arXiv subjects

Zoltán Ható

Publications and source records attributed to Zoltán Ható.

5 recordsLinked to original sources

arXiv2026

Multiscale Modeling of Ion Transport in Nanopores: Fitting Implicit-Water Radial Diffusion Profiles to Explicit-Water Molecular Dynamics

We develop a multiscale approach for incorporating molecular-scale transport information into computationally efficient models of ion transport through nanopores. A radially varying effective diffusion coefficient profile is fitted to radial conductivity profiles obtained from explicit-water molecular dynamics (MD) simulations. The fitting is performed within the NP+LEMC framework, which combines the Nernst--Planck equation with Local Equilibrium Monte Carlo to account for ion correlations beyond mean-field approximation. We apply the approach to NaCl, CaCl$_2$, and their mixtures in a negatively charged silica nanopore. The resulting diffusion coefficient profiles reproduce the radial current distributions of the MD simulations, including the strong suppression of ionic mobility near the pore wall that cannot be captured by a spatially constant diffusion coefficient inside the pore. NaCl and CaCl$_2$ exhibit qualitatively different transport behavior: the former is cation selective due to enhanced near-wall Na$^+$ conduction, whereas the latter shows weak anion selectivity because strongly bound Ca$^{2+}$ ions have strongly suppressed mobility near the surface. For NaCl--CaCl$_2$ mixtures, preferential Ca$^{2+}$ binding leads to nonlinear changes in ionic conductance. The approach establishes a bridge between experimentally relevant device behavior and computationally efficient reduced models, with explicit-water MD providing the molecular-scale information that can be incorporated into the effective transport coefficients.

cond-mat.mes-hall↗

arXiv2026

Interplay of ion availability and mobility in the loss of cation selectivity for CaCl\textsubscript{2} in negatively charged nanopores: molecular dynamics using scaled-charge models

Ion transport through charged nanopores is commonly interpreted in terms of electrical double layer structure, leading to the expectation of cation-selective conduction in negatively charged pores. This picture can break down for multivalent electrolytes, where strong ion-urface correlations and charge inversion modify transport behavior. Here, we study NaCl and CaCl$_2$ conduction through negatively charged silica nanopores using atomistic molecular dynamics simulations with scaled-charge ion models. By separating concentration and velocity contributions to the radial particle current density, we connect static adsorption to dynamic perm-selectivity. While NaCl exhibits conventional cation selectivity, CaCl$_2$ shows nearly bulk-like or even anion-favored transport due to Ca$^{2+}$ immobilization near the surface and dominant Cl$^-$ conduction in the pore interior following charge inversion. Although this qualitative mechanism is robust, its detailed manifestation depends sensitively on the balance of ion-surface and ion-water interactions encoded in the force field.

cond-mat.stat-mech↗

arXiv2021

From nanotubes to nanoholes: scaling of selectivity in uniformly charged nanopores through the Dukhin number for 1:1 electrolytes

Scaling of the behavior of a nanodevice means that the device function (selectivity) is a unique smooth and monotonic function of a scaling parameter that is an appropriate combination of the system's parameters. For the uniformly charged cylindrical nanopore studied here these parameters are the electrolyte concentration, $c$, voltage, $U$, the radius and the length of the nanopore, $R$ and $H$, and the surface charge density on the nanopore's surface, $σ$. Due to the non-linear dependence of selectivites on these parameters, scaling can only be applied in certain limits. We show that the Dukhin number, $\mathrm{Du}=|σ|/eRc\sim |σ|λ_{\mathrm{D}}^{2}/eR$ ($λ_{\mathrm{D}}$ is the Debye length), is an appropriate scaling parameter in the nanotube limit ($H\rightarrow\infty$). Decreasing the length of the nanopore, namely, approaching the nanohole limit ($H\rightarrow 0$), an alternative scaling parameter has been obtained that contains the pore length and is called the modified Dukhin number: $\mathrm{mDu}\sim \mathrm{Du}\, H/λ_{\mathrm{D}}\sim |σ|λ_{\mathrm{D}}H/eR$. We found that the reason of non-linearity is that the double layers accumulating at the pore wall in the radial dimension correlate with the double layers accumulating at the entrances of the pore near the membrane on the two sides. Our modeling study using the Local Equilibrium Monte Carlo method and the Poisson-Nernst-Planck theory provides concentration, flux, and selectivity profiles, that show whether the surface or the volume conduction dominates in a given region of the nanopore for a given combination of the variables. We propose that the inflection point of the scaling curve may be used to characterize the transition point between the surface and volume conductions.

cond-mat.mes-hall↗

arXiv2019

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

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.

cond-mat.mes-hall↗

arXiv2017

Multiscale modeling of a rectifying bipolar nanopore: explicit-water versus implicit-water simulations

In a multiscale modeling approach, we present computer simulation results for a rectifying bipolar nanopore on two modeling levels. In an all-atom model, we use explicit water to simulate ion transport directly with the molecular dynamics technique. In a reduced model, we use implicit water and apply the Local Equilibrium Monte Carlo method together with the Nernst-Planck transport equation. This hybrid method makes the fast calculation of ion transport possible at the price of lost details. We show that the implicit-water model is an appropriate representation of the explicit-water model when we look at the system at the device (i.e., input vs.\ output) level. The two models produce qualitatively similar behavior of the electrical current for different voltages and model parameters. Looking at details of concentration and potential profiles, we find profound differences between the two models. These differences, however, do not influence the basic behavior of the model as a device because they do not influence the $z$-dependence of the concentration profiles which are the main determinants of current. These results then address an old paradox: how do reduced models, whose assumptions should break down in a nanoscale device, predict experimental data? Our simulations show that reduced models can still capture the overall device physics correctly, even though they get some important aspects of the molecular-scale physics quite wrong; reduced models work because they include the physics that is necessary from the point of view of device function. Therefore, reduced models can suffice for general device understanding and device design, but more detailed models might be needed for molecular level understanding.

cond-mat.mes-hall↗