Download InGaN QWs and SF (supporting information

Supporting information for:
Multi-microscopy study of the influence of stacking faults
and 3D In distribution on the optical properties of mplane InGaN quantum wells grown on microwire sidewalls
L. Mancini1, D. Hernandez-Maldonado1, W. Lefebvre1, J. Houard1, I.
Blum1, F. Vurpillot1, J. Eymery2, C. Durand2, M. Tchernycheva3, L.
Rigutti1
Groupe de Physique des Matériaux, UMR CNRS 6643, Normandie University, INSA et
Université de Rouen, St Etienne du Rouvray, France
2
CEA, CNRS, Université Grenoble Alpes, 38000 Grenoble, France
3
Institut d’Electronique Fondamentale, UMR CNRS 8622, University Paris Saclay, 91405
Orsay, France
1
Table of contents:
S-1.
Assessing structure and composition of quantum wells
(QWs) by correlated atom probe tomography (APT) and scanning
transmission electron microscopy (STEM)
a) Shape and size variations between QWs
b) Structural characterization by APT 1-dimensional profiles
c) Quantification of InN fraction fluctuations by 3-dimensional alloy maps
S-2.
Supplementary information on simulations
a) Determination of the position of stacking faults with respect to QWs
subvolumes used in simulations
S-1.
Assessing structure and composition of quantum wells
(QWs) by correlated atom probe tomography (APT) and scanning
transmission electron microscopy (STEM)
The correlative use of APT and STEM allows making the most of the capabilities of both
techniques: the size and shape of nanostructures can be assessed by STEM characterization.
Furthermore, STEM images can be used for finding the best parameters for the APT
reconstruction. The 3-dimensional nature of APT gives access to information which is not
accessible to STEM, along with the possibility of studying the composition of the system at
the nanoscale. Fig. 1 of main text shows the results of such a correlative approach. In the
following, we report the additional information which can be obtained from the APT
reconstructions and STEM images.
a) Shape and size variations between QWs
High angle annular dark field (HAADF) STEM images allows for the characterization of the
thickness of QWs and of the quality of their interfaces. Still, this characterization can be
affected by artifacts which can lead to a wrong estimation of the latter quantities. The
complementary information provided by the APT analysis can then be of help in correcting
the biases. This was the case for the STEM characterization of sample-A (Fig. S-1): QWs can
be identified as periodic lines of brighter contrast propagating almost perpendicularly with
respect to the tip axis. The three wells highlighted by the green dashed square in Fig. S-1 (a)
appear to be wider than the three on top (the red lines define the APT reconstruction field
of view). A measure of the thickness of the wells from this image would lead to a wrong
conclusion. In fact, the APT analysis shows that the wider area of bright contrast is due to a
projection effect which is in turn due to an ‘s-like’ shape of the considered wells, as can be
seen by looking at different angles (same angle from which the tip was observed by STEM
and after rotations of 90° and 10° around the vertical and horizontal axes respectively) of
the APT reconstruction of the positions of In atoms showed in Fig. S-1 (b). A better
estimation of the QWs thickness can be obtained considering 1-dimensional composition
profiles as we will show in the following.
Fig. S-1 (a) HAADF STEM image and (b) APT reconstruction of the position of In atoms of sample-A.
The APT reconstruction is first shown as if observed from the same angle at which the STEM image
was taken and then after rotations of 90° and 10° around the vertical and horizontal axes
respectively. The red lines define the APT field of view, while the green dashed square highlight the
three wells which appear to be wider in the STEM image.
b) Structural characterization by APT 1-dimensional profiles
1D concentration profiles were extracted from APT data considering subvolumes of
(15x15xL) nm where L is the reconstructed volume length. The profiles, expressed in terms
of the InN alloy fraction computed as the In/(In+Ga) atomic ratio, show triangular wells
characterized by a typical thickness of 5±1 nm. Fig. S-2 reports the results of the profiling for
a subvolume of (15x15x170) nm extracted from the sample-B reconstruction. On top, the
profile obtained for the whole length of the reconstructed volume is shown (distance = 0
corresponds to the top of the reconstruction). Close-up profiles of single QWs are reported
below.
Fig. S-2 1-dimensional In concentration profiles computed for a subvolume of (15x15x170) nm.
Distance = 0 correspond to the top of the reconstructed volume. On top, the whole profile is shown;
while below close-ups of single QWs can be seen.
Composition profiles computed considering different volumes within the same
reconstruction indicate that, while the QW thicknesses dispersion is quite small, strong
variations of composition characterize the wells at the scales probed by APT. Fig. S-3 shows
1D profiles computed from 4 subvolumes of (15x15x170) nm taken from different positions
of sample-B (the boxes considered are shown in red on the APT reconstructions). A
comparison between the profiles shows that the average In concentration of QWs from
volume-3 is around 30% higher than the one observed for volume-2 and -4, and almost 50%
higher than the one measured for volume-2.
Fig. S-3 1-D In composition profiles (left) computed for the four subvolumes represented along with
the APT reconstructions (right).
The previous observations suggest that the simple 1-dimensional approach is not sufficient
for a good estimation of the wells In content. The 3-dimensional information provided by
APT has to be taken into account in order to obtain an adequate knowledge of the QWs
structure.
Even considering local variations, in general sample-A reconstructed QWs show a lower
maximum In concentration content with respect to those of sample-B as shown in Fig. S-4. ,
Where 1D profiles showing the average highest concentration found for both sample-A and
-B are reported.
Fig. S-4 1-D In composition profiles of sample-A (top) and sample-B (bottom). The profiles showing
the highest average In concentration found for each sample are reported.
c) Quantification of InN fraction fluctuations by 3-dimensional alloy maps
1-D alloy fraction profiles average the local computed indium fraction impeding to have a
good indication of the maximum indium concentration which actually characterize the wells
when high concentration region have a small extension in space. A better insight into the
real In distribution can be obtained considering the APT 3-dimensional chemical mapping.
As reported in the main text, 3D In concentration maps were calculated computing the
atomic ratio In/(In+Ga) for each bin of a grid of (1x1x1) nm. The values of the latter map
were than interpolated using a sub-grid of (0.25x0.25x0.25) nm. These maps allow seeing
local In concentration which are considerably higher than the highest ones observed from
the 1D profiles (around 0.2) and from the 2D maps. Note that the 2-D maps reported in Fig.
1-(d,f) of main text are obtained averaging the concentration on the wole extension of each
well along the axis of the tip, thus there is still an averaging effect influencing the
measurement of the maximum In concentration. Fig. S-5 shows slices of the In
concentration map computed for the first QW from bottom of sample-B (corresponding to
QW6 in Fig. S-2 ) along the m-plane (a), within the triangular well, and the a-plane (b),
crossing the well in the position indicated by the orange dashed line. The 3-D analysis shows
alloy fluctuations with an extension of few nanometers for which the alloy concentration is
higher than 0.35 (Note that the small high concentration dot in the top-right of (a) is a
border artifact and does not have to be taken into account). The latter concentration was
the higher concentration we observed in the APT data obtained from sample-A and -B.
Fig. S-5 slices of the In fraction map obtained for the first QW from bottom of sample-B along the mplane (a) and the a-plane (b).
S-1.
Supplementary information on simulations
The transition energies of reconstructed QWs were simulated using the alloy fraction map
obtained by APT analysis and by adding within the considered sub-volume a cubic layer of 0.
5 nm (twice the resolution of the map). The composition of both cubic and wurtzite layers
was inferred by APT data. As stated in the main text, the exact positions of the stacking
faults with respect to the APT reconstructed wells were unknown for sample-B, the latter
having been analyzed only by µPL and APT. On the other hand, for sample-A it was possible
to deduce the position of SF using in a correlative fashion APT and STEM.
a) Determination of the position of stacking faults with respect to QWs
subvolumes used in simulations
The procedure used for establishing the relative positions of QWs and SFs is reported in Fig.
S-6. Sub volumes for the simulations were taken along the axis of the reconstruction. Their
positions with respect to the real sample were reconstructed considering the limited field of
view of the APT reconstruction. Finally, the position of SFs were simply inferred by the STEM
image and related to those of the sub-volumes used for the simulations.
Fig. S-6 STEM image of sample-A and reference features considered for reconstructing the relative
position of QWs and SFs.