Multiobjective Optimization of Silver-Nanowire Deposition for Flexible Transparent Conducting Electrodes.

Lee, Mark; Piper, Robert T; Bhandari, Bishal; Hsu, Julia W P

Lee, Mark; Piper, Robert T; Bhandari, Bishal; Hsu, Julia W P.

Afiliación

Lee M; Department of Physics, University of Texas at Dallas, Richardson, Texas 75080, United States.
Piper RT; Department of Materials Science and Engineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Bhandari B; Department of Physics, University of Texas at Dallas, Richardson, Texas 75080, United States.
Hsu JWP; Department of Materials Science and Engineering, University of Texas at Dallas, Richardson, Texas 75080, United States.

ACS Appl Nano Mater ; 6(19): 17364-17368, 2023 Oct 13.

Article en En | MEDLINE | ID: mdl-37854852

RESUMEN

Optimizing the spin coating of silver nanowires to form transparent conducting electrodes (TCE) is guided by machine learning (ML). A good TCE has two competing characteristics: high transmittance and high conductance. Optimization using a scalar figure of merit, as often done in the field, cannot satisfy the independent requirements for transmittance and conductance imposed by specific applications. By performing a Pareto front analysis based on ML models, we show that the desired outcomes of transmittance ≥ 75% and sheet resistance ≤ 15 Ω/sq are challenging but can be achieved using processing parameters identified by ML analysis.

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: ACS Appl Nano Mater Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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