Dataset of the Deep Potential Long Range Model and the Deep Wannier Model for Describing Solvated Glycine Tautomerism under Electric Field

The "dplr" dataset comprises configurations of glycine molecules in aqueous environments, including zwitterionic, neutral, anionic, and cationic forms, as well as pure water systems. All configurations are labeled using the M06-2X density functional and incorporate 0–1 pairs of hydronium and hydroxide ions to capture water autoionization effects through enhanced sampling techniques. This dataset is used to train the Deep Potential Long Range (DPLR) model to describe the influence of electric fields and interfacial effects on the tautomerism of solvated glycine. The "dpwc" dataset contains the corresponding Wannier centroid positions for the above systems and is used to train the Deep Wannier model. Additional details and data are available at the project’s [Github](https://github.com/Zhang-pchao/research/tree/main/GlycineEfield).