Near-infrared hyperspectral imaging for monitoring the thickness distribution of thin poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) layers

Abstract

The thickness of thin layers of the conductive polymer PEDOT:PSS in the range between about 60 and 300 nm was determined by a near-infrared spectroscopic method using a hyperspectral camera. The reflection spectra of the layers do not contain bands, but consist of a moderate slope of the overall reflectance in the range between 1320 and 1850 nm. Despite the low thickness, the spectra show an extremely strong dependence on the thickness of the layers, which allows their use for quantitative measurements. The prediction of quantitative thickness data from the reflection spectra was based on a chemometric approach using the partial least squares (PLS) algorithm. Calibration was carried out by means of spin-coated layers of PEDOT:PSS, whose thickness was determined by white-light interferometry and stylus profilometry. Finally, this resulted in a calibration model with a root mean square error of prediction (RMSEP) of about 9 nm. After external validation of this model, it was used for quantitative imaging of the thickness distribution in PEDOT:PSS layers. The precision of the predicted values was confirmed by comparison with data from the reference methods. Moreover, it was shown that this approach can be also used for hyperspectral imaging of the thickness of thin printed layers and structures of this conductive polymer on polymer film or paper with excellent thickness resolution. This analytical approach opens new possibilities for in-line process control by large-scale monitoring of thickness and homogeneity of thin layers of conductive polymers.