Existence of Multiple Phases of Water at Nanotube Interfaces

Water, because of its anomalous properties, can exhibit complex behavior under strong confinement. At room temperature and pressure, water is assumed to exist in a single phase as a liquid under confinement (e.g., in a carbon nanotube). In this study, using extensive molecular dynamics simulations, we show the existence of multiple phases of water when water meets a nanotube surface under atmospheric conditions (<i>T</i> = 300 K, <i>P</i> = 1 atm). Vapor, high-density ice, and liquid water phases coexist in the region within ∼1 nm from the surface. Structure factor, entropy, pressure, viscosity, and rotational diffusion of water layers near the surface reveal substantial phase anomalies induced by confinement. We show the presence of a new high-density solid-state ice layer (ρ = 3.9 g/cm³) with rhombic structure coexisting adjacent to vapor and liquid water. The existence of multiple phases of water near an interface can explain, for example, the slip phenomena, self-filling behavior of a carbon nanotube, and fast transport of water

Mechanistic Insights into Hydration of Solid Oxides

Some of the solid oxide materials, used in solid oxide fuel and electrolysis cells, are known to conduct protons once they are hydrated. However, the mechanisms by which solid oxide materials get hydrated is not clear. By performing detailed density functional theory calculations, we investigate hydration of two typical solid oxides with a single-crystal structurea proton-conducting yttrium-doped strontium zirconate (SZY) and an oxide ion-conducting yttria-stabilized zirconia (YSZ). We suggest a four-step process to understand the hydration of solid oxideswater adsorption on the surface, proton migration from the surface to bulk, proton migration in the bulk, and oxide ion vacancy migration in the bulk. The hydroxide ion migration with a lower energy barrier, compared to the proton hopping mechanism, is proposed for the conduction of proton between the surface and subsurface of the perovskite oxide. Our analysis provides mechanistic insights into the hydration of single-crystal SZY and nonhydration of single-crystal YSZ. The study presented here not only explains the hydration of materials but also provides the importance of structural rearrangement when a proton is incorporated into the bulk of the solid oxide material

DNA Base Detection Using a Single-Layer MoS₂

Nanopore-based DNA sequencing has led to fast and high-resolution recognition and detection of DNA bases. Solid-state and biological nanopores have low signal-to-noise ratio (SNR) (< 10) and are generally too thick (> 5 nm) to be able to read at single-base resolution. A nanopore in graphene, a 2-D material with sub-nanometer thickness, has a SNR of ∼3 under DNA ionic current. In this report, using atomistic and quantum simulations, we find that a single-layer MoS₂ is an extraordinary material (with a SNR > 15) for DNA sequencing by two competing technologies (<i>i.e.</i>, nanopore and nanochannel). A MoS₂ nanopore shows four distinct ionic current signals for single-nucleobase detection with low noise. In addition, a single-layer MoS₂ shows a characteristic change/response in the total density of states for each base. The band gap of MoS₂ is significantly changed compared to other nanomaterials (<i>e.g.</i>, graphene, h-BN, and silicon nanowire) when bases are placed on top of the pristine MoS₂ and armchair MoS₂ nanoribbon, thus making MoS₂ a promising material for base detection <i>via</i> transverse current tunneling measurement. MoS₂ nanopore benefits from a craftable pore architecture (combination of Mo and S atoms at the edge) which can be engineered to obtain the optimum sequencing signals

Antibody Subclass Detection Using Graphene Nanopores

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

Legislative Documents

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Quantitative Chemical Imaging of Nonplanar Microfluidics

Confocal and multiphoton optical imaging techniques have been powerful tools for evaluating the performance of and monitoring experiments within microfluidic devices, but this application suffers from two pitfalls. The first is that obtaining the necessary imaging contrast often requires the introduction of an optical label which can potentially change the behavior of the system. The emerging analytical technique stimulated Raman scattering (SRS) microscopy promises a solution, as it can rapidly measure 3D concentration maps based on vibrational spectra, label-free; however, when using any optical imaging technique, including SRS, there is an additional problem of optical aberration due to refractive index mismatch between the fluid and the device walls. New approaches such as 3D printing are extending the range of materials from which microfluidic devices can be fabricated; thus, the problem of aberration can be obviated simply by selecting a chip material that matches the refractive index of the desired fluid. To demonstrate complete chemical imaging of a geometrically complex device, we first use sacrificial molding of a freeform 3D printed template to create a round-channel, 3D helical micromixer in a low-refractive-index polymer. We then use SRS to image the mixing of aqueous glucose and salt solutions throughout the entire helix volume. This fabrication approach enables truly nonperturbative 3D chemical imaging with low aberration, and the concentration profiles measured within the device agree closely with numerical simulations

Solution-Synthesized Chevron Graphene Nanoribbons Exfoliated onto H:Si(100)

There has been tremendous progress in designing and synthesizing graphene nanoribbons (GNRs). The ability to control the width, edge structure, and dopant level with atomic precision has created a large class of accessible electronic landscapes for use in logic applications. One of the major limitations preventing the realization of GNR devices is the difficulty of transferring GNRs onto nonmetallic substrates. In this work, we developed a new approach for clean deposition of solution-synthesized atomically precise chevron GNRs onto H:Si(100) under ultrahigh vacuum. A clean transfer allowed ultrahigh-vacuum scanning tunneling microscopy (STM) to provide high-resolution imaging and spectroscopy and reveal details of the electronic structure of chevron nanoribbons that have not been previously reported. We also demonstrate STM nanomanipulation of GNRs, characterization of multilayer GNR cross-junctions, and STM nanolithography for local depassivation of H:Si(100), which allowed us to probe GNR–Si interactions and revealed a semiconducting-to-metallic transition. The results of STM measurements were shown to be in good agreement with first-principles computational modeling

X-ray scattering analysis of lipid films.

Reconfiguration of SLM films as a function of compression. A) 2D GIWAXS diffraction patterns of DPPC films before and after compression by 10%. The brackets denote a family of planes hkl. The inset are schematics of the changes in layer alignment corresponding with changes in correlation length ξ induced in the DPPC SLM by compression. B) Linear integration of the GIWAXS data. C) Schematic of GIWAXS peak shift and widening related to the effect of compression at the hydrocarbon chain length scale. D) Schematic of DPPC hexagonal phase from GIWAXS data which displays changes in lattice spacing a and increased disorder of lipid tails.</p

Effect of compression on lipid tilt.

A) Color coded representation of the simulated DPPC systems at three compressive strains. The color represents lipid orientation (tilt) angle with respect to z-axis. The box represents the simulation unit cell. B) The tilt angle distributions of the Lβ phase DPPC lipids. The inset shows the average order parameter values.</p

X-ray scattering data analysis.

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