Issue 2, 2023

Diagnosis of doped conjugated polymer films using hyperspectral imaging

Abstract

Absorption spectra of doped conjugated polymer films provide valuable information on the degree of crystallinity, doping efficiency, material composition, and film thickness. The absorption spectral features commonly observed in doped polymers are due to intra-, inter-chain excitons, exciton–phonon coupling, polarons, and bipolarons that are branched differently in films prepared at different process parameters and doping conditions. Thus, the spectral features of thin films can be used to monitor and tune process parameters. However, probing spectral information at a point does not provide complete information on the solution-processed films where film characteristics are significantly influenced by uncontrolled process parameters. Hyperspectral imaging (HSI) is a high throughput spectral diagnostic method that provides the spatial distribution of spectral features where the process-induced variations of thin film quality and their influence on final performance metrics can be effectively analysed. In this report, we present a methodology for diagnosing thin film characteristics using the HSI technique by implementing automated spectral feature extraction and visualisation. For this study, we used the well-established F4TCNQ-doped regio regular poly-3-hexyl thiophene (P3HT) film as a model system and show film quality parameters, such as variation in film thickness, homogeneity of materials composition, degree of crystallinity and polaron concentration. We also present a generic process flow for the rapid screening of thin film and process optimization using the HSI technique.

Graphical abstract: Diagnosis of doped conjugated polymer films using hyperspectral imaging

Article information

Article type
Paper
Submitted
07 Oct 2022
Accepted
10 Feb 2023
First published
10 Feb 2023
This article is Open Access
Creative Commons BY-NC license

Digital Discovery, 2023,2, 471-480

Diagnosis of doped conjugated polymer films using hyperspectral imaging

V. Chellappan, A. Kumar, S. Ali khan, P. Kumar and K. Hippalgaonkar, Digital Discovery, 2023, 2, 471 DOI: 10.1039/D2DD00108J

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