IET Nanodielectrics最新文献

Improving the energy storage density of dielectric capacitors has absorbed extensive attention for energy storage. However, a decrease in breakdown strength may be aroused after the addition of abundant fillers, it is necessary to design the composite film with a sandwich structure without the sacrifice of mechanical properties. The PPy-TiO₂/PVDF monolayer film and PVDF/PPy-TiO₂/PVDF sandwich-structured composite films were successfully prepared via electrospinning and a hot-press treatment. The experiment results show that the dielectric constant of the composite films can be enhanced effectively by adding PPy-TiO₂.When the filling amount is 30 wt%, the energy storage density of PVDF/PPy-TiO₂/PVDF sandwich-structured composite films is outstanding before the breakdown strength, which is higher than that of the pure PVDF film. The energy storage density of PVDF/PPy-TiO₂/PVDF sandwich-structured composite films could be achieved to 2.68 J/cm³ under the electric strength of 1700 kV/cm.

Most commonly used dielectric elastomers (DEs) such as acrylic dielectric elastomers VHB^TM 4910 need a high actuation voltage and pre-stretching to obtain a large actuation strain, and present high mechanical loss caused by viscoelasticity. In this work, we fabricated a new acrylic elastomer by UV curing based on CN9021 and lauryl acrylate. By manipulating crosslinker content, crosslink density changed and physical entanglements of the new material can be affected. Therefore, mechanical properties such as Young's Modulus and mechanical loss of the new material can be controlled, and little change of its glass transition temperature was induced. Results of the actuation test show that the new DE is capable of 9.0% actuation area strain under 11 kV/mm and a good performance under oscillating voltage with different waveforms and frequencies.

The agglomeration causes a significant challenge to nanodielectrics. Identification of agglomerates in scanning electron microscopy (SEM) images is an important step of solving this issue. Motivated by the fast development of image recognition in computer vision, we propose a new approach for agglomerates identification in SEM images of nanodielectrics by semantic segmentation, which is more efficient and accurate than traditional methods. Three models based on convolutional neural networks are investigated in this work, namely pixel blocks classification network, full convolutional segmentation network employed with data augmentation and unsupervised self-encoding network. All three networks can preliminarily identify agglomerates of spherical silica-based blend polyethylene nanocomposites. The mean intersection over union (mIoU) of pixel blocks classification network is 0.843 and it takes 25 s to process an image. Full convolutional segmentation network only needs 0.059 s to process a sample, with a mIoU of 0.777. Unsupervised self-encoding network can reach a mIoU of 0.747 at a speed of 5.806 s. According to the amount of data sets, and requirements for different speed and accuracy, three kinds of networks can be flexibly selected.

Focussing on the insulating material of power transformer—cellulose insulation paper, this paper first introduces the basic characteristics and engineering application background of insulation paper. Then, the research progress of improving the mechanical properties, thermal stability and electrical properties of insulation paper by nano modification in recent years is compared, and the promotion mechanism is analysed. In addition, in practical engineering application, the oil–paper composite insulation system composed of insulation paper and insulating oil is used for the internal insulation of oil immersed transformer. Therefore, the influence of modified insulation paper on the performance of oil–paper composite insulation system is analysed. Finally, the newly reported new insulation paper is introduced, and the future development trend of modification of traditional insulation paper is analysed.

Dielectric elastomers (DEs) could transduce electrical energy to mechanical energy, but their applications are currently limited by the elevated driving voltages. To obtain satisfactory actuated strains at low voltages, titanate oxide@tannic acid-ferric ion@silver (labelled as TiO₂@TA-Fe³⁺@Ag) satellite-structure nanoparticles were obtained in this study by in situ synthesis followed by incorporating the nanoparticles into natural rubber (NR) to prepare DE composites (denoted as TiO₂@TA-Fe³⁺@Ag/NR). The presence of surface coating of TA-Fe³⁺ and Ag nanoparticles improved the electromechanical performance of TiO₂@TA-Fe³⁺@Ag/NR composites. Among the samples, 30 wt% TiO₂@TA-Fe³⁺@Ag/NR composite displayed a relatively high actuated strain of 9.09% at a relatively low electric field of 22.78 kV/mm. In sum, the green, facile, and cost-effective surface modification method looks promising for improving the electromechanical properties of particulate-filled polymer composites.

Polymer-based dielectrics are extensively applied in various electrical and electronic devices such as capacitors, power transmission cables and microchips, in which a variety of distinct performances such as the dielectric and thermal properties are desired. To fulfil these properties, the emerging machine learning (ML) technique has been used to establish a surrogate model for the structure–property linkage analysis, which provides an effective tool for the rational design of the chemical and morphological structure of polymers/nanocomposites. In this article, the authors reviewed the recent progress in the ML algorithms and their applications in the rational design of polymer-based dielectrics. The main routes for collecting training data including online libraries, experiments and high-throughput computations are first summarized. The fingerprints charactering the microstructures of polymers/nanocomposites are presented, followed by the illustration of ML models to establish a mapping between the fingerprinted input and the target properties. Further, inverse design methods such as evolution searching strategies and generative models are described, which are exploited to accelerate the discovery of new polymer-based dielectrics. Moreover, structure–property linkage analysis techniques such as Pearson correlation calculation, decision-tree-based methods and interpretable neural networks are summarized to identify the key features affecting the target properties. The future development prospects of the ML-driven design method for polymer-based dielectrics are also presented in this review.

Nano-materials have undergone tremendous advancement in recent years, specifically in the field of engineering applications. To demonstrate these advances, seven high quality articles have been presented in this Special Issue, including one review and six original research works in various fields of engineering applications.

Reference [1], ‘Polypropylene-based nanocomposites for high voltage direct current (HVDC) cable insulation’ (by Adnan, M. et al.), presents an excellent review of different aspects of nanomaterials used in cable insulation for HVDC applications. The review shows that nanocomposites based on polypropylene exhibit enhanced dielectric properties, making them suitable for DC high voltage applications. Electrical double-layer, multicore and multi-region structure models are used for nanocomposite materials. Different fabrication methods have been improved, such as ‘Intercalation method’, ‘Sol gel method’ and ‘In situ polymerisation’. The paper presents DC breakdown characteristics for nanofiller loading, followed by the different types and effects for different nanocomposites.

In Reference [2], ‘Structure for fast photonic medium on application of space-division multiplexing (SDM) communication using SiO₂ doped with GeO₂, and F materials’ (by Behera, B. et al.), an advanced doping structure has been found suitable for applications in SDM communication for a fast photonic medium. A few-mode fibre has been introduced which shows a very small bit-error-rate, confirming the suitability of the advanced doping structure.

In Reference [3], ‘Nickel-cobalt-zinc ferrite nanoparticles for radio-frequency/terahertz frequency-selective surface application’ (by Arya, M. et al.), an advanced nanoparticle structure has been introduced for radio-frequency/terahertz frequency-selective surface applications. Terahertz time domain spectroscopy was used for analysis which revealed that the saturation magnetisation, remanent magnetisation and coercivity increased with an increase in temperature from 50 to 300 K.

Reference [4], ‘Investigation on the partial discharge characteristics of eco-friendly nanofluid insulation of corn oil nanofluid’ (by Shantha Kumar M. et al.), has revealed phase-resolved partial discharge analysis useful features of corn oil nanofluid. The oil is biodegradable in nature and, moreover, the analysis with different percentages of SiO₂ has shown improvements of partial discharge inception voltage, reduction of the repetition rate, equivalent time length, magnitude, lower discharge activity due to a rise in the wave shape etc. Thus, the authors have shown that it can be considered eco-friendly as well as an alternate for mineral oils.

Reference [5], ‘Switching transient-based state of ampere-hour prediction of lithium-ion, nickel-cadmium, nickel-metal-hydride and lead acid batteries used in vehicles’ (

The importance of surface roughness with respect to the bulk properties of dielectric materials is often overlooked. Surface roughness or interfaces between different material layers often significantly affects the external properties of thin films. Surface roughness holds its commonalty and critical impact among many materials properties. This review summarises the recent work on the effect of surface roughness on the mechanical, thermal, physical, and dielectric properties of dielectric films. Appropriate roughness favours adhesion, filtration, biological fouling, tribological properties, and magnetic properties. Nevertheless, lower roughness generally benefits the dielectric properties of dielectric materials, with thicknesses ranging from a few nanometres to up to 50 μm. This review discusses surface roughness control and the techniques of measurement as well. It emphasises the importance and characterisation of sample surface roughness for a better understanding of the dielectric phenomenon, mechanisms, and electrical stress test setup for various dielectric films.

The polyaniline/graphite oxide (PANI/GO) nanocomposite was prepared by the in situ chemical polymerisation method. The synthesis involved the formation of dark green coloured polyaniline/graphite oxide composite. The crystalline structure and morphology of the composite were studied using UV-visible spectroscopy (UV), X-ray diffraction (XRD) and transmission electron microscopy (TEM).The characteristic peaks in XRD and UV-visible spectra confirmed the formation of the PANI/GO nanocomposite. DC conductivity measurements were performed using a two-probe method. Dielectric responses of the composites were investigated in the frequency range100 MHz to 3 GHz by the RF impedance analyser. The dielectric constant ϵ′(w) and dielectric loss ϵ′′(w) were investigated. It was observed that the dielectric constant ϵ′(w) and dielectric loss ϵ′′(w) decreased with an increase in frequencies (for different wt % of GO). The antibacterial activity of this composite was examined.