Project in collaboration with TNM-Celaya
Our research group develops custom software to support our activities. Currently, we are working on a user-friendly application for modeling XPS spectra of polymers based on physical parameters. This tool has enhanced our understanding of how these parameters influence the line shape, as well as the Tougaard and Shirley background corrections.
As part of their degree project, students José Jesús Ladinos Pantoja and Carlos Alberto Moreno San Martín from UPJR-IPL are actively contributing to this development
Proyecto desarrollado en UPJR
Proyecto desarrollado en UPJR en colaboración con el TNM-Celaya
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.
Proyecto realizado en la Universidad Politécnica de Juventino Rosas con el apoyo de IDEA-GTO con el convenio SICES/CONV/141/2020
Responsable Técnico : Jorge Alejandro Torres Ochoa
Colaboradores
Víctor Alfonso Morales Nieto, Miguel Moreno Reyes, Juan Ignacio Ruiz Guerrero