Structure-Informed Design of Optical Oxide Glasses via Machine Learning and Solid-State NMR

• Grant number: 25/13921-4
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2025
• End date: July 31, 2027
• Field of knowledge: Engineering - Materials and Metallurgical Engineering - Nonmetallic Materials
• Principal Investigator: Edgar Dutra Zanotto
• Grantee: André Tamake Yoshioka
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 13/07793-6 - CEPIV - Center for Teaching, Research and Innovation in Glass, AP.CEPID

Abstract

This master's project aims to develop and characterize new oxide glasses with optimized optical properties by integrating our current understanding of glass structure, physicochemical characterization, and machine learning (ML) algorithms. Focus will be placed on the rational design of silicate-based glasses with low silica content, particularly lead-free systems incorporating ZnO, TiO2, and Nb2O5 - oxides often proposed by ML models to enhance refractive index, transparency, and thermal stability.Beyond the objective of developing high-performance optical glasses, the project also seeks to address a fundamental scientific question: how do intermediate oxides (such as Nb2O5) structurally integrate into significantly depolymerized silicate glass networks, and how does their local environment influence the overall network connectivity and the macroscopic optical properties? These questions will be explored using solid-state nuclear magnetic resonance (NMR) spectroscopy - especially 29Si magic-angle-spinning (MAS) NMR techniques - and Raman spectroscopy, which together provide insight into the degree of network polymerization, the presence of non-bridging oxygens, and potential formation of mixed bonding environments involving Nb-O-Si linkages.The combined application of predictive ML models and experimental structure-property analysis aims to establish robust correlations between glass composition, atomic-scale structure, and optical performance. The expected outcomes will contribute both to the practical development of next-generation optical glasses and to a deeper understanding of the structural role of intermediate oxides in complex glass systems.¿