, a former research associate at Bigelow Laboratory who is now an associate research scientist at the Anderson Cabot Center for Ocean Life at the New England Aquarium. "Our novel approach accounts for the preferences and needs of a hungry whale, highlighting the importance of smaller species in the right whale diet.”

“You can’t protect whales if you don’t know where they are — and they go where the food is,” added Damian Brady, a professor of oceanography at the University of Maine’s Darling Marine Center and a co-author on the new paper. “This study helps us map that more precisely than ever before.”

The study was published in the journal Endangered Species Research and brings together experts on modeling, right whale physiology, and zooplankton ecology from Bigelow Laboratory, the University of Maine’s Darling Marine Center, the Anderson Cabot Center for Ocean Life at the New England Aquarium, Duke University, and the NOAA Northeast Fisheries Science Center.

Given the logistical challenges of tracking right whales, species distribution models are important tools for management. Most of these models account for the abundance of the tiny zooplankton whales feed on, like the fatty copepod Calanus finmarchicus. But they do so by using indirect measures, or proxies. For example, NASA orbiters measure the pigment chlorophyll, allowing scientists to estimate the biomass of the plants that zooplankton like Calanus feed on, and then, in turn, approximate the density of those zooplankton.

These indirect proxies, like chlorophyll, are widely available and relatively easy to get from satellite data. In comparison, getting first-hand observations of zooplankton abundance across an ocean basin — given their small size and the depths they inhabit — is next to impossible (though researchers at Bigelow Laboratory are working to develop methods of detecting zooplankton with satellites).

But these proxies are also several steps removed from actual measures of prey abundance. They can be inaccurate for depicting zooplankton presence, and obscure nuances in the whale diet, including the specific species of zooplankton whales prefer.

“Right whales target only a few key zooplankton species, and their feeding habits vary by location and season,” Ross said. “Replacing prey proxies with direct prey observations tailored to the whales’ foraging requirements has great potential to improve model performance.”

In 2023, Ross and some of the same co-authors published the first description of this new approach, interpolating historical observations of Calanus to create a more direct estimate of their abundance relative to how much daily energy a whale needs. In the new paper, the team takes that work further by expanding the approach to two secondary prey species, which right whales appear to rely on in certain places at specific times of year but are less well studied.

Data on the prey species was collected during the NOAA Fisheries Ecosystem Monitoring Survey.

They then incorporated different combinations of these new variables into models to predict the density of right whales in different parts of their foraging habitat. As hoped, including direct estimates of prey availability significantly improved how well the models matched with actual observations by NOAA of right whale movements compared to the models that just included indirect proxies, like chlorophyll.

The researchers also found that the most accurate models included information on the abundance of both Calanus and the secondary prey — but not in the way they expected. Where the abundance of the smaller, less fatty copepod Pseudocalanus was higher, the model actually predicted fewer right whales. That raises many new questions that the researchers hope to tackle on the role of these secondary species in the right whale diet.

Improving predictive tools with this more direct, accurate information on prey will give scientists and managers a more holistic view of right whale habitat and how they’re using it. That’s essential, Ross said, for being proactive to potential shifts in their behavior as environmental conditions change.

"The key to developing models that will help move things forward is working together with actual users, like NOAA, the Maine Department of Marine Resources, and the fishing and shipping industries," said co-author Nick Record, senior research scientist and director of the Tandy Center for Ocean Forecasting at Bigelow Laboratory. "This more direct approach for including prey information is an important step toward meeting those user needs."

But the value of having better tools for zooplankton distribution goes beyond right whales.

“This paper is specifically focused on a right whale application, but this idea of interpolating zooplankton data from the perspective of the energetic requirements of the predator could be used across marine science,” Ross said. “There are other species, like larval lobster, that feed on Calanus, and there’s no reason that our method couldn’t be extended to those species.”

A microscopy image of Calanus finmarchicus, one of the key prey species of the North Atlantic right whale in the Gulf of Maine (Credit: Cameron Thompson).

Credit

Cameron Thompson (Northeastern Regional Association of Coastal Ocean Observing Systems)

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Journal

Endangered Species Research

DOI

10.3354/esr01435 

Method of Research

Computational simulation/modeling

Subject of Research

Animals

Article Title

Incorporating prey fields into North Atlantic right whale density surface models

Article Publication Date

11-Sep-2025

 

As pesticides and wildfires rise, kids with cancer need resources

University of California - San Francisco

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A growing body of research ties environmental pollutants to worse health and shorter life spans for childhood cancer survivors. Yet medical providers lack sufficient resources to address these risks with patients, a recent federally funded study found.

The study, published in Cancers, revealed 80% of pediatric oncology providers surveyed received questions from families about the impact of environmental pollutants on children’s health, but only 25% of providers said they felt comfortable discussing the topic.

“Medical providers receive little to no education or clinical training on the impacts of environmental pollutants like pesticides and wildfire smoke but need resources to better treat patients,” said Mark Miller, MD, MPH, senior author of the study and an associate professor in UCSF’s Occupational and Environmental Medicine division.

To fill the gap, UCSF’s Western States Pediatric Environmental Health Specialty Units (WSPEHSU) is partnering with physicians from across the country to help develop a pediatric cancer environmental referral service.The service will take children’s environmental health histories and risk assessments, then provide a toolkit to their families. The kit will include air quality and carbon dioxide monitors, an air purifier, and simple and cost-effective strategies to reduce exposure to harmful pollutants.

“Many families express frustration that there are not enough resources to prevent and reduce the impact of environmental pollutants on their kids,” said first author Omar Shakeel, MD, a pediatric hematologist and oncologist at Texas Children’s Hospital. “Ninety-six percent of pediatric cancer providers reported in our study that an environmental referral service would help address these families’ concerns.”

Exposure to pollutants — like pesticides, wildfire smoke, and tobacco smoke — largely goes unnoticed day to day but has serious long-term consequences. Studies have shown pesticides decrease brain and behavioral function in children, while wildfire smoke has the following impacts, according to past research by Miller:

• Developing or worsening chronic lung diseases like asthma
• Exacerbating ADHD and autism, and worsening school performance
• Decreasing birth weight and height and increasing obesity
• Increasing exposure to known carcinogenic chemicals like benzo(a)pyrene, formaldehyde, and benzene

One Texas study showed childhood cancer survivors had higher death rates if they resided at the time of diagnosis near an oil or gas well, which emit hazardous pollutants. Another found that pediatric cancer survivors living in Utah zip codes with higher levels of particulate air pollutants had an increased risk of respiratory hospitalization and death.

Additional research has found that paternal smoking before conception and secondhand smoke exposure during and after pregnancy both increase the death rate of childhood cancer survivors.

“If you believe children in every state should have the cleanest air, water, and environment, then we need policymakers, medical providers, and communities to come together,” said Miller. “Increasing federal funding for research and resources could help reduce children’s exposure to dangerous pollutants, while improving health and survival outcomes.”

Authors: Please see the paper for a full list of authors.

Funding: The Centers for Disease Control and Prevention’s Agency for Toxic Substances and Disease Registry, the U.S. Environmental Protection Agency (EPA), and the Public Health Institute.

Disclosures: The authors declare no conflicts of interest. The funders had no role in the

writing of the manuscript or in the decision to publish the results.

 

About UCSF Benioff Children’s Hospitals

UCSF Benioff UCSF Benioff Children’s Hospitals are among the nation’s leading pediatric specialty hospitals, according to U.S. News & World Report 2024-25 rankings. Their expertise covers virtually all pediatric conditions, including cancer, heart disease, neurological disorders, pulmonology, diabetes and endocrinology, as well as the care of critically ill newborns. The two campuses in San Francisco and Oakland are known for basic and clinical research, and for translating research into interventions for treating and preventing pediatric disease. They are part of UCSF Health, whose adult hospital ranks among the top medical centers nationwide and serves as the teaching hospital for the University of California, San Francisco, a national leader in biomedical research and graduate-level health/sciences education. Visit www.ucsfhealth.org.  

 

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Journal

Cancers

 

Monitoring underwater bridge tunnels with the help of high-energy muons

Researchers applied particle physics techniques to solve real-world problems for measuring sediment buildup in underwater infrastructure.

American Institute of Physics

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The Shanghai Outer Ring Tunnel runs across the Huangpu River, with areas covered by mucky soil and silty clay (top). The researchers placed a portable muon detector within the tunnel to monitor muon flux as a way to measure the sediment buildup (bottom).

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Credit: Khaw et al.

WASHINGTON, Sept. 16, 2025 – Over 200 underwater bridge tunnels exist for vehicular traffic around the world, providing connectivity between cities. Once constructed, however, these tunnels are difficult to monitor and maintain, often requiring shutdowns or invasive methods that pose structural risks.

Muography — an imaging technique using high-energy particles, called muons, which can traverse hundreds of meters within the earth — can provide a noninvasive approach to examining subterranean infrastructure. In the Journal of Applied Physics, by AIP Publishing, a group of researchers from public and private organizations in Shanghai applied this technique to the Shanghai Outer Ring Tunnel, which runs under the Huangpu River as part of the city’s ring expressway.

Because sediment composed of mucky soil and silty clay has a higher density than the water surrounding the tunnel, it is more effective at reducing muon flux than water on its own. When placed within the tunnel, the researchers’ portable muon flux detection system is sensitive to these differences, proving useful for identifying locations with high levels of sediment buildup.

“Muons lose energy primarily through ionization, where they electromagnetically interact with and eject electrons from atoms — denser materials lead to a higher energy loss, effectively blocking more muons,” said author Kim Siang Khaw. “The granular or clay composition of sediment intensifies this effect.”

Using a combination of a spatial scan over the length of the tunnel and a simulation of muons passing through a simplified tunnel model, the researchers mapped the thickness of the sediment. They took 10 minutes of data per location at 50-meter intervals as proof of their technique, but in its actual deployment, they plan to permanently install multiple detectors at fixed points throughout the tunnel, allowing for round-the-clock monitoring.

They intend to extend their studies to several more tunnels in Shanghai and note that other cities can easily adopt the technique into their own infrastructure. All that is needed is basic information about the tunnel’s geometry and materials, environmental data, and baseline muon flux measurements.

“No complex models are necessary upfront — the method works with simplified inputs, validated through simulations in this study,” said Khaw. “This technique can also identify dangerous underground cavities, such as those formed when a burst pipe washes away soil, creating a hidden collapse hazard.”

Muography has been used for archaeological studies, mine exploration, and more, but tracking a system’s change over time is a relatively new, real-world application.

“We are now in a truly exciting era for muography,” said Khaw. “We hope to collaborate with more researchers to apply these advancements in fundamental science to solving pressing societal challenges.”

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The article “Toward noninvasive sediment monitoring using muography: A pilot run at the Shanghai Outer Ring Tunnel” is authored by Kim Siang Khaw, Siew Yan Hoh, Tianqi Hu, Xingyun Huang, Jun Kai Ng, Yusuke Takeuchi, Min Yang Tan, Jiangtao Wang, Yinghe Wang, Guan Ming Wong, Mengjie Wu, Ning Yan, Yonghao Zeng, Min Chen, Shunxi Gao, Lei Li, Yujin Shi, Jie Tan, Qinghua Wang, Siping Zeng, Shibin Yao, Yufu Zhang, Gongliang Chen, Houwang Wang, Jinxin Lin, and Qing Zhan. It will appear in THE Journal of Applied Physics on Sept. 16, 2025 (DOI: 10.1063/5.0273686). After that date, it can be accessed at https://doi.org/10.1063/5.0273686.

ABOUT THE JOURNAL

The Journal of Applied Physics is an influential international journal publishing significant new experimental and theoretical results in all areas of applied physics. See https://pubs.aip.org/aip/jap.

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Journal

Journal of Applied Physics

DOI

10.1063/5.0273686 

Article Title

Toward noninvasive sediment monitoring using muography: A pilot run at the Shanghai Outer Ring Tunnel

Article Publication Date

16-Sep-2025

 

Fast traffic algorithm could improve real-time traffic forecasts

Computer model could help city planners design better streets and reroute drivers for smoother commutes.

American Institute of Physics

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A map of the streets of Manhattan, comparing the real-world traffic data to a conventional traffic model and the authors’ data-driven macroscopic mobility model.

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Credit: Toprak Firat and Deniz Eroğlu

WASHINGTON, Sept. 16, 2025 – Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and a small change in one part of the system can have ripple effects that alter traffic patterns throughout a city. City planners attempting to improve local traffic grids can often struggle to foresee all the effects their changes could have.

In Chaos, by AIP Publishing, a pair of researchers from Kadir Has University in Istanbul developed a more efficient and flexible algorithm to model traffic. The duo’s desire to tackle this issue stems from more than just idle curiosity.

“Being based in Istanbul, we live in one of the most congested cities in the world,” said author Toprak Firat. “Traffic isn’t just an academic problem here; it’s part of daily life and that gave us a strong motivation.”

While traffic flow algorithms do exist, they often require detailed trip information and rely on hard-coded rules to determine how vehicles move through intersections. This leads to a rigid algorithm that the authors wanted to avoid. Instead, they developed a model they called the data-driven macroscopic mobility model (D3M), which relies only on simple observations that city planners routinely collect, like how packed the streets are.

“Rather than using fixed equations for flow dynamics, we calibrate the model parameters directly from real-world traffic data,” said Firat. “This allows D3M to adapt its behavior to the observed conditions in each city, making it more flexible and realistic than models with hard-coded assumptions.”

The researchers tested their model on both synthetic benchmarks and real-world traffic data from London, Istanbul, and New York City. In the benchmark tests, the D3M model was more accurate than a conventional model and up to three times faster. In the real-world tests, it could accurately represent the diverse traffic conditions of these very different cities.

The faster simulation speeds and easier data requirements mean city planners have the tools to design better, smarter cities.

“The key breakthrough is that cities can now run sophisticated traffic simulations without needing expensive data collection,” said author Deniz Eroğlu. “Urban planners could test ‘what-if’ scenarios — like temporary closures due to accidents or maintenance — and see the predicted traffic impact before spending millions on construction.”

But the real impact could be felt directly by city residents, who could benefit from real-time traffic forecasting, making their commutes easier.

“Imagine a system that doesn’t just react to traffic locally, but simulates how congestion can spread in complex, often unexpected ways across an entire city,” said Eroğlu. “A jam in one part of the network might trigger bottlenecks kilometers away — not because of local crowding, but due to the ripple effects of shifting flows. Our model captures these dynamics, offering system-level foresight instead of piecemeal reaction.”

The authors are planning to test their model in a real-time operational environment, with the goal of bringing traffic forecasting to real cities soon.

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The article “Data-driven modeling of traffic flow in macroscopic network systems” is authored by Toprak Firat and Deniz Eroğlu. It will appear in Chaos on Sept. 16, 2025 (DOI: 10.1063/5.0285930). After that date, it can be accessed at https://doi.org/10.1063/5.0285930.

ABOUT THE JOURNAL

Chaos is devoted to increasing the understanding of nonlinear phenomena in all areas of science and engineering and describing their manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines. See https://pubs.aip.org/aip/cha.

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Journal

Chaos An Interdisciplinary Journal of Nonlinear Science

DOI

10.1063/5.0285930 

Article Title

Data-driven modeling of traffic flow in macroscopic network systems

Article Publication Date

16-Sep-2025

 

If every home and personal vehicle went electric in the U.S., power outages could spike — unless key measures are taken

Purdue University

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Kevin Kircher, a Purdue University assistant professor of mechanical engineering, stands next to a home's heating, ventiliation and air conditioning unit. He studies the electrification of homes and vehicles.

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Credit: Purdue University/Jared Pike

WEST LAFAYETTE, Ind. — A future where all homes and vehicles in the U.S. are fully electrified could overwhelm power supply and risk outages unless key upgrades are made, says a new study conducted by Purdue University engineers. But a few strategies could cut two-thirds of the potential costs of reinforcing the nation’s distribution grid to handle this demand.

Electrifying would mean switching a home’s heating system from a boiler to a heat pump and transitioning from gas- or diesel-fueled vehicles to electric vehicles.

“If we install a whole bunch of new electric heating systems for homes and use more electric vehicles and electric water heaters, then we’re going to increase electricity demand a lot. And that’s basically going to require putting in thicker wires, bigger transformers and other infrastructure into the power grid,” said Kevin Kircher, a Purdue assistant professor of mechanical engineering and faculty member in the university’s Ray W. Herrick Laboratories. “And if that happens, utilities will pass the cost of those upgrades to us, the customers.”

The study, published in Cell Reports Sustainability on Sept. 16, found that reinforcing the U.S. distribution grid, which provides power to residential areas, could cost $350-$790 billion — about $2,000-$6,400 total per household between now and 2050. Much of this cost would be due to increased electric space heating, with the coldest regions of the U.S. experiencing electricity demand peaks up to five times higher than today’s peaks.

But taking measures such as installing better insulation and air sealing, improving equipment efficiency, and coordinating the operation of the home’s electric devices could mitigate the costs of upgrading the grid.

An example of boosting the efficiency of the home’s electric equipment would be using ground-source heat pumps instead of air-source heat pumps because the constant ground temperature reduces the energy needed to heat and cool homes. Coordinating the home’s electric device operation could mean adjusting when the home’s electric vehicle charges so that it doesn’t happen at the same time when the heat pump is in use.

“If electric vehicles could communicate with the heating, ventilation and air conditioning units that we install in the house, and if they can coordinate when they have to charge or when they have to heat or precool the homes, this strategy could contribute to a 40% decrease in grid reinforcement costs,” said Priyadarshan, a PhD student in Purdue’s School of Mechanical Engineering and the first author of this paper. “Let’s say there’s a cold snap coming. The heat pump could preheat the house, and the home’s electric vehicles could be charged at a different time to reduce strain on the grid.”

The study focused on each county of the Lower 48 U.S. states. The researchers modeled the grid impacts of fully electrifying homes and vehicles using public surveys of home electricity usage and electric vehicle travel where available for each county, specifications from equipment manufacturers, building code guidelines, and weather data. The team also calibrated the home data against a fully electrified test house in West Lafayette called the DC Nanogrid House.

After analyzing the impact of full electrification to the distribution grid, the researchers adjusted the parameters of their model to include the home weatherization and equipment efficiency strategies they were proposing to cut grid upgrade costs. For their strategy to coordinate electric device operation, they used an optimization algorithm to take into consideration heating, electricity demand and electric vehicle usage and devise an optimal solution for when to charge the vehicles and how hard to run the heat pumps.

Other studies have investigated the future of increased home and vehicle electrification in the U.S. but not on the scale of residential areas by county nationwide.

“On the one hand it’s kind of scary — if we electrify everything, we might have a crazy expensive future. But on the other hand, if we electrify in a smart way, then we don’t have nearly as many of those problems,” Kircher said.

This study was funded by Purdue’s Center for High Performance Buildings.

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Journal

Cell Reports Sustainability

DOI

10.1016/j.crsus.2025.100518 

Article Title

Distribution grids may be a barrier to residential electrification

Article Publication Date

16-Sep-2025

 

New electrical flash method rapidly purifies red mud into strong ceramics, aluminum feedstock

Rice University

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From left to right: Justin Sharp, Shichen Xu, James Tour, Qiming Liu, and Jaeho Shin.

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Credit: Photo by Jared Jones/Rice University.

A team of researchers at Rice University has developed a faster and cleaner method for recovering aluminum and removing toxic metals from bauxite residue, or red mud, which is a hazardous by-product of aluminum production. This new technique, published in American Chemical Society Applied Materials and Interfaces Sept. 15, involves a brief electrical pulse lasting under one minute along with a small amount of chlorine gas. If implemented on a larger scale, it could revolutionize global waste management and materials recovery.

The process uses flash Joule heating (FJH), which rapidly heats materials with a short, high-power electrical pulse to vaporize harmful metals, leaving behind a residue rich in aluminum. This aluminum-rich material can then be repurposed into durable ceramic tiles or bricks or resubjected to the normal aluminum production process. The breakthrough offers a practical and scalable solution to address a significant pollution problem by transforming it into valuable materials, marking an advancement in industrial waste recovery.

“Our research presents a potential game-changing solution for the red mud crisis,” said James Tour, the T.T. and W.F. Chao Professor of Chemistry, professor of materials science and nanoengineering and the study’s corresponding author. “This advance is massive from an industrial perspective, turning what was once a toxic liability into a valuable asset in under one minute.”

Turning toxic waste into tiles

Each year, millions of tons of red mud accumulate as toxic waste from aluminum production, which contains harmful metals. Disasters related to its storage have caused river contamination and flooding in affected communities. The researchers aimed to explore whether this waste could be repurposed rather than merely contained.

The FJH method works by delivering electricity in a flash, similar to a bolt of lightning, while simultaneously introducing chlorine gas. This approach selectively vaporizes iron and other toxic metals, leaving behind the aluminum.

“The speed and simplicity of this method set it apart,” said Qiming Liu, a postdoctoral researcher at Rice and a co-first author of the study. “In just 60 seconds, we extracted 96% of the iron and nearly all the toxic species, while retaining almost all the aluminum.”

This process is significantly faster and cleaner than traditional methods, which often require prolonged heating in furnaces or the use of corrosive chemicals. The new method uses no water and no solvents while also removing the sodium salts in the process, relieving the end use of the typically caustic red mud. 

A promising route to sustainability

This method could benefit industries dealing with other high-volume waste streams such as steel manufacturing, mining and rare earth processing, said Shichen Xu, a postdoctoral researcher at Rice and co-first author of the study.

“What was once an environmental threat can now be transformed into building materials,” Xu said. “We have turned cleaned red mud into ceramics that are super hard, making them suitable for construction and aluminum recovery.”

The approach offers a threefold advantage: reducing waste piles, cutting greenhouse gas emissions and decreasing the need for new bauxite mining. For communities affected by red mud disasters, this development signifies renewed hope through applied science.

“This is not just about red mud; it’s about changing our perspective on waste,” Tour said. “If we can apply this method to other industrial residues, it could represent the beginning of a new era in sustainable materials recovery.”

The process, Tour said, is being scaled by the Rice spinoff company, Flash Metals USA, a division of Metallium Ltd., and deployed in partnership with aluminum production companies around the world.

Co-authors of the study include Rice’s Phelecia Scotland, Justin Sharp, Yi Cheng, Jaeho Shin, Nicholas Lowell Viscomi, Lucas Eddy, Shihui Chen, Bowen Li, Tengda Si and Carter Kittrell and Mine Ucak-Astarlioglu from the U.S. Army Engineer Research and Development Center. 

The research was funded by the Air Force Office of Scientific Research and the U.S. Army Corps of Engineers.

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Journal

ACS Applied Materials & Interfaces

DOI

10.1021/acsami.5c13121 

Article Title

Iron and Heavy Metal Removal from Bauxite Residues by Flash Joule Heating with Chlorination

Article Publication Date

15-Sep-2025