Machine Learning-Driven Characterization of Optical Materials: Predicting JO Parameters in Rare-Earth Doped Glasses
This paper presents a machine learning-driven approach for predicting the spectroscopic properties of rare-earth (RE) doped glass systems, with a focus on Dy3+ ions. Glass compositions of 0.25 PbO–0.2 SiO2–(0.55−x) B2O3–x Dy2O3 were synthesized using the melt-quenching technique, and their density,...
| الحاوية / القاعدة: | Chemical Review and Letters |
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| المؤلف الرئيسي: | |
| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Iranian Chemical Science and Technologies Association
2025
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| الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215939814&doi=10.22034%2fcrl.2024.488643.1474&partnerID=40&md5=b85ab45849a8633605d3963ea72ce0cf |