scholarly journals Deformation and cracking behavior of La2O3-doped oxide glasses with high Poisson's ratio

2018 ◽  
Vol 494 ◽  
pp. 86-93 ◽  
Author(s):  
Kacper Januchta ◽  
Ruofu Sun ◽  
Liping Huang ◽  
Michal Bockowski ◽  
Sylwester J. Rzoska ◽  
...  
Materials ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 2837
Author(s):  
Martin B. Østergaard ◽  
Mikkel S. Bødker ◽  
Morten M. Smedskjaer

In glass materials, Poisson’s ratio (ν) has been proposed to be correlated with a variety of features, including atomic packing density (Cg), liquid fragility (m), and network connectivity. To further investigate these correlations in oxide glasses, here, we study cesium borate and cesium silicate glasses with varying modifier/former ratio given the difference in network former coordination and because cesium results in relatively high ν compared to the smaller alkali modifiers. Within the binary glass series, we find positive correlations between ν on one hand and m and Cg on the other hand. The network former is found to greatly influence the correlation between ν and the number of bridging oxygens (nBO), with a negative correlation for silicate glasses and positive correlation for borate glasses. An analysis based on topological constraint theory shows that this difference cannot be explained by the effect of superstructural units on the network connectivity in lithium borate glasses. Considering a wider range of oxide glasses from the literature, we find that ν generally decreases with increasing network connectivity, but with notable exceptions for heavy alkali borate glasses and calcium alumino tectosilicate glasses.


Materials ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2439 ◽  
Author(s):  
Martin B. Østergaard ◽  
Søren R. Hansen ◽  
Kacper Januchta ◽  
Theany To ◽  
Sylwester J. Rzoska ◽  
...  

Poisson’s ratio (ν) defines a material’s propensity to laterally expand upon compression, or laterally shrink upon tension for non-auxetic materials. This fundamental metric has traditionally, in some fields, been assumed to be a material-independent constant, but it is clear that it varies with composition across glasses, ceramics, metals, and polymers. The intrinsically elastic metric has also been suggested to control a range of properties, even beyond the linear-elastic regime. Notably, metallic glasses show a striking brittle-to-ductile (BTD) transition for ν-values above ~0.32. The BTD transition has also been suggested to be valid for oxide glasses, but, unfortunately, direct prediction of Poisson’s ratio from chemical composition remains challenging. With the long-term goal to discover such high-ν oxide glasses, we here revisit whether previously proposed relationships between Poisson’s ratio and liquid fragility (m) and atomic packing density (Cg) hold for oxide glasses, since this would enable m and Cg to be used as surrogates for ν. To do so, we have performed an extensive literature review and synthesized new oxide glasses within the zinc borate and aluminoborate families that are found to exhibit high Poisson’s ratio values up to ~0.34. We are not able to unequivocally confirm the universality of the Novikov-Sokolov correlation between ν and m and that between ν and Cg for oxide glass-formers, nor for the organic, ionic, chalcogenide, halogenide, or metallic glasses. Despite significant scatter, we do, however, observe an overall increase in ν with increasing m and Cg, but it is clear that additional structural details besides m or Cg are needed to predict and understand the composition dependence of Poisson’s ratio. Finally, we also infer from literature data that, in addition to high ν, high Young’s modulus is also needed to obtain glasses with high fracture toughness.


2008 ◽  
Vol 39-40 ◽  
pp. 137-146 ◽  
Author(s):  
Tanguy Rouxel ◽  
Hui Ji ◽  
Vincent Keryvin ◽  
Tahar Hammouda ◽  
Satoshi Yoshida

Although Poisson's ratio (ν) is a macroscopic elastic parameter it depends much on the fine details of the atomic packing. Glasses exhibit a wide range of values for  from 0.1 to 0.4 which correlate to the glass network polymerisation degree, hence reproducing at the atomic scale what is observed in cellular materials at the macroscopic scale[1]. As for pure oxide glasses, we found in various multi-component glasses built on ionic-, covalent- or Van der Waals bonds that an increase of Poisson’s ratio corresponds to a decrease of the atomic network crosslink degree[2]. Noteworthy, an extension of this analysis to the case of metallic glasses correlate the recently proposed cluster-like network structure for these glasses[3,4]. A general feature is that a highly cross-linked atomic network results in a glass with a low atomic packing density (large free volume fraction), as exemplified with the case of amorphous silica. The lower the atomic packing density is and the larger the volume change the glass experiences under high pressure (1 to 25 GPa). Indentation experiments with sharp indenters (such as the Vickers one) give birth to hydrostatic stresses of the same order of magnitude and thus induce glass densification. There is hence a direct correlation between ν (reflecting the packing density) and the indentation behavior[5].


2013 ◽  
Vol 6 (1) ◽  
pp. 36-43 ◽  
Author(s):  
Ai Chi ◽  
Li Yuwei

Coal body is a type of fractured rock mass in which lots of cleat fractures developed. Its mechanical properties vary with the parametric variation of coal rock block, face cleat and butt cleat. Based on the linear elastic theory and displacement equivalent principle and simplifying the face cleat and butt cleat as multi-bank penetrating and intermittent cracks, the model was established to calculate the elastic modulus and Poisson's ratio of coal body combined with cleat. By analyzing the model, it also obtained the influence of the parameter variation of coal rock block, face cleat and butt cleat on the elastic modulus and Poisson's ratio of the coal body. Study results showed that the connectivity rate of butt cleat and the distance between face cleats had a weak influence on elastic modulus of coal body. When the inclination of face cleat was 90°, the elastic modulus of coal body reached the maximal value and it equaled to the elastic modulus of coal rock block. When the inclination of face cleat was 0°, the elastic modulus of coal body was exclusively dependent on the elastic modulus of coal rock block, the normal stiffness of face cleat and the distance between them. When the distance between butt cleats or the connectivity rate of butt cleat was fixed, the Poisson's ratio of the coal body initially increased and then decreased with increasing of the face cleat inclination.


2019 ◽  
Vol 11 (19) ◽  
pp. 5283 ◽  
Author(s):  
Gowida ◽  
Moussa ◽  
Elkatatny ◽  
Ali

Rock mechanical properties play a key role in the optimization process of engineering practices in the oil and gas industry so that better field development decisions can be made. Estimation of these properties is central in well placement, drilling programs, and well completion design. The elastic behavior of rocks can be studied by determining two main parameters: Young’s modulus and Poisson’s ratio. Accurate determination of the Poisson’s ratio helps to estimate the in-situ horizontal stresses and in turn, avoid many critical problems which interrupt drilling operations, such as pipe sticking and wellbore instability issues. Accurate Poisson’s ratio values can be experimentally determined using retrieved core samples under simulated in-situ downhole conditions. However, this technique is time-consuming and economically ineffective, requiring the development of a more effective technique. This study has developed a new generalized model to estimate static Poisson’s ratio values of sandstone rocks using a supervised artificial neural network (ANN). The developed ANN model uses well log data such as bulk density and sonic log as the input parameters to target static Poisson’s ratio values as outputs. Subsequently, the developed ANN model was transformed into a more practical and easier to use white-box mode using an ANN-based empirical equation. Core data (692 data points) and their corresponding petrophysical data were used to train and test the ANN model. The self-adaptive differential evolution (SADE) algorithm was used to fine-tune the parameters of the ANN model to obtain the most accurate results in terms of the highest correlation coefficient (R) and the lowest mean absolute percentage error (MAPE). The results obtained from the optimized ANN model show an excellent agreement with the laboratory measured static Poisson’s ratio, confirming the high accuracy of the developed model. A comparison of the developed ANN-based empirical correlation with the previously developed approaches demonstrates the superiority of the developed correlation in predicting static Poisson’s ratio values with the highest R and the lowest MAPE. The developed correlation performs in a manner far superior to other approaches when validated against unseen field data. The developed ANN-based mathematical model can be used as a robust tool to estimate static Poisson’s ratio without the need to run the ANN model.


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