Environmental damping and vibrational coupling of confined fluids within isolated carbon nanotubes.

Because of their large surface areas, nanotubes and nanowires demonstrate exquisite mechanical coupling to their surroundings, promising advanced sensors and nanomechanical devices. However, this environmental sensitivity has resulted in several ambiguous observations of vibrational coupling across various experiments. Herein, we demonstrate a temperature-dependent Radial Breathing Mode (RBM) frequency in free-standing, electron-diffraction-assigned Double-Walled Carbon Nanotubes (DWNTs) that shows an unexpected and thermally reversible frequency downshift of 10 to 15%, for systems isolated in vacuum. An analysis based on a harmonic oscillator model assigns the distinctive frequency cusp, produced over 93 scans of 3 distinct DWNTs, along with the hyperbolic trajectory, to a reversible increase in damping from graphitic ribbons on the exterior surface. Strain-dependent coupling from self-tensioned, suspended DWNTs maintains the ratio of spring-to-damping frequencies, producing a stable saturation of RBM in the low-tension limit. In contrast, when the interior of DWNTs is subjected to a water-filling process, the RBM thermal trajectory is altered to that of a Langmuir isobar and elliptical trajectories, allowing measurement of the enthalpy of confined fluid phase change. These mechanisms and quantitative theory provide new insights into the environmental coupling of nanomechanical systems and the implications for devices and nanofluidic conduits.

Tuning Interfacial Water Friction through Moiré Twist.

Foundations of nanofluidics can enable advances in diverse applications such as water desalination, energy harvesting, and biological analysis. Dynamically manipulating nanofluidic properties, such as diffusion and friction, is an area of great scientific interest. Twisted bilayer graphene, particularly at the magic angle, has garnered attention for its unconventional superconductivity and correlated insulator behavior due to strong electronic correlations. The impact of the electronic properties of moiré patterns in twisted bilayer graphene on structural and dynamic properties of water remains largely unexplored. Computational challenges, stemming from simulating large unit cells using density functional theory, have hindered progress. This study addresses this gap by investigating water behavior on twisted bilayer graphene, employing a deep neural network potential (DP) model trained with a data set from ab initio molecular dynamics simulations. It is found that as the twisted angle approaches the magic angle, interfacial water friction increases, leading to a reduced water diffusion. Notably, the analysis shows that at smaller twisted angles with larger moiré patterns, water is more likely to reside in AA stacking regions than AB (or BA) stacking regions, a distinction that diminishes with smaller moiré patterns. This study illustrates the potential for leveraging the distinctive properties of moiré systems to effectively control and optimize interfacial fluid behavior.

Tunable Magnetic Coupling in Graphene Nanoribbon Quantum Dots.

Carbon-based quantum dots (QDs) enable flexible manipulation of electronic behavior at the nanoscale, but controlling their magnetic properties requires atomically precise structural control. While magnetism is observed in organic molecules and graphene nanoribbons (GNRs), GNR precursors enabling bottom-up fabrication of QDs with various spin ground states have not yet been reported. Here the development of a new GNR precursor that results in magnetic QD structures embedded in semiconducting GNRs is reported. Inserting one such molecule into the GNR backbone and graphitizing it results in a QD region hosting one unpaired electron. QDs composed of two precursor molecules exhibit nonmagnetic, antiferromagnetic, or antiferromagnetic ground states, depending on the structural details that determine the coupling behavior of the spins originating from each molecule. The synthesis of these QDs and the emergence of localized states are demonstrated through high-resolution atomic force microscopy (HR-AFM), scanning tunneling microscopy (STM) imaging, and spectroscopy, and the relationship between QD atomic structure and magnetic properties is uncovered. GNR QDs provide a useful platform for controlling the spin-degree of freedom in carbon-based nanostructures.

Beyond the electrical double layer model: ion-dependent effects in nanoscale solvent organization.

The nanoscale organization of electrolyte solutions at interfaces is often described well by the electrical double-layer model. However, a recent study has shown that this model breaks down in solutions of LiClO4 in acetonitrile at a silica interface, because the interface imposes a strong structuring in the solvent that in turn determines the preferred locations of cations and anions. As a surprising consequence of this organisation, the effective surface potential changes from negative at low electrolyte concentration to positive at high electrolyte concentration. Here we combine previous ion-current measurements with vibrational sum-frequency-generation spectroscopy experiments and molecular dynamics simulations to explore how the localization of ions at the acetonitrile-silica interface depends on the sizes of the anions and cations. We observe a strong, synergistic effect of the cation and anion identities that can prompt a large difference in the ability of ions to partition to the silica surface, and thereby influence the effective surface potential. Our results have implications for a wide range of applications that involve electrolyte solutions in polar aprotic solvents at nanoscale interfaces.

Data-Driven Approach to Coarse-Graining Simple Liquids in Confinement.

We propose a data-driven framework for identifying coarse-grained (CG) Lennard-Jones (LJ) potential parameters in confined systems for simple liquids. Our approach involves the use of a Deep Neural Network (DNN) that is trained to approximate the solution of the Inverse Liquid State (ILST) problem for confined systems. The DNN model inherently incorporates essential physical characteristics specific to confined fluids, enabling an accurate prediction of inhomogeneity effects. By utilizing transfer learning, we predict single-site LJ potentials of simple multiatomic liquids confined in a slit-like channel, which effectively replicate both the fluid structure and molecular force of the target All-Atom (AA) system when the electrostatic interactions are not dominant. In addition, we showcase the synergy between the data-driven approach and the well-known Bottom-Up coarse-graining method utilizing Relative-Entropy (RE) Minimization. Through the sequential utilization of these two methods, the robustness of the iterative RE method is significantly augmented, leading to a remarkable enhancement in convergence.

Imaging the electron charge density in monolayer MoS2 at the Ångstrom scale.

Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spatial resolution. These electric field maps represent the integrated effect of the nucleus, core electrons and valence electrons, and separating their contributions is non-trivial. In this paper, we utilized simultaneously acquired 4D-STEM center of mass (CoM) images and annular dark field (ADF) images to determine the projected electron charge density in monolayer MoS2. We evaluate the contributions of both the core electrons and the valence electrons to the derived electron charge density; however, due to blurring by the probe shape, the valence electron contribution forms a nearly featureless background while most of the spatial modulation comes from the core electrons. Our findings highlight the importance of probe shape in interpreting charge densities derived from 4D-STEM and the need for smaller electron probes.

Mapping Nanoscale Electrostatic Field Fluctuations around Graphene Dislocation Cores Using Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM).

Defects in crystalline lattices cause modulation of the atomic density, and this leads to variations in the associated electrostatics at the nanoscale. Mapping these spatially varying charge fluctuations using transmission electron microscopy has typically been challenging due to complicated contrast transfer inherent to conventional phase contrast imaging. To overcome this, we used four-dimensional scanning transmission electron microscopy (4D-STEM) to measure electrostatic fields near point dislocations in a monolayer. The asymmetry of the atomic density in a (1,0) edge dislocation core in graphene yields a local enhancement of the electric field in part of the dislocation core. Through experiment and simulation, the increased electric field magnitude is shown to arise from "long-range" interactions from beyond the nearest atomic neighbor. These results provide insights into the use of 4D-STEM to quantify electrostatics in thin materials and map out the lateral potential variations that are important for molecular and atomic bonding through Coulombic interactions.

Ion transport in two-dimensional flexible nanoporous membranes.

Ion transport is a fundamental mechanism in living systems that plays a role in cell proliferation, energy conversion, and maintaining homeostasis. This has inspired various nanofluidic applications such as electricity harvesting, molecular sensors, and molecular separation. Two dimensional (2D) nanoporous membranes are particularly promising for these applications due to their ultralow transport barriers. We investigated ion conduction across flexible 2D membranes via extensive molecular dynamics simulations. We found that the microscopic fluctuations of these membranes can significantly increase ion conductance, for example, by 320% in Cu-HAB with 0.5 M KCl. Our analysis of ion dynamics near the flexible membranes revealed that ion hydration is destabilized when the membrane fluctuated within a specific frequency range leading to improved ion conduction. Our results show that the dynamic coupling between the fluctuating membrane and ions can play a crucial role in ion conduction across 2D nanoporous membranes.

Inducing Electric Current in Graphene Using Ionic Flow.

Classical nanofluidic frameworks account for the confined fluid and ion transport under an electrostatic field at the solid-liquid interface, but the electronic property of the solid is often overlooked. Harvesting the interaction of the nanofluidic transport with the electron transport in solid requires a route effectively coupling ion and electron dynamics. Here we report a nanofluidic analogy of Coulomb drag for exploring the dynamic ion-electron interactions at the liquid-graphene interface. An induced electric current in graphene by ionic flow with no bias directly applied to the graphene channel is observed experimentally, featuring an opposite electron current direction to the ion current. Our experiments and ab initio calculations show that the current generation stems from the confined ion-electron interactions via a nanofluidic Coulomb drag mechanism. Our findings may open up a new dimension for nanofluidics and transport control by ion-electron coupling.

Immunoglobulin adsorption and film formation on mechanically wrinkled and crumpled surfaces at submonolayer coverage.

Understanding protein adsorption behavior on rough and wrinkled surfaces is vital to applications including biosensors and flexible biomedical devices. Despite this, there is a dearth of study on protein interaction with regularly undulating surface topographies, particularly in regions of negative curvature. Here we report nanoscale adsorption behavior of immunoglobulin M (IgM) and immunoglobulin G (IgG) on wrinkled and crumpled surfaces via atomic force microscopy (AFM). Hydrophilic plasma treated poly(dimethylsiloxane) (PDMS) wrinkles with varying dimensions exhibit higher surface coverage of IgM on wrinkle peaks over valleys. Negative curvature in the valleys is determined to reduce protein surface coverage based both on an increase in geometric hindrance on concave surfaces, and reduced binding energy as calculated in coarse-grained molecular dynamics simulations. The smaller IgG molecule in contrast shows no observable effects on coverage from this degree of curvature. The same wrinkles with an overlayer of monolayer graphene show hydrophobic spreading and network formation, and inhomogeneous coverage across wrinkle peaks and valleys attributed to filament wetting and drying effects in the valleys. Additionally, adsorption onto uniaxial buckle delaminated graphene shows that when wrinkle features are on the length scale of the protein diameter, hydrophobic deformation and spreading do not occur and both IgM and IgG molecules retain their dimensions. These results demonstrate that undulating wrinkled surfaces characteristic of flexible substrates can have significant effects on protein surface distribution with potential implications for design of materials for biological applications.

Fluids and Electrolytes under Confinement in Single-Digit Nanopores.

Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Existing theories often fail to predict the exotic effects observed in the narrowest of such pores, called single-digit nanopores (SDNs), which have diameters or conduit widths of less than 10 nm, and have only recently become accessible for experimental measurements. What SDNs reveal has been surprising, including a rapidly increasing number of examples such as extraordinarily fast water transport, distorted fluid-phase boundaries, strong ion-correlation and quantum effects, and dielectric anomalies that are not observed in larger pores. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies at the water-energy nexus, from new membranes for precise separations and water purification to new gas permeable materials for water electrolyzers and energy-storage devices. SDNs also present unique opportunities to achieve ultrasensitive and selective chemical sensing at the single-ion and single-molecule limit. In this review article, we summarize the progress on nanofluidics of SDNs, with a focus on the confinement effects that arise in these extremely narrow nanopores. The recent development of precision model systems, transformative experimental tools, and multiscale theories that have played enabling roles in advancing this frontier are reviewed. We also identify new knowledge gaps in our understanding of nanofluidic transport and provide an outlook for the future challenges and opportunities at this rapidly advancing frontier.

Observation and Isochoric Thermodynamic Analysis of Partially Water-Filled 1.32 and 1.45 nm Diameter Carbon Nanotubes.

Recent measurements of fluids under extreme confinement, including water within narrow carbon nanotubes, exhibit marked deviations from continuum theoretical descriptions. In this work, we generate precise carbon nanotube replicates that are filled with water, closed from external mass transfer, and studied over a wide temperature range by Raman spectroscopy. We study segments that are empty, partially filled, and completely filled with condensed water from -80 to 120 °C. Partially filled, nanodroplet states contain submicron vapor-like and liquid-like domains and are analyzed using a Clausius-Clapeyron-type model, yielding heats of condensation of water inside closed 1.32 nm diameter carbon nanotubes (3.32 ± 0.10 kJ/mol and 3.72 ± 0.11 kJ/mol) and 1.45 nm diameter carbon nanotubes (3.50 ± 0.07 kJ/mol) that are lower than the bulk enthalpy of vaporization and closer to the bulk enthalpy of fusion. Favored partial filling fractions are calculated, highlighting the effect of subnanometer changes in confining diameter on fluid properties and suggesting the promise of molecular engineering of nanoconfined liquid/vapor interfaces for water treatment or membrane distillation.

Multiscale compression-induced restructuring of stacked lipid bilayers: From buckling delamination to molecular packing.

Lipid membranes in nature adapt and reconfigure to changes in composition, temperature, humidity, and mechanics. For instance, the oscillating mechanical forces on lung cells and alveoli influence membrane synthesis and structure during breathing. However, despite advances in the understanding of lipid membrane phase behavior and mechanics of tissue, there is a critical knowledge gap regarding the response of lipid membranes to micromechanical forces. Most studies of lipid membrane mechanics use supported lipid bilayer systems missing the structural complexity of pulmonary lipids in alveolar membranes comprising multi-bilayer interconnected stacks. Here, we elucidate the collective response of the major component of pulmonary lipids to strain in the form of multi-bilayer stacks supported on flexible elastomer substrates. We utilize X-ray diffraction, scanning probe microscopy, confocal microscopy, and molecular dynamics simulation to show that lipid multilayered films both in gel and fluid states evolve structurally and mechanically in response to compression at multiple length scales. Specifically, compression leads to increased disorder of lipid alkyl chains comparable to the effect of cholesterol on gel phases as a direct result of the formation of nanoscale undulations in the lipid multilayers, also inducing buckling delamination and enhancing multi-bilayer alignment. We propose this cooperative short- and long-range reconfiguration of lipid multilayered films under compression constitutes a mechanism to accommodate stress and substrate topography. Our work raises fundamental insights regarding the adaptability of complex lipid membranes to mechanical stimuli. This is critical to several technologies requiring mechanically reconfigurable surfaces such as the development of electronic devices interfacing biological materials.

Real-Space Charge Density Profiling of Electrode-Electrolyte Interfaces with Angstrom Depth Resolution.

The accumulation and depletion of charges at electrode-electrolyte interfaces is crucial for all types of electrochemical processes. However, the spatial profile of such interfacial charges remains largely elusive. Here we develop charge profiling three-dimensional (3D) atomic force microscopy (CP-3D-AFM) to experimentally quantify the real-space charge distribution of the electrode surface and electric double layers (EDLs) with angstrom depth resolution. We first measure the 3D force maps at different electrode potentials using our recently developed electrochemical 3D-AFM. Through statistical analysis, peak deconvolution, and electrostatic calculations, we derive the depth profile of the local charge density. We perform such charge profiling for two types of emergent electrolytes, ionic liquids, and highly concentrated aqueous solutions, observe pronounced sub-nanometer charge variations, and find the integrated charge densities to agree with those derived from macroscopic electrochemical measurements.

Innermost Ion Association Configuration Is a Key Structural Descriptor of Ionic Liquids at Electrified Interfaces.

The structure of electric double layers (EDLs) is crucial for all types of electrochemical processes. While in dilute solutions EDL structure can be approximately treated within the Gouy-Chapman-Stern regime, in highly ionic electrolytes the description of EDL has been largely elusive. Here we study the EDL structure of an ionic liquid on a series of crystalline electrodes. Through molecular dynamics (MD) simulations, we observe strong intermolecular interaction among cations and anions and propose that the cation-anion association structure at the innermost layer is a key descriptor of the EDL. Using our recently developed electrochemical 3D atomic force microscopy (EC-3D-AFM) technique, we confirm the theoretical prediction and further find that the width of the first EDL is an experimental gauge of the ion association structure in that layer. We expect such ion association descriptors to be broadly applicable to a large range of highly ionic electrolytes on various electrode surfaces.

A culture-free biphasic approach for sensitive and rapid detection of pathogens in dried whole-blood matrix.

Blood stream infections (BSIs) cause high mortality, and their rapid detection remains a significant diagnostic challenge. Timely and informed administration of antibiotics can significantly improve patient outcomes. However, blood culture, which takes up to 5 d for a negative result, followed by PCR remains the gold standard in diagnosing BSI. Here, we introduce a new approach to blood-based diagnostics where large blood volumes can be rapidly dried, resulting in inactivation of the inhibitory components in blood. Further thermal treatments then generate a physical microscale and nanoscale fluidic network inside the dried matrix to allow access to target nucleic acid. The amplification enzymes and primers initiate the reaction within the dried blood matrix through these networks, precluding any need for conventional nucleic acid purification. High heme background is confined to the solid phase, while amplicons are enriched in the clear supernatant (liquid phase), giving fluorescence change comparable to purified DNA reactions. We demonstrate single-molecule sensitivity using a loop-mediated isothermal amplification reaction in our platform and detect a broad spectrum of pathogens, including gram-positive methicillin-resistant and methicillin-susceptible Staphylococcus aureus bacteria, gram-negative Escherichia coli bacteria, and Candida albicans (fungus) from whole blood with a limit of detection (LOD) of 1.2 colony-forming units (CFU)/mL from 0.8 to 1 mL of starting blood volume. We validated our assay using 63 clinical samples (100% sensitivity and specificity) and significantly reduced sample-to-result time from over 20 h to <2.5 h. The reduction in instrumentation complexity and costs compared to blood culture and alternate molecular diagnostic platforms can have broad applications in healthcare systems in developed world and resource-limited settings.

Modified Lucas-Washburn theory for fluid filling in nanotubes.

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.

Machine Learning Assisted Screening of Two-Dimensional Materials for Water Desalination.

There exists a vast expanse of data in the literature which can be harnessed for accelerated design and discovery of advanced materials for various applications of importance ─ for example, desalination of seawater. Here, we develop a machine learning (ML) model, training it with ∼260 molecular dynamics (MD) computation results, to predict the desalination performance of 2D membranes that exist in the literature. The desalination performance variables of water flux and salt rejection rates are correlated to 49 material features related to the chemistry of the pores and the membranes along with applied pressure, salt concentration, partial charges on the atoms, geometry of the pore, the mechanical properties of the membranes, and the properties of water for the water model used. We used the ML model to screen 3814 structurally optimized 2D materials for maximum water flux and salt rejection rates from the literature. We found some candidates that perform ∼4 times better than the more popularly known 2D materials such as graphene and MoS2. This result is verified using data obtained from MD simulations performed on several representative 2D membranes for different classes. Such validated statistical frameworks using literature data can be very useful in guiding experiments in the field of functional materials for varied applications.

Nonlinear electrohydrodynamic ion transport in graphene nanopores.

Mechanosensitivity is one of the essential functionalities of biological ion channels. Synthesizing an artificial nanofluidic system to mimic such sensations will not only improve our understanding of these fluidic systems but also inspire applications. In contrast to the electrohydrodynamic ion transport in long nanoslits and nanotubes, coupling hydrodynamical and ion transport at the single-atom thickness remains challenging. Here, we report the pressure-modulated ion conduction in graphene nanopores featuring nonlinear electrohydrodynamic coupling. Increase of ionic conductance, ranging from a few percent to 204.5% induced by the pressure­an effect that was not predicted by the classical linear coupling of molecular streaming to voltage-driven ion transport­was observed experimentally. Computational and theoretical studies reveal that the pressure sensitivity of graphene nanopores arises from the transport of capacitively accumulated ions near the graphene surface. Our findings may help understand the electrohydrodynamic ion transport in nanopores and offer a new ion transport controlling methodology.