Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Zhudan Chen"'
Publikováno v:
APL Machine Learning, Vol 1, Iss 2, Pp 021501-021501-20 (2023)
The design and development of polymeric materials have been a hot domain for decades. However, traditional experiments and molecular simulations are time-consuming and labor-intensive, which no longer meet the requirements of new materials developmen
Externí odkaz:
https://doaj.org/article/2f5ef1c5bccc41c28570b10c373af100
Publikováno v:
Molecular Simulation. 49:617-627
Autor:
Qionghai Chen, Zhiyu Zhang, Yongdi Huang, Hengheng Zhao, Zhudan Chen, Ke Gao, Tongkui Yue, Liqun Zhang, Jun Liu
Publikováno v:
ACS Applied Polymer Materials. 4:3575-3586
Publikováno v:
Langmuir : the ACS journal of surfaces and colloids. 38(33)
Polymer nanocomposites (PNCs) have been attracting myriad scientific and technological attention due to their promising mechanical and functional properties. However, there remains a need for an efficient method that can further strengthen the mechan
Publikováno v:
Molecular Simulation. 46:1509-1521
Molecular dynamics (MD) simulation has been an invaluable tool for polymer nanocomposites (PNCs) research. MD simulation investigations provide massive data about the movements of PNCs beads on the...
Publikováno v:
Langmuir. 36:7427-7438
Through molecular dynamics (MD) simulation, the structure and mechanical properties of matrix-free polymer nanocomposites (PNCs) constructed via polymer-grafted graphene nanosheets are studied. The dispersion of graphene sheets is characterized by th
Publikováno v:
Computational Materials Science. 216:111859
Autor:
Haixiao Wan, Yachen Wang, Liqun Zhang, Zhudan Chen, Ke Gao, Hengheng Zhao, Guanyi Hou, Jun Liu, Zhiyu Zhang
Publikováno v:
Langmuir : the ACS journal of surfaces and colloids. 37(42)
Understanding polymer-substrate interfacial dynamics at the molecular level is crucial for tailoring the properties of polymer ultrathin films (PUFs). Herein, through coarse-grained molecular dynamics simulation, the effect of length (Nloop) and rigi
Publikováno v:
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS).
Due to the extensively existing complexity and uncertainty of systems, feature extraction based on samples is an important task in controller design. As one of the research hotspots, deep auto-encoder neural network can be used to extract features fr
Autor:
Ke Gao, Hengheng Zhao, Yachen Wang, Haixiao Wan, Zhiyu Zhang, Zhudan Chen, Guanyi Hou, Jun Liu, Liqun Zhang
Publikováno v:
Langmuir; 10/26/2021, Vol. 37 Issue 42, p12290-12303, 14p