Prediction of pull-out force of multi-walled carbon nanotube (MWCNT) in sword-in-sheath mode

The pull-out force of some outer walls against other inner walls in multi-walled carbon nanotubes (MWCNTs) was systematically studied by molecular mechanics simulations. The obtained results reveal that the pull-out force is proportional to the square of the diameter of the immediate outer wall on the sliding interface, which highlights the primary contribution of the capped section of MWCNT to the pull-out force. A simple empirical formula was proposed based on the numerical results to predict the pull-out force for an arbitrary pull-out in a given MWCNT directly from the diameter of the immediate outer wall on the sliding interface. Moreover, tensile tests for MWCNTs with and without acid-treatment were performed with a nanomanipulator inside a vacuum chamber of a scanning electron microscope (SEM) to validate the present empirical formula. It was found that the theoretical pull-out forces agree with the present and some previous experimental results very well

Preparation of Novel Graphene/Silicone Rubber Nanocomposite Dielectric Foams

In order to obtain high dielectric silicone rubber (SR)-based nanocomposites, graphene (Gr) was added by ultrasonication and mechanical mixing for the preparation of a microporous structure. It was discovered that the Gr content and the expansion rate had a great impact on the cellular structure. Based on the effects of the Gr content and the expansion rate on the dielectric property, hybrid materials were prepared and better properties appeared, as expected. For all samples, the dielectric constant increased with the Gr content until 3 wt% and then decreased. When the Gr content was 3 wt% and the expansion rate was 2, the dielectric constant reached 18.14 (1 kHz), which was 55% higher than that of the non-expansion sample (11.74) and several times that of the pure sample (3~6). Meanwhile, the dielectric loss was less than 0.01. This work proposed a method for producing high dielectric materials with important applications in the field of capacitors, sensors, and micro-resistors

Spatiotemporal Analysis of Regional Ionospheric TEC Prediction Using Multi-Factor NeuralProphet Model under Disturbed Conditions

The ionospheric total electron content (TEC) is susceptible to factors, such as solar and geomagnetic activities, resulting in the enhancement of its non-stationarity and nonlinear characteristics, which aggravate the impact on radio communications. In this study, based on the NeuralProphet hybrid prediction framework, a regional ionospheric TEC prediction model (multi-factor NeuralProphet model, MF-NPM) considering multiple factors was constructed by taking solar activity index, geomagnetic activity index, geographic coordinates, and IGS GIM data as input parameters. Data from 2009 to 2013 were used to train the model to achieve forecasts of regional ionospheric TEC at different latitudes during the solar maximum phase (2014) and geomagnetic storms by sliding 1 day. In order to verify the prediction performance of the MF-NPM, the multi-factor long short-term memory neural network (LSTMNN) model was also constructed for comparative analysis. At the same time, the TEC prediction results of the two models were compared with the IGS GIM and CODE 1-day predicted GIM products (COPG_P1). The results show that the MF-NPM achieves good prediction performance effectively. The RMSE and relative accuracy (RA) of MF-NPM are 2.33 TECU and 93.75%, respectively, which are 0.77 and 1.87 TECU and 1.91% and 6.68% better than LSTMNN and COPG_P1 in the solar maximum phase (2014). During the geomagnetic storm, the RMSE and RA of TEC prediction results based on the MF-NPM are 3.12 TECU and 92.86%, respectively, which are improved by 1.25 and 2.30 TECU and 2.38% and 7.24% compared with LSTMNN and COPG_P1. Furthermore, the MF-NPM also achieves better performance in low–mid latitudes

Improved energy harvesting capability of poly(vinylidene fluoride) films modified by reduced graphene oxide

Piezoelectric energy harvesters can be used to convert ambient energy into electrical energy and power small autonomous devices. In recent years, massive effort has been made to improve the energy harvesting ability in piezoelectric materials. In this study, reduced graphene oxide was added into poly(vinylidene fluoride) to fabricate the piezoelectric nanocomposite films. Open-circuit voltage and electrical power harvesting experiments showed remarkable enhancement in the piezoelectricity of the fabricated poly(vinylidene fluoride)/reduced graphene oxide nanocomposite, especially at an optimal reduced graphene oxide content of 0.05 wt%. Compared to pristine poly(vinylidene fluoride) films, the open-circuit voltage, the density of harvested power of alternating current, and direct current of the poly(vinylidene fluoride)/reduced graphene oxide nanocomposite films increased by 105%, 153%, and 233%, respectively, indicating a great potential for a broad range of applications

Preparation of PVDF-HFP/CB/Ni nanocomposite films for piezoelectric energy harvesting

As a representative flexible piezoelectric polymer, polyvinylidene fluoride (PVDF) and its copolymers have been widely used in energy harvesters and piezoelectric sensors. In this work, hybrid nanocomposite films were prepared by adding a small amount of carbon black (CB) and Ni nanoparticles to the poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) matrix using the solution casting method, followed by stretching and poling to increase the electroactive β-phase content. The results show that the hybrid fillers consisting of 0.3 wt% CB and 0.1 wt% Ni nanoparticles exhibit the best piezoelectric performance. The maximum output voltage of the PVDF-HFP/CB/Ni films reaches 3.5 V under 1 mm micro-vibration, which is 75% higher than that of pure PVDF-HFP films. Characterization results by X-ray diffraction analysis, Fourier-transform infrared spectrometry, and differential scanning calorimeter analysis show that the hybrid fillers are more effective in promoting the phase transformation from the α-phase to the β-phase in the matrix due to synergistic effect

Understanding the mechanical properties and deformation behavior of 3-D graphene-carbon nanotube structures

Here, a new three-dimensional graphene-carbon nanotube (3-D GR-CNT) structure was proposed, and the compressive mechanical properties and deformation behavior of the 3-D GR-CNT structure were evaluated using molecular dynamics (MD) simulations. It was found that the 3-D GR-CNT structure had outstanding mechanical properties, especially the ultrahigh Young's modulus, which was up to 1018 GPa and as high as that of GR. The 3-D GR-CNT structure did not have plastic deformation during the compression. The effects of GR length and CNT diameter were evaluated, and it was demonstrated that when the ratio of CNT diameter to GR length was about 0.6, the ultimate stress of the 3-D GR-CNT structure was the highest. Owing to the low density of the 3-D GR-CNT structure, the structure had outstanding specific strength. At a small compressive deformation, GRs produced buckling deformation with wrinkles to resist compression. After reaching the critical buckling stress, CNTs began to produce wrinkles; and after reaching the failure stress, the destruction started from the junctions. In addition, compared with the sp3 carbon atoms, the sp2 carbon atoms were more suitable for the junctions, as more energy could be absorbed by the sp2 carbon atoms in the junctions

An Efficient Algorithm Embedded in an Ultrasonic Visualization Technique for Damage Inspection Using the AE Sensor Excitation Method

To improve the reliability of a Lamb wave visualization technique and to obtain more information about structural damages (e.g., size and shape), we put forward a new signal processing algorithm to identify damage more clearly in an inspection region. Since the kinetic energy of material particles in a damaged area would suddenly change when ultrasonic waves encounter the damage, the new algorithm embedded in the wave visualization technique is aimed at monitoring the kinetic energy variations of all points in an inspection region to construct a damage diagnostic image. To validate the new algorithm, three kinds of surface damages on the center of aluminum plates, including two non-penetrative slits with different depths and a circular dent, were experimentally inspected. From the experimental results, it can be found that the new algorithm can remarkably enhance the quality of the diagnostic image, especially for some minor defects