New material found by AI could reduce lithium use in batteries

[bnew]

New material found by AI could reduce lithium use in batteries

Microsoft said AI and supercomputing were used to synthesise an entirely new material.

www.bbc.com

New material found by AI could reduce lithium use in batteries​

9th January 2024, 11:00 EST

By Shiona McCallum Technology reporter

Dan DeLong for Microsoft

Samples of the new solid electrolyte discovered by Microsoft AI and HPC tools

A brand new substance, which could reduce lithium use in batteries, has been discovered using artificial intelligence (AI) and supercomputing.

The findings were made by Microsoft and the Pacific Northwest National Laboratory (PNNL), which is part of the US Department of Energy.

Scientists say the material could potentially reduce lithium use by up to 70%.

Since its discovery the new material has been used to power a lightbulb.

Microsoft researchers used AI and supercomputers to narrow down 32 million potential inorganic materials to 18 promising candidates in less than a week - a screening process that could have taken more than two decades to carry out using traditional lab research methods.

The process from inception to the development of a working battery prototype took less than nine months.

The two organisations achieved this by using advanced AI and high-performance computing which combines large numbers of computers to solve complex scientific and mathematical tasks.

Executive vice president of Microsoft, Jason Zander, told the BBC one of the tech giant's missions was to "compress 250 years of scientific discovery into the next 25".

"And we think technology like this will help us do that. This is the way that this type of science I think is going to get done in the future," he said.

The problem with lithium​

Lithium is often referred to as "white gold" because of its market value and silvery colour. It is one of the key components in rechargeable batteries (lithium-ion batteries) that power everything from electric vehicles (EVs) to smartphones.

As the need for the metal ramps up and the demand for EVs rises, the world could face a shortage of the material as soon as 2025, according to the International Energy Agency.

It is also expected that demand for lithium-ion batteries will increase up to tenfold by 2030, according to the US Department for Energy, so manufacturers are constantly building battery plants to keep up.

Lithium mining can be controversial as it can take several years to develop and has a considerable impact on the environment. Extracting the metal requires large amounts of water and energy, and the process can leave huge scars in the landscape, as well as toxic waste.

Dr Nuria Tapia-Ruiz, who leads a team of battery researchers at the chemistry department at Imperial College London, said any material with reduced amounts of lithium and good energy storage capabilities are "the holy grail" in the lithium-ion battery industry.

"AI and supercomputing will become crucial tools for battery researchers in the upcoming years to help predict new high-performing materials," she said.

But Dr Edward Brightman, lecturer in chemical engineering at the University of Strathclyde, said the tech would need to be "treated with a bit of caution".

"It could throw up spurious results, or results that look good at first, and then turn out to either be a material that is known or that can't be synthesised in the lab," he said.

This AI-derived material, which at the moment is simply called N2116, is a solid-state electrolyte that has been tested by scientists who took it from a raw material to a working prototype.

It has the potential to be a sustainable energy storage solution because solid-state batteries are safer than traditional liquid or gel-like lithium.

In the near future, faster charging solid-state lithium batteries promise to be even more energy-dense, with thousands of charge cycles.

How is this AI different?​

The way in which this technology works is by using a new type of AI that Microsoft has created, trained on molecular data that can actually figure out chemistry.

"This AI is all based on scientific materials, database and properties," explained Mr Zander.

"The data is very trustworthy for using it for scientific discovery."

After the software narrowed down the 18 candidates, battery experts at PNNL then looked at them and picked the final substance to work on in the lab.

Karl Mueller from PNNL said the AI insights from Microsoft pointed them "to potentially fruitful territory so much faster" than under normal working conditions.

"[We could] modify, test and tune the chemical composition of this new material and quickly evaluate its technical viability for a working battery, showing the promise of advanced AI to accelerate the innovation cycle," he said.

Batteries

Artificial intelligence

Mining

Microsoft

 

[bnew]

https://www.fastcompany.com/91006385/microsofts-lithium-battery-research-bottle-rocket-azure-quantum-elements

• 01-09-24
• 11:00 AM

Satya Nadella on the bigger vision behind Microsoft’s new battery​

Working with a national lab, the software giant used AI to tackle the flaws of today’s lithium batteries—and pave a new path for scientific discovery.​

[Photos: Harry McCracken]

BY HARRY MCCRACKEN 10 MINUTE READ

Recently, Microsoft built a clock.

Well, “built” may be overstating things. Members of the company’s quantum computing team found a small digital clock in a wood case on Amazon—the kind you might mistake for a nicer-than-usual trade show tchotchke. They hacked it to run off two experimental batteries they’d created in collaboration with staffers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL). Then they dressed up its enclosure by adding the logo of Azure Quantum Elements, the Microsoft platform for AI-enhanced scientific discovery that had been instrumental in developing the new battery technology.

The point of this little DIY project was to prove the batteries worked in a visceral way: “You want to have a wow moment,” explains Brian Bilodeau, the head of partnerships, strategy, and operations for Azure Quantum. And the person the quantum team hoped to wow was Microsoft CEO Satya Nadella.

Not that getting Nadella’s attention was such a daunting prospect. Throwing vast amounts of Azure high-performance computing (HPC) resources at a big, hairy technical challenge such as materials research is the sort of challenge he’s predisposed to take a personal interest in. Still, the tangible evidence of success made for a memorable moment: “I was very, very excited to see it come through,” Nadella remembers.

A digital clock and LED lights powered by Microsoft and PNNL’s experimental battery material—and a 3D model of its molecular structure. [Photo: Harry McCracken]

The coin-sized CR2032 batteries powering the clock looked like the ones you might find in a pocket calculator or garage door opener. But on the inside, they used a solid-state electrolyte that replaces 70% of the lithium in garden-variety batteries with sodium. That holds the potential to address multiple issues with lithium batteries as we know them: their limited life on a charge, shrinking capacity over time, subpar performance in extreme temperatures, and risk of catching fire or even exploding. In addition, reducing lithium use in favor of cheap, plentiful sodium could be a boon to the fraught battery supply chain.

With further development, the new material could benefit the myriad aspects of modern life that depend on batteries, from smartphones to EVs to the power grid. But Microsoft, being Microsoft, regards all this promise first and foremost as proof of Azure Quantum Elements’ usefulness to the customers it’s designed to serve. Unveiled last June, the cloud service is currently a “private preview” being tested by organizations such as Britain’s Johnson Matthey, which is using it to help design catalytic converters and hydrogen fuel cells.

Nathan Baker says that Microsoft threw battery research at its scientific discovery platform “to prove to ourselves that it works.” [Photo: courtesy of Microsoft]

Using the evocative term for a tech company living with its products like a customer would, Microsoft senior director of partnerships for chemistry and materials Nathan Baker—who joined the company in 2022 after a dozen years at PNNL—cites the foray into battery research as an example of Microsoft eating its own dog food. When developing a new product, he says, “the first thing you [say] is, ‘Well, let’s, let’s prove to ourselves that it works—let’s try it out for ourselves.”

Nadella, too, emphasizes that the learnings from the battery experiment—which the company dubbed “Project Bottle Rocket”—will go back into improving the Azure Quantum Elements platform. “At the end of the day, it’s about being able to democratize powerful technology so that others can build more technology,” he says. “I sort of refrain from talking about ‘our great scientific achievement.’ That’s not us.”

BEYOND TRIAL AND ERROR​

Even the scientists at 59-year-old PNNL, where building better batteries has long been a key research area, see their collaboration with Microsoft as being about bigger ambitions. Based at a sprawling 664-acre campus in Richland, Washington, 200 miles to the east of Microsoft’s Redmond HQ, its scientists know well how bogged down lab research can get in dead ends. A century and a half ago, Thomas Edison famously tested thousands of filaments before finding one that would make the electric light bulb practical. That willingness to try anything and everything—known as the Edisonian approach—is still reflected in scientific discovery today.

“It’s always trial and error,” says Vijay Murugesan, head of PNNL’s Material Sciences Group. “Something comes up in my dreams or the shower, and then I come in and spend two years testing whether it works or not. And then you go back and do that cycle again for a decade. The success rate is not that great, to be honest.”

PNNL material sciences chief Vijay Murugesan on traditional lab research: “The success rate is not that great, to be honest.” [Photo: Andrea Star for PNNL]

The implications of that traditionally poky pace are sweeping. PNNL’s research initiatives cover ground ranging from coastal science to national security, “The timescale on which we do discovery today isn’t fast enough to meet some of the global challenges we’re trying to address,” says associate laboratory director and chief digital officer Brian Abrahamson. “And if we can move the needle on that significantly, that’s a huge deal.”

Enter Microsoft. Virtualizing some of the up-front work and turning it over to the company’s newest, fastest computers could change everything in the years to come. As Nadella puts it, “We have to take 250 years of progress in chemistry and compress it into 25 years—and the only way to do that is by having a lot of computational simulation power.”

“I was very, very excited” to see the battery work, says Satya Nadella [Photo: Brian Smale for Microsoft]

In the case of the new battery technology, Microsoft began with a data set of 32.6 million materials. Using Azure Quantum Elements HPC resources to run simulations and AI models, it reduced the field of contenders to 500,000, then 500, then 150, then 18. The company consulted with PNNL material-science experts to further winnow the list and ultimately identified the lithium-sodium material as worthy of lab synthesis and testing.

Zipping through so many possibilities and rejecting most of them in the cloud “only took us two weeks,” says Jason Zander, Microsoft’s executive VP of strategic missions and technologies and a 31-year veteran of the company. “That’s dramatically faster than the traditional approach, which sometimes can take years.” In total, the battery project has been underway for about a year, from its inception through the fabrication of around 40 test batteries. (Along with powering the clock, they’ve also been used to light up LEDs in the colors of Microsoft’s corporate logomark: red, yellow, blue, and green.)

The fact that two weeks of high-performance computing was just one element in a year-long research effort is evidence that there’s still a crucial physical element to testing a new material such as Microsoft’s lithium-sodium compound. During my visit to PNNL, materials scientists Shannon Lee and Dan Thien Nguyen walked me through some of the intricate steps involved in validating the material—grinding it up with a mortar and pestle, subjecting it to three tons of pressure, melting it at up to 600 degrees Celsius, inspecting it with a microscope.

PNNL scientist Shannon Lee grinds up some battery material. [Photo: Dan DeLong for Microsoft]

Technical derring-do is sometimes required. Having produced samples of the material Microsoft identified through algorithmic investigation, PNNL’s researchers found it wasn’t exactly a breeze to work with in the real world. “After 30 minutes of just open air, it’ll actually absorb moisture from the air and turn into kind of a goo,” says Lee.

Watching Lee and Nguyen at work, you get the feeling that old-school lab experimentation of the sort that Thomas Edison would instantly recognize isn’t going anywhere—it’s just going to come later in the process, after computers have given it some direction. It’s not a given that a government facility would turn to a platform provider such as Microsoft for help on this front—another Department of Energy site, the Oak Ridge National Laboratory, is home to the world’s fastest supercomputer. But PNNL prides itself on its willingness to embrace the nimble, on-demand resources that cloud services such as Azure Quantum Elements can offer.

 

[bnew]

Coin-sized CR2032 batteries undergoing testing at PNNL. [Photo: Harry McCracken]

“We are exceptionally favorably disposed to commercial partnerships in computing,” says PNNL deputy director for science and technology Tony Peurrung. He adds that “being in Microsoft’s backyard” hasn’t hurt the lab’s relationship with the software giant. (It also has deals with other cloud-computing providers.)[/SIZE]

IT’S NOT QUANTUM COMPUTING (YET)​

By this point, I’m probably overdue to bring up an important point about Microsoft and PNNL’s battery. Despite a platform called Azure Quantum Elements playing a crucial role in developing it, quantum computing was not involved. And yet the Microsoft employees involved do work in the company’s quantum computing group, making the achievement decidedly quantum-adjacent.

All of this is explained by the current state of quantum computers. By leveraging quantum physics, the technology dispenses with a classical computer’s bits—each capable of representing only a one or a zero—in favor of “qubits” that can represent a zero, a one . . . or both at the same time. This mind-bending advance could lead to computers powerful enough to swiftly perform calculations that even today’s fastest computers couldn’t complete in several lifetimes. That would make them ideally suited for jobs with an insatiable hunger for computational resources, such as scientific discovery.

Along with other tech giants such as IBM and Google as well as numerous startups, Microsoft is betting big on quantum’s potential. But “potential” is the right word. Decades after it was conceived, the technology is still a work in progress, not a commercial reality. Experts can make only educated guesses about when it might be ready to tackle serious tasks with epoch-shifting impact: “We do believe it’s measured in years and not decades,” says Krista Svore, Microsoft’s VP of advanced quantum development.

Meanwhile, computers of the more conventional type are nowhere near tapped out. Equipped with massive quantities of ever-more powerful GPU chips, they’re capable of performing increasingly transformative AI feats—not at some unspecified point in the future, but right now. This advance enabled high-performance computing in the cloud—basically, supercomputing as a service—such as the Azure resources Microsoft used to pinpoint its battery material.

The turn of events surprised even quantum champions such as Nadella. “I was thinking, quantum is the next big accelerator,” he told me. “It turned out the GPU was the next big accelerator.”

However quantum computing develops from here, it’s unlikely to entirely displace high-performance computing of the sort Microsoft employed to find its battery material. In the future, Svore predicts, scientists will be able to call on “a tightly integrated system among these three capabilities—HPC, AI, and quantum—that ultimately drives a more accurate solution for types of problems that we can’t solve today.”

Once that era arrives, the avenues for exploration could be unlimited. “What’s always amazing to me is the amount of things that we somehow take for granted, but realize we don’t even [comprehend],” says Zander. “Like we can’t even tell you precisely how photosynthesis actually works.”

For now, Microsoft’s collaboration with PNNL offers one concrete case study in how Azure Quantum Elements can fit into the discovery pipeline. The fundamental relatability of batteries explains why the company settled on them as a research subject: “Quite frankly, it’s something that people understand,” says Bilodeau.

Nobody I spoke with at Microsoft or PNNL got very specific about how the batteries presently in the lab might lead to ones that would be produced at scale. “A lot of work needs to be done before we put something in a consumer’s hand,” acknowledges Murugesan. Obvious short-term steps include fabricating and testing larger batteries, such as the “pouch” cells widely used in consumer electronics, EVs, and other items.

Could there be an eventual Microsoft-sized business opportunity here? The company doesn’t seem indifferent to that possibility, though the details are seemingly TBD. (For what it’s worth, I was asked not to snap any photos of a PowerPoint about the project on the grounds that it might contain information not yet patented.) “Microsoft isn’t going to go into battery manufacturing, and PNNL’s not going to go into battery manufacturing,” muses Bilodeau. “It would be something where we would partner with someone to make the batteries.”

Regardless of what happens with the technology, Microsoft has already achieved the initial goal it set for itself. “The reason I love this is because it proves—not just in theory, but in practice—that you can complete the loop,” says Nadella. “You can [create] a new material that actually works.” And maybe even do it at a clip that would have been unimaginable just a few years ago.

 

[Joe Sixpack]

This is awesome

 

[bnew]

This is awesome

the technological advancements within this decade are gonna happen in cycles that would have taken decades or centuries without AI. a big breakthrough would be retooling labs/factories in such a way as to mass produce new prototypes and creations.

 

[Rice N Beans]

Pretty sure sodium was considered as a possible alternative before ChatGPT?

Also, we should be on Lithium Iron in full swing for our hybrid and BEV vehicles.