Research News

As demand for electricity surges from artificial intelligence, data centers, and other new technologies, companies are increasingly pledging to procure carbon-free electricity to mitigate emissions associated with their electricity use. While quantifying system-wide emissions is relatively straightforward, the complex nature of power grid operations makes it more challenging to ascertain the emissions impacts of a single consumer that also procures its own clean energy. This challenge is further compounded by clean energy sources like solar and wind, whose hour to hour generation can vary drastically, depending on weather patterns.

A new study by researchers at NYU Tandon and the Massachusetts Institute of Technology evaluated the system impacts of so-called 24/7 or hourly matching, involving matching grid electricity consumption with generation from procured clean electricity, a strategy of growing corporate and regulatory interest. By incorporating multiple years of weather variability into sophisticated power-system models, the researchers found that procuring clean electricity to match consumption every hour of the day can deliver emissions benefits, but at higher cost than previous studies suggested. The work also indicates that in regions already pursuing aggressive renewable energy policies, less strict approaches may achieve nearly the same climate benefits for considerably less money.

The study, published in Environmental Science & Technology, focuses on electricity-based production of hydrogen, a pathway of growing interest to decarbonize difficult-to-electrify segments of the economy like heavy industry. Recently, governments in both the United States and Europe have proposed or implemented rules requiring producers to match their electricity use with generation from newly built renewable energy resources, initially on an annual basis and eventually on an hourly basis. Beyond hydrogen, the findings apply broadly to other large electricity consumers, including data centers, and speak directly to ongoing revisions of the Greenhouse Gas Protocol's Scope 2 rules, the standard many companies use to account for and report the emissions tied to their electricity use, where hourly matching is a central proposal under debate.

Until now, however, most analyses on hourly matching have relied on a single year of weather data to characterize wind and solar resource variability. In reality, wind and solar resources fluctuate significantly from year to year.

"We wanted to understand how real-world, inter-annual weather variability changes the economics and emissions of clean electricity procurement," said senior author Dharik S. Mallapragada, associate professor of chemical and biomolecular engineering at NYU Tandon. "When projects are expected to operate for decades, designing them around a single weather year can paint an overly optimistic picture of both cost and performance."

To explore that question, the researchers modeled a grid-connected hydrogen facility operating in the Texas power grid, one of the nation's largest renewable energy markets. They optimized investments across nine representative years of historical wind and solar conditions, both individually and collectively, and then tested those designs for their robustness against additional weather scenarios.

The team's model consistently showed that hourly matching costs more than annual matching and that the cost premium is sensitive to the weather year, varying between ranging from $0.68 to $1.18/kg of H2 produced. For context, the average cost of fossil H2 production is around $1/kg. The team also showed that such single weather-year based investment plans can lead to shortfalls in clean electricity supply across multiple hours of the year when tested against additional weather scenarios not included in the planning analysis.

The cost of clean electricity procurement to be robust to inter-annual weather variations was found to lead to a still higher cost premium, of $1.29 per kilogram compared with annual matching. This cost premium stems from oversizing the capacity of wind and solar farms to manage shortfalls in supply as well as installing larger electrolyzers capable of ramping production up and down, along with extensive hydrogen storage to buffer periods when renewable generation falls short.

The researchers also examined ways to reduce costs of 24/7 matching without sacrificing most of the environmental benefits. Allowing hydrogen producers to match80 to 90 percent of their hourly electricity needs with clean power lowered costs while retaining much of the emissions benefits achieved under full compliance. Likewise, if hydrogen production operates within electricity grids already governed by strong renewable portfolio standards, annual matching performed nearly as well as hourly matching from an emissions standpoint, but at much lower costs. A further option, with similar emissions outcomes at a comparable or lower cost, is to fold new electricity demand directly into those existing renewable portfolio standards rather than layering separate, granular, matching requirements on top. These findings speak directly to ongoing debates among governments and corporations over the role of "24/7 matching" in voluntary and regulatory emissions reporting.

Michael A. Giovanniello, Dharik S. Mallapragada; Emissions and Cost Trade-Offs of Time-Matched Clean Electricity Procurement under Interannual Weather Variability: A Case Study of Hydrogen Production. Environ. Sci. Technol. 21 July 2026; 60 (28): 19854–19865. https://doi.org/10.1021/acs.est.6c00988

Solar panels have become the most iconic symbol of the clean energy transition. They cover rooftops, stretch across deserts, and quietly convert sunlight into electricity without emitting carbon dioxide. But hidden behind this success story is a growing environmental challenge that few people think about: what happens when millions of those panels reach the end of their lives?

By 2050, discarded photovoltaic modules could generate more than 80 million metric tons of waste. Unless new recycling methods are developed, many of those panels could end up in landfills, taking with them valuable metals that required enormous amounts of energy and mining to produce in the first place.

"Solar panels are the clean energy infrastructure of the future," says Juanita Hidalgo, Assistant Professor of Chemical and Biomolecular Engineering at NYU Tandon. "But to make solar truly sustainable, we also need to think about what happens after these technologies reach the end of their lifetime."

A new perspective paper, coauthored by Hidalgo and post-doctoral researcher Sara Hamilton, argues that one of the most promising solutions lies not in hotter furnaces or more intensive manufacturing, but in chemistry. Researchers are increasingly turning to hydrometallurgy, a family of recycling techniques that uses liquids to selectively dissolve and recover valuable metals. Instead of heating an entire solar panel at temperatures approaching 2,000 degrees Celsius, hydrometallurgy carefully separates individual components at low temperatures so they can be reused in new devices.

"It's a much more selective approach," explains Hamilton. "Rather than treating a solar panel as waste, we're treating it as a source of valuable materials that can be recovered and put back into the supply chain."

Today's recycling systems recover relatively simple materials such as aluminum frames, glass, and copper wiring. But the heart of every solar panel contains metals that are both economically valuable and strategically important. Silver, indium, gallium, tellurium, and lead all play critical roles in different kinds of solar cells, yet recovering them remains technically difficult and often too expensive to justify. Current recycling methods frequently rely on pyrometallurgy, which uses extremely high temperatures to melt materials apart. While effective, the process consumes large amounts of energy and can make it difficult to separate individual metals cleanly.

Hydrometallurgy offers a more tunable alternative. Carefully selected solvents dissolve specific metals, which can then be purified and recovered for reuse. In principle, the approach requires less energy and can recover materials with much greater precision.

But the researchers found that not all solar technologies are equally easy to recycle. Conventional crystalline silicon panels, which account for roughly 95 percent of the global solar market, typically require strong acids such as nitric acid to extract valuable silver. Those acids work well, but they are corrosive, hazardous to handle, and difficult to recycle themselves. Thin-film solar cells face similar challenges. Although they contain smaller amounts of material overall, they rely on critical metals such as indium, gallium, and tellurium that are usually recovered using equally aggressive chemical treatments.

One surprise was the recyclability of the hottest new solar technology. Perovskite solar cells have generated enormous excitement because they can be manufactured at lower cost than conventional silicon while achieving record-setting efficiencies in the laboratory. The new perspective suggests they are also remarkably well suited for environmentally friendly recycling.

Unlike conventional solar cells, perovskites are built from layers connected by relatively weak chemical interactions. As a result, several recent studies have shown that researchers can recover one of their most important ingredients — lead — using something unexpectedly simple: hot water. As the water cools, the dissolved lead crystallizes back into a compound that can be used to manufacture new perovskite solar cells.

The authors argue that recyclability should become a design goal rather than an afterthought. Instead of maximizing efficiency first and worrying about disposal decades later, engineers could build future solar cells with disassembly and material recovery in mind from the very beginning.

When the Marshall Fire tore through suburban Colorado in late 2021, residents had only hours to decide where to go. Some fled to nearby towns. Others stayed farther away for weeks or months. Now a recent study published in Humanities and Social Sciences Communications suggests those decisions were shaped not only by distance or danger, but also by something more human: the pull of familiar communities and social ties.

Researchers at NYU Tandon analyzed anonymized mobile phone location data from more than 200,000 devices in Colorado before and after the fast-moving wildfire, which destroyed more than 1,000 homes and displaced thousands of people. They combined those movement patterns with demographic data and measures of social connectedness between neighborhoods. Their conclusion: evacuees were more likely to choose destinations that resembled their home communities or where they had stronger social links.

“Even during a chaotic emergency, people do not move randomly,” says lead author Takahiro Yabe, Assistant Professor of Technology Management and Innovation and the Center for Urban Science + Progress. “They tend to seek places where they feel socially connected or where the community feels familiar.”

The study adds nuance to how scientists understand evacuation behavior. Traditional models often assume people head to the nearest available safe place or to larger population centers. But this research found that social factors strongly influenced where people actually went.

Most evacuees relocated between 20 and 60 kilometers from the fire zone, suggesting many wanted to remain relatively close to home. Yet when researchers compared real evacuation destinations with simulated destinations based only on population size and distance, the real destinations scored significantly higher for demographic similarity and friendship connections. In other words, people often chose places where they knew someone, or places that looked socially like where they came from.

The findings also revealed inequality in who could access those familiar refuges. Residents from whiter, wealthier, and more highly educated neighborhoods were more likely to evacuate to destinations with stronger social similarity and connectedness. Black, Asian, and lower-income populations were less likely to do so. That gap may matter because social networks can provide practical help during crises: a spare bedroom, child care, transportation, local knowledge, or emotional support.

“Access to social capital can shape recovery just as much as physical damage does,” says Vaidehi Raipat, a PhD candidate and lead author on the paper. “If some groups have fewer options to relocate into supportive communities, that can deepen existing inequalities after disasters.”

The team also examined what happened after the initial evacuation. People who relocated to areas with stronger social connectedness were more likely to return home over the following months. But those who moved to places that were demographically similar to their original communities were somewhat less likely to return, suggesting that a comfortable temporary destination may sometimes become a longer-term alternative.

That distinction could help officials plan for future climate disasters, which are becoming more frequent and more destructive. Wildfires, floods, and storms increasingly force sudden movement, yet emergency planning still tends to focus on roads, shelters, and hazard maps rather than the social geography of where people want to go.

The researchers argue that disaster response could improve by accounting for community ties. Knowing where evacuees are likely to head could help agencies position aid, anticipate population surges, and better support displaced residents. It could also identify people who lack strong networks and may need more assistance.

The study focused on one wildfire, so its authors caution that patterns may differ in hurricanes, floods, or other disasters. Still, the broader message is clear: in moments of upheaval, people often search not just for safety, but for belonging.

For most of us, watching a movie feels effortless. We follow dialogue, read facial expressions, notice music cues and shifting scenery, and somehow fuse it all into a coherent story. But beneath that smooth experience, the brain is constantly deciding which sensory stream matters most in each moment.

A new study suggests that the frontal cortex, a region associated with planning and higher cognition, may act as a kind of traffic controller for this process — dynamically shifting attention between what we hear and what we see as a story unfolds.

To investigate, neuroscientists recorded brain activity directly from 19 epilepsy patients who had temporarily implanted electrodes for clinical monitoring. While in the hospital, participants watched a 12-minute multilingual short film* containing scenes in English, Greek, German, and French. Some foreign-language scenes included English subtitles, creating a natural test of how the brain handles changing audiovisual demands. Because the electrodes sat on or inside the brain, the researchers could track neural responses with millisecond precision, far faster than MRI scans allow.

They found that the frontal cortex was not processing all sensory information equally. Instead, it showed a striking internal division. Ventral, or lower, frontal regions responded more strongly to auditory information, while dorsal, or upper, frontal regions were more tuned to visual input.

“This suggests the frontal cortex has an organized map for handling different kinds of information during real-world experiences,” said first author Faxin Zhou, a Ph.D. candidate in the NYU Tandon Biomedical Engineering Department. “It is not just a general control center, it appears to separate sound and sight in a structured way.”

The pattern became even more interesting when the language changed. During English-language scenes, when listeners could understand speech directly, frontal brain areas leaned more heavily on auditory processing. But during scenes in unfamiliar languages, activity shifted toward visual regions, suggesting viewers relied more on facial expressions, gestures, and subtitles to follow the plot.

To confirm that interpretation, the team recruited online volunteers to rate short clips from the film. Participants judged which moments were most important to understanding the story and whether audio or visual cues were more useful in each scene. Those ratings closely matched the neural data: spoken English favored sound, while foreign-language scenes favored visual cues. In other words, the brain appears to reweight its sensory priorities on the fly.

“When comprehension through speech becomes harder, the brain flexibly reallocates resources toward visual signals,” said senior author Adeen Flinker, Associate Professor of Biomedical Engineering at NYU Tandon and Neurology at NYU Grossman School of Medicine. “That adaptability may be essential for navigating everyday environments filled with competing information.”

The findings help illuminate a long-standing question in neuroscience: how the brain merges multiple senses in realistic settings. Much prior research has relied on simplified laboratory tasks. Movies, by contrast, more closely resemble real life, where sensory cues arrive continuously and unpredictably.

The study also hints that the frontal cortex may do more than merge information after the fact. It may actively decide which stream — sound or sight — deserves priority before conscious understanding emerges.

That insight could have practical implications. Better understanding how the brain reallocates sensory attention may help researchers design therapies for people with language disorders, autism, attention deficits, or hearing loss. It could also inspire more adaptive artificial intelligence systems that shift between audio and visual inputs depending on context.

The work has limitations. Because the participants were hospital patients with epilepsy, they may not perfectly represent the general population. Electrode placement was determined by medical need, not experimental design, leaving some brain areas less sampled than others. Still, the precision of direct neural recording offers a rare glimpse into how the living human brain manages everyday perception.

*"Foreign Language," Adam Kelly Morton, Ack, No Ledge Creative

Zhou, F., Khalilian-Gourtani, A., Dugan, P. et al. Frontal cortex organization supporting audiovisual processing during naturalistic viewing. Nat Commun 17, 5355 (2026). https://doi.org/10.1038/s41467-026-73947-8

As robots increasingly move out of factories and into workplaces, hospitals, warehouses and public spaces, a simple challenge becomes increasingly important: helping people understand what those machines are about to do.

A new study by researchers at Bowling Green State University (BGSU) and NYU Tandon suggests that augmented reality (AR) may offer a surprisingly effective solution. By overlaying a robot's goals, planned routes and safety zones onto the real world through a smartphone, the researchers found that people became significantly better at anticipating robot behavior and identifying potential hazards.

The work, published in the journal Empathic Computing, addresses a growing concern in human-robot interaction: transparency. While robots are becoming increasingly autonomous, their decision-making processes often remain opaque to nearby humans. That uncertainty can create confusion, reduce trust and, in some situations, compromise safety.

"One of the biggest challenges in human-robot collaboration is helping people understand what a robot intends to do before it acts," says co-author Vikram Kapila, Professor of Mechanical and Aerospace Engineering at NYU Tandon. "When users can see a robot's planned path, destination and safety boundaries, they are better able to anticipate its actions and make informed decisions about their own movements."

To tackle the problem, the researchers developed a smartphone-based AR application that communicates a mobile robot's intentions in real time. Using a standard Android phone equipped with Google's ARCore software, the system overlays digital information directly onto the user's view of the physical environment.

The application provides three types of visual information. One mode displays the robot's destination as a virtual location pushpin. Another reveals the route the robot plans to follow. A third shows a digital twin of the robot itself moving through the environment, complete with a visual buffer zone indicating areas where collisions or interference could occur.

Unlike many previous AR systems, which rely on specialized headsets or projection hardware, the new approach works on an ordinary smartphone. That simplicity could make the technology easier to deploy in workplaces where workers and autonomous machines routinely share space.

To test whether the system actually improved understanding, the researchers recruited 58 participants with varying levels of experience in robotics and augmented reality. Participants viewed a series of AR scenarios showing robot navigation tasks and then answered questions designed to measure what human-factors researchers call situational awareness — the ability to perceive, understand and predict events unfolding in an environment.

The evaluation was based on the Situational Awareness Global Assessment Technique, or SAGAT, a widely used framework that measures three levels of awareness: perception of relevant information, comprehension of its meaning and projection of future events.

Participants were asked to identify robot goals, recognize obstacles, determine whether objects would interfere with the robot's movement and predict which areas of the environment would remain safe for human occupancy.

The results were striking. Across all tasks, participants achieved an average situational-awareness score of 86.5 percent. They were particularly successful at recognizing obstacles and identifying safe zones where they could avoid interfering with the robot's operation.

Just as important, participants reported feeling more confident about working alongside robots. More than 96 percent said the AR interface improved their understanding of robot intentions and increased their confidence in predicting robot behavior.

"The findings demonstrate that even a lightweight, smartphone-based AR system can substantially improve people's awareness of a robot's goals and movements," Kapila says. "That increased understanding is an important foundation for building trust, safety and effective collaboration between humans and autonomous systems," said paper’s lead author Sonia Chacko, Assistant Professor at BGSU, who received her doctoral degree from NYU Tandon.  

The study arrives at a moment when robots are becoming more common in settings that were once the exclusive domain of humans. Warehouses increasingly rely on autonomous mobile robots to move goods. Hospitals are experimenting with robotic delivery systems. Service robots are beginning to appear in airports, hotels and retail environments. In such settings, the ability to quickly understand what a robot is planning to do may be as important as the robot's ability to understand human behavior.

Kapila also recently developed a mixed-reality system that allows people to communicate force instructions to a robot using a tablet. Instead of programming the robot through complex controls, users place a virtual arrow on the tablet screen over a real-world object. The arrow's position tells the robot where to apply force, its orientation indicates the direction of the force, and its length specifies how much force should be used. The robot then carries out the task and provides visual feedback through a moving virtual indicator that shows whether the desired force has been achieved.

The findings reported in the journal Machines, authored by Christian Lourido, Kishan Reddy Raghunath and Kapila, suggest that mixed reality can make human-robot collaboration more intuitive by allowing people to communicate complex physical intentions visually rather than through specialized programming or expensive haptic equipment. Such technology could eventually be useful in manufacturing, healthcare, and other environments where humans and robots must work together safely and precisely.

The findings suggest that making robotic intentions visible may help bridge one of the most persistent gaps in human-machine collaboration. As autonomous systems become more common in everyday life, a digital window into a robot's plans could make working alongside them feel far more comfortable.

Chacko S, Kapila V. Making robots understandable: Augmented reality for enhancing situational awareness in human–robot co-located environments. Empath Comput. 2026;2:202517. https://doi.org/10.70401/ec.2026.0016