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The nanoscale effects of solid–fluid molecular interactions on the nanoconfined fluid flow have received increasing attention in science and engineering. Additionally, due to the complex microstructures of porous media, the nanoconfined fluid flow behaviors will be more complicated. In this paper, we comprehensively use theoretical analysis and lattice Boltzmann simulations with a new slip curved boundary condition to study the microstructures and molecular interaction effects on nanoconfined water flow. The viscous dissipation rate caused by the entrance effect (streamlines bending), and the nanoscale effects of the slip boundary and the varying interfacial water viscosity caused by molecular interactions are considered and discussed. The results show that the entrance viscous dissipation rate can result in the negative effects near the pore entrance and exit because of the bending streamlines. The increasing entrance viscous dissipation rate can make the enhancement factor approach to 1 by weakening the nanoscale effects. With an increasing contact angle, the entrance viscous dissipation rate causes the main pressure drop and gradually dominates the overall water flow. As nanoscale effects enhance the water flow capacity, the enhancement factor decreases to near 1 with an increasing porous media size because of the decreasing nanoscale effects. As nanoscale effects weaken the water flow capacity, due to the different decreasing effects of the slip length and interfacial water viscosity, the enhancement factor decreases first and then increases to near 1. Our work can guide for studying the oil/water flow in unconventional reservoirs and provide microscopic basics to design artificial nanopores with excellent performance.

The electrification of ice has been a subject of research since 1940, mostly in the context of charge generation in thunderstorms. This generation of electric charge is spontaneous, distinct from applying an external electric field to affect the diffusive growth of ice crystals. Here, we exploit the spontaneous electrification of ice to reveal a surprising phenomenon of jumping frost dendrites. We use side-view high-speed imaging to experimentally observe frost dendrites breaking off from mother dendrites and/or the substrate to jump out-of-plane toward an opposing polar liquid. Analytical and numerical models are then developed to estimate the attractive force between the frost dendrites and liquid, in good agreement with the experimental results. These models estimate the extent of charge separation within a growing sheet of frost, which is caused by mismatches in the mobilities of the charge carriers in ice. Our findings show that the unexpected jumping frost event can serve as a model system for resolving long-standing questions in atmospheric physics regarding charge separation in ice, while also having potential as a deicing construct.

Magnetic particles confined in microchannels can be actuated to perform translation motion using a rotating magnetic field, but their actuation in such a situation is not yet well understood. Here, the actuation of a ferromagnetic particle confined in square microchannels is studied using immersed-boundary lattice Boltzmann simulations. In wide channels, when a sphere is positioned close to a side wall but away from channel corners, it experiences a modest hydrodynamic actuation force parallel to the channel walls. This force decreases as the sphere is shifted toward the bottom wall but the opposite trend is found when the channel is narrow. When the sphere is positioned midway between the top and bottom channel walls, the actuation force decreases as the channel width decreases and can reverse its direction. These phenomena are elucidated by studying the flow and pressure fields in the channel-particle system and by analyzing the viscous and pressure components of the hydrodynamic force acting on different parts of the sphere.

Thermoelectric effects of ice play an important role in many natural and engineering phenomena. We investigate, numerically and analytically, the electrification of finite-thickness ice slabs due to an imposed temperature difference across them. When exposed to a temperature gradient, thermoelectrification involves a fast initial stage dominated by Bjerrum defects and a subsequent slow stage driven by ionic defects. The time scales of the first and second stages are derived analytically and correspond to the Debye time scales based on the density of Bjerrum and ionic defects, respectively. For a given ice slab, at the steady state, the thermovoltage across it and the charge accumulation near its two ends depend strongly on its thickness, with the sensitivity of the thermovoltage being more pronounced. The discrepancy between the computed thermovoltage and experimental measurements is analyzed. The analysis shows that, although thermoelectric effects in ice were discovered 50 years ago, significant gaps, ranging from the bulk and interfacial properties of defects to the measurement of thermovoltage, exist in the quantitative understanding of these effects. Filling these gaps requires further experimental, theoretical, and computational studies.

Severe deviation in structure and chemistry at grain boundaries has been regarded as the source of the poor conductivity of Li3xLa2/3-xTiO3. In this work, we report an in situ grain boundary engineering method to address this bottleneck. A lithium-rich electrolyte, Li3OCl, was introduced into Li3xLa2/3-xTiO3 to replenish lithium at the grain boundaries. Both the Li-gain on the boundary and generation of a Li-rich grain-engineered layer contributed to an optimized grain boundary conductivity of 1.52 × 10−4 (S/cm) and a depressed activation energy of 0.32 eV for grain boundary. Full batteries were further employed to demonstrate the enhancement in conductivity.

Liquid electrolytes with high ionic conductivity, high transference number for the target ions, and excellent electrochemical, chemical, and thermal stability are essential for electrochemical energy storage devices. Water-in-salt (WIS) electrolytes, in which the salt–water ratio is larger than one, are gaining intensive attention in the electrochemical community. Here, we review the recent work on WIS electrolytes and the closely related water-in-ionic liquid electrolytes. We highlight the fact that many properties of these electrolytes, in bulk and at electrolyte–electrode interfaces, are underpinned by the physics and chemistry of the interfaces formed between water and ions (or aggregated water/ion clusters). Manipulating these interfaces by tailoring the selection of ions and water–ion ratio opens up new dimensions in the optimization of liquid electrolytes but also poses new challenges. We conclude the review by highlighting several directions for research on WIS electrolytes, in particular, the study of WIS electrolyte–electrode interfaces using surface force measurements.

After an attack the by pine wood nematode, pine tree needles turn red. Using convolutional neural networks (CNNs) based object detection methods, machines can detect red-attacked trees. However, mo...

Summary In nanoporous rocks, potential size/mobility exclusion and fluid–rock interactions in nanosized pores and pore throats can turn the rock into a semipermeable membrane, blocking or hindering the passage of certain molecules while allowing other molecules to pass freely. In this work, we conducted several experiments to investigate whether CO2 can mitigate the sieving effect on the hydrocarbon molecules flowing through Niobrara samples. Molecular dynamics (MD) simulations of adsorption equilibrium with and without CO2 were performed to help understand the trends observed in the experiments. The experimental procedure includes pumping liquid binary hydrocarbon mixtures (C10 and C17) of known compositions into Niobrara samples, collecting the effluents from the samples, and analyzing the compositions of the effluents. A specialized experimental setup that uses an in-line filter as a minicore holder was built for this investigation. Niobrara samples were cored and machined into 0.5-in. diameter and 0.7-in. length minicores. Hydrocarbon mixtures were injected into the minicores, and effluents were collected periodically and analyzed using gas chromatography (GC). After observing the sieving effect of the minicores, CO2 huff ‘n’ puff was performed at 600 psi, a pressure much lower than the miscibility pressure. CO2 was injected from the production side to soak the sample for a period, then the flow of the mixture was resumed, and effluents were analyzed using GC. Experimental results show that CO2 huff ‘n’ puff in several experiments noticeably mitigated the sieving of heavier components (C17). The observed increase in the fraction of C17 in the produced fluid can be either temporary or lasting. In most experiments, temporary increases in flow rates were also observed. MD simulation results suggest that for a calcite surface in equilibrium with a binary mixture of C10 and C17, more C17 molecules adsorb on the carbonate surface than the C10 molecules. Once CO2 molecules are added to the system, CO2 displaces C10 and C17 from calcite. Thus, the experimentally observed increase in the fraction of C17 can be attributed to the release of adsorbed C17. This study suggests that surface effects play a significant role in affecting flows and compositions of fluids in tight formations. In unconventional oil reservoirs, observed enhanced recovery from CO2 huff ‘n’ puff could be partly attributed to surface effects in addition to the recognized thermodynamic interaction mechanisms.

The identification of CN- in water, seeds and biological systems has, due to its high toxicity, attracted the increasing attention of many chemical industry researchers. In the work, a novel highly...

CO2-based enhanced oil recovery is widely practiced. The current understanding of its mechanisms largely focuses on bulk phenomena such as achieving miscibility or reducing oil density and viscosity. Using molecular dynamics simulations, we show that CO2 adsorption on calcite surfaces impedes decane transport at moderate adsorption density but enhances decane transport when CO2 adsorption approaches surface saturation. These effects change the decane permeability through 8 nm-wide pores by up to 30% and become negligible only in pores wider than several tens of nanometers. The strongly nonlinear, non-monotonic dependence of decane permeability on CO2 adsorption is traced to CO2's modulation of interfacial structure of long-chain hydrocarbons, and thus the slippage between interfacial hydrocarbon layers and between interfacial CO2 and hydrocarbon layers. These results highlight a new and critical role of CO2-induced interfacial effects in influencing oil recovery from unconventional reservoirs, whose porosity is dominated by nanopores.

Ultra-fast detection of hazardous gases with high selectivity is important for environmental safety monitoring. In this study, we report a Li0.5La0.5TiO3 (LLTO) sensor with an ultrafast response to H2S. We used a simple solvothermal method to controllably synthesize hollow LLTO nano-spheres. The LLTO nano-spheres had a porous surface structure, which provides sufficient channels for diffusion of H2S gas. Response/recovery speeds of 0.7 s/0.8 s were achieved at an optimum working temperature of 340 °C. To further improve the response, the band structure was modulated by Fe doping (FLTO). When doped with Fe3+, more oxygen vacancies were generated which enhanced the chemical absorption of O2 and generation of active oxygen species (O− and O2−). Furthermore, the band gap was also narrowed and the conduction band was elevated by 0.44 eV, which promoted charge transfer from the conduction band of FLTO to chemisorbed gas molecules. After doping, the response was 5.5 times as great as that of the pristine LLTO sensor for 30 ppm H2S and the optimum temperature decreased to 300 °C. In addition, the detection limit was as low as 100 ppb. The doped LLTO sensor also had good repeatability and long-term stability.

Thin brine films are ubiquitous in oil-brine-rock systems such as oil reservoirs and play a crucial role in applications such as enhanced oil recovery. We report the results of molecular simulations of brine films that are confined between model oil (

A methionine methyl ester-modified coumarin derivative was designed and synthesized, which could discriminate Cu2+ from other metal ions in HEPES buffer (10 mM, pH 7.4)/CH3CN (40:60, V/V). The detection limit of WM toward Cu2+ was 1.84 × 10−7 M, which was lower than the concentration of Cu2+ in drinking water suggested by WHO and EPA. And the proposed coordination mode exhibiting the interaction between WM and Cu2+ was studied by UV–Vis, fluorescence spectrum, ESI-MS and FT-IR. Based on the fluorescent reversibility of WM, WM was considered as a molecular logic gate and molecular keypad lock. In addition, the test strips and the silica gel plates prepared from the solution of WM also demonstrate the favorable selectivity toward Cu2+.

The fluorescent probe L, based on naphthalimide-modified coumarin, was designed, synthesized, and characterized, which could recognize Cu2+ from other cations selectively and sensitively in HEPES buffer (10 mM, Ph = 7. 4)/CH3CN (1:4, V/V). When the probe L interacted with Cu2+, the color and the fluorescent intensity changed obviously and it provided the naked-eye detection for Cu2+. The recognition mode between them was achieved by Job's plot, IR, MS, SEM, and 1HNMR. In addition, test strips made from L could still interact with Cu2+ in tap water effectively. The limit of detection (LOD) of L was 3.5 × 10-6 M. Additionally, the density functional theory (DFT) calculation method was used to analyze the action mechanism of L toward Cu2+. Importantly, the fluorescent probe L could demonstrate favorable selectivity toward Cu2+ in Caenorhabditis elegans. Thus, L was considered to have some potential for application in bioimaging.

Multiphase transport at a nanoscale level plays a key role in applications including drying of nanoporous materials and gas/oil recovery from low permeability rocks. A frequently encountered scenario in multiphase transport is the presence of droplets near nanopores. Whether droplets invade the nanopores or become trapped at their entrance greatly affects the operation of engineered systems. Here we analyze the free energy profile of nanometer-sized droplets entering the nanopore and how the profile is affected by the pressure difference and the size of the droplet and the nanopore. We show that, for nanopores whose surface is fully wetted by water but not the droplet, a droplet larger than the pore diameter must overcome a higher free energy barrier than that predicted by classical theories due to the large disjoining pressure. For smaller nanodroplets, the threshold pressure for their invasion into a given nanopore can be lowered by thermal activation. When a droplet is slightly narrower than a pore, and thus is often assumed to enter the pore freely, a large energy barrier for droplet entry can actually exist. The droplet cannot easily enter the pore even with hydrodynamic drag by moving fluids. Entering the pore through Brownian motion is possible, and the mean entry time depends sensitively on the pore size and can reach seconds or even longer. These findings provide molecular insights on the invasion of droplets into nanopores and lay foundations for large-scale modeling of multiphase nanofluidic transport. Public domain – authored by a U.S. government employee

Summary The inevitable presence of water at the interfaces of ionic liquids and solid surfaces can either be a nuisance or a delight, depending on the applications. Here, researches on the adsorption of water at these interfaces, its effects on the interfaces’ molecular structure and dynamics, and its practical implications are reviewed.

Electroencephalogram (EEG) signal-based emotion recognition has attracted wide interests in recent years and has been broadly adopted in medical, affective computing, and other relevant fields. However, the majority of the research reported in this field tends to focus on the accuracy of classification whilst neglecting the interpretability of emotion progression. In this paper, we propose a new interpretable emotion recognition approach with the activation mechanism by using machine learning and EEG signals. This paper innovatively proposes the emotional activation curve to demonstrate the activation process of emotions. The algorithm first extracts features from EEG signals and classifies emotions using machine learning techniques, in which different parts of a trial are used to train the proposed model and assess its impact on emotion recognition results. Second, novel activation curves of emotions are constructed based on the classification results, and two emotion coefficients, i.e., the correlation coefficients and entropy coefficients. The activation curve can not only classify emotions but also reveals to a certain extent the emotional activation mechanism. Finally, a weight coefficient is obtained from the two coefficients to improve the accuracy of emotion recognition. To validate the proposed method, experiments have been carried out on the DEAP and SEED dataset. The results support the point that emotions are progressively activated throughout the experiment, and the weighting coefficients based on the correlation coefficient and the entropy coefficient can effectively improve the EEG-based emotion recognition accuracy.

Inverse problems involving transport phenomena are ubiquitous in engineering practice, but their solution is often challenging. In this work, we build a data-driven deep learning model to predict the heterogeneous distribution of circle-shaped fillers in two-dimensional thermal composites using the temperature field in the composite as an input. The deep learning model is based on convolutional neural networks with a U-shape architecture and encoding–decoding processes. The temperature field is cast into images of 128 × 128 pixels. When the true temperature at each pixel is given, the trained model can predict the distribution of fillers with an average accuracy of over 0.979. When the true temperature is only available at 0.88% of the pixels inside the composite, the model can predict the distribution of fillers with an average accuracy of 0.94, if the temperature at the unknown pixels is obtained through the Laplace interpolation. Even if the true temperature is only available at pixels on the boundary of the composite, the average prediction accuracy of the deep learning model can still reach 0.80; the prediction accuracy of the model can be improved by incorporating true temperature in regions where the model has low prediction confidence.

The adsorption of gas molecules at electrode–electrolyte interfaces is an important step in electrochemical reactions. Using molecular dynamics simulations, we investigate the adsorption of dissolved N2 in the electrical double layers (EDLs) of an aqueous electrolyte near planar and 1 nm radius spherical carbon electrodes. The adsorption of N2 is found to be overall enriched near neutral electrodes regardless of their surface curvature, although it can be locally enriched or depleted depending on the distance from the electrode surface. In comparison, the adsorption of N2 in the EDL near negatively charged electrodes is found to increase under a moderate surface charge density, but decrease under a high surface charge density, especially near a planar electrode. By analyzing the potential of mean force for dissolved N2, the solvent-induced effects are found to play important roles in influencing the adsorption of N2 in the EDLs. The adsorption behavior of N2 molecules, especially their dependence on the s...

Solvate ionic liquids (SILs) are a promising electrolyte for Li-ion batteries; thus, their behavior at electrified interfaces is crucial for the operation of these batteries. We report molecular dynamics simulation results for a prototypical SIL of lithium triglyme bis(trifluoromethanesulfonyl)imide ([Li(G3)][TFSI]) sandwiched between electrified surfaces. At negatively charged as well as neutral electrodes, the electrolyte largely maintains the characteristics of SILs in terms of the interfacial Li+ ions’ coordination by a similar number of oxygen atoms on G3 ligands as the bulk Li+ ions. The persistence of the complex ions is attributed to the 1:1 Li–G3 ratio in bulk SILs and the fact that G3 molecules readily adapt to the interfacial environment by aligning themselves with the surface to ensure good solvation of the interfacial Li+ ions. Nevertheless, the interfacial Li+ ions also display changes of solvation from that in bulk SIL by deviating from the molecular plane formed by the oxygen atoms on G3 l...

A new fluorescent probe L based on the rhodamine 6G platforms for Fe3+ has been designed and synthesised. L showed excellent selectivity and high sensitivity for Fe3+ against other metal ions such ...

A fluorescent probe for Zn2+ based on rhodamine-6G has been synthesised. It showed excellent fluorescent specific selectivity and high sensitivity for Zn2+ compared with other metal ions, such as Fe3+, Cr3+, Hg2+, Ag+, Ca2+, Cu2+, Pb2+, Cd2+, Ni2+, Co2+ and Mg2+, in CH3CN–phosphate buffer saline solution. The distinct colour change and the rapid emergence of fluorescence emission provided ‘naked-eye’ detection of Zn2+. The detection limit of the fluorescent probe towards Zn2+ was 1.78 μM. In addition, the fluorescence lifetime and fluorescence quantum yield were measured.

Influenza viruses have threatened animals and public health systems continuously. Moreover, there are many subtypes of influenza viruses, which have brought great difficulties to the classification of influenza viruses during any influenza outbreak. So it is crucial to develop a rapid and accurate method for detecting and subtyping influenza viruses. In this work, we reported a rapid method for simultaneously detecting and subtyping multiple influenza viruses (H1N1, H3N2 and H9N2) based on nucleic acid hybridization on a microfluidic chip integrated with controllable micro-magnetic field. H1N1, H3N2 and H9N2 could be simultaneously detected in 80min with detection limits about 0.21nM, 0.16nM, 0.12nM in order. Moreover, the sample and reagent consumption was as low as only 3μL. The results indicated that this approach possessed fast analysis and high specificity. Therefore, it is expected to be used to simultaneously subtype and detect multiple targets, and may provide a powerful technique platform for the rapid detection and subtyping analysis of influenza viruses.

Finite-impulse response filters are widely used in digital signal processing applications. Prodigious research in the past two decades has substantially reduced the implementation cost of the multiple constant multiplication blocks. Further area and power consumption savings are stagnated by the structural adders and registers in the tap delay-and-accumulate line, which unfortunately dominate the overall hardware cost of FIR filter and are difficult to minimize by existing resource sharing approaches. Retiming or relocating the structural adders and registers can improve merely the throughput. To close the area-power efficiency gap, we reformulate the filter coefficient synthesis problem to explore the design space for the tap delay-and accumulate line by bisecting at some tap position. An efficient Genetic Algorithm is proposed to solve this integer programming problem at quadratic computational complexity by refining the search space for finding an optimized solution to fulfill the frequency response specifications. Field programmable gate array and application specific integrated circuit logic synthesis results from twelve benchmark filter specifications showed that the average area and power consumptions of the solutions generated by our proposed algorithm have been reduced by up to 26.8% and 27.5% respectively, in comparison with the solutions obtained by existing design methods.

Bioelectrochemical systems (BES) can recover ammonia from wastewater driven by electricity generation. However, energy consumption of such an approach has not been well evaluated. In this study, the effects of several key operating factors including catholyte aeration rate, external voltage, and external resistance on both ammonia recovery and energy consumption were systematically investigated. A mathematical model developed for ammonia removal/recovery in BES was applied to help interpret the experimental results. It was found that a high aeration rate in the catholyte could facilitate ammonia recovery. An aeration rate of 100 mL min −1 resulted in the lowest energy consumption of 4.9 kWh kg −1 N recovery among the tested aeration rates. A low external resistance facilitated the ammonia recovery via higher current generation, while a moderate external voltage (e.g., 0.5 V) helped to achieve low energy consumption. The highest ammonia recovery rate of 7.1 g N m −2 d −1 was obtained with energy consumption of 5.7 kWh kg −1 N recovery. Therefore, there is a trade-off between energy consumption and ammonia recovery.

The adsorption of multicomponent gas mixtures in shale formations and their recovery are of great interest to the shale gas industry. Here we report molecular dynamics simulations of the adsorption of methane/ethane mixtures in 2 and 4 nm-wide nanopores and their recovery from these nanopores. Surface adsorption contributes significantly to the storage of methane and ethane inside the pores, and ethane is enriched inside the nanopores in equilibrium with bulk methane–ethane mixtures. The enrichment of ethane is enhanced as the pore is narrowed but is weakened as the pressure increases due to entropic effects. These effects are captured by the ideal adsorbed solution (IAS) theory, but the theory overestimates the adsorption of both gases. Upon opening the mouth of the nanopores to gas baths with lower pressure, both gases enter the bath. The production rates of both gases show only weak deviation from the square root scaling law before the gas diffusion front reaches the dead end of the pores. The ratio of...

Nanopores in graphene-based membranes have shown great potential in enabling highly efficient water desalination. The effective engineering of these membranes necessitates a fundamental understanding of how the physical structure and chemical details of their nanopores govern their desalination performance. Using molecular dynamics simulations, we investigate how the ionization of the functional groups along the perimeter of the nanopores in single-layer graphene oxide membranes affects water transport and salt leakage. Moderate ionization enhances water transport and leads to higher salt leakage. With further ionization of the functionalization groups, water flux through the pore is reduced while the salt leakage shows little change. The significant role of functionalization groups’ ionization in modulating the water flux and salt leakage through the nanopores is attributed to the different organizations of water molecules and ions in and near the pore as the pore becomes charged due to ionization.

Porous liquids are a promising new class of materials featuring nanoscale cavity units dispersed in liquids that are suitable for applications such as gas storage and separation. In this work, we use molecular dynamics simulations to examine the multicomponent gas storage in a porous liquid consisting of crown-ether-substituted cage molecules dissolved in a 15-crown-5 solvent. We compute the storage of three prototypical small molecules including CO2, CH4, and N2 and their binary mixtures in individual cage molecules. For porous liquids in equilibrium with a binary 1:1 gas mixture bath with partial gas pressure of 27.5 bar, a cage molecule shows a selectivity of 4.3 and 13.1 for the CO2/CH4 and CO2/N2 pairs, respectively. We provide a molecular perspective of how gas molecules are stored in the cage molecule and how the storage of one type of gas molecule is affected by other types of gas molecules. Our results clarify the molecular mechanisms behind the selectivity of such cage molecules toward different...

The electrical double layers (EDLs) in the mixtures of room-temperature ionic liquids and water play an important role in many applications but have only begun to receive widespread attention recently. Here, we report the molecular dynamics simulations of EDLs near rigid polyanion nanorods immersed in electrolytes containing ionic liquids [C2mim][TfO], water, and Na+ ions. When the water content in bulk electrolyte is high, the EDLs near the rods are similar to those in aqueous electrolytes except that TfO– ions accumulate notably near the cation layer adsorbed on the rods. When the water content in the bulk electrolyte becomes very low, even though water is greatly enriched in the interfacial region, the microenvironment in the region offers weak dielectric screening and the EDL exhibits features common to those in neat ionic liquids, e.g., charge overscreening. Na+ ions are readily adsorbed on the sulfonate groups of the polyanion rod in the range of water contents explored here but can experience an en...

Single-layer graphene oxide (SLGO) is emerging as a new-generation membrane material for high-flux, high-selectivity water purification, owing to its favorable two-dimensional morphology that allows facile fabrication of ultrathin membranes with subnanometer interlayer channels. However, reliable and precise molecular sieving performance still necessarily depends on thick graphene oxide (GO) deposition that usually leads to low water flux. This trade-off between selectivity and flux significantly impedes the development of ultrathin GO membranes. In this work, we demonstrate that the selectivity/flux trade-off can be broken by self-assembly of SLGO via simple deposition rate control. We find GO membranes, prepared by slow deposition of SLGO flakes, exhibit considerably improved salt rejection, while counterintuitively having 2.5-4 times higher water flux than that of membranes prepared by fast deposition. This finding has extensive implications of designing/tuning interlayer nanostructure of ultrathin GO membranes by simply controlling SLGO deposition rate and thus may greatly facilitate their development for high flux, high selectivity water purification.

Driven by a magnetic field, the rotation of a particle near a wall can be rectified into a net translation. The particles thus actuated, or surface walkers, are a kind of active colloid that finds application in biology and microfluidics. Here, we investigate the motion of spherical surface walkers confined between two walls using simulations based on the immersed-boundary lattice Boltzmann method. The degree of confinement and the nature of the confining walls (slip vs no-slip) significantly affect a particle's translational speed and can even reverse its translational direction. When the rotational Reynolds number

Drainage and evaporation can occur simultaneously during the drying of porous media, but the interactions between these processes and their effects on drying are rarely studied. In this work, we develop a pore network model that considers drainage, evaporation, and rarefied multi-component gas transport in porous media with nanoscale pores. Using this model, we investigate the drying of a liquid solvent-saturated porous medium enabled by the flow of purge gas through it. Simulations show that drying progresses in three stages, and the solvent removal by drainage effects (evaporation effects) becomes weaker (stronger) as drying progresses through these stages. Interestingly, drainage can contribute considerably to solvent removal even after evaporation effects become very strong, especially when the applied pressure difference across the porous medium is low. We show that these phenomena are the results of the coupling between the drainage and evaporation effects and this coupling depends on the operating conditions and the stage of drying.

A fluorescent and colorimetric chemosensor L based on rhodamine 6G was designed, synthesized, and characterized. Based on a two-step reaction, the chemosensor L effectively recognized Hg2+. The interaction between the chemosensor and Hg2+ was confirmed by ultraviolet–visible spectrophotometry, fluorescence spectroscopy, electrospray ionization–mass spectrometry, Fourier-transform infrared spectroscopy, and frontier molecular orbital calculations. The chemosensor L was also incorporated into test strips and silica gel plates, which demonstrated good selectivity and high sensitivity for Hg2+.

Safe and scalable dynamic autonomous data interaction between medical institutions can increase the number of clinical trial records, which is of great significance for improving the level of medical trial collaboration, especially for clinical decision-making with regard to rare diseases. Through a preset authorization access and consensus mechanism, consortium chain provides integrity and traceability management for medical clinical data. However, how to enable users have ownership of their own medical data and share their medical data safely and dynamically between different medical institutions remains an area of particular concern. To achieve dynamic communication between medical consortium chains, this paper proposes (i) a cross-chain communication mechanism by simplifying the heterogeneous node communication topology and (ii) the construction rules of the node identity credibility path-proof to carry out dynamic construction and verification of the path-proof for cross-chain transactions. In addition, the consensus of the cross-chain transaction is modeled as a threshold digital signature process with multiple privileged subgroups; thus, the intra-chain consortium consensus based on the verification node list is extended to the cross-chain consensus. A smart contract deployment and execution scheme based on rational node value transfer mechanism is proposed by analyzing the value transfer game between nodes. Experimental results showed that the proposed scheme can not only enable patients to share their records safely and autonomously in an authorized medical consortium chain within milliseconds but also realize dynamic adaptive interaction among heterogeneous consortium chains.

We report the application of machine learning methods for predicting the effective diffusivity (De) of two-dimensional porous media from images of their structures. Pore structures are built using reconstruction methods and represented as images, and their effective diffusivity is computed by lattice Boltzmann (LBM) simulations. The datasets thus generated are used to train convolutional neural network (CNN) models and evaluate their performance. The trained model predicts the effective diffusivity of porous structures with computational cost orders of magnitude lower than LBM simulations. The optimized model performs well on porous media with realistic topology, large variation of porosity (0.28–0.98), and effective diffusivity spanning more than one order of magnitude (0.1 ≲ De < 1), e.g., >95% of predicted De have truncated relative error of De is larger than 0.2. The CNN model provides better prediction than the empirical Bruggeman equation, especially for porous structure with small diffusivity. The relative error of CNN predictions, however, is rather high for structures with De De

Polyamine plays the important role in human body. Here, the convenient synthesis of AIE material 2-(pyren-1-ylmethylene) malononitrile (L) was capable of fluorescent recognition for 1, 3-diaminopropane in gas-liquid-solid three-phase with good selectivity and high sensitivity. And it's interesting that other amines did not interfere with the recognition between L and 1,3-diaminopropane. The proposed sensing mechanism was supported by Job's plots, 1H NMR titration, FT-IR, electron-spray ionization, and density functional theory calculation analysis. The limits of detection were estimated as 1.34 × 10−8 M. The self-made test strips and silica gel plates realized the easy detection of 1, 3-diaminopropane. L-1, 3-diaminopropane possessed the potential for fingerprint recognition based on AIEE in the silica gel plates developed within this study. Notably, bioimaging in seeds, plant tissues, Caenorhabditis elegans, and mice revealed that L could be suitable as an effective sensor for detecting 1, 3-diaminopropane in living systems with the strong “turn-on” fluorescence. Importantly, L showed good biocompatibility and could effectively recognize 1, 3-diaminopropane and reveal its location with colored AIEE fluorescence in HeLa cells.

In this paper, the natural sepiolite nanofibers (Sep) were selected to be as the dispersion supporter of conductive polymer polypyrrole (PPy) owing to low cost, natural nanowires and well dispersibility in the PVDF matrix. The one-dimensional core-shell polypyrrole/sepiolite (PPy@Sep) nanofibers were synthesized by in-situ polymerization and subsequently introduced into the PVDF matrix by the solution blending method. The experimental results demonstrated that PPy was uniformly coated on the Sep surface. The PPy@Sep nanofibers could disperse in PVDF matrix well and produce the effect of heterogeneous nucleation on PVDF crystallization. With the increasing content of PPy@Sep from 1 wt% to 5 wt%, the dielectric constant of PVDF-based nanocomposites improved from 12 to 40 at 100 Hz because of the hierarchical interfacial polarization originating from the PPy/Sep interface and PPy/PVDF interface and microcapacitor effect. Meanwhile, a low dielectric loss was observed in the nanocomposites.

It is discovered that a non-uniform alternating magnetic field can induce a translational motion of an anisotropic magnetic particle or cluster near a surface. Unlike a permanent magnet pulling a magnetic particle, the particle moves away from the magnetic source with a periodic fluctuation in its trajectory that varies with a frequency that is twice that of the field frequency. The moving speed can be tuned by varying the magnetic field strength and gradient, its alternating frequency, and the particle size. A hydrodynamic model is developed that can qualitatively explain all of the phenomena observed. Such a simple particle manipulation method has a great potential in applications such as cell biology and microfluidics.

The recent fabrication of liquid crystalline ion gels featuring rigid-rod polyanions aligned within room-temperature ionic liquids (RTILs) opens up exciting new avenues for engineering ion conducting materials. These gels exhibit an unusual combination of properties including high ionic conductivity, distinct transport anisotropy, and widely tunable elastic modulus. Using molecular simulations, we study the structure and dynamics of the ions in an ion gel consisting of rigid-rod polyanions and [C2mim][TfO] RTILs. We show that the ion distribution in the interstitial space between polymer rods exhibits the hallmarks of the RTIL structure near charged surfaces; i.e., cations (C2mim+) and anions (TfO–) form alternating layers around the polymer rods and the charge on the rod is overscreened by the ionic layer surrounding it. The distinct ordering of ions suggests the formation of a long-range “electrostatic network” in the ion gel, which may contribute to its mechanical cohesion and high modulus. The dynamic...

Microemulsions are thermodynamically stable dispersions of nano-droplets stabilized by surfactants. In water-in-oil microemulsions, the nano-droplets exist in the form of swollen reverse micelles. Recent experiments demonstrated very high critical heat fluxes (CHF) in boiling of water-in-oil microemulsions, which makes these microemulsions ideal heat transfer fluids for high heat-flux thermal management applications. While the nanoscale structure of the microemulsions is inevitably changed during their boiling, little is known about such change and its energetics, which are critical for understanding the microemulsion boiling. Here we report a study of the pathway and energetics of thermally-induced structural change in water-in-oil microemulsions using microsecond-long molecular dynamics simulations. We show that, for microemulsions that are thermodynamically stable at room temperature, upon increasing their temperature to similar to that found in boiling experiments, their spherical reverse micelles transition to cylindrical wormlike reverse micelles through merging and splitting of individual reverse micelles. These structural transitions are accompanied by a gradual release of water molecules from the reverse micelles. These transitions are endothermic with the heat absorption dominated by the release of water molecules from the water core of the reverse micelles. The release rate of water molecules from the interior of reverse micelles, hence the heat absorption rate, slows down as the structural transition proceeds because the remaining water molecules in the interior bind more strongly to the polar moieties of the surfactants.

The recent synthesis of organic molecular liquids with permanent porosity opens up exciting new avenues for gas capture, storage, and separation. Using molecular simulations, we study the thermodynamics and kinetics for the storage of CH4, CO2, and N2 molecules in porous liquids consisting of crown-ether-substituted cage molecules in a 15-crown-5 solvent. It is found that the intrinsic gas storage capacity per cage molecule follows the order CH4 > CO2 > N2, which does not correlate simply with the size of gas molecules. Different gas molecules are stored inside the cage differently; e.g., CO2 molecules prefer the cage's core whereas CH4 molecules favor both the core and the branch regions. All gas molecules considered can enter the cage essentially without energy barriers and leave the cage on a nanosecond time scale by overcoming a modest energy penalty. The molecular mechanisms of these observations are clarified.

The swelling of clay at high temperature and pressure is important for applications including nuclear waste storage but is not well understood. A molecular dynamics study of the swelling of Na montmorillonite in water at several temperatures (T = 298, 400, and 500 K) and water environment pressures (Pe = 5 and 100 MPa) is reported here. Adopting a rarely used setup that enables swelling pressure to be resolved with an accuracy of ~1 MPa, the swelling pressure was computed at basal spacings 1.6–2.6 nm (or 2–5 water layers between neighboring clay sheets), which has not been widely studied before. At T = 298 K and Pe = 5 MPa, swelling pressure Ps oscillates at d-spacing d smaller than 2.2 nm and decays monotonically as d increases. Increasing T to 500 K but keeping Pe at 5 MPa, Ps remains oscillatory at small d, but its repulsive peak at d = 2.2 nm shifts to ~2.0 nm and Ps at different d-spacings can grow more attractive or repulsive. At d > 2.0 nm, Ps is weakened greatly. Keeping T at 500 K and increasing Pe to 100 MPa, Ps recovers toward that at T = 298 K and Pe = 5 MPa, however, the repulsive peak at d = 2.0 nm remains the same. The opposite effects of increasing temperature and pressure on the density and dielectric screening of water, which control ion correlations and thus double layer repulsion, are essential for understanding the observed swelling pressure at elevated temperatures and its response to environment pressures.

The preparation of large-aspect-ratio nanofillers is challenging due to the complicated and expensive artificial processing procedures and low yields, obstructing scale-up production of 1D nanofillers/polymer dielectric nanocomposites. In this paper, a kind of natural sepiolite nanofiber was utilized to fabricate scale-up of PVDF-based dielectric nanocomposites. The sepiolite nanofibers were modified by aminopropyltriethoxysilane (denoted as APTES@Sep) and 1H,1H,2H,2H-perfluoroheptadecane trimethysiloxane (denoted as PFDTES@Sep), respectively, before being incorporated into PVDF. The effect of nanfibers loading and modifiers on the dielectric behaivor and energy stroage properties of nanocomposites was investigated. As results, the nanocomposites with 7.5 vol% PFDTES@Sep exhibited highest permittivity of 16.4 at 103 Hz originating from well dispersibility, strong interfacial polarization and orientation polarization. The nanocomposites with 2.5 vol% APTES@Sep displayed maximal discharged energy density of 7.2 J·cm−3 owing to highest breakdown strength. This work provides a simple and cheap strategy for developing high performance flexible dielectric nanocomposites, which is suitable for large-scale preparation.

Graph pattern matching that aims to seek out answer graphs in a data graph matching a provided graph, plays a fundamental role as a part of graph search for graph databases. “Matching” indicates that the two graphs are correlated, such as bisimulation, isomorphism, simulation, etc. The strictness of bisimulation is between simulation and isomorphism. Seldom work has been done to search for bisimulation subgraphs. This research focuses on the problem. The symbol [Formula: see text] is introduced to fundamental modal logic language, thereby yielding [Formula: see text] language; the symbols [Formula: see text] is added for forming [Formula: see text] formulas. Then conclusions about graph bisimulations are shown. Subsequently, a theorem with detailed proof is presented, stating that [Formula: see text] formulas characterize finite directed graphs modulo bisimulation. According to the conclusions and theorem, algorithms for finding subgraphs are proposed. After dividing the query graph, the match graphs undergo the characterization using [Formula: see text] formulas. In the data graphs, by model checking the formulas, the answer graphs exhibiting bisimilarity to the match graphs are able to be captured.

The ubiquitous biomacromolecule DNA has an axial rigidity persistence length of ~50 nm, driven by its elegant double helical structure. While double and multiple helix structures appear widely in nature, only rarely are these found in synthetic non-chiral macromolecules. Here we report a double helical conformation in the densely charged aromatic polyamide poly(2,2′-disulfonyl-4,4′-benzidine terephthalamide) or PBDT. This double helix macromolecule represents one of the most rigid simple molecular structures known, exhibiting an extremely high axial persistence length (~1 micrometer). We present X-ray diffraction, NMR spectroscopy, and molecular dynamics (MD) simulations that reveal and confirm the double helical conformation. The discovery of this extreme rigidity in combination with high charge density gives insight into the self-assembly of molecular ionic composites with high mechanical modulus (~ 1 GPa) yet with liquid-like ion motions inside, and provides fodder for formation of other 1D-reinforced composites., Double helix structures appear widely in nature, but only rarely in synthetic non-chiral macromolecules. Here the authors describe a double helix in a densely charged aromatic polyamide, which exhibits an axial rigidity persistence length of ~ 1 μm, much higher than that of DNA (~ 50 nm).

A nanostructured, carbon-based physical catalyst electrochemically reduces N2 to ammonia under ambient conditions., Ammonia synthesis consumes 3 to 5% of the world’s natural gas, making it a significant contributor to greenhouse gas emissions. Strategies for synthesizing ammonia that are not dependent on the energy-intensive and methane-based Haber-Bosch process are critically important for reducing global energy consumption and minimizing climate change. Motivated by a need to investigate novel nitrogen fixation mechanisms, we herein describe a highly textured physical catalyst, composed of N-doped carbon nanospikes, that electrochemically reduces dissolved N2 gas to ammonia in an aqueous electrolyte under ambient conditions. The Faradaic efficiency (FE) achieves 11.56 ± 0.85% at −1.19 V versus the reversible hydrogen electrode, and the maximum production rate is 97.18 ± 7.13 μg hour−1 cm−2. The catalyst contains no noble or rare metals but rather has a surface composed of sharp spikes, which concentrates the electric field at the tips, thereby promoting the electroreduction of dissolved N2 molecules near the electrode. The choice of electrolyte is also critically important because the reaction rate is dependent on the counterion type, suggesting a role in enhancing the electric field at the sharp spikes and increasing N2 concentration within the Stern layer. The energy efficiency of the reaction is estimated to be 5.25% at the current FE of 11.56%.

Ensuring the integrity and security of the memory system is critical. Recent studies have shown serious security concerns due to "rowhammer" attacks, where repeated accesses to a row of memory cause bit flips in adjacent rows. Recent work by Google's Project Zero has shown how to leverage rowhammer-induced bit-flips as the basis for security exploits that include malicious code injection and memory privilege escalation. Being an important security concern, industry has attempted to defend against rowhammer attacks. Deployed defenses employ two strategies: (1) doubling the system DRAM refresh rate and (2) restricting access to the CLFLUSH instruction that attackers use to bypass the cache to increase memory access frequency (i.e., the rate of rowhammering). We demonstrate that such defenses are inadequte: we implement rowhammer attacks that both avoid using the CLFLUSH instruction and cause bit flips with a doubled refresh rate. Our next-generation CLFLUSH-free rowhammer attack bypasses the cache by manipulating cache replacement state to allow frequent misses out of the last-level cache to DRAM rows of our choosing. To protect existing systems from more advanced rowhammer attacks, we develop a software-based defense, ANVIL, which thwarts all known rowhammer attacks on existing systems. ANVIL detects rowhammer attacks by tracking the locality of DRAM accesses using existing hardware performance counters. Our detector identifies the rows being frequently accessed (i.e., the aggressors), then selectively refreshes the nearby victim rows to prevent hammering. Experiments running on real hardware with the SPEC2006 benchmarks show that ANVIL has less than a 1% false positive rate and an average slowdown of 1%. ANVIL is low-cost and robust, and our experiments indicate that it is an effective approach for protecting existing and future systems from even advanced rowhammer attacks.

We studied the transport of room-temperature ionic liquids (RTILs) through charged conical nanopores using a Landau–Ginzburg-type continuum model (Bazant et al. Phys. Rev. Lett 2011, 106, 046102) that takes steric effect and strong ion–ion correlations into account. When the surface charge is uniform on the pore wall, weak current rectification is observed. When the charge density near the pore base is removed, the ionic current is greatly suppressed under negative bias voltage while nearly unchanged under positive bias voltage, thereby leading to enhanced current rectification. These predictions agree qualitatively with prior experimental observations, and we elucidated them by analyzing the different components of the ionic current and the structural changes of electrical double layers (EDLs) at the pore tip under different bias voltages and surface charge patterns. These analyses reveal that the different modifications of the EDL structure near the pore tip by the positive and negative bias voltages ca...

Molecular simulations of the diffusion of EMIM(+) and TFSI(-) ions in slit-shaped micropores under conditions similar to those during charging show that in pores that accommodate only a single layer of ions, ions diffuse increasingly faster as the pore becomes charged (with diffusion coefficients even reaching ∼5 × 10(-9) m(2)/s), unless the pore becomes very highly charged. In pores wide enough to fit more than one layer of ions, ion diffusion is slower than in the bulk and changes modestly as the pore becomes charged. Analysis of these results revealed that the fast (or slow) diffusion of ions inside a micropore during charging is correlated most strongly with the dense (or loose) ion packing inside the pore. The molecular details of the ions and the precise width of the pores modify these trends weakly, except when the pore is so narrow that the ion conformation relaxation is strongly constrained by the pore walls.