Materials Science

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

Ying Diao University of Illinois at Urbana−Champaign


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.


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Supplementary material

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SI Image analysis Zhu, Diao Apr2018