Analysing hyperspectral image features to optimize degree of crystallinity in molecularly-doped P3HT thin films - Saif Ali Khan Shahrull Khan (Nanyang Technological University, 2021)
Conjugated polymers are materials that have high potential and applicability in many types of electronic devices ranging from thermoelectric materials to photovoltaic applications. It has many beneficial qualities due to its cheaper cost of fabrication, low thermal conductivity, and chemical stability. However, these polymers are intrinsically influenced by their processing conditions during fabrication which results in the variation of their electric properties. Due to their ability of being solution processed, parameters involved in spin coating like spin speed and spin time are crucial factors that determine the morphology and crystallinity of the films. In this experiment, we are trying to show the correlation of crystallinity to its electrical performance. However, we are using hyperspectral imaging (HSI) as a proxy tool to investigate the crystallinity of the material from its absorbance spectra. Hyperspectral imaging is a new spectroscopic tool that offers vast amount spectral and spatial information that are being exploited in many fields ranging from medical to food technology. Here, we are employing HSI to showcase its effectiveness in correlating crystallinity of the films to its electrical performance. P3HT is a well-studied conjugated polymer with observable features within the UV-VIS region. Together with its trait of solution processability, this is a suitable material to be used in this case study. Through this investigation, we were able to show a correlation between higher annealing temperature to narrower full-width half maximum (FWHM) of the interchain absorption. To understand this significance, we employed the Spano Analysis which is key to the calculation of excitonic widths of the films. To corroborate our results, we employed additional characterisation method like four -point probe to provide a link between improved crystallinity and improved electrical conductivity via hyperspectral image analysis. Since processing hyperspectral data cube requires huge resources and time, we employed python to process the hyperspectral image cube to analyse the exciton, vibronic and intrachain widths of P3HT films. By using HSI, we can get a localised analysis of the interchain width as HSI allows us to perform analysis of a pixel’s spectra. Therefore, in this experiment, we can process hyperspectral data and visualise it in the form of colour maps which is an important foundation for future machine-learning applications.