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Johnatan Mucelini
Johnatan Mucelini
PhD in Chemistry at University of São Paulo
Bestätigte E-Mail-Adresse bei usp.br - Startseite
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Zitiert von
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Machine learning prediction of nine molecular properties based on the SMILES representation of the QM9 quantum-chemistry dataset
GA Pinheiro, J Mucelini, MD Soares, RC Prati, JLF Da Silva, MG Quiles
The Journal of Physical Chemistry A 124 (47), 9854-9866, 2020
942020
Methane dehydrogenation on 3d 13-atom transition-metal clusters: A density functional theory investigation combined with Spearman rank correlation analysis
KF Andriani, J Mucelini, JLF Da Silva
Fuel 275, 117790, 2020
272020
Ab Initio Insights into the Formation Mechanisms of 55-Atom Pt-Based Core–Shell Nanoalloys
PCD Mendes, SG Justo, J Mucelini, MD Soares, KEA Batista, MG Quiles, ...
The Journal of Physical Chemistry C 124 (1), 1158-1164, 2019
272019
Ab initio investigation of the formation of ZrO2-like structures upon the adsorption of Zrn on the CeO2 (111) surface
J Mucelini, R Costa-Amaral, Y Seminovski, JLF Da Silva
The Journal of Chemical Physics 149 (24), 2018
132018
Ab initio insights into the structural, energetic, electronic, and stability properties of mixed Ce n Zr 15− n O 30 nanoclusters
P Felício-Sousa, J Mucelini, L Zibordi-Besse, KF Andriani, Y Seminovski, ...
Physical Chemistry Chemical Physics 21 (48), 26637-26646, 2019
112019
Understanding the interplay between π–π and cation–π interactions in [janusene–Ag]+ host–guest systems: a computational approach
J Mucelini, I Østrøm, AO Ortolan, KF Andriani, GF Caramori, RLT Parreira, ...
Dalton Transactions 48 (35), 13281-13292, 2019
72019
Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters
J Mucelini, MG Quiles, RC Prati, JLF Da Silva
Journal of Chemical Information and Modeling 61 (3), 1125-1135, 2021
32021
From Bulk CeO2 to Transition-Metal Clusters Supported on the CeO2(111) Surface: A Critical Discussion
RC Amaral, J Mucelini, Y Seminovski, JLF Da Silva
Encyclopedia of Interfacial Chemistry, 452--459, 2018
12018
Investigação das propriedades estruturais, energéticas e ópticas das perovskitas abx3 utilizando a teoria do funcional da densidade
MC Gallego, J Mucelini, S Malladi, JLF Silva
Resumos, 2020
2020
Estudo ab initio do papel dos átomos nas propriedades eletrônicas e estruturais das perovskitas
MC Gallego, J Mucelini, S Malladi, JLF Silva
Resumos, 2019
2019
Methane Dehydrogenation on 3d 13-Atoms Transition-metal Clusters–A DFT Investigation
KF Andriani, J Mucelini, JLF Da Silva
zeolites (Cu-MOR, Cu-ZSM-5) 24, 25, 2019
2019
Estudo ab initio da adsorção de átomos de zircônio sobre superfí­cies de óxido de cério: Zrn/CeO2(111)
J Mucelini
São Carlos Institute of Chemistry, 2018
2018
From bulk Ce O2 to transition-metal clusters supported on the CeO2 (111) surface
RC Amaral, J Mucelini, Y Seminovski, JLF Silva
Encyclopedia of Interfacial Chemistry: Surface Science and Electrochemistry, 2017
2017
A coordenaçãao dos janusenos: uma abordagem teórica do efeito dos ligantes
J Mucelini
Florianópolis, SC, 2016
2016
Combined Ab initio Calculation Plus Machine Learning Framework Applied to Perovskites Properties and Structural Study
MC Gallego, J Mucelini, JLF Da Silva
Center for Innovation on New Energies, 33, 0
Experimental Analysis of the Importance of the Descriptors to Reduce the Training and Validation Error
GAL Pinheiro, MD Soares, J Mucelini, JLF Da
Center for Innovation on New Energies, 60, 0
Data Mining and Statistical Tools based Framework to Investigate Quantum Chemistry Data
J Mucelini, MG Quiles, RC Prati, JLF Da Silva
Center for Innovation on New Energies, 62, 0
Methane Dehydrogenation on 13-Atom Transition-Metal (Fe, Co, Ni, Cu) via Density Functional Theory
KF Andriani, J Mucelini, JLF Da Silva
Center for Innovation on New Energies, 7, 0
Correlating Stability and the Properties of 55-Atom Bimetallic Pt-based Nanoalloys to Understand the Formation of Core-Shell Systems through Density Functional Theory
PCD Mendes, SG Justo, J Mucelini, MD Soares, KEA Batista, MG Quiles, ...
Center for Innovation on New Energies, 10, 0
Combination of Molecular Representations and Machine Learning Algorithms for a Set of Molecular Systems with the Same Number of Atoms
MD Soares, GA Pinheiro, J Mucelini, JLF Da Silva, MG Quiles
Center for Innovation on New Energies, 65, 0
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