No Arabic abstract
Janus -- or two-sided, asymmetrical -- charged membranes offer promise as ionic current rectifiers. In such systems, pores consisting of two regions of opposite charge can be used to generate a current from a gradient in salinity. The efficiency of Janus pores increases dramatically as their diameter becomes smaller. However, little is known about the underlying transport processes, both for water and ions, in Janus nanopores. In this work, the molecular basis for rectification in Janus nanopores is examined both at rest and in the presence of an applied electric field. By relying on detailed equilibrium and far-from-equilibrium simulations, using explicit models of water and ions, we analyse the structure and dynamics of all molecular species in solution, as well as the overall response of these asymmetric nanopore devices subject to a positive or negative bias, respectively. While there is no precedent for atomistic simulations of a functioning Janus pore, the calculations are able to reproduce key macroscopic experimental observations of asymmetric membranes, serving to establish the validity of the models adopted here. As opposed to the most popularly implemented continuum approaches, here a detailed view is presented of the molecular structures and characteristics that give rise to ionic rectification in such systems, including the local re-orientation of water in the pores and the segregation of ionic species. New insights for the technological development of practical nanofluidic devices are also presented on the basis of these findings.
Recent studies of the hydration of micro- and nanoscale solutes have demonstrated a strong {it coupling} between hydrophobic, dispersion and electrostatic contributions, a fact not accounted for in current implicit solvent models. We present a theoretical formalism which accounts for coupling by minimizing the Gibbs free energy with respect to a solvent volume exclusion function. The solvent accessible surface is output of our theory. Our method is illustrated with the hydration of alkane-assembled solutes on different length scales, and captures the strong sensitivity to the particular form of the solute-solvent interactions in agreement with recent computer simulations.
Steric hindered frustrated Lewis pairs (FLPs) have been shown to activate hydrogen molecules, and their reactivity is strongly determined by the geometric parameters of the Lewis acid s and bases. A recent experimental study showed that ionic liquids (ILs) could largely improve the effective configuration of FLPs. However, the detailed mechanistic profile is still unclear. Herein, we performed a molecular dynamics (MD) simulations, aimi ng to reveal the effects of ILs on the structures of FLPs, and to present a rule for selecting more efficient reaction media. For this purpose, mixture systems were adopt consisting of the ILs [Cnmim][NTf2] (n= 6, 10, 14), and the typical FLP (tBu)3P/B(C6F5)3 . Radial distribution function (RDF) results show that toluene competes with (tBu)3P to interact with B(C6F5)3 , resulting in a relatively low effective (tBu)3P/B(C6F5)3 complex. [Cnmim][NTf2] is more intended to form a solvated shell surrounding the (tBu)3P/B(C6F5)3 , which increases the amount of effective FLPs. Spatial distribution function (SDF) results show that toluene formed a continuum solvation shell, which hinders the interactions of (tBu)3P and B(C6F5)3 , while [Cnmim][NTf2] leave a relatively large empty space, which is accessible by (tBu3)P molecules, resulting in a higher probability of Lewis acids and bases interactions. Lastly, we find that the longer alkyl chain length of[Cnmim] cations, the higher probability of effective FLPs.
Room Temperature Ionic Liquids (RTILs) have attracted much of the attention of the scientific community in the past decade due the their novel and highly customizable properties. Nonetheless their high viscosities pose serious limitations to the use of RTILs in practical applications. To elucidate some of the physical aspects behind transport properties of RTILs, extensive classical molecular dynamics (MD) calculations are reported. Bulk viscosities and ionic conductivities of butyl-methyl-imidazole based RTILs are presented over a wide range of temperatures. The dependence of the properties of the liquids on simulation parameters, e.g. system size effects and choice of the interaction potential, is analyzed.
Hydrogen bonds (HBs) play a crucial role in the physicochemical properties of ionic liquids (ILs). At present, HBs between cations and anions (Ca-An) or between cations (Ca-Ca) in ILs have been reported extensively. Here, we provided DFT evidences for the exists of HBs between anions (An-An) in the IL 1-(2-hydroxyethyl)-3-methylimidazolium 4-(2-hydroxyethyl)imidazolide [HEMIm][HEIm]. The thermodynamics stabilities of anionic, cationic, and H2O dimers together with ionic pairs were studied by potential energy scans. The results show that the cation-anion pair is the most stable one, while the HB in anionic dimer possesses similar thermodynamics stability to the water dimer. The further geometric, spectral and electronic structure analyses demonstrate that the inter-anionic HB meets the general theoretical criteria of traditional HBs. The strength order of four HBs in complexes is cation-anion pair > H2O dimer = cationic dimer > anionic dimer. The energy decomposition analysis indicates that induction and dispersion interactions are the crucial factors to overcome strong Coulomb repulsions, forming inter-anionic HBs. Lastly, the presence of inter-anionic HBs in ionic cluster has been confirmed by a global minimum search for a system containing two ionic pairs. Even though hydroxyl-functionalized cations are more likely to form HBs with anions, there still have inter-anionic HBs between hydroxyl groups in the low-lying structures. Our studies broaden the understanding of HBs in ionic liquids and support the recently proposed concept of anti-electrostatic HBs.
Implicit solvent models, such as Poisson-Boltzmann models, play important roles in computational studies of biomolecules. A vital step in almost all implicit solvent models is to determine the solvent-solute interface, and the solvent excluded surface (SES) is the most widely used interface definition in these models. However, classical algorithms used for computing SES are geometry-based, thus neither suitable for parallel implementations nor convenient for obtaining surface derivatives. To address the limitations, we explored a machine learning strategy to obtain a level-set formulation for the SES. The training process was conducted in three steps, eventually leading to a model with over 95% agreement with the classical SES. Visualization of tested molecular surfaces shows that the machine-learned SES overlaps with the classical SES on almost all situations. We also implemented the machine-learned SES into the Amber/PBSA program to study its performance on reaction field energy calculation. The analysis shows that the two sets of reaction field energies are highly consistent with 1% deviation on average. Given its level-set formulation, we expect the machine-learned SES to be applied in molecular simulations that require either surface derivatives or high efficiency on parallel computing platforms.