Microsoft is using powerful computers and artificial intelligence to help researchers speed up the painstaking work required to discover new chemical compounds and materials that could be used for everything from batteries to eco-friendly paints.

The Pacific Northwest National Laboratory used the company’s Azure Quantum Elements service to quickly assess 32 million potential materials for a new battery, according to Jason Zander, Microsoft’s executive vice president for strategic missions and technologies. The US department of energy facility turned up 18 promising candidates after using the service for just 80 hours — a process that would take decades using traditional research methods. AkzoNobel, the paint company, has also used the service to develop sustainable products, while the British chemical maker, Johnson Matthey, is using it to speed up work on hydrogen fuel cells.

Introduced last year, Azure Quantum Elements doesn’t actually rely on quantum computing despite the name. That’s partly because the company’s effort to develop working quantum computers, which use the movement of subatomic particles to process massive amounts of data, is running behind schedule. But Microsoft has been rapidly baking generative AI into most of its products, including this one. “AI isn’t going to just be for helping make Office and enterprise products better,” Zander said. “It’s also going to be something that can accelerate scientific discovery.”

One area of particular focus is the ongoing effort to weed out so-called forever chemicals that have been linked to cancer and are used in hundreds of everyday products — from fabric protectors, electronics and non-stick pans to foams, tapes and even toilet paper. Zander said Microsoft can help customers more quickly find safer alternatives.

Read: Microsoft could send 240 million PCs to an early grave

Ultimately, the company plans to harness the power of quantum computing to accelerate scientific discovery.

“In order to do computational chemistry and molecular science, we need very large-scale quantum computers,” he said. “We’re all working on those, but eventually we will get there.” — (c) 2024 Bloomberg LP