I hold a bachelor's degree in Chemistry from the Federal University of Santa Catarina, which I obtained between 2013 and 2016. Subsequently, I pursued a Master's degree in Physical Chemistry at the São Carlos Institute of Chemistry, University of São Paulo, from 2016 to 2018. Throughout my undergraduate and master's studies, I focused on investigating various properties of organic molecules and oxide surfaces using the Density Functional Theory (DFT).
Since 2018, I have been pursuing a PhD at the São Carlos Institute of Chemistry, University of São Paulo. My current research is centered around data mining quantum chemistry datasets to extract valuable insights and knowledge. In addition to my doctoral studies, I am in the final stages of completing an MBA in Data Science and Analytics at Luiz de Queiroz College of Agriculture, University of São Paulo. As part of my MBA program, I conducted research utilizing Web Scraping to collect thousands of news and Natural Language Processing (NLP) techniques to analyze media bias.
During the first phase of my PhD, from 2018 to 2021, I worked under the supervision of Prof. Dr. Juarez L. F. Da Silva. I am now in the process of developing the second part of my PhD research under the guidance of Albérico Borges Ferreira da Silva.
Additionally, I engage in freelance work as a scientific illustrator, where I utilize my skills to visually communicate scientific concepts and ideas.
PhD in Physical Chemistry (2018-Present)
MBA in Data Science and Analytics (2021-Present)
MSc in Physical Chemistry (2016-2018)
BSc in Chemistry (2013-2016)
As a freelance scientific illustrator, I go by the artistic name Atomic Render.
You can check out my illustrations on Instagram @atomic.render
For a detailed portfolio, please access my online portfolio , or download it .
Art for presentations:
Animation based on paper result: Transition Metal clusters of Fe, Co, Ni, and Cu growing until 15 atoms. I processed and rendered the cluster's structures, which were previously developed in my research group (QTNano) by Dr. Anderson S. Chaves and coworkers (Phys. Chem. Chem. Phys., 2017,19, 15484-15502).
Graphical entry of the publication: Ab initio investigation of the role of the d-states occupation on the adsorption properties of H2, CO, CH4 and CH3OH on the Fe13, Co13, Ni13 and Cu13 clusters
This algorithm generates sets of atomic structures of two adsorbed molecules, considering ridge structures and atoms as spheres of VDW radius.
My methods mimic the ideia that two melecules could interact based on different chemical environments on the surface of the molecules. First, it get a representative sets of chemical environments of each one of the molecules. Second, we find structures combining the molecules through each possible pair of chemical environments in the molecules. Finally, this poll of structures is sampled to find a representative set of thepossible ways of interaction.
This python script analyzes which atoms of a molecule (in xyz file, for instance) are exposed to the vacuum and is exposed area.
The atoms exposed to the vacuum could be considered surface atoms and often play important roles in the physical-chemical properties of small clusters/nanoclusters/nanostructures. I strongly recommend this analysis for the investigations of structures with more than 20 atoms.
I developed and implemented this methodology. Check a detailed description in Section V of this document.
This python script calculates, for each atom i, the effective coordination number (ECNi) and the average bond distance (davi), based on the weights the effective coordination (Pij) with other atoms j.
My implementation works with any atomic structures file readable by ase (atomic simulation environment), including structures with periodic boundary conditions. Method developed by Da Silva, et al..
A python package that presents several tools to deal with Quantum Chemistry (QC) data of molecular systems (non-periodic): extraction of data from QC calculations; structural analysis, such as effective coordination bonds and surface atoms analysis (see above); Atomic to Molecular Featurization (see above); correlation and correlation significance analysis with bootstrap approaches.
The version presented here is an old version of Quandarium. I am developing the 1.0.0 version, which I expect to release soon, together with more tools and information about how to install and use it.
The following papers employed AtoMF features:
I am working on developing models that facilitate the extraction of knowledge and the relationship between AtoMF features and the targets.
I am also working on anlysis
Scientific illustration portfolio:
E-mail is the best way to get in touch with me.