Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis
The optical, structural, and physical characteristics of zinc tellurite glasses doped with neodymium oxide nanoparticles, which are produced by the melt-quenching method, were examined in this work. The amorphous character of the glasses was verified by XRD analysis. Using the Pair Distribution Func...
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Politeknik Negeri Padang
2025
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| author | Nazrin S.N. Zaman H.B. Jothi N. Jouay D. Lahrach B. Halimah M.K. |
| author2 | 57201365934 |
| author_facet | 57201365934 Nazrin S.N. Zaman H.B. Jothi N. Jouay D. Lahrach B. Halimah M.K. |
| author_sort | Nazrin S.N. |
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| continent | Asia |
| country | Malaysia |
| description | The optical, structural, and physical characteristics of zinc tellurite glasses doped with neodymium oxide nanoparticles, which are produced by the melt-quenching method, were examined in this work. The amorphous character of the glasses was verified by XRD analysis. Using the Pair Distribution Function (PDF) and Monte Carlo simulations and visualisation for precise molecule distribution representation, an intuitive Python interface was created to emphasize these features. The density increased with increasing Nd2O3 concentrations, from 5346 to 5606 kg/cm2. Density data was used to infer the molar volume. The best projected density was achieved by the Gradient Boosting Regressor model, with a R2 of 0.9988 and an RMSE of 0.0032; the best predicted molar volume was achieved by linear regression, with a R2 of 1 and an RMSE of 2.67e-15. These models successfully represent the correlations between dopant concentration and glass properties, advancing our knowledge of the optical properties for further glass technology research. ? 2024, Politeknik Negeri Padang. All rights reserved. |
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| id | my.uniten.dspace-36965 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Politeknik Negeri Padang |
| record_format | dspace |
| spelling | my.uniten.dspace-369652025-03-03T15:46:10Z Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis Nazrin S.N. Zaman H.B. Jothi N. Jouay D. Lahrach B. Halimah M.K. 57201365934 57226220128 54928769700 59377286400 59377286500 12784680800 The optical, structural, and physical characteristics of zinc tellurite glasses doped with neodymium oxide nanoparticles, which are produced by the melt-quenching method, were examined in this work. The amorphous character of the glasses was verified by XRD analysis. Using the Pair Distribution Function (PDF) and Monte Carlo simulations and visualisation for precise molecule distribution representation, an intuitive Python interface was created to emphasize these features. The density increased with increasing Nd2O3 concentrations, from 5346 to 5606 kg/cm2. Density data was used to infer the molar volume. The best projected density was achieved by the Gradient Boosting Regressor model, with a R2 of 0.9988 and an RMSE of 0.0032; the best predicted molar volume was achieved by linear regression, with a R2 of 1 and an RMSE of 2.67e-15. These models successfully represent the correlations between dopant concentration and glass properties, advancing our knowledge of the optical properties for further glass technology research. ? 2024, Politeknik Negeri Padang. All rights reserved. Final 2025-03-03T07:46:10Z 2025-03-03T07:46:10Z 2024 Article 10.62527/joiv.8.3.3097 2-s2.0-85207006029 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207006029&doi=10.62527%2fjoiv.8.3.3097&partnerID=40&md5=36d0d31a51e0d3360bf384e30df29c8a https://irepository.uniten.edu.my/handle/123456789/36965 8 3 1476 1486 All Open Access; Gold Open Access Politeknik Negeri Padang Scopus |
| spellingShingle | Nazrin S.N. Zaman H.B. Jothi N. Jouay D. Lahrach B. Halimah M.K. Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title | Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title_full | Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title_fullStr | Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title_full_unstemmed | Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title_short | Atomic Structure Simulation and Properties? Prediction using Machine Learning on Neodymium Oxide Nanoparticles Zinc Tellurite Glasses Aided by FTIR and TEM Analysis |
| title_sort | atomic structure simulation and properties? prediction using machine learning on neodymium oxide nanoparticles zinc tellurite glasses aided by ftir and tem analysis |
| url_provider | http://dspace.uniten.edu.my/ |