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8. The Effect of Ligand Field on Enhanced Electrocatalytic Performance of NO Reduction Under Applied Potential.

Author

Wu, Zhi-Jun, Zhang, Xue-Long, Zhang, Xian-Jie, Fang, Shui-Yang, Chen, Wen-Xian, Wang, Meng-Di, and Zhuang, Gui-Lin

Subjects
LIGAND field theory, INDUCTIVE effect, CONDUCTION electrons, HYDROGEN evolution reactions, DENSITY functional theory
Abstract

We employed density functional theory to investigate Co-N4/Gra single-atom catalysts, focusing on the modification of axial ligand (X=-F, -CN and -C3H4N2) and examined the influence of ligand field and electric potential on eNORR. Our results demonstrate that Co-N4[X]/Gra exhibit favorable thermodynamic adsorption (Δ G *NO < 0) and remarkable activation activity toward NO molecules. Co-N4/Gra demonstrates a limiting potential of −0.13 V with the potential-determining step (PDS) of *NH3 → * + NH3(g). Notably, under the introduction of ligands, Co-N4[F]/Gra achieves the most favorable overpotential of −0.07 V, superior to most of NORR electrocatalysts, and meanwhile shows an exceptional selectivity of 99.99% for eNORR compared to competitive hydrogen evolution reaction. Under the solvent environment, Co-N4/Gra features the triggering potentials of −0.33 V for a pH of 1, −0.71 V for a pH of 7, and −1.10 V vs RHE for a pH of 13, respectively. Additionally, the potential reduces the desorption energy and adsorption energy of NH3, facilitating the accessibility of the NH3 desorption step (PDS) and promoting NO reduction. Thus, under realistic conditions, the Co ion's active site displays variable valence electrons and forms a dynamic interplay with the ligand field effect, rendering a crucial effect on the adsorption of reaction species during the eNORR. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Exosomal microRNA-15a from mesenchymal stem cells impedes hepatocellular carcinoma progression via downregulation of SALL4

Author

Ma, Yu-Shui, Liu, Ji-Bin, Lin, Lan, Zhang, Hui, Wu, Jian-Jun, Shi, Yi, Jia, Cheng-You, Zhang, Dan-Dan, Yu, Fei, Wang, Hui-Min, Yin, Yu-Zhen, Jiang, Xiao-Hui, Wang, Pei-Yao, Tian, Lin-Lin, Cao, Ping-Sheng, Wu, Xu-Ming, Lu, Hai-Min, Gu, Li-Peng, Zhang, Jia-Jia, Cong, Gu-Jun, Luo, Pei, Zhong, Xiao-Ming, Cai, Bo, Shi, Min-Xin, Zhang, Su-Qing, Li, Liu, Zhang, Wen-Jie, Liu, Yu, Li, Zhi-Zhen, Wu, Ting-Miao, Wu, Zhi-Jun, Wang, Gao-Ren, Lv, Zhong-Wei, Ling, Chang-Chun, Chu, Kai-Jian, and Fu, Da

Published
2021
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14. A 4D Trajectory Prediction Model Based on the BP Neural Network

Author

Wu Zhi-Jun, Tian Shan, and Ma Lan

Subjects
air traffic, 4d trajectory prediction, bp neural network, k-means clustering, real-time prediction, Science, Electronic computers. Computer science, QA75.5-76.95
Abstract

To solve the problem that traditional trajectory prediction methods cannot meet the requirements of high-precision, multi-dimensional and real-time prediction, a 4D trajectory prediction model based on the backpropagation (BP) neural network was studied. First, the hierarchical clustering algorithm and the k-means clustering algorithm were adopted to analyze the total flight time. Then, cubic spline interpolation was used to interpolate the flight position to extract the main trajectory feature. The 4D trajectory prediction model was based on the BP neural network. It was trained by Automatic Dependent Surveillance – Broadcast trajectory from Qingdao to Beijing and used to predict the flight trajectory at future moments. In this paper, the model is evaluated by the common measurement index such as maximum absolute error, mean absolute error and root mean square error. It also gives an analysis and comparison of the predicted over-point time, the predicted over-point altitude, the actual over-point time and the actual over-point altitude. The results indicate that the predicted 4D trajectory is close to the real flight data, and the time error at the crossing point is no more than 1 min and the altitude error at the crossing point is no more than 50 m, which is of high accuracy.

Published
2019
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