MIT spinout turns plastic waste into resilient building materials

The world needs more homes. The world also has too much plastic. Perhaps the only thing those two problems have in common is that they’re hard to solve.

Atlas Building Composites, a spinout of MIT, is on a mission to address both problems with a single solution. The company has developed an AI-powered robotic manufacturing platform capable of turning single-use plastics into durable building materials.

The company emerged from MIT HAUS, a research effort in the MIT Department of Mechanical Engineering that’s short for “Home Architecture for Universal Sustainability.” Atlas uses waterless plastic recycling and large-scale composite additive manufacturing technology to make parts like home foundations, decks, and trusses for walls, floors, and roofs.

“Our mission is to convert waste plastic pollution into durable composites to build 1 billion homes,” says Atlas chair and co-founder A.J. Perez ’13, MNG ’14, PhD ’23, who is also an MIT research scientist. “You can’t divorce these things from each other. We’re not here just to build homes, and we’re not here just to recycle plastic. The conventional way of building homes involves cutting down trees, mining, refining, and a bunch of other dirty activities. We want to avoid all that and address all the plastic bound for our oceans and landfills. We’re turning bottles into buildings.”

Atlas’ parts are already being used to support barns, sheds, decks, and docks. Most recently, the company supplied the U.S. Army Corps of Engineers with American-made recycled composite trusses to construct a 40-foot bridge in a Massachusetts wetland.

Perez and Atlas co-founder Matt Pouliot envision deploying thousands of their AI robotic production systems around the world. A key enabler for that scale is the company’s ability to recycle low-grade plastic into building components without water.

“This is key to democratizing recycling,” Perez says. “Now, every country around the world, regardless of their water access, will be able to do something about their plastic. We strive to study these issues in the real world, not just a lab. When you talk to government officials about creating a new recycling facility, they have to get the local water agency involved, there’s permitting, etc. A lot of that work disappears with the waterless recycling process.”

Research for impact

Since earning his PhD at MIT, Perez has been developing advanced fabrication techniques for homes and new techniques for plastic recycling. In 2019, he started MIT HAUS with David Hardt, MIT’s Ralph E. and Eloise F. Cross Professor in Manufacturing.

“It started with the simple mission of enabling the production of 1 billion homes over a 30-year period,” Perez says. “Then we realized how much the materials needed for those homes would strain global supply chains.”

Perez says building those homes using conventional methods would require a doubling of global production capacity for materials like concrete, not to mention a dramatic acceleration of global deforestation.

“That’s where the light bulb went off,” Perez says. “There’s this other problem humanity has, which is 8 gigatons of plastic that have been produced and are polluting our oceans, rivers, and cities. We decided to plug two really big, hairy problems together.”

Perez met Pouliot, a former Maine senator, and the pair started Atlas to commercialize the technology Perez had been developing at MIT. The founders worked with MIT’s Technology Licensing Office and have since worked with researchers at other universities to independently develop technology for the company’s robotic manufacturing platform, which the founders call the Atlas Factory Stack.

First, single-use plastic from water bottles and other objects is shredded and fed into the Atlas system, where it is melted and fused with American-made fiberglass to make it stronger than wood. From there, a large-scale 3D printer creates the parts, including trusses for floors, walls, roofs, and bridges.

Through research at MIT, Perez has shown large composite trusses can be printed in under 13 minutes and support over 4,000 pounds, exceeding key building standards.

“At MIT, we’ve demonstrated we can produce 60 to 80 pounds of parts per hour, and the systems we’re specifying in Atlas factories operate in the 150 to 200 pound per hour range,” Perez says. “There’s the potential for our robotic manufacturing platform to produce each part at a lower cost than injection molding, and it’s far more flexible and convenient. For example,  we can manufacture the parts in the reverse order so that they’ll be placed on the finished goods pallet next to the machine.”

The founders envision Atlas as a technology provider enabling the creation of home factories close to wherever homes need to be built. Today, each Atlas factory cell is capable of producing the structural framing components for about one small home per day.

“The old way of doing things would be some huge factory in China would mass produce one type of part and ship it far away,” Perez says. “I don’t think that’s good for the planet. Another reason we don’t use injection molding is economic: Mega factories don’t produce as many jobs and have a much higher carbon footprint. We want this to be localized to benefit local communities. The plastic is already everywhere. The more local Atlas is, the lower the cost and footprint.”

Going global

Plastics last far longer than wood, especially for applications where they’re in contact with the ground or water. That adds to the company’s environmental benefits.

“If you get a material into the building world and it does its job, it’s going to be used for a very long time and not need to be recycled again for a very long time,” Pouliot says. “That’s important because when you recycle something over and over again, it degrades. This is one of the most sustainable use cases for recycled petrochemical products.”

Atlas’ bridge with the Army Corps of Engineers was installed in less than a day. The founders are also in talks with international franchise partners to deploy the Atlas Factory Stack across the globe.

“To accomplish our mission, I fundamentally believe it’s not going to be one far-away company dominating the industry,” Perez says. “It’s going to be every country leveraging Atlas Factory Stacks to create local recycling jobs, local factory jobs, local construction jobs, and to stimulate their economies with local materials.”

de MIT News https://ift.tt/dbKGJEU

Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award

The Federal Laboratory Consortium (FLC) selected AI-GUIDE, a medical device developed by MIT Lincoln Laboratory and Massachusetts General Hospital (MGH), for its 2026 Excellence in Technology Transfer Award. This award recognizes federal laboratories and collaborators who have accomplished outstanding work in the process of transferring technology. With funding from the U.S. Army's Combat Casualty Care Research Program (CCC), Lincoln Laboratory and MGH developed AI-GUIDE and are in the process of transferring the prototype to the startup company AutonomUS Medical Technologies, Inc.

"This recognition reflects what effective technology transfer looks like — aligning the Army's operational need with Mass General's clinical expertise and Lincoln Laboratory's engineering capabilities to deliver a solution with a clear path to impact. The transition to AutonomUS underscores how strong partnerships can carry a technology from development into real-world adoption," says Asha Rajagopal, Lincoln Laboratory's chief technology transfer officer. 

AI-GUIDE's transition to industry promises improved health outcomes for injured service members and civilians. Unlike ultrasound devices typically found in hospitals, AI-GUIDE is small and portable, making it ideal for use in pre-hospital settings. Pairing custom-developed AI software with commercial handheld ultrasound technology, AI-GUIDE helps the user insert a guidewire and catheter into a patient's blood vessel. This capability is especially important for U.S. military medics, who must keep injured soldiers alive in the field — sometimes for days — before they can be evacuated to a hospital. AI-GUIDE allows medics with minimal specialized training to administer medical interventions that would otherwise be impossible outside of the hospital, drastically improving patients’ chances of survival. 

The AI-GUIDE project has served as a framework for effective technology development and transfer. Within just three years, AI-GUIDE went from an idea proposed by CCC to a fully working proof-of-concept technology with its own startup company. Once the prototype was developed, clinical testing at MGH proved its viability, and Lincoln Laboratory and MGH staff then founded AutonomUS Medical Technologies to facilitate the commercialization process. With support from the MIT Technology Licensing Office, Lincoln Laboratory Technology Transfer Office, and CCC, the company secured U.S. Food and Drug Administration (FDA) Breakthrough Device Designation, a regulatory fast-track pathway that is only granted to highly innovative technologies with lifesaving potential, as well as a Small Business Innovation Research grant from the U.S. Department of the Air Force and funding from private investors, the Department of War, and the National Institutes of Health. 

These strong technology transfer collaborations are designed to streamline the transfer process, ensuring that lifesaving capabilities can be made available to military personnel and civilians as quickly as possible. While much of the initial work on vascular access has already been transferred, the AI-GUIDE team continues to develop and transition additional capabilities, including peripheral nerve block technology for trauma care and pain management. AI-GUIDE has previously been recognized with a Lincoln Laboratory Best Invention Award and an R&D 100 Award. 

"Lincoln Laboratory has a long record of transferring technology to industry. We are honored and proud to be recognized for the transfer of AI‑GUIDE and look forward to seeing the technology commercialized and saving lives in the field. This achievement reflects the strength of the partnership among the Defense Health Agency, Lincoln Laboratory, Massachusetts General Hospital, and AutonomUS Medical Technologies," says Samuel Kesner, a technical staff member in the Systems Engineering Group, who currently oversees the AI-GUIDE program at Lincoln Laboratory. 

Winning team members from the laboratory include Brian Telfer, Samuel Kesner, Lars Gjesteby, Joshua Werblin, Benjamin Roop, Alec Carruthers, Nancy DeLosa, and former Lincoln Laboratory staff members Matt Johnson (now the vice president of engineering at AutonomUS) and Laura Brattain (now an associate professor at the University of Central Florida). Asha Rajagopal, Jordan Mizerak, Melly Coronado, and Jonathan Dan supported technology transfer efforts.

de MIT News https://ift.tt/qa70561

MIT Schwarzman College of Computing launches pilot to help educators teach AI across disciplines

This summer, the MIT Schwarzman College of Computing welcomed faculty from colleges and universities across Greater Boston, South Carolina, West Virginia, and Texas to campus for the inaugural AI Educators Pilot, a weeklong workshop aimed at expanding how artificial intelligence is taught across disciplines and learning environments. 

Inspired by MIT class C01/C51 (Modeling with Machine Learning), a course developed through the Common Ground for computing and AI education that focuses on helping students understand and apply foundational AI and machine learning concepts to problem-solving in their own disciplines, the workshop gave educators an opportunity to explore how its materials and teaching methods could be adapted for their classrooms. 

“The broader goal is to expand AI education to more students by investing in training for instructors,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Panasonic Professor of Electrical Engineering and Computer Science (EECS).

“We want to empower students to become critical thinkers about AI, not just users of the technology,” says Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College and department head of EECS.

A collaborative model for expanding AI education

Bringing the program to life required broad collaboration across the college, including support from leadership, staff, and contributions from more than half a dozen instructors in fields ranging from finance and computer science to sustainability. Together, they helped shape a workshop that paired core technical concepts with examples and teaching materials adaptable to a range of classroom settings.

“I have not seen an effort quite like it — this many dedicated instructors assembling materials of this richness, all to equip the educators who serve their students,” says Saurabh Amin, the Edmund K. Turner Professor in Civil Engineering and faculty director of the AI Educators Pilot. Amin is also co-director of the Operations Research Center, which is jointly housed within the MIT Schwarzman College of Computing and MIT Sloan School of Management.

With support provided by Jake and Robin Reynolds, the pilot brought together 19 participants in July from Allen University, Babson College, Brandeis University, Marshall University, the University of Massachusetts at Lowell, the University of North Texas, and Wentworth Institute of Technology. Working alongside MIT faculty and instructors, participants explored the pedagogy behind Modeling with Machine Learning through a mix of demos, videos, and exercises, and collaborated in hands-on activities focused on translating the course’s materials and methods to their own classrooms.

“This opportunity has been very timely because we are starting an AI and data science program in my department,” says Wenjin Zhou, assistant professor of computer science at UMass Lowell. “We’ve already been thinking about: How do we teach our next generation of computer scientists within the area of AI? How do we integrate AI in the teaching? I wanted to learn more about how other people are doing it, and especially answer the question: If AI can create tools for anyone now, what does a computer scientist do?”

Moving beyond the black box

When it comes to AI, Amin notes, there is no shortage of high-quality material. What is usually missing is context: Opportunities for instructors and students to connect AI concepts to specific disciplines, problems, and ways of thinking. Those connections are often built through dialogue and reasoning, rather than by presenting AI as a fixed set of ideas to be received. But instructor capacity remains one of the scarcest resources.

“What is scarce are educators prepared to teach AI as more than a fixed body of concepts and tools, to ground it in their own field, help students use it with judgment, and demystify it, so students do not just apply models but learn to question, adapt, and build with them,” explains Amin.

Shen Shen, an EECS lecturer and one of the workshop instructors, adds, “How do we make sure that machine learning is not just a black box, nor this magic piece of new technology? You can think of it as a tool, or a new framing to help you solve the problem in your specific domain.”

From pilot workshop to educator network

Participants ended the week by reflecting on which workshop materials and teaching approaches they planned to adapt for their disciplines and courses. Their feedback will help shape future iterations of the pilot and support the development of a broader network of educators committed to expanding AI education across diverse learning environments.

Weijie Pang, an assistant professor of computer science at the Wentworth Institute of Technology who attended the workshop, looks most forward to ongoing community building activities. “This is a really valuable opportunity to communicate with other faculty from different majors and areas. I can see what other universities are doing and what we can learn from each other,” she says.

“It's helpful to know that everybody within different disciplines at different universities is struggling with the same questions of how we can best serve our students as the technology is changing. Hopefully, we can set them up for success by being a little bit more forward and anticipatory of what the AI use is going to be,” says Dylan Cashman, an assistant professor of computer science at Brandeis University.

de MIT News https://ift.tt/LN4HKkl

Injectable nanodevices could provide effective treatment for drug-resistant glioblastoma

The brain cancer glioblastoma is one of the most aggressive and treatment-resistant cancers known to medicine, carrying a median survival of just 12-15 months, even with the best available care. Now, researchers at the MIT Media Lab have developed injectable nanoantennas, each about one-hundredth the width of human hair, that can be magnetically activated to create localized therapeutic electric fields that target and kill brain cancer cells without damaging healthy brain tissue.

“In laboratory and animal studies, this approach significantly reduced tumor growth and extended survival without detectable side effects, highlighting its potential as a precise and safe brain cancer therapy,” says Deblina Sarkar, associate professor and AT&T Career Development Chair at the MIT Media Lab and head of the Nano-Cybernetic Biotrek group.

The researchers named their technology “HITMAN” — short for highly-localized electric-field-induced tumor therapy using magnetically actuated nanoantennas. 

An open-access paper describing this technology published today in Science Advances.

To test HITMAN against the most clinically realistic version of this disease, the research team worked with tumor tissue obtained from patients diagnosed with aggressive and chemotherapy-resistant glioblastoma at Mayo Clinic. Using cells derived from this tissue in the laboratory, the researchers demonstrated that HITMAN eliminated 52.2 percent of these drug-resistant cancer cells — more than five times than that achieved by the standard chemotherapy drug temozolomide (TMZ) — while leaving healthy neurons and brain-supporting astrocytes unharmed.

The team then implanted those patient-derived tumor cells into the brains of mice to recreate the disease in a living system. In these orthotopic animal models — widely regarded as the gold standard for preclinical brain tumor research — HITMAN substantially inhibited tumor growth, extending median survival by more than 50 percent with no detectable toxicity to major organs or surrounding healthy tissue. 

The injectable nanoantennas can be activated wirelessly from outside the body, with the application of a low-frequency (no higher than 200 kHz, to prevent tissue-damaging heat) magnetic field that can penetrate the skull and brain tissue. The magnetic field actuates parts within the nanoantennas made of magnetostrictive material, creating stress and strain, which result in deformation of a piezoelectric film, producing localized electric fields.

Such localized electric fields were demonstrated to preferentially attack glioblastoma at the cellular level, disrupting the cells’ inherent bioelectric currents and fields, which regulate cellular function. Such disruption provoked a number of antitumor mechanisms, including protein unfolding, membrane damage, and endoplasmic reticulum stress, curtailing the production of a cell’s functional proteins. Such forms of cell dysfunction led to cell death. According to the researchers, cancer cells were selectively targeted over healthy cells due to their high proliferative rate, which elevates protein-folding demand, as well as their characteristic abnormalities in membrane composition and intracellular organelles.

Among a wide array of control experiments, the researchers also exposed glioblastoma cells to the nanoantennas without applying a magnetic field, as well as exposing the cancer cells to a magnetic field alone, confirming that the demonstrated effects were in fact due to the nanoantennas and their magnetic field activation. They also tested for side effects damaging to the animal models’ major organs — kidneys, liver, spleen, lungs, and heart — and detected none.

Also demonstrated by the research was a significant reduction in the number of cancer cell colonies formed after application of the nanoantennas, from 112-150 in the control groups to just 26 in the experimental group, indicating significant potential to reduce tumor recurrence and metastasis.

If translated to clinical use, the nanoantennas, whose size is approximately 150 nanometers, could be injected through the skull. Sarkar points out, however, that a technology developed previously in her lab could make their deployment even simpler.

In 2025, Sarkar and her colleagues created “circulatronics,” a technology that could allow devices like the HITMAN nanoantennas to be administered through an injection in a patient’s arm and to travel to a target region of the brain. In that previous work, the electronic devices were integrated with living cells so they would not be attacked by the body’s immune system and could easily cross the blood-brain barrier, as was demonstrated in pre-clinical studies. 

A glioblastoma diagnosis comes with formidable treatment challenges. Because this type of cancer is extremely infiltrative, complete tumor removal is difficult to achieve and can affect cognitive function. Also, the tumors often resist radiotherapy and chemotherapy, and immunotherapy is challenged by an immunosuppressive tumor environment. 

“The persistent failure of these therapies underscores the urgent need for novel approaches to target treatment-resistant glioblastoma cells,” the researchers write. “HITMAN offers a minimally invasive, spatially precise, and clinically translatable therapy for glioblastoma.”

Sarkar is joined on the paper by other members of her lab, including Monochura Saha, a former MIT postdoc; Ishaq Khan, a former MIT senior postdoc; Baju Joy, Shun Ying Chen, Hao-Tung Yang, Preet Patel, and Pengrui Zhang, all MIT graduate students; and Faheem Azeemi, an MIT undergraduate student.

de MIT News https://ift.tt/iwpMBWR

A burst of “pink noise” may lead to more restorative sleep

During the day, waste products such as lactic acid and worn-out proteins build up in the brain. When we sleep at night, waves of cerebrospinal fluid (CSF) help to wash away this waste, keeping the brain healthy.

In a new study, MIT researchers have shown that they can strengthen these CSF waves through exposure to short bursts of a gentle, staticky sound known as “pink noise” during sleep. These bursts increase the amplitude of slow electrical waves in the brain, which then enlarges the CSF waves.

The researchers now hope to explore whether this enhanced CSF flow could help to boost cognitive function, improve memory, or even slow the progression of neurodegenerative diseases caused by the buildup of harmful proteins such as amyloid beta.

“We found that we were able to increase the size of the CSF flow wave during sleep, which as far as we know, there hasn’t been a method to do before. Now that we can enhance CSF flow during sleep in healthy adults, we’re really excited to bring this technology to clinical populations to see what effects we can have,” says Laura Lewis, the Athinoula A. Martinos Associate Professor of Electrical Engineering and Computer Science, a member of MIT’s Institute for Medical Engineering and Science and the Research Laboratory of Electronics, and an associate member of the Picower Institute for Learning and Memory. 

Lewis is the senior author of the study, which appears today in Science Translational Medicine. Joshua Levitt, who recently earned his PhD from Boston University and was a visiting graduate student in Lewis’ lab, is the paper’s lead author.

Cleaning up the brain

Cerebrospinal fluid is a clear liquid that surrounds and cushions the brain and spinal cord. In addition to protecting the brain from injury, it also helps provide nutrients such as glucose and removes waste products secreted by brain cells as they burn energy.

In 2019, Lewis reported a way to use functional magnetic resonance imaging (fMRI) to measure CSF waves as they flow in and out of the brain during sleep. That study showed that these waves are tightly coupled with brain waves called slow waves, which are associated with deep sleep.

In the new study, she wanted to further explore further the relationship between brain waves and CSF flow, and investigate whether manipulating brain waves might enhance CSF flow. Previous work had already shown that delivering an auditory stimulus at the peak of slow waves can deepen the waves.

“You can make more of these electrical slow waves through an auditory stimulus, if it comes at just the right time. Similar to a child on a swing, if you push them when they’re at the right moment in their movement, you can make that swing go farther,” Lewis says. “The challenge is: How do you find just the right time?”

The auditory stimulus used for this study is a 50-millisecond burst of pink noise. Similar to white noise, pink noise contains all sound frequencies audible to the human ear, but the lower pitch frequencies are louder and the higher pitch frequencies are softer. This creates a balanced, gentle sound similar to steady rain or a distant waterfall.

To deliver these bursts at the peak of the brain’s slow waves, the researchers had to measure each participant’s EEG activity as they slept. This proved challenging because they also needed to measure fMRI signals to monitor CSF flow, and the magnetic fields used for fMRI interfere with EEG signals.

To overcome that, the researchers developed a way to process the EEG signals to eliminate the noise caused by fMRI, very rapidly — in less than 100 milliseconds. To make up for that small lag time in the EEG measurement, they also developed an algorithm that could predict when the slow wave peaks would occur. This allowed them to deliver the pink noise stimulus at the correct time.

More restorative sleep

In tests of 14 healthy volunteers, the researchers found that the auditory stimulus they delivered — which is not loud enough to wake a sleeping person — increased the amplitude of both the slow electrical waves and the CSF waves, during sleep.

Their fMRI studies also revealed that the slow waves stimulate blood vessels to constrict and dilate, allowing them to act as a pump that drives CSF out of the brain. Slow waves are seen only during non-REM sleep, and they become more prominent in deeper stages of sleep.

The researchers now hope to study whether enhancing CSF flow could help people to get more restorative sleep, especially people with insomnia. They also plan to explore whether increasing the flow of CSF, and the removal of waste products from the brain, could help people with Alzheimer’s and other diseases characterized by buildup of harmful proteins. 

“Brain waste clearance is really important for Alzheimer’s and other forms of dementia, which are caused, in part, by the buildup of molecules like amyloid and tau in the brain. If we can improve brain waste clearance, we may be able to help prevent the buildups of these plaques that lead to disease,” Levitt says.

Levitt has started a company that hopes to develop a device, such as a headband, that people could use at home to increase CSF flow by delivering an auditory stimulus at the right time. 

The research was funded by a McKnight Scholar Award, a Sloan Fellowship, a Pew Biomedical Scholars Award, the Simons Foundation Collaboration on Plasticity in the Aging Brain, the MIT EECS Transformative Research Fund, the National Institutes of Health, the Corundum Convergence Institute, and the Panasonic Well Fellowship for AI and Wellness.

de MIT News https://ift.tt/ZAiGPgR

An electrochemical approach turns ammonia into pure hydrogen

As a liquid that is easily stored and transported, ammonia (NH₃) is an attractive carrier for hydrogen, which is used in fuel cells, semiconductor manufacturing, chemical processing, and other applications. However, breaking ammonia into hydrogen and nitrogen typically requires high temperatures, and the resulting gas mixture must undergo additional purification before the hydrogen can be used in many applications. 

MIT researchers have now developed an electrochemical approach to promote hydrogen release from ammonia while simultaneously separating and concentrating the hydrogen into a high-purity stream. Their strategy, which uses electricity to speed up the extraction, reduces the temperature and energy required to recover hydrogen from ammonia and other hydrogen carriers.

In a new study, the researchers showed that their approach can generate highly concentrated, pure streams of hydrogen.

“We have shown the ability to use electrochemistry to drive thermodynamically uphill and kinetically difficult dehydrogenation reactions,” says Yogesh Surendranath, the Donner Professor of Science and a professor of chemistry and chemical engineering. “In this case, we studied the conversion of ammonia and a liquid organic molecule because of their importance as possible hydrogen carriers for a hydrogen economy. But the concepts we learned here could in principle be translated further, and we’re actively working on translating it to other important dehydrogenation reactions.”

Surendranath is the corresponding author of the study, which appears today in Nature. MIT postdoc Rui Zeng, now a professor of materials science and engineering at Harbin Institute of Technology in Shenzhen, China, is the paper’s lead author.

Extracting hydrogen

Hydrogen is widely used in semiconductor manufacturing and chemical processing and is also an energy carrier in fuel cells that use hydrogen and oxygen to generate electricity without combustion. Expanding its use, however, will require practical ways to store and distribute it.

Hydrogen gas itself is difficult to transport efficiently without compression or liquefaction. One alternative is to store hydrogen chemically in compounds that are liquids or can be readily liquefied, then release it where and when it is needed.

Ammonia is one promising hydrogen carrier because it is already produced and transported across large distances, but recovering hydrogen from ammonia remains challenging. That process, known as “cracking,” requires temperatures higher than 500 degrees Celsius to achieve high reaction rates and conversion. The hydrogen must then be separated from nitrogen and unreacted ammonia.

“We wanted to ask whether we could use electrical inputs to drive what would otherwise be an unfavorable dehydrogenation reaction, and simultaneously do it in a way that would separate the hydrogen from the hydrogen carrier, so that it would be very pure and could be used directly in a fuel cell or other application that requires a high purity hydrogen stream,” Surendranath says. 

The key element of the researchers’ new design is the coupling of a palladium-based separation membrane with a hydrogen-generating electrode through a molten hydroxide electrolyte. The separation membrane selectively transports hydrogen while preventing other components of the reaction mixture from passing through.

Using the new setup, ammonia is first dehydrogenated by a catalyst containing ruthenium and cesium. The hydrogen then reaches the separation membrane, whose opposite side is in contact with a molten hydroxide electrolyte. 

The electrochemical gradient across this membrane effectively creates a “vacuum” for hydrogen, providing a strong driving force for its transport across the membrane. It also converts the hydrogen into protons and electrons, which travel separately through the molten electrolyte and external circuit, respectively, before recombining at a second electrode to form hydrogen gas. 

Because the membrane selectively transports hydrogen, the system produces a concentrated stream of hydrogen gas without requiring a separate downstream purification process.

“Using this electrochemical process, we’re able to do this active pumping of hydrogen from a low concentration to a high concentration,” Surendranath says.

Continuously extracting hydrogen can also help drive the dehydrogenation reaction forward, especially when the presence of hydrogen inhibits the reaction. In this way, this strategy does more than separate the product: It changes the reaction environment and enables hydrogen recovery under milder conditions.

This process thus can be performed at temperatures around 200 or 300 degrees Celsius, much lower than those required for conventional ammonia cracking. Another advantage is that it creates a pure stream of hydrogen that doesn’t need to be purified later on — a step that requires additional energy.

Curtis Berlinguette, a professor of chemistry and chemical and biological engineering at the University of British Columbia, described the method as “a powerful new way” to solve the problem of obtaining a pure stream of hydrogen from ammonia and other hydrogen carriers. 

“By using electricity to pull hydrogen through the membrane as it is released, they accelerate the dehydrogenation of ammonia and liquid organic hydrogen carriers while simultaneously producing a purified hydrogen stream. This is an important advance for the energy sciences because it opens a credible pathway for transporting hydrogen in stable chemical carriers and releasing it where and when it is needed,” says Berlinguette, who was not involved in the research.

Powering transportation

In this study, the researchers showed that this approach could be used to dehydrogenate not only ammonia but also methylcyclohexane. This molecule is part of a class known as liquid organic hydrogen carriers (LOHCs), which also hold potential as an energy carrier.

The researchers envision that their new strategy could be useful for transportation applications, such as powering cars, buses, or ships, or for fabricating semiconductors or electronics. Pure hydrogen gas is used for several steps in semiconductor manufacturing, where it plays important roles in boosting manufacturing yields and reducing surface defects.

Because palladium is an expensive metal, the researchers are now working on ways to reduce the amount of palladium needed for the separation membrane. They are also working on scaling up the process, and on applying it to other dehydrogenation reactions that could be industrially useful.

The research was funded by the U.S. National Science Foundation.

de MIT News https://ift.tt/KSeC1as

Study predicts large disparities in access to food, water, and energy in 2050

How will global access to food, water, and energy evolve in coming decades? A new study co-authored by MIT researchers suggests the answers could be very different depending on region, resource, and income.

Based on extensive modeling of many different resource scenarios, the study finds that in some regions, lower-income people could be spending roughly 50 percent of their income on food by the year 2050, in contrast to higher-income groups that could spent about 5 percent of income on food in the same areas. 

“For a lot of these outcomes, the lower-income groups see much worse potential insecurity,” says Jennifer Morris, a principal research scientist at the MIT Center for Sustainability Science and Strategy and the MIT Energy Initiative, and co-author of a new paper detailing the findings. The results, she notes, can be evaluated by policymakers in different global regions to understand what the long-term, large-scale resource security risks may become for different parts of their populations. 

“Anything that’s taking up half of your income is potentially destabilizing for your entire life because it leaves so few resources for the other critical needs and basic life necessities,” Morris says. 

The study focuses on projecting future access to food, water, and energy, based on long-term variation across a dozen major factors influencing their availability, from economic conditions and agriculture production to trade conditions, climate, land use, and more. 

“This study shows that there is no single driver of future food, energy, and water insecurity,” says Gi Joo Kim, a research scientist at Tulane University and co-author of the paper. “Income is important, but regional conditions, land use, energy systems, water availability, and consumer behavior all shape the risks people face.” For policymakers, he adds, “This means they need to consider specific combinations of factors that create vulnerability in each region.”

The paper, “Identifying Key Uncertainties and Drivers of Future Resource Security Outcomes Through a Multisector Scenario Ensemble,” appears in the journal Earth’s Future.

In addition to Morris and Kim, the authors include Brian O’Neill, an earth scientist at the Pacific Northwest National Laboratory; Marshall Wise, a system engineer at the Pacific Northwest National Laboratory; John Weyant, a professor of management science and engineering at Stanford University; and Jonathan Lamontagne, an associate professor of civil and environmental engineering at Tufts University. 

Filling a gap

The current study fills a gap in modeling among scientists studying issues such as long-term resource security. Given the complications of long-term analyses, many studies have used what scientists term “shared socioeconomic pathway” circumstances, a small set of senarios spanning broad global narratives about the future, rather than exploring specific outcomes such as how long-term resource access may shift in linked fashion across income groups in different regions of the world. Two years ago, the same group of authors wrote a paper calling for more socioeconomically specific scenario analysis focused on outcomes for human well-being; the current study is their effort to develop that kind of modeling. 

“For this type of study, where we’re focused on human well-being outcomes, the income piece is really important,” Morris says. 

To conduct the study, the researchers adopted an existing framework in the field, the Global Change Analysis Model (GCAM) version 7.1, which represents interactions between energy, economies, water, land, and climate while dividing the world into 32 regions, 235 water basins, and 384 land-use regions and making adjustments for things like estimated commodity prices over time.

The research group used 12 main variables connected to resource availability, including population, GDP, income distribution, carbon intensity, land use, agricultural trade, multiple energy consumption scenarios, multiple water-use projections, and more. They ran simulations for 3,735 different scenarios involving these factors, to better understand the range of possible resource outcomes by 2050. 

Broadly, the modeling does uncover some significant regional variations. In 2050 food security may be most acute in parts of sub-Saharan Africa, while energy security could be most acute for low-income residents in some parts of Asia, Eastern Europe, and the Middle East. 

But within any region, there may still be substantial variation in resource security. In southern Africa, the modeling suggests that the poorest 10 percent of the population by income could be spending 49.6 percent of its income on food, compared to just 5.5 percent for the wealthiest 10 percent of the population. In West and East Africa the projected food burden for the bottom 10 percent of the population in terms of income is projected to be 48.4 percent and 42.5 percent, respectively. 

To understand the potential change this represents over time, the researchers compared the results to data from the year 2015 in the GCAM model. For the lowest-income group across western Africa in 2015, the average food burden was about 25 percent of people’s income, compared to estimates for 2050 that range from about 20 percent to 75 percent of income. In southern Africa, the lowest-income group spent about 20 percent of their income on food in 2015, but the scholars’ modeling projects an increase in food burden ranging from 25 percent to 65 percent of income. The wide variation in projected burden reflects the wide range in possible future scenarios.

When it comes to energy, variation by income is also apparent. In some parts of the Middle East, for instance, the residential energy burden in 2050 is estimated to be just 1.7 percent for the highest income bracket but 18.9 for the lowest income bracket; in Eastern Europe, the energy burden reaches 11.3 percent of income for the lowest-income bracket, while resting at under 5 percent for the highest-income bracket. 

“Regional averages can make future resource-security risks appear more manageable than they actually are,” Kim says. “This means analyses that stop at the average may miss exactly the populations most vulnerable to future change.”

Understanding the dynamics

To be sure, as the scholars emphasize, there are many uncertainties when it comes to resource access, and uncertainty is always part of modeling the global economy and resources. Still, they believe these kinds of projections can provide a more detailed outlook about social conditions in 2050 than has previously been available.

“At the very least, it’s highlighting areas of concern and showing that they differ in different parts of the world,” Morris says. “One of the outputs of this type of study is to map that out and provide that kind of insight. That can also inform the focus of further studies into specific regions and concerns.”

The researchers also believe the results will provide a new roadmap for policymakers who may be concerned about long-term resource provision across the entirety of their societies. While having new projections is valuable, modeling also helps analysts and policymakers see which factors most clearly influence future resource outcomes, as well.

“Our method was designed to identify the conditions that produce different resource security outcomes, rather than to predict one most likely future,” Kim says. 

“It’s a different approach to scenarios than we typically see,” Morris adds. “The approach and method have been appealing to people because they have a broad range of uses and applications.”

The research was supported, in part, by the U.S. Department of Energy; Stanford University; and the National Research Foundation of Korea. 

de MIT News https://ift.tt/s70iIx4