Microkinetic modeling of the water-gas shift reaction over cobalt catalysts supported on multi-walled carbon nanotubes (2020)
- Authors:
- USP affiliated authors: GIUDICI, REINALDO - EP ; ALVES, RITA MARIA DE BRITO - EP ; SCHMAL, MARTIN - EP ; CAVALCANTI, FÁBIO MACHADO - EP
- Unidade: EP
- DOI: 10.3390/ECCS2020-07581
- Subjects: CATALISADORES; NANOTUBOS DE CARBONO; HIDROGÊNIO
- Language: Inglês
- Imprenta:
- Source:
- Título: Chemistry Proceedings
- ISSN: 2673-4583
- Volume/Número/Paginação/Ano: v. 2, n. 1, p. 1-6, Nov. 2020
- Conference titles: International Electronic Conference on Catalysis Sciences
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
CAVALCANTI, Fábio Machado et al. Microkinetic modeling of the water-gas shift reaction over cobalt catalysts supported on multi-walled carbon nanotubes. Chemistry Proceedings. Basel: MDPI. Disponível em: https://doi.org/10.3390/ECCS2020-07581. Acesso em: 12 fev. 2026. , 2020 -
APA
Cavalcanti, F. M., Poissonnier, J., Vandevyvere, T., Giudici, R., Alves, R. M. de B., Schmal, M., & Thybaut, J. W. (2020). Microkinetic modeling of the water-gas shift reaction over cobalt catalysts supported on multi-walled carbon nanotubes. Chemistry Proceedings. Basel: MDPI. doi:10.3390/ECCS2020-07581 -
NLM
Cavalcanti FM, Poissonnier J, Vandevyvere T, Giudici R, Alves RM de B, Schmal M, Thybaut JW. Microkinetic modeling of the water-gas shift reaction over cobalt catalysts supported on multi-walled carbon nanotubes [Internet]. Chemistry Proceedings. 2020 ; No 2020( 1): 1-6.[citado 2026 fev. 12 ] Available from: https://doi.org/10.3390/ECCS2020-07581 -
Vancouver
Cavalcanti FM, Poissonnier J, Vandevyvere T, Giudici R, Alves RM de B, Schmal M, Thybaut JW. Microkinetic modeling of the water-gas shift reaction over cobalt catalysts supported on multi-walled carbon nanotubes [Internet]. Chemistry Proceedings. 2020 ; No 2020( 1): 1-6.[citado 2026 fev. 12 ] Available from: https://doi.org/10.3390/ECCS2020-07581 - Aprimorando o design de catalisadores com técnicas de Machine Learning: um estudo de caso para a Reação Water-Gas Shift
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Informações sobre o DOI: 10.3390/ECCS2020-07581 (Fonte: oaDOI API)
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