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Despite decades of dominance in separation technology, progress in the design and development of high-performance polymer-based membranes has been incremental. Recent advances in materials science and chemical synthesis provide opportunities for molecular-level design of next-generation membrane materials. Such designs necessitate a fundamental understanding of transport and separation mechanisms at the molecular scale. Molecular simulations are important tools that could lead to the development of fundamental structure-property-performance relationships for advancing membrane design. In this Perspective, we assess the application and capability of molecular simulations to understand the mechanisms of ion and water transport across polymeric membranes. Additionally, we discuss the reliability of molecular models in mimicking the structure and chemistry of nanochannels and transport pathways in polymeric membranes. We conclude by providing research directions for resolving key knowledge gaps related to transport phenomena in polymeric membranes and for the construction of structure-property-performance relationships for the design of next-generation membranes.

We performed nonequilibrium molecular dynamics (NEMD) simulations and solvent permeation experiments to unravel the mechanism of water transport in reverse osmosis (RO) membranes. The NEMD simulations reveal that water transport is driven by a pressure gradient within the membranes, not by a water concentration gradient, in marked contrast to the classic solution-diffusion model. We further show that water molecules travel as clusters through a network of pores that are transiently connected. Permeation experiments with water and organic solvents using polyamide and cellulose triacetate RO membranes showed that solvent permeance depends on the membrane pore size, kinetic diameter of solvent molecules, and solvent viscosity. This observation is not consistent with the solution-diffusion model, where permeance depends on the solvent solubility. Motivated by these observations, we demonstrate that the solution-friction model, in which transport is driven by a pressure gradient, can describe water and solvent transport in RO membranes.

Synthesizing nanopores which mimic the functionality of ion-selective biological channels has been a challenging yet promising approach to advance technologies for precise ion-ion separations. Inspired by the facilitated fluoride (F-) permeation in the biological fluoride channel, we designed a highly fluoride-selective TiO2 film using the atomic layer deposition (ALD) technique. The subnanometer voids within the fabricated TiO2 film (4 A < d < 12 A, with two distinct peaks at 5.5 and 6.5 A), created by the hindered diffusion of ALD precursors (d = 7 A), resulted in more than eight times faster permeation of sodium fluoride compared to other sodium halides. We show that the specific Ti-F interactions compensate for the energy penalty of F- dehydration during the partitioning of F- ions into the pore and allow for an intrapore accumulation of F- ions. Concomitantly, the accumulation of F- ions on the pore walls also enhances the transport of sodium (Na+) cations due to electrostatic interactions. Molecular dynamics simulations probing the ion concentration and mobility within the TiO2 pore further support our proposed mechanisms for the selective F- transport and enhanced Na+ permeation in the TiO2 film. Overall, our work provides insights toward the design of ion-selective nanopores using the ALD technique.

Ultrafast water transport in carbon nanotubes (CNTs) has drawn a great deal of attention in a number of applications, such as water desalination, power generation, and biomolecule detection. With the recent experimental advances in water filling of isolated CNTs, the Lucas-Washburn theory for capillary rise in tubes needs to be revisited for a better understanding of the physics and dynamics of water filling in CNTs. Here, the Lucas-Washburn theory is corrected for the hydrodynamic entrance effects as well as the variation of capillary pressure and hydrodynamic properties with the radius and length of CNTs. Due to the large slippage in CNTs, inclusion of the entrance effects is important particularly for the initial stages of filling where a L∝t scaling, as opposed to L^{2}∝t, is observed in our molecular dynamics (MD) simulations. The corrected Lucas-Washburn theory is shown to predict the water filling dynamics in CNTs as observed in MD simulations. With the corrected theory, we achieve a better understanding of capillary rise and water filling dynamics in CNTs.

The properties of water interfacing with functionalized 2D materials play a crucial role in the design and development of high-performance nanofluidic devices. Developing nonbonding force field par...

State-of-the-art polymeric membranes are unable to perform the high-precision ion separations needed for technologies essential to a circular economy and clean energy future. Coordinative interactions are a mechanism to increase sorption of a target species into a membrane, but the effects of these interactions on membrane permeability and selectivity are poorly understood. We use a multilayered polymer membrane to assess how ion-membrane binding energies affect membrane permeability of similarly sized cations: Cu 2+ , Ni 2+ , Zn 2+ , Co 2+ , and Mg 2+ . We report that metals with higher binding energy to iminodiacetate groups of the polymer more selectively permeate through the membrane in multisalt solutions than single-salt solutions. In contrast, weaker binding species are precluded from diffusing into the polymer membrane, which leads to passage proportional to binding energy and independent of membrane thickness. Our findings demonstrate that selectivity of polymeric membranes can markedly increase by tailoring ion-membrane binding energy and minimizing membrane thickness.

Synthesizing nanopores which mimic the functionality of ion-selective biological channels has been a challenging yet promising approach to advance technologies for precise ion-ion separations. Inspired by the facilitated fluoride (F

The electrical double layer (EDL), consisting of two parallel layers of opposite charges, is foundational to many interfacial phenomena and unique in atomically thin materials. An important but unanswered question is how the "transparency" of atomically thin materials to their substrates influences the formation of the EDL. Here, we report that the EDL of graphene is directly affected by the surface energy of the underlying substrates. Cyclic voltammetry and electrochemical impedance spectroscopy measurements demonstrate that graphene on hydrophobic substrates exhibits an anomalously low EDL capacitance, much lower than what was previously measured for highly oriented pyrolytic graphite, suggesting disturbance of the EDL ("disordered EDL") formation due to the substrate-induced hydrophobicity to graphene. Similarly, electrostatic gating using EDL of graphene field-effect transistors shows much lower transconductance levels or even no gating for graphene on hydrophobic substrates, further supporting our hypothesis. Molecular dynamics simulations show that the EDL structure of graphene on a hydrophobic substrate is disordered, caused by the disruption of water dipole assemblies. Our study advances understanding of EDL in atomically thin limit.

Diffusion cannot be a major water transport mechanism in osmotic membranes because of the lack of true water concentration gradient within the membrane. Due to the semipermeable property of osmotic membranes, water concentration in the membrane is virtually constant because of the absence of salts. The recently confirmed porous structure of the skin layer of osmotic membranes cannot support the basis to exclude bulk water flow in the membrane as assumed in the classic solution-diffusion model. Herein we demonstrate that the concentration difference of water at the membrane-solution interface manifests itself as a negative hydraulic pressure in the membrane. Hence, the only possible driving force for water movement in osmotic membranes is hydraulic pressure gradient. Osmotically driven membrane processes are characterized with negative pressure within the membrane below the water vapor pressure, inevitably leading to the formation of vapor or small bubbles within the membrane matrix. This phenomenon is expected to markedly reduce the effectiveness of osmotic pressure as a driving force for water transport. Delineation of the breakdown and possible restoration of water continuity under negative pressure is essential for proper understanding of the principles governing water transport in osmotic membranes.

Solid-state nanopores are promising for label-free protein detection. The large thickness, ranging from several tens of nanometers to micrometers and larger, of solid-state nanopores prohibits atomic-scale scanning or interrogation of proteins. Here, a single-atom thick graphene nanopore is shown to be highly capable of sensing and discriminating between different subclasses of IgG antibodies despite their minor and subtle variation in atomic structure. Extensive molecular dynamics (MD) simulations, rigorous statistical analysis with a total aggregate simulation time of 2.7 μs, supervised machine learning (ML), and classification techniques are employed to distinguish IgG2 from IgG3. The water flux and ionic current during IgG translocation reveal distinct clusters for IgG subclasses facilitating an additional recognition mechanism. In addition, the histogram of ionic current for each segment of IgG can provide high-resolution spatial detection. Our results show that nanoporous graphene can be used to detect and distinguish antibody subclasses with good accuracy.

High performance water transport in nanopores has drawn a great deal of attention in a variety of applications, such as water desalination, power generation, and biosensing. High water transport enhancement factors in carbon-based nanopores have been reported over the classical Hagen-Poiseuille (HP) equation which does not account for the physics of transport at molecular scale. Instead, comparing the experimentally measured transport rates to that of a theory, that accounts for the microscopic physics of transport, would result in enhancement factors approaching unity. Such a theory is currently missing. Here, molecular corrections are introduced into the HP equation by considering the variation of key hydrodynamical properties (viscosity and friction) with thickness and diameter of pores in ultrathin graphene and finite-length carbon nanotubes (CNTs) using Green-Kubo relations and molecular dynamics (MD) simulations. The corrected HP (CHP) theory successfully predicts the permeation rates from nonequilibrium MD pressure driven flows. The previously reported enhancement factors over no-slip HP (of the order of 1000) approach unity when the permeations are normalized by the CHP flow rates. The results of our study will help better understand nanoscale flows in carbon-based pores and tubes.

The unique properties of aqueous electrolytes in ultrathin nanopores have drawn a great deal of attention in a variety of applications, such as power generation, water desalination, and disease diagnosis. Inside the nanopore, at the interface, properties of ions differ from those predicted by the classical ionic layering models (e.g., Gouy-Chapman electric double layer) when the thickness of the nanopore approaches the size of a single atom (e.g., nanopores in a single-layer graphene membrane). Here, using extensive molecular dynamics simulations, the structure and dynamics of aqueous ions inside nanopores are studied for different thicknesses, diameters, and surface charge densities of carbon-based nanopores [ultrathin graphene and finite-thickness carbon nanotubes (CNTs)]. The ion concentration and diffusion coefficient in ultrathin nanopores show no indication of the formation of a Stern layer (an immobile counter-ionic layer) as the counter-ions and nanopore atoms are weakly correlated in time compared to the strong correlation observed in thick nanopores. The weak correlation observed in ultrathin nanopores is indicative of a weak adsorption of counter-ions onto the surface compared to that of thick pores. The vanishing counter-ion adsorption (ion-wall correlation) in ultrathin nanopores leads to several orders of magnitude shorter ionic residence times (picoseconds) compared to the residence times in thick CNTs (seconds). The results of this study will help better understand the structure and dynamics of aqueous ions in ultrathin nanopores.

Protein detection plays a key role in determining the single point mutations which can cause a variety of diseases. Nanopore sequencing provides a label-free, single base, fast and long reading platform, which makes it amenable for personalized medicine. A challenge facing nanopore technology is the noise in ionic current. Here, we show that a nanoporous single-layer molybdenum disulfide (MoS2) can detect individual amino acids in a polypeptide chain (16 units) with a high accuracy and distinguishability. Using extensive molecular dynamics simulations (with a total aggregate simulation time of 66 µs) and machine learning techniques, we featurize and cluster the ionic current and residence time of the 20 amino acids and identify the fingerprints of the signals. Using logistic regression, nearest neighbor, and random forest classifiers, the sensor reading is predicted with an accuracy of 72.45, 94.55, and 99.6%, respectively. In addition, using advanced ML classification techniques, we are able to theoretically predict over 2.8 million hypothetical sensor readings’ amino acid types. Molecular dynamics simulations combined with machine learning techniques enable the prediction of MoS2 nanopore sequencing capabilities. A team led by N. R. Aluru at the University of Illinois at Urbana-Champaign used logistic regression, nearest neighbor, and random forest classifiers to develop a machine learning-based platform capable of predicting the sensing capabilities of nanoporous, atomically thin MoS2. The material was shown to be able to identify individual amino acids in polypeptide chains with high accuracy and distinguishability. Twenty amino acids could be detected and categorized in different classes based on current-residence time training data, with an accuracy of up to 99.6%. These results show promise for the development of amino acid detection platforms with atomically thin materials assisted by machine learning.

Making use of the osmotic pressure difference between fresh water and seawater is an attractive, renewable and clean way to generate power and is known as 'blue energy'(1-3). Another electrokinetic phenomenon, called the streaming potential, occurs when an electrolyte is driven through narrow pores either by a pressure gradient(4) or by an osmotic potential resulting from a salt concentration gradient(5). For this task, membranes made of two-dimensional materials are expected to be the most efficient, because water transport through a membrane scales inversely with membrane thickness(5-7). Here we demonstrate the use of single-layer molybdenum disulfide (MoS2) nanopores as osmotic nanopower generators. We observe a large, osmotically induced current produced from a salt gradient with an estimated power density of up to 10(6) watts per square metre-a current that can be attributed mainly to the atomically thin membrane of MoS2. Low power requirements for nanoelectronic and optoelectric devices can be provided by a neighbouring nanogenerator that harvests energy from the local environment(8-11)-for example, a piezoelectric zinc oxide nanowire array(8) or single-layer MoS2 (ref. 12). We use our MoS2 nanopore generator to power a MoS2 transistor, thus demonstrating a self-powered nanosystem.

The droplet interface bilayer (DIB)--a method to assemble planar lipid bilayer membranes between lipid-coated aqueous droplets--has gained popularity among researchers in many fields. Well-packed lipid monolayer on aqueous droplet-oil interfaces is a prerequisite for successfully assembling DIBs. Such monolayers can be achieved by two different techniques: "lipid-in", in which phospholipids in the form of liposomes are placed in water, and "lipid-out", in which phospholipids are placed in oil as inverse micelles. While both approaches are capable of monolayer assembly needed for bilayer formation, droplet pairs assembled with these two techniques require significantly different incubation periods and exhibit different success rates for bilayer formation. In this study, we combine experimental interfacial tension measurements with molecular dynamics simulations of phospholipids (DPhPC and DOPC) assembled from water and oil origins to understand the differences in kinetics of monolayer formation. With the results from simulations and by using a simplified model to analyze dynamic interfacial tensions, we conclude that, at high lipid concentrations common to DIBs, monolayer formation is simple adsorption controlled for lipid-in technique, whereas it is predominantly adsorption-barrier controlled for the lipid-out technique due to the interaction of interface-bound lipids with lipid structures in the subsurface. The adsorption barrier established in lipid-out technique leads to a prolonged incubation time and lower bilayer formation success rate, proving a good correlation between interfacial tension measurements and bilayer formation. We also clarify that advective flow expedites monolayer formation and improves bilayer formation success rate by disrupting lipid structures, rather than enhancing diffusion, in the subsurface and at the interface for lipid-out technique. Additionally, electrical properties of DIBs formed with varying lipid placement and type are characterized.

Spatially nonuniform strain is important for engineering the pseudomagnetic field and band structure of graphene. Despite the wide interest in strain engineering, there is still a lack of control on device-compatible strain patterns due to the limited understanding of the structure-strain relationship. Here, we study the effect of substrate corrugation and curvature on the strain profiles of graphene via combined experimental and theoretical studies of a model system: graphene on closely packed SiO2 nanospheres with different diameters (20-200 nm). Experimentally, via quantitative Raman analysis, we observe partial adhesion and wrinkle features and find that smaller nanospheres induce larger tensile strain in graphene, theoretically, molecular dynamics simulations confirm the same microscopic structure and size dependence of strain and reveal that a larger strain is caused by a stronger, inhomogeneous interaction force between smaller nanospheres and graphene. This molecular-level understanding of the strain mechanism is important for strain engineering of graphene and other two-dimensional materials., Comment: Nano Letters (2018)

Understanding the interaction between water and molybdenum disulfide (MoS2) is of crucial importance to investigate the physics of various applications involving MoS2 and water interfaces. An accurate force field is required to describe water and MoS2 interactions. In this work, water–MoS2 force field parameters are derived using the high-accuracy random phase approximation (RPA) method and validated by comparing to experiments. The parameters obtained from the RPA method result in water–MoS2 interface properties (solid-liquid work of adhesion) in good comparison to the experimental measurements. An accurate description of MoS2-water interaction will facilitate the study of MoS2 in applications such as DNA sequencing, sea water desalination, and power generation.

A fully controllable nano-electro-mechanical device that can pump fluids at nanoscale is proposed. Using molecular dynamics simulations, we show that an applied electric field to an ion@C60 inside a water-filled carbon nanotube can pump water with excellent efficiency. The key physical mechanism governing the fluid pumping is the conversion of electrical energy into hydrodynamic flow with efficiencies as high as 64%. Our results show that water can be compressed up to 7% higher than its bulk value by applying electric fields. High flux of water (up to 13,000 molecules/ns) is obtained by the electro-mechanical, piston-cylinder-like moving mechanism of the ion@C60 in the CNT. This large flux results from the piston-like mechanism, compressibility of water (increase in density of water due to molecular ordering), orienting dipole along the electric field and efficient electrical to mechanical energy conversion. Our findings can pave the way towards efficient energy conversion, pumping of fluids at nanoscale, and drug delivery.

Biological nanopores have been extensively used for DNA base detection since these pores are widely available and tunable through mutations. Distinguishing bases of nucleic acids by passing them through nanopores has so far primarily relied on electrical signals-specifically, ionic currents through the nanopores. However, the low signal-to-noise ratio makes detection of ionic currents difficult. In this study, we show that the initially closed mechanosensitive channel of large conductance (MscL) protein pore opens for single-stranded DNA (ssDNA) translocation under an applied electric field. As each nucleotide translocates through the pore, a unique mechanical signal is observed-specifically, the tension in the membrane containing the MscL pore is different for each nucleotide. In addition to the membrane tension, we found that the ionic current is also different for the four nucleotide types. The initially closed MscL adapts its opening for nucleotide translocation due to the flexibility of the pore. This unique operation of MscL provides single nucleotide resolution in both electrical and mechanical signals. Finally, we also show that the speed of DNA translocation is roughly 1 order of magnitude slower in MscL compared to Mycobacterium smegmatis porin A (MspA), suggesting MscL to be an attractive protein pore for DNA sequencing.