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Artigo de periodico
Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach (2024)
Gul, Saima; Hussain, Sajjad ; Khan, Hammad ; Arshad, Muhammad; Khan, Javaid Rabbani ; Motheo, Artur de Jesus
Source: Chemosphere. Unidade: IQSC
Subjects: INTELIGÊNCIA ARTIFICIAL, REDES NEURAIS, ANTIBIÓTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GUL, Saima et al. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach. Chemosphere, v. 357, p. 141868, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.chemosphere.2024.141868. Acesso em: 16 nov. 2024.
APA
Gul, S., Hussain, S., Khan, H., Arshad, M., Khan, J. R., & Motheo, A. de J. (2024). Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach. Chemosphere, 357, 141868. doi:10.1016/j.chemosphere.2024.141868
NLM
Gul S, Hussain S, Khan H, Arshad M, Khan JR, Motheo A de J. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach [Internet]. Chemosphere. 2024 ; 357 141868.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.chemosphere.2024.141868
Vancouver
Gul S, Hussain S, Khan H, Arshad M, Khan JR, Motheo A de J. Integrated AI-driven optimization of Fenton process for the treatment of antibiotic sulfamethoxazole: Insights into mechanistic approach [Internet]. Chemosphere. 2024 ; 357 141868.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.chemosphere.2024.141868
Artigo de periodico
Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study (2021)
Hussain, Sajjad; Khan, Hammad; Gul, Saima; Steter, Juliana R; Motheo, Artur de Jesus
Source: Chemosphere. Unidade: IQSC
Subjects: TRATAMENTO QUÍMICO DE ÁGUAS RESIDUÁRIAS, FÁRMACOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HUSSAIN, Sajjad et al. Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study. Chemosphere, v. 276, n. 130151 August 2021, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.chemosphere.2021.130151. Acesso em: 16 nov. 2024.
APA
Hussain, S., Khan, H., Gul, S., Steter, J. R., & Motheo, A. de J. (2021). Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study. Chemosphere, 276( 130151 August 2021). doi:10.1016/j.chemosphere.2021.130151
NLM
Hussain S, Khan H, Gul S, Steter JR, Motheo A de J. Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study [Internet]. Chemosphere. 2021 ; 276( 130151 August 2021):[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.chemosphere.2021.130151
Vancouver
Hussain S, Khan H, Gul S, Steter JR, Motheo A de J. Modeling of photolytic degradation of sulfamethoxazole using boosted regression tree (BRT), artificial neural network (ANN) and response surface methodology (RSM); energy consumption and intermediates study [Internet]. Chemosphere. 2021 ; 276( 130151 August 2021):[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.chemosphere.2021.130151
Artigo de periodico
Photo-assisted electrochemical degradation of sulfamethoxazole using a Ti/Ru0.3Ti0.7O2 anode: Mechanistic and kinetic features of the process (2017)
Hussain, Sajjad; Steter, Juliana Ribeiro; Gul, Saima; Motheo, Artur de Jesus
Source: Journal of Environmental Management. Unidade: IQSC
Subjects: ANTIBIÓTICOS, MEIO AMBIENTE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HUSSAIN, Sajjad et al. Photo-assisted electrochemical degradation of sulfamethoxazole using a Ti/Ru0.3Ti0.7O2 anode: Mechanistic and kinetic features of the process. Journal of Environmental Management, v. 201, p. 153-162, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.jenvman.2017.06.043. Acesso em: 16 nov. 2024.
APA
Hussain, S., Steter, J. R., Gul, S., & Motheo, A. de J. (2017). Photo-assisted electrochemical degradation of sulfamethoxazole using a Ti/Ru0.3Ti0.7O2 anode: Mechanistic and kinetic features of the process. Journal of Environmental Management, 201, 153-162. doi:10.1016/j.jenvman.2017.06.043
NLM
Hussain S, Steter JR, Gul S, Motheo A de J. Photo-assisted electrochemical degradation of sulfamethoxazole using a Ti/Ru0.3Ti0.7O2 anode: Mechanistic and kinetic features of the process [Internet]. Journal of Environmental Management. 2017 ; 201 153-162.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.jenvman.2017.06.043
Vancouver
Hussain S, Steter JR, Gul S, Motheo A de J. Photo-assisted electrochemical degradation of sulfamethoxazole using a Ti/Ru0.3Ti0.7O2 anode: Mechanistic and kinetic features of the process [Internet]. Journal of Environmental Management. 2017 ; 201 153-162.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.jenvman.2017.06.043

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