Meet OMNI-P2x — the First Universal ML Potential for Excited States!

Are universal machine learning potentials for excited states possible?

Such a potential would be a major breakthrough — enabling key applications like the design of advanced photomaterials.

We’ve already seen successful universal potentials for ground states — ANI-1ccx, MACE-OFF, our own AIQM — you name it. Some of these go back to 2017.

But 8 years later, not a single universal potential exists for excited states. So… are there fundamental obstacles preventing them?

We’re excited to share: they are possible. We’ve built the first-ever universal excited-state potential — OMNI-P2x.

It can simulate UV/Vis absorption spectra with quality approaching TD-DFT — but in milliseconds, orders of magnitude faster.

Here’s a real-time demo on the Aitomistic Hub — the simulation finishes in a flash. You can try it yourself online, either on Aitomistic Hub or with a Jupyter notebook on the XACS cloud, or on your computer (👉 instructions and tutorials).

Thanks to its speed and accuracy, OMNI-P2x enables high-throughput virtual screening and affordable excited-state molecular dynamics, something existing ML models struggle with.

Want us to go deeper? A full tutorial or even a live Q&A session? Let us know in the comments!

As with any new approach, questions remain —
but OMNI-P2x is a strong YES to a once open question.