Interpretation of temperature-programmed desorption data with multivariate curve resolution: Distinguishing sample and background desorption mathematically

Jing Zhao, Jia Ming Lin, Juan Carlos F. Rodríguez-Reyes, Andrew V. Teplyakov

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1 Scopus citations

Abstract

Efficient interpretation of thermal desorption data for complex surface processes is often complicated further by species desorbing from heating elements, support materials, and sample holder parts. Multivariate curve resolution (MCR) can be utilized as an unbiased method to assign specific temperature-dependent profiles for evolution of different species from the target surface itself as opposed to traces evolving from the surroundings. Analysis of thermal desorption data for iodoethane, where relatively low exposures are needed to form a complete monolayer on a clean Si(100)-2 × 1 surface in vacuum, provides convenient benchmarks for a comparison with the chemistry of chloroethane on the same surface. In the latter set of measurements, very high exposures are required to form the same type of species as for iodoethane, and the detection and analysis process is complicated by both the desorption from the apparatus and by the presence of impurities, which are essentially undetectable during experiments with iodoethane because of low exposures required to form a monolayer. Thus, MCR can be used to distinguish desorption from the sample and from the apparatus without the need to perform complicated and multiple additional desorption experiments.

Original languageEnglish
Article number061406
JournalJournal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Volume33
Issue number6
DOIs
StatePublished - 1 Nov 2015

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