Tim Duignan

This is the most surprising and exciting result of my career: we were running simulations of NaCl with a neural network potential that implicitly accounts for the effect of the water, ie a continuum solvent model (trained on normal MD) when Junji noticed something strange: 1/n 

A crystal was nucleating and growing! despite the NNP only being trained on solution data (4 M). Amazingly it has the correct crystal structure, i.e., FCC. This is a phase transitions, an emergent phenomena, totally out of distribution, supposedly where AI is no good.

Impressively this is actually more correct than the all-atom MD as the true solubility of this model is actually very low, all atom MD is just too slow to see it. I think this pretty conclusively disproves the idea that NNPs are only interpolating on the data they are given.

The lattice parameter is a bit high compared to experiment, so we took a KCl coarse grained force field trained on quantum chemical solution MD data and showed that it could simulate crystal dissolution. It maintains the correct lattice spacing and appears to dissolve in the same manner as all atom MD. (Haven’t seen it nucleate yet sadly but it has a much higher solubility.)

I have always assumed it would be impossible to study crystal nucleation etc with a continuum solvent model. Here it just dropped out for free. They're incredibly cheap to run too. ie. tens of cpu hours. More info on continuum solvent models here: https://x.com/TimothyDuignan/status/1789288857663664502

We also simulated LiCl,LiBr and KCl at quantum chemical accuracy and reproduced the ion specific pairing affinities and matching experimental activity coefficient derivatives. Activity coefficients are the most important property of electrolyte solutions, they are ubiquitous throughout chemical engineering.

We also showed you can extract infinite dilution pairing free energies and diffusivities and get almost perfect radial distribution functions with the continuum solvent model and more.

Check out the preprint here: https://arxiv.org/abs/2310.12535
Code etc.:  https://github.com/timduignan/Scalable-Electrolyte-Simulation/
Videos: https://youtube.com/shorts/4ixfnrc-XDg and https://www.youtube.com/watch?v=eAuS4hDXQBo

If you want to know more about how NNPs and why they're so exciting check out this thread and paper: https://x.com/TimothyDuignan/status/1788181545863524608