�鶹��Ѱ�����

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 �鶹��Ѱ�����Boulder��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,��, 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?

“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 �鶹��Ѱ�����Boulder's Ascent Deep Tech Community Showcase on June 25, 2025. (Credit: Casey Cass/�鶹��Ѱ�����Boulder)

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.”