Preparation and enhanced properties of Fe3O4 nanoparticles reinforced polyimide nanocomposites

Polyimide (PI) nanocomposite reinforced with Fe3O4 nanoparticles (NPs) at various NPs loadings levels of 5.0, 10.0, 15.0, and 20.0 wt% were prepared. The chemical interactions of the Fe3O4 NPs/PI nanocomposites were characterized using Fourier Transform Infrared (FT-IR) spectroscopy. X-ray Diffraction (XRD) results revealed that the addition of NPs had a significant effect on the crystallization of PI. Scanning electron microscope (SEM) and the atomic force microscope (AFM) were used to characterize the dispersion and surface morphology of the Fe3O4 NPs and the PI nanocomposites. The obtained optical band gap of the nanocomposites characterized using Ultraviolet-Visible Diffuse Reflectance Spectroscopy (UV-Vis DRS) was decreased with increasing the Fe3O4 loading. Differential scanning calorimetry (DSC) results showed a continuous increase of Tg with increasing the Fe3O4 NPs loading. Some differences were observed in the onset decomposition temperature between the pure PI and nanocomposites since the NPs and the PI matrix were physically entangled together to form the nanocomposites. The contact angle of pure PI was larger than that of Fe3O4/PI nanocomposites films, and increased with increasing the loading of Fe3O4. The degree of swelling was increased with increasing the Fe3O4 loading and the swelling time. The dielectric properties of the nanocomposite were strongly related to the Fe3O4 loading levels. The Fe3O4/PI magnetic property also had been improved with increasing the loading of the magnetic nanoparticles

Enhanced Electrochemical Performance Promoted by Tin in Silica Anode Materials for Stable and High-Capacity Lithium-Ion Batteries

Although the silicon oxide (SiO2) as an anode material shows potential and promise for lithium-ion batteries (LIBs), owing to its high capacity, low cost, abundance, and safety, severe capacity decay and sluggish charge transfer during the discharge–charge process has caused a serious challenge for available applications. Herein, a novel 3D porous silicon oxide@Pourous Carbon@Tin (SiO2@Pc@Sn) composite anode material was firstly designed and synthesized by freeze-drying and thermal-melting self-assembly, in which SiO2 microparticles were encapsulated in the porous carbon as well as Sn nanoballs being uniformly dispersed in the SiO2@Pc-like sesame seeds, effectively constructing a robust and conductive 3D porous Jujube cake-like architecture that is beneficial for fast ion transfer and high structural stability. Such a SiO2@Pc@Sn micro-nano hierarchical structure as a LIBs anode exhibits a large reversible specific capacity ~520 mAh·g−1, initial coulombic efficiency (ICE) ~52%, outstanding rate capability, and excellent cycling stability over 100 cycles. Furthermore, the phase evolution and underlying electrochemical mechanism during the charge–discharge process were further uncovered by cyclic voltammetry (CV) investigation

Energy-efficient Optimization of Reorganization-Enabled Wireless Sensor Networks

Abstract: This paper studies the target tracking problem in wireless sensor networks where sensor nodes are deployed randomly. To achieve tracking accuracy constrained by energy consumption, an energy-efficient optimization approach that enables reorganization of wireless sensor networks is proposed. The approach includes three phases which are related to prediction, localization and recovery, respectively. A particle filter algorithm is implemented on the sink node to forecast the future movement of the target in the first prediction phase. Upon the completion of this phase, the most energy efficient sensor nodes are awakened to collaboratively locate the target. Energy efficiency is evaluated by the ratio of mutual information to energy consumption. The recovery phase is needed to improve the robustness of the approach. It is performed when the target is missed because of the incorrect predicted target location. In order to recapture the target by awakening additional sensor nodes as few as possible, a genetic-algorithm-based mechanism is introduced to cover the recovery area. We show that the proposed approach has excellent tracking performance. Moreover, it can efficiently reduce energy consumption, prolong network lifetime and reduce network overheads

Study of the Synergistic Effect of Nanoporous Nickel Phosphates on Novel Intumescent Flame Retardant Polypropylene Composites

A char forming agent (CFA) and silica-gel microencapsulated ammonium polyphosphate (Si-MCAPP) were selected to form novel intumescent flame retardant system to prepare flame retardant polypropylene (PP) composites, and then the influences of nanoporous nickel phosphates (NiP) on the thermal and flame retardant properties of flame retardant PP composites were studied by the real time FTIR (RTFTIR) spectra, limited oxygen index (LOI) test, and the scanning electron microscopy. RTFTIR shows the addition of NiP can improve the thermal stability of flame retardant PP composites. LOI test shows LOI value is increased with the increase of the content of NiP, and the optimized concentration of NiP is 1.0%. Furthermore, smoke toxicity of the novel flame retardant PP composites was studied by mice experiment. The upper limit of the no death smoke concentration of the composite is 12.37 mg/L

Numerical Simulation on Stress Distribution and Deformation of Large Hydro Turbine Blade with Complex Surface during Heat Treatment Process

A three dimensional finite element model of the heat treatment process of ZG06Cr13Ni4Mo stainless steel was established in this paper. The distribution of stress and deformation for large hydro turbine blade with complex surface during normalizing and tempering treatment has been simulated. The simulated results are consistent with the measured equivalent stress values by hole-drilling method, which indicates that the model is effective to predict the stress distribution of heat treated ZG06Cr13Ni4Mo material. Based on this model, the distribution law of stress field and deformation of the large hydro turbine blade of complex surface after the heat treatment were simulated. The established model provided a theoretical prediction method for designing of optimized complex surface blade and formulating a reasonable heat treatment process

Microwave assisted formation of magnetic core-shell carbon nanostructure

This letter describes a facile high temperature microwave assisted process to form the magnetic core-shell carbon nanostructure from polyaniline (PANI)-magnetite (Fe3O4) nanocomposites. The amorphous combined with graphitized carbon shell is observed by the transmission electron microscopy (TEM). The crystalline metallic iron, cementite, Fe3O4 and iron oxide (Fe2O3) are observed in the magnetic core in the M̈ossbauer spectrum measurements. The increased magnetic properties are observed in the formed core-shell carbon nanostructure after microwave annealing. The formed solid carbon nanostructure can protect the material from the acid dissolution and magnetic core favors the recycling of material. © 2013 The Electrochemical Society

Hierarchical Wireless Multimedia Sensor Networks for Collaborative Hybrid Semi-Supervised Classifier Learning

Abstract: Wireless multimedia sensor networks (WMSN) have recently emerged as one of the most important technologies, driven by the powerful multimedia signal acquisition and processing abilities. Target classification is an important research issue addressed in WMSN, which has strict requirement in robustness, quickness and accuracy. This paper proposes a collaborative semi-supervised classifier learning algorithm to achieve durative online learning for support vector machine (SVM) based robust target classification. The proposed algorithm incrementally carries out the semi-supervised classifier learning process in hierarchical WMSN, with the collaboration of multiple sensor nodes in a hybrid computing paradigm. For decreasing the energy consumption and improving the performance, some metrics are introduced to evaluate the effectiveness of the samples in specific sensor nodes, and a sensor node selection strategy is also proposed to reduce the impact of inevitable missing detection and false detection. With the ant optimization routing, the learning process is implemented with the selected sensor nodes, which can decrease the energy consumption. Experimental results demonstrate that the collaborative hybrid semisupervised classifier learning algorithm can effectively implement target classification in hierarchical WMSN. It has outstanding performance in terms of energy efficiency and time cost, which verifies the effectiveness of the sensor nodes selection and ant optimization routing

Electromagnetic field absorbing polypropylene nanocomposites with tuned permittivity and permeability by nanoiron and carbon nanotubes

Highly efficient electromagnetic field absorption at gigahertz (GHz) was reported in the novel magnetic polymer nanocomposites (MPNCs) with in-situ synthesized Fe@Fe2O3 core@shell nanoparticles (NPs) or their decorated multiwall carbon nanotubes (MWNTs) dispersed in the polypropylene (PP) matrix through a one-pot bottom-up method. PP grafted maleic anhydride (PP-g-MA) with different molecular weights served as surfactant to stabilize the in-situ-formed NPs and simultaneously as compatibilizer to enhance the bonding at the PP-filler interfaces. Because of the strong magnetization of the PP MPNCs filled with 20.0 wt % Fe@Fe2O3 NPs stabilized by PP-g-MA (Mn = 800), a minimum reflection loss (RL) of -31.5 dB was observed at 18.0 GHz, and the frequency bandwidth with RL lower than -10.0 dB was 3.1 GHz (from 16.9 to 20.0 GHz) in the MPNC sample with a thickness of 5.5 mm. However, due to the lack of magnetic loss, only a weak RL of 4.3 dB was found at frequency of 16.8 GHz for the PP/PP-g-MA (Mn = 800)/1.0 wt % MWNTs nanocomposites sample with a thickness of 5.5 mm. When the PP MPNCs filled with Fe@Fe2O3 NPs decorated MWNTs (sample thickness of 5.0 mm) in the presence of low molecular weight PP-g-MA (Mn = 800), the RL of -24.5 dB at 20.0 GHz was observed. Through simply changing Mn of PP-g-MA from 800 to 8000, more oxidized iron resulted in a decreased permeability and smaller RL in the high frequency range. The in-situ-formed nanofillers significantly reduced the flammability of PP for potential wide applications

Mesoporous magnetic carbon nanocomposite fabrics for highly efficient Cr(vi) removal

We have demonstrated that magnetic carbon nanocomposite fabrics prepared by microwave assisted heating are advanced adsorbents in the removal of Cr(vi) with a much higher removal capacity of 3.74 mg g-1 compared to 0.32 mg g-1 for cotton fabrics and 0.46 mg g-1 for carbon fabrics. The enhanced Cr(vi) removal is attributed to the highly porous structure of the nanocomposites. The adsorption kinetics follow the pseudo-second-order model, which reveals a very large adsorption capacity and high adsorption rate. The removal process takes only 10 min, which is much faster than conventional adsorbents such as activated carbon and biomass that often requires hours of operation. The significantly reduced treatment time and the large adsorption capacity make these nanocomposite fabrics promising for the highly efficient removal of heavy metals from polluted water. © 2014 The Royal Society of Chemistry

Reinforced magnetic epoxy nanocomposites with conductive polypyrrole nanocoating on nanomagnetite as a coupling agent

The new function of polypyrrole (PPy) to serve as a coupling agent has been demonstrated in preparing conductive epoxy resin nanocomposites with PPy coating on magnetite (f-Fe3O4) nanoparticles. The effects of magnetic nanofiller loading level on the rheological behavior, thermal stability, dynamic mechanical properties, mechanical properties, electrical conductivity, dielectric properties and magnetic properties were systematically studied. Compared with pure epoxy suspension, a reduced viscosity was observed in epoxy nanosuspensions with 5.0 wt% f-Fe3O4 nanoparticles, and the viscosity increased with further increasing f-Fe 3O4 nanoparticle loading. Increased glass transition temperature (Tg) and enhanced mechanical tensile strength were observed in the cured solid epoxy polymer nanocomposites (PNCs) with f-Fe 3O4 nanoparticles. The volume resistivity of the cured epoxy PNCs with 30.0 wt% f-Fe3O4 nanoparticles was decreased almost 7 orders of magnitude compared with the cured pure epoxy (1.6 × 1013 Ω cm). The cured epoxy PNCs exhibited good magnetic properties, and the surface functionality and epoxy matrix have little effect on the magnetic moment of the Fe3O4 nanoparticles. The role of PPy nanocoating on the nanocomposite formation mechanism was investigated by using the Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric analysis (TGA) tests. © the Partner Organisations 2014