Manipulation and statistical analysis of the fluid flow of polymer semiconductor solutions during meniscus-guided coating

Leo Shaw, Ying Diao, Geoffrey C. Martin-Noble, Hongping Yan, Pascal Hayoz, R. Thomas Weitz, Daniel Kaelblein, Michael F. Toney, Zhenan Bao

Research output: Contribution to journalArticlepeer-review

Abstract

Recent work in structure-processing relationships of polymer semiconductors have demonstrated the versatility and control of thin-film microstructure offered by meniscus-guided coating (MGC) techniques. Here, we analyze the qualitative and quantitative aspects of solution shearing, a model MGC method, using coating blades augmented with arrays of pillars. The pillars induce local regions of high strain rates-both shear and extensional-not otherwise possible with unmodified blades, and we use fluid mechanical simulations to model and study a variety of pillar spacings and densities. We then perform a statistical analysis of 130 simulation variables to find correlations with three dependent variables of interest: Thin-film degree of crystallinity and transistor field-effect mobilities for charge-transport parallel (μpara) and perpendicular (μperp) to the coating direction. Our study suggests that simple fluid mechanical models can reproduce substantive correlations between the induced fluid flow and important performance metrics, providing a methodology for optimizing blade design.

Original languageEnglish (US)
JournalMRS Bulletin
DOIs
StateAccepted/In press - 2020

Keywords

  • polymer
  • semiconducting
  • simulation
  • solution deposition
  • statistics

ASJC Scopus subject areas

  • Materials Science(all)
  • Condensed Matter Physics
  • Physical and Theoretical Chemistry

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