Jun Li

And this is how we've seen AI in science lately is, oh, okay, so we need to either, one, the AI models handling the thousands of mundane tests that need to be done in any context.

you know any field whether it's material sciences chemistry you know those kinds of things um or in the design and testing and that's that seems to be the uh the key feature right now is so their ai model came up with 520 different chemical com uh compositions for um uh for for their testing and they were able to find a solution um after testing 11. so

Yeah.

So part of that loop, so they discovered highly fluorescent covalent organic frameworks, the COFs, and after testing only 11 out of 520 designs.

So...

And they, as part of their process, they were able to find a yield of 41.3%.

And part of, I guess, this COF realm of testing is...

is a lot of anything that has to deal with light sensitivity, water testing sensors, and everything that I listed out previously.

So Beth, I'd love to get your thoughts on what kind of benefit do you see from these,

from this particular type of research.

And, or, or even just of those things that I listed, and I'll go through them again, where, where you see, where you will see the biggest benefit.

So let's see, I'll, I'll list it out again.

So it is.

Um, I don't think so.

It's, uh, they call it, um, they, uh, they call it it's photo luminescence.

So it probably does need some sort of, uh, of light source, right?

So this is, this is them looking at it and going, they, um, they run their test.

They talk about quantum-related fields and things like that.

So that's a little deeper into it than I went into the story.

But essentially, it's like this four to six set process, right?