Posted on 01/19/2024 1:05:22 PM PST by Red Badger
Using AI and cloud computing, Microsoft was able to identify promising new battery materials for the Department of Energy (DoE) — in a fraction of the time it would usually take.
The challenge: Batteries are an essential part of the clean energy future. We need them to power electric vehicles and to store energy from solar and wind.
Currently, lithium-ion batteries are our best option for both of these uses, but they aren’t ideal. Because lithium is relatively scarce, it’s also expensive, and the metal is often unethically mined using child labor and environmentally destructive processes.
Identifying better battery materials is a time-consuming process, though.
“It’s always trial and error,” Vijay Murugesan, head of the Material Sciences Group at the DoE’s Pacific Northwest National Laboratory (PNNL), told Fast Company.
“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,” he continued. “The success rate is not that great, to be honest.”
What’s new? To speed up that process, PNNL teamed up with Microsoft.
Using a combination of AI models and cloud computing, the tech giant simulated potential chemical combinations for batteries, starting from a list of 32.6 million materials. Within just 80 hours, it had identified 18 promising candidates for new battery materials.
“Something that could have taken years, we did in two weeks,” Jason Zander, an executive VP at Microsoft, told Reuters.
Looking ahead: PNNL scientists have already synthesized one of the candidate battery materials for testing — if it performs well, it could enable production of batteries containing 70% less lithium.
They also expect Microsoft’s technology to lead to the discovery of far more than just new battery materials.
“That’s the part we’re most excited about … We just picked one problem,” said Zander. “There are thousands of problems to go solve, and it’s applicable to all of them.”
VIDEO AT LINK....................
Doesn’t mean they are going to make a new and better battery.
Time well tell.
Wow, someone wrote a program to simulate materials.
So amazing.
NOT!!!
I want AI to do drug regime recommendations for heart “failure”.
It also doesn’t mean that the materials they found will work outside laboratory conditions. They may very well have found materials that will form a battery with the same work efficiency as gasoline, 12,000 watts per gallon. However, it might cost $150,000/battery to create.
Good AI is good, bad AI is bad.
QED
Good news AI only works 40 hour weeks!
No, but you can always ask ChatGp to write you one!.......
So Skynet is now producing its own power sources. Marvelous. /s
hey Jason Zander whats up ? long time no see. Say hi to Scott Guthrie and Alex Chi for me
Did it also test the material in a real world lab or an AI lab ?
So why don’t they ask for zero energy production and peer reviewed papers.
I’m researching the nano-tech material graphene for a company. It isn’t just the graphene, but resins and inorganic binders. So I’ve used AI a fair amount.
From my experience it can do wonders, if you think of it as a research ASSISTANT. But it makes mistakes all over the place. It is good for first pass chemistry, but you need to know what you are doing.
I want AI to do drug regime recommendations for heart “failure”.
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Hell I could do that. First off - avoid all covid vaccines.
Now do Cold Fusion.
The author managed to get the two words that kill the entire hopium in just six words, nice work.
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