Topology and Toughening of Sparse Elastic Networks

被引:17
|
作者
Yamaguchi, Tetsuo [1 ]
Onoue, Yudai [1 ]
Sawae, Yoshinori [1 ,2 ]
机构
[1] Kyushu Univ, Dept Mech Engn, Fukuoka 8190395, Japan
[2] Kyushu Univ, Int Inst Carbon Neutral Energy Res, Fukuoka 8190395, Japan
关键词
HYDROGELS; FRACTURE;
D O I
10.1103/PhysRevLett.124.068002
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The toughening of sparse elastic networks, such as hydrogels, foams, or meshes against fracture is one of the most important problems in materials science. However, the principles of toughening have not yet been established despite urgent engineering requirements and several efforts made by materials scientists. Here we address the above-mentioned problem by focusing on the topology of a network. We perform fracture experiments for two-dimensional periodic lattices fabricated from rubber strings and connecters with well-defined topological structures. We find that systematic increase in the largest coordination number while maintaining the average coordination number (= 4) as constant leads to significant improvement in toughness. We reproduce the observed toughening behavior through numerical simulations and confirm that the stress concentration in the vicinity of a crack tip can be controlled by the topology of the network. This provides a new strategy for creating tough sparse elastic networks, especially hydrogels.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Sparse coding in sparse winner networks
    Starzyk, Janusz A.
    Liu, Yinyin
    Vogel, David
    ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 2, PROCEEDINGS, 2007, 4492 : 534 - +
  • [32] Controlled topology toughening epoxy via incorporation of partially reacted substructures
    Gao, Jian
    Palmese, Giuseppe
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 257
  • [33] A Topology-Based Spectrum Assignment Solution for Static Elastic Optical Networks With Ring Topologies
    Jara, Nicolas
    Salazar, Jesenia
    Vallejos, Reinaldo
    IEEE ACCESS, 2020, 8 (08): : 218828 - 218837
  • [34] Topology-Risk Balance Based Virtual Network Mapping Algorithm of Elastic Optical Networks
    He, Jinhong
    Luo, Anqin
    Zhang, Jing
    Zhang, Lei
    2020 12TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2020), 2020, : 9 - 12
  • [35] Toughening Hydrogels with Fibrillar Connected Double Networks
    Fang, Yu-Huang
    Liang, Chen
    Liljestrom, Ville
    Lv, Zhong-Peng
    Ikkala, Olli
    Zhang, Hang
    ADVANCED MATERIALS, 2024, 36 (27)
  • [36] SPARSE REGULATORY NETWORKS
    James, Gareth M.
    Sabatti, Chiara
    Zhou, Nengfeng
    Zhu, Ji
    ANNALS OF APPLIED STATISTICS, 2010, 4 (02): : 663 - 686
  • [37] Percolation on Sparse Networks
    Karrer, Brian
    Newman, M. E. J.
    Zdeborova, Lenka
    PHYSICAL REVIEW LETTERS, 2014, 113 (20)
  • [38] Sparse Wavelet Networks
    Sadri, Amir Reza
    Celebi, Mehemmed Emre
    Rahnavard, Nazanin
    Viswanath, Satish E.
    IEEE SIGNAL PROCESSING LETTERS, 2020, 27 : 111 - 115
  • [39] Robust Topology Identification in Distribution Networks Enabled by Latent Low-Rank and Sparse Embedding Feature Extraction
    Jafarian, Mohammad
    Keane, Andrew
    2022 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES, SEST, 2022,
  • [40] Estimating topology of networks
    Yu, Dongchuan
    Righero, Marco
    Kocarev, Ljupco
    PHYSICAL REVIEW LETTERS, 2006, 97 (18)