Z
Zhufeng Liu
Researcher at Huazhong University of Science and Technology
Publications - 10
Citations - 47
Zhufeng Liu is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Engineering & Computer science. The author has an hindex of 1, co-authored 1 publications receiving 12 citations.
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In-situ deposition of three-dimensional graphene on selective laser melted copper scaffolds for high performance applications
Kaka Cheng,Wei Xiong,Yan Li,Liang Hao,Chunze Yan,Zhaoqing Li,Zhufeng Liu,Yushen Wang,Khamis Essa,Li Lee,Xin Gong,Ton Peijs +11 more
TL;DR: In this paper, a bottom-up strategy that leverages the selective laser melting (SLM) technique to manufacture a three-dimensional (3D) porous copper template was creatively proposed, and Graphene was then in-situ grown via chemical vapor deposition on the obtained porous Cu template, forming 3DG composites.
Journal ArticleDOI
Large‐Scale, Abrasion‐Resistant, and Solvent‐Free Superhydrophobic Objects Fabricated by a Selective Laser Sintering 3D Printing Strategy
Zhenhua Wu,Congcan Shi,Aotian Chen,Yike Li,Shuang Chen,D. W. Sun,Changshun Wang,Zhufeng Liu,Qi Wang,Jianyu Huang,Yamei Yue,Shanfei Zhang,Zichuan Liu,Yizhuo Xu,Jin Su,Yan Zhou,Shifeng Wen,Chunze Yan,Yusheng Shi,Xu Deng,Lei Jiang,Bin Su +21 more
TL;DR: In this paper , a half-a-meter scaled superhydrophobic objects can be one-step realized by the selective laser sintering (SLS) 3D printing technology using hydrophobic-fumed-silica (HFS)/polymer composite grains.
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Magnetic/Conductive/Elastic Multi-Material 3D-Printed Self-Powered Sensing Gloves for Underwater/Smoke Environmental Human-Computer Interaction
TL;DR: In this paper , a home-made multi-extrusion-head manipulator was used to print three kinds of functional inks including magnetic, conductive and elastic materials.
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Real-time physical field reconstruction for nanofluids convection using deep learning with auxiliary tasks
TL;DR: Wang et al. as mentioned in this paper developed a deep learning framework to achieve the main task of real-time reconstruction mapping from design variables to physical fields, and auxiliary tasks of prediction mapping from physical fields to performance characteristics are tailored to improve the accuracy and generalization of reconstruction mapping.