CV Lattes
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Ministério da Ciência, Tecnologia e Inovação (Brasil). Centro Nacional de Pesquisa em Energia e Materiais (CNPEM) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Daniel holds a PhD in Materials Science and Engineering from the Federal University of São Carlos (UFSCar, 2014), through a CAPES grade-7 program, with a FAPESP fellowship, under the supervision of Prof. Dr. Edgar Dutra Zanotto. Bachelor's degree in Materials Engineering from UFSCar (2009), with emphasis in Polymeric Materials. Postdoctoral researcher at the Laboratory of Vitreous Materials of São Carlos (LaMaV). Currently Assistant Professor in the Bachelor's degree program in Science and Technology at Ilum School of Science, part of the Brazilian Center for Research in Energy and Materials (CNPEM). Develops research at the interface between data science and materials science (materials informatics), focusing on the development of predictive models to accelerate the discovery of new materials of technological interest. Has special interest in explainable artificial intelligence, including interpretable models and explanation tools for machine learning models. (Source: Lattes Curriculum)
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Predictive models of material properties can be used for inverse design, that is, the search for materials that satisfy certain desired design constraints. Therefore, predictive models with better performance are desired, since the better the performance, the more efficient the inverse design search will be. Recently, a new predictive model capable of predicting 85 properties of glass mat…
Heated glasses undergo a variety of kinetic processes that are very important both scientifically and technologically, such as crystallization. When controlled, crystallization is the key to make glass-ceramics but it must be avoided in order to make a glass. In this research we will study some microscopic aspects of crystallization. For example, we want to investigate the eluding "diffus…
The Stokes-Einstein/Eyring (SEE) equations are frequently used to estimate the effective diffusion coefficients that control crystallization by using viscosity data. Such equation is accepted for low to medium values of viscosity (10^-1 - 10^5 Pa.s) but has been questioned for higher viscosities (near 10^12 Pa.s). Nucleation and crystal growth mechanisms have received increasing attention…
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