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Over the past three decades, the widespread utility and applicability of X-ray photoelectron spectroscopy (XPS) in research and applications has made it the most popular and widely used method of surface analysis. Associated with this increased use has been an increase in the number of new or inexperienced users which has led to erroneous uses and misapplications of the method. This article is the first in a series of guides assembled by a committee of experienced XPS practitioners that are intended to assist inexperienced users by providing information about good practices in the use of XPS. This first guide outlines steps appropriate for determining whether XPS is capable of obtaining the desired information, identifies issues relevant to planning, conducting and reporting an XPS measurement, and identifies sources of practical information for conducting XPS measurements. Many of the topics and questions addressed in this article also apply to other surface-analysis techniques.

a †ToF-SIMS spectra are formed by bombarding a surface with a pulse of primary ions and detecting the resultant ionized surface species using a time-of-flight mass spectrometer. Typically, the detector is a time-to-digital converter. Once an ion is detected using such detectors, the detector becomes insensitive to the arrival of additional ions for a period termed as the (detector) dead-time. Under commonly used ToF-SIMS data acquisition conditions, the time interval over which ions arising from a single chemical species reach the detector is on the order of the detector dead-time. Thus, only the first ion reaching the detector at any given mass is counted. The event registered by the data acquisition system, then, is the arrival of one or more ions at the detector. This behavior causes ToF-SIMS data to violate, in the general case, the assumption of linear additivity that underlies many multivariate statistical analysis techniques. In this article, we show that high-mass-resolution ToF-SIMS spectral-image data follow a generalized linear model, and we propose a data transformation and scaling procedure that enables such data sets to be successfully analyzed using standard methods of multivariate image analysis.

Although polydimethylsiloxane (PDMS) transfer during microcontact printing (microCP) has been observed in previous reports, which generally focused on only one or a few different substrates, in this work we investigate the extent of PDMS transfer onto a series of surfaces with a wide range of hydrophobicities using an uninked, unpatterned PDMS stamp. These surfaces include clean silicon, clean titanium, clean gold, "dirty" silicon, polystyrene, Teflon, surfaces modified with PEG, amino, dodecyl, and hexadecyl monolayers, and also two loose molecular materials. The PDMS transferred onto planar surfaces is, in general, easily detected by wetting and spectroscopic ellipsometry. More importantly, it is detected by time-of-flight secondary ion mass spectrometry (ToF-SIMS) because of the sensitivity of this technique to PDMS. The effect of surface free energy on PDMS transfer in microcontact printing is investigated, and the relationship between the amount of PDMS in ToF-SIMS spectra and the surface tensions of initial surfaces is revealed. We show that PDMS transfer can be applied as a probe of surface free energies using ToF-SIMS, where PDMS preferentially transfers onto more hydrophilic surface features during stamping, with little being transferred onto very hydrophobic surface features. Multivariate curve resolution (MCR) analysis of the ToF-SIMS image data further confirms and clarifies these results. Our data lend themselves to the hypothesis that it is the free energy of the surface that plays a major role in determining the degree of PDMS transfer during microCP.