Quantitative Image Analysis of Fractal-like Thin Films of Organic Semiconductors
2018-05-07T13:36:17Z (GMT) by
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-dioctylbenzothieno[3,2-b]benzothiophene (C<sub>8</sub>-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 C<sub>8</sub>-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.