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  • Source: Chemical Engineering and Processing. Unidade: EP

    Subjects: FOTOQUÍMICA, PESO MOLECULAR (DISTRIBUIÇÃO), POLIMERIZAÇÃO, POLÍMEROS (MATERIAIS) (PROPRIEDADES), REAÇÕES QUÍMICAS, REATORES QUÍMICOS

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    • ABNT

      TEIXEIRA, Soraia et al. Approaches towards a technically feasible photoinitiated prepolymerization of methly methacrylate. Chemical Engineering and Processing, v. 43, n. 10, p. 1317-1328, 2004Tradução . . Disponível em: https://doi.org/10.1016/j.cep.2003.12.007. Acesso em: 25 nov. 2025.
    • APA

      Teixeira, S., Giudici, R., Bossmann, S. H., Lang, J., & Braun, A. M. (2004). Approaches towards a technically feasible photoinitiated prepolymerization of methly methacrylate. Chemical Engineering and Processing, 43( 10), 1317-1328. doi:10.1016/j.cep.2003.12.007
    • NLM

      Teixeira S, Giudici R, Bossmann SH, Lang J, Braun AM. Approaches towards a technically feasible photoinitiated prepolymerization of methly methacrylate. [Internet]. Chemical Engineering and Processing. 2004 ;43( 10): 1317-1328.[citado 2025 nov. 25 ] Available from: https://doi.org/10.1016/j.cep.2003.12.007
    • Vancouver

      Teixeira S, Giudici R, Bossmann SH, Lang J, Braun AM. Approaches towards a technically feasible photoinitiated prepolymerization of methly methacrylate. [Internet]. Chemical Engineering and Processing. 2004 ;43( 10): 1317-1328.[citado 2025 nov. 25 ] Available from: https://doi.org/10.1016/j.cep.2003.12.007
  • Source: Water Science And Technology. Unidade: EP

    Subjects: ESTATÍSTICA APLICADA, FOTOQUÍMICA, REDES NEURAIS

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    • ABNT

      GÖB, Sabine et al. Optimal experimental design and artificial neural networks applied to the photochemically enhanced Fenton reaction. Water Science And Technology, v. 44, n. 5, p. 339-345, 2001Tradução . . Disponível em: https://doi.org/10.2166/wst.2001.0321. Acesso em: 25 nov. 2025.
    • APA

      Göb, S., Bossmann, S. H., Braun, A. M., Oliveros, E., Nascimento, C. A. O. do, & Guardani, R. (2001). Optimal experimental design and artificial neural networks applied to the photochemically enhanced Fenton reaction. Water Science And Technology, 44( 5), 339-345. doi:10.2166/wst.2001.0321
    • NLM

      Göb S, Bossmann SH, Braun AM, Oliveros E, Nascimento CAO do, Guardani R. Optimal experimental design and artificial neural networks applied to the photochemically enhanced Fenton reaction [Internet]. Water Science And Technology. 2001 ; 44( 5): 339-345.[citado 2025 nov. 25 ] Available from: https://doi.org/10.2166/wst.2001.0321
    • Vancouver

      Göb S, Bossmann SH, Braun AM, Oliveros E, Nascimento CAO do, Guardani R. Optimal experimental design and artificial neural networks applied to the photochemically enhanced Fenton reaction [Internet]. Water Science And Technology. 2001 ; 44( 5): 339-345.[citado 2025 nov. 25 ] Available from: https://doi.org/10.2166/wst.2001.0321
  • Source: Chemical Engineering and Processing. Unidade: EP

    Subjects: REDES NEURAIS, TRATAMENTO DE ÁGUAS RESIDUÁRIAS

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    • ABNT

      GOB, Sabine et al. Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks. Chemical Engineering and Processing, v. 38, n. 4-6, p. 373-382, 1999Tradução . . Disponível em: https://doi.org/10.1016/s0255-2701(99)00028-8. Acesso em: 25 nov. 2025.
    • APA

      Gob, S., Oliveros, E., Bossmann, S. H., Guardani, R., & Nascimento, C. A. O. do. (1999). Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks. Chemical Engineering and Processing, 38( 4-6), 373-382. doi:10.1016/s0255-2701(99)00028-8
    • NLM

      Gob S, Oliveros E, Bossmann SH, Guardani R, Nascimento CAO do. Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks [Internet]. Chemical Engineering and Processing. 1999 ; 38( 4-6): 373-382.[citado 2025 nov. 25 ] Available from: https://doi.org/10.1016/s0255-2701(99)00028-8
    • Vancouver

      Gob S, Oliveros E, Bossmann SH, Guardani R, Nascimento CAO do. Modeling the kinetics of a photochemical water treatment process by means of artificial neural networks [Internet]. Chemical Engineering and Processing. 1999 ; 38( 4-6): 373-382.[citado 2025 nov. 25 ] Available from: https://doi.org/10.1016/s0255-2701(99)00028-8

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