by Microsoft announced Tuesday that a team of scientists used artificial intelligence and high-performance computing to plow through 32.6 million potential battery materials — many not found in nature — in 80 hours, a task the team previously estimated would take 20 years. . The findings kick off an ambitious effort to create a new generation of batteries that rely less on toxic and environmentally damaging lithium.
The company shared some of the best candidates with the government’s Pacific Northwest National Laboratory in Richland, Wash., which investigated the most promising and built a prototype battery using a brand new material.
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While the dime-size prototype isn’t yet ready for a prime-time role powering today’s watches and car keys, it operates using less lithium than commercially available options and has the potential to power to recharge. Furthermore, this achievement demonstrates the potential of new technologies to revolutionize the underappreciated but rapidly developing field of materials science.
“It’s no exaggeration to say that almost every major problem we face as a society could have better materials,” said Christopher M. Wolverton, a professor at Northwestern University’s department of materials science and engineering. . Wolverton, who was not involved with Microsoft’s battery project but has worked on similar projects of his own, called the company’s claim that it filtered 32.6 million items in 80 hours “scenic.”
“I’m told right away 32 million they weren’t screening [just] known subjects,” he said. “They were screening for new hypothetical subjects they hoped to discover.”
Like other outside experts interviewed, he was able to review news releases from Microsoft and the Pacific Northwest National Laboratory but was unable to see the scientific paper describing the work before it was released. The paper, which has not yet been peer-reviewed, was posted Tuesday on the science preprint site arXiv.
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High-powered mixing and matching
Although estimates vary, experts generally estimate that there are about 200,000 known materials worldwide, and materials scientists continue to look for new ones that may hold the key to solving some of the planet’s most pressing challenges. solution.
To combat climate change, scientists need to find the best materials to capture and store carbon dioxide in the atmosphere. To reduce the huge accumulation of plastic trash beaches, blocking landfills and threatening human health, scientists need to find safe ways to break it down into fuel and raw materials. To respond quickly to new pathogens that can cause future pandemics, scientists need to design effective drugs that use proteins to attack viruses and bacteria or to stimulate the body’s defenses.
They all depend on finding the right materials, a process slowed by a hypothesis-driven trial-and-error approach.
High performance computing and artificial intelligence are now allowing scientists to quickly use the elements in the periodic table as a painter might use a palette of colors, mixing them and finding new formations.
“This is a new way of doing science,” said Nathan Baker, author of the paper and senior director of partnerships for chemistry and materials at Microsoft. The project used the company’s Azure Quantum Elements platform, unveiled in June with the aim of using high computing power to speed up the discovery process.
Starting with all the known materials, Baker said, “we can basically pick up the periodic table and drop new atoms in. [various] locations through a process of representation.”
Azure Quantum Elements quickly weeded out materials that are poor conductors, too unstable, too reactive or too expensive to use for batteries. The high-performance computing used by Microsoft essentially harnessed the power of about 5,000 standard laptops. Baker emphasized that when they had early results, Microsoft consulted with subject matter experts at the government laboratory believing, “Okay, a computer gave us the answer…. Let’s go create.”
Officials with Microsoft and the national lab said they will continue the battery project as part of a three-year collaboration aimed at accelerating the pace of innovation and discovery.
“This is not just a stunt announcement, a headline-grabbing announcement. This is the nature of things to come,” said Chirag Dekate, vice president and analyst at the Stamford, Conn.-based research and consulting firm Gartner who was not on the research team.
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The hunt for a better battery
The need for better battery technology has emerged as a major challenge facing scientists.
“Many of the current battery technologies are very inefficient,” said Dekate. “If you look at one of the reasons why the promise of a green future has so far faltered despite advances in solar and wind. [power]if you look at the root cause, it’s really the challenges of battery technologies.”
Lithium-ion batteries power most electric cars as well as most of the electric scooters and electric bicycles that have become ubiquitous in modern cities around the globe. In 2022, the global lithium ion battery market size was valued at $46.2 billion, and the industry is expected to reach $189.4 billion by 2032.
But the current crop of batteries cannot charge quickly or hold their charge for long periods. In addition, some have been proven to be volatile.
In 2023, the New York fire department reported that 18 people died in fires involving electric vehicle batteries.
Microsoft searched for materials to build a solid-state electrolyte battery; these have a greater energy density than liquid ion batteries and do not pose a risk of fire or leakage. The material used for the prototype contained some lithium ― but up to 70 percent less than that found in current batteries.
Microsoft’s work on the battery project “started in earnest about nine months ago,” Baker said.
The team trained their artificial intelligence system by showing it samples of different materials, helping it learn their crystal structures and energetic properties. “As we go through different compositions, he starts to learn how structure and composition relate to energy,” Baker said.
The Microsoft team then used AI to act as a funnel. Many possibilities were added to the top of the funnel and then passed through various filters that narrowed down the list of candidates. The best ones emerged from the bottom of the funnel.
Since battery material must be stable, the artificial intelligence began by filtering the number of candidates just below 590,000 that would remain in the form required to function in a battery. From there, the AI basically asked each candidate: Will it react to oxygen? Will it do something weird when an electric current is applied across it? How do you get lithium atoms to move through the material, a necessary process for a battery to function?
Eventually, Microsoft contacted the Pacific Northwest National Laboratory, which has deep experience in battery research.
“They asked, what properties would you typically need from a material to make a better battery?” said Vijay Murugasan, co-author of the paper and head of the lab’s materials science group in the Division of Physical Sciences. He called it a huge challenge to develop a solid material that will only allow lithium ions to move from one side of the battery to the other.
When he examined a list of the top 120 to 130 candidates, Murugesan said his reactions varied from “Why? What really?” to some of the most surprised candidates “I see that the next step is clear from what we are doing.”
The scientists said they were encouraged by the fact that some of the subjects proposed by artificial intelligence had already been pointed out by experts as promising.
The laboratory staff analyzed the best candidates and produced a handful of hypothetical subjects that the computers imagined. The new material chosen for the prototype contains some lithium along with sodium, chloride and yttrium. The lab is doing further work on the material used for the prototype and is preparing to investigate at least two more candidate materials.
Responding by email to a preview presented by Microsoft, Aron Walsh, professor and chair of content design at Imperial College London, said, “AI is providing a new generation of relatable yet practical tools, enabling us to tackle problems that previously seemed impossible. , like the rapid exploration of large chemical spaces described here.”
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