Dr. Qichao Hu

So map it meaning dry data and the wet data.

Dry data just use computing horsepower and then compute all the properties.

And the wet data is basically we have these high throughput robots that actually run these experiments 24 seven and then collect the wet data.

And so we use the wet data to calibrate the computer dry data.

And then we end up with this modern day encyclopedia.

And then this, we can feed it into new models that we are developing for the different applications.

So this goes way beyond just batteries.

And the goal is to apply this to almost any material R&D.

So the other day we had this, so one of our employees is working on a,

project with a home goods product.

It's basically detergent, and he's testing different cocktails for detergent.

And that's quite similar.

That's cool.

Yes, because if you only do the dry computation, it's not very accurate.

I'll give you one example.

If you just use models to compute, for example, melting point and boiling point of certain molecules,

Typically, you're off by 30, 50 degrees Celsius.

But if you have actual data from the wet lab, like actual raw data, and then you use those to calibrate, then that error bar can shrink to maybe plus minus two or five degrees.

Yeah.

So the dry data really allows you to map a much bigger map.