Interlayer Engineering of Molybdenum Trioxide toward High‐Capacity and Stable Sodium Ion Half/Full Batteries

Orthorhombic molybdenum trioxide (MoO₃) is one of the most promising anode materials for sodium‐ion batteries because of its rich chemistry associated with multiple valence states and intriguing layered structure. However, MoO₃ still suffers from the low rate capability and poor cycle induced by pulverization during de/sodiation. An ingenious two‐step synthesis strategy to fine tune the layer structure of MoO₃ targeting stable and fast sodium ionic diffusion channels is reported here. By integrating partially reduction and organic molecule intercalation methodologies, the interlayer spacing of MoO₃ is remarkably enlarged to 10.40 Å and the layer structural integration are reinforced by dimercapto groups of bismuththiol molecules. Comprehensive characterizations and density functional theory calculations prove that the intercalated bismuththiol (DMcT) molecules substantially enhanced electronic conductivity and effectively shield the electrostatic interaction between Na⁺ and the MoO₃ host by conjugated double bond, resulting in improved Na⁺ insertion/extraction kinetics. Benefiting from these features, the newly devised layered MoO₃ electrode achieves excellent long‐term cycling stability and outstanding rate performance. These achievements are of vital significance for the preparation of sodium‐ion battery anode materials with high‐rate capability and long cycling life using intercalation chemistry.     

Performance investigation on a novel 3D wave flow channel design for PEMFC

Flow field structure can largely determine the output performance of Polymer electrolyte membrane fuel cell. Excellent channel configuration accelerates electrochemical reactions in the catalytic layer, effectively avoiding flooding on the cathode side. In present study, a three-dimensional, multi-phase model of PEMFC with a 3D wave flow channel is established. CFD method is applied to optimize the geometry constructions of three-dimensional wave flow channels. The results reveal that 3D wave flow channel is overall better than straight channel in promoting reactant gases transport, removing liquid water accumulated in microporous layer and avoiding thermal stress concentration in the membrane. Moreover, results show the optimal flow channel minimum depth and wave length of the 3D wave flow channel are 0.45 mm and 2 mm, respectively. Due to the periodic geometric characteristics of the wave channel, the convective mass transfer is introduced, improving gas flow rate in through-plane direction. Furthermore, when the cell output voltage is 0.4 V, the current density in the novel channel is 23.8% higher than that of conventional channel.     

Combating Biofilm Associated Infection In Vivo: Integration of Quorum Sensing Inhibition and Photodynamic Treatment based on Multidrug Delivered Hollow Carbon Nitride Sphere

Recently, quorum sensing (QS) inhibitors (QSIs) have been combined with antibiotics to enhance antibiofilm efficacy in vitro and in vivo. However, targeting QS signals alone is not enough to prevent bacterial infections. Drug resistance and recurrence of biofilms makes it difficult to eradicate. Herein, photodynamic therapy (PDT) is selected to unite QSIs and antibiotics. A synergistically antibiofilm system, which combines QSIs, antibiotics, and PDT based on hollow carbon nitride spheres (HCNSs) is envisaged. First, HCNS provides the multidrug delivering ability, enabling QSIs and antibiotics to be released in sequence. Subsequently, multistage releases sensitize bacteria effectively, potentiating the chemotherapeutic effects of the antibiotics. Finally, the integration of QSIs and PDT not only minimizes the possibility of drug resistance, but also overcomes the problem of limited mass and extension of PDT. Even after 48 h of incubation, the bacterial biofilm is obviously inhibited. And its biofilm disperse efficiency exceeds 48% (compared with QSI‐potentiated chemotherapy group) and 40% (compared with PDT group). Besides, the inhibition of the QS system influences phenotypes related to virulence factor production and surface hydrophobicity, which weaken biofilm invasion and formation. Eventually, this system is applied to disperse bacterial biofilm in vivo. Overall, PDT and QS modulation are devoted to eradicate drug resistance and recurrence of the biofilm.     

High-rate capability of carbon-coated micron-sized hexagonal TT-Nb2O5 composites for lithium-ion battery

With excellent specific capacity, superior cycle stability, safety and strong practical, Nb₂O₅ has been considered as one of the prospective anode materials for lithium-ion batteries (LIBs). However, current study suggests that Nb₂O₅ electrode materials for LIBs still face the vital issues of low electrical conductivity and poor rate performance. Therefore, carbon-coated TT-Nb₂O₅ materials are designed and synthesized through solid state method in this work, which present high specific capacity (228 mA h g^?1 at 0.2C), satisfactory rate properties (107 mA h g^?1 at 20 C). The outstanding electrochemical property can not only give the credit to the pseudocapacitance effect of TT-Nb₂O₅, but also attribute to introduction of carbon. The homogeneous carbon-coated materials enhance the electrical conductivity, increase the electron transmission speed and alleviate particle crushing. This research not only offers a new method for preparing excellent electrode materials, but also provides a kind of excellent anode material with prospective application for LIBs.     

Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Synergistic flame retardant effects of activated carbon and molybdenum oxide in poly(vinyl chloride)

The synergistic effects of activated carbon (AC) and molybdenum oxide (MoO₃) in improving the flame retardancy of poly(vinyl chloride) (PVC) were investigated. The effects of AC, MoO₃ and their mixture with a mass ratio of 1:1 on the flame retardancy and smoke suppression properties of PVC were studied using the limiting oxygen index and cone calorimeter tests. It was found that the flame retardancy of the relatively cheaper AC was slightly weaker than that of MoO₃. In addition, the incorporation of AC and MoO₃ greatly reduced the total heat release and improved smoke suppressant property of PVC composites. When the total content of AC and MoO₃ was 10 phr, PVC/AC/MoO₃ had the lowest peak heat release rate and peak smoke production rate values of 173.80 kW m^?2 and 0.1472 m² s^?1, which represented reductions of 47.3 and 59.9%, respectively, compared with those of PVC. Furthermore, thermogravimetric analysis and gel content tests were used to analyze the flame retardant mechanism of AC and MoO₃, with results showing that AC could promote early crosslinking in PVC. Char residue left after heating at 500 °C was analyzed using scanning electron microscopy and Raman spectroscopy, and the results showed that MoO₃ produced the most compact char, with the smallest and most organized carbonaceous microstructures. © 2017 Society of Chemical Industry     

酸碱理论及其在有机反应中的应用研究

酸碱反应无论是在无机化学还是有机化学中,都占有极高的地位,文章以综述的形式讨论酸碱理论及其在一些重要的有机反应中应用研究。     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Disappearance and recovery of colossal permittivity in (Nb+Mn) co-doped TiO2

We investigate the effects of doping and annealing on the dielectric properties of metal ions doped TiO₂ ceramics. Colossal permittivity (CP) above 10⁴ was observed in single Nb ion doped TiO₂, which was dominated by electron transport related interfacial polarization. Moreover, the CP can be dropped to 120 when simultaneously introducing Mn ion into the sample. The disappearance of CP behaviors maybe due to the multivalence of Mn which would inhibit the reduction of Ti⁴⁺ to Ti³⁺, and thus reduce delocalized electrons. Interestingly, the CP was recovered for the (Nb+Mn) co-doped TiO₂ after post-sintering heat treatment in N₂ atmosphere. The recovery of CP in the sample after annealing can be ascribed to the semiconducting grain and the insulating grain boundary, according to impedance spectroscopy. We therefore believe that this work can help us understand the mechanism of CP from a new perspective.