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661 results on '"Fang, Yanyan"'

1. Electrocatalytic hydrogenation of acetonitrile to ethylamine in acid.

Author

Tang, Chongyang, Wei, Cong, Fang, Yanyan, Liu, Bo, Song, Xianyin, Bian, Zenan, Yin, Xuanwei, Wang, Hongbo, Liu, Zhaohui, Wang, Gongming, Xiao, Xiangheng, and Duan, Xiangfeng

Abstract

Electrochemical hydrogenation of acetonitrile based on well-developed proton exchange membrane electrolyzers holds great promise for practical production of ethylamine. However, the local acidic condition of proton exchange membrane results in severe competitive proton reduction reaction and poor selection toward acetonitrile hydrogenation. Herein, we conduct a systematic study to screen various metallic catalysts and discover Pd/C exhibits a 43.8% ethylamine Faradaic efficiency at the current density of 200 mA cm-2 with a specific production rate of 2912.5 mmol g-1 h-1, which is about an order of magnitude higher than the other screened metal catalysts. Operando characterizations indicate the in-situ formed PdHx is the active centers for catalytic reaction and the adsorption strength of the *MeCH2NH2 intermediate dictates the catalytic selectivity. More importantly, the theoretical analysis reveals a classic d-band mediated volcano curve to describe the relation between the electronic structures of catalysts and activity, which could provide valuable insights for designing more effective catalysts for electrochemical hydrogenation reactions and beyond.

Published
2024

6. Cross-domain Trajectory Prediction with CTP-Net

Author

Huang, Pingxuan, Cui, Zhenhua, Li, Jing, Gao, Shenghua, Hu, bo, and Fang, Yanyan

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Most pedestrian trajectory prediction methods rely on a huge amount of trajectories annotation, which is time-consuming and expensive. Moreover, a well-trained model may not effectively generalize to a new scenario captured by another camera. Therefore, it is desirable to adapt the model trained on an annotated source domain to the target domain. To achieve domain adaptation for trajectory prediction, we propose a Cross-domain Trajectory Prediction Network (CTP-Net). In this framework, encoders are used in both domains to encode the observed trajectories, then their features are aligned by a cross-domain feature discriminator. Further, considering the consistency between the observed and the predicted trajectories, a target domain offset discriminator is utilized to adversarially regularize the future trajectory predictions to be in line with the observed trajectories. Extensive experiments demonstrate the effectiveness of our method on domain adaptation for pedestrian trajectory prediction., Comment: Work is accepted by CICAI(CAAI International Conference on Artificial Intelligence), 12 pages

Published
2021

19. Locality-constrained Spatial Transformer Network for Video Crowd Counting

Author

Fang, Yanyan, Zhan, Biyun, Cai, Wandi, Gao, Shenghua, and Hu, Bo

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Compared with single image based crowd counting, video provides the spatial-temporal information of the crowd that would help improve the robustness of crowd counting. But translation, rotation and scaling of people lead to the change of density map of heads between neighbouring frames. Meanwhile, people walking in/out or being occluded in dynamic scenes leads to the change of head counts. To alleviate these issues in video crowd counting, a Locality-constrained Spatial Transformer Network (LSTN) is proposed. Specifically, we first leverage a Convolutional Neural Networks to estimate the density map for each frame. Then to relate the density maps between neighbouring frames, a Locality-constrained Spatial Transformer (LST) module is introduced to estimate the density map of next frame with that of current frame. To facilitate the performance evaluation, a large-scale video crowd counting dataset is collected, which contains 15K frames with about 394K annotated heads captured from 13 different scenes. As far as we know, it is the largest video crowd counting dataset. Extensive experiments on our dataset and other crowd counting datasets validate the effectiveness of our LSTN for crowd counting., Comment: Accepted by ICME2019(Oral)

Published
2019

22. Cross-domain Trajectory Prediction with CTP-Net

Author

Huang, Pingxuan, Cui, Zhenhua, Li, Jing, Gao, Shenghua, Hu, Bo, Fang, Yanyan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fang, Lu, editor, Povey, Daniel, editor, Zhai, Guangtao, editor, Mei, Tao, editor, and Wang, Ruiping, editor

Published
2022
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31. Elucidating the Discrepancy between the Intrinsic Structural Instability and the Apparent Catalytic Steadiness of M‐N‐C Catalysts toward Oxygen Evolution Reaction.

Author

Cai, Jinyan, Hao, Xiaobin, Bian, Zenan, Wu, Yishang, Wei, Cong, Yin, Xuanwei, Liu, Bo, Fang, Ming, Lv, Youming, Xie, Yufang, Fang, Yanyan, and Wang, Gongming

Subjects
OXYGEN evolution reactions, CATALYSTS, DENSITY functional theory, X-ray absorption, X-ray spectroscopy
Abstract

Despite the widespread investigations on the M‐N‐C type single atom catalysts (SACs) for oxygen evolution reaction (OER), an internal conflict between its intrinsic thermodynamically structural instability and apparent catalytic steadiness has long been ignored. Clearly unfolding this contradiction is necessary and meaningful for understanding the real structure‐property relation of SACs. Herein, by using the well‐designed pH‐dependent metal leaching experiments and X‐ray absorption spectroscopy, an unconventional structure reconstruction of M‐N‐C catalyst during OER process was observed. Combining with density functional theory calculations, the initial Ni−N coordination is easily broken in the presence of adsorbed OH*, leading to favorable formation of Ni−O coordination. The formed Ni−O works stably as the real active center for OER catalysis in alkaline media but unstably in acid, which clearly explains the existing conflict. Unveiling the internal contradiction between structural instability and catalytic steadiness provides valuable insights for rational design of single atom OER catalysts. [ABSTRACT FROM AUTHOR]

Published
2024
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