Quantitative Image Analysis of Fractal-Like Thin Films of Organic Semiconductors

Weikun Zhu, Erfan Mohammadi, Ying Diao

Research output: Contribution to journalArticle

Abstract

Morphology modulation offers significant control over organic electronic device performance. However, morphology quantification has been rarely carried out via image analysis. In this work, we designed a MATLAB program to evaluate two key parameters describing morphology of small molecule semiconductor thin films: fractal dimension and film coverage. We then use this program in a case study of meniscus-guided coating of 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) under various conditions to analyze a diverse and complex morphology set. The evolution of morphology in terms of fractal dimension and film coverage was studied as a function of coating speed. We discovered that combined fractal dimension and film coverage can quantitatively capture the key characteristics of C8-BTBT thin film morphology; change of these two parameters further inform morphology transition. Furthermore, fractal dimension could potentially shed light on thin film growth mechanisms.

Original languageEnglish (US)
Pages (from-to)1622-1634
Number of pages13
JournalJournal of Polymer Science, Part B: Polymer Physics
Volume57
Issue number23
DOIs
StatePublished - Dec 1 2019

Keywords

  • coverage
  • fractal dimension
  • image analysis
  • organic semiconductor
  • solution processing

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Physical and Theoretical Chemistry
  • Polymers and Plastics
  • Materials Chemistry

Fingerprint Dive into the research topics of 'Quantitative Image Analysis of Fractal-Like Thin Films of Organic Semiconductors'. Together they form a unique fingerprint.

  • Cite this