Researchers used AI to design a new material that they used to build a working battery – it requires up to 70 percent less lithium than some competing designs.
Look them up. Neurons excite elections in layered plates. It's suspected to be some lost Tesla technology. It may have been around but kept secret for decades. Also, on the known tech side, nuclear bombs generate a ton of neutrons. So harness that energy better and we have a lot more power for cheap. Next gen nuclear tech is cool.
I can't find anything about this. Any "lost/secret Tesla technology" is typically quack snake oil. He's been dead since before nuclear energy was developed.
There's plenty more info too. Those are just top results from the first page.
Tesla had a fire. A lot of his papers were lost and he was notorious for not having much documentation. The technology matches what some people had claimed to be Tesla's free energy machine. Maybe this wasn't it. No one knows. Just because he didn't experiment with fusion or fission that doesn't mean he didn't experiment with neutrinos. There's billions passing through your body right now. Given they interact with gravity and electromagnetism, it is not that hard to believe Tesla may have figured out how to harness them in some super rudimentary way.
Neutrons and neutrinos are different classes of particles. I didn't get any results because you told me the wrong thing to search for. Cursory searches agree with what I said earlier, it's yet another goofy Tesla "free energy" pipe dream. Science has come incredibly far since the early 1900s, no one works as independent inventors or physicists anymore because we have huge institutions and advanced instruments to perform work as a collaboration. Neutrinos only interact with matter very weakly, as you said, so detecting them let alone setting up an absorber is technically challenging. On the other hand the sun gives off a huge amount of energy as electromagnetic waves so it hurts to look directly at it.
Research "photovoltaic solar energy" to learn more.
They used the AI to narrow 23 milliom candidate materials down to a few hundred, then focused on testing the ones out of that set that hadn’t been tested yet.
In terms of AI speeding up research this is enormous.