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Your search keyword '"Jiao, Yueyue"' showing total 15 results
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15 results on '"Jiao, Yueyue"'

5. A Study on Teaching Evaluation of Random Simulation Algorithm

Author

Jiao, Yueyue, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Xu, Zheng, editor, Parizi, Reza M., editor, Loyola-González, Octavio, editor, and Zhang, Xiaolu, editor

Published
2021
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6. Unveiling the Structure–Surface Energy Relationship of Zeolites through Machine Learning

Author

Ma, Huan, Chen, Yunlei, Jiao, Yueyue, Pang, Xueqian, Guo, Wenping, Liu, Xingchen, Li, Yongwang, and Wen, Xiaodong

Abstract

Understanding the intricate relationship between structure and surface energy is essential for a thorough comprehension of the external surface structure and crystal morphology of zeolites. In this study, we evaluated the surface energies of various zeolite surfaces across multiple representative frameworks with DFT calculations. Our analysis reveals a linear relationship between the calculated surface energy and the surface hydroxyl density, which is slightly disrupted due to the formation of hydrogen bonds. Using a symbolic regression approach, we establish a mathematical formula that correlates the surface energy with the density of surface hydroxyl groups and hydrogen bonds. We show that using the surface hydroxyl density alone can rapidly predict zeolite crystal morphologies with a high degree of accuracy, demonstrated by a promising Wulff similarity of 98%. The applicability and potential of our findings are demonstrated in estimating the Wulff shapes of 237 zeolite framework types in the database and predicting the crystal morphology evolution of a representative zeolite with pH, confirming the general validity of our approach based on straightforward structural analysis and thermodynamic principles. This work establishes a solid foundation for advancing the structural design of silica-based materials, particularly in applications requiring precise control of the surface structure and crystal habit.

Published
2024
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7. Water-Induced Structural Evolution of LaTMSi Ternary Intermetallic Electrides

Author

Sun, Yongfang, primary, Ma, Huan, additional, Jiao, Yueyue, additional, Chen, Yunlei, additional, Yuan, Xiaoze, additional, Zhang, Xiangyu, additional, Wang, Fei, additional, Xiao, Dongdong, additional, Wang, Yi, additional, Hong, Dachao, additional, Zhou, Yuwei, additional, Gu, Lin, additional, Yang, Yong, additional, Li, Yongwang, additional, and Wen, Xiao-Dong, additional

Published
2023
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8. Atomic-Dispersed Rh Enables Efficient Catalytic Nitrile Hydrogenation: Size Effect and Metal-Dependent Effect

Author

Chen, Jiawei, Jiao, Yueyue, Qin, Xuetao, Cai, Xiangbin, Wang, Maolin, Diao, Jiangyong, Wang, Linlin, Li, Chengyu, Ren, Pengju, Wen, Xiaodong, Wang, Ning, Rong, Junfeng, Xiao, Dequan, Liu, Hongyang, Ma, Ding, Chen, Jiawei, Jiao, Yueyue, Qin, Xuetao, Cai, Xiangbin, Wang, Maolin, Diao, Jiangyong, Wang, Linlin, Li, Chengyu, Ren, Pengju, Wen, Xiaodong, Wang, Ning, Rong, Junfeng, Xiao, Dequan, Liu, Hongyang, and Ma, Ding

Abstract

The hydrogenation of nitriles to amines, as an atom-economical synthetic route, has attracted wide attention in industrial production. Despite that some catalysts for nitrile hydrogenation have been investigated in recent years, achieving high activity and selectivity in this process remains a major challenge. Here, we fabricated an atomically dispersed Rh catalyst anchored on defect-rich nanodiamond-graphene (ND@G) via a deposition–precipitation strategy (Rh1/ND@G), which showed the highest activity (TOF = 2592 h–1) in the hydrogenation of benzonitrile reaction among all the known catalysts under mild reaction conditions (333 K, 0.6 MPa H2), and delivered high selectivity (>99%) toward secondary amines. Significantly, we prepared the Rh-cluster catalyst (Rhn/ND@G) and a series of atomically dispersed M1 catalysts (M = Rh, Ru, Pd, Ir, and Pt) to understand the size effect and metal-dependent effect in the hydrogenation of benzonitrile. Experimental and theoretical investigations revealed that the Rh1/ND@G catalyst has higher selectivity toward dibenzylamine than Rhn/ND@G, as it is less likely to form benzylamine on the Rh1 active sites. Meanwhile, the difference of adsorption energies (as a catalyst descriptor) between benzylideneimine and benzonitrile was used to understand the activity of benzonitrile hydrogenation influenced by the metal-dependent effect of M1 catalysts. Modulating the size and metal-dependent effects could lead to high catalytic performance, paving the way to design efficient nitrile hydrogenation catalysts.

Published
2023

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