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Dr. Paweł Piotr Michałowski

Dr. Paweł Piotr Michałowski

Head of Department of Structural Research and Materials Characterization, Łukasiewicz Research Network - Institute of Microelectronics and Photonics

3D SIMS ANALYSIS 3D SIMS for planar power electronics

From Dr. Paweł Piotr Michałowski

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Three dimensional secondary ion mass spectrometry can reveal precipitations and contamination agglomerations which may significantly deteriorate operation of planar power electronic devices.

Distribution of oxygen counts in gallium nitride, as registered.
Distribution of oxygen counts in gallium nitride, as registered.
(Source: Dr. Paweł Piotr Michałowski)

Secondary ion mass spectrometry (SIMS) is one of the most important techniques in semiconductor industry. Known for its excellent detection limits (usually in ppm-ppb regime) SIMS applications range from growth and processing optimization, quality assurance purposes to failure analysis. Recent transition from one dimensional depth profiles to three-dimensional imaging was a most welcomed innovation considering an ongoing paradigm change towards the 3D integration of nanoscale structures.

Figure 1: Standard SIMS depth profiles of aluminum doped silicon carbide samples.
Figure 1: Standard SIMS depth profiles of aluminum doped silicon carbide samples.
(Source: Dr. Paweł Piotr Michałowski)

However, power electronic devices are often based on a planar architecture and thus a simple question arises: is 3D SIMS really needed for such samples? Let’s find out!

Dopant precipitations

Let us consider a simple case of p-type silicon carbide doped with aluminum. A simple depth profile (Figure 1) shows a little difference between Sample A and B – the total dose of Al is about 8% higher for the latter. However, the electrical properties are by far superior for Sample A. SIMS contamination analysis do not show anything that may explain these discrepancies. 3D SIMS analysis presented on Figure 2, on the other hand, reveals the problem: the distribution of aluminum is very homogenous for Sample A whereas precipitations of metallic Al can be easily identified for Samples B.

Figure 2: 3D SIMS reveals homogenous distribution of Al in Sample A and formation of metallic precipitations in Sample B.
Figure 2: 3D SIMS reveals homogenous distribution of Al in Sample A and formation of metallic precipitations in Sample B.
(Source: Dr. Paweł Piotr Michałowski)

Such an analysis can be obtained within an hour and does not need any sophisticated sample preparation procedure – it can be used instead of transmission electron microscopy.

Contamination agglomeration

Unintentional n-type conductivity is a known problem for gallium nitride samples grown on sapphire. It is widely accepted that residual impurities, particularly oxygen, are responsible for this issue. The proposed solution is to look for and seal leaks and purify precursors. Despite these precautions the oxygen concentration often remains at the elevated level. Can 3D SIMS shed some light on this issue?

Figure 3: Distribution of oxygen counts in gallium nitride, as registered.
Figure 3: Distribution of oxygen counts in gallium nitride, as registered.
(Source: Dr. Paweł Piotr Michałowski)

At the beginning it may seem that it is not the case – as it can be clearly see on Figure 3 the oxygen distribution is very uniform. It should be, however, emphasized that oxygen is also present in SIMS analysis chamber as residual gases and vast majority (even more than 90%) of registered counts are parasitic and do not represent the oxygen distribution in the tested sample.

What will happen if we randomly remove 90% of voxels from Figure 3? This is shown on video and Figure 4. It becomes apparent that oxygen atoms are not distributed homogenously – they are agglomerated along pillar-shaped structures. Further analysis [1,2] reveals that these are cores of screw and mixed dislocations. It means that the resulting oxygen incorporation is not only related to a tightness of a reactor or a purity of precursors. It depends strongly a threading dislocation density.

Figure 4: Distribution of oxygen counts in gallium nitride, after removal of 90% randomly chosen voxels. Oxygen is agglomerated along pillar-shaped structures.
Figure 4: Distribution of oxygen counts in gallium nitride, after removal of 90% randomly chosen voxels. Oxygen is agglomerated along pillar-shaped structures.
(Source: Dr. Paweł Piotr Michałowski)

Conclusions

3D SIMS analysis has been used to characterize materials commonly used for power electronics – silicon carbide and gallium nitride. The presented samples cannot be even considered as a planar architecture devices, these are just basic materials. And yet 3D analysis shows its superiority over standard depth profiling mode. Is it reasonable to assume that full device structures do not have similar inhomogeneities? So what do you think? Is 3D SIMS really needed for planar power electronics?

References

[1] Michałowski, P. P., Zlotnik, S., Rudziński, M. Three dimensional localization of unintentional oxygen impurities in gallium nitride Chem. Commun., 55, 11539-11542, doi: 10.1039/C9CC04707G (2019)

[2] Michałowski, P. P., Zlotnik, S., Jóźwik, I., Chamryga, A., Rudziński, M. 3D Depth Profile Reconstruction of Segregated Impurities using Secondary Ion Mass Spectrometry. J. Vis. Exp. (158), e61065, doi:10.3791/61065 (2020).

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