Optimization of secondary ion mass spectrometry for quantitative trace analysis

Abstract

The potential of dynamic secondary ion mass spectrometry (SIMS) for quantitative trace analysis is evaluated from the basic equations of signal formation and instrumental detection. The key factors are sputtering yield and ionization probability. The aim of optimization of measurement technique for problem solving is to gain maximum relevant quantitative information. In qualitative analysis elemental ions have to be identified and interfering molecular ions are separated by differences in kinetic energy distribution (energy discrimination) or mass (high mass resolution). Due to the complex signal formation process, quantification of intensities is performed by relative sensitivity factors obtained by calibration samples. Practically no certified reference materials are available. Calibration samples can be produced by chemical doping of substances, but routinely ion implantation is applied. Transfer of sensitivity factors between different laboratories respectively utilization of compiled values from the literature leads only to semiquantitative results. The prerequisite for accurate quantitative analysis are low random errors and reduction, preferably elimination of systematic errors. In an empirical problem oriented approach, variation of measurement parameters, use of different calibration methods and analytical techniques are combined to achieve optimum or maximum accuracy or information. For homogeneous samples a reproducibility of typically ± 2%rel. and an accuracy of ± 5%rel. can be obtained. Matrix and charging effects can severely limit SIMS analysis. Our experiences to control these effects are discussed. The course of the surface charge during depth profiling of a layer system can yield additional information on the quality of insulating layers. Examples for elimination of the matrix effect by flooding the surface with oxygen and by utilizing the energy distribution of the secondary ions are presented. Some references are given for the combination of SIMS depth profiling with imaging methods like electron probe micro analysis (EMPA), scanning tunneling microscopy (STM), atomic force microscopy (AFM), and transmission electron microscopy (TEM) to gain additional information.