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Artigo de periodico
Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining (2022)
Moraes, Alex S.; Pinheiro, Gabriel A.; Lourenço, Tuanan da Costa ; Lopes, Mauro C.; Quiles, Marcos G.; Dias, Luis G. ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidades: FFCLRP, IQSC
Assuntos: ÍONS ELETRÔNICOS, ESTRUTURA ATÔMICA (QUÍMICA TEÓRICA), ENERGIA
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ABNT
MORAES, Alex S. et al. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, v. 62, n. 19, p. 4702–4712, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00748. Acesso em: 08 out. 2025.
APA
Moraes, A. S., Pinheiro, G. A., Lourenço, T. da C., Lopes, M. C., Quiles, M. G., Dias, L. G., & Silva, J. L. F. da. (2022). Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, 62( 19), 4702–4712. doi:10.1021/acs.jcim.2c00748
NLM
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Vancouver
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Artigo de periodico
Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles (2022)
Mendonça, João Paulo A. de ; Calderan, Felipe V.; Lourenço, Tuanan da Costa ; Quiles, Marcos G.; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: COMBUSTÍVEIS, COBRE, NANOCOMPOSITOS
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ABNT
MENDONÇA, João Paulo A. de et al. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, v. 27, p. 5503-5512, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00957. Acesso em: 08 out. 2025.
APA
Mendonça, J. P. A. de, Calderan, F. V., Lourenço, T. da C., Quiles, M. G., & Silva, J. L. F. da. (2022). Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, 27, 5503-5512. doi:10.1021/acs.jcim.2c00957
NLM
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957
Vancouver
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957
Artigo de periodico
Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters (2021)
Batista, Krys E. A.; Soares, Marinalva D.; Quiles, Marcos G.; Piotrowski, Maurício J.; Da Silva, Juarez Lopes Ferreira
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: METAIS, ADSORÇÃO, FÍSICO-QUÍMICA
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ABNT
BATISTA, Krys E. A. et al. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters. Journal of Chemical Information and Modeling, v. 61, n. 5, p. 2294–2301, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00097. Acesso em: 08 out. 2025.
APA
Batista, K. E. A., Soares, M. D., Quiles, M. G., Piotrowski, M. J., & Da Silva, J. L. F. (2021). Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters. Journal of Chemical Information and Modeling, 61( 5), 2294–2301. doi:10.1021/acs.jcim.1c00097
NLM
Batista KEA, Soares MD, Quiles MG, Piotrowski MJ, Da Silva JLF. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 5): 2294–2301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00097
Vancouver
Batista KEA, Soares MD, Quiles MG, Piotrowski MJ, Da Silva JLF. Energy Decomposition to Access the Stability Changes Induced by CO Adsorption on Transition-Metal 13-Atom Clusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 5): 2294–2301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00097
Artigo de periodico
Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition (2021)
Azevedo, Luis Cesar de; Pinheiro, Gabriel A.; Quiles, Marcos G.; Silva, Juarez Lopes Ferreira da ; Prati, Ronaldo C.
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: QUÍMICA QUÂNTICA, ALGORITMOS
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ABNT
AZEVEDO, Luis Cesar de et al. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition. Journal of Chemical Information and Modeling, v. 61, p. 4210−4223, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00503. Acesso em: 08 out. 2025.
APA
Azevedo, L. C. de, Pinheiro, G. A., Quiles, M. G., Silva, J. L. F. da, & Prati, R. C. (2021). Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition. Journal of Chemical Information and Modeling, 61, 4210−4223. doi:10.1021/acs.jcim.1c00503
NLM
Azevedo LC de, Pinheiro GA, Quiles MG, Silva JLF da, Prati RC. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4210−4223.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00503
Vancouver
Azevedo LC de, Pinheiro GA, Quiles MG, Silva JLF da, Prati RC. Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 4210−4223.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00503

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