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The Electro-Optical Performance of Silver Nanowire Networks.
Manning, Hugh G; da Rocha, Claudia Gomes; Callaghan, Colin O'; Ferreira, Mauro S; Boland, John J.
Afiliação
  • Manning HG; School of Chemistry, Trinity College Dublin, Dublin 2, Ireland. manninh@tcd.ie.
  • da Rocha CG; Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) & Advanced Materials and Bioengineering Research (AMBER) Centre, Trinity College Dublin, Dublin 2, Ireland. manninh@tcd.ie.
  • Callaghan CO; Department of Physics and Astronomy, University of Calgary, 2500 University Drive NW Calgary, Alberta, T2N 1N4, Canada.
  • Ferreira MS; School of Physics, Trinity College Dublin, Dublin 2, Ireland.
  • Boland JJ; Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) & Advanced Materials and Bioengineering Research (AMBER) Centre, Trinity College Dublin, Dublin 2, Ireland.
Sci Rep ; 9(1): 11550, 2019 Aug 09.
Article em En | MEDLINE | ID: mdl-31399603
Networks of metallic nanowires have the potential to meet the needs of next-generation device technologies that require flexible transparent conductors. At present, there does not exist a first principles model capable of predicting the electro-optical performance of a nanowire network. Here we combine an electrical model derived from fundamental material properties and electrical equations with an optical model based on Mie theory scattering of light by small particles. This approach enables the generation of analogues for any nanowire network and then accurately predicts, without the use of fitting factors, the optical transmittance and sheet resistance of the transparent electrode. Predictions are validated using experimental data from the literature of networks comprised of a wide range of aspect ratios (nanowire length/diameter). The separation of the contributions of the material resistance and the junction resistance allows the effectiveness of post-deposition processing methods to be evaluated and provides a benchmark for the minimum attainable sheet resistance. The predictive power of this model enables a material-by-design approach, whereby suitable systems can be prescribed for targeted technology applications.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article