Electrocatalytic activity and volatile product selectivity for nitrate reduction at tin-modified Pt(100), Pd(100) and Pd–Pt(100) single crystal electrodes in acidic media

We prepared Sn-modified Pt(100), Pd(100) and Pd–Pt(100) single crystal electrodes and investigated the nitrate reduction reaction (NO3RR) activity and the product selectivity for them using online electrochemical mass spectroscopy (OLEMS), also known as differential electrochemical mass spectroscopy (DEMS). OLEMS measurements allowed us to quantify volatile products of N2, N2O and NO and confirm the production of N2 at Sn/Pd(100) but not at Sn/Pt(100). Pd-doping to Pt(100) with a 3 atomic % increased the product selectivity for the NO3RR to N2. These results indicate that the presence of Pd in the (100) surface is the key to produce N2, which seems to be related to the hydrogen adsorption energy to the metal surface. The suppression of hydrogenation of intermediate species at the electrode surface could lead to the production of N2. This work will guide us to understand N2 production mechanism for the NO3RR and develop highly selective electrocatalysts for denitrification

DV-Hop Algorithm Based on Multi-Objective Salp Swarm Algorithm Optimization

The localization of sensor nodes is an important problem in wireless sensor networks. The DV-Hop algorithm is a typical range-free algorithm, but the localization accuracy is not high. To further improve the localization accuracy, this paper designs a DV-Hop algorithm based on multi-objective salp swarm optimization. Firstly, hop counts in the DV-Hop algorithm are subdivided, and the average hop distance is corrected based on the minimum mean-square error criterion and weighting. Secondly, the traditional single-objective optimization model is transformed into a multi-objective optimization model. Then, in the third stage of DV-Hop, the improved multi-objective salp swarm algorithm is used to estimate the node coordinates. Finally, the proposed algorithm is compared with three improved DV-Hop algorithms in two topologies. Compared with DV-Hop, The localization errors of the proposed algorithm are reduced by 50.79% and 56.79% in the two topology environments with different communication radii. The localization errors of different node numbers are decreased by 38.27% and 56.79%. The maximum reductions in localization errors are 38.44% and 56.79% for different anchor node numbers. Based on different regions, the maximum reductions in localization errors are 56.75% and 56.79%. The simulation results show that the accuracy of the proposed algorithm is better than that of DV-Hop, GWO-DV-Hop, SSA-DV-Hop, and ISSA-DV-Hop algorithms

Solving the 0-1 Knapsack Problem by Using Tissue P System With Cell Division

Membrane computing is a kind of distributed and parallel computing model inspired by a biological cell mechanism. The maximum parallelism of membrane computing improves the computational efficiency of its computational model. In this paper, a tissue P system named Π KP is proposed to solve the 0-1 knapsack problem, which is one of the classic NP-hard problems. Π KP could obtain the accurate solutions of knapsack problem and points out the number of accurate solutions, which mainly consists of three stages: first, generate all the solutions of knapsack problem by a cell division; then calculate the weights and total values in all the candidate membranes, which will be kept or dissolved according to the restriction of knapsack problem; and check out the final solutions. The instances are executed on a membrane simulator named UPSimulator, and the result of the experiments shows the whole searching procedure by the rules and proves the correctness and efficiency of the system.Fundamental Research Funds for the Central Universities (China) 2019CDXYJSJ002

Separation and Quantification of Four Main Chiral Glucosinolates in Radix Isatidis and Its Granules Using High-Performance Liquid Chromatography/Diode Array Detector Coupled with Circular Dichroism Detection

As chemical drugs, separation and quantification of the specific enantiomer from the chiral compounds in herbal medicines are becoming more important. To clarify the chemical characterization of chiral glucosinolates—the antiviral active ingredients of Radix Isatidis, an optimized efficient method of HPLC-UV-CD was developed to simultaneously separate and quantify the four main chiral glucosinolates: progoitrin, epiprogoitrin, and R,S-goitrin. The first step was to determine progoitrin, epiprogoitrin, and R,S-goitrin using HPLC-UV, and then determine the R-goitrin and S-goitrin by coupling with CD detection. Subsequently, through the linear relations between anisotropy factor (g factor) and the percent optical purity of R-goitrin, the contents of R-goitrin and S-goitrin from the R,S-goitrin mixture were calculated separately. Furthermore, the chemical composition features of the four chiral glucosinolates in 37 samples from crude drugs, decoction pieces, and granules of R. Isatidis were conducted. The total content of the four glucosinolates was obviously higher in crude drugs, and the variance character of each glucosinolate contents was different. In summary, the accurate measurement method reported here allows for better control of the internal quality of R. Isatidis and its granules and provides a powerful approach for the analysis of other chiral components in traditional Chinese medicines

Effect of Particle Sizes of Nickel Powder on Thermal Conductivity of Epoxy Resin-Based Composites under Magnetic Alignment

Magnetically oriented three-phase composite systems of epoxy resin, aluminum nitride, and nickel have been prepared, the thermal conductivity of composites filled with nickel powder with different particle sizes and content under different applied magnetic fields was studied. The vibrating scanning magnetometer (VSM) and scanning electron microscopy (SEM) were applied to investigate the dispersion of nickel powder in the composites. The results showed that the anisotropic thermal conductivity of the composites treated by applied magnetic field forming chain structure is obtained. The epoxy resin-based composites filled with 30 vol% aluminum nitride with particle size of 1 μm and 2 vol% nickel powder with particle size of 1 μm and aligned with vertical magnetic field have the highest thermal conductivity (1.474 W/mk), which increases the thermal conductivity of the composites by 737% and 58% compared to the pure epoxy resin (0.2 W/mk) and the composites filled with 30 vol% aluminum nitride (0.933 W/mk). In addition, we simulated the influence of nickel powder particles with different particle sizes and arrangements on the thermal conductivity of the composite material in COMSOL Multiphysics software, and the results were consistent with the experimental results

Modular reconfiguration of hybrid PV-TEG systems via artificial rabbit algorithm: Modelling, design and HIL validation

To further improve the power generation efficiency of traditional photovoltaic (PV) systems, this paper designs a theoretical model of a hybrid power generation system that consists of the individual PV system and thermoelectric generation (TEG) system. Meanwhile, partial shielding condition (PSC) is a common but serious problem during operation that might lead to power loss and component mismatch in hybrid PV-TEG system. Therefore, a reconfiguration method for the hybrid PV-TEG system based on artificial rabbit optimization (ARO) algorithm is proposed in this study to alleviate the negative impact caused by PSC and thus improve the power generation efficiency of the hybrid system. ARO algorithm is applied to adjust the switching matrix of the hybrid system to change the electrical connection among PV arrays and TEG arrays, and thus further to reduce the adverse effect of PSC and maximize the output power of the hybrid system. To verify the effectiveness of the proposed method, simulation tests are carried out on 4 × 4 and 20 × 15 arrays, respectively. For a quantitative and fair comparison, this work employs maximum output power, average output power, mismatch loss, and standard deviation as evaluation indexes, upon which four different algorithms including GA, PSO, WOA, AOA and ACO are thoroughly compared. Simulation results show that the output power of the hybrid system after ARO algorithm based reconfiguration is improved by 34.05% in the 4 × 4 array and 23.10% in the 20 × 15 array, respectively. In addition, hardware-in-the-loop (HIL) experiments are carried out based on RTLAB platform to verify the hardware feasibility of the proposed reconfiguration strategy