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

07 May 2018, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


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 employ 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.


image analysis
organic electronics
solution coating
thin film morphology
fractal dimension

Supplementary materials

SI Image analysis Zhu, Diao Apr2018


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