Analysis of suitability of TPP ash-slag waste as materials for hydrogen fuel storage

The current trends in energy were described, the main of which is the use of alternative energy sources, especially hydrogen. The most common methods of hydrogen accumulation were proposed: accumulation of compressed gaseous hydrogen in high-pressure tanks; accumulation of liquid hydrogen in cryogenic tanks; storing hydrogen in a chemically bound state; accumulation of gaseous hydrogen in carriers with a high specific surface area. Based on the combination of advantages and disadvantages, the most promising methods of accumulation were selected: storage of liquid hydrogen and storage of hydrogen in carriers with a high specific surface area. The main requirement for materials for hydrogen storage by these methods was revealed – a high specific surface area. Prospects for the development of waste-free low-emission technologies due to the recycling of secondary raw materials and the development of low-temperature technologies for the synthesis of functional and structural materials were substantiated. The applicability of large-scale ash and slag waste from coal-fired thermal power plants as a raw material for obtaining materials by low-temperature technologies was shown. The traditional ways of using ash and slag waste as a raw material, active additive and filler in the production of cements were described. Modern technologies for the production of innovative materials with a unique set of properties were presented, namely carbon nanotubes, silica aerogel and geopolymer materials. The prospect of using geopolymer matrices as a precursor for the synthesis of a number of materials was described; the most promising type of materials was selected – geopolymer foams, which are mainly used as sorbents for purifying liquids and gases or accumulating target products, as well as heat-insulating materials. The possibility of obtaining products of any shape and size on the basis of geopolymer matrices without high-temperature processing was shown. The special efficiency of the development of the technology of porous granules and powders obtained from a geopolymer precursor using various methods was substantiated. The obtained granules can be used in the following hydrogen storage technologies: direct accumulation of hydrogen in porous granules; creation of insulating layers for liquid hydrogen storage units.     

High quality 3D reconstruction based on fusion of polarization imaging and binocular stereo vision

Polarization imaging can retrieve inaccurate objects’ 3D shapes with fine textures, whereas coarse but accurate depths can be provided by binocular stereo vision. To take full advantage of these two complementary techniques, we investigate a novel 3D reconstruction method based on the fusion of polarization imaging and binocular stereo vision for high quality 3D reconstruction. We first generate the polarization surface by correcting the azimuth angle errors on the basis of registered binocular depth, to solve the azimuthal ambiguity in the polarization imaging. Then we propose a joint 3D reconstruction model for depth fusion, including a data fitting term and a robust low-rank matrix factorization constraint. The former is to transfer textures from the polarization surface to the fused depth by assuming their relationship linear, whereas the latter is to utilize the low-frequency part of binocular depth to improve the accuracy of the fused depth considering the influences of missing-entries and outliers. To solve the optimization problem in the proposed model, we adopt an efficient solution based on the alternating direction method of multipliers. Extensive experiments have been conducted to demonstrate the efficiency of the proposed method in comparison with state-of-the-art methods and to exhibit its wide application prospects in 3D reconstruction.     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

使能未来工厂的5G能力综述

5G系统将移动通信服务从移动电话、移动宽带和大规模机器通信扩展到新的应用领域，即所谓对通信服务有特殊要求的垂直领域。对使能未来工厂的5G能力进行了全面的分析总结，包括弹性网络架构、灵活频谱、超可靠低时延通信、时间敏感网络、安全和定位，而弹性网络架构又包括对网络切片、非公共网络、5G局域网和边缘计算的支持。希望从广度到深度，对相关的理论及技术应用做透彻、全面的梳理，对其挑战做清晰的总结，从而为相关研究和工程技术人员提供借鉴。     

Preparation,structural and photocatalytic activity of Sn/Fe co-doped TiO2 nanoparticles by sol-gel method

Pure and Sn/Fe co-doped (0.2 at.% Sn and 0.6 at.% Fe, 0.6 at.% Sn and 0.2 at.% Fe, 1.0 at.% Sn and 1.0 at.% Fe) TiO₂ nanoparticles were synthesized via a sol-gel method and subsequently calcined at different temperatures. Furthermore, the particles were analyzed by TG-DSC, XRD, TEM, HRTEM, EDS, SAED and UV–Vis for investigating the influences of dopant and calcination temperature on the thermal effect, composition, morphology, energy band gap (E_g) and the degradation efficiency of methyl orange (MO) under various light irradiations respectively. Results indicated that Sn/Fe co-doping inhibited the crystallization transformation from anatase to rutile phase of TiO₂ and decreased the E_g. The increased calcination temperature and Sn/Fe co-doped effect brought about the abnormal grain growth of TiO₂ nanoparticles. 0.6 at.% Sn/0.2 at.% Fe and 1.0 at.% Sn/1.0 at.% Fe co-doped TiO₂ nanoparticles presented better photocatalytic performance than pure and 0.2 at.% Sn/0.6 at.% Fe co-doped TiO₂ nanoparticles under visible light irradiation mainly due to the decreased E_g. On the contrary, 0.2 at.% Sn and 0.6 at.% Fe co-doped TiO₂ nanoparticles calcined at 650 °C showed the most excellent photocatalytic performance under UV light irradiation, which was about twice as large as that of pure TiO₂ possibly due to the formed hybrid structure of anatase and rutile phase as well as the h⁺-mediated decomposition pathway.     

Fabrication of alumina ceramics with functional gradient structures by digital light processing 3D printing technology

Alumina ceramics with different unit numbers and gradient modes were prepared by digital light processing (DLP) 3D printing technology. The side length of each functional gradient structure was 10 mm, the porosity ratio was controlled to 70%, and the number of units were (1 × 1 × 1 unit) and (2 × 2 × 2 unit) respectively. The different gradient modes were named FCC, GFCC-1, GFCC-2 and GFCC-3. SEM, XRD, and other characterization methods proved that these gradient structures of alumina ceramics had only α-Al2O3 phase and good surface morphology. The mechanical properties and energy absorption properties of alumina ceramics with different functional gradient structures were studied by compression test. The results show that the gradient structure with 1 × 1 × 1 unit has better mechanical properties and energy absorption properties when the number of units is different. When the number of units is the same, GFCC-2 and GFCC-3 gradient structures have better compressive performance and energy absorption potential than FCC structures. The GFCC-2 gradient structure with 1 × 1 × 1 unit has a maximum compressive strength of 19.62 MPa and a maximum energy absorption value of 2.72 × 105 J/m3. The good performance of such functional gradient structures can provide new ideas for the design of lightweight and compressive energy absorption structures in the future.     

Dense and core-rim structured B4C-TiB2 ceramics with Mo-Co-WC additive

B₄C-TiB₂ ceramics (TiB₂ ranging 5~70 vol%) with Mo-Co-WC as the sintering additive were prepared by spark plasma sintering. In comparison with B₄C-TiB₂ without additive, the enhanced densification was evident in the sintered specimen with Mo-Co-WC additive. Core-rim structured grain was observed around TiB₂ grains. The interface of the rim between TiB₂ and B₄C phases demonstrated different feature: the inner borderline of the rim exhibited a smooth feature, whereas a sharp curved grain boundary was observed between the rim and the B₄C grain. The formation mechanism is discussed: the epitaxial growth of (Ti,Mo,W)B₂ rim around the TiB₂ core may occur as a result of the solid solution and dissolution-precipitation between TiB₂ phase and the sintering additive. It was revealed that the fracture toughness increased as the content of TiB₂ content increased, alongside the decreased hardness. B₄C-30 vol% TiB₂ specimen demonstrated the optimal combination of mechanical properties, reaching Vickers hardness of 24.3 GPa and fracture toughness of 3.33 MPa·m^1/2.     

Enhanced wide-activated residual network for efficient and accurate image deblocking

To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity.     

Benchmark experiment of large-angle scattering reaction cross section of iron at 14 MeV using two shadow bars – Comparison of experimental results with ENDF/B-VIII –

ABSTRACT

It is important to perform neutron transport simulations with accurate nuclear data in the neutronics design of a fusion reactor. However, absolute values of large-angle scattering cross sections vary among nuclear data libraries even for well-examined nuclide of iron. Benchmark experiments focusing on large-angle scattering cross sections were thus performed to confirm the correctness of nuclear data libraries. The series benchmark experiments were performed at a DT neutron source facility, OKTAVIAN of Osaka University, Japan, by the unique experimental system established by the authors’ group, which can extract only the contribution of large-angle scattering reactions. This system consists of two shadow bars, target plate (iron), and neutron detector (niobium). Two types of shadow bars were used and four irradiations were conducted for one experiment, so that contribution of room-return neutrons was effectively removed and only large-angle scattering neutrons were extracted from the measured four Nb reaction rates. The obtained experimental results were compared with calculations for five nuclear data libraries including JENDL-4.0, JEFF.-3.3, FENDL-3.1, ENDF/B- VII, and recently released ENDF/B-VIII. It was found from the comparison that ENDF/B-VIII showed the best result, though ENDF/B-VII showed overestimation and others are in large underestimation at 14 MeV.