scholarly journals Topological constraint model of high lithium content borate glasses

2019 ◽  
Vol 3 ◽  
pp. 100028 ◽  
Author(s):  
Wataru Takeda ◽  
Collin J. Wilkinson ◽  
Steven A. Feller ◽  
John C. Mauro
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.


2019 ◽  
Vol 2 ◽  
pp. 100019 ◽  
Author(s):  
Collin J. Wilkinson ◽  
Qiuju Zheng ◽  
Liping Huang ◽  
John C. Mauro

2018 ◽  
Vol 502 ◽  
pp. 172-175 ◽  
Author(s):  
Collin J. Wilkinson ◽  
Evgeny Pakhomenko ◽  
Martha R. Jesuit ◽  
Anthony DeCeanne ◽  
Brittney Hauke ◽  
...  

1982 ◽  
Vol 43 (C9) ◽  
pp. C9-497-C9-500 ◽  
Author(s):  
M. Devaud ◽  
J.-Y. Prieur

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.


1995 ◽  
Vol 68 (3) ◽  
pp. 383 ◽  
Author(s):  
Neil A. Doherty ◽  
James R. Garven

2021 ◽  
Vol 1811 (1) ◽  
pp. 012112
Author(s):  
Juniastel Rajagukguk ◽  
Rappel Situmorang ◽  
Budiman Nasution ◽  
Donna Helen Rajagukguk ◽  
Rr M I Retno Susilorini ◽  
...  

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