Showing papers by "South China University of Technology published in 2017"

Zn/MnO2 Battery Chemistry With H+ and Zn2+ Coinsertion

Abstract: Rechargeable aqueous Zn/MnO2 battery chemistry in a neutral or mildly acidic electrolyte has attracted extensive attention recently because all the components (anode, cathode, and electrolyte) in a Zn/MnO2 battery are safe, abundant, and sustainable. However, the reaction mechanism of the MnO2 cathode remains a topic of discussion. Herein, we design a highly reversible aqueous Zn/MnO2 battery where the binder-free MnO2 cathode was fabricated by in situ electrodeposition of MnO2 on carbon fiber paper in mild acidic ZnSO4+MnSO4 electrolyte. Electrochemical and structural analysis identify that the MnO2 cathode experience a consequent H+ and Zn2+ insertion/extraction process with high reversibility and cycling stability. To our best knowledge, it is the first report on rechargeable aqueous batteries with a consequent ion-insertion reaction mechanism.

Diverse Applications of Nanomedicine

Abstract: The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.

MoS2–Ni3S2 Heteronanorods as Efficient and Stable Bifunctional Electrocatalysts for Overall Water Splitting

Abstract: Exploring noble-metal-free electrocatalysts with high efficiency for both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) holds promise for advancing the production of H2 fuel through water splitting. Herein, one-pot synthesis was introduced for MoS2–Ni3S2 heteronanorods supported by Ni foam (MoS2–Ni3S2 HNRs/NF), in which the Ni3S2 nanorods were hierarchically integrated with MoS2 nanosheets. The hierarchical MoS2–Ni3S2 heteronanorods allow not only the good exposure of highly active heterointerfaces but also the facilitated charge transport along Ni3S2 nanorods anchored on conducting nickel foam, accomplishing the promoted kinetics and activity for HER, OER, and overall water splitting. The optimal MoS2–Ni3S2 HNRs/NF presents low overpotentials (η10) of 98 and 249 mV to reach a current density of 10 mA cm–2 in 1.0 M KOH for HER and OER, respectively. Assembled as an electrolyzer for overall water splitting, such heteronanorods show a quite low cell voltage of 1.50 V at 10 mA...

Removing Rain from Single Images via a Deep Detail Network

Abstract: We propose a new deep network architecture for removing rain streaks from individual images based on the deep convolutional neural network (CNN). Inspired by the deep residual network (ResNet) that simplifies the learning process by changing the mapping form, we propose a deep detail network to directly reduce the mapping range from input to output, which makes the learning process easier. To further improve the de-rained result, we use a priori image domain knowledge by focusing on high frequency detail during training, which removes background interference and focuses the model on the structure of rain in images. This demonstrates that a deep architecture not only has benefits for high-level vision tasks but also can be used to solve low-level imaging problems. Though we train the network on synthetic data, we find that the learned network generalizes well to real-world test images. Experiments show that the proposed method significantly outperforms state-of-the-art methods on both synthetic and real-world images in terms of both qualitative and quantitative measures. We discuss applications of this structure to denoising and JPEG artifact reduction at the end of the paper.

A Two-Dimensional Lamellar Membrane: MXene Nanosheet Stacks

Abstract: Two-dimensional (2D) materials are promising candidates for advanced water purification membranes. A new kind of lamellar membrane is based on a stack of 2D MXene nanosheets. Starting from compact Ti3AlC2, delaminated nanosheets of the composition Ti3C2Tx with the functional groups T (O, OH, and/or F) can be produced by etching and ultrasonication and stapled on a porous support by vacuum filtration. The MXene membrane supported on anodic aluminum oxide (AAO) substrate shows excellent water permeance (more than 1000 L m−2 h−1 bar−1) and favorable rejection rate (over 90 %) for molecules with sizes larger than 2.5 nm. The water permeance through the MXene membrane is much higher than that of the most membranes with similar rejections. Long-time operation also reveals the outstanding stability of the MXene membrane for water purification.

Observation of topological valley transport of sound in sonic crystals

Abstract: Valleytronics — exploiting a system’s pseudospin degree of freedom — is being increasingly explored in sonic crystals. Now, valley transport of sound is reported for a macroscopic triangular-lattice array of rod-like scatterers in a 2D air waveguide.

Index Modulation Techniques for Next-Generation Wireless Networks

Abstract: What is index modulation (IM)? This is an interesting question that we have started to hear more and more frequently over the past few years. The aim of this paper is to answer this question in a comprehensive manner by covering not only the basic principles and emerging variants of IM, but also reviewing the most recent as well as promising advances in this field toward the application scenarios foreseen in next-generation wireless networks. More specifically, we investigate three forms of IM: spatial modulation, channel modulation and orthogonal frequency division multiplexing (OFDM) with IM, which consider the transmit antennas of a multiple-input multiple-output system, the radio frequency mirrors (parasitic elements) mounted at a transmit antenna and the subcarriers of an OFDM system for IM techniques, respectively. We present the up-to-date advances in these three promising frontiers and discuss possible future research directions for IM-based schemes toward low-complexity, spectrum- and energy-efficient next-generation wireless networks.

Mussel-Inspired Adhesive and Tough Hydrogel Based on Nanoclay Confined Dopamine Polymerization.

Abstract: Adhesive hydrogels are attractive biomaterials for various applications, such as electronic skin, wound dressing, and wearable devices. However, fabricating a hydrogel with both adequate adhesiveness and excellent mechanical properties remains a challenge. Inspired by the adhesion mechanism of mussels, we used a two-step process to develop an adhesive and tough polydopamine-clay-polyacrylamide (PDA-clay-PAM) hydrogel. Dopamine was intercalated into clay nanosheets and limitedly oxidized between the layers, resulting in PDA-intercalated clay nanosheets containing free catechol groups. Acrylamide monomers were then added and in situ polymerized to form the hydrogel. Unlike previous single-use adhesive hydrogels, our hydrogel showed repeatable and durable adhesiveness. It adhered directly on human skin without causing an inflammatory response and was easily removed without causing damage. The adhesiveness of this hydrogel was attributed to the presence of enough free catechol groups in the hydrogel, which we...

Multisensor Feature Fusion for Bearing Fault Diagnosis Using Sparse Autoencoder and Deep Belief Network

Abstract: To assess health conditions of rotating machinery efficiently, multiple accelerometers are mounted on different locations to acquire a variety of possible faults signals. The statistical features are extracted from these signals to identify the running status of a machine. However, the acquired vibration signals are different due to sensor’s arrangement and environmental interference, which may lead to different diagnostic results. In order to improve the fault diagnosis reliability, a new multisensor data fusion technique is proposed. First, time-domain and frequency-domain features are extracted from the different sensor signals, and then these features are input into multiple two-layer sparse autoencoder (SAE) neural networks for feature fusion. Finally, fused feature vectors can be regarded as the machine health indicators, and be used to train deep belief network (DBN) for further classification. To verify the effectiveness of the proposed SAE-DBN scheme, the bearing fault experiments were conducted on a bearing test platform, and the vibration data sets under different running speeds were collected for algorithm validation. For comparison, different feature fusion methods were also applied to multisensor fusion in the experiments. Experimental results demonstrated that the proposed approach can effectively identify the machine running conditions and significantly outperform other fusion methods.

A Mussel-Inspired Conductive, Self-Adhesive, and Self-Healable Tough Hydrogel as Cell Stimulators and Implantable Bioelectronics.

Abstract: A graphene oxide conductive hydrogel is reported that simultaneously possesses high toughness, self-healability, and self-adhesiveness. Inspired by the adhesion behaviors of mussels, our conductive hydrogel shows self-adhesiveness on various surfaces and soft tissues. The hydrogel can be used as self-adhesive bioelectronics, such as electrical stimulators to regulate cell activity and implantable electrodes for recording in vivo signals.

Solution-processed organic tandem solar cells with power conversion efficiencies >12%

Abstract: Careful selection of small-molecule materials provides solution-processed tandem organic solar cells with a boost in efficiency. An effective way to improve the power conversion efficiency of organic solar cells is to use a tandem architecture consisting of two subcells, so that a broader part of the solar spectrum can be used and the thermalization loss of photon energy can be minimized1. For a tandem cell to work well, it is important for the subcells to have complementary absorption characteristics and generate high and balanced (matched) currents. This requires a rather challenging effort to design and select suitable active materials for use in the subcells. Here, we report a high-performance solution-processed, tandem solar cell based on the small molecules DR3TSBDT and DPPEZnP-TBO, which offer efficient, complementary absorption when used as electron donor materials in the front and rear subcells, respectively. Optimized devices achieve a power conversion efficiency of 12.50% (verified 12.70%), which represents a new level of capability for solution-processed, organic solar cells.

Fluorescent Sensors Based on Aggregation-Induced Emission: Recent Advances and Perspectives

Abstract: Fluorescent sensors with advantages of excellent sensitivity, rapid response, and easy operation are emerging as powerful tools in environmental monitoring, biological research, and disease diagnosis. However, conventional fluorophores featured with π-planar structures usually suffer from serious self-quenching in the aggregated state, poor photostability, and small Stokes’ shift. In contrast to conventional aggregation-caused quenching (ACQ) fluorophores, the newly emerged aggregation-induced emission fluorogens (AIEgens) are featured with high emission efficiency in the aggregated state, which provide unique opportunities for various sensing applications with advantages of high signal-to-noise ratio, strong photostability, and large Stokes’ shift. In this review, we will first briefly give an introduction of the AIE concept and the turn-on sensing principles. Then, we will discuss the recent examples of AIE sensors according to types of analytes. Finally, we will give a perspective on the future develop...

Ammonia Electrosynthesis with High Selectivity under Ambient Conditions via a Li+ Incorporation Strategy

Abstract: We report the discovery of a dramatically enhanced N2 electroreduction reaction (NRR) selectivity under ambient conditions via the Li+ incorporation into poly(N-ethyl-benzene-1,2,4,5-tetracarboxylic diimide) (PEBCD) as a catalyst. The detailed electrochemical evaluation and density functional theory calculations showed that Li+ association with the O atoms in the PEBCD matrix can retard the HER process and can facilitate the adsorption of N2 to afford a high potential scope for the NRR process to proceed in the “[O—Li+]·N2—Hx” alternating hydrogenation mode. This atomic-scale incorporation strategy provides new insight into the rational design of NRR catalysts with higher selectivity.

Controllable design of tunable nanostructures inside metal-organic frameworks.

Abstract: The controllable encapsulation of nanoentities (such as metal nanoparticles, quantum dots, polyoxometalates, organic and metallorganic molecules, biomacromolecules, and metal–organic polyhedra) into metal–organic frameworks (MOFs) to form composite materials has attracted significant research interest in a variety of fields These composite materials not only exhibit the properties of both the nanoentities and the MOFs but also display unique and synergistic functionalities Tuning the sizes, compositions, and shapes of nanoentities encapsulated in MOFs enables the final composites to exhibit superior performance to those of the separate constituents for various applications In this tutorial review article, we summarized the state-of-the-art development of MOFs containing encapsulated tunable nanoentities, with special emphasis on the preparation and synergistic properties of these composites

A unified phase-field theory for the mechanics of damage and quasi-brittle failure

Abstract: Being one of the most promising candidates for the modeling of localized failure in solids, so far the phase-field method has been applied only to brittle fracture with very few exceptions. In this work, a unified phase-field theory for the mechanics of damage and quasi-brittle failure is proposed within the framework of thermodynamics. Specifically, the crack phase-field and its gradient are introduced to regularize the sharp crack topology in a purely geometric context. The energy dissipation functional due to crack evolution and the stored energy functional of the bulk are characterized by a crack geometric function of polynomial type and an energetic degradation function of rational type, respectively. Standard arguments of thermodynamics then yield the macroscopic balance equation coupled with an extra evolution law of gradient type for the crack phase-field, governed by the aforesaid constitutive functions. The classical phase-field models for brittle fracture are recovered as particular examples. More importantly, the constitutive functions optimal for quasi-brittle failure are determined such that the proposed phase-field theory converges to a cohesive zone model for a vanishing length scale. Those general softening laws frequently adopted for quasi-brittle failure, e.g., linear, exponential, hyperbolic and Cornelissen et al. (1986) ones, etc., can be reproduced or fit with high precision. Except for the internal length scale, all the other model parameters can be determined from standard material properties (i.e., Young’s modulus, failure strength, fracture energy and the target softening law). Some representative numerical examples are presented for the validation. It is found that both the internal length scale and the mesh size have little influences on the overall global responses, so long as the former can be well resolved by sufficiently fine mesh. In particular, for the benchmark tests of concrete the numerical results of load versus displacement curve and crack paths both agree well with the experimental data, showing validity of the proposed phase-field theory for the modeling of damage and quasi-brittle failure in solids.

A review of industrial wireless networks in the context of Industry 4.0

Abstract: There have been many recent advances in wireless communication technologies, particularly in the area of wireless sensor networks, which have undergone rapid development and been successfully applied in the consumer electronics market. Therefore, wireless networks (WNs) have been attracting more attention from academic communities and other domains. From an industrial perspective, WNs present many advantages including flexibility, low cost, easy deployment and so on. Therefore, WNs can play a vital role in the Industry 4.0 framework, and can be used for smart factories and intelligent manufacturing systems. In this paper, we present an overview of industrial WNs (IWNs), discuss IWN features and related techniques, and then provide a new architecture based on quality of service and quality of data for IWNs. We also propose some applications for IWNs and IWN standards. Then, we will use a case from our previous achievements to explain how to design an IWN under Industry 4.0. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make IWNs truly ubiquitous for a wide range of applications.

A Transparent, Self-Healing, Highly Stretchable Ionic Conductor.

Abstract: Self-healing materials can repair damage caused by mechanical wear, thereby extending lifetime of devices. A transparent, self-healing, highly stretchable ionic conductor is presented that autonomously heals after experiencing severe mechanical damage. The design of this self-healing polymer uses ion-dipole interactions as the dynamic motif. The unique properties of this material when used to electrically activate transparent artificial muscles are demonstrated.

SnS nanoparticles electrostatically anchored on three-dimensional N-doped graphene as an active and durable anode for sodium-ion batteries

Abstract: SnS nanoparticles (SnS NPs) electrostatically anchored on a 3D N-doped graphene (3DNG) network exhibit the best cycling performance reported so far for SnS-based anodes. The stronger affinity of 3DNG to SnS NPs and to the discharge product compared to pure graphene is the fundamental reason for achieving a stable electrode architecture during cycling.

Tough, self-healable and tissue-adhesive hydrogel with tunable multifunctionality

Abstract: An ideal hydrogel for biomedical engineering should mimic the intrinsic properties of natural tissue, especially high toughness and self-healing ability, in order to withstand cyclic loading and repair skin and muscle damage. In addition, excellent cell affinity and tissue adhesiveness enable integration with the surrounding tissue after implantation. Inspired by the natural mussel adhesive mechanism, we designed a polydopamine–polyacrylamide (PDA–PAM) single network hydrogel by preventing the overoxidation of dopamine to maintain enough free catechol groups in the hydrogel. Therefore, the hydrogel possesses super stretchability, high toughness, stimuli-free self-healing ability, cell affinity and tissue adhesiveness. More remarkably, the current hydrogel can repeatedly be adhered on/stripped from a variety of surfaces for many cycles without loss of adhesion strength. Furthermore, the hydrogel can serve as an excellent platform to host various nano-building blocks, in which multiple functionalities are integrated to achieve versatile potential applications, such as magnetic and electrical therapies. A self-healing, super-resilient hydrogel that can accelerate skin regeneration has been made using an adhesive mechanism inspired by mussels. Hydrogels have similar structures to soft biological tissues and have great potential for tissue engineering applications. However, most are too fragile for use in the body and lack the ability to self-heal and adhere to tissue. Now, Xiong Lu from China's Southwest Jiaotong University and co-workers have synthesized a self-healing, super-resilient hydrogel using a process that preserves PDA's catechols – substances that impart mussels with high adhesiveness – when embedded in an elastic polymer matrix. The numerous non-covalent bonds between PDA catechols enable the hydrogel to perfectly re-form after being sliced open and help it stretch over 30 times its initial length without breaking. The material could also carry magnetic or conductive nanoparticles for future integrated healthcare applications. Inspired by mussel chemistry, a novel polydopamine–polyacrymide hydrogel simultaneously possesses super stretchability, stimuli-free self-healing properties, cell affinity and tissue adhesiveness. The current hydrogel lasts its adhesiveness for a long term, and can be repeatedly adhered on/stripped from a variety of substrates. The hydrogel can host various nano-building blocks and be tuned to magnetic and conductive hydrogels with above-mentioned properties.

High-Performance Ternary Organic Solar Cell Enabled by a Thick Active Layer Containing a Liquid Crystalline Small Molecule Donor.

Abstract: Ternary organic solar cells (OSCs) have attracted much research attention in the past few years, as ternary organic blends can broaden the absorption range of OSCs without the use of complicated tandem cell structures. Despite their broadened absorption range, the light harvesting capability of ternary OSCs is still limited because most ternary OSCs use thin active layers of about 100 nm in thickness, which is not sufficient to absorb all photons in their spectral range and may also cause problems for future roll-to-roll mass production that requires thick active layers. In this paper, we report a highly efficient ternary OSC (11.40%) obtained by incorporating a nematic liquid crystalline small molecule (named benzodithiophene terthiophene rhodanine (BTR)) into a state-of-the-art PTB7-Th:PC71BM binary system. The addition of BTR into PTB7-Th:PC71BM was found to improve the morphology of the blend film with decreased π–π stacking distance, enlarged coherence length, and enhanced domain purity. This resulte...

Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma

Abstract: Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).Experimental Design: One-hundred and eighteen patients (training cohort: n = 88; validation cohort: n = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps.Results: The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; P < 2.68 × 10-9). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; P < 1.60 × 10-7). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages.Conclusions: Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies. Clin Cancer Res; 23(15); 4259-69. ©2017 AACR.

New Nanoconfined Galvanic Replacement Synthesis of Hollow Sb@C Yolk–Shell Spheres Constituting a Stable Anode for High-Rate Li/Na-Ion Batteries

Abstract: In the current research project, we have prepared a novel Sb@C nanosphere anode with biomimetic yolk–shell structure for Li/Na-ion batteries via a nanoconfined galvanic replacement route. The yolk–shell microstructure consists of Sb hollow yolk completely protected by a well-conductive carbon thin shell. The substantial void space in the these hollow Sb@C yolk–shell particles allows for the full volume expansion of inner Sb while maintaining the framework of the Sb@C anode and developing a stable SEI film on the outside carbon shell. As for Li-ion battery anode, they displayed a large specific capacity (634 mAh g–1), high rate capability (specific capabilities of 622, 557, 496, 439, and 384 mAh g–1 at 100, 200, 500, 1000, and 2000 mA g–1, respectively) and stable cycling performance (a specific capacity of 405 mAh g–1 after long 300 cycles at 1000 mA g–1). As for Na-ion storage, these yolk–shell Sb@C particles also maintained a reversible capacity of approximate 280 mAh g–1 at 1000 mA g–1 after 200 cycles.

Achieving High-Performance Nondoped OLEDs with Extremely Small Efficiency Roll-Off by Combining Aggregation-Induced Emission and Thermally Activated Delayed Fluorescence

Abstract: Luminescent materials with thermally activated delayed fluorescence (TADF) can harvest singlet and triplet excitons to afford high electroluminescence (EL) efficiencies for organic light-emitting diodes (OLEDs). However, TADF emitters generally have to be dispersed into host matrices to suppress emission quenching and/or exciton annihilation, and most doped OLEDs of TADF emitters encounter a thorny problem of swift efficiency roll-off as luminance increases. To address this issue, in this study, a new tailor-made luminogen (dibenzothiophene-benzoyl-9,9-dimethyl-9,10-dihydroacridine, DBT-BZ-DMAC) with an unsymmetrical structure is synthesized and investigated by crystallography, theoretical calculation, spectroscopies, etc. It shows aggregation-induced emission, prominent TADF, and interesting mechanoluminescence property. Doped OLEDs of DBT-BZ-DMAC show high peak current and external quantum efficiencies of up to 51.7 cd A−1 and 17.9%, respectively, but the efficiency roll-off is large at high luminance. High-performance nondoped OLED is also achieved with neat film of DBT-BZ-DMAC, providing excellent maxima EL efficiencies of 43.3 cd A−1 and 14.2%, negligible current efficiency roll-off of 0.46%, and external quantum efficiency roll-off approaching null from peak values to those at 1000 cd m−2. To the best of the authors' knowledge, this is one of the most efficient nondoped TADF OLEDs with small efficiency roll-off reported so far.

Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision

Abstract: Robots with coordinated dual arms are able to perform more complicated tasks that a single manipulator could hardly achieve. However, more rigorous motion precision is required to guarantee effective cooperation between the dual arms, especially when they grasp a common object. In this case, the internal forces applied on the object must also be considered in addition to the external forces. Therefore, a prescribed tracking performance at both transient and steady states is first specified, and then, a controller is synthesized to rigorously guarantee the specified motion performance. In the presence of unknown dynamics of both the robot arms and the manipulated object, the neural network approximation technique is employed to compensate for uncertainties. In order to extend the semiglobal stability achieved by conventional neural control to global stability, a switching mechanism is integrated into the control design. Effectiveness of the proposed control design has been shown through experiments carried out on the Baxter Robot.

A Manufacturing Big Data Solution for Active Preventive Maintenance

Abstract: Industry 4.0 has become more popular due to recent developments in cyber-physical systems, big data, cloud computing, and industrial wireless networks. Intelligent manufacturing has produced a revolutionary change, and evolving applications, such as product lifecycle management, are becoming a reality. In this paper, we propose and implement a manufacturing big data solution for active preventive maintenance in manufacturing environments. First, we provide the system architecture that is used for active preventive maintenance. Then, we analyze the method used for collection of manufacturing big data according to the data characteristics. Subsequently, we perform data processing in the cloud, including the cloud layer architecture, the real-time active maintenance mechanism, and the offline prediction and analysis method. Finally, we analyze a prototype platform and implement experiments to compare the traditionally used method with the proposed active preventive maintenance method. The manufacturing big data method used for active preventive maintenance has the potential to accelerate implementation of Industry 4.0.