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Filtros : "ACS Applied Nano Materials" "GRU015" Limpar

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  • Artigo de periodico

    A comprehensive comparison among capacitive, thermodynamic, and drift-diffusion models for steady-state responses of nanostructured organic electrochemical transistors (2025)

    Unigarro, Andres David Peña ; Günther, Florian Steffen

    Fonte: ACS Applied Nano Materials. Unidade: IFSC

    Assuntos: SEMICONDUTORES, POLÍMEROS (MATERIAIS), NANOELETRÔNICA

    Versão PublicadaAcesso à fonteDOIComo citar
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    • ABNT

      UNIGARRO, Andres David Peña e GÜNTHER, Florian Steffen. A comprehensive comparison among capacitive, thermodynamic, and drift-diffusion models for steady-state responses of nanostructured organic electrochemical transistors. ACS Applied Nano Materials, v. 8, n. 23, p. 12329-12341 + supporting information, 2025Tradução . . Disponível em: https://doi.org/10.1021/acsanm.5c02101. Acesso em: 18 nov. 2025.

    • APA

      Unigarro, A. D. P., & Günther, F. S. (2025). A comprehensive comparison among capacitive, thermodynamic, and drift-diffusion models for steady-state responses of nanostructured organic electrochemical transistors. ACS Applied Nano Materials, 8( 23), 12329-12341 + supporting information. doi:10.1021/acsanm.5c02101

    • NLM

      Unigarro ADP, Günther FS. A comprehensive comparison among capacitive, thermodynamic, and drift-diffusion models for steady-state responses of nanostructured organic electrochemical transistors [Internet]. ACS Applied Nano Materials. 2025 ; 8( 23): 12329-12341 + supporting information.[citado 2025 nov. 18 ] Available from: https://doi.org/10.1021/acsanm.5c02101

    • Vancouver

      Unigarro ADP, Günther FS. A comprehensive comparison among capacitive, thermodynamic, and drift-diffusion models for steady-state responses of nanostructured organic electrochemical transistors [Internet]. ACS Applied Nano Materials. 2025 ; 8( 23): 12329-12341 + supporting information.[citado 2025 nov. 18 ] Available from: https://doi.org/10.1021/acsanm.5c02101

  • Artigo de periodico

    Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection (2024)

    Pazin, Wallance Moreira ; Furini, Leonardo Negri; Braz, Daniel César ; Popolin Neto, Mário ; Fernandes, José Diego ; Constantino, Carlos José Leopoldo ; Oliveira Junior, Osvaldo Novais de

    Fonte: ACS Applied Nano Materials. Unidades: IFSC, ICMC

    Assuntos: APRENDIZADO COMPUTACIONAL, COVID-19, EFEITO RAMAN

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    • ABNT

      PAZIN, Wallance Moreira et al. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, v. 7, n. Ja 2024, p. 2335-2342, 2024Tradução . . Disponível em: https://doi.org/10.1021/acsanm.3c05848. Acesso em: 18 nov. 2025.

    • APA

      Pazin, W. M., Furini, L. N., Braz, D. C., Popolin Neto, M., Fernandes, J. D., Constantino, C. J. L., & Oliveira Junior, O. N. de. (2024). Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection. ACS Applied Nano Materials, 7( Ja 2024), 2335-2342. doi:10.1021/acsanm.3c05848

    • NLM

      Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2025 nov. 18 ] Available from: https://doi.org/10.1021/acsanm.3c05848

    • Vancouver

      Pazin WM, Furini LN, Braz DC, Popolin Neto M, Fernandes JD, Constantino CJL, Oliveira Junior ON de. Explainable machine learning to unveil detection mechanisms with au nanoisland-based surface-enhanced raman scattering for SARS-CoV-2 antigen detection [Internet]. ACS Applied Nano Materials. 2024 ; 7( Ja 2024): 2335-2342.[citado 2025 nov. 18 ] Available from: https://doi.org/10.1021/acsanm.3c05848
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