Improvement of the Correlative AFM and ToF-SIMS Approach Using an Empirical Sputter Model for 3D Chemical Characterization

Abstract

Technological progress has spurred the development of increasingly sophisticated analytical devices. The full characterization of structures in terms of sample volume and composition is now highly complex. Here, a highly improved solution for 3D characterization of samples, based on an advanced method for 3D data correction, is proposed. Traditionally, secondary ion mass spectrometry (SIMS) provides the chemical distribution of sample surfaces. Combining successive sputtering with 2D surface projections enables a 3D volume rendering to be generated. However, surface topography can distort the volume rendering by necessitating the projection of a nonflat surface onto a planar image. Moreover, the sputtering is highly dependent on the probed material. Local variation of composition affects the sputter yield and the beam-induced roughness, which in turn alters the 3D render. To "circumvent these drawbacks, the correlation of atomic force microscopy (AFM) with SIMS has been proposed in previous studies as a solution for the 3D chemical characterization. To extend the applicability of this approach, we have developed a methodology using AFM time-of-flight (ToF)-SIMS combined with an empirical sputter model, "dynamic-model-based volume correction", to universally correct 3D structures. First, the simulation of 3D structures highlighted the great advantages of this new approach compared with classical methods. Then, we explored the applicability of this new correction to two types of samples, a patterned metallic multilayer and a diblock copolymer film presenting surface asperities. In both cases, the dynamic-model-based volume correction produced an accurate 3D reconstruction of the sample volume and composition. The combination of AFM SIMS with the dynamic-model-based volume correction improves the understanding of the surface characteristics. Beyond the useful 3D chemical information provided by dynamic-model-based volume correction, the approach permits us to enhance the correlation of chemical information from spectroscopic techniques with the physical properties obtained by AFM.