Evaluation of fischer-tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network (2021)
- Authors:
- USP affiliated authors: SCHMAL, MARTIN - EP ; ALVES, RITA MARIA DE BRITO - EP ; GARONA, HIGOR AZEVEDO - EP ; CAVALCANTI, FÁBIO MACHADO - EP ; ABREU, VALDEIR ARAÚJO DE - EP
- Unidade: EP
- DOI: 10.1016/j.jclepro.2021.129003
- Subjects: REDES NEURAIS; DIÓXIDO DE CARBONO; CATALISADORES
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Cleaner Production
- ISSN: 0959-6526
- Volume/Número/Paginação/Ano: v.321, p. 1-13, Sept. 2021
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
GARONA, Higor Azevedo et al. Evaluation of fischer-tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network. Journal of Cleaner Production, v. 321, p. 1-13, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.jclepro.2021.129003. Acesso em: 12 fev. 2026. -
APA
Garona, H. A., Cavalcanti, F. M., Abreu, T. F. de, Schmal, M., & Alves, R. M. de B. (2021). Evaluation of fischer-tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network. Journal of Cleaner Production, 321, 1-13. doi:10.1016/j.jclepro.2021.129003 -
NLM
Garona HA, Cavalcanti FM, Abreu TF de, Schmal M, Alves RM de B. Evaluation of fischer-tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network [Internet]. Journal of Cleaner Production. 2021 ;321 1-13.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1016/j.jclepro.2021.129003 -
Vancouver
Garona HA, Cavalcanti FM, Abreu TF de, Schmal M, Alves RM de B. Evaluation of fischer-tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network [Internet]. Journal of Cleaner Production. 2021 ;321 1-13.[citado 2026 fev. 12 ] Available from: https://doi.org/10.1016/j.jclepro.2021.129003 - Using artificial neural networks for fischer-tropsch synthesis to lower-olefins production optimization
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Informações sobre o DOI: 10.1016/j.jclepro.2021.129003 (Fonte: oaDOI API)
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