Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model

Quaternary glass series of nano and micro-particles europium oxide (III), i.e. Eu2O3, of composition [{(TeO2)0.7 (B2O3)0.3}0.7 (ZnO)0.3](1-y) (EnOm)y, where EnOm is nano or micro Eu2O3 particles coded as TBZEu-NPs and TBZEu-MPs with y = 1.0–5.0 mol% was prepared by melt-quenching technique. Using th...

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Published in:Journal of Materials Research and Technology
Main Author: Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
Format: Article
Language:English
Published: Elsevier Editora Ltda 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123028575&doi=10.1016%2fj.jmrt.2022.01.035&partnerID=40&md5=09422c87267cfff2d59d40b2fffa8a22
id 2-s2.0-85123028575
spelling 2-s2.0-85123028575
Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
2022
Journal of Materials Research and Technology
17

10.1016/j.jmrt.2022.01.035
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123028575&doi=10.1016%2fj.jmrt.2022.01.035&partnerID=40&md5=09422c87267cfff2d59d40b2fffa8a22
Quaternary glass series of nano and micro-particles europium oxide (III), i.e. Eu2O3, of composition [{(TeO2)0.7 (B2O3)0.3}0.7 (ZnO)0.3](1-y) (EnOm)y, where EnOm is nano or micro Eu2O3 particles coded as TBZEu-NPs and TBZEu-MPs with y = 1.0–5.0 mol% was prepared by melt-quenching technique. Using the pulse-echo technique, the ultrasonic velocities of the glasses were examined. The experimental value of TBZEu-NPs longitudinal, shear, bulk, and Young's modulus ranges between 53.469 and 85.259 GPa, 21.801–24.086 GPa, 24.401–54.790 GPa, and 50.394–61.419 GPa, respectively. For the TBZEu-MPs glasses, they ranged from 46.335 to 87.365 GPa, 21.645–24.649 GPa, 17.475–54.499 GPa, and 45.959–64.260 GPa, respectively. Density and elastic properties were predicted and simulated using an artificial neural network (ANN) model. The correlation coefficients for density, elastic moduli, and Poison's ratio obtained using the ANN model range from 0.9881 to 0.9997. The fitted R-squared value is greater than 95%, and the percentage error calculated is less than 7%. The obtained results were compared to those obtained using the Makishima-Mackenzie elastic model. The prepared glass sample's physical properties and elastic constants indicate that they are sufficiently strong for laser applications. © 2022
Elsevier Editora Ltda
22387854
English
Article
All Open Access; Gold Open Access
author Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
spellingShingle Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
author_facet Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
author_sort Adamu S.B.; Halimah M.K.; Chan K.T.; Muhammad F.D.; Nazrin S.N.; Scavino E.; Kamaruddin S.A.; Az'lina A.H.; Ghani N.A.M.
title Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
title_short Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
title_full Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
title_fullStr Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
title_full_unstemmed Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
title_sort Structural, prediction and simulation of elastic properties for tellurite based glass systems doped with nano and micro Eu2O3 particles via artificial neural network model
publishDate 2022
container_title Journal of Materials Research and Technology
container_volume 17
container_issue
doi_str_mv 10.1016/j.jmrt.2022.01.035
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123028575&doi=10.1016%2fj.jmrt.2022.01.035&partnerID=40&md5=09422c87267cfff2d59d40b2fffa8a22
description Quaternary glass series of nano and micro-particles europium oxide (III), i.e. Eu2O3, of composition [{(TeO2)0.7 (B2O3)0.3}0.7 (ZnO)0.3](1-y) (EnOm)y, where EnOm is nano or micro Eu2O3 particles coded as TBZEu-NPs and TBZEu-MPs with y = 1.0–5.0 mol% was prepared by melt-quenching technique. Using the pulse-echo technique, the ultrasonic velocities of the glasses were examined. The experimental value of TBZEu-NPs longitudinal, shear, bulk, and Young's modulus ranges between 53.469 and 85.259 GPa, 21.801–24.086 GPa, 24.401–54.790 GPa, and 50.394–61.419 GPa, respectively. For the TBZEu-MPs glasses, they ranged from 46.335 to 87.365 GPa, 21.645–24.649 GPa, 17.475–54.499 GPa, and 45.959–64.260 GPa, respectively. Density and elastic properties were predicted and simulated using an artificial neural network (ANN) model. The correlation coefficients for density, elastic moduli, and Poison's ratio obtained using the ANN model range from 0.9881 to 0.9997. The fitted R-squared value is greater than 95%, and the percentage error calculated is less than 7%. The obtained results were compared to those obtained using the Makishima-Mackenzie elastic model. The prepared glass sample's physical properties and elastic constants indicate that they are sufficiently strong for laser applications. © 2022
publisher Elsevier Editora Ltda
issn 22387854
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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