GENERAL INFORMATION

This dataset contains the machine learning model and the training data relating to the manuscript "Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential", by Cao et al.. 

DATA & FILE OVERVIEW

 (1) NNP-model -- the folder contains the deep neural network potential model produced in this work for ZnCl2 solutions. 
 (2) training_data -- the folder contains the full training data for the neural network potential model.
 (3) run-model -- the folder contains input files and starting structures for MD simulation using NNP model for pure H2O and 3.5 m ZnCl2 solution. 

METHODOLOGICAL INFORMATION

Description of methods used for collection/generation of data:
The DNN models were generated using the DeepMD-kit v2.2.1 (https://github.com/deepmodeling/deepmd-kit) software using the DP-GEN methodology (https://doi.org/10.1016/j.cpc.2020.107206).