A new perspective of co-doping and Nd segregation effect on proton stability and transportation in Y and Nd co-doped BaCeO3

Bulk and surface properties of proton stability and transportation in Y and Nd co-doped BaCeO₃ (BCYN), especially the effect of Nd segregation, were investigated by first-principles calculations. Since the structure of doped BaCeO₃ at the operating temperature of proton-conducting has been unclear for a long time, we have summarized the latest experimental results and calculated the structure of the asymmetric BCYN for the first time. The results show that compared with Y, Nd doping promotes oxygen vacancy formation, however reduces proton stability. Our calculation can also provide a possible explanation for the formation of space charge layer at the grain boundary of doped BaCeO₃ in experiment. Unlike the stable Y in BCYN, Nd is calculated to be easily segregated, which can facilitate both proton hydration and proton transportation near the surface. Moreover, Nd segregation at the grain boundary is predicted to be beneficial for proton transportation between grains.     

Microstructural and electrical changes in Ca0.9R0.1CeNbMoO8 (R = Y,Sm, Nd,La) ceramics induced by rare-earth ion doping

Rare-earth ions doped Ca_0.9R_0.1CeNbMoO₈ (R = Y, Sm, Nd, La) ceramics have been successfully prepared by solid-state method, and their modifications to the microstructure and electrical properties are also investigated. The rare-earth ions doped ceramics exhibit the scheelite structure. With the increase in the radius of rare-earth ions, the lattice distortion and bond interaction will be enhanced, and the consistency of grain size will be reduced. The ceramics exhibit negative temperature coefficient (NTC) thermistor characteristics in the temperature range of 473 K-1273 K, and the activation energy decreases with the increase of the radius of rare-earth ions. Rare-earth ions doping can increase the content of Ce³⁺ ions and promote the conductivity of ceramics. Except for Sm³⁺-doped ceramics, the high-temperature aging rate of other ceramics is less than 2%. The existence of some metastable Sm²⁺ ions in Sm³⁺-doped ceramics not only increases the activation energy, but also reduces the high-temperature stability of the ceramics.     

射频电缆的幅相稳定性测试研究

对射频电缆幅相稳定性进行了介绍,阐述了射频测试电缆相位和幅度变化的因素,并详细分析了射频电缆相位性能以及幅度性能的不同测试方法,最后通过实测数据的展示,总结说明了在日常测试中该如何正确使用测试电缆。     

毒品滥用流行病模型的稳定性分析

现有毒品滥用流行病模型假设吸毒者康复后对毒品拥有永久"免疫"力，而忽视了其再次成为毒品易感者的可能性。针对这一问题，通过考虑社区治疗和隔离治疗两种措施，分析了毒品滥用人群的演化过程，提出了基于暂时"免疫"力的毒品滥用流行病模型，并计算了模型的基本再生数，讨论了模型平衡点的存在性和稳定性。当基本再生数小于1时，模型存在一个局部渐进稳定的无毒平衡点；当基本再生数大于1时，模型存在唯一的地方病平衡点，并利用几何方法证明了地方病平衡点的全局稳定性；当基本再生数等于1时，如果满足一定条件，模型出现后向分支现象。数值模拟验证了上述所有结果。研究结果表明提高隔离治疗率、改善社区治疗效果和降低接触传染率可以有效抑制毒品滥用的流行。     

Effect of Ni/tubular g-C3N4 on hydrogen storage properties of MgH2

Additive doping is one of the effective methods to overcome the shortcomings of MgH₂ on the aspect of relatively high operating temperatures and slow desorption kinetics. In this paper, hollow g-C₃N₄ (TCN) tubes with a diameter of 2 μm are synthesized through the hydrothermal and high-temperature pyrolysis methods, and then nickel is chemically reduced onto TCN to form Ni/TCN composite at 278 K. Ni/TCN is then introduced into the MgH₂/Mg system by means of hydriding combustion and ball milling. The MgH₂–Ni/TCN composite starts to release hydrogen at 535 K, which is 116 K lower than the as-milled MgH₂ (651 K). The MgH₂–Ni/TCN composite absorbs 5.24 wt% H₂ within 3500 s at 423 K, and takes up 3.56 wt% H₂ within 3500 s, even at a temperature as low as 373 K. The apparent activation energy (E_a) of the MgH₂ decreases from 161.1 to 82.6 kJ/mol by the addition of Ni/TCN. Moreover, the MgH₂–Ni/TCN sample shows excellent cycle stability, with a dehydrogenation capacity retention rate of 98.0% after 10 cycles. The carbon material enhances sorption kinetics by dispersing and stabilizating MgH₂. Otherwise, the phase transformation between Mg₂NiH₄ and Mg₂NiH_0.3 accelerates the re/dehydrogenation reaction of the composite.     

Classic and inverse compositional Gauss-Newton in global DIC

Today, effective implementations of digital image correlation (DIC) are based on iterative algorithms with constant linear operators. A relevant idea of the classic finite element (or, more generally, global) DIC solver consists in replacing the gradient of the deformed state image with that of the reference image, so as to obtain a constant operator. Different arguments (small strains, small deformations, equality of the two gradients close to the solution, etc) have been given in the literature to justify this approximation, but none of them are fully accurate. Indeed, the convergence of the optimization algorithm has to be investigated from its ability to produce descent directions. Through such a study, this paper attempts to explain why this approximation works and what is its domain of validity. Then, an inverse compositional Gauss-Newton implementation of finite element DIC is proposed as a cost-effective and mathematically sound alternative to this approximation.     

On global Hessenberg based methods for solving Sylvester matrix equations

In the first part of this paper, we investigate the use of Hessenberg-based methods for solving the Sylvester matrix equation $AX+XB=C$. To achieve this goal, the Sylvester form of the global generalized Hessenberg process is presented. Using this process, different methods based on a Petrov–Galerkin or on a minimal norm condition are derived. In the second part, we focus on the SGl-CMRH method which is based on the Sylvester form of the Hessenberg process with pivoting strategy combined with a minimal norm condition. In order to accelerate the SGl-CMRH method, a preconditioned framework of this method is also considered. It includes both fixed and flexible variants of the SGl-CMRH method. Moreover, the connection between the flexible preconditioned SGl-CMRH method and the fixed one is studied and some upper bounds for the residual norm are obtained. In particular, application of the obtained theoretical results is investigated for the special case of solving linear systems of equations with several right-hand sides. Finally, some numerical experiments are given in order to evaluate the effectiveness of the proposed methods.     

Impact of high-intensity ultrasound on physical properties and degree of oxidation of lipase modified menhaden oil with caprylic acid and/or stearic acid

The purpose of this research was to determine the effect of high-intensity ultrasound (HIU) on physical properties, degree of oxidation, and oxidative stability of structured lipids (SLs). Caprylic acid (C) and stearic acid (S) were incorporated into menhaden oil using Lipozyme® 435 lipase to obtain five samples: (1) LC 20 (menhaden oil with 20% of C), (2) LC 30 (menhaden oil with 30% C), (3) LS 20 (menhaden oil with 20% S), (4) LS 30 (menhaden oil with 30% S), and (5) Blend C (menhaden oil with 16.24% C and 13.04% S). Samples were crystallized for 90 min at the following temperatures: (1) LC 20 at 15.5°C, (2) LC 30 at 17.5°C, (3) LS 20 at 24°C, (4) LS 30 at 30°C, and (5) Blend C at 18.0°C, and HIU was applied at the onset of crystallization. Physical properties, degree of oxidation, and oxidative stability were evaluated in sonicated and nonsonicated samples. All SLs had statistically higher G′ after sonication. Sonicated LS 30, LC 30, and Blend C had a higher melting enthalpy than the nonsonicated ones, while enthalpy values in sonicated LS 20 and LC 20 samples were not statistically different than the nonsonicated ones. No significant difference between sonicated and nonsonicated samples was observed in peroxide values (1.2 ± 0.1 meq/kg, p > 0.05) and in the oxidative stability index (6.3 ± 0.2 h, p > 0.05). These results showed that HIU was effective at changing physical properties without affecting the oxidation of the samples.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

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.     

Preparation of a CeO2–ZrO2 based nano-composite with enhanced thermal stability by a novel chelating precipitation method

In this study, a chelating agent is introduced to prepare CeO₂–ZrO₂ nano-composite through a precipitation process. The physicochemical properties of the oxide precursors, nano composite materials are strongly dependent on the preparation method and whether a chelating agent is used. Adding an appropriate quantity of chelating agent SO₄²⁻ can facilitate thermal stability and phase structure uniformity of CeO₂–ZrO₂ mixed oxides. The calculation results showed that the Gibbs free energy of chelating complex of [ZrSO₄]²⁺ (ΔG = −127.2469 kJ/mol) is higher than the [Ce(III)SO₄]⁺ (ΔG = -29.8279 kJ/mol). The precipitation chemical potential of Zr⁴⁺ moves close to the precipitation chemical potential of Ce³⁺. The novel and low-cost chelating precipitation method can modify the homogeneity of the compounds at the atomic scale, which can offer a powerful opportunity for, and provide direction in, the design of materials with exceptional properties.