Nanopores in Atomically Thin 2D Nanosheets Limit Aqueous Single-Stranded DNA Transport.

Nanopores in 2D materials are highly desirable for DNA sequencing, yet achieving single-stranded DNA (ssDNA) transport through them is challenging. Using density functional theory calculations and molecular dynamics simulations we show that ssDNA transport through a pore in monolayer hexagonal boron nitride (h-BN) is marked by a basic nanomechanical conflict. It arises from the notably inhomogeneous flexural rigidity of ssDNA and causes high friction via transient DNA desorption costs exacerbated by solvation effects. For a similarly sized pore in bilayer h-BN, its self-passivated atomically smooth edge enables continuous ssDNA transport. Our findings shed light on the fundamental physics of biopolymer transport through pores in 2D materials.

Communication: Relaxation-limited electronic currents in extended reservoir simulations.

Open-system approaches are gaining traction in the simulation of charge transport in nanoscale and molecular electronic devices. In particular, "extended reservoir" simulations, where explicit reservoir degrees of freedom are present, allow for the computation of both real-time and steady-state properties but require relaxation of the extended reservoirs. The strength of this relaxation, γ, influences the conductance, giving rise to a "turnover" behavior analogous to Kramers turnover in chemical reaction rates. We derive explicit, general expressions for the weak and strong relaxation limits. For weak relaxation, the conductance increases linearly with γ and every electronic state of the total explicit system contributes to the electronic current according to its "reduced" weight in the two extended reservoir regions. Essentially, this represents two conductors in series-one at each interface with the implicit reservoirs that provide the relaxation. For strong relaxation, a "dual" expression-one with the same functional form-results, except now proportional to 1/γ and dependent on the system of interest's electronic states, reflecting that the strong relaxation is localizing electrons in the extended reservoirs. Higher order behavior (e.g., γ2 or 1/γ2) can occur when there is a gap in the frequency spectrum. Moreover, inhomogeneity in the frequency spacing can give rise to a pseudo-plateau regime. These findings yield a physically motivated approach to diagnosing numerical simulations and understanding the influence of relaxation, and we examine their occurrence in both simple models and a realistic, fluctuating graphene nanoribbon.

Molecular dynamics simulation of thermal ripples in graphene with bond-order-informed harmonic constraints.

We describe the results of atomistic molecular dynamics simulations of thermal rippling in graphene with the use of a generic harmonic constraint model. The distance and angular constraint constants are calculated directly from the second-generation bond-order interatomic potential that describes carbon binding in graphene. We quantify the thermal rippling process in detail by calculating the overall rippling averages, the normal-normal correlation distributions and the height distributions. In addition, we consider the effect of a dihedral angular constraint, as well as the effect of sample size on the simulated rippling averages. The dynamic corrugation morphologies of simulated graphene samples obtained with the harmonic constraint model at various temperatures are, overall, consistent with those obtained with the bond-order potential and are in qualitative accord with previously reported findings. Given the wide availability of the harmonic constraint model in various molecular mechanics implementations, along with its high computational efficiency, our results indicate a possible use for the presented model in multicomponent dynamic simulations, including atomically thin layers.

Memristive Response and Capacitive Spiking in Aqueous Ion Transport through Two-Dimensional Nanopore Arrays.

In living organisms, information is processed in interconnected symphonies of ionic currents spiking through protein ion channels. As a result of dynamic switching of their conductive states, ion channels exhibit a variety of current-voltage nonlinearities and memory effects. Fueled by the promise of computing architectures entirely different from von Neumann, recent attempts to identify and harness similar phenomena in artificial nanofluidic environments focused on demonstrating analogue circuit elements with memory. Here we explore aqueous ionic transport through two-dimensional (2D) membranes featuring arrays of ion-trapping crown-ether-like pores. We demonstrate that for aqueous salts featuring ions with different ion-pore binding affinities, memristive effects emerge through coupling between the time-delayed state of the system and its transport properties. We also demonstrate a nanopore array that behaves as a capacitor with a strain-tunable built-in barrier, yielding behaviors ranging from current spiking to an ohmic response. By focusing on the illustrative underlying mechanisms, we demonstrate that realistically observable memory effects may be achieved in nanofluidic systems featuring crown-porous 2D membranes.

Adhesion-dependent negative friction coefficient on chemically modified graphite at the nanoscale.

From the early tribological studies of Leonardo da Vinci to Amontons' law, friction has been shown to increase with increasing normal load. This trend continues to hold at the nanoscale, where friction can vary nonlinearly with normal load. Here we present nanoscale friction force microscopy (FFM) experiments for a nanoscale probe tip sliding on a chemically modified graphite surface in an atomic force microscope (AFM). Our results demonstrate that, when adhesion between the AFM tip and surface is enhanced relative to the exfoliation energy of graphite, friction can increase as the load decreases under tip retraction. This leads to the emergence of an effectively negative coefficient of friction in the low-load regime. We show that the magnitude of this coefficient depends on the ratio of tip-sample adhesion to the exfoliation energy of graphite. Through both atomistic- and continuum-based simulations, we attribute this unusual phenomenon to a reversible partial delamination of the topmost atomic layers, which then mimic few- to single-layer graphene. Lifting of these layers with the AFM tip leads to greater deformability of the surface with decreasing applied load. This discovery suggests that the lamellar nature of graphite yields nanoscale tribological properties outside the predictive capacity of existing continuum mechanical models.

High-Throughput Nanopore Fabrication and Classification Using Xe-Ion Irradiation and Automated Pore-Edge Analysis.

Large-area nanopore drilling is a major bottleneck in state-of-the-art nanoporous 2D membrane fabrication protocols. In addition, high-quality structural and statistical descriptions of as-fabricated porous membranes are key to predicting the corresponding membrane-wide permeation properties. In this work, we investigate Xe-ion focused ion beam as a tool for scalable, large-area nanopore fabrication on atomically thin, free-standing molybdenum disulfide. The presented irradiation protocol enables designing ultrathin membranes with tunable porosity and pore dimensions, along with spatial uniformity across large-area substrates. Fabricated nanoporous membranes are then characterized using scanning transmission electron microscopy imaging, and the observed nanopore geometries are analyzed through a pore-edge detection and analysis script. We further demonstrate that the obtained structural and statistical data can be readily passed on to computational and analytical tools to predict the permeation properties at both individual pore and membrane-wide scales. As an example, membranes featuring angstrom-scale pores are investigated in terms of their emerging water and ion flow properties through extensive all-atom molecular dynamics simulations. We believe that the combination of experimental and analytical approaches presented here will yield accurate physics-based property estimates and thus potentially enable a true function-by-design approach to fabrication for applications such as osmotic power generation and desalination/filtration.

Field-Dependent Dehydration and Optimal Ionic Escape Paths for C2N Membranes.

Most analytic theories describing electrostatically driven ion transport through water-filled nanopores assume that the corresponding permeation barriers are bias-independent. While this assumption may hold for sufficiently wide pores under infinitely small bias, transport through subnanometer pores under finite bias is difficult to interpret analytically. Given recent advances in subnanometer pore fabrication and the rapid progress in detailed computer simulations, it is important to identify and understand the specific field-induced phenomena arising during ion transport. Here we consider an atomistic model of electrostatically driven ion permeation through subnanoporous C2N membranes. We analyze probability distributions of ionic escape trajectories and show that the optimal escape path switches between two different configurations depending on the bias magnitude. We identify two distinct mechanisms contributing to field-induced changes in transport-opposing barriers: a weak one arising from field-induced ion dehydration and a strong one due to the field-induced asymmetry of the hydration shells. The simulated current-voltage characteristics are compared with the solution of the 1D Nernst-Planck model. Finally, we show that the deviation of simulated currents from analytic estimates for large fields is consistent with the field-induced barriers and the observed changes in the optimal ion escape path.

Large Variations in the Composition of Ionic Liquid-Solvent Mixtures in Nanoscale Confinement.

Mixtures of an ionic liquid with an organic solvent are widely used as electrolytes in supercapacitors where they are often confined in porous electrodes with pore widths only slightly larger than the sizes of bare ions or solvent molecules. The composition of the electrolyte inside these pores, which may depend on the pore width and choice of electrolyte, can affect supercapacitor performance but remains poorly understood. Here, we perform all-atom molecular dynamics simulations of solutions of two different ionic liquids in acetonitrile under confinement between graphene sheets forming slit pores of various widths. We observe significant oscillations in the in-pore ionic liquid mole fraction with varying pore widths. Ions are excluded from very narrow pores, while for pore widths that tightly fit a single layer of ions, we observe an in-pore ionic liquid mole fraction over three times greater than that in the bulk. At slightly larger pore widths, we observe for different ionic liquids either a nearly complete exclusion of ions from the pore or a slight depletion of ions, while ion population again increases as pore width further increases. We develop an analytical model that can qualitatively predict the in-pore ionic liquid mole fraction based on the effective molar volumes and the pore wall interaction energies of each species. Our work suggests a new avenue for tuning the ionic liquid mole fraction in nanopores with potentially significant implications for designing systems involving nanoconfined liquid electrolytes such as supercapacitors where in-pore ion population can affect charging dynamics.

Aqueous Ion Trapping and Transport in Graphene-Embedded 18-Crown-6 Ether Pores.

Using extensive room-temperature molecular dynamics simulations, we investigate selective aqueous cation trapping and permeation in graphene-embedded 18-crown-6 ether pores. We show that in the presence of suspended water-immersed crown-porous graphene, K+ ions rapidly organize and trap stably within the pores, in contrast with Na+ ions. As a result, significant qualitative differences in permeation between ionic species arise. The trapped ion occupancy and permeation behaviors are shown to be highly voltage-tunable. Interestingly, we demonstrate the possibility of performing conceptually straightforward ion-based logical operations resulting from controllable membrane charging by the trapped ions. In addition, we show that ionic transistors based on crown-porous graphene are possible, suggesting utility in cascaded ion-based logic circuitry. Our results indicate that in addition to numerous possible applications of graphene-embedded crown ether nanopores, including deionization, ion sensing/sieving, and energy storage, simple ion-based logical elements may prove promising as building blocks for reliable nanofluidic computational devices.

Nucleobase-functionalized graphene nanoribbons for accurate high-speed DNA sequencing.

We propose a water-immersed nucleobase-functionalized suspended graphene nanoribbon as an intrinsically selective device for nucleotide detection. The proposed sensing method combines Watson-Crick selective base pairing with graphene's capacity for converting anisotropic lattice strain to changes in an electrical current at the nanoscale. Using detailed atomistic molecular dynamics (MD) simulations, we study sensor operation at ambient conditions. We combine simulated data with theoretical arguments to estimate the levels of measurable electrical signal variation in response to strains and determine that the proposed sensing mechanism shows significant promise for realistic DNA sensing devices without the need for advanced data processing, or highly restrictive operational conditions.

A MoS2-Based Capacitive Displacement Sensor for DNA Sequencing.

We propose an aqueous functionalized molybdenum disulfide nanoribbon suspended over a solid electrode as a capacitive displacement sensor aimed at determining the DNA sequence. The detectable sequencing events arise from the combination of Watson-Crick base-pairing, one of nature's most basic lock-and-key binding mechanisms, with the ability of appropriately sized atomically thin membranes to flex substantially in response to subnanonewton forces. We employ carefully designed numerical simulations and theoretical estimates to demonstrate excellent (79% to 86%) raw target detection accuracy at ∼70 million bases per second and electrical measurability of the detected events. In addition, we demonstrate reliable detection of repeated DNA motifs. Finally, we argue that the use of a nanoscale opening (nanopore) is not requisite for the operation of the proposed sensor and present a simplified sensor geometry without the nanopore as part of the sensing element. Our results, therefore, potentially suggest a realistic, inherently base-specific, high-throughput electronic DNA sequencing device as a cost-effective de novo alternative to the existing methods.