X-ray photoelectron spectroscopy (XPS) is a highly sensitive surface technique that facilitates the understanding of the chemical environment present on material surfaces. Core level spectra obtained through XPS provide crucial information on chemical species, oxidation states, composition, and thickness in thin films. These spectra are typically divided into two components: the intrinsic signal and the background. The intrinsic signal consists of core photoelectrons unaffected by inelastic scattering as they traverse the solid, potentially including multiplets and satellites. Conversely, the background comprises the remaining portion of the signal. Accurate quantification of chemical composition relies on distinguishing the core photoelectron signal free from the photoelectrons that experienced inelastic scattering, necessitating the recognition and removal of the background.

The methodology for estimating the background has been extensively studied and is grounded in robust theoretical principles. This work presents the development of a user-friendly application designed to apply this theoretical framework and estimate the intrinsic signal contained within experimental photoelectron spectra. Specifically, we propose an iterative algorithm to extract the intrinsic signal from experimental data using background calculation techniques.

The user-friendly application is based on a Python program that efficiently estimates the intrinsic signal within experimental photoelectron spectra. Leveraging a robust iterative algorithm, our application facilitates the rapid determination of the extrinsic background, thereby enabling accurate quantification of chemical composition. With an intuitive user interface, our tool streamlines the analysis process, making it accessible to researchers across various fields. Our application stands as a competitive alternative to existing software solutions, offering both speed and accuracy in surface chemistry analysis.

Project in collaboration with the nanofilm processing and characterization laboratory of cinvestav queretaro, LPCN.

In the research group we develop the necessary software for our activities. Currently, we're working on a user-friendly app for modeling XPS spectra of polymers based on the physical parameters. This app has allowed us to better understand the influence of the parameters on the line shape used in the settings, as well as the background Tougaard and Shirley. 

The students José Jesús Ladinos Pantoja and Carlos Alberto Moreno San Martín from the UPJR-IPL are working on this project as part of their degree project