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1.
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
2.
《International Journal of Hydrogen Energy》2022,47(100):42280-42292
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
3.
《International Journal of Hydrogen Energy》2022,47(80):33919-33937
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
4.
《International Journal of Hydrogen Energy》2022,47(84):35641-35654
The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty. 相似文献
5.
《International Journal of Hydrogen Energy》2022,47(94):39961-39972
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
6.
A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone. 相似文献
7.
边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明:和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。 相似文献
8.
《Advanced Powder Technology》2022,33(12):103847
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
9.
《International Journal of Hydrogen Energy》2022,47(11):6975-6985
A technology for cyclic generation of hydrogen and oxygen using electrodes made of variable valency material that does not need the use of separating ion-exchange membranes is presented. The technological solution enables to fabricate electrolyzers for uninterrupted producing high-pressure hydrogen with reduced energy intensity of the production. The total work for compressing 1 m3 of hydrogen and 0.5 m3 of oxygen has been estimated. Results of investigation of influence of discrete supply of DC current to the electrolysis cell, in order to improve the processes of gas evolution and to simplify the power systems of the electrolysis plant, have been considered. There is also considered an electrolysis installation equipped with a thermosorption compressor in which LaNi5 is used as a hydride-forming compound. The comparative characteristics of the developed electrolyzer and the currently used hydrogen generators are given. 相似文献
10.
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (Tg) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (nd) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high nd (1.7 or more) and low Tg (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses. 相似文献