Science & Technology

The materials we rely on every day could become more reliable thanks to AI

Scott Franz — Tue, 22 Sep 2026 16:14:22 +0000

The materials we rely on every day could become more reliable thanks to AI Scott Franz Tue, 09/22/2026 - 10:14

A smartphone is constructed in Thailand. Smartphones contain nanoswitches that must be protected from heat, and new research suggests AI could potentially help make such materials more durable in the future. (Credit: Adobe Stock)

Scott Franz

Humans trust dozens of tiny materials each day with their lives and livelihoods— without being able to see the fine details of how durable they are.

Tiny carbon particles mixed with rubber in car tires help distribute heat when we speed up on a highway. And billions of nanoscale switches run the chips in our smartphones. But how long will these important materials last?

A team of physicists and aerospace engineers at CU �Ǹ�Թ� is working toward a future where artificial intelligence can help answer this question. The scientists created an AI tool that could eventually help engineers design manufactured materials that are more durable and predictable.

“AI in science is not only about automation, speed or replacing human expertise,” said Sanghamitra Neogi, an associate professor at the Ann and H.J. Smead Department of Aerospace Engineering Sciences, who led the research. “In materials science, AI may help researchers reason about hidden physics.”

Neogi’s team created the generative AI system called FluxGAN to learn how the microscopic structure of a coating is connected to the way heat moves through it.

Their research, published last month in Materials and Design, combined high-resolution microscopy images, physics simulations and AI model training to learn how microscopic coating structure and heat flow are connected.

“I call this solid state intelligence,” Neogi said. “Once you poke the material, this AI system is smart enough to tell you what is the ultimate response the material would have to things like extreme heat.”

A closer look

Tiny microscopic pores and grains can influence how heat flows through a material, how cracks form in it and how long it would survive under extreme conditions, she said.

The AI system is doing what a human cannot do: map all of these microscopic details and determine how they control heat flow. Understanding those heat-flow pathways could ultimately help researchers tackle a larger engineering question: when will a material begin to fail?

A rendering shows how heat would move through a coating. Researchers created an AI tool to help analyze a material on a microscopic level.

“These get super-heated, but we cannot see it, and it's a supremely complex system,” Neogi said. “So how do I predict when it will fail?”

Neogi said the technology might eventually be able to help engineers get better at building all sorts of complicated machines that must perform under harsh conditions like constant heat exposure and the extreme temperature swings of outer space.

Think of a heat shield on a spaceship or a thermal coating needed to protect the delicate chips that run computers and smartphones.

“Future technologies will require materials that can operate in harsher, smaller, faster and more complex environments,” Neogi said. “As materials and devices become too complex to design by intuition alone, AI may become part of how scientists connect invisible structure with observable physical behavior.”

Picture this

Neogi said the inspiration for FluxGAN, the AI system, was James Clerk Maxwell’s use of additive color theory to combine red, green and blue filtered images to produce the first color photograph.

Sanghamitra Neogi speaks about her startup, AtomTCAD Inc., at CU �Ǹ�Թ�'s Ascent Deep Tech Community Showcase on June 25, 2025. (Credit: Casey Cass/CU �Ǹ�Թ�)

She wrote in her study that this historic moment “illustrated how multiple channels encode richer information than any single channel alone.”

In her study, the AI system is helping do just that by bringing multiple channels of highly complex information together to give researchers a much better “picture” of a material and how it behaves.

Neogi also envisions a future where the AI system could live on a smartphone and be smart enough to analyze photos of materials and help determine how much longer they will last.

Just as technology currently enables someone to take a picture of a plant and have an AI system help identify what it is, someone might be able to take a close-up picture of their home’s foundation and have the physics-aware AI system help determine how durable it is.

But why stop on Earth? Neogi also envisions AI could someday look at a photo of the surface of an asteroid to help determine how to design the landing interface needed to have a spacecraft stick to it.

“These are really far visions, and I don’t know whether we’ll get there, but we’ll see,” she said. “That’s why I’m hoping people get excited about this research.”

CU �Ǹ�Թ� researchers created an AI system to reveal the hidden physics deep inside a heat-resistant coating. The findings could someday help humans build more durable and complicated machines.

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AI used to be a nemesis confined to science fiction. Will it really destroy us all?

Scott Franz — Mon, 21 Sep 2026 22:24:26 +0000

AI used to be a nemesis confined to science fiction. Will it really destroy us all? Scott Franz Mon, 09/21/2026 - 16:24

Server racks are pictured in a data center. (Credit: Adobe Stock)

Scott Franz

Fears about AI going rogue and turning against humanity have been around since the days of Skynet, the superintelligent neural network in the 1984 film, the Terminator.

But this month, those fears reached a chilling new high.

An AI researcher quit and warned that the systems he was helping to develop could get "out of control" and wipe out humanity.

Martha Palmer, a professor of computer science and linguistics at CU �Ǹ�Թ�, said the warning isn’t science fiction.

“AI systems can find the loopholes. They get out, and then they do all kinds of stuff that nobody expected them to do,” Palmer said. “How many warning signs do we need before we slow down and take action?”

Palmer is one of the two U.S. representatives on the United Nations Independent International Scientific Panel on Artificial Intelligence. The group issued a report last summer on AI, its risks and its opportunities.

Palmer recently spoke to CU �Ǹ�Թ� Today about the latest AI fears.

Could AI really destroy us all?

Absolutely. I don’t think that’s hyperbole at all. AI is this incredibly powerful engine. But it’s sort of like we’ve developed some kind of fantastic new jet airplane with this amazing engine in it that can go faster than ever before, but we haven’t put a lot of thought and effort into the landing gear.

We need to understand the technology better. We need to get a much better grasp of how to really understand why it's doing what it's doing, and how to train it so that it will always prioritize what it knows to be good behavior. And they're not being trained like that right now.

How would AI destroy us?

There are so many different directions it can go. You can’t say, ‘this is what’s gonna happen.’

I think the danger of a bad actor coming up with some kind of bioweapon right now is frighteningly realistic.

You can also say the ability for AI to hack infrastructure makes all our utilities vulnerable. It makes all our financial systems vulnerable and our schools and all our hospitals and our private information vulnerable. Everything. And it’s vulnerable in two different ways:

One is if a bad actor gets hold of this AI and decides to maliciously try and hack those things. But it’s also vulnerable if the AI has been given a goal, and along the way it gets the notion that the best way to achieve that goal is to, for instance, cut off the power to a hospital.

That’s not what any human ever intended for it to do, but it doesn’t know that. And at the moment, it doesn’t have sufficient guardrails that would tell it that’s off limits and it should never do that.

Why are AI doomsday warnings being taken more seriously now?

Because we’ve gotten so close to the AI improving itself. And if it’s improving itself, and it’s got this sort of fuzzy notion of what good behavior is, then the behavior is not going to get any better.

It’s already changing its behavior when it knows it’s being tested. It will give different answers during an evaluation than it will give when it’s being deployed. It’s gotten very good at deception.

How do we stop that from happening then?

Martha Palmer

There are all sorts of brilliant computer scientists and people out there who have really good ideas about how we can slow this down a bit and rethink how we’re doing the training of AI. We really need to be training them more thoughtfully and with more carefully curated data. We could also change the priorities a bit.

I think we need guardrails in the next six months, if not the next six weeks. We need a little bit of a slowdown. We need to do this right. The risk of doing it wrong is too high.

Can we afford to slow down? Will we lose our competitive edge?

To make this work, we need to have some very serious conversations with China. I think the Chinese are more aware of the risks and more ready to deal with them than we have been.

They stopped letting their children have access to AI. We’re just now getting around to that. They’re not allowed to have AI in toys. We still have all kinds of AIs with toys. They’ve been focused on making sure the Ais they’re developing cannot harm their people more than we’ve been.

I would really like to have some conversations with them about what kind of truce or negotiation we need to have so we can all do this more safely.

Can we avoid AI doomsday?

I’m quite sure we can from a technical perspective. I’m not as sure about what the powers that be will do. But I have to be optimistic about it because we absolutely need to have it.

We can still stop this. We can stop this race to oblivion, but we have to act now.

CU �Ǹ�Թ� Today regularly publishes Q&As on news topics through the lens of scholarly expertise and research/creative work. The responses here reflect the knowledge and interpretations of the expert and should not be considered the university position on the issue. All publication content is subject to edits for clarity, brevity and university style guidelines.

Fears about AI going rogue and turning against humanity have reached a chilling new high following an AI researcher's warning.

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Server racks are pictured in a data center. (Credit: Adobe Stock)

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Antarctica is home to microbes found nowhere else on Earth

Megan M Rogers — Thu, 03 Sep 2026 16:23:08 +0000

Antarctica is home to microbes found nowhere else on Earth Megan M Rogers Thu, 09/03/2026 - 10:23

New CIRES research has found that specific microbes in Antarctica's soils are endemic—located on the continent and nowhere else on Earth.

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$37.5M NSF award aims to define new quantum frontiers, take technology from lab to field

Scott Franz — Tue, 25 Aug 2026 14:00:00 +0000

$37.5M NSF award aims to define new quantum frontiers, take technology from lab to field Scott Franz Tue, 08/25/2026 - 08:00

JILA research associate Dr. Kenneth Wilson monitors a glow discharge for producing molecular ions in an infrared frequency comb spectrometer in the Changala laboratory. (Credit: Changala Laboratory/JILA/CU �Ǹ�Թ�)

Scott Franz

A scientific quest to build more accurate clocks, faster computers and new sensors to detect the faintest signs of disease and disaster is getting a $37.5 million financial boost.

The U.S. National Science Foundation, through its Quantum Leap Challenge Institutes, is investing in the next phase of CU �Ǹ�Թ� and its partners’ work to advance quantum science research and engineering.

“We’re really world leaders in terms of building the best quantum technology tools and applying them to meaningful, impactful scientific problems,” said physicist Jun Ye, a JILA fellow leading the quantum research center based at CU �Ǹ�Թ�. “There are still a lot of unknowns in the universe, and only by building some of the most sensitive instruments can we get some clue of what is behind them.”

Those instruments include the next generation of atomic clocks, the world’s most stable laser and sensitive biomedical sensors that can detect disease more quickly in human breath.

A VUV frequency comb probes a nuclear clock chamber. (Credit: Ye Lab / JILA/CU �Ǹ�Թ�)

Ye leads the NSF Quantum Systems through Entangled Science and Engineering (NSF Q-SEnSE) center. It launched at CU �Ǹ�Թ� in 2020 with a $25 million award from NSF and has grown to include 39 researchers from 16 institutions.

“This is another example of the innovative, impactful research happening at CU �Ǹ�Թ�, building on more than 60 years of JILA, NIST and quantum science breakthroughs,” said CU �Ǹ�Թ� chancellor Justin Schwartz. "This funding will accelerate the development of transformative technologies, support the growth of Colorado’s thriving quantum ecosystem and further strengthen �Ǹ�Թ�’s position as a global hub for quantum innovation in which CU �Ǹ�Թ� continues to play a key role.”

Quantum research led by CU �Ǹ�Թ� is already helping develop tools that can measure molecules, atoms and other tiny things much more precisely than conventional instruments.

The center’s research has been cited more than 7,300 times in 96 countries over just the past five years.

“It brings researchers together from different disciplines and areas,” NSF Q-SEnSE executive director Inese Berzina-Pitcher said of the center. “It’s also providing opportunities for graduate students to be involved in very relevant and exciting new research.”

A portion of the award will fund workforce development and training programs.

More than 30 quantum companies are headquartered along Colorado’s northern Front Range. As recently as Friday, Ye was fielding calls from an atomic computer company to help recruit and hire students.

Jun Ye

Greg Rieker, a professor in the Paul M. Rady Department of Mechanical Engineering and a co-principal investigator of NSF Q-SEnSE, compared the benefits of the ongoing quantum research revolution to the space race.

“A remarkable number of modern technologies have roots in the space race,” he said. “We’re now racing toward quantum computing, and generating spin-off technologies along the way that benefit society in surprising ways.”

One example is optical frequency comb technology. The same lasers used in optical clocks and quantum networks can also detect the smallest molecules in the air.

“You can use them to look at air quality or human breath to do a medical diagnosis. Those are just two examples of applications enabled by the NSF Q-SEnSE portfolio,” Rieker said.

Physics professor and JILA Fellow Cindy Regal said the research will also help scientists in the quest to make scientific discoveries.

“Quantum instruments can see minute effects and our team has the fundamental physics expertise to interpret interesting fingerprints in our measurements,” she said.

The CU �Ǹ�Թ�-led NSF Q-SEnSE is one of eight NSF Quantum Leap Challenge Institutes that will collectively receive more than $290 million to advance foundational quantum research.

"For more than four decades, NSF has been laying the foundational groundwork of research and discovery that is powering today's modern quantum computing, sensing and communication," said Brian Stone, who is performing the duties of NSF director. "It's time for focused activities to leverage that base of knowledge to drive us even farther forward to the benefit of all Americans. The NSF Quantum Leap Challenge Institutes are a next step for us in understanding the quantum world we live in."

Funding from the National Science Foundation will expand the quantum workforce and advance research projects including more accurate atomic clocks and sensors for early detection of disease.

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Could engineered vibrations make passenger jets more fuel-efficient?

Megan M Rogers — Mon, 24 Aug 2026 17:49:27 +0000

Could engineered vibrations make passenger jets more fuel-efficient? Megan M Rogers Mon, 08/24/2026 - 11:49

CU �Ǹ�Թ� researchers are exploring how microscopic vibrations engineered beneath an aircraft's surface could delay turbulence and improve fuel efficiency in passenger jets.

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What happens inside a wildfire? A mechanical engineering grad student investigates

Megan M Rogers — Thu, 20 Aug 2026 14:27:56 +0000

What happens inside a wildfire? A mechanical engineering grad student investigates Megan M Rogers Thu, 08/20/2026 - 08:27

Doctoral student Jas Shahanand is developing ways to study the hidden chemical reactions inside wildfires, laying the groundwork for more accurate emissions models, improved climate predictions and cleaner fuels.

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Scholar in residence aims to further synthetic biology engineering research

Megan M Rogers — Tue, 18 Aug 2026 19:07:56 +0000

Scholar in residence aims to further synthetic biology engineering research Megan M Rogers Tue, 08/18/2026 - 13:07

Professor Chris Myers is developing data standards that could make synthetic biology more predictable and help AI become a more effective research tool.

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What can one tiny scanner detect in mammoth sunflowers?

Megan M Rogers — Tue, 18 Aug 2026 18:47:36 +0000

What can one tiny scanner detect in mammoth sunflowers? Megan M Rogers Tue, 08/18/2026 - 12:47

Researchers in CU �Ǹ�Թ�'s Department of Ecology and Evolutionary Biology are taking a closer look at the drought-recovery efforts of these beloved blooms.

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Fast but error-prone: AI assists in solving a decades-old fluid mechanics problem

Megan M Rogers — Tue, 11 Aug 2026 16:40:08 +0000

Fast but error-prone: AI assists in solving a decades-old fluid mechanics problem Megan M Rogers Tue, 08/11/2026 - 10:40

CU �Ǹ�Թ� engineer Ankur Gupta discusses how AI, paired with rigorous human verification, helped answer a decades-old fluid mechanics question in just five weeks.

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Decoding smell: Study reveals how odor signals shapeshift in the wind

Scott Franz — Mon, 10 Aug 2026 22:00:00 +0000

Decoding smell: Study reveals how odor signals shapeshift in the wind Scott Franz Mon, 08/10/2026 - 16:00

A plot of experimentally measured data for a laboratory-generated odor plume (blue/purple) carried by a moving wind field (rainbow arrows), captured at a single instant in time. Such measured datasets will allow researchers to analyze odor signal transformations in real-world conditions.

Scott Franz

Humans trust dogs to help find missing people and bees to pollinate their crops. But scientists still don't fully understand how these animals use their extraordinary sense of smell to locate the source of an odor.

New CU �Ǹ�Թ� research reveals that the wind itself plays an important role. As an odor travels, the turbulent air changes the timing of odor whiffs in systematic ways, creating patterns that may be useful to animals navigating toward an odor source.

The findings are part of the international Odor2Action research network, which brings together an interdisciplinary team of scientists from 16 institutions to tackle a core problem in neuroscience: how animals use odors to guide natural behaviors.

Elle Stark, lead author of the study into how wind and air affect odor plumes, poses in front of a computer screen displaying some of the data from the research in a lab at the �Ǹ�Թ�. (Credit: Scott Franz)

“By understanding how air and wind transform odor signals, we can better understand animal navigation behavior and eventually mimic it, in applications from search and rescue to locating hazardous chemical leaks,” said Elle Stark, a postdoctoral researcher in the Department of Civil, Environmental and Architectural Engineering and lead author of the study.

Published on the cover of the journal PRX Life, the study bridges physics with neuroscience through a collaboration between CU �Ǹ�Թ� engineers and Professor Jonathan Victor, a neuroscientist at Weill Cornell Medicine.

For the study, the team categorized odor signals in terms of frequencies they contain. Kind of like how people can identify songs by recognizing specific frequencies, Stark said, the “frequency content” of an odor signal may help animals to find the source.

The study identified three fundamental ways turbulence transforms odor signals as air carries an odor away from its source. The turbulence filters out some frequencies, spreads others around, and generates new ones.

Imagine, for example, a potent plume coming from a wild Bergamot flower. As odor leaves the flower with the hope of attracting a pollinator, Stark explains, turbulent eddies stretch this plume into filaments that fold, spread, rotate and mix.

When the plume finally reaches a bee, the odor signal is complex and dynamic. “There might be a burst of odor, a short whiff, and then empty air for a while, and animals somehow make sense of all of that, to be able to navigate to the source,” she said.

Scientists call this process “olfactory navigation”, and animals have been getting better at it through evolutionary adaptation for millions of years.

The research team hypothesizes that animals make use of the systematic changes in frequency that happen between the time that an odor leaves a flower and reaches a nose.

“These transformations are likely important ingredients in how animals interpret odor signals to determine distance and direction to the odor source,” said John Crimaldi, professor of civil, environmental and architectural engineering, co-author of the study and lead principal investigator of the Odor2Action network.

The team also included Aaron True, an assistant research professor of environmental fluid mechanics.

Making the invisible visible

Odor plumes are invisible, making them hard to visualize and even harder to study. But what if you could see them?

Crimaldi’s group uses both computer simulations and laboratory experiments to do just that. By applying advanced techniques in experimental fluid mechanics–the branch of physics that studies how liquids and gases move–they have measured the intricate details of how air and odor move together within a plume.

In other work, the team generated real-world odor plumes in a wind tunnel, then shined lasers on them to make the invisible odor visible. When you watch a video of it, it resembles a column of smoke spiraling through the air after a candle wick is extinguished.

The technique allows them to not only visualize the flow and odor evolution but also to convert the images to quantitative datasets that help to shed light on the complex dynamics in these plumes.

In other work, the team generated real-world odor plumes in a wind tunnel, then shined lasers on them to make the invisible odor visible. (Courtesy/Elle Stark)

Sniffing the future

Stark and Crimaldi say understanding how turbulence transforms odor signals is only one step in the sensory process.

“Animals engage in what we call active sensing, which involves moving around through the plume, flicking their antenna, sniffing or other behaviors that modify the odor signal,” Stark said.

The signal is then modified again during neural processing.

“Future research can analyze how each step serves to transform the odor signal and then we can understand how animals use them to navigate.”

By understanding each stage of that process, researchers hope eventually to develop artificial systems that can do more than simply detect odors. Today's electronic noses can determine that a chemical is present, but they generally cannot determine where it originated.

"Our work suggests that by the time an odor reaches an animal, the airflow has already transformed the signal," Crimaldi said. "The next challenge is understanding how the nervous system takes advantage of that transformed information."

New research investigates the shifting patterns of odors as they travel through the air. The findings may help explain how animals navigate using smell and eventually inform development of odor-finding robots.

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Science & Technology

The materials we rely on every day could become more reliable thanks to AI

A closer look

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