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To mimic and use the functions of the ion transport system that are central to biological processes, bioinspired ion-selective membranes are developed and show great potential in a variety of fields. However, the practical applications of them are now limited due to low pore density, low conductivity, or scale-up difficulty. Herein, we demonstrate a 2-hydroxyethyl methacrylate phosphate (HEMAP) hydrogel membrane with 3D interconnected nanopores and space charged through simple photopolymerization. The HEMAP hydrogel membrane exhibits high conductance and outstanding ion selectivity, and the membrane-based osmotic power generator shows the excellent output power density up to 5.38 W/m2. Both experimentally and theoretically, the 3D interconnected structure is revealed to play a key role in enhancing charge-governed ion transport and energy conversion. This work highlights the advantages of 3D interconnected nanopores in ion diffusion and shows the potential of our designed hydrogel membrane in osmotic energy conversion, water desalination, and sensors.

A kinetic investigation into the formation of spinel from alumina (Al2O3) and magnesia (MgO) powder compaction with a stoichiometric mixing molar ratio of 1:1 was conducted in the temperature range of 1573 K to 1773 K over a certain time interval up to 25 h. The samples were pressed at pressures of 125, 375 and 750 MPa. The progress of the reaction was evaluated by monitoring the expansion ratio instead of the thickness of the spinel layer that was generated. The expansion ratio increases with increasing pressing pressure and holding time, and high temperature favored spinel formation. However, densification was observed at temperatures above 1673 K due to the occurrence of sintering between the powders. A kinetic model taking electrochemical potential as the driving force of the reaction was established, and the apparent activation energy was calculated to be 310.6 kJ/mol in the temperature range between 1573 K and 1673 K. The reaction was controlled by the inter-diffusion of Al3+ and Mg2+ ions in the spinel layer that was formed.

Biological ion channel-based mass transport and signal transduction play a crucial role in physiological activities, and biomimetic nanochannels in aqueous solutions for ion transport regulation have been extensively studied. Few studies on non-aqueous systems, gel-based nanochannels, mainly focus on the charged gel network or embedded electrolytes. However, the basic issue of how a nanoscale gel network affects the ion transport in nanochannels has been neglected. Here, we demonstrate a non-aqueous biomimetic nanochannel system by employing the agarose hydrogel in conical nanochannels. To tune the hydrogel network by adjusting the gel concentration, the ion transport behavior in gel-based nanochannels is systemically investigated. The experimental results show that the ion transport behaviors in gel-nanochannels with 2% gel present similar ion selectivity and rectification performance to the aqueous system, indicating fast investigation of gel-based systems with the knowledge of the extensively studied aqueous systems. Furthermore, a gel-based solid-state diode and logic circuits were fabricated.

Bioinspired nanochannels whose functions are similar to those of the biological prototypes attract increasing attention due to their potential applications in signal transmission, mass transport, energy conversion, etc. Up to now, however, it is still a challenge to extract low-grade waste heat from the ambient environment in an aqueous solution. Herein, a thermo-driven nanofluidic system was developed to extract low-grade waste heat efficiently based on directed ionic transport at a micro-/nanoscale. A steady streaming current increases linearly with the temperature gradient, achieving as high as 14 nA at a temperature gradient of 47.5 °C (δT = 47.5 °C) through a 0.5 cm2 porous membrane (106 cm−2). And an unexpected theoretical power of 25.48 pW using a single nanochannel at a temperature difference of 40 °C has been achieved. This bioinspired multifunctional system broadens thermal energy recovery and will accelerate the evolution of nanoconfined mass transport for practical applications.

Capturing the osmotic power between seawater and river water is thought to be an effective strategy to solve the global energy crisis. The existing designs of membrane-based nanofluids with high io...

With the development of deep learning techniques and large scale datasets, the question answering (QA) systems have been quickly improved, providing more accurate and satisfying answers. However, current QA systems either focus on the sentence-level answer, i.e., answer selection, or phrase-level answer, i.e., machine reading comprehension. How to produce compositional answers has not been throughout investigated. In compositional question answering, the systems should assemble several supporting evidence from the document to generate the final answer, which is more difficult than sentence-level or phrase-level QA. In this paper, we present a large-scale compositional question answering dataset containing more than 120k human-labeled questions. The answer in this dataset is composed of discontiguous sentences in the corresponding document. To tackle the ComQA problem, we proposed a hierarchical graph neural networks, which represent the document from the low-level word to the high-level sentence. We also devise a question selection and node selection task for pre-training. Our proposed model achieves a significant improvement over previous machine reading comprehension methods and pre-training methods. Codes, dataset can be found at https://github.com/benywon/ComQA.

In this paper, the phase field method is used to study the multi control factors during directional solidification sidebranching growth of Al-Si alloy. The effects of primary dendritic spacing, pulling velocity, temperature gradient and thermal noise on the evolution of sidebranch are studied. As the primary dendritic spacing increases, the number of secondary branches symmetrically growing on both sides of the primary dendrites increases and the secondary branches are more developed; The increase of the pulling velocity and the temperature gradient can increase the instability of the sidebranch and the degree of solute enrichment in the secondary branches gap. Sidebranch remelting and coarsening will occur when the pulling velocity and temperature gradient are large; Without changing the tip morphology and steady-state behavior of the dendrite, appropriate thermal noise can trigger the sidebranching and make the sidebranch on both sides of the dendrite asymmetrically growth.

In this study, the phase field method was used to study the multi-controlling factors of dendrite growth in directional solidification. The effects of temperature gradient, propelling velocity, thermal disturbance and growth orientation angle on the growth morphology of the dendritic growth in the solid/liquid interface were discussed. It is found that the redistribution of solute leads to multilevel cavity and multilevel fusion to form multistage solute segregation, and the increase of temperature gradient and propelling velocity can accelerate the dendrite growth of directional solidification, and also make the second dendrites more developed, which reduces the primary distance and the solute segregation. When the temperature gradient is large, the solid-liquid interface will move forward in a flat interface mode, and the thermal disturbance does not affect the steady state behavior of the directionally solidified dendrite tip. It only promotes the generation and growth of the second dendrites and forms the asymmetric dendrite. Meanwhile, it is found that the inclined dendrite is at a disadvantage in the competitive growth compared to the normal dendrite, and generally it will disappear. When the inclination angle is large, the initial primary dendrite may be eliminated by its secondary or third dendrite.

Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous researches utilizing machine learning algorithms judge the semantic types of medical concept pair mentions independently. In fact, different concept pair mentions in the same context are of dependencies which can provide beneficial evidences for identifying their relation types. To the best of our knowledge, only one study has considered such dependencies in discharge summaries. However, its hard constraints are not applied effectively to the History of Present Illness (HPI) in electronic Medical Records. According to the writing characteristics of HPI records, we generalize two regularities of dependencies among concept pairs mentioned in an HPI record to enhance the performance of relation extraction. We incorporate the two soft constraints corresponding to the regularities and the posterior probabilities returned by a local classifier into a joint inference process which applies Integer Quadratic Programming method to carry out collective classification for all concept pair mentions in an HPI record. We implement four local classification models including support vector machine, logistics regression, random forest and piecewise convolutional neural networks to examine the performance of our approach. A series of experimental results demonstrate that our collective classification method has made a principal improvement and outperforms the other state-of-the-art methods.

We study the pairing symmetry of ${\mathrm{Sr}}_{2}{\mathrm{RuO}}_{4}$ through the group-theoretical approach. We emphasize the role of pairing interaction between the quasi-one-dimensional (Q1D) ${d}_{xz/yz}$ and quasi-two-dimensional (Q2D) ${d}_{xy}$ orbitals. It is found that two degenerate interorbital time-reversal-invariant(TRI) $p$-wave pairings, one spin singlet and the other spin triplet with out-of-plane $\mathbit{d}$ vector, could be the most promising candidates. Several important physical quantities are presented, including the near-nodal gap structure, the unchanged out-of-plane Knight shift, and no splitting of transition under strain, which are consistent with the experiments. In addition, these $p$-wave pairings shed light on resolving the contradiction between the time-reversal breaking and reduced in-plane Knight shift measurements. As the system reaches the Van Hove singularity under applied strain, the pairing symmetry would become a $d$-wave pairing mainly consisting of interorbital components, which could be responsible for the strained $3K$ phase.

News recommendation, which aims to help users find the news they are interested in, is essential for online news platforms to alleviate the information overload problem. News is full of textual information with some knowledge entities, so recent studies try to leverage knowledge graphs (KGs) as side information to better model user preferences over news. However, most knowledge-enhanced methods assume that users are interested in the knowledge entities that occurred in the news. In real scenarios, users may like the news because of the news content rather than the knowledge entities. To take both knowledge and content factors into consideration, we propose a news recommendation method, namely knowledge and content aware network for news recommendation (KCNR). KCNR represents user and news in terms of knowledge and content, then it predicts the weight of user preferences on knowledge and content via a user preferences prediction mechanism. Besides, based on the weight of user preferences on knowledge, it extends user preferences along with entities in knowledge graphs. Experiments on two real-world datasets show that our approach achieves significant improvements over several state-of-the-art baselines in news recommendation.

The concurrent think-aloud protocol (CTA) is an effective method for collecting abundant product comments related to user satisfaction during the execution of evaluation tasks. However, manual analysis of these audio comments is time-consuming and labor-intensive. This paper aims to propose an approach for automated comprehensive evaluation of user interface (UI) satisfaction. It takes advantage of text mining and sentiment analysis (SA) techniques instead of manual analysis in order to assess user comments collected by the CTA. Based on the results of the SA, the proposed approach makes use of the analytic hierarchy process (AHP) method to evaluate the overall satisfaction and support developers for UI design improvements. In order to enhance the objectivity of evaluation, a sentiment matrix originating from text mining and SA on user comments is used to replace the criteria and the relative weights of the AHP method which were previously defined by experts. A comparison between the questionnaire survey method and the proposed approach in the empirical study suggested that the latter can efficiently evaluate UI satisfaction with high accuracy and provide designers abundant and specific information directly related to defects in design. It is argued that the proposed approach could be used as an automated framework for handling any type of comments.

With the development of technology and society, ocean development is becoming more and more necessary and frequent. During this process, marine biofouling is an extensive problem, causing economic loss and operational problems. A lot of attempts have been made to overcome these troubles. However, there is still an urgent need to develop an efficient and environmentally friendly method to resist marine antifouling. As reported, the adhesion of diatoms is one of the key steps in the marine fouling process. In this research, for the first time, 3-(trimethoxysilyl)propylmethacrylate (TMSPMA), which is a synthetic orthosilicic acid analog (SOSA) after hydrolysis, is used as an anti-diatom agent against diatom adhesion in the preparation of a SOSA hydrogel. Detailed investigations suggest that the hydrogel with the SOSA shows excellent anti-diatom adhesion properties (0 Navicula and 0.2 ± 0.5 diatoms mm−2 of Nitzschia closterium adhered). The results also indicate that the SOSA anti-diatom effects are targeted; only the organisms that attempted to adhere to the surface of the SOSA hydrogel are affected. Owing to its high efficiency and environmentally-friendly properties, SOSA hydrogels have great potential for marine antifouling applications.

Liu, C.; Huang, Z., and Chen, W., 2017. A numerical study of a submerged horizontal heaving plate as a breakwater. Using a nonlinear numerical wave tank (NWT) based on potential flow, a submerged horizontal plate heaving in regular waves was simulated, and its performance as a breakwater was examined. The NWT is based on a Mixed Eulerian-Lagrangian formulation and a de-singularized boundary integral equation method. The viscous effect on the motion of the plate is estimated by a linear damping coefficient, and the natural frequency of the heaving plate is controlled by the system stiffness. Compared with a fixed submerged horizontal plate, our results showed that the heaving motion of the plate with a critical stiffness could reduce the wave-transmission coefficient to almost zero and effectively suppress the free and locked waves on the leeside of the plate. The new type of breakwater can be an ideal alternative for small marinas and recreational harbors.

We study the possibility of topological superconductivity in the noncentrosymmetric monolayer and trilayer TaS$_2$ with out-of-plane mirror symmetry. A gapless time-reversal invariant f+s-wave pairing state with even mirror parity is found to be a promising candidate. This mixing state holds 12(36) nodes at the Fermi pockets around $\Gamma$ for monolayer(trilayer) case and its unconventional superconductivity is consistent with the STM experiments observed in 2$H$-TaS$_2$ thin flakes. Furthermore, with doping or under uniaxial pressure for trilayer 2$H$-TaS$_2$, large-Chern-number time-reversal symmetry breaking mixing states between d+id- and p-ip-wave pairings can be realized in the phase diagram., Comment: 11 pages, 5 figures

We study transport properties of topological Weyl nodal-line semimetals(NLSs). Starting from a minimal lattice model with a single nodal loop, and by focusing on a normal-metal-NLS-normal-metal junction, we investigate the dependence of the novel transport behavior on the orientation of the nodal loop. When the loop is parallel to the junction interfaces, the transmitted current is found to be nearly fully spin-polarized. Correspondingly, there exists a spin orientation, along which the incident electrons would be totally reflected. An unusual resonance of half transmission with the participation of surface states also occurs for a pair of incident electrons with opposite spin orientations. All these phenomena have been shown to originate from the existence of a single forward-propagating mode in the NLS of the junction, and argued to survive in more generic multi-band Weyl NLSs., Comment: 12 pages, 11 figures

© 2020 Elsevier Ltd Bioinspired nanofluidic devices have drawn increasing global interest due to their giant applicable potential in a wide range of fields. By mimicking biological prototype, it is expected to achieve high energy conversion efficiency and tunable ion transport. However, the low osmotic conversion efficiency, weak ion transport capability and poor mechanical performance limit practical application. We designed a class of heterogeneous membrane consisting of a support layer and a thin top layer to meet fundamental requirements. To achieve higher power generation, we incorporated metal organic framework (MOF) nanosheets (dispersed phase) into polymer matrix (continuous phase) to afford a mixed matrix top layer. This unique structure addressed the geometric restriction associated with the polymeric specie due to their limited pore accessibility. As a result, the presented membranes produced high power density of ca. 7 W m−2 and a high energy conversion efficiency of ca. 40% under a salinity gradient of 50 (0.5 M|0.01 M, NaCl). This work thus offers an insight into a new methodology in the development of a novel membrane technology for highly efficient energy conversion.

The microstructure of boron doped diamond (BDD) is the main factor affecting its degradation performance, and the type of wastewater is also a major factor. In this paper, niobium based BDD electrodes were prepared by hot filament chemical vapor deposition (HFCVD) technology at 650 °C, 750 °C, 850 °C substrate temperatures. For the three BDD electrodes with different substrate temperatures, the comparison of electrochemical performance and degradation efficiency was conducted. The results showed that with the increase of deposition temperature, the microstructure of BDD electrodes surface changed, the grain size and boron content increased, and the sp3/sp2 phase ratio also increased, which caused the electrochemical oxidation performance of the BDD electrodes improved, the color removal rate of the electrodes increased, and the energy consumption reduced. The decolorization rates of the 850 °C-BDD electrode for Reactive orange X-GN and Reactive blue 19 at 180 min were 99.79 % and 93.38 %, respectively. In addition, the degradation performance of 8 dyes by 850 °C-BDD electrode was systematically studied. Affected by the molecular structure of dye, the degradation degree of each type of dye from easy to difficult was: Fuchsin acid, Reactive red 2, Acid orange G, Alizarin red, Acid blue 92, Reactive orange X-GN, Orange II, Reactive blue 19.

Biological ion channels and ion pumps with intricate ion transport functions widely exist in living organisms and play irreplaceable roles in almost all physiological functions. Nanofluidics provides exciting opportunities to mimic these working processes, which not only helps understand ion transport in biological systems but also paves the way for the applications of artificial devices in many valuable areas. Recent progress in the engineering of smart nanofluidic systems for artificial ion channels and ion pumps is summarized. The artificial systems range from chemically and structurally diverse lipid-membrane-based nanopores to robust and scalable solid-state nanopores. A generic strategy of gate location design is proposed. The single-pore-based platform concept can be rationally extended into multichannel membrane systems and shows unprecedented potential in many application areas, such as single-molecule analysis, smart mass delivery, and energy conversion. Finally, some present underpinning issues that need to be addressed are discussed.