“pySiRC”: machine learning combined with molecular fingerprints to predict the reaction rate constant of the radical-based oxidation processes of aqueous organic contaminants

Sanches Neto, Flávio Olimpio; Silva, Jefferson Richard Dias da; Queiroz Júnior, Luiz Henrique Keng; Silva, Valter Henrique Carvalho

“pySiRC”: machine learning combined with molecular fingerprints to predict the reaction rate constant of the radical-based oxidation processes of aqueous organic contaminants

Data

2021-09-02

Autores

Sanches Neto, Flávio Olimpio

Silva, Jefferson Richard Dias da

Queiroz Júnior, Luiz Henrique Keng

Silva, Valter Henrique Carvalho

Palavras-chave

Artificial intelligence, Emerging contaminant degradation, Kinetic parameters, Apps and web applications

Citação

SANCHES-NETO, Flávio Olimpio et al. “pySiRC”: machine learning combined with molecular fingerprints to predict the reaction rate constant of the radical-based oxidation processes of aqueous organic contaminants. Environmental Science & Technology, Washington, v. 55, n. 18, p. 12437-12448, 2021. DOI: 10.1021/acs.est.1c04326. Disponível em: https://pubs.acs.org/doi/10.1021/acs.est.1c04326. Acesso em: 8 mar. 2024.