AVS 64th International Symposium & Exhibition
    Applied Surface Science Division Wednesday Sessions
       Session AS+2D+NS+SA-WeA

Invited Paper AS+2D+NS+SA-WeA3
Correlation of Morphological and Hyperspectral Characterization Techniques for Nanoelectronic and Energy Applications

Wednesday, November 1, 2017, 3:00 pm, Room 13

Session: 2D, 3D and nD Imaging of Surfaces, Buried Interfaces and Nanostructures
Presenter: Jean-Paul Barnes, Univ. Grenoble Alpes, CEA, LETI, France
Authors: J.-P. Barnes, Univ. Grenoble Alpes, CEA, LETI, France
A. Priebe, Univ. Grenoble Alpes, CEA, LETI, France
G. Goret, Univ. Grenoble Alpes, CEA, LETI, France
I. Mouton, Univ. Grenoble Alpes, CEA, LETI, France
A. Grenier, Univ. Grenoble Alpes, CEA, LETI, France
G. Audoit, Univ. Grenoble Alpes, CEA, LETI, France
P. Bleuet, Univ. Grenoble Alpes, CEA, LETI, France
Y. Mazel, Univ. Grenoble Alpes, CEA, LETI, France
E. Nolot, Univ. Grenoble Alpes, CEA, LETI, France
S. Legendre, Horiba France S.a.s., France
A.L. Tempez, Horiba France S.a.s., France
R. Estivill, STMicroelectronics, France
M. Juhel, STMicroelectronics, France
S. Duguay, Normandie Univ, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, France
F. Vurpillot, Normandie Univ, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, France
D. Blavette, Normandie Univ, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, France
Correspondent: Click to Email

The integration of a growing variety of materials in increasingly complex structures drives the need to correlate characterization techniques. In this presentation we will discuss the advantages of correlating pairs of techniques such as focused ion beam-time of flight-secondary ion mass spectrometry (FIB-TOF-SIMS) and X-ray computed nanotomography (CNT); atom probe tomography (APT) and electron tomography (ET); and TOF-SIMS depth profiling and plasma profiling time-of-flight mass spectrometry (PPTOFMS).

FIB-TOF-SIMS tomography extends the capacity of TOF-SIMS instruments to analyze large heterogeneous samples of several tens of microns in size as well as porous samples or those with strong surface topography. Standard depth profiling is often not possible as the depth scale information is rapidly lost in such samples. Examples include copper pillars used in 3-D integration in nanoelectronics and solid oxide fuel cells (SOFCs) which have a complex porous multilayer (sandwich) structure. Whilst FIB-TOF-SIMS provides unique information on the sample chemical composition, there may be morphological artefacts such as curtaining. These may be identified and corrected by analyzing the sample beforehand by X-ray CNT in an SEM. We have developed a method to analyze the same object by both techniques by using novel sample preparation protocols [1].

The correlation of morphological with hyperspectral data can also be applied to APT and ET. APT is increasingly used for the analysis of semiconductor devices because of its unique ability to measure composition in 3D at the atomic scale with high sensitivity. However the APT data sets are often distorted and care must be taken in quantifying composition. The morphological information obtained from analyzing the APT tip beforehand by ET can be used to optimize the parameters when reconstructing the APT data.

PPTOFMS is a rapid depth profiling technique that uses a plasma to etch away the sample and analyze the composition as a function of depth. Unlike SIMS based techniques, the ionization takes place in the plasma and the ratio of ions extracted from the plasma is directly representative (within a factor of 2-3) of the sputtered sample composition. However, the sensitivity and depth resolution are worse than for TOF-SIMS. Combining PPTOFMS with TOF-SIMS depth profiling enables the standard-free quantification and rapid sample screening capabilities of the PPTOFMS to be combined with the sensitivity and high depth and lateral resolution of TOF-SIMS [3].

[1] A. Priebe et al. Ultramicroscopy. 173 (2017):10-13.[2] A. Grenier et al APL 106, 213102 (2015). [3] A. Tempez et al., J. Vac. Sci. Technol. B (2016) 34