Sub-critical crack growth in silicate glasses: Role of network topology

2015 ◽  
Vol 107 (14) ◽  
pp. 141901 ◽  
Author(s):  
Morten M. Smedskjaer ◽  
Mathieu Bauchy
Keyword(s):  
Crack Growth ◽  
Network Topology ◽  
Silicate Glasses ◽  
Critical Crack

scholarly journals Unique Slow Crack Growth Behavior of Isotactic Polypropylene: The Role of Shear Layer-Spherulites Layer Alternated Structure

Polymers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2746
Author(s):  
Mingjin Liu ◽  
Jiaxu Luo ◽  
Jin Chen ◽  
Xueqin Gao ◽  
Qiang Fu ◽  
...  
Keyword(s):  
Shear Layer ◽  
Crack Growth ◽  
Isotactic Polypropylene ◽  
Slow Crack Growth ◽  
Crack Growth Behavior ◽  
Polymer Science ◽  
The Past ◽  
Propagation Behavior ◽  
Crack Propagation Behavior

With the development of polymer science, more attention is being paid to the longevity of polymer products. Slow crack growth (SCG), one of the most important factors that reveal the service life of the products, has been investigated widely in the past decades. Here, we manufactured an isotactic polypropylene (iPP) sample with a novel shear layer–spherulites layer alternated structure using multiflow vibration injection molding (MFVIM). However, the effect of the alternated structure on the SCG behavior has never been reported before. Surprisingly, the results showed that the resistivity of polymer to SCG can be enhanced remarkably due to the special alternated structure. Moreover, this sample shows unique slow crack propagation behavior in contrast to the sample with the same thickness of shear layer, presenting multiple microcracks in the spherulites layer, which can explain the reason of the resistivity improvement of polymer to SCG.

Role of precursor concentrations on the formation of ternary Pb1−Sr Se QDs in silicate glasses

2021 ◽  
Vol 266 ◽  
pp. 115066
Author(s):  
Yingrui Liu ◽  
Xiaochun Li ◽  
Yong Su ◽  
Jing Wang ◽  
Xin Shao ◽  
...  
Keyword(s):  
Silicate Glasses

Sub-Critical Crack Growth Behavior of a Low-Temperature Co-Fired Ceramic

2007 ◽  
Vol 90 (5) ◽  
pp. 1527-1533 ◽  
Author(s):  
Rajan Tandon ◽  
Clay S. Newton ◽  
Saundra L. Monroe ◽  
S. Jill Glass ◽  
Christine J. Roth
Keyword(s):  
Low Temperature ◽  
Crack Growth ◽  
Growth Behavior ◽  
Crack Growth Behavior ◽  
Critical Crack

scholarly journals Relaxation of scratch-induced surface deformation in silicate glasses: Role of densification and shear flow in lateral indentation experiments

2018 ◽  
Vol 500 ◽  
pp. 382-387 ◽  
Author(s):  
Elham Moayedi ◽  
Shigeki Sawamura ◽  
Jana Hennig ◽  
Enrico Gnecco ◽  
Lothar Wondraczek
Keyword(s):  
Shear Flow ◽  
Surface Deformation ◽  
Silicate Glasses

Modeling of phase interfaces during pre-critical crack growth in concrete

2011 ◽  
Vol 33 (9) ◽  
pp. 966-977 ◽  
Author(s):  
D. Asahina ◽  
E.N. Landis ◽  
J.E. Bolander
Keyword(s):  
Crack Growth ◽  
Critical Crack

scholarly journals On Synchronizing Coupled Retinogeniculocortical Pathways: A Toy Model

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
B. L. Mayer ◽  
L. H. A. Monteiro
Keyword(s):  
Neural Network ◽  
Visual Cortex ◽  
Corpus Callosum ◽  
Neuronal Activity ◽  
Network Topology ◽  
Cerebral Hemisphere ◽  
State Transition ◽  
Regular Lattice ◽  
Visual Cortices

A Newman-Watts graph is formed by including random links in a regular lattice. Here, the emergence of synchronization in coupled Newman-Watts graphs is studied. The whole neural network is considered as a toy model of mammalian visual pathways. It is composed by four coupled graphs, in which a coupled pair represents the lateral geniculate nucleus and the visual cortex of a cerebral hemisphere. The hemispheres communicate with each other through a coupling between the graphs representing the visual cortices. This coupling makes the role of the corpus callosum. The state transition of neurons, supposed to be the nodes of the graphs, occurs in discrete time and it follows a set of deterministic rules. From periodic stimuli coming from the retina, the neuronal activity of the whole network is numerically computed. The goal is to find out how the values of the parameters related to the network topology affect the synchronization among the four graphs.

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