Influence of SiC microstructure on its corrosion behavior in molten FLiNaK salt

The influence of the microstructure on the corrosion rate of three monolithic SiC samples in FLiNaK salt at 900 °C for 250 h was studied. The SiC samples, labeled as SiC-1, SiC-2, and SiC-3, had corrosion rates of 0.137, 0.020, and 0.043 mg/cm²h, respectively. Compared with grain size and the presence of special grain boundaries (i.e., Σ3), the content of high-angle grain boundaries (HAGBs) appeared to have the strongest influence on the corrosion rate of SiC in FLiNaK salt, since the corrosion rate increased six times as the concentration of high-angle grain boundaries increased from 19 to 32% for SiC-2 and SiC-1, respectively. These results stress the importance of controlling the content of HAGBs during the production process of SiC.     

Statistical Piezotronic Effect in Nanocrystal Bulk by Anisotropic Geometry Control

Utilizing inner-crystal piezoelectric polarization charges to control carrier transport across a metal-semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano-electromechanical system (MEMS/NEMS), human-machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress-induced piezo-potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m⁻¹ MPa⁻¹ and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.     

New insight into subcritical rupture of SiC-based filaments at intermediate temperatures (400–900 °C) under air

The delayed failure of SiC fibrous reinforcement has continuously been investigated to warrant the long term performances of Ceramic Matrix Composite (CMC). Chiefly assessed on multifilament tow samples to alleviate some handling difficulties, subcritical crack growth (SCG) parameters are however ruled by structural artifacts which hinder the identification of intrinsic filament behavior. In this paper, we propose to estimate the true filament parameters for 5 fiber types from bundle behavior using a recently communicated Monte Carlo algorithm integrating flaw and stress distributions through a deterministic fracture mechanics law under Paris’ formulation. So computed tow lifetime are broadly dispersed, encompassing raw data, and show a structure-dependent scale effect, revealed by n_filament>n_tow where n is the stress exponent. The relationship between SCG coefficient and chemical composition of the substrate is discussed and highlights the major effect of doping elements (Ti or Zr), oxygen or hydrogen content.     

碳中和背景下配电网差异化节能降耗潜力评估分

为了提高配电网差异化节能降耗效果，解决现有潜力评估方法存在的应用性能差的问题，提出碳中和背景下配电网差异化节能降耗潜力优化评估方法。根据配电网的空间结构，构建相应的等值电路模型。在该模型下，从设备损耗和运行附加损耗2个方面计算配电网的损耗量。根据损耗量计算结果，确定配电网差异化碳中和节能降耗方式。从静态和动态2个角度设置潜力评估指标，通过指标数据处理、指标权重求解等步骤，得出配电网差异化节能降耗潜力的综合量化评估结果。将设计潜力评估方法应用到配电网的差异化节能降耗改造工作中，能够有效降低配电网的实际线损量、降低区域损耗费用，并具有较高的应用价值。     

水力空化改质对重质原油沥青质及性质的影响

利用水力空化过程产生局部的高温、高压、高射流以及强大的剪切力等极端化学物理条件改质处理沙特重质原油，试验结果表明：沙特重质原油经过水力空化改质后粘度由13.61降低至7.22mm2/s，残碳由7.16%降低至6.48%，实沸点蒸馏后减压渣油降低1个百分点。进一步采用APPI FT-IR MS、XRD、FT-IR、SEM和粒度分布等技术研究了水力空化改质对沙重原油分子组成，沥青质团聚体微晶结构、沥青质胶束粒径分布、沥青质官能团、沥青质形貌等方面的影响，从分子角度阐述空化改质重油的机理。研究结果表明：水力空化改质后沙重原油分子量分布、芳烃类化合物缔合作用变小；沥青质对低DBE化合物吸附性能降低；沥青质团聚体微晶结构更加松散；沥青质胶束粒度分布降低；沥青质分子相互团聚作用力减弱。进一步考察了水力空化改质前后减压渣油延迟焦化性能，改质处理后焦炭产率降低1.85个百分点，液体收率和气体产率分别增加1.52和0.33个百分点，水力空化改质对沥青质性质、结构特点的改善能够有效的提高其加工性能。     

象山隧道液压凿岩台车开挖斜孔掏槽施工技术

新建的龙岩至厦门单线铁路象山隧道断面比较小,使用液压凿岩台车开挖,斜孔掏槽方案受到很大限制。本文介绍了使用液压凿岩台车钻爆开挖象山隧道,选择斜孔掏槽方案实现快速开挖,为类似的隧道工程施工提供经验。     

Reasonable construction of proton conducting channel via biomimetic caterpillar-like alumina fiber to improve the properties of its composite proton exchange membrane

In this paper, we prepare a novel biomimetic caterpillar-like alumina fiber with the characteristic of continuous alumina backbone and fine needle whiskers spine. Then the high-performance caterpillar-like alumina fiber composite proton exchange membrane (CAPEM) is obtained by introducing the amino modified biomimetic caterpillar-like alumina fiber into sulfonated polysulfone (SPSF) matrix, which successfully reasonable construction of the proton conducting channels in both vertical and horizontal orientation. The properties of CAPEM, including proton conductivity, methanol permeability, etc. Are systematically studied. The results show that the proton conductivity of CAPEM increases with rising the temperature, which reaches the maximum of 0.263 S/cm at 80 °C and 100% RH, respectively. The excellent proton conductivity of CAPEM is attributed to the long-range continuous proton conducting channel formed by the horizontal continuous alumina skeleton in the in-plane direction and the vertical overlapped fine needle whiskers spine in the through-plane direction. In addition, the interfacial compatibility between amino modified caterpillar-like alumina fiber and SPSF matrix is enhanced through the reasonable construction of proton conducting channels, which effectively inhibits the methanol permeation of the composite membrane with 4.18 × 10^?7 cm² s^?1 and improves the comprehensive performance of the CAPEM.     

Effects of high hydrostatic pressure on the structure and retrogradation inhibition of oat starch

As a non-thermal processing technology, high hydrostatic pressure (HHP) can be used for starch modification without affecting the quality and flavour constituents. The effect of HHP on starch is closely related to the treatment pressure of HHP. In this paper, we investigated the impacts of HHP treatment pressure (0, 100, 200, 300, 400, 500, 600 MPa) on the microstructure and retrogradation characteristics of oat starch, established the retrogradation kinetic model and elaborated the mechanism of HHP treatment inhibiting the retrogradation of oat starch. Results show that HHP treatment caused the microstructure of oat starch experienced crystallisation perfection (100–300 MPa), crystallisation destruction (400 MPa), crystallisation disintegration and gelatinisation (500–600 MPa). Results of oat starch retrogradation showed that, after treated at 500 MPa for 15 min, the recrystallisation rate of oat starch was reduced, the formation of nuclei at the early stage of oat starch retrogradation suppressed and its nucleation mode was changed from instantaneous to spontaneous, otherwise, the mobility of water in oat starch gel system reduced. Therefore, 500 MPa treated for 15 min can inhibits the retrogradation of oat starch. This study provides theoretical guidance for the application of HHP technology in starch modification and food processing.     

Analysis of pressure and heat distribution in a dilating or contracting filter chamber with two outlets using multivariate spectral quasilinearization method

The development of efficient filters is an essential part of industrial machinery design, specifically to increase the lifespan of a machine. In the filter chamber design considered in this study, the magnetic material is placed along the horizontal surface of the filter chamber. The inside of the filter chamber is layered with a porous material to restrict the outflow of unwanted particles. This study aims to investigate the flow, pressure, and heat distribution in a dilating or contracting filter chamber with two outlets driven by injection through a permeable surface. The proposed model of the fluid dynamics within the filter chamber follows the conservation equations in the form of partial differential equations. The model equations are further reduced to a steady case through Lie's symmetry group of transformation. They are then solved using a multivariate spectral-based quasilinearization method on the Chebyshev–Gauss–Lobatto nodes. Insights and analyses of the thermophysical parameters that drive optimal outflow during the filtration process are provided through the graphs of the numerical solutions of the differential equations. We find, among other results, that expansion of the filter chamber leads to an overall decrease in internal pressure and an increase in heat distribution inside the filter chamber. The results also show that shrinking the filter chamber increases the internal momentum inside the filter, which leads to more outflow of filtrates.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).