Stefano Toso1,2, Dmitry Baranov1, Cinzia Giannini3, Liberato Manna1. 1. Nanochemistry Department, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy. 2. International Doctoral Program in Science, Università Cattolica del Sacro Cuore, 25121 Brescia, Italy. 3. Istituto di Cristallografia - Consiglio Nazionale delle Ricerche (IC-CNR), Via Amendola 122/O, I-70126 Bari, Italy.
Abstract
The research on two-dimensional colloidal semiconductors has received a boost from the emergence of ultrathin lead halide perovskite nanoplatelets. While the optical properties of these materials have been widely investigated, their accurate structural and compositional characterization is still challenging. Here, we exploited the natural tendency of the platelets to stack into highly ordered films, which can be treated as single crystals made of alternating layers of organic ligands and inorganic nanoplatelets, to investigate their structure by multilayer diffraction. Using X-ray diffraction alone, this method allowed us to reveal the structure of ∼12 Å thick Cs-Pb-Br perovskite and ∼25 Å thick Cs-Pb-I-Cl Ruddlesden-Popper nanoplatelets by precisely measuring their thickness, stoichiometry, surface passivation type and coverage, as well as deviations from the crystal structures of the corresponding bulk materials. It is noteworthy that a single, readily available experimental technique, coupled with proper modeling, provides access to such detailed structural and compositional information.
The research on two-dimensional colloidal semiconductors has received a boost from the emergence of ultrathin lead halide perovskite nanoplatelets. While the optical properties of these materials have been widely investigated, their accurate structural and compositional characterization is still challenging. Here, we exploited the natural tendency of the platelets to stack into highly ordered films, which can be treated as single crystals made of alternating layers of organic ligands and inorganic nanoplatelets, to investigate their structure by multilayer diffraction. Using X-ray diffraction alone, this method allowed us to reveal the structure of ∼12 Å thick Cs-Pb-Br perovskite and ∼25 Å thick Cs-Pb-I-Cl Ruddlesden-Popper nanoplatelets by precisely measuring their thickness, stoichiometry, surface passivation type and coverage, as well as deviations from the crystal structures of the corresponding bulk materials. It is noteworthy that a single, readily available experimental technique, coupled with proper modeling, provides access to such detailed structural and compositional information.
Colloidal semiconductor nanoplatelets
are materials characterized by large exciton binding energy and oscillator
strength, sharp spectral features,[1−4] and short photoluminescence lifetimes,[2] all properties that make them appealing in devices
such as light-emitting diodes and lasers.[2,5−7] The extreme thinness, down to just a few atoms, is
both the source of their unique optical properties and a major challenge
for their structural characterization. Several studies have demonstrated
that nanoplatelets can be much different from an ideal “slice”
of the corresponding bulk material: they are structurally less constrained
than the bulk and can readily relax through structural distortions
and altered lattice constants.[8] Two examples
are the rock-salt cubic PbS, which becomes orthorhombic when shaped
into thin platelets,[9] and the CdSe zincblende
nanoplatelets, which are better described by a tetragonal structure
rather than the cubic structure of the bulk.[10] Furthermore, due to their high surface-to-volume ratio, the surface
layers become a relevant fraction of the whole nanoplatelet, to the
point that the type of surface termination affects the overall stoichiometry
of the platelets and their physical properties.[2,11]The emergence of colloidal lead halide perovskites considerably
expanded interest in nanoplatelets in the past five years. Lead halide
perovskite nanoplatelets can be synthesized with excellent control
over their thickness from six down to one single [PbX6]4– octahedron, providing access to a level of quantum
confinement that would be challenging to achieve in isotropic nanocrystals.[1,2,8,12] However,
significantly less is known about these particles with respect to
their cuboidal nanocrystal counterparts. Because of the intrinsic
structural softness of halide perovskites and the symmetry breaking
due to their finite thickness,[13−16] such platelets may undergo a structural reorganization
if compared to the bulk, which is challenging to capture in its fine
details. Moreover, the extreme thinness of platelets makes their surface
a considerable fraction of their entire volume, therefore requiring
a careful investigation of their termination layers. Finally, films
of lead halide perovskite nanoplatelets are actively explored for
use in light-emitting devices. In such films, the platelet orientation,
the interplatelet distance, and the stacking disorder affect the electronic
coupling between nanoplatelets, their dielectric screening, and the
orientation of their transition dipole moments. Therefore, such parameters
can be relevant for tuning the optical characteristics of the device.[17−19]To retrieve all this information, a combination of several
techniques
is typically required. For example, high-resolution transmission electron
microscopy (HRTEM) is commonly used to investigate the structure of
nanoplatelets.[20] These, however, often
lie flat with respect to the electron beam, and TEM is blind to their
more elusive thin dimension unless in perfectly vertical stacks, a
condition that is rarely met for thin and laterally extended platelets.[21] Furthermore, curling and bending can prevent
atomic resolution in ultrathin nanoplatelets, and the electron beam
can cause severe damage.[8,10,22] X-ray powder diffraction is a less invasive and more versatile and
sensitive technique than TEM, but diffraction signals from nanoplatelets
are smeared due to their limited periodicity along the thin direction.
Thus, Bragg diffraction and its derived methods such as Rietveld refinement
are poorly suited to characterize nanoplatelets, which are better
studied with Total Scattering methods.[8,10] However, these
methods rely on high-quality data, usually from synchrotrons,[23] and require an a priori 3D
atomistic model of the entire nanoparticle to start with. Moreover,
Total Scattering methods are usually applied on samples composed of
randomly oriented crystallites: their extension to films of oriented
nanoparticles requires the introduction of corrections for the preferred
orientation, which would add further complexity to the method.In this work, we investigate the structure of colloidal cesium
lead halide nanoplatelets along their thinnest dimension through the
application of Multilayer Diffraction to highly ordered nanoplatelet
films. This technique has first emerged as a powerful and nondestructive
analytical method following advances in the preparation of atomically
precise multilayer structures.[24,25] It is nowadays well-established
for materials grown by physical methods,[24,26−32] to the point that several user-written programs have been developed
to apply the theory of Multilayer Diffraction to a variety of materials,
such as metals, oxides, or organic multilayers.[28,33−36] Our groups recently expanded the domain of application of Multilayer
Diffraction to superlattices of colloidal semiconductor nanocrystals.[37,38] Briefly, these materials can be considered as multilayers where
high-density inorganic domains (i.e., the nanocrystals)
alternate with low-density organic layers (i.e.,
the ligands), whose scattering power can be neglected or approximated.
Consequently, their diffractograms can be simulated by first computing
the diffraction profile of the individual nanoparticles and then including
the effects of the multilayer interference phenomena arising from
the precise particle stacking. This allows us to extract the sample
structural parameters by performing a least-squares refinement of
the experimental diffractogram. In the present work, we further developed
this approach by introducing a fully atomistic description of the
nanoplatelet structure, in contrast to the previous approximation
of the nanocrystal as a stacking of scattering planes with no chemical
identity.[38] This enabled us to refine the
atomic structure of the constituent nanoplatelets, greatly increasing
the potential of the method.The single- and mixed-halide Cs–Pb–X
(X = Br or I–Cl)
nanoplatelets analyzed in this work were prepared by colloidal synthesis
and self-assembled into thin films by slow solvent evaporation. Such
a self-assembly process was exploited to create an extended periodicity
along the thin direction of the nanoplatelets, producing a peculiar
pattern of periodic peaks when the film is subject to a θ:2θ
diffraction experiment. By applying the knowledge derived from our
previous work on lead halide nanocrystal superlattices,[37,38] we developed an algorithm that enables the refinement of the nanoplatelets
structure by means of a full-profile multiparametric fitting of their
diffractogram. Despite relying only on a widely available lab-grade
diffractometer, the amount of structural and compositional information
that can be retrieved is noteworthy. When the method was applied to
Cs–Pb–Br nanoplatelets, it demonstrated that they were
two-monolayer (i.e., two [PbBr6]4– octahedra) thick, stacked at about ∼34 Å from each other
with a standard deviation of only ∼0.5 Å. Furthermore,
the method enabled us to discern the surface termination of the platelets,
which consisted of a partially defective plane of Br– ions and R-NH3+ ligands, and to demonstrate
that oleic acid, although present during the synthesis, played no
role in their surface passivation. We also measured the anisotropic
structural expansion of nanoplatelets with respect to bulk CsPbBr3, confirming a behavior reported for cesium lead halide nanostructures
in the past.[8,38,39]While a relatively simple structure and a well-documented
relationship
between thickness and optical properties ease the identification of
the number of lead halide octahedra layers in the case of Cs–Pb–Br
nanoplatelets, the presented method enables the investigation of more
elusive materials as well. Here, we report the example of Cs2PbI2Cl2 Ruddlesden–Popper nanoplatelets,
for which the number of layers cannot be determined from optical spectra.
Nonetheless, for this system the Multilayer Diffraction approach enabled
us to accurately measure a thickness of three [PbI2Cl4]4– octahedra, capture the anisotropic expansion
of the structure along its thin dimension, and determine the nature
of the surface termination layer, which was found to be composed of
I– and R-NH3+ ions. Contrary
to our initial expectations, we also found that the Cs+ and I– ions form a common atomic plane in the
nanoplatelets, as opposed to being located in separate planes as in
bulk Cs2PbI2Cl2, providing yet another
example of structural differences between a nanoparticle and the corresponding
bulk material.
Results and Discussion
Sample Preparation, Data
Processing, and Model Outline
In this work, we prepared Cs–Pb–Br
nanoplatelets with
a lateral dimension of a few dozens of nanometers (Figure a) via a previously
published procedure.[40] The films of oriented
nanoplatelets for the Multilayer Diffraction analysis were prepared
by slowly drying a suspension of nanoplatelets in hexane on top of
a tilted silicon wafer. Upon the successful film deposition, a region
of the substrate became covered by a smooth and iridescent film and
was selected for the diffraction experiment. As a matter of fact,
a brilliant and homogeneous color over mm2 areas, originated
by thin-film light interference, attests to the expected constant
thickness and limited roughness of the film (Figure b).[41] The samples
were probed in θ:2θ out-of-plane diffraction experiments,
producing signals in the form of equally spaced fringes whose intensity
and sharpness decreased at higher angles. Such diffraction fringes
appear when the structural perfection of the multilayer reaches the
angstrom level,[38] far beyond what can be
probed optically, and encode the structure of the film along its vertical
direction. This includes the overall periodicity of the multilayer
and its stacking disorder, as well as the vertical coordinates and
the electron densities of all the atomic planes in the sample.
Figure 1
Experimental
and simulated multilayer diffraction patterns. The
slow solvent evaporation drives the self-assembly of (a) colloidal
nanoplatelets of uniform thickness into (b) highly oriented iridescent
thin films on top of a silicon wafer (1 cm × 1 cm). In such films,
the electron-dense platelets and the comparatively electron-light
ligands alternate along the vertical direction. These are multilayered
systems that modulate the intensity of the diffracted X-rays yielding
patterns into characteristic periodic sharp fringes. Such experimental
patterns (c, black solid line “Raw Data”) can be conveniently
exploited to refine the structure of the nanoplatelets by comparing
them with a simulation once the Lorentz Polarization Absorption correction
has been applied (c, red solid line “LPA-corrected data”).
Indeed, the ordered stacking into a multilayer allows the reduction
of the 3D structure of randomly oriented nanoplatelets (d) to a 1D
representation of the film along its z-axis (e).
Such representation is used to compute the nanoplatelet structure
factor FNPL(q) through eq and then to convolute
its square modulus |FNPL(q)|2 (f, black dashed line) with the fringes arising from
the nanometer-scale periodicity of the multilayer (f, vertical blue
lines). This produces a simulation of the whole multilayer diffractogram
(f, red solid line) that can be matched with the experimental data
to refine the input 1D representation of the nanoplatelet structure.
Experimental
and simulated multilayer diffraction patterns. The
slow solvent evaporation drives the self-assembly of (a) colloidal
nanoplatelets of uniform thickness into (b) highly oriented iridescent
thin films on top of a silicon wafer (1 cm × 1 cm). In such films,
the electron-dense platelets and the comparatively electron-light
ligands alternate along the vertical direction. These are multilayered
systems that modulate the intensity of the diffracted X-rays yielding
patterns into characteristic periodic sharp fringes. Such experimental
patterns (c, black solid line “Raw Data”) can be conveniently
exploited to refine the structure of the nanoplatelets by comparing
them with a simulation once the Lorentz Polarization Absorption correction
has been applied (c, red solid line “LPA-corrected data”).
Indeed, the ordered stacking into a multilayer allows the reduction
of the 3D structure of randomly oriented nanoplatelets (d) to a 1D
representation of the film along its z-axis (e).
Such representation is used to compute the nanoplatelet structure
factor FNPL(q) through eq and then to convolute
its square modulus |FNPL(q)|2 (f, black dashed line) with the fringes arising from
the nanometer-scale periodicity of the multilayer (f, vertical blue
lines). This produces a simulation of the whole multilayer diffractogram
(f, red solid line) that can be matched with the experimental data
to refine the input 1D representation of the nanoplatelet structure.To extract this information, we refined a starting
model of the
multilayer by minimizing the differences between the experimental
data and a simulated diffractogram, similarly to what is done in a
Rietveld refinement. First, the data must be prepared for the analysis
by subtracting the instrumental background and any residual reflection
from misaligned nanoplatelets or from the substrate. In addition,
the Lorentz Polarization Absorption correction must be applied to
compensate for the instrumental contributions to the measured intensity
(LPA, Figure c).[28] This step is needed to make the experimental
pattern comparable with the simulation. Indeed, the so-processed data
are an experimental measurement of |FML(q)|2, that is the square modulus of
the multilayer structure factor FML(q) describing the amplitude and phase of X-rays diffracted
by the multilayer. Our analysis relies on the fact that FML(q) can be simulated starting from
a structural representation of the multilayer.To achieve such
a description, the multilayer can be broken down
into two parts: the high-density inorganic nanoplatelets and the low-density
interparticle spacings composed of organic ligands. Due to their low
density, the interparticle spacings minimally contribute to the signal
intensities across the experimentally studied q-range, and for the
purpose of the analysis they can be approximated as amorphous carbon
layers with fixed density. The most important part of the multilayer
are the nanoplatelets, whose structure factor FNPL(q) is the main component of FML(q). In this work, we describe FNPL(q) in its most essential
form, that is, the sum in phase of the radiation scattered by each
individual atom j(42)where f is the element-specific
atomic form factor, q⃗ is the scattering vector,
and R⃗ = x̂·x + ŷ·y + ẑ·z is the position
vector of the jth atom inside the nanoplatelet. Computing
the structure factor in this way would be demanding for platelets
containing dozens of thousands of atoms; however, developing eq one step further immediately
highlights the huge advantage of dealing with ordered multilayers
instead of randomly oriented nanoplatelets. During a θ:2θ
out-of-plane diffraction experiment, the scattering vector q⃗ is perpendicular to the sample surface plane xy; therefore, q⃗·R⃗ = q·z:As small as it might seem, this change has
a major impact on the data treatment. Instead of considering a complex
3D model (Figure d),
we can describe the structure entirely by the handful of atoms needed
to capture the composition of each atomic plane along the z direction. For example, two [PbBr6]4– octahedra thick Cs–Pb–Br nanoplatelets are described
by just 10 atoms divided in five layers: Br–PbBr2–CsBr–PbBr2–Br (Figure e). Based on this representation,
our algorithm computes FNPL(q) and then exploits it to calculate FML(q) by introducing the effects of the multilayer
periodicity and stacking disorder. Finally, FML(q) is turned into |FML(q)|2, producing a simulation
that can be matched with the experimental data (Figure f). Additional details on the sample preparation,
the data analysis, and the diffractogram simulation can be found in
the Methods and in the Supporting Information (SI), sections S1–S3.
Structural
Refinement of Cs–Pb–Br Nanoplatelets
The model
we outlined allows us to refine the structure of Cs–Pb–Br
nanoplatelets via the optimization of a consistent
starting model, which is a 1D representation of the nanoplatelets
where the number of atomic planes, their stacking sequence, and the
elements they contain is imposed a priori. For quantum-confined
platelets, the thickness can be estimated through the absorption spectrum:
in our case, it matched with reports for ∼12 Å thick nanoplatelets
(excitonic absorption peak at 428 nm, Figure a).[12,40,43] Taking the CsPbBr3 crystal structure as a reference,
where the Pb–Br bonds are about ∼3 Å long, the
nanoplatelets must be composed of five alternating CsBr and PbBr2 layers. To complete the nanoplatelet model, we had to provide
a description for the surface as well. Indeed, as a consequence of
the extreme thinness the surface layers are a significant fraction
of the entire nanoplatelet, as they constitute two out of five atomic
layers along the thin direction. Such a high contribution is expected
to leave a clear mark on the diffraction pattern, therefore giving
insight into the nature of the surface passivation layer. To elucidate
this aspect, we considered three surface models that have been previously
proposed for CsPbBr3 nanocrystals: PbBr2-termination,
CsBr-termination, and Br–/R-NH3+ termination (Figure b–d, insets).[44−49] A preliminary comparison between calculated and experimental patterns,
performed by refining only a few selected parameters (Pb–Pb
distance, interparticle spacing, stacking disorder), easily discarded
the PbBr2- and CsBr-terminations (Figure b,c), while the Br–/R-NH3+ termination produced a good match with the experimental
data (SI, section S4).
Figure 2
Structural refinement
of Cs–Pb–Br nanoplatelets.
(a) Absorption (ABS) and photoluminescence (PL) spectra of two [PbBr6]4– octahedra thick Cs–Pb–Br
nanoplatelets. Inset: a photograph of a colloidal suspension of nanoplatelets
under ambient illumination (left) and UV light (right), the latter
showing the characteristic bright blue emission. Preliminary simulations
testing the hypotheses of (b) a PbBr2 surface termination
and (c) a CsBr surface termination. A visual examination reveals that
these surface terminations do not capture accurately the intensity
of the peaks in the experimental patterns. (d) Best-fit of the diffraction
pattern obtained by refining the structural parameters of the Br–/R-NH3+ termination model, including
the occupancies, and the vertical coordinates of atoms in the platelet
structure. The residual signal at q ∼ 15 Å–1 is not a multilayer fringe, but a peak from a fraction
of misaligned platelets ({110} in the pseudocubic notation for CsPbBr3). The inset illustrates the nanoplatelet structure in scale,
highlighting its expansion along the vertical direction, the partially
occupied surface layers and the tilted [PbBr6]4– octahedra. Color legend for atoms: Cs+ = light-blue;
Br– = brown; Pb2+ = dark gray (octahedra); N = violet; C = black; H = white.
Structural refinement
of Cs–Pb–Br nanoplatelets.
(a) Absorption (ABS) and photoluminescence (PL) spectra of two [PbBr6]4– octahedra thick Cs–Pb–Br
nanoplatelets. Inset: a photograph of a colloidal suspension of nanoplatelets
under ambient illumination (left) and UV light (right), the latter
showing the characteristic bright blue emission. Preliminary simulations
testing the hypotheses of (b) a PbBr2 surface termination
and (c) a CsBr surface termination. A visual examination reveals that
these surface terminations do not capture accurately the intensity
of the peaks in the experimental patterns. (d) Best-fit of the diffraction
pattern obtained by refining the structural parameters of the Br–/R-NH3+ termination model, including
the occupancies, and the vertical coordinates of atoms in the platelet
structure. The residual signal at q ∼ 15 Å–1 is not a multilayer fringe, but a peak from a fraction
of misaligned platelets ({110} in the pseudocubic notation for CsPbBr3). The inset illustrates the nanoplatelet structure in scale,
highlighting its expansion along the vertical direction, the partially
occupied surface layers and the tilted [PbBr6]4– octahedra. Color legend for atoms: Cs+ = light-blue;
Br– = brown; Pb2+ = dark gray (octahedra); N = violet; C = black; H = white.The match between the measured and calculated diffractograms could
be further improved by refining the fractional occupancies of the
atoms in each plane, which is described in the model by multiplying
each atomic form factor f in eq by a number
in between 0 (zero occupancy) and 1 (full occupancy). The resulting
picture of the nanoplatelets structure is hereby presented (Figure d, see the SI, section S5, for further details on the analysis).
The Cs–Pb–Br nanoplatelets were confirmed to be composed
of two [PbBr6]4– octahedra layers, for
an overall thickness of 11.85 ± 0.01 Å, and were separated
by a layer of organic ligands 34.00 ± 0.01 Å thick with
a stacking disorder parameter of 0.51 ± 0.01 Å (i.e., the standard deviation of the interparticle distance).
This corresponds to an overall multilayer periodicity of 45.89 ±
0.01 Å. The most electron-dense atomic layers, namely the PbBr2 ones, were assumed to be fully occupied to serve as a reference
for refining the relative occupancies of all the other layers. With
respect to this reference, the CsBr layer in the middle of the platelet
was found to be slightly to nondefective (occupancy = 95 ± 1%),
while the surface Br–/R-NH3+ layer was significantly defective (occupancy = 73 ± 2%). The
nanoplatelet structure was found to be expanded along the thin direction:
the Pb–Pb distance is 5.924 ± 0.004 Å, longer than
that measured for the horizontal direction by 1.56% (5.833 Å,
from the residual signal of nonstacked platelets, see the SI, section, S2). Furthermore, both Pb–Pb
distances are longer than those found in bulk CsPbBr3 (vertical
= +0.75% [010] bulk, horizontal = +0.22% ⟨101⟩ bulk, Pnma setting, ICSD-97851).[50] This
finding is in line with the known tendency of lead halides to relax
their structure anisotropically at the nanoscale[8,38] and
provides insight about the lattice symmetry.Lead halide perovskites
can adopt a cubic, tetragonal, or orthorhombic
structure depending on whether and how the [PbX6]4– octahedra are tilted.[51,52] While the debate on
bulk and large nanocrystals of CsPbBr3 points in favor
of the orthorhombic polymorph under normal temperature and pressure,
this aspect is still not entirely clarified for small nanocrystals
and thin platelets.[53−57] The different Pb–Pb distances along the horizontal and vertical
directions easily exclude the cubic symmetry: we tried to discern
between the two options left based on the atoms in the PbBr2 planes being coplanar (tetragonal) or misaligned (orthorhombic)
due to the tilting of octahedra (see SI, Section S5, for details). To do so, we allowed the z-coordinate of the Br– ions in the PbBr2 planes to relax, finding that |zPb–zBr| = 0.241 ± 0.054 Å. This is compatible
within error with the |zPb–zBr| = 0.294 Å found in bulk CsPbBr3,[50] suggesting that the two-monolayer
Cs–Pb–Br nanoplatelets adopt an orthorhombic structure,
in line with a previous report on six-octahedra-thick nanoplatelets.[8] See the SI, Section S5, for further details on the analysis of Cs–Pb–Br nanoplatelets.
On the Surface Passivation of Cs–Pb–Br Nanoplatelets
X-ray diffraction is not often exploited to study the surface of
nanocrystals due to the predominant contribution of the volume to
the overall diffracted intensity.[58] However,
assembling the platelets into a multilayer effectively turned their
surface into a periodic component of a larger crystal, therefore enabling
its investigation. The diffraction methods are sensitive to the electron
density of the sample, which depends on its chemical composition.
Thus, the nanoplatelet surface experimentally appears as a layer of
atoms with a lower electron density than the core, to which we must
give an interpretation in terms of chemical composition. This is done
by assuming a starting model passivated by a layer of Br– and R-NH3+ ions, in line with prior findings
and with our preliminary simulation (Figure S7a), and then refining the occupancy of surface ions by matching the
electron density of the model with the one measured experimentally.
For example, the 73% occupation found for the Br–/R-NH3+ surface layers indicates that they
have an electron count of ∼31.4 e–/formula
unit (= 0.73·[e–Br + e–N]) if compared to the PbBr2 layers we took
as a reference (152 e–/formula unit). The raw data
is the electron count, while the vacant layer of Br–/R-NH3+ ions is the way our model accounts
for it. In principle, many other surface terminations are compatible
with the same electron count and would be indistinguishable by relying
only on the diffraction data from our experiments. Therefore, we had
to validate this interpretation by independent methods.The
first hint toward a Br–/R-NH3+ termination is provided by the comparison with 2D-layered perovskites.
Those are bulk materials where layers of A+ cations of
the perovskite (i.e., Cs+ for CsPbBr3) are replaced with a long-chain ammonium cation, that has
the effect of dissecting the perovskite structure into inorganic slices
separated by the organic component.[59,60] At the interface
between the inorganic and the organic domains of the crystal, the
polar heads of the ammonium cations replace the A+ cations.
The same happens in our nanoplatelets films, where thin inorganic
nanoplatelets are separated by organic molecules: it is fair to assume
that the Cs+ ions on the surface are replaced by the polar
heads of oleylammonium ions. Based on this assumption we can calculate
the theoretical elemental ratio in the sample. For vacancy-free two
octahedra-thick platelets the calculated ratio is Cs/Pb/Br = 1:2:7,
or otherwise 0.95:2:6.41 if the occupancies from the fit are included.
By SEM-EDS we measured Cs/Pb/Br = 0.93:2:6.43, while by XPS we found
Cs: Pb/Br = 1:2:6.1 (see the SI, section S6). In both cases, the Pb/Cs ratio is consistent with the model, demonstrating
that no Cs+ is found on the surface of the platelets. The
amount of bromine measured by SEM-EDS is also compatible with the
expectations, while it is slightly lower by XPS. In the latter case,
the lower Br content is rationalized as either due to a beam-induced
Br desorption or to the segregation of defective platelets on the
film surface (that is the spatial region to which XPS is most sensitive)
during the self-assembly process.Another open question is whether
oleic acid plays a role in surface
passivation of the nanoplatelets.[45] Both
oleylamine and oleic acid are used in the synthesis, and while an
oleylammonium bromide termination easily accounts for the role of
oleylamine, the presence of oleic acid cannot be easily excluded.
We addressed this question by characterizing self-assembled nanoplatelets
that had been synthesized with either a longer carboxylic acid (erucic
acid with C22 as compared to C18 in oleic acid)
or a shorter amine (octylamine with C8 as compared to C18 in oleylamine), taking advantage of the sensitivity of Multilayer
Diffraction to the interparticle spacing. The introduction of erucic
acid produced no appreciable change in the diffractogram. Instead,
in the octylamine-containing sample the interparticle distance dropped
from 34.0 to15.2 Å and the stacking disorder parameter decreased
from 0.50 to 0.24 Å. These findings confirmed the hypothesis
that oleic acid plays no significant role in the passivation of the
nanoplatelet surface, and are consistent with a prior NMR study by
de Roo et al. demonstrating that oleic acid is not
interacting with the surface of CsPbBr3 nanocrystals in
liquid dispersion.[45] See the SI, Section S6 for data and details regarding
the investigation of the surface passivation.
Identification and Refinement
of the Cs–Pb–I–Cl
Nanoplatelet Structure
We then turned our attention to mixed-halide
I–Cl nanoplatelets, a system that offers an increased structural
complexity due to the presence of two different anions which can,
in principle, share the same positions within the structures of cesium
lead halides. This combination of halides is appealing for a diffraction
analysis due to the large difference in the electron densities between
Cl– and I–, which makes it easier
to tell them apart, and because the different ionic radii favors the
segregation of halides, inducing the formation of the Cs2PbI2Cl2 Ruddlesden–Popper phase.[63] Only a few reports were published on nanocrystals
of this compound, and a detailed characterization of their structure
is lacking to date.[61,62,64,65]The Cs–Pb–I–Cl
nanoplatelets were prepared by a modification of the protocol used
for Cs–Pb–Br nanoplatelets. The modifications consisted
in using a doubled amount of Cs-oleate and in injecting a 1:1 mixture
of benzoyl chloride and iodide at 50 °C. Upon injection, the
solution immediately turned red, followed by a color transition to
light red-orange after a minute of growth, and to pale yellow upon
the addition of ethyl acetate during the nanoplatelet isolation. The
synthesized particles were analyzed by absorption spectroscopy and
TEM (Figure ). The
absorption spectrum features a strong excitonic peak at 3.12 eV, compatible
with that reported in the past for Cs2PbI2Cl2 nanoplatelets.[61,62] It is worth noting
that in Cs2PbI2Cl2 the exciton absorption
position is weakly dependent on the thickness of nanocrystals, as
the exciton peak in the bulk is red-shifted by only 0.08 eV (being
at 3.04 eV). This is because the [PbX6]4– octahedra are disconnected along the c crystallographic
axis, and behave as individually confined systems regardless of the
thickness of the crystal.[61] Therefore,
the thickness of the platelets had to be inferred directly from the
diffraction pattern. The sample was self-assembled into a multilayer
film and analyzed through X-ray diffraction, producing a pattern that
appeared very different from the case of bromine-based platelets:
the most intense group of fringes was found at a different position
in the q-scale (∼2 Å–1), and was less broad, suggesting thicker platelets than in the previous
case. Furthermore, we identified two diffraction features that did
not belong to the general periodicity of the multilayer, located at q = ∼1.12 Å–1 and q = ∼2.22 Å–1. The {100} and
{200} Bragg peaks of pseudocubic CsPbCl3[66,67] provided a potential match for these diffraction features, possibly
indicating an impurity of this compound in the sample. Since their
overlap with the Cs–Pb–I–Cl diffraction features
is minimal, we decided not to subtract them to minimize unnecessary
data processing.
Figure 3
Cs–Pb–I–Cl Ruddlesden–Popper
nanoplatelets.
(a) Absorption spectrum of Cs–Pb–I–Cl nanoplatelets.
The spectral position of the excitonic peak matches that reported
in the past for nanocrystals of the same material (400 nm/3.10 eV),[61,62] and is only weakly shifted from that of bulk Cs2PbI2Cl2 (408 nm/3.04 eV).[63] (b,c) TEM images and SAED diffraction pattern of Cs2PbI2Cl2. The SAED pattern provides information about
the structure of the platelets along the horizontal direction and
is compatible with what is expected for oriented Cs2PbI2Cl2 crystals. (d) Multilayer Diffraction fit of
the Cs–Pb–I–Cl nanoplatelets pattern. The starting
model for the fit was a slice of the published bulk structure (ICSD-6337),[63] I–/R-NH3+ terminated, with a thickness of three [PbI2Cl4]4– octahedra. In the refined structure, the Cs+ and I– ions are found to converge into
one common layer of ions as the platelet expands slightly along the
vertical direction (Pb–Pb distance +1.4%). The residual nonfitted
signals correspond to the {100} and {200} Bragg peaks of the CsPbCl3 impurity and to some signals from the substrate. Color legend
for atoms: Cs+ = light-blue; Cl– = green;
I– = purple; Pb2+ = dark gray (octahedra);
N = violet; C = black; H = white.
Cs–Pb–I–Cl Ruddlesden–Popper
nanoplatelets.
(a) Absorption spectrum of Cs–Pb–I–Cl nanoplatelets.
The spectral position of the excitonic peak matches that reported
in the past for nanocrystals of the same material (400 nm/3.10 eV),[61,62] and is only weakly shifted from that of bulk Cs2PbI2Cl2 (408 nm/3.04 eV).[63] (b,c) TEM images and SAED diffraction pattern of Cs2PbI2Cl2. The SAED pattern provides information about
the structure of the platelets along the horizontal direction and
is compatible with what is expected for oriented Cs2PbI2Cl2 crystals. (d) Multilayer Diffraction fit of
the Cs–Pb–I–Cl nanoplatelets pattern. The starting
model for the fit was a slice of the published bulk structure (ICSD-6337),[63] I–/R-NH3+ terminated, with a thickness of three [PbI2Cl4]4– octahedra. In the refined structure, the Cs+ and I– ions are found to converge into
one common layer of ions as the platelet expands slightly along the
vertical direction (Pb–Pb distance +1.4%). The residual nonfitted
signals correspond to the {100} and {200} Bragg peaks of the CsPbCl3 impurity and to some signals from the substrate. Color legend
for atoms: Cs+ = light-blue; Cl– = green;
I– = purple; Pb2+ = dark gray (octahedra);
N = violet; C = black; H = white.In order to find a suitable starting model for the refinement of
Cs–Pb–I–Cl nanoplatelets we tested several possible
structures obtained by slicing the reported bulk structure, until
we found a good match withthree [PbX6]4– octahedra thick, I-/R-NH3+ terminated Ruddlesden–Popper
nanoplatelets (see the SI, Section S7).
Starting from this preliminary model, we refined the atomic coordinates
and occupancies of the atoms on the surface. The platelets were found
to be 25.11 ± 0.03 Å thick, and were separated by an interparticle
layer of 30.25 ± 0.08 Å with a stacking disorder parameter
of 0.41 ± 0.07 Å. This corresponds to an overall multilayer
periodicity of 55.36 ± 0.08 Å. Like the Cs–Pb–Br
platelets, the crystal structure was slightly expanded along the thickness
of the platelets (Pb–Pb vertical distance = 9.58 Å vs 9.44 Å published,[63] +
1.46%). The surface coverage was found to be 90 ± 6%, higher
than that measured for pure bromide nanoplatelets.Thanks to
the excellent quality of the diffractogram, we could
also refine the coordinates of the atomic planes within the platelets.
Interestingly, the Cs+ and I– ions were
found to be almost coplanar (|zCs–zI| = 0.17 ± 0.15 Å), whereas in the
structure reported for bulk Cs2PbI2Cl2 they are shifted by 0.68 Å, therefore forming strongly staggered
planes. This is most likely an effect of the expansion along the thin
direction, that stretches the structure forcing the alignment. To
conclude, we remark that the fit produced excellent results even if
the iodide and chloride atoms were assigned to strictly different
crystallographic positions, without the need of considering mixed
occupancies. This indicates that the two halides segregate completely
within the nanoplatelets, a result that is expected based on the crystal
structure of bulk Cs2PbI2Cl2, but
that is not trivial for ultrathin nanoplatelets exposed to a reaction
environment containing an excess of both Cl– and
I– ions. The proposed structural model corresponds
to a composition of Cs/Pb/I/Cl = 4:3:5.8:6. The experimental composition
of the sample was found to be Cs/Pb/I/Cl = 4.8:4.3:5.8:9.2 by SEM-EDS
and 7.0:5.6:5.8:12.2 by XPS (see the SI, Section S8). After subtracting the predicted ratio, the measured compositions
leave Cs/Pb/Cl = 0.8:1.3:3.2 ratio (from SEM-EDS result) and 3:2.6:6.2
(from XPS result). Such residuals are consistent with a CsPbCl3 impurity in the sample, which was also indicated by XRD.
The higher fraction of impurity detected by XPS is explained by a
segregation of CsPbCl3 at the top of the nanoplatelet film,
which, again, is the region that contributes the most to the XPS signal.
It is indeed worth noting that any impurity situated in between the
substrate and the multilayer would inevitably increase the measured
stacking disorder of the multilayer, which is not the case for our
samples.
Conclusions
The self-assembled periodic
stacks of cesium lead halide nanoplatelets
can be considered the analogue of a hybrid organic–inorganic
single crystal, at least along the probed z-direction.
In such stacks, the nanoplatelets, their surface layers, and the organic
ligands between them constitute the structural motif that is repeated
by the periodicity of the multilayer. Such order is exclusive to the
stacking direction, as the samples are polycrystalline in-plane. However,
the in-plane mosaicity of the film does not impact our analysis, as
the experiments we reported selectively probe the sample perpendicularly
to the substrate.In analogy with the refinement procedures
adopted for conventional
crystals, the multilayer structure can be refined through a multiparametric
fit of its diffraction pattern. Given a starting structural model
that qualitatively matches the experimental data, the refinement procedure
allows to measure the multilayer periodicity, its structural disorder,
and the interparticle distance. Furthermore, it gives access to the
accurate determination of the nanoplatelets thickness, crystal structure,
stoichiometry and even surface passivation. As a result, the method
is able to provide insights into the surface composition, such as
the determination of the surface coverage of nanoplatelets and the
absence of oleic acid in their passivation layer. Furthermore, the
analysis enables a detailed comparison between the structure of nanoplatelets
and that of the corresponding bulk phases. This is the case of Cs2PbI2Cl2, where the Cs+ and
I– ions were found to be coplanar in nanoplatelets
while they are misaligned in bulk crystals (see Figure d, inset).While relevant per
se, we predict that such insights
will become even more significant for the rapidly growing field of
self-assembled halide perovskite superstructures,[5,18,37,38,68−70] where the methodology we have
developed might complement or even outmatch more elaborate characterization
tools within the limits imposed by probing a single direction. The
Multilayer Diffraction approach we adopted provides indeed a large
amount of detailed information, while relying solely on a simple and
widely accessible θ:2θ out-of-plane diffraction experiment.
Such experimental geometry is often used for in situ investigations and if applied to nanoplatelet multilayers would
give the opportunity to monitor their structural response under external
stimuli such as illumination, charge injection, temperature or pressure
gradients, and exchange or intercalation of chemical species. To help
further developments in this direction, we provided the simulated
diffraction patterns for Cs–Pb–Br and Cs–Pb–I–Cl
nanoplatelets of several different thicknesses (see the SI, section S9).Finally, by performing
a broad literature search we identified
a large number of published diffraction patterns that could be analyzed
with a Multilayer Diffraction approach. Those are recognizable by
the equally spaced diffraction peaks whose intensity shows a collective
trend (e.g., decreasing in intensity toward higher q or, as in this work, organized in broad groups with maximum
intensity at their center). Such diffraction patterns are often reported
for other metal halides, both in the form of colloidal two-dimensional
nanostructures or of bulk layered phases.[71−73] However, we
also found several other examples for metal oxides,[74−77] metal hydroxides,[78,79] natural layered silicates,[80] and MXenes,[81,82] both in the form of colloidal two-dimensional nanostructures and
layered bulk crystals. For these materials, and for any others that
exhibit a tendency to form stacks, the application of Multilayer Diffraction
represents an opportunity to gain deeper insight into their compositional,
structural, and surface-related properties.
All
the nanoplatelets were prepared according to the same general procedure,
which is here exemplified for the case of oleylammonium-capped Cs–Pb–Br
nanoplatelets. The specific conditions applied for each sample discussed
in this work are detailed in the SI, Table S1. First, a solution of ligands (120 μL of oleylamine and 160
μL of oleic acid) in 2 mL of decane was heated to 100 °C
inside an 8 mL glass vial. Second, the metal carboxylates (60 μL
of Pb-oleate and 20 μL of Cs-oleate) were preheated to the same
temperature to achieve a good homogeneity and an adequate fluidity,
and added to the solution by dipping and flushing the micropipette
tips inside the liquid several times to ensure a quantitative release.
Finally, the benzoyl halide (20 μL of Bz-Br) was injected in
the solution at 100 °C, triggering the immediate nucleation of
the nanoplatelets. After a growth time of 1 min, the reaction was
quenched by immersing the vial in water at room temperature. The resulting
colloidal suspension was destabilized by adding ethyl acetate until
it turned cloudy (∼4 mL). The particles were recovered by centrifugation
at 4000 rpm for 2 min and were resuspended in 1.2 mL of hexane. The
so-obtained suspension was filtered with a 0.2 μm PTFE syringe
filter and stored in a closed vial.
Benzoyl Iodide Preparation
Benzoyl iodide (Bz-I) was
prepared by mixing 1.4 mL of Bz-Cl and 3.0 g of sodium iodide at ∼75
°C overnight inside a N2-filled glovebox. The liquid
was recovered with a syringe, filtered with a PTFE 0.2 μm filter,
and collected inside a vial. After a few hours at room temperature
a solid, likely a sodium halide, formed on the vial walls and was
discarded by repeating the filtration process. The reaction product
was an orange-red liquid, that could be stored inside a glovebox in
a dark vial for more than one month without any appreciable change
in its aspect or reactivity.
Preparation of Metal Carboxylates
Lead oleate was prepared
by mixing 379 mg (1 mmol) of lead acetate trihydrate with 1.5 mL of
oleic acid at 100 °C for 3 h. The process was carried out under
mild vacuum to ease the volatilization of acetic acid. Cesium oleate
was prepared by mixing 192 mg (1 mmol) of cesium acetate with 1.0
mL of oleic acid at 100 °C for ∼1 h. As in the case above,
the process was carried out under mild vacuum to ease the volatilization
of acetic acid. Both processes yielded dense yellow liquids which
readily solidified when cooled at room temperature. Metal oleates
were preheated to 100 °C and stirred for a few minutes before
taking any aliquot to ensure the compositional homogeneity of the
precursor. Lead and cesium erucates were prepared in a similar way,
simply replacing oleic acid with an equimolar amount of erucic acid.
For Cs-erucate 1.07 g was used, while for Pb-erucate 1.61 g was used.
Preparation of Nanoplatelet Films
The films for the
Multilayer Diffraction experiments were prepared by diluting with
hexane the nanoparticles solutions obtained as described above by
a factor of 2–5. After the dilution, 50 μL of solution
were carefully deposited on a 1 × 1 cm silicon wafer (Ted Pella,
Inc., ⟨100⟩ orientation) placed inside a glass Petri
dish (inner volume ∼25 cm3). Then, the Petri dish
was closed with its glass lid, and a chink in between the edge and
the lid was created by adding a small piece of folded aluminum foil.
The solution was let drying completely until a homogeneous and iridescent
film was formed: the process required about 2–5 min. If the
film appeared opaque and not iridescent, the solution was further
diluted, and the process repeated. If the film appeared too thin or
invisible, a more concentrated solution was used instead. Figure S3 shows one successfully prepared film
as seen from above. A 1 mm thick glass slide placed underneath the
silicon to tilt it at an angle of about 10–15° helps in
getting more homogeneous films on at least one region of the substrate.
The thickness of the films in the iridescent areas was found to be
around 0.5 μm (see SI, Figure S4).
Diffraction Data Collection and Processing
The diffraction
patterns of the nanoplatelet films were collected with a Panalytical
Empyrean diffractometer in a parallel-beam configuration, equipped
with a 1.8 kW Cu Kα ceramic X-ray tube operating at 45 kV, 1
mm wide incident and receiving slits, and a 40 mA PIXcel3D 2 ×
2 two-dimensional detector. While the two-dimensional detector is
not a strict requirement for the application of the Multilayer Diffraction
method, it can help better visualizing the data and recognizing the
signals coming from multilayer stacks of nanoplatelets from those
produced by other sources (e.g. the substrate or
misaligned particles). In fact, multilayer diffraction signals appear
in the form of vertical straight stripes. Instead, the substrate produces
clusters of sharp and intense spots, while misaligned nanoparticles
produce arc-shaped signals. The two-dimensional data were integrated
over a rectangular sector, chosen to exclude or minimize the contribution
of other signals than those coming from the multilayers. Figure S5a shows a representative two-dimensional
diffractogram containing signals from the multilayer film, the substrate,
and some residual misaligned particles, together with the rectangular
sector selected for the integration, shown in yellow.The instrumental
background was measured on a clean silicon wafer and integrated under
the same conditions applied for the sample. Then, its 1D profile was
modeled into a spline using the MagicPlot software version 2.9.2,
and subtracted from the sample diffractogram after being rescaled
if needed. A background was considered well-paired with the experimental
data if it could adequately describe the diffracted intensity found
in regions far from intense multilayer diffraction fringes. Figure S5b shows an example of 1D diffractogram
as obtained after the integration of the 2D raw data, together with
a properly scaled background ready for the subtraction.In the
event that not all the spurious signals could be excluded
during the integration step, a subtraction was attempted. If the extra
signal was far from any multilayer fringe, it was simply described
as a sum of gaussians, subtracted, and the pattern was locally smoothed
by a moving average algorithm. If it was closed or overlapped with
the multilayer signal, instead, a different approach was taken. First,
the nearby multilayer fringes were fitted with a Gaussian profile
to recover their position and broadening. Then, the position and broadening
of the overlapping multilayer fringe overlap was inferred from those
of the neighboring fringes. Finally, the pattern region affected by
the overlap was fitted with the sum of a Gaussian peak, representing
the multilayer fringe and having its position and broadening fixed,
and a sum of additional peaks describing the additional, unwanted
signals. Those were subtracted, and the pattern was then ready for
the fit. This data treatment was performed only if the spurious signal
was reasonably weak if compared to the neighboring multilayer fringes.
If not, the pattern was fitted as it was (as for Figure in the main text), or simply
discarded. Figure S5c shows a diffraction
pattern after the subtraction of the background and of some spurious
signals, shown in red.The application of the Lorentz Polarization
Absorption (LPA) correction
is the last treatment performed on the diffractogram before proceeding
with the Multilayer Diffraction fit. This step is needed to compensate
for the geometrical and instrumental contributions to the diffracted
intensity, in order to transform the experimental diffractogram into
an measurement of the square modulus of the multilayer structure factor
|F(q)|2. This is the mathematical entity computed by our fitting
algorithm and directly relatable to the structure of the multilayer.
The LPA correction is a function of the beam incidence angle θ
and must be applied to each experimental point of the diffractogram
and is described by eq :[28]In the equation above, I0 is the intensity
measured experimentally (after the background subtraction), μ
is the absorption coefficient of the material, τ is the film
thickness, and θ is the Goebel mirror Bragg angle of the diffractometer (1°
in our case). The product μτ is responsible
for correcting the effects of the X-rays absorption occurring in thick
films. However, all our samples belonged to the thin film regime,
where the absorption is negligible and μτ → 0. Therefore, the product μτ was set constant to a small enough value in the fitting algorithm
(μτ = 0.00001). Smaller values would
lead our algorithm to crash. The pattern resulting from the LPA correction
is shown in Figure S5d.
Outline of
the Multilayer Diffraction Method
The fitting
algorithm presented in this work is an evolution of the one we presented
in our previous work on the diffraction analysis of nanocrystal superlattices,
to which we refer the reader for additional details.[38] In short, the algorithm computes the square modulus of
the multilayer structure factor |FML(q)|2 based on a structural model of the multilayer,
and considers both instrumental and structural parameters. Our algorithm
refines these parameters by comparing the simulated |FML(q)|2 with the experimental data processed
as illustrated
above, via the nonlinear least-squares minimization
of a cost function. The number and nature of the optimizable parameters
was editable, to allow for the maximum flexibility of the code. Those
can be divided into three groups, whose impact on the simulation is
described below.The instrumental parameters describe the contribution of the diffractometer to the measured
diffraction profile. These account for the incident X-ray wavelength,
the instrumental broadening of the diffraction signal, the Goebel
mirror incidence angle and for possible misalignments of the sample
during the measurement. The multilayer parameters describe the structure of the multilayer at a superatomic scale.
These mostly impact the periodicity and broadening of the diffraction
fringes in the diffractogram, and account for the nanoplatelet thickness,
the interplatelet distance, the structural disorder of the multilayer,
and the electron density of the organic layers in between the nanoplatelets.
The nanoplatelet parameters describe the atomistic
structure of the nanoplatelets. These contribute to the simulation
of the nanoplatelet structure factor, and mostly impact the integrated
areas of the diffraction fringes in the diffractograms. Their number
can be changed to meet the requirements of the specific experiments,
and constraints can be imposed during the fit to account for relationships
in between them. In general, these parameters describe the vertical
coordinate of each atomic layer inside the nanoplatelet, the elements
each layer contains and the fractional occupancy of each atom in the
layer. A more detailed breakdown of the meaning and role of each parameter
is provided in the SI, section S3.Based on these parameters, the algorithm first computes the structure
factors of both the nanoplatelets (FNPL, by applying the eq ) and of the interplatelet organic layer (FOL). The latter is modeled for simplicity as an amorphous layer
of carbon atoms, whose density is estimated a priori based on the density of long-chain liquid hydrocarbons. For further
details see the SI, section S5. The structure
factor of the organic layer is computed according to eq where ρC is the linear density
of carbon atoms expressed in atoms/Å formula unit, fC is the atomic form factor of carbon, and L is the interparticle
distance. Once FNPL and FOL have been calculated, the algorithm proceeds with computing
the multilayer structure factor FML first
and the multilayer diffraction pattern |FML(q)|2 then, according to the equations
derived by Fullerton et al. (here not shown for brevity).[28] As a last step, the algorithm simulates the
effects of the instrumental broadening on the just obtained diffraction
pattern, and then compares the obtained profile with the experimental
one. This comparison is repeated over and over while the program optimizes
all the fittable parameters by minimizing the mismatch in between
the experimental and the simulated pattern.To conclude, the
values and the standard deviations reported in
this article for each parameter are the result of a bootstrap analysis
performed on the fit. In short, the algorithm adds to the experimental
data set a Gaussian noise estimated over the variance of the experimentally
measured diffracted intensity, and then performs the fit. This procedure
is repeated 300 times, then the value and standard deviation of each
fittable parameter are expressed as the average and standard deviation
of the values found at each iteration for said parameter. For further
details on the bootstrap procedure and the estimation of the experimental
data variance please refer to our previous publication.[38]
Other Characterization Techniques
The absorption spectra
from colloidal suspensions of nanoplatelets were acquired on Cary300
spectrophotometer. The photoluminescence spectra were collected instead
on a Cary Eclipse spectrofluorometer. Low magnification transmission
electron microscopy (TEM) and selected-area electron diffraction (SAED)
images were acquired on a JEOL JEM-1011 microscope equipped with a
thermionic gun at an accelerating voltage of 100 kV. The samples were
prepared by depositing a diluted suspension of nanoparticles on a
200-mesh carbon-coated copper grids. Energy dispersive X-ray spectroscopy
(EDS) measurements were performed at 25 kV on a JEOL JSM-6490LA scanning
electron microscope (SEM). X-ray photoelectron spectroscopy XPS measurements
were performed with a Kratos Axis Ultra DLD spectrometer. For XPS
analysis, high-resolution spectra were acquired at a pass energy of
10 eV using a monochromatic Al Kα source (15 kV, 20 mA). The
thickness of iridescent areas of the nanoplatelet films was quantified
using a ZETA-20 true color 3D optical profilometer, after the sample
surface was softly scratched with a tip of a pair of plastic tweezers.
All the crystal structure models presented in this work have been
built using VESTA, ver. 3.4.6.[83]
Authors: Matthew J Jurow; Thomas Morgenstern; Carissa Eisler; Jun Kang; Erika Penzo; Mai Do; Manuel Engelmayer; Wojciech T Osowiecki; Yehonadav Bekenstein; Christopher Tassone; Lin-Wang Wang; A Paul Alivisatos; Wolfgang Brütting; Yi Liu Journal: Nano Lett Date: 2019-03-15 Impact factor: 11.189
Authors: Jasmina A Sichert; Yu Tong; Niklas Mutz; Mathias Vollmer; Stefan Fischer; Karolina Z Milowska; Ramon García Cortadella; Bert Nickel; Carlos Cardenas-Daw; Jacek K Stolarczyk; Alexander S Urban; Jochen Feldmann Journal: Nano Lett Date: 2015-09-03 Impact factor: 11.189
Authors: Quinten A Akkerman; Eva Bladt; Urko Petralanda; Zhiya Dang; Emanuela Sartori; Dmitry Baranov; Ahmed L Abdelhady; Ivan Infante; Sara Bals; Liberato Manna Journal: Chem Mater Date: 2019-03-04 Impact factor: 9.811