Ir-Pt/C composite with high metal loading as a high-performance anti-reversal anode catalyst for proton exchange membrane fuel cells

Voltage reversal induced by hydrogen starvation can severely corrode the anode catalyst support and deteriorate the performance of proton exchange membrane fuel cells. A material-based strategy is the inclusion of an oxygen evolution reaction catalyst (e.g., IrO₂) in the anode to promote water electrolysis over harmful carbon corrosion. In this work, an Ir-Pt/C composite catalyst with high metal loading is prepared. The membrane-electrode-assembly (MEA) with 80 wt% Ir-Pt(1:2)/C shows a first reversal time (FRT) of up to 20 hours, which is about ten times that of MEA with 50 wt% Ir-Pt(1:2)/C does. Furthermore, the MEA with 80 wt% Ir-Pt(1:2)/C exhibits a minimum cell voltage loss of 6 mV@1 A/cm² when the FRT is terminated in 2 hours, in which the MEA with 50 wt% Ir-Pt(1:2)/C exhibits a voltage loss of 105 mV@1 A/cm². Further physicochemical and electrochemical characterizations demonstrate that the destruction of anode catalyst layer caused by the voltage reversal process is alleviated by the use of the composite catalyst with high metal loading. Hence, our results reveal that the combination of OER catalyst on the Pt/C with high metal loading is a promising approach to alleviate the degradation of anode catalyst layer during the voltage reversal process for PEMFCs.     

Ferulic acid and EGCG alter the structural characteristics of ovalbumin and its application in mineral loading

This study aims to fabricate mineral-loading nanocarriers using natural materials. The interaction patterns between ovalbumin (OVA) and four water-soluble polyphenols, namely ferulic acid (FA), (-)-Epigallo-catechin 3-gallate (EGCG), gallic acid (GA) and epicatechin (EC), were investigated. Results showed that the optimised conditions for preparing stable OVA–polyphenol complexes are at the OVA–polyphenol ratio of 4:1 at pH 6, under which OVA–FA and OVA–EGCG showed the highest stability and mineral-loading capacity among four OVA–polyphenol complexes. The fluorescence results indicated that the addition of EGCG and FA induced a significant fluorescence quenching to OVA. The interaction between OVA and polyphenols involved hydrogen bonding, hydrophobic interaction and electrostatic interaction. Fourier transform infrared spectroscopy (FTIR) analysis suggested that both FA and EGCG enhanced the stability and orderliness of the structure of OVA. The transmission electron microscopy images also exhibited the spherical structure of OVA after the addition of FA and EGCG. Furthermore, scanning electron microscope–energy dispersive X-ray spectrum results suggested that OVA–FA and OVA–EGCG complexes were better mineral carriers than OVA–GA and OVA–EC. This study may serve as the theoretical support for the promising application of OVA in the fabrication of mineral-loading nanocarriers in functional food and pharmaceutic.     

Evaluation of a sulfidogenic system fed with microalgal biomass of Chlorella pyrenoidosa as an electron donor: Sulfate reduction kinetics

In this study, a sulfidogenic reactor fed with microalgal biomass of Chlorella pyrenoidosa as an electron donor was operated in a continuous mode. This study evaluated the influence of various initial sulfate concentration from 1.0 to 2.5 g/L on anaerobic sulfate reduction kinetics by a sulfidogenic enrichment culture predominantly Desulfovibrio sp. VSV2. It was observed that volumetric sulfate reduction rate (VSRR) was consistently increasing with an increase in volumetric sulfate loading rate (VSLR) across the retention time of 7–10 days. For a retention time of 7 days, the maximum VSRR was noted as 0.0050 g/(L.h) with a corresponding VSLR of 0.0089 g/(L.h). When retention time was maintained for 10 days, a maximum sulfate reduction of 65% and a maximum bacterial concentration of 1.632 g/L were achieved for an initial sulfate concentration of 1.5 g/L. It was concluded that VSLR facilitated through both dilution rate and initial sulfate concentration had a significant influence over sulfate reduction kinetics. The results of the study suggested that the microalgal-fed sulfidogenic system could be effectively employed for reduction of sulfate from sulfate-rich wastewater.     

Piecewise constant strain kinematic model of externally loaded concentric tube robots

This paper presents a piecewise constant strain kinematic model for concentric tube robots (CTR) in externally loaded conditions. It discretizes the pre-curved tubes comprising the robot into a finite number of pieces and involves external effects as a set of wrench vectors exerted along the robot backbone. Constant strain lets us describe the pieces with helices in which shear deformation and elongation are neglected. The resulting piecewise helix is the simplest curve that can catch the torsion of tubes that play a crucial role in kinematic behavior. This approximation transforms the conventional boundary value problem (BVP) of CTRs models into a set of nonlinear equations that drastically decreases the model resolution time. The present method uses a Lyapunov function and torsional Jacobian to ensure the distal torsion constraint consistently and, as a result, the solution’s convergence. The paper’s primary purpose is to present a fast, numerically stable, and relatively accurate kinematic model not reliant on measurement data. Experimental results on a two-tube prototype and provided for different tip loading conditions reveal maintaining a balance between adequate accuracy and reasonable running time, about 7 ms for five pieces per section, for real-time applications in the presence of external load.     

Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

石油化工管道安装常见问题及控制

目前,石油化工已成为我国重要产业之一,是我国社会经济的中流砥柱,因此石油化工业的稳定发展成为社会关注的热点。但随着石油化工产业的蓬勃发展,石油化工管道的安装问题愈加明显,较为常见的有阀门安装、焊接质量和防腐性差等问题。若不及时改善与调整,必然对化工管道的使用寿命与性能产生巨大影响。有鉴于此,通过对相关文献研究以及结合自己多年工作经验情况下,首先针对石油化工管道安装常见的问题进行分析与探讨,然后提出相应措施用以提高石油化工管道的安装质量。     

Pore-scale study of effects of different Pt loading reduction schemes on reactive transport processes in catalyst layers of proton exchange membrane fuel cells

Reducing the Platinum (Pt) loading while maintaining the performance is highly desired for promoting the commercial use of proton exchange membrane fuel cells (PEMFCs). Different methods have been adopted to fabricate catalyst layers (CLs) with low Pt loading, including utilizing lower Pt/C catalysts (MA), mixing high Pt/C catalysts with bare carbon black particles (MB), and reducing CL thickness while maintaining high Pt/C ratio (MC). In this study, self-developed pore-scale model is adopted to investigate the performance of the three Pt reduction methods. It is found that MA shows the best performance while MB shows the worst. Then, effects of Pt dispersion are further explored. The results show that denser Pt sites will result in higher local oxygen flux and thus higher local transport resistance. Therefore, MA method, which shows the better Pt dispersion, leads to improved performance. Third, CLs with quasi-realistic structures are investigated. Higher tortuosity resulting from the random pores produces higher bulk resistance along the thickness direction, while MA still exhibits the best performance. Finally, improved CL structures are investigated by designing perforated CL structures. It is found that adding perforations can significantly reduce the bulk transport resistance and can improve the CL performance. It is demonstrated that CL structure plays important roles on performance, and there are still huge potentials to further improve CL performance by increasing Pt dispersion and optimizing CL structures.     

A globally convergent BFGS method for pseudo-monotone variational inequality problems

In this paper, we propose a globally convergent BFGS method to solve Variational Inequality Problems (VIPs). In fact, a globalization technique on the basis of the hyperplane projection method is applied to the BFGS method. The technique, which is independent of any merit function, is applicable for pseudo-monotone problems. The proposed method applies the BFGS direction and tries to reduce the distance of iterates to the solution set. This property, called Fejer monotonicity of iterates with respect to the solution set, is the basis of the convergence analysis. The method applied to pseudo-monotone VIP is globally convergent in the sense that subproblems always have unique solutions, and the sequence of iterates converges to a solution to the problem without any regularity assumption. Finally, some numerical simulations are included to evaluate the efficiency of the proposed algorithm.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.