Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Mengxiong Liu"'
Autor:
Kun Wang, Xiucai Sun, Shuting Cheng, Yi Cheng, Kewen Huang, Ruojuan Liu, Hao Yuan, Wenjuan Li, Fushun Liang, Yuyao Yang, Fan Yang, Kangyi Zheng, Zhiwei Liang, Ce Tu, Mengxiong Liu, Mingyang Ma, Yunsong Ge, Muqiang Jian, Wanjian Yin, Yue Qi, Zhongfan Liu
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Direct chemical vapor deposition (CVD) growth of graphene on dielectric/insulating materials is a promising strategy for subsequent transfer-free applications of graphene. However, graphene growth on noncatalytic substrates is faced with tho
Externí odkaz:
https://doaj.org/article/e321ef22afb24efcb9b3842ed2d5299a
Autor:
MengXiong Liu, XiDe Li
Publikováno v:
Proceedings, Vol 2, Iss 8, p 412 (2018)
Considering the Mooney–Rivlin hyperelastic model, a semi-analytical approach is introduced to analyze the rigid–flexible contact behavior of an inflated membrane balloon between two plates with various interface conditions. This approach is based
Externí odkaz:
https://doaj.org/article/2f785c752f214beea419ecaff62d67e9
Autor:
Mengxiong Liu, Run Li, Jie Wang, null Xuan ye, Haomin Wang, Yingying Zhang, Rufan Zhang, Xide Li
Publikováno v:
Carbon. 199:300-317
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::764f32148b98df58ea174c50a048f30f
https://doi.org/10.1016/j.carbon.2022.08.022
https://doi.org/10.1016/j.carbon.2022.08.022
Publikováno v:
Engineering Fracture Mechanics. 284:109282
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e54995886b8de1c4cb06267af749dd2d
https://doi.org/10.1016/j.engfracmech.2023.109282
https://doi.org/10.1016/j.engfracmech.2023.109282
Publikováno v:
IEEE BigData
In the past decade, the amount of attributed network data has skyrocketed, and the problem of identifying their underlying group structures has received significant attention. By leveraging both attribute and link information, recent state-of-the-art
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59bd75dacc4b9da047ad93282af119f0
https://doi.org/10.1109/bigdata50022.2020.9378031
https://doi.org/10.1109/bigdata50022.2020.9378031
Publikováno v:
International Journal of Mechanical Sciences. 217:107022
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f183b654c84aa76a6099caa3c9ec0276
https://doi.org/10.1016/j.ijmecsci.2021.107022
https://doi.org/10.1016/j.ijmecsci.2021.107022
Autor:
Xide Li, Mengxiong Liu
Publikováno v:
Optics and Lasers in Engineering. 150:106853
In the past three decades, we have witnessed the explosive development of micro/nano science and technology, where remarkable research efforts have been made in synthesizing of materials and fabricating of devices at micro- and nano-scale. The unusua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5be2735d72a180f5f5d9f6ac444c0b4
https://doi.org/10.1016/j.optlaseng.2021.106853
https://doi.org/10.1016/j.optlaseng.2021.106853
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109271
ECML/PKDD (2)
ECML/PKDD (2)
Heterogeneous networks are widely used to model real-world semi-structured data. The key challenge of learning over such networks is the modeling of node similarity under both network structures and contents. To deal with network structures, most exi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce53354dc902f5adc2fa1fbabee23996
https://doi.org/10.1007/978-3-030-10928-8_3
https://doi.org/10.1007/978-3-030-10928-8_3
Publikováno v:
Journal of the Mechanics and Physics of Solids. 142:104032
Ultralow inter-wall interaction is realized in centimeter-long double-walled carbon nanotube (DWCNT) (Zhang, R. et al. Nat. Nanotech. 8, 912-916 (2013)). To further illustrate the mechanism of this special phenomenon, theoretical analysis combining w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d22b750cded91725c6c0055d6bae324
https://doi.org/10.1016/j.jmps.2020.104032
https://doi.org/10.1016/j.jmps.2020.104032
Publikováno v:
ASONAM
Networks or graphs provide a natural and generic way for modeling rich structured data. Recent research on graph analysis has been focused on representation learning, of which the goal is to encode the network structures into distributed embedding ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::865e3efc4110da7cb69014444fdcc4d7
https://doi.org/10.1109/asonam.2018.8508729
https://doi.org/10.1109/asonam.2018.8508729