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Importance of Substrate Work Function Homogeneity for Reliable Ionization Energy Determination by Photoelectron Spectroscopy
Author(s) -
Schultz Thorsten,
Amsalem Patrick,
Kotadiya Naresh B.,
Lenz Thomas,
Blom Paul W. M.,
Koch Norbert
Publication year - 2019
Publication title -
physica status solidi (b)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.51
H-Index - 109
eISSN - 1521-3951
pISSN - 0370-1972
DOI - 10.1002/pssb.201800299
Subject(s) - work function , x ray photoelectron spectroscopy , ultraviolet photoelectron spectroscopy , materials science , ionization energy , homogeneity (statistics) , semiconductor , ionization , substrate (aquarium) , electronic structure , valence (chemistry) , photoemission spectroscopy , spectroscopy , work (physics) , optoelectronics , analytical chemistry (journal) , chemistry , nanotechnology , computer science , computational chemistry , physics , nuclear magnetic resonance , ion , oceanography , layer (electronics) , quantum mechanics , chromatography , machine learning , thermodynamics , organic chemistry , geology
Ultraviolet photoelectron spectroscopy (UPS) is the most widely used technique to determine the ionization energy (IE) of electronic materials, as this parameter is critically important for the energy level alignment in electronic and optoelectronic devices. For organic semiconductor IE assessment, molecules are typically evaporated and polymers spin‐coated onto a conductive substrate, and then measured by UPS. For substrates that possess a constant work function over large area, the determination of IE from the measured UPS data is straight forward. However, if the substrate is heterogeneous (intentionally or unintentionally) in local work function, the conventional method to determine IE yields erroneous results and a more careful data evaluation is necessary. While the secondary electron cutoff (SECO) can exhibit area‐averaged values, the valence levels are split in energy according to the local work function. Here, we demonstrate the possible pitfalls of heterogeneous substrates by employing well‐controlled model systems, and show how appropriate data analysis can still yield correct IE values.