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Chemical doping is verified to be a promising strategy to regulate local electron distribution and further promote the poor intrinsic catalytic activity of graphdiyne. However, the current doping approach still faces problems such as precise doping for creating active sites and the destruction of graphdiyne skeleton calling for high temperature. Here, we achieved charge redistribution on graphdiyne surface through molecule functionalization. A p-type molecule–F4TCNQ (2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane) was introduced and the site-defined functionalization was accomplished. Theoretical calculations showed that the charge transfer ability is improved and graphdiyne becomes positively charged. The oxygen reduction electrocatalysis was conducted as a proof of principle, where the electronic states of sp hybridized C active site was tuned toward favorable reaction intermediates’ adsorption. Such work from both theoretical prediction and experimental validation, found that molecule functionalization is effective to promote the electrocatalytic oxygen reduction, which creates new possibilities for graphdiyne’s applications in different electrochemical reactions.

Summary Interfacial solar vapor generation is an emerging technology for producing purified water with a minimized carbon footprint. While the evaporation rate has been significantly increased, the rate of water collection has been limited because of ineffective heat transfer during condensation and compromised light absorption in the conventionally designed solar still. In this work, an invert-structured, single-stage solar water purifier (ISWP) is elaborately designed and fabricated and consists of a top selective absorber and a honeycombed bottom water condenser based on hydrophobic nanostructured copper. This inverted structure not only avoids optical loss due to the vapor condensation but also realizes enhanced heat transfer and condensation. As a result, it can achieve a high water-collection rate of 1.063 kg m−2 h−1 and an overall efficiency of solar collected water of ∼70% for single-stage solar purification systems.

The progress on human pose estimation by deep neural networks has been significantly advanced in recent years. However, the problem of precision loss caused by the prediction of the coordinates back to the original image has been neglected. In this paper, we propose a simple but effective method using Heatmap and Offset for Pose Estimation (HOPE). In order to solve the human pose estimation problem, firstly a general top-down method is used in HOPE to generate the human detection box based on a detector, and then the keypoints in each cropped box image are located. To alleviate the precision loss of mapping process, HOPE embeds the coordinate offset into the structure of the neural network, allowing the network to self-learn the slight offset in the mapping process in an end-to-end manner, which improves the accuracy in the current field of pose estimation. Experimental results on the multi-person pose estimation dataset MSCOCO, the single-person pose estimation dataset MPII and CrowdPose Pose Estimation dataset indicate that our method achieves state-of-the-art performance in terms of accuracy and computational complexity.

Knowledge graph completion has become a well-studied problem and a non-trivial task with the broad application of the knowledge graphs. Previously, a lot of works have been proposed to solve the knowledge graph completion problem, for example, a series of Trans model, semantic matching models, convolutional neural networks based methods and so on. However, a series of Trans models and semantic matching models only focused on the shadow information of the knowledge graph, thus failed to capture the implicit fine-grained feature in the triple of knowledge graphs; convolutional neural networks based methods learned more expressive feature for knowledge graph completion, and it also ignored the directional relation characteristic and implicit fine-grained feature in the triple. In this paper, we propose a novel knowledge graph completion model named directional multi-dimensional attention convolution model that explores directional information and an inherent deep expressive characteristic of the triple. At last, we evaluate our directional multi-dimensional attention convolution model based on three standard evaluation criteria in two robust datasets, and the experiment shows that our model achieves state-of-the-art MeanRank.

A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protein-protein interactions (PPI) network, it is critical but non-trivial to detect protein complexes, the subsets of proteins that are tightly coupled, from it. Network embedding is a technique to learn low-dimensional representations of vertices in networks. It has been proved quite useful for community detection in social networks in recent years. However, unlike social networks, PPI network does not contain rich metadata, so that existing network embedding methods cannot fully capture the network structure of PPI to improve the effect of protein complexes detection significantly. We propose a semi-supervised network embedding model by adopting graph convolutional networks to detect densely connected subgraphs effectively. We compare the performance of our model with state-of-the-art approaches on three popular PPI networks with various data sizes and densities. The experimental results show that our approach significantly outperforms other approaches on all three PPI networks.

Entropy has been widely measured the complexity of complex networks. At present, many measures about entropies were defined based on the directed connection of nodes. The similarity of nodes can better represent the relationship among all nodes in complex networks. In the definition of similarity of nodes, the importance of a node in the network depends not only on the degree of the node itself, but also on the extent of dependence of neighboring nodes on the node. In this paper, we proposed a new structure entropy based on nonextensive statistical mechanics and similarity of nodes. In the proposed method, the similarity of nodes and the betweenness of nodes are both quantified. The proposed method considers the extent of dependence between neighbouring nodes. For some complex networks, the proposed structure entropy can distinguish complexity of that while other entropies can not be. Meanwhile, we construct five ER random networks and small-world networks and some real-world complex networks such as the US Air Lines networks, the GD'01-GD Proceedings Self-Citing networks, the Science Theory networks, the Centrality Literature networks and the Yeast networks are measured by the proposed method. The results illustrated our method for quantifying the complexity of complex networks is effective.

Porous spinel-structured Co3O4 nanowires partially substituted by Sn in tetrahedral sites (CSO) were grown on a multi-layered graphene film (CSO@GF) with a high specific surface area (SSA) through a simple and low-cost hydrothermal method, followed by a thermal annealing process. The as-synthesized binder-free CSO@GF electrode exhibited high specific capacitance (2032.6 F g−1 at 1 A g−1), superior rate capability (approximately 55.1% capacitance retention even at a current density of up to 40 A g−1), and remarkable cycling stability (94.3% capacitance retention after 10 000 cycles) due to significantly improved conductivity, which was further verified by density functional (DFT) calculations. A quasi-solid-state asymmetric supercapacitor (ASC) composed of the prepared CSO@GF and Fe2O3@GF as the positive and negative electrodes, respectively, was fabricated using a PVA-KOH gel electrolyte. The as-assembled supercapacitor delivered a prominent specific capacitance of 200.2 F g−1, an outstanding energy density of 62.6 W h kg−1 at a power density of 751.2 W kg−1, and an excellent cycling stability with 91.69% capacity retention after 10 000 cycles, suggesting great potential for CSO@GF in high energy density storage devices.

Monolithic all-perovskite tandem solar cells offer an avenue to increase power conversion efficiency beyond the limits of single-junction cells. It is an important priority to unite efficiency, uniformity and stability, yet this has proven challenging because of high trap density and ready oxidation in narrow-bandgap mixed lead–tin perovskite subcells. Here we report simultaneous enhancements in the efficiency, uniformity and stability of narrow-bandgap subcells using strongly reductive surface-anchoring zwitterionic molecules. The zwitterionic antioxidant inhibits Sn2+ oxidation and passivates defects at the grain surfaces in mixed lead–tin perovskite films, enabling an efficiency of 21.7% (certified 20.7%) for single-junction solar cells. We further obtain a certified efficiency of 24.2% in 1-cm2-area all-perovskite tandem cells and in-lab power conversion efficiencies of 25.6% and 21.4% for 0.049 cm2 and 12 cm2 devices, respectively. The encapsulated tandem devices retain 88% of their initial performance following 500 hours of operation at a device temperature of 54–60 °C under one-sun illumination in ambient conditions. Ensuring both stability and efficiency in mixed lead–tin perovskite solar cells is crucial to the development of all-perovskite tandems. Xiao et al. use an antioxidant zwitterionic molecule to suppress tin oxidation thus enabling large-area tandem cells with 24.2% efficiency and operational stability over 500 hours.

Very high power conversion efficiencies (PCEs) have been demonstrated by multijunction cells made of epitaxial III–V semiconductors; but they are too expensive to manufacture for terrestrial applic...

While mullite is a significant oxide ceramic material, its current preparation process has many limitations such as complicated process, low efficiency, and high cost. In this paper, directed laser deposition (DLD) was used to prepare mullite ceramics directly using α-Al2O3 and SiO2 powder as raw materials. The phase composition, microstructure, and primary defects of prepared samples were investigated by XRD, Raman spectroscopy, and SEM/EDS. Vickers indentation and three-point bending experiments were used to evaluate mechanical properties. The results showed that microstructure was mainly composed of a mullite crystal phase and Si-rich glass phase. It is shown that mullite ceramics were successfully synthesized in situ during the DLD process with the use of Al2O3 and SiO2 powder. Morphology of mullite crystal inside cylindrical sample was particular “tabular cellular,” which transformed into “rod cellular” at the edge. Two mullite crystals were arranged along deposition direction basically, surrounded by the Si-rich glass phase. The defects included pores with various sizes and crack, in which large pores were mainly distributed at the edge of the sample, and small pores were throughout the section. The crack was distributed in the center of the sample and spread to the edge. Mechanical properties test showed flexural strength, microhardness, and fracture toughness were 62.8 ± 30.3 MPa, 12.7 ± 0.34 GPa, and 1.84 ± 0.14 MPa·m1/2, respectively. It is considered that pores and crack were responsible for poor mechanical properties. This research is expected to provide a new option for the rapid preparation of mullite ceramics.

Slow kinetics of polysulfide conversion reactions lead to severe issues for lithium-sulfur (Li-S) batteries, for example, low rate capability, polysulfide migration, and low Coulombic efficiencies. These challenges hinder the practical applications of Li-S batteries. In this study, we proposed a rational strategy of tuning the d-band of catalysts to accelerate the conversion of polysulfides. Nitrogen vacancies were engineered in hexagonal Ni3N (space group P6322) to tune its d-band center, leading to the strong interaction between polysulfides and Ni3N. Because of the greater electron population in the lowest occupied molecular orbital of Li2S4, the terminal S-S bonds were weakened for breaking. Temperature-dependent experiments confirm that Ni3N0.85 demonstrates a much low activation energy, thereby accelerating the conversion of polysulfides. A Li-S cell using Ni3N0.85 can deliver a high initial discharge capacity of 1445.9 mAh g-1 (at 0.02 C) and low decay per cycle (0.039%). The Ni3N0.85 cell can also demonstrate an initial capacity of 1200.4 mAh g-1 for up to 100 cycles at a high loading of 5.2 mg cm-2. The high efficiency of rationally designed Ni3N0.85 demonstrates the effectiveness of the d-band tuning strategy to develop low-activation-energy catalysts and to promote the atomic understanding of polysulfide conversion in Li-S batteries.

Plasmonics enables the manipulation of light beyond the optical diffraction limit1–4 and may therefore confer advantages in applications such as photonic devices5–7, optical cloaking8,9, biochemical sensing10,11 and super-resolution imaging12,13. However, the essential field-confinement capability of plasmonic devices is always accompanied by a parasitic Ohmic loss, which severely reduces their performance. Therefore, plasmonic materials (those with collective oscillations of electrons) with a lower loss than noble metals have long been sought14–16. Here we present stable sodium-based plasmonic devices with state-of-the-art performance at near-infrared wavelengths. We fabricated high-quality sodium films with electron relaxation times as long as 0.42 picoseconds using a thermo-assisted spin-coating process. A direct-waveguide experiment shows that the propagation length of surface plasmon polaritons supported at the sodium–quartz interface can reach 200 micrometres at near-infrared wavelengths. We further demonstrate a room-temperature sodium-based plasmonic nanolaser with a lasing threshold of 140 kilowatts per square centimetre, lower than values previously reported for plasmonic nanolasers at near-infrared wavelengths. These sodium-based plasmonic devices show stable performance under ambient conditions over a period of several months after packaging with epoxy. These results indicate that the performance of plasmonic devices can be greatly improved beyond that of devices using noble metals, with implications for applications in plasmonics, nanophotonics and metamaterials. A thermo-assisted spin-coating process followed by packaging is used to fabricate sodium films that are stable for several months, enabling the realization of plasmonic devices with state-of-the-art performance at near-infrared wavelengths.

Developing novel and visible-light drive photocatalysts is a hot topic, and bismuth oxychloride is one of the popular photocatalysts. In this paper, a series of bismuth oxychloride were synthesized by ultrasonic-hydrothermal method with different ultrasonic time. By simply changing the ultrasonic time, we can control the morphology, structure, stoichiometry and photoelectric performance of bismuth oxychloride. The possible mechanism for the formation of BixOyCl photocatalysts involved the ultrasonic destruction of chemical bonds and increase of oxygen vacancy concentration, and the influence of ultrasonic on the pH during preparation. The sample of ultrasonic 30 min (U-30) showed the best photocatalytic activity due to the suitable morphology, structure, photoelectric performance, the formation of the heterostructure, and the presence of oxygen vacancies. For the removal of Rhodamine B (/Ciprofloxacin), the reaction rate constant for U-30 was 10.4 (/3.6), 4.9 (/1.6), 6.9 (/4.8), and 9.3 (/2.3) times that of the U-0, U-10, U-20, and U-40, respectively. Photoluminescence spectra showed that the photogenerated electron-hole recombination rate decreased gradually with the ultrasonic time. Further, the possible mechanism of photocatalytic process was investigated. This research provides a green, economical and simple method to modify bismuth oxychloride.

Summary The recent advancements in evaporating water using renewable energy provide one of the promising pathways for treating water with minimized carbon footprint. Pursuing a high evaporation rate of water has been the central focus of this field, as it is directly related to the throughput of evaporative water treatment. However, in conventional designs of evaporators, diffusion of vapor into the atmospheric environment has been the limiting step for evaporation. In this work, we demonstrate that a carbon foam with a three-dimensional interconnected porous structure enables sufficient diffusion of vapor with a convective flow and therefore realizes an evaporation rate as high as 10.9 kg m−2 h−1 and outdoor evaporation of 42.0 kg m−2 for continuous 13 h. With such a high evaporation rate achieved, it shows great promise toward a high-throughput, around-the-clock, and eco-friendly technology of evaporative wastewater disposal.

Summary Energy and clean water are two intertwined fundamental elements for human civilization and sustainable development. Here, we devise a monolithic tandem solar electricity-water generator that synergistically produces electricity and clean water by utilizing the full spectrum of solar irradiance. The tandem generator has two components: a top infrared-transparent photovoltaic device using above-band-gap photons, and a bottom solar water purifier using the below-band-gap photons. More strikingly, a well-designed water-proof thermal interconnecting layer (WTIL) makes these two components work synergistically: the bottom purifier serves as an evaporative cooler of the top solar cell to increase its efficiency, whereas the thermalization energy of the top cell is reutilized by the bottom purifier for producing more clean water. We experimentally demonstrate that a prototype hybrid tandem solar device with WTIL can generate electricity with a power output of 204 W m−2 and purify water at a rate of 0.80 kg m−2 h−1 under 1-sun illumination.

In this paper, we consider an energy-harvesting (EH) relay system consisting of a source, a destination, and multiple EH decode-and-forward (DF) relays that can harvest the energy from their received radio signals. A power-splitting ratio is employed at an EH DF relay to characterize a trade-off between an energy used for decoding the source signal received at the relay and the remaining energy harvested for retransmitting the decode outcome. We propose an optimal power splitting and relay selection (OPS-RS) framework and also consider the conventional equal power splitting and relay selection (EPS-RS) for comparison purposes. We derive closed-form expressions of outage probability for both the OPS-RS and EPS-RS schemes and characterize their diversity gains through an asymptotic outage analysis in the high signal-to-noise ratio region. We further examine an extension of our OPS-RS framework to an energy-harvesting battery (EHB) enabled cooperative relay scenario, where the EH relays are equipped with batteries used to store their harvested energies. We propose an amplify-and-forward (AF) based EHB-OPS-RS and a DF based EHB-OPS-RS schemes for AF and DF relay networks, respectively. Numerical results show that the proposed OPS-RS always outperforms the EPS-RS in terms of outage probability. Moreover, the outage probabilities of AF and DF based EHB-OPS-RS schemes are much smaller than that of OPS-RS and EPS-RS methods, demonstrating the benefit of exploiting the batteries in EH relays. Additionally, the DF based EHB-OPS-RS substantially outperforms the AF based EHB-OPS-RS and such an outage advantage becomes more significant, as the number of EH relays increases., Comment: 14 pages

In recent years, China’s environmental pollution is serious, manufacturing industry has become one of the main targets of government environmental regulation. This paper uses the SBM model to calculate efficiency value of 29 manufacturing industries from 2008 to 2017. The results show that the overall performance of environmental regulation in manufacturing industry is high (the average efficiency value is 0.7806), but it shows a declining trend. The efficiency of environmental regulation also varies widely. The government should consider focusing on the 11 industries with low SBM value in the next step to improve the performance of environmental regulation.

Measurements of the gas sensing performance of nanomaterials typically involve the use of interdigitated electrodes (IDEs). A separate heater is often integrated to provide elevated temperature for improved sensing performance. However, the use of IDEs and separate heaters increases fabrication complexity. Here, a novel gas sensing platform based on a highly porous laser-induced graphene (LIG) pattern is reported. The LIG gas sensing platform consists of a sensing region and a serpentine interconnect region. A thin film of metal (e.g., Ag) coated in the serpentine interconnect region significantly reduces its resistance, thereby providing a localized Joule healing in the sensing region (i.e., self-heating) during typical measurements of chemoresistive gas sensors. Dispersing nanomaterials with different selectivity in the sensing region results in an array to potentially deconvolute various gaseous components in the mixture. The self-heating of the LIG gas sensing platform is first studied as a function of the applied voltage during resistance measurement and LIG geometric parameters (e.g., linewidth from 120 to 240 μm) to achieve an operating temperature from 20 to 80 °C. Systematic investigations of various nanomaterials demonstrate the feasibility of the LIG gas sensing performance. Taken together with the stretchable design layout in the serpentine interconnect region to provide mechanical robustness over a tensile strain of 20%, the gas sensor with a significant response (6.6‰ ppm−1), fast response/recovery processes, excellent selectivity, and an ultralow limit of detection (1.5 parts per billion) at a modest temperature from self-heating opens new opportunities in epidermal electronic devices.

Two-photon fluorescent (TPF) probes, which allow imaging of biological events in a high spatiotemporal resolution, are in great demand. Recently, carbon quantum dots (CQDs) have emerged as a promising class of TPF probes. Unfortunately, the use of the existing CQDs has been limited by their weak TPF capacities. Herein, we report the first facile and large-scale synthesis of nitrogen-rich CQDs (NRCQDs) based on a donor-π-acceptor (D-π-A) strategy. The resulting NRCQDs demonstrated a tremendous TPF capacity with a two-photon absorption cross section (TPACS) and quantum yield (QY) up to 61 200 Göppert-Mayer (GM) units and 63%, respectively, which is greater than those that could be achieved by the existing TPF carbon probes. Structural and optical analyses of NRCQDs revealed that the great TPF capacity is contributed by the nitrogen-rich D-π-A structure as well as the high crystallinity, large plane, rigid, graphitic nitrogen-doped π-conjugated system. We further demonstrated that NRCQDs allow imaging of live cells as well as live liver tissues at depths of up to 440 μm. Our results suggest NRCQDs as a robust TPF probe that can be potentially used for a variety of biological applications.

A series of Schiff base diphenylamines (SDs) have been successfully prepared in a one-pot synthesis process. These novel antioxidants exhibit higher antioxidative activities than the traditional an...

We introduce a unified system for SCHOLAT to import information into Encyclopedia, called Semi-automatic Scholar Encyclopedia Generating System, which consists of four modules: website display page, backstage administration module, version comparison and website security module. Scholar Encyclopedia is implemented as a subsystem of Semi-automatic Scholar Encyclopedia Generating System. Scholar Encyclopedia is a scholar information website that has been independently compiled by the scholars and filled in by personal information. Scholar Encyclopedia Import Model consists of three modules: user evaluation, information import and manual review. At present, Semi-automatic Scholar Encyclopedia Generating System has been used, and the beta version of Scholar Encyclopedia has been deployed in our school network center. The online application shows that Scholar Encyclopedia Import Model has good accuracy and practicability.

Knowledge graphs have shown increasing importance in broad applications such as question answering, web search, and recommendation systems. The objective of knowledge graph embedding is to encode both entities and relations of knowledge graphs into continuous low-dimensional vector spaces to perform various machine learning tasks. Most of the existing works only focused on the local structure of knowledge graphs when utilizing structural information of entities, which may not sincerely preserve the global structure of knowledge graphs.In this paper, we propose a semi-supervised model by adopting graph convolutional networks to utilize both local and global structural information of entities. Specifically, our model takes textual information of each entity into consideration as entity attributes in the process of learning. We show the effectiveness of our model by applying it to two traditional tasks for knowledge graph: entity classification and link prediction. Experimental results on two well-known corpora reveal the advantages of this model compared to state-of-the-art methods on both tasks. Moreover, the results show that even with only 1% labeled data to train, our model can still achieve good performance.

Combining wide-bandgap and narrow-bandgap perovskites to construct monolithic all-perovskite tandem solar cells offers avenues for continued increases in photovoltaic (PV) power conversion efficiencies (PCEs). However, actual efficiencies today are diminished by the subpar performance of narrow-bandgap subcells. Here we report a strategy to reduce Sn vacancies in mixed Pb–Sn narrow-bandgap perovskites that use metallic tin to reduce the Sn4+ (an oxidation product of Sn2+) to Sn2+ via a comproportionation reaction. We increase, thereby, the charge-carrier diffusion length in narrow-bandgap perovskites to 3 μm for the best materials. We obtain a PCE of 21.1% for 1.22-eV narrow-bandgap solar cells. We fabricate monolithic all-perovskite tandem cells with certified PCEs of 24.8% for small-area devices (0.049 cm2) and of 22.1% for large-area devices (1.05 cm2). The tandem cells retain 90% of their performance following 463 h of operation at the maximum power point under full 1-sun illumination. Improvements in the efficiency and stability of low-bandgap perovskite solar cells are key to enabling all-perovskite solar cells. Here, Lin et al. use metallic tin to prevent oxidation in such low-gap perovskite and demonstrate 24.8%-efficient tandems that are stable for over 400 h under operating conditions.

In this paper, we investigate physical-layer security for a heterogeneous cellular network consisting of a macro cell and a small cell in the presence of a passive eavesdropper that intends to tap both the macro-cell and small-cell transmissions. Both the orthogonal spectrum sharing (OSS) and non-orthogonal spectrum sharing (NOSS) are considered for the heterogeneous cellular network. The OSS allows the macro cell and small cell to access a given spectrum band in an orthogonal manner, whereas the NOSS enables them to access the same spectrum simultaneously and mutual interference exits. As a consequence, we present two NOSS schemes, namely the interference-limited NOSS (IL-NOSS) and interference-canceled NOSS (IC-NOSS), where the mutual interference is constrained below a tolerable level in the IL-NOSS through power control and the IC-NOSS scheme exploits a specially-designed signal for canceling out the interference received a legitimate cellular user while confusing the passive eavesdropper. We derive closed-form expressions for an overall secrecy outage probability of the OSS, IL-NOSS, and IC-NOSS schemes, which take into account the transmission secrecy of both the macro cell and small cell. We further characterize the secrecy diversity of OSS, IL-NOSS and IC-NOSS schemes through an asymptotic secrecy outage analysis in the high signal-to-noise ratio region. It is shown that the OSS and IL-NOSS methods obtain the same secrecy diversity gain of zero only, and a higher secrecy diversity gain of one is achieved by the IC-NOSS scheme. Additionally, numerical results demonstrate that the IC-NOSS scheme significantly performs better than the OSS and IL-NOSS methods in terms of the overall secrecy outage probability., 32 pages

Recent advances in the development of advanced solar evaporation have opened up new possibilities for the revived explorations of solar thermal utilization. Among them, microstructure-enabled solar evaporation received the most attention due to its unique capability of solar energy harvesting and localized heating effects, which are beneficial for an enhanced vapor production rate, a fast-responsive high-temperature steam generation, and so on. Here we review the primary photothermal properties of interfacial solar evaporators and the recent progress in potential point-of-use applications of solar desalination, solar sterilization as well as enthalpy-recycled power generation. A brief summary and prospective analysis have been discussed as well.

A cobalt sulfide (CoS)/graphene sheets (GS) nanocomposite was successfully synthesized through a simple one-pot hydrothermal route assisted by ethylenediamine. The crystalline phase, structure and morphology of this nanocomposite were systematically characterized via X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), nitrogen (N₂) absorption-desorption isotherm, Raman spectroscopy and thermogravimetric analysis (TGA). The results revealed that the CoS nanoparticles with size distribution of 30-100 nm were highly dispersed on or well anchored in the creasy GS substrate. Integrating nanosized CoS compound and GS outstanding merits, the as-obtained CoS/GS nanocomposite as an anode material for lithiumion battery exhibited high reversible capacity, excellent long-cycle stability and remarkable high-rate capability, which were all superior to those of pristine CoS. Moreover, this nanocomposite maintained a high capacity of ˜600 mAh·g-1 after 200 cycles at a current density of 100 mA·g-1. The approach presented in this work is readily applicable to nanoparticle decoration of graphene sheets and preparation of other graphene-based nanocomposites as anode materials for lithium-ion batteries.

Xiuqiang Li obtained his PhD at College of Engineering and Applied Sciences, Nanjing University. Currently, he is a postdoc at Duke University. His research focuses on solar energy conversion and nanoscale heat transfer. George Ni is a research scientist at Lincoln Laboratory, Massachusetts Institute of Technology. He obtained his PhD in mechanical engineering at Massachusetts Institute of Technology. His research focuses on solar energy conversion. Thomas Cooper is an assistant professor at York University. He received his PhD and MSc from ETH Zurich in 2014 and 2010, respectively, and his BASc from the University of Toronto in 2008, all in mechanical engineering. His research focuses on solar energy and converting it into useful forms. Ning Xu, Jinlei Li, and Pengcheng Yao are PhD students at College of Engineering and Applied Sciences, Nanjing University. Their research focuses on solar energy conversion. Xiaozhen Hu and Bin Zhu are research scientists at College of Engineering and Applied Sciences, Nanjing University. Lin Zhou is an associate Professor at College of Engineering and Applied Sciences, Nanjing University. Their research focuses on solar energy conversion. Jia Zhu is a Professor at College of Engineering and Applied Sciences, Nanjing University. He obtained his bachelor’s degree in physics at Nanjing University and received his MS and PhD in electrical engineering from Stanford University. He worked as a postdoctoral fellow at University of California, Berkeley and Lawrence Berkeley National Lab. His scientific research interest is in the area of nanomaterials, nanophotonics and nanoscale heat transfer.

The charge-transport properties of charge-transfer complexes (CTCs) play a key role in the potential applications toward novel optoelectronic devices. We have systematically studied the charge-transport properties of perylene-F4TCNQ CTCs with different stoichiometric ratios by first-principles calculations. Our calculated results showed that 1P1F4 (perylene-F4TCNQ 1:1) exhibits a higher charge-carrier mobility than 3P2F4 (perylene-F4TCNQ 3:2) due to the strong interlayer interactions in 3P2F4. Compared with the perylene-TCNQ CTC, the higher charge-carrier mobility in perylene-F4TCNQ CTC indicates that introducing fluorine atoms can enhance the charge-carrier mobility due to stronger intermolecular interactions. More importantly, the experimental measurements carried out with 1P1F4- and 3P2F4-based field-effect transistors are consistent with the theoretical predictions. Our study reveals that tuning the charge-transport properties in CTCs by controlling the stoichiometry between the donor and acceptor is a promising strategy in accelerating the development of high-performance organic electronic materials.

Modeling the interests of authors over time from documents has important applications in broad applications such as recommendation systems, authorship identification and opinion extraction. In this paper, we propose an Ordering-sensitive and Semantic-aware Dynamic Author Topic Model (OSDATM), which monitors the evolution of author interest in time-stamped documents. The model further uses the discovered author interest information to discover better topics. Unlike traditional topic models, OSDATM is sensitive to the ordering of words, thus it extracts more information from the semantic meaning of the context. The experimental results show that OSDATM learns better topics than state-of-the-art topic models. In addition, the dynamic interests of authors that the OSDATM model discovers are interpretable and consistent with the truth.

Plasmonic nanostructures with strong light-matter interactions have been intensively explored in the past decades. The plasmonic photothermal effect has garnered significant research interest and triggered plenty of applications, such as photothermal therapy, photothermal imaging, and photocatalysis. Recently, plasmonic nanostructures are emerging as one of the most exciting candidates for solar vapor generation, inspiring the revival of solar-thermal-based water purification technologies. Here we present a review of state-of-the-art plasmonic-enhanced solar evaporation, including the theoretical background, various designs of plasmonic materials and structures, and their potential applications. The current challenges and future perspective are outlined as well.

Nowadays, water shortage has become an ever-increasing severe problem for human beings. Lately, there has been exciting progress in two different ways for desalination, namely, interfacial solar evaporation and film filtration. Graphene oxide based film is playing a critical role in both developments due to its high absorption, porous structure, high chemical stability, hydrophilicity, and excellent anti-fouling properties. In this works, we first introduce the mechanisms and key requirements for interfacial solar evaporation and filtration based desalination, and then explain how various forms of graphene oxide can be tailored for both types of desalination. Then, we summarize and discuss recent researches concerning both relevant technology advances and persisting problems, and finally provide a prospective view.

In the last decades, many similarity measures are proposed, such as Jaccard coefficient, cosine similarity, BM25, language model, etc. Despite the effectiveness of the existing similarity measures, we observe that none of them can consistently outperform the others in most typical situations. Choosing which similarity predicate to use is usually treated as an empirical question by evaluating a particular task with a number of different similarity predicates, which is not computationally efficient and the obtained results are not portable. In this paper, we propose a novel approach to combine different similarity predicates together to form a committee so that we do not need to worry about choosing which of them to use. Empirically, we can obtain a better result than any individual similarity predicate, which is quite meaningful in practice. Specifically, our method models the problem of committee generation as a 0–1 integer programming problem based on the confidence of similarity predicates and the reliability of attributes. We demonstrate the effectiveness of our model by applying it on three datasets with controlled errors. Experimental results demonstrate that our similarity predicate committee is more robust and superior over existing individual similarity predicates.

Community question answering (CQA) is an important but challenging task. Meantime, as the theory of deep learning develops, remarkable progress has been made by deep neural networks. This paper studies an advanced deep neural network that not only uses external knowledge to learn better representations of questions and answers but also improves representation learning by considering question categorization as an auxiliary task. Specifically, we propose a novel Multi-task and Knowledge enhanced Multi-head Interactive Attention network for Community Question Answering (MKMIA-CQA). It contains a document modeling module responsible for utilizing external commonsense knowledge to help identify background information (entity mentions and their relations) and filter out noise information from the long text which has complicated semantic and syntactic structures. Moreover, the model is trained in a multi-task manner. It regards community question answering as the primary task and question categorization as the auxiliary task, which aims to learn a category-aware encoder and improve the quality of locating the salient information of a long question. The experimental results on three widely used CQA datasets demonstrate that our model achieves impressive results compared to other strong competitors.

A 8-hydroxylquinoline-benzothiazole conjugate (HQ-BT) was facilely synthesized by two steps with >60% total reaction yield. The HQ-BT showed a weak fluorescence that could be strongly enhanced by coordination with various metal ions such as Al3+, Cd2+, Zn2+ in methanol containing 1% water. Interestingly, the selectivity toward Cd2+ was achieved by increasing water fraction to 30% aqueous methanol solution. Thus, the HQ-BT was developed as a new and selective fluorescent chemosensor for Cd2+ in aqueous solution with a broad pH region 4–12. A good linear relationship between the fluorescence intensity and the Cd2+ concentration was found in the range of 0–5 μM with a detection limit of 0.1 μM (S/N = 3). It was also succesfully used for fluorescence imaging of Cd2+ in living cells.

Fe3O4–Fe–C nanosheets composed of nanopores with an average size of 9.1 nm and ~ 60 nm thicked carbon nanosheets inlaid homogenously with ~ 13.4 nm Fe3O4–Fe nanocrystals are successfully prepared via a facile solvothermal process and a subsequent annealing treatment. These porous Fe3O4–Fe–C nanosheets used as catalytic-type anode material for lithium-ion batteries exhibit a high reversible capacity of 1041.3 mAh g−1, 88.0% of the second cycle discharge capacity after 200 cycles at 1 A g−1, and a high-rate delivery of 820.0 mAh g−1 after 500 cycles at 6 A g−1. The superior performance of Fe3O4–Fe–C nanosheets was attributed to the catalytic effect of Fe nanoparticles on the electrochemical activity of Fe3O4. These results revealed the potential applications of Fe3O4–Fe–C nanostructure materials as catalytic-type anodes for high-rate LIBs.

Wireless technology plays a critical role in the development of flexible and stretchable electronics due to the increasing demand for compactness, portability, and level of comfort. As an important candidate in wireless technology, microstrip antennas have recently been explored for flexible and stretchable electronics. However, the stretchable characteristics of the microstrip antenna typically come at the cost of reduced electrical conductivity and radiation efficiency. By utilizing a soft silicone substrate and the structural design of the conventional metallic materials for both patch and ground plane in the microstrip antennas, we have demonstrated two designs of stretchable microstrip antennas: "meshed microstrip antenna" and "arched microstrip antenna". The former exploits initially wavy structures from patterning, and the latter also uses the deformed wavy structures created from the prestrain strategy. In comparison to their solid microstrip antenna counterpart, the radiation properties of the resulting stretchable microstrip antennas do not change much. Meanwhile, the resonance frequency decreases with the externally applied tensile strain along the feeding direction in the design of the meshed microstrip antenna but increases with the increasing strain in the design of the arched microstrip antenna. The change in the resonance frequency with the externally applied tensile strain in the latter design has a high sensitivity, manifesting a 3.35- and a 1.49-fold increase of sensitivity when compared to those in previous reports that used silver nanowire- or liquid-metal-based stretchable microstrip antennas. Considering the high sensitivity and compliant characteristic of the stretchable microstrip antenna, we have demonstrated an arched microstrip antenna-based strain sensor that is capable of detecting the motion of human wrists with high sensitivity, little hysteresis, and possible wireless communication.

A cobalt sulfide decorated reduced graphene oxide (CoS/rGO) nanocomposite was successfully synthesized via a facile one-step hydrothermal route assisted by ethylenediamine. The crystalline phase, structure and morphology of the products were systematically characterized by x-ray diffraction, transmission electron microscopy, scanning electron microscopy, x-ray photoelectron spectroscopy, nitrogen (N2) absorption–desorption isotherm, Raman spectra and thermogravimetric analysis. The results show that CoS nanoparticles with the size of 30–100 nm are well dispersed on or anchored in the creasy rGO sheets substrate. Combining the CoS compound nature with the rGO outstanding characteristics, the as-obtained CoS/rGO as an electrode for a supercapacitor harvests high specific capacitance, excellent long-cycle stability and remarkable high-rate capability, which are all superior to those of pristine CoS. Importantly, this nanocomposite possesses a specific capacitance of 813 F g−1 at 0.5 A g−1 (about 2 times that of pure CoS) and excellent cycling stability with 91.2% capacitance retention after 1000 repetitive charge–discharge cycles. It is noteworthy that this approach can be readily applicable to the nanoparticle decoration of graphene sheets and the preparation of other graphene-based nanocomposites for supercapacitors.

Despite that neural networks have demonstrated their good potential to be used in constructing learners which exhibit strong predictive performance, there are still some uncertainty issues that can greatly affect the effectiveness of the employed supervised learning algorithms, such as class imbalance and labeling errors (or class noise). Technically, imbalanced data resource can cause more difficulties or limitations for learning algorithms to distinguish different classes, while data with labeling errors can lead to an unreasonable problem formulation due to incorrect hypotheses. Indeed, noise and class imbalance are pervasive problems in the domain of educational data analytics. This study aims at developing improved randomized learning algorithms by investigating a novel type of cost function that focuses on the combined effects of class imbalance and class noise. Instead of concerning these uncertainty issues isolation, we present a convex combination of robust and imbalanced modelling objectives, contributing to a generalized formulation of weighted least squares problems by which the improved randomized learner models can be built. Our experimental study on several educational data classification tasks have verified the advantages of our proposed algorithms, in comparison with some existing methods that either takes no account of class imbalance and labeling errors, or merely consider one specific aspect in problem-solving.

Modulating the charge distribution over the carbon skeleton via heteroatom doping is critical for creating active centres for efficient metal-free electrocatalysts. However, effective approaches to precisely control heteroatom co-doping to guide catalytic activities are still lacking. Herein, a P and N-coordinated fullerene-like carbon (N,P-FC) multi-functional catalyst was constructed via a facile soft-template pyrolysis method, which achieves impressive activity for the electrochemical reduction of CO2 to CO (CO2RR, 83.3% faradaic efficiency for CO (FECO), a high current density of ∼24 mA cm−2 at −0.8 V), along with high selectivity and long-term stability. The activity of N,P-FC for CO2RR is strongly dependent on the P/N atomic ratio. Also, N,P-FC possesses an impressive oxygen reduction reaction (ORR) performance with a half-wave overpotential (E1/2) of 0.910 V, 79 mV higher than that of commercial Pt/C, and it outperforms all documented carbon-based electrocatalysts. Combined theoretical calculation studies suggest that the P-coordinated C site is more active for CO2RR, while the N-coordinated neighboring C site is responsible for ORR in this catalyst. This work highlights a new concept for modulating surface charge redistribution by heteroatom co-doping and morphology control toward designing efficient and low-cost electrocatalysts.

With the broad adoption of the global positioning system-enabled devices, the massive amount of trajectory data is generated every day, which results in meaningful traffic patterns. This study aims to predict the future state of road traffic instead of merely showing the current traffic condition. First, we use a clustering method to group similar trajectories of a particular period together into a cluster for each road. Second, for each cluster, we average the lengths and angles of the entire trajectories in the group as the representative trajectory, which is regarded as the road pattern. Third, we create a feature vector for each road based on its historical traffic conditions and neighbor road patterns. Finally, we design a recurrent convolutional neural network for modeling the complex nonlinear relationship among features to predict road traffic conditions. Experimental results show that our approach performs more favorably compared with several traditional machine learning and state-of-the-art algorithms.

The water and energy sectors of an economy are inextricably linked. Energy is required in water production, distribution, and recycling, while water is often used for energy generation. In many geographical locations, the energy-water nexus is exacerbated by the shortage of both fresh water resources and energy generation infrastructure. New materials, including metamaterials, are now emerging to address the challenges of providing renewable energy and fresh water, especially to off-the-grid communities struggling with water shortages. Novel nanomaterials have fueled recent technology breakthroughs in solar water desalination, fog and dew collection, and cloud seeding. Materials for passive thermal management of buildings and individuals offer promising strategies to reduce the use of energy and water for heating and cooling. While many challenges remain, emerging materials and technologies improve sustainable management of water and energy resources.

Lithium is considered to be a promising anode material for high-energy batteries on account of its high capacity and low potential. However, both dendritic lithium formation and very large volume changes during cycling severely restrict its practical applications. Herein, we propose a 3D hollow reduced graphene oxide foam as a host for prestoring lithium. Aside from the advantages of accommodating volume change and lowering the local current density, this unique structure also provides a large host space, one that enables lithium prestorage both outside and inside the reduced graphene oxide, in which Li occupies ∼85 weight percent of the whole composite electrode. The anode showed a corresponding gravimetric specific capacity as high as 3280 mA h g−1. Moreover, it showed highly stable cycling with small hysteresis at 1 mA cm−2 in the carbonate electrolyte. When it was assembled into a full cell with NCM (Li(Ni1/3Co1/3Mn1/3)O2) as the cathode, the resulting battery showed good cycling performance, having displayed 92% capacity retention (128.2 mA h g−1) and appealing power capacity (82 mA h g−1 at 5C) after being cycled 200 times at 0.3C.

As a ubiquitous solar-thermal energy conversion process, solar-driven evaporation has attracted tremendous research attention owing to its high conversion efficiency of solar energy and transformative industrial potential. In recent years, solar-driven interfacial evaporation by localization of solar-thermal energy conversion to the air/liquid interface has been proposed as a promising alternative to conventional bulk heating-based evaporation, potentially reducing thermal losses and improving energy conversion efficiency. In this Review, we discuss the development of the key components for achieving high-performance evaporation, including solar absorbers, evaporation structures, thermal insulators and thermal concentrators, and discuss how they improve the performance of the solar-driven interfacial evaporation system. We describe the possibilities for applying this efficient solar-driven interfacial evaporation process for energy conversion applications. The exciting opportunities and challenges in both fundamental research and practical implementation of the solar-driven interfacial evaporation process are also discussed. The thermal properties of solar energy can be exploited for many applications, including evaporation. Tao et al. review recent developments in the field of solar-driven interfacial evaporation, which have enabled higher-performance structures by localizing energy conversion to the air/liquid interface.

Chemical and physical properties of silver nanoparticles (Ag NPs) are strongly influenced by NP size. The control of NP size is crucial for tuning or enhancing the properties of Ag NPs. In this paper, the size controlled Ag NPs have been achieved and dispersed on graphene (GE) sheets (Ag NPs/GE) using an eco-friendly and environment-friendly approach of thermal annealing method. The formation of size controlled Ag NPs has been restrained and it includes two stages. One is the formation of metallic Ag by reduction of Ag+ at low temperature (below 400 °C), wherein the ultrafine and highly dispersed Ag NPs can be obtained; another is growth and aggregation of Ag NPs at high temperature due to increasing surface diffusion coefficient of Ag atoms (above 400 °C). The Ag NPs/GE-400 presented an excellent antimicrobial activity due to the ultrafine size (∼9.6 nm), while the Ag NPs/GE-700 exhibited an excellent SERS activity and sensitivity because of the appreciate size (∼95.8 nm). The Ag NPs/GE-500 (∼25.3 nm) presented the modest antimicrobial and SERS properties. Thus, our work may provide a reference to synthesize size-selected Ag NPs-based materials with a certain application using the thermal annealing method.

Summary In this work, it is shown that by storing and recycling steam enthalpy derived from the solar steam process, we can enable simultaneous generation of clean water and electricity. Energy-transfer efficiency of solar to steam can reach 72.2% with extra electricity power (with 1.23% efficiency) generated simultaneously. With advanced thermal management to further elevate the working temperature and exciting progress in the fields of thermoelectrics and desalination, it is expected that the performance of this system can be further improved. This approach with scalable materials and processes, high energy-transfer efficiency, and integrated storage capability will provide an attractive avenue to produce electricity and clean water in an individualized manner, particularly desirable in various off-grid areas.

Highlights The “ordered-unraveling” of hierarchical structures from mechanical assembly contributes to not only the improved overall stretchability, but also the small resonance shift of the stretchable microstrip antenna upon stretching.The mechanical-electromagnetic properties of stretchable microstrip antennas can be controlled by changing the number of arches in the meshed patch.A double-arched microstrip antenna was demonstrated to communicate wirelessly upon 25% stretching or when being placed on human bodies. Supplementary Information The online version contains supplementary material available at (10.1007/s40820-021-00631-5)., As the key component of wireless data transmission and powering, stretchable antennas play an indispensable role in flexible/stretchable electronics. However, they often suffer from frequency detuning upon mechanical deformations; thus, their applications are limited to wireless sensing with wireless transmission capabilities remaining elusive. Here, a hierarchically structured stretchable microstrip antenna with meshed patterns arranged in an arched shape showcases tunable resonance frequency upon deformations with improved overall stretchability. The almost unchanged resonance frequency during deformations enables robust on-body wireless communication and RF energy harvesting, whereas the rapid changing resonance frequency with deformations allows for wireless sensing. The proposed stretchable microstrip antenna was demonstrated to communicate wirelessly with a transmitter (input power of − 3 dBm) efficiently (i.e., the receiving power higher than − 100 dBm over a distance of 100 m) on human bodies even upon 25% stretching. The flexibility in structural engineering combined with the coupled mechanical–electromagnetic simulations, provides a versatile engineering toolkit to design stretchable microstrip antennas and other potential wireless devices for stretchable electronics. Supplementary Information The online version contains supplementary material available at (10.1007/s40820-021-00631-5).

Cobalt sulphide/graphene aerogel nanocomposite (CGA) is successfully fabricated via a one-pot hydrothermal approach aided with ethylenediamine. CoS nanoparticles constructed by nanoplates are uniformly anchored and well distributed on the loose graphene aerogel framework. Owing to a synergistic effect combining nanosized CoS with graphene aerogel advantages, CGA as an anode material for lithium energy storage exhibits high reversible capacity, superior long-cycle property and excellent high-rate capability. Prominently, CGA maintains a high capacity approaching ~1100 mAh g−1 after 200 cycles at 100 mA g−1. Even at 1 A g−1, CGA still delivers a capacity of 460 mAh g−1. This approach can be readily applicable to prepare other graphene aerogel-based nanocomposites as anode materials.

Tetrabromodiphenyl ether (BDE-47) is widely used as commercial flame retardants that can be released into the environment and finally enter human body through the food chain. It has been identified to generate neurotoxicity, but little is known about auditory damage and the underlying mechanism following BDE-47 exposure. This study aimed to assess the cell viability with BDE-47 concentration ranging from 0 to 150 μM in mouse organ of Corti-derived cell lines (HEI-OC1). Aryl hydrocarbon receptor (AhR) as an environmental sensor, reactive oxygen species (ROS), NLRP3 inflammasome and p38 MAPK pathways were detected. Results: (1) BDE-47 inhibited the viability in a time- and dose-dependent way in HEI-OC1 cells. Cell cycle was arrested in G1 phase by BDE-47; (2) Elevated intracellular ROS, LDH levels and necrosis were found, which was alleviated by pretreatment with ROS scavenger N-acetylcysteine (NAC); (3) AhR plays an essential role in ligand-regulated transcription factor activation by exogenous environmental compounds. We found increased expression of AhR and decreased downstream targets of CYP 1A1 and CYP 1B1 in BDE-47-treated HEI-OC1 cells, which was reversed by the AhR antagonist CH-223191 for 2 h before BDE-47 exposure. No significant change was detected in CYP 2B; (4) Enhanced expressions of NLRP3 and caspase-1 were induced by BDE-47, with up-regulations of both pro-inflammatory factors for IL-1β, IL-6 and TNF-α, and anti-inflammatory factors for IL-4, IL-10 and IL-13, but down-regulation for IL-1α; (5) Additionally, the p38 MAPK signaling pathway was activated with increased phosphorylation levels of MKK/3/6, p38 MAPK and NF-kB. Overall, our findings illustrate a role of AhR in ROS-induced necrosis of cochlear hair cells by BDE-47 exposure, in which NLRP3 inflammasome and p38 MAPK signaling pathways are activated. The current study first elucidates the sense of hearing damage induced by BDE-47, and cell-specific or mixture exposures in vivo or human studies are needed to confirm this association.

Micro/nanodevices have been widely applied for the real-time monitoring of intracellular activities and the delivery of exogenous substances in the past few years. This review focuses on miniaturized micro/nanodevices for assessment and treatment in stomatology and ophthalmology. We first summarize the recent progress in this field by examining the available materials and fabrication techniques, device design principles, mechanisms, and biosafety aspects of micro/nanodevices. Following a discussion of biochemical sensing technology from the cellular level to the tissue level for disease assessment, we then summarize the use of microneedles and other micro/nanodevices in the treatment of oral and ocular diseases and conditions, including oral cancer, eye wrinkles, keratitis, and infections. Along with the identified key challenges, this review concludes with future directions as a small fraction of vast opportunities, calling for joint efforts between clinicians and engineers with diverse backgrounds to help facilitate the rapid development of this burgeoning field in stomatology and ophthalmology.

There has been a persistent effort to understand and control the incorporation of metal impurities in semiconductors at nanoscale, as it is important for semiconductor processing from growth, doping to making contact. Previously, the injection of metal atoms into nanoscaled semiconductor, with concentrations orders of magnitude higher than the equilibrium solid solubility, has been reported, which is often deemed to be detrimental. Here our theoretical exploration reveals that this colossal injection is because gold or aluminum atoms tend to substitute Si atoms and thus are not mobile in the lattice of Si. In contrast, the interstitial atoms in the Si lattice such as manganese (Mn) are expected to quickly diffuse out conveniently. Experimentally, we confirm the self-inhibition effect of Mn incorporation in nanoscaled silicon, as no metal atoms can be found in the body of silicon (below 10(17) atoms per cm(−3)) by careful three-dimensional atomic mappings using highly focused ultraviolet-laser-assisted atom-probe tomography. As a result of self-inhibition effect of metal incorporation, the corresponding field-effect devices demonstrate superior transport properties. This finding of self-inhibition effect provides a missing piece for understanding the metal incorporation in semiconductor at nanoscale, which is critical not only for growing nanoscale building blocks, but also for designing and processing metal–semiconductor structures and fine-tuning their properties at nanoscale.