Lithium Ion Recognition with Nanofluidic Diodes through Host–Guest Complexation in Confined Geometries

Ali, Mubarak; Ahmed, Ishtiaq; Ramı́rez, Patricio; Nasir, Saima; Mafé, Salvador; Niemeyer, Christof M.; Ensinger, Wolfgang

doi:10.1021/acs.analchem.8b00902

Cited by 62 publications

(45 citation statements)

References 67 publications

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“…Surface charge is an essential feature of nanopores with which selectivity and conduction properties of the pore can be influenced [3,53,54,55,56,57]. Surface charge can be manipulated by chemical modifications [58,59,60,61,62], adding components that bind selectively to functional molecules (sensing) [63,60,38,39], or by applying voltage at embedded electrodes [64,7,65,29,8,9,66]. Different charge patterns allow different functions of the nanopore.…”

Section: Introductionmentioning

confidence: 99%

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

Valiskó

Matejczyk

Ható

et al. 2019

The Journal of Chemical Physics

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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. 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 -4/15

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Section: Introductionmentioning

confidence: 99%

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

Valiskó

Matejczyk

Ható

et al. 2019

The Journal of Chemical Physics

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“…The molecule that binds the targeted ion depends on the chemical specificity of that ion. For example, different active molecules are used for Li + [22], Cs + [23], Ca 2+ /Mg 2+ [24], K + [25,29], Na + [25], F − [30], or Zn 2+ [31]. Especially sensitive sensors can be fabricated by using the high specificity of enzymatic recognition mechanisms [32,33,34].…”

Section: Introductionmentioning

confidence: 99%

The effect of the charge pattern on the applicability of a nanopore as a sensor

Mádai

Valiskó

Boda

2019

Journal of Molecular Liquids

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We investigate a model nanopore sensor that is able to detect analyte ions that are present in the electrolyte solution in very small concentrations. The nanopore selectively binds the analyte ions with which the local concentrations of the ions of the background electrolyte (KCl), and, thus, the ionic current flowing through the pore is changed. Analyte concentration can be determined from calibration curves. In our previous study (Mádai et al. J. Chem. Phys., 147(24):244702, 2017.), we proposed a symmetric model (surface charge is negative all along the pore). The mechanism of sensing was a competition between K + and positive analyte ions, so increasing analyte concentration decreased K + current. Here we allow asymmetric charge patterns on the pore wall (positive/negative/neutral along the pore), thus, gaining an additional device function, rectification, resulting in a dual responsive device. We find that a bipolar nanopore is an efficient geometry with Cl − ions being the main charge carriers. The mechanism of sensing is that more positive analyte ions attract more Cl − ions into the pore thus increasing the current. Also they make the pore less asymmetric and, thus, decrease rectification. We use a hybrid computer simulation method, where a generalization of the grand canonical Monte Carlo method to non-equilibrium (Local Equilibrium Monte Carlo) is coupled to the Nernst-Planck equation with which the flux is computed.

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“…Modeling studies of pH-control require knowledge of the surface charge on the nanopore's wall. One strategy is using PNP to solve the reverse problem: on the basis of experimental current-voltage curves PNP provides estimates for the surface charges [45,52,53,54]. The other strategy, which we use here, is to relate pH to protonation/deprotonation degrees, and, thus, surface charges, through dissociation equilibrium [14,55].…”

Section: Introductionmentioning

confidence: 99%

Controlling ionic current through a nanopore by tuning pH: a local equilibrium Monte Carlo study

2019

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The purpose of this work is to create a model of a nanofluidic transistor which is able to mimic the effects of pH on nanopore conductance. The pH of the electrolyte is an experimentally controllable parameter through which the charge pattern can be tuned: pH affects the ratio of the protonated/deprotonated forms of the functional groups anchored to the surface of the nanopore (for example, amino and carboxyl groups). Thus, the behavior of the bipolar transistor changes as it becomes ion selective in acidic/basic environments. We relate the surface charge to pH and perform particle simulations (Local Equilibrium Monte Carlo) with different nanopore geometries (cylindrical and double conical). The simulations form a self consistent system with the Nernst-Planck equation with which we compute ionic flux. We discuss the mechanism behind pH-control of ionic current: formation of depletion zones.

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Lithium Ion Recognition with Nanofluidic Diodes through Host–Guest Complexation in Confined Geometries

Cited by 62 publications

References 67 publications

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

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

The effect of the charge pattern on the applicability of a nanopore as a sensor

Controlling ionic current through a nanopore by tuning pH: a local equilibrium Monte Carlo study

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