Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning
(2009)
Journal Article
It is widely accepted that correctly accounting for polarization within simulations involving water is critical if the structural, dynamic, and thermodynamic properties of such systems are to be accurately reproduced. We propose a novel potential for... Read More about Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning.