Microstructure,mechanical, tribological,and oxidizing properties of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings with different modulated thicknesses

Multilayer structure design is one of the most promising methods for improving the comprehensive performance of AlCrN-based hard coatings applied to cutting tools. In this study, four types of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings, with different modulated thicknesses, were deposited to investigate their microstructure, mechanical, tribological, and oxidizing properties. All multilayer coatings exhibited grain growth along the crystallographic plane of (200) with a NaCl-type face-centered cubic (FCC) structure. The results show that, as the modulation thickness decreases from ～35 nm to ～10 nm, (1) the grain refinement effect is increasingly evident; (2) all multilayer coatings show a hardness of >30 GPa and an elastic modulus of >300 GPa. Both the ability to resist elastic strain to failure and the plastic deformation of multilayer coatings increase. In addition, their resistance to cracking reduces; (3) the wear rates of these multilayer coatings reduce successively from 1.78 × 10^?16 m³ N^?1 m^?1 to 7.7 × 10^?17 m³ N^?1 m^?1. This is attributed to an increase in self-lubricating VO_x and a decrease in adhesives from the counterparts; (4) the best high-temperature oxidation resistance was obtained for the multilayer coating with a modulated thickness of ～15 nm.     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

Effect of mesoporous carbon on oxygen reduction reaction activity as cathode catalyst support for proton exchange membrane fuel cell

In this paper, a new carbon support with a large number of mesoporous-structures is selected to prepare Pt/C catalysts. Transmission electron microscope (TEM) results show that the Pt/3# catalyst presents a sponge-like morphology, Pt particles are not only evenly distributed on the surface of carbon support, but also the smaller Pt particles are deposited in the mesoporous inside the support. The average diameter of Pt particles is only 2.8 nm. The membrane electrode assembly (MEA) based on Pt/3# catalyst also shows excellent performance. In conclusion, the 3# support is an idea carbon support for PEMFC, which helps to improve the oxygen reduction reaction (ORR) activity of the catalyst. Based on the “internal-Pt” structure of the support mesoporous, the efficient three-phase boundaries (TPBs) are construct to avoid the poisoning effect of ionomer on the nano-metal particles, reduce the activation impedance and oxygen mass transfer impedance, and improve the reaction efficiency.     

Activation of LSCF–YSZ interface by cobalt migration during electrolysis operation in solid oxide electrolysis cells

High-temperature water electrolysis through solid oxide electrolysis cells (SOEC) will play a key role in building a hydrogen economy in the future. However, the delamination between the air electrode and the electrolyte remains a critical issue to be addressed. Previously, it was hypothesized that Co migration may improve the catalytic activity of the SrZrO₃ second phase at the LSCF-YSZ interface, eventually leading to the delamination. In this work, the LSCF-YSZ interfaces sintered at different temperatures were examined in detail. The activation behaviors of the LSCF electrodes upon application with electrolysis current were characterized under different conditions. Further, samples containing purposely added SrZrO₃ interlayer with and without cobalt were fabricated and compared. The activation process is less significant for the sample with cobalt-added SrZrO₃ interlayer than the sample with pure SrZrO₃ layer, supporting the hypothesis that Co migration may lead to the activation behavior.     

Improving gelling properties of myofibrillar proteins incorporating with cellulose micro/nanofibres

The effects of cellulose microfibres (CMFs, Average size: 100 ± 5 μm) and cellulose nanofibres (CNFs, Average size: 60 ± 3 nm) on the properties of myofibrillar protein (MP) gels from duck breast meat were studied. The results demonstrated that CMFs and CNFs were mostly connected to MP by non-covalent bonds, the diffusion and cross-linking of MP molecules was promoted, and a denser and more complete gel network was formed. With the increases of CMFs and CNFs concentration (0–10%), the hardness was increased by 13.15% and 19.78% for CMFs10% and CNFs10% gels, respectively, and the elasticity was increased by 40% and 80%, respectively. At the same concentration (0–10%), the increase in gel hardness, viscoelasticity and immobilised water content was greater in the CNFs-MP group than in the CMFs-MP group. The CNFs-MP group had a tighter gel network, and CNFs had a better potential to improve the gelation performance of MP.     

Effects of electron-beam generated X-ray irradiation on the postharvest storage quality of Agaricus bisporus

The objective of this study was to investigate the effects of electron-beam generated X-ray irradiation on the postharvest storage quality and antioxidant capacity of Agaricus bisporus. All mushrooms were treated with different doses of electron-beam generated X-ray irradiation (0, 0.5, 1.0, 1.5 and 2.0 kGy) followed by stored at 4 °C for 21 days. Results showed that when compared with the control group at the end of storage, the firmness of Agaricus bisporus treated with 1.0 kGy was increased by 43.68%, the cell membrane permeability and malondialdehyde (MDA) content were decreased by 14.48% and 32.27% respectively, and the polyphenol oxidase (PPO) activity was reduced by 44.30%. One-kGy treatment was better than the control group to maintain superoxide dismutase (SOD) and catalase (CAT) activity. The finding suggested that the dose of 1.0 kGy generated by electron beam was suitable for keeping the postharvest quality for 21 days of Agaricus bisporus.Industrial relevanceThis study stated that electron-beam generated X-ray pretreatment could be a green and safe technology to improve the overall quality of Agaricus bisporus at 4 °C for 21 days.     

低压静电场辅助冷冻对竹笋品质的影响

为研究低压静电场辅助冷冻对竹笋冻结特性的影响，以冻结曲线、硬度、水分损失率、水分迁移、冰晶形态和组织微观结构为指标，探究低压静电场辅助冷冻（－35 ℃）和普通冷冻（－35 ℃）条件下竹笋品质的变化规律。结果表明：低压静电场辅助冷冻提高了冻结效率，改变了冰晶形态及分布，减轻了组织微观结构破损程度，改善了解冻汁液流失情况。与静电板间距10、20、30、40 cm处的冷冻竹笋解冻后水分损失率分别为14.16%、12.58%、9.73%、10.44%，显著低于对照组（21.01%）（P＜0.05），硬度分别为461.19、507.48、496.65 g和455.31 g，显著高于对照组（350.70 g）（P＜0.05）。低场核磁共振分析结果表明，在低压静电场辅助冷冻下竹笋解冻后汁液流失减少，扫描电子显微镜观察结果显示，竹笋纤维排列整齐，组织微观结构保持较好。低压静电场辅助冷冻可有效改善竹笋品质，可为利用低压静电场进行果蔬的冷冻贮藏和冷链运输提供参考。     

基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

Catalytic behavior in CH4 decomposition of catalysts derived from red mud: Impact of residual Na2O

Catalyst samples for CH₄ decomposition were prepared from red mud (RM) by an acid-leaching neutralization precipitation approach. Water-washing the resultant precipitates multiple times, followed by drying at 105 °C and calcination at 500 °C, resulted in a threshold of residual Na₂O, equivalent to 96% Na₂O removal. Drying the precipitate at a higher temperature of 200 °C, followed by repeated water washing, provided a deeper Na₂O removal of 99% and made the resultant samples more active for the targeted reaction. Subsequently, four catalyst samples with a simulated red mud composition and NaOH contents from 0 to 0.3 wt% were prepared and the catalytic test results revealed that the Na₂O remaining in the RM-derived catalysts did not only inhibit their activation in CH₄ but also lower their maximal activities for CH₄ decomposition. Finally, two catalysts with the same simulated red mud composition and their Na impregnated respectively on Fe₂O₃ and a mixture support of Al₂O₃-SiO₂-TiO₂ were prepared and tested to explore the effect of Na distribution on the activation behavior of RM-derived catalysts for CH₄ decomposition. The activity testing results showed that it was the Na residual dispersed on iron oxides in the RM-derived samples to significantly inhibit the activation of CH₄ decomposition.