# Multiscale analysis of the effect of surface charge pattern on a nanopore's rectification and selectivity properties: from all-atom model to Poisson-Nernst-Planck

## TL;DR

This study employs multiscale modeling to analyze how surface charge patterns influence nanopore rectification and selectivity, demonstrating that reduced models can effectively replicate device functions across various charge configurations.

## Contribution

It introduces a multiscale approach combining all-atom MD, Monte Carlo, and PNP models to understand nanopore behavior and relates diffusion coefficients across models.

## Key findings

- Reduced models accurately reproduce device functions.
- Diffusion coefficients are sensitive to net pore charge.
- Implicit-water models can be calibrated to match explicit-water results.

## Abstract

We report a multiscale modeling study for charged cylindrical nanopores using three modeling levels that include (1) an all-atom explicit-water model studied with molecular dynamics (MD), and reduced models with implicit water containing (2) hard-sphere ions studied with the Local Equilibrium Monte Carlo simulation method (computing ionic correlations accurately), and (3) point ions studied with Poisson-Nernst-Planck (PNP) theory (mean-field approximation). We show that reduced models are able to reproduce device functions (rectification and selectivity) for a wide variety of charge patterns; that is, reduced models are useful in understanding the mesoscale physics of the device (i.e., how the current is produced). We also analyze the relationship of the reduced implicit-water models with the explicit-water model and show that diffusion coefficients in the reduced models can be used as adjustable parameters with which the results of the explicit- and implicit-water models can be related. We find that the values of the diffusion coefficients are sensitive to the net charge of the pore, but are relatively transferable to different voltages and charge patterns with the same total charge.