Optimization of hydrogen enrichment via palladium membrane in vacuum environments using Taguchi method and normalized regression analysis

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.     

Recent progress of electrocatalysts for hydrogen proton exchange membrane fuel cells

Due to stringent environmental regulations and the limited resources of fossil-based fuels, there is an urgent demand for clean and eco-friendly energy conversion devices. These criteria appear to be met by hydrogen proton exchange membrane fuel cells (PEMFCs). PEMFCs have attracted tremendous attention on account of their excellent performance with tunable operability and good portability. Nonetheless, their practical applications are hugely influenced by the scarcity and high cost of platinum (Pt) used as electrocatalysts at both cathode and anode. Pt is also susceptible to easy catalyst poisoning. Herein, this paper reviews the progress of the research regarding the development of electrocatalysts practically used in hydrogen PEMFCs, where the corner-stone reactions are cathodic oxygen reduction reaction (ORR) and anodic hydrogen oxidation reaction (HOR). To reduce the costs of PEMFCs, lessening or eliminating the use of Pt is of prime importance. For current and forthcoming laboratory/large-scale PEMFCs, there is much interest in developing substitute catalysts based on cheaper materials. As such are non-platinum (non-Pt), non-platinum group metals (non-PGMs), metal oxides, and non-metal electrocatalysts. Hence, high-performance, state-of-the-art, and novel structured electrocatalysts as replacements for Pt are needed.     

Increased hydroxyl concentration by tungsten oxide modified h-BN promoted catalytic performance in partial oxidation of methane

Hexagonal boron nitride (h-BN) as a layered inorganic nonmetallic material has been widely used. Hydrogen peroxide (H₂O₂) modification can trigger exfoliation and afford abundant B–OH active sites at edge of h-BN, which can enhance methane activation ability. Introducing tungsten oxide (WO₃) to h-BN produces a similar effect, because doping WO₃ into h-BN resulted in electron transfer to N, inducing fracture of B–N bond, resulting in N vacancy (triboron center), exposing more B sites and promoting the generation of B–OH. Significantly, the introduction of WO₃ on the modified h-BN dramatically increased the concentration of B–OH compared with the unmodified h-BN, because H₂O₂ modification weakened B–N bond. By means of XRD, TEM, XPS,EPR, FT-IR, it is proved that the high concentration of B–OH active sites contributed to activating C–H bond, thus methane conversion and CO and H₂ selectivity were significantly improved.     

Volatile and non-volatile compound profiles of commercial sweet pickled mango and its correlation with consumer preference

Sweet pickled mango named Ma-Muang Bao Chae-Im is a traditional preserved mango from Hat Yai, Thailand. This study investigated (I) volatile and non-volatile compound profiles of commercial Ma-Muang Bao Chae-Im and (II) their relationship to consumer preference. Untargeted metabolomics profiling was performed by gas chromatography-mass quadrupole-time of flight analysis. There were 117 volatile and 44 non-volatile compounds annotated in six commercial brands of Ma-Muang Bao Chae-Im. Furthermore, 46 volatile and 19 non-volatile compounds’ discriminant markers were found by Partial least square discriminant analysis. Among those markers, sorbic and benzoic acid were observed in several brands; moreover, the combination of both compounds altered the volatile profile, especially the ester group. Partial least square regression revealed that overall consumer liking is correlated to 1-heptanol; 1-octanol; acetoin; acetic acid, 2-phenylethyl ester; D-manitol; terpenes and terpenoids, while firmness to sucrose and L-(-)-sorbofuranose. On the other hand, most ester compounds were not related to consumer preference.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

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。     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

Numerical simulation of water and heat transport in the cathode channel of a PEM fuel cell

Cathode channel of a PEM fuel cell is the critical domain for the transport of water and heat. In this study, a mathematical model of water and heat transport in the cathode channel is established by considering two-phase flow of water and air as well as the phase change between water and vapor. The transport process of the species of air is governed by the convection-diffusion equation. The VOSET (coupled volume-of-fluid and level set method) method is used to track the interface between air and water, and the phase equilibrium method of water and vapor is employed to calculate the mass transfer rate on the two-phase interface. The present model is validated against the results in the literature, then applied to investigate the characteristics of two-phase flow and heat transfer in the cathode channel. The results indicate that in the inlet section, water droplets experience three evolution stages: the growing stage, the coalescence stage and the generation stage of dispersed water drops. However, in the middle and outlet sections of the channel, there are only two stages: the growth of water droplets, and the formation of a water film. The mass transfer rate of phase change in the inlet section of the channel varies over time, exhibiting an initial increase, a decrease followed, and a stabilization finally, with the maximum and stable values of 1.78 × 10^?4 kg/s and 1.52 × 10^?4 kg/s for Part 1, respectively. In the middle and outlet sections, the mass transfer rate increase firstly and then keeps stable gradually. Furthermore, regarding the distribution of the temperature and vapor mass fraction in the channel, near the upper surface of the channel, the temperature and vapor mass fraction first change slightly (x < 0.03 m) and then rapidly decrease with fluctuations (x > 0.03 m). In the middle of the channel, the temperature and vapor mass fraction slowly decrease with fluctuation.     

A dotted nanowire arrayed by 5 nm sized palladium and nickel composite nanopaticles showing significant electrocatalytic activity towards ethanol oxidation reaction (EOR)

To the best of our knowledge, this is the first time to report the preparation of a dotted nanowire arrayed by 5 nm sized palladium and nickel composite nanoparticles (denoted as Pd_xNi_y NPs) via a hydrothermal method using NU and PdO·H₂O as the starting materials. The samples prepared at the mass ratio of NU to PdO·H₂O 1:1, 1:2 and 2:1 were, respectively, nominated as catalyst c₁, c₂ and c₃. The chemical compositions of all synthesized catalysts were mainly studied by using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), revealing that metallic Ni was one main component of all prepared catalysts. Surprisingly, the main diffraction peaks appearing in the XRD patterns of all prepared catalysts were assigned to the metallic Ni rather than the metallic Pd. Very interestingly, as indicated by the TEM images, a large number of dotted nanowires arrayed by numerous equidistant 5 nm sized nanoparticles were distinctly exhibited in catalyst c₁. More importantly, when being used as electrocatalysts for EOR, all prepared catalysts exhibited an evident electrocatalytic activity towards EOR. In the cyclic voltammetry (CV) test, the peak current density of the forward peak of EOR on catalyst c₁ measured at 50 mV s^?1 was as high as 56.1 mA cm^?2, being almost 9 times higher than that of EOR on catalyst c₃ (6.3 mA cm^?2). Particularly, the polarized current density of EOR on catalyst c₁ at 3600 s, as indicated by the chronoamperometry (CA) experiment, was still maintained to be around 1.47 mA cm^?2, a value higher than the latest reported data of 1.3 mA cm^?2 (measured on the pure Pd/C electrode). Presenting a novel method to prepare dotted nanowires arranged by 5 nm sized nanoparticles and showing the significant eletrocatalytic activities of the newly prepared dotted nanowires towards EOR were the major contributions of this preliminary work.     

Investigation of stress fields for non-standard sized glass plates loaded by ring-on-ring

A ring-on-ring (ROR) test is a prevailing test method for evaluating the equi-biaxial strength of glass materials. However, current ROR test standards limit the strength and size of glass to prevent a nonlinear behavior. In this study, the feasibility of ROR testing for non-standard, high-strength glass, such as tempered or ion-exchanged rectangular glass is investigated. To this end, ROR simulation based on theory and experiment is conducted for thirty non-standard glasses with widths of 100–300 mm and aspect ratios of 1.0–2.0. As a result, the maximum measurable stress was about 215.6 MPa for 100 × 200 mm glass and 481.3 MPa for 300 × 600 mm glass with a 3% deviation, which is well above the strength of regular tempered glass. The main purpose of this work is to understand the range of aspect ratio of horizontal and vertical widths of a glass plate that can be evaluated by the standard ROR test.     

High-temperature oxidation behavior of monolithic Zr3[Al(Si)]4C6 and its composite incorporating 30vol% ZrB2-SiC: Providing a basis for broadening the service temperature

To provide a basis for the high-temperature oxidation of ultra-high temperature ceramics (UHTCs), the oxidation behavior of Zr₃[Al(Si)]₄C₆ and a novel Zr₃[Al(Si)]₄C₆-ZrB₂-SiC composite at 1500 °C were investigated for the first time. From the calculation results, the oxidation kinetics of the two specimens follow the oxidation dynamic parabolic law. Zr₃[Al(Si)]₄C₆ exhibited a thinner oxide scale and lower oxidation rate than those of the composite under the same conditions. The oxide scale of Zr₃[Al(Si)]₄C₆ exhibited a two-layer structure, while that of the composite exhibited a three-layer structure. Owing to the volatilization of B₂O₃ and the active oxidation of SiC, a porous oxide layer formed in the oxide scale of the composite, resulting in the degradation of its oxidation performance. Furthermore, the cracks and defects in the oxide scale of the composite indicate that the reliability of the oxide scale was poor. The results support the service temperature of the obtained ceramics.