Predicting the nonlinear refractive index in glassy materials using machine learning

• Grant number: 23/18280-1
• Support Opportunities: Scholarships in Brazil - Master
• Start date: August 01, 2024
• End date: February 28, 2026
• Field of knowledge: Physical Sciences and Mathematics - Physics
• Principal Investigator: Cleber Renato Mendonça
• Grantee: Murilo Neco Saraiva
• Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 18/11283-7 - Nonlinear photonics: spectroscopy and advanced processing of materials, AP.TEM

Abstract

Photonics is closely linked to non-linear Optics, which studies processes resulting from the interaction of light with matter in the regime of high light intensities. Thus, the development of new devices or applications in Photonics requires a comprehensive approach, integrating from fundamental studies in non-linear Optics to advanced material processing. This project is situated in the field of Photonics, addressing aspects of interest from the point of view of Basic Physics. Considering the potential of machine learning to play an important role in accelerating the development and application of materials, we propose, in this work, the application of neural networks to predict the effect of the vitreous matrix composition on the non-linear refractive index in glasses. Glasses have great applicability in the creation of photonic devices, in addition to exhibiting interesting photophysical properties and potential in the areas of telecommunications, quantum computing, and laser manufacturing. Therefore, the proposed project is aligned with the global advancement of research in the area of non-linear Photonics, a fundamental area for the generation of new technologies, also involving aspects of interest from the fundamental point of view.