Use of Fourier Transform-Infrared Spectroscopy in HgCdTe Thin Film Characterization and Greenhouse Gas Detection in Hyperspectral Data

This paper explores the application of Fourier Transform (FT) and Fourier Transform-Infrared Spectroscopy (FTIR) in two domains: the characterization of Mercury-Cadmium Telluride (HgCdTe) thin films for infrared imaging and the detection of greenhouse gases in hyperspectral data. FTIR is a popular method for characterization of many thin film materials, including HgCdTe, a material used for the most sensitive of IR detectors. Using novel advanced spectroscopy techniques and noise reduction methods, we employ FTIR in identifying composition and thickness uniformity in HgCdTe thin films grown via Molecular-Beam Epitaxy (MBE). As Hyperspectral IR data is invaluable in detecting greenhouse gas emissions, our utilization of both Principal Component Analysis (PCA) and noise reduction algorithms (e.g. contrast limited adaptive histogram equalization (CLAHE)) can enhance the accuracy of gas detection in hyperspectral data. Our work Closes the loop between material characterization and environmental monitoring through the combination of FTIR with data analysis techniques. Our approach not only validates FTIR's efficacy in semiconductor characterization but also advances its utility in detecting greenhouse gases, offering a robust methodology for both material and environmental applications.