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High-purity mullite ceramics, promising engineering ceramics for high-temperature applications, were fabricated using transient liquid phase sintering to improve their high-temperature mechanical properties. Small amounts of ultrafine alumina or silica powders were uniformly mixed with the mullite precursor depending on the silica-alumina ratio of the resulting ceramics to allow for the formation of a transient liquid phase during sintering, thus, enhancing densification at the early stage of sintering and mullite formation by the reaction between additional alumina and the residual glassy phase (mullitization) at the final stage of sintering. The addition of alumina powder to the silica-rich mullite precursor resulted in a reaction between the glassy silica and alumina phases during sintering, thereby forming a mullite phase without inhibiting densification. The addition of fine silica powder to the mullite single-phase precursor led to densification with an abnormal grain growth of mullite, whereas some of the added silica remained as a glassy phase after sintering. The resulting mullite ceramics prepared using different powder compositions showed different sintering behaviors, depending on the amount of alumina added. Upon selecting an optimum process and the amount of alumina to be added, the pure mullite ceramics obtained via transient liquid phase sintering exhibited high density (approximately 99%) and excellent high-temperature flexural strength (approximately 320 MPa) at 1500 °C in air. These results clearly demonstrate that pure mullite ceramics fabricated via transient liquid phase sintering with compositions close to those of stoichiometric mullite could be a promising process for the fabrication of high-temperature structural ceramics used in an ambient atmosphere. The transient liquid phase sintering process proposed in this study could be a powerful processing tool that allows for the preparation of superior high-temperature structural ceramics used in the ambient processing atmosphere.  相似文献   
3.
In this study, the separation of hydrogen from gas mixtures using a palladium membrane coupled with a vacuum environment on the permeate side was studied experimentally. The gas mixtures composed of H2, N2, and CO2 were used as the feed. Hydrogen permeation fluxes were measured with membrane operating temperature in the range of 320–380 °C, pressures on the retentate side in the range of 2–5 atm, and vacuum pressures on the permeate side in the range of 15–51 kPa. The Taguchi method was used to design the operating conditions for the experiments based on an orthogonal array. Using the measured H2 permeation fluxes from the Taguchi approach, the stepwise regression analysis was also employed for establishing the prediction models of H2 permeation flux, followed by the analysis of variance (ANOVA) to identify the significance and suitability of operating conditions. Based on both the Taguchi approach and ANOVA, the H2 permeation flux was mostly affected by the gas mixture composition, followed by the retentate side pressure, the vacuum degree, and the membrane temperature. The predicted optimal operating conditions were the gas mixture with 75% H2 and 25% N2, the membrane temperature of 320 °C, the retentate side pressure of 5 atm, and the vacuum degree of 51 kPa. Under these conditions, the H2 permeation flux was 0.185 mol s?1 m?2. A second-order normalized regression model with a relative error of less than 7% was obtained based on the measured H2 permeation flux.  相似文献   
4.
Development of efficient, low cost and multifunctional electrocatalysts for water splitting to harvest hydrogen fuels is a challenging task, but the combination of carbon materials with transition metal-based compounds is providing a unique and attractive strategy. Herein, composite systems based on cobalt ferrite oxide-reduced graphene oxide (Co2FeO4) @(rGO) using simultaneous hydrothermal and chemical reduction methods have been prepared. The proposed study eliminates one step associated with the conversion of GO into rGO as it uses direct GO during the synthesis of cobalt ferrite oxide, consequently rGO based hybrid system is achieved in-situ significantly, the optimized Co2FeO4@rGO composite has revealed an outstanding multifunctional applications related to both oxygen evolution reaction (OER) and hydrogen counterpart (HER). Various metal oxidation states and oxygen vacancies at the surface of Co2FeO4@rGO composites guided the multifunctional surface properties. The optimized Co2FeO4@rGO composite presents excellent multifunctional properties with onset potential of 0.60 V for ORR, an overpotential of 240 mV at a 20 mAcm?2 for OER and 320 mV at a 10 mAcm?2 for HER respectively. Results revealed that these multifunctional properties of the optimized Co2FeO4@ rGO composite are associated with high electrical conductivity, high density of active sites, crystal defects, oxygen vacancies, and favorable electronic structure arisinng from the substitution of Fe for Co atoms in binary spinel oxide phase. These surface features synergistically uplifted the electrocatalytic properties of Co2FeO4@rGO composites. The multifunctional properties of the Co2FeO4@ rGO composite could be of high interest for its use in a wide range of applications in sustainable and renewable energy fields.  相似文献   
5.
This work develops a novel magnetic photocatalysts ZnO/SrFe12O19 (ZS) synthesized with hydrothermal process. The introduction of SrFe12O19 not only enhances the photocatalytic behavior of ZnO towards Rhodamine B (RhB) decomposition, but also reinforces the recycling stability. Especially, ZS-5 composite exhibits the optimal photocatalytic performance, and the RhB decomposition reaches 99.5% after being exposed to simulative sunlight for 70 min, which is obviously superior to that of bare ZnO. Furthermore, the ZS-5 can be recovered from RhB solution by an extra magnet space and reused. After five recycles, the RhB removal efficiency can still be maintained over 90%. Such prominent photocatalytic property and stability of ZS-5 are associated with the greatly improved detachment efficiency of photoexcited carriers in a magnetic field. This study could provide a new-type recyclable photocatalyst that can effectively purify dye wastewater for convenient recovery.  相似文献   
6.
Micro-cracks commonly occur on the catalyst layers (CLs) during the manufacturing of catalyst coated membranes (CCMs). However, the crack shape parameters effect on CLs in-plane (IP) electronic conductivity λs is not clear. In this work, the relationship between crack parameters and the λs is obtained based on the two-dimensional (2D) multiple-relaxation time (MRT) lattice Boltzmann method (LBM). The LBM numerical model is validated by the normalized λs experiment applied on three different home-made cracked CLs, and the parameter study focus on crack width, length, quantity and phase angle are carried out. The results show that the decrease of λs has different sensitivity |k| to the parameters above. The crack width has little effect on λs decrease, and the |kw| is 0.038. However, crack arm length and quantity show more significant impact, which |kl| and |kN| are 0.753 and 0.725, respectively. The CLs with different crack propagation directions show significant anisotropy on λs, and a 53.53% decrease in λs is observed between 0° and 90° crack phase angle change. To manufacture a high electronic conductivity CL, crack initiation and migration mitigation are highly encouraged.  相似文献   
7.
本文主要总结了新冠疫情期间作者的电磁场理论课程在线教学经验。对比分析了录播和直播的优缺点后,选择录播教学方式。基于超星网络教学平台,展示了录播网络教学的具体措施,包括网上答疑和学习效果检查以及在线批改作业等。给出了网络教学可以为线下教学继续使用的方法和手段,为疫情结束后的正常教学提供了新的网络教学补充措施。  相似文献   
8.
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。  相似文献   
9.
We investigate synthesis, phase evolution, hollow and porous structure and magnetic properties of quasi-amorphous intermediate phase (QUAIPH) and hematite (α-Fe2O3) nanostructure synthesized by annealing of akaganeite (β-FeOOH) nanorods. It is found that the annealing temperature determines the phase composition of the products, the crystal structure/size dictates the magnetic properties whereas the final nanorod morphology is determined by the starting material. Annealing of β-FeOOH at ~300 °C resulted in the formation of hollow QUAIPH nanorods. The synthesized material shows low-cytotoxicity, superparamagnetism and good transverse relaxivity, which is rarely reported for QUAIPH. The QUAIPH nanorods started to transform to porous hematite nanostructures at ~350 °C and phase transformation was completed at 600 °C. During the annealing, the crystal structure changed from monoclinic (akaganeite) to quasi-amorphous and rhombohedral (hematite). Unusually, the crystallite size first decreased (akaganeite → QUAIPH) and then increased (QUAIPH → hematite) during annealing whereas the nanorods retained particle shape. The magnetic properties of the samples changed from antiferromagnetic (akaganeite) to superparamagnetic with blocking temperature TB = 84 K (QUAIPH) and finally to weak-ferromagnetic with the Morin transition at TM = 244 K and high coercivity HC = 1652 Oe (hematite). The low-cytotoxicity and MRI relaxivity (r2 = 5.80 mM?1 s?1 (akaganeite), r2 = 4.31 mM?1 s?1 (QUAIPH) and r2 = 5.17 mM?1 s?1 (hematite)) reveal potential for biomedical applications.  相似文献   
10.
In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.  相似文献   
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