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1.
《International Journal of Hydrogen Energy》2022,47(10):6755-6766
Mg-based hydride is a promising hydrogen storage material, but its capacity is hindered by the kinetic properties. In this study, Mg–Mg2Ni–LaHx nanocomposite is formed from the H-induced decomposition of Mg98Ni1·67La0.33 alloy. The hydrogen capacity of 7.19 wt % is reached at 325 °C under 3 MPa H2, attributed to the ultrahigh hydrogenation capacity in Stage I. The hydrogen capacity of 5.59 wt % is achieved at 175 °C under 1 MPa H2. The apparent activation energies for hydrogen absorption and desorption are calculated as 57.99 and 107.26 kJ/mol, which are owing to the modified microstructure with LaHx and Mg2Ni nanophases embedding in eutectic, and tubular nanostructure adjacent to eutectic. The LaH2.49 nanophase can catalyze H2 molecules to dissociate and H atoms to permeate due to its stronger affinity with H atoms. The interfaces of these nanophases provide preferential nucleation sites and alleviate the “blocking effect” together with tubular nanostructure by providing H atoms diffusion paths after the impingement of MgH2 colonies. Therefore, the superior hydrogenation properties are achieved because of the rapid absorption process of Stage I. The efficient synthesis of nano-catalysts and corresponding mechanisms for improving hydrogen storage properties have important reference to related researches. 相似文献
2.
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
3.
《International Journal of Hydrogen Energy》2022,47(12):7836-7845
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. 相似文献
4.
Shilin Du Yichen Dong Feiqiang Guo Beile Tian Songbo Mao Lin Qian Chengyun Xin 《International Journal of Hydrogen Energy》2021,46(27):14138-14147
The potential of using high metals containing coal gangue and lignite to prepare high-activity coal char-based catalysts is investigated for effective biomass tar decomposition. Loose structure and rough surface are formed for these char-based catalysts with heterogeneous distribution of a large number of inorganic particles. In the biomass tar decomposition, the performance of the coal char-based catalysts is significantly influenced by the content of the metals in the raw materials and coal gangue char (GC) with the ash content as high as 50.80% exhibits the highest activity in this work. A high biomass tar conversion efficiency of 93.5% is achieved at 800 °C along with a significant increase in the fuel gas product. During the five-time consecutive tests, the catalytic performance of GC increases a little at the second or third times reuse and remains relatively stable, showing the remarkable stability of the catalyst in biomass tar decomposition applications. 相似文献
5.
磁声发射(MAE)是铁磁性材料磁化过程中产生的声发射信号,在构件应力检测和微观损伤检测中有着广泛的应用。针对MAE信号非稳态、复杂性、衰减性等特点,提出海鸥算法结合变分模态分解(SOA-VMD)的去噪方法,为克服海鸥算法求解过程中易陷入局部最优解问题,利用柯西变异算子产生随机迭代过程,使改进算法即柯西变异海欧算法(CVSOA)跳出早熟收敛。采用以幅值谱熵为适应度函数,优化VMD算法中分解模态个数K和二次惩戒因子α ![]()
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两个参数,将含噪声的MAE信号进行VMD分解重构。经仿真信号和实际检测信号分析表明,改进后的CVSOA-VMD算法全局寻优能力和去噪性能优于传统的SOA-VMD算法,降噪后的MAE信号特征值对于不同应力下均方根、偏斜度特征值的重复性更好,可靠性更高。 相似文献
6.
Hydrogen production via ammonia decomposition catalyzed by Ni/M–Mo–N (M = Ni,Co) bimetallic nitrides
《International Journal of Hydrogen Energy》2022,47(77):32893-32902
This study demonstrates the significant improvement in NH3 decomposition using Ni-decorated M–Mo–N-based catalysts (M = Co and Ni) compared with conventional catalysts. Catalysts are prepared using a mixture of the corresponding metal salts and hexamethylenetetramine, and the impregnation method is used to decorate the Ni-particles on the catalysts. Among all the samples, 10 wt% Ni-decorated Co3Mo3N exhibits the highest NH3 conversion rate (71%) at 500 °C, and the performance remains stable for 30 h of long-term testing. According to the gas chromatography measurements, the H2/N2 ratio is approximately 3 in all cases, which is consistent with the theoretical value. X-ray photoelectron spectroscopy results show that Co3Mo3N possesses the highest NH3 conversion efficiency because of the weaker binding energy of Mo–N. Furthermore, Co3Mo3N exhibits a stronger Lewis acidity and higher NH3 decomposition, which is attributed to the easy breaking of the N–H bond on the Co3Mo3N surface. 相似文献
7.
Yasoub Eghbali Mahmoud Ferdosizade Naeiny 《International Journal of Communication Systems》2020,33(14)
In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals. 相似文献
8.
In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model. 相似文献
9.
为提高稀疏表示跟踪模型性能,提出一种分段加权的反向稀疏跟踪算法,将跟踪问题转化为在贝叶斯框架下寻找概率最高的候选对象问题,构造不同的分段权重函数来分别度量候选目标与正负模板的判别特征系数。通过池化来降低跟踪结果的不确定性干扰,选择正负模板加权系数差值最大的候选表示作为跟踪结果。实验表明,在光照变化、遮挡、快速运动、运动模糊情况下,所提出的算法可以确保跟踪结果的准确性和鲁棒性。 相似文献
10.
Anis Zeglaoui Anouar Houmia Maher Mejai Radhouane Aloui 《International Journal of Adaptive Control and Signal Processing》2021,35(9):1842-1859
In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method. 相似文献