A breakthrough in materials science may offer a powerful tool against extreme urban heat. Researchers have developed a paint using artificial intelligence that can sharply reduce building surface temperatures. According to scientists, this AI-designed paint could lower building temperatures by 5°C to 20°C (9°F to 36°F) compared to regular coatings, potentially cutting cooling costs and easing heat stress in cities.
The findings come as many urban areas continue to face the growing challenge of the urban heat island effect—a phenomenon where concrete and asphalt trap heat, raising temperatures above those in surrounding rural zones.
The AI-generated coatings are designed to reflect more sunlight and release heat more effectively, helping to cool rooftops, vehicles, and even outdoor equipment.
Teams from the University of Texas at Austin, Shanghai Jiao Tong University, the National University of Singapore, and Umeå University in Sweden led the research. Their peer-reviewed study, published in Nature, highlights how artificial intelligence can streamline the development of advanced materials and speed up innovation.
Energy savings could power thousands of AC units
The study finds that coating the roof of a four-story apartment building in hot cities like Rio de Janeiro or Bangkok with the AI-formulated paint could reduce electricity use by as much as 15,800 kilowatt-hours per year. Applied at scale—say, to 1,000 similar buildings—the energy savings would be enough to power over 10,000 air conditioning units for a year.
Professor Yuebing Zheng, who co-led the project at the University of Texas, said machine learning changed how researchers approached the problem. “What once took a month can now be done in just a few days,” he said.
“Now, we follow the machine learning output, [its instructions for] the structure and what kind of materials we should use, and we can get it right without going through many, many design and fabrication testing cycles.”
This research contributes to a growing trend where artificial intelligence is transforming how scientists design new materials. In the past, developing a coating or magnet might have required countless cycles of lab work. Now, researchers can ask an algorithm to find materials that match desired features and receive reliable options in a fraction of the time.
AI speeds up discovery and flips the research process
The British company MatNex, for example, utilized AI to create a magnet that avoids rare earth metals, which are costly to mine and harmful to the environment.
Microsoft has also introduced tools to help researchers design materials for solar panels and medical devices. There is growing optimism that similar methods could improve batteries or help remove carbon from the atmosphere.
Dr. Alex Ganose, a chemistry lecturer at Imperial College London, said AI is shifting the process entirely. “Things are moving very fast in this space. In the last year or so, there have been so many startups trying to use generative AI for materials,” he said.
As global temperatures rise and energy demand grows, scientists say tools like AI-designed paint could become essential in helping cities and buildings stay cooler and more efficient.
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