Betting on AI and Robots to Automate Superconductor Discovery

Dozens of materials today outperform the world’s most common superconductor— niobium-titanium (NbTi). But no competing material can beat niobium-titanium’s ability to be manufactured at scale and rolled out into usable wire. Two startups say that AI and robots could help close that gap.

The San Francisco-based Periodic Labs and Cambridge, Mass.-based Quantum Formatics are searching for materials that work at temperatures higher than 10 Kelvin (−264 °C), the transition temperature of NbTi, below which it loses all electrical resistance. Quantum Formatics has several candidate materials for a new generation of superconductors. Company founder Jason Gibson says the company is about a year away from making a prototype wire that can be used in qualification tests to demonstrate superconductor performance.

“We’re trying to get operating temperatures of 10 to 20 K,” says Gibson. “We focus on moderate-temperature superconductors with excellent mechanical properties that lead to good manufacturability. This approach means we can adopt a standard wire manufacturing process.” Periodic Labs co-founder Ekin Doğuş Çubuk says his company, established in September 2025, has developed a technique based on x-ray diffraction.

XRD, as it’s called for short, is a method of mapping the atomic structure of a material by bouncing x-ray beams off it. Periodic Labs’ XRD procedures help the company to study candidate superconductors and automate its superconductor discovery process, says Çubuk.

Periodic Labs cofounder Ekin Doğuş Çubuk says the company has pioneered an AI-powered robot arm system that can test 1,000 candidate superconductors per day. Richard Morgenstein/Periodic Labs How Can Robots and AI Help Discover New Superconductors.

Because no human can sift through thousands of XRD patterns a day, the company is developing machine-learning algorithms to use XRD and measure materials’ magnetic properties to speed detection of new superconductors. “We have built robots that can physically use x-ray diffraction machines,” Çubuk says.

“Robotic arms load samples, and then the measurement gets done, sent to an LLM. The robot takes a sample out, puts in a new sample, and then the LLM analyzes all the X-ray diffraction patterns to determine if the experiment worked—and if it didn’t work, what to do next.” Çubuk adds that developing and creating new materials from scratch hasn’t been easy to automate.

“Our biggest bottleneck is being able to make these different materials for the first time,” says Çubuk, previously a research scientist at Google DeepMind. Meanwhile, according to competing teams also using AI to make progress in the field, new superconductor discoveries are hotly anticipated today.

“Magnets could come very fast if we are very lucky and find something very easily,” says Päivi Törmä, the leading physicist of the SuperC consortium of European and American universities aiming to make the first room-temperature superconductors by 2033. New superconductors can boost energy efficiency in data centers and hospital magnetic resonance imaging equipment by an order of magnitude, she says.

“I made estimates based on the best data that I could get,” Törmä says. “For sure, it’s 10 times more, but it can easily be 100 or 1000 times more energy efficient.” Periodic Labs has been conducting 100 experiments a day, according to Çubuk.

The company is also opening a second lab to accelerate testing. “That’s going to ramp up to 1,000 attempts a day,” Çubuk says.

“I think that will be by far the highest-throughput superconductivity research ever done. We want to see by doing 1,000 good attempts a day if we can discover really exciting superconductors.” Quantum Formatics is using what it calls The System, its proprietary AI-accelerated superconductor-discovery algorithm.

The company has published three articles in Nature Computational Materials describing how its automated discovery system works. Quantum Formatics founder Jason Gibson says AI can assist in the discovery of hardened superconductors, to power strong magnets for nuclear fusion—since existing magnets turn brittle in a reactor’s high-radiation environment.

Minks Media “We realized there was a critical gap between where the research of superconductor discovery was and what actually gets implemented in a device,” says Quantum Formatics’ Gibson. “Dozens of superconductors have been discovered that vastly exceed the superconducting properties of NbTi.