Robert S Weatherup1,2, Ashwin J Shahani3, Zhu-Jun Wang4, Ken Mingard5, Andrew J Pollard5, Marc-Georg Willinger4, Robert Schloegl4, Peter W Voorhees3, Stephan Hofmann1. 1. Department of Engineering, University of Cambridge , Cambridge CB3 0FA, United Kingdom. 2. Materials Sciences Division, Lawrence Berkeley National Laboratory , 1 Cyclotron Road, Berkeley California 94720, United States. 3. Department of Materials Science and Engineering, Northwestern University , 2220 Campus Drive, Evanston, Illinois 60208, United States. 4. Fritz Haber Institute , Faradayweg 4-6, D-14195 Berlin, Germany. 5. National Physical Laboratory , Hampton Road, Teddington, Middlesex TW11 0LW, United Kingdom.
Abstract
The dynamics of graphene growth on polycrystalline Pt foils during chemical vapor deposition (CVD) are investigated using in situ scanning electron microscopy and complementary structural characterization of the catalyst with electron backscatter diffraction. A general growth model is outlined that considers precursor dissociation, mass transport, and attachment to the edge of a growing domain. We thereby analyze graphene growth dynamics at different length scales and reveal that the rate-limiting step varies throughout the process and across different regions of the catalyst surface, including different facets of an individual graphene domain. The facets that define the domain shapes lie normal to slow growth directions, which are determined by the interfacial mobility when attachment to domain edges is rate-limiting, as well as anisotropy in surface diffusion as diffusion becomes rate-limiting. Our observations and analysis thus reveal that the structure of CVD graphene films is intimately linked to that of the underlying polycrystalline catalyst, with both interfacial mobility and diffusional anisotropy depending on the presence of step edges and grain boundaries. The growth model developed serves as a general framework for understanding and optimizing the growth of 2D materials on polycrystalline catalysts.
The dynamics of graphene growth on polycrystalline Pt foils during chemical vapor deposition (CVD) are investigated using in situ scanning electron microscopy and complementary structural characterization of the catalyst with electron backscatter diffraction. A general growth model is outlined that considers precursor dissociation, mass transport, and attachment to the edge of a growing domain. We thereby analyze graphene growth dynamics at different length scales and reveal that the rate-limiting step varies throughout the process and across different regions of the catalyst surface, including different facets of an individual graphene domain. The facets that define the domain shapes lie normal to slow growth directions, which are determined by the interfacial mobility when attachment to domain edges is rate-limiting, as well as anisotropy in surface diffusion as diffusion becomes rate-limiting. Our observations and analysis thus reveal that the structure of CVD graphene films is intimately linked to that of the underlying polycrystalline catalyst, with both interfacial mobility and diffusional anisotropy depending on the presence of step edges and grain boundaries. The growth model developed serves as a general framework for understanding and optimizing the growth of 2D materials on polycrystalline catalysts.
The catalytic
growth of graphene and other two-dimensional (2D) materials on polycrystalline
metal foils by chemical vapor deposition (CVD) has emerged as the
most versatile and commercially viable technique for manufacturing
continuous films to meet the industrial demand for electronic-grade
material.[1,2] Remarkable in this process is that continuous
single-layer graphene can be produced over large areas (up to several
square meters) on low-cost polycrystalline supports[3,4] and
can exhibit electronic properties comparable to those achieved by
mechanical exfoliation of graphite.[5] This
also represents a unique case in crystal growth as the graphene remains
confined to the quasi-2D surface of a bulk metal support, assuming
the barrier to additional layer formation is sufficiently large.[6] The catalyst support is therefore critical to
CVD of 2D materials, where its structure can have a definitive influence
on the properties of the material formed, including its thickness
uniformity,[6−9] domain size,[10−15] and defect density.[10,16]The ability to engineer
these material properties to meet specific application requirements
is one of the foremost goals of current 2D materials research. However,
the extent to which the catalyst serves as a template for growth remains
an open question, despite being one of the main levers alongside temperature
and gas environment, available for controlling the growth outcome.
Although there have been several efforts to elucidate epitaxial[17−19] or pseudoepitaxial relationships[20,21] between catalyst
surfaces and the growing graphene, the influence of surface morphology
including step edges and grain boundaries on growth dynamics is less
well understood. The elevated temperatures and reactive gas environments
under which growth occurs make direct observation challenging, while
ex situ measurements are ambiguous as the catalyst surface may be
highly dynamic and far from thermodynamic equilibrium during growth.
Nevertheless, several attempts have been made to explain the growth
dynamics by fitting ex situ microscopy data with established models
of crystal growth,[22,23] such as the Johnson–Mehl–Avrami–Kolmogorov
(JMAK) model.[24−29] In addition to the ambiguities associated with the post-mortem characterization,
these studies suffer from sparse data points, given that a separate
growth experiment must be performed for each point. Surface science
techniques that enable the direct in situ imaging of graphene growth
on the surface of carefully prepared single-crystalline samples under
ultrahigh-vacuum conditions avoid many of these problems.[18,30−32] However, there exists a substantial “pressure
and material gap” between these studies and the actual conditions
of large-area graphene deposition onto polycrystalline foils.[2,33] Furthermore, existing theoretical frameworks used to analyze the
growth dynamics of 2D materials suffer from a number of significant
limitations. The JMAK model for example assumes a constant nucleation
rate or a fixed number of nucleation sites, circular domain geometry,
and constant, isotropic radial growth velocity, which may not be valid
under realistic growth conditions.Here, we apply in situ scanning
electron microscopy (SEM) to directly observe graphene growth under
realistic CVD conditions on polycrystalline Pt samples and combine
this with structural characterization of the catalyst support to reveal
the interplay between the graphene structure and that of the catalyst
on which it forms. We find that established models of crystal growth,
such as the JMAK equation, do not adequately describe the growth behavior
observed on realistic polycrystalline catalysts, with major assumptions
being violated, including those of constant nucleation rate, and a
constant, isotropic growth rate. We therefore outline a general model
for growth that considers precursor dissociation, mass transport (bulk,
grain boundary, and surface diffusion), and attachment to the edge
of a growing domain. In this context, we analyze graphene growth dynamics
at different length scales (across multiple catalyst grains, for multiple
graphene domains within a grain, and for a single graphene domain)
to understand the rate-limiting steps in growth and how these influence
the geometry of the graphene domains that ultimately define the microstructure
of the continuous graphene film. We observe that growth is typically
interface-attachment-limited immediately after nucleation, changing
to diffusion-limited as the local carbon supersaturation is depleted,
and eventually transitioning to dissociation-limited as graphene domains
impinge on each other, isolating the surface from the precursor supply.
Significantly, we find that as well as varying throughout the growth
process, the rate-limiting step can vary across the catalyst surface,
even between different facets of the same graphene domain.When
growth is interface-attachment-limited, the graphene domain shape
is defined by the interfacial mobility, which varies as a function
of both graphene lattice orientation and the catalyst grain orientation.
The higher barrier for attachment to graphene facets embedded in step
edges compared to nonembedded facets gives rise to domain shapes that
lack rotational symmetry. As growth transitions toward being diffusion-limited,
the effects of anisotropic surface diffusion become more dominant,
with facet normals aligning with slow diffusion directions. This is
particularly apparent close to regions of high local surface curvature,
e.g., grain boundaries, where step edge densities are high and anisotropy
in surface diffusion is correspondingly increased. We thereby reveal
that the structure of CVD graphene films formed on polycrystalline
catalyst foils is intimately related to that of the underlying catalyst.
Results
and Discussion
We investigate the growth of graphene on polycrystalline
Pt foils (25 μm, 99.99%, Alfa Aesar) by CVD using in situ SEM
(see the Methods section). The samples are
first annealed in H2 (10–4 mbar) at 900–1000
°C for 15 min to promote Pt grain growth and remove adventitious
carbon from the surface of the foil and then exposed to C2H4 (10–6–10–4 mbar) at temperatures of 900–1000 °C, with SEM images
(∼0.1 Hz frame rate) acquired throughout.Figure shows SE micrographs of the
Pt surface during C2H4 exposure at different
times during the growth. Prior to the introduction of the precursor
(Figure A), the polycrystalline
nature of the catalyst surface is apparent from the variations in
contrast between different grains related to electron-channeling contrast[7,34] and the topographical contrast arising from the network of grain
boundaries separating them. The few small (<1 μm), bright
features visible within some of the Pt grains are attributed to residual
oxygen contamination of the Pt surface (as also observed in corresponding
X-ray photoelectron spectroscopy measurements; not shown) and disappear
early in the precursor exposure as they presumably react with carbonaceous
species arriving at the surface. Although the precursor pressure within
the chamber is reached within ∼15s (as confirmed by a residual
gas analyzer), there is a distinct incubation period during which
no graphene forms on any of the Pt grains. As the precursor exposure
continues, faceted graphene domains appear on several Pt grains (Figure B). Their darker
contrast compared to the bare Pt surface is related to the lower secondary
electron generation of graphene.[35] The
graphene domains grow in size with time and merge with the other graphene
domains upon which they impinge. Meanwhile, the nucleation of new
graphene domains occurs on other Pt grains that show longer incubation
times (Figure C).
The incubation times of different Pt grains vary widely, with graphene
domains nucleating on several grains within 90 s of the precursor
being introduced, while others show no nucleation events even after
>2500 s and only become covered with graphene due to the expansion
of domains from adjacent Pt grains across grain boundaries (Figure D). This is attributable
to grain orientation dependent variations in the precursor dissociation
rate, graphene nucleation barrier, or both, which are likely to be
affected by the density of low-coordination sites such as step edges.[36] During graphene growth, we note that ripening
of the Pt grains is also observed (compare panels A and D of Figure ), again highlighting
the need for in situ measurements when considering the relationship
between the microstructure of the catalyst and 2D material.
Figure 1
Graphene growth
evolution on polycrystalline Pt. (A–D) Sequence of in situ
SEM images of Pt (25 μm) during C2H4 (∼10–4 mbar) exposure at 900 °C, acquired 0 s (A),
150 s (B), 1500 s (C), or 6000 s (D) after precursor introduction.
The approximate orientations of the Pt grains determined by EBSD analysis
are indicated within the respective grains in (A). (E) Plot of the
areal coverage of graphene, A, with C2H4 exposure time, t, for the regions
marked with red and green boxes in (A). Inset: The same data plotted
in terms of Avrami coordinates, ln(−ln(1 – A)) vs ln(t).
Graphene growth
evolution on polycrystalline Pt. (A–D) Sequence of in situ
SEM images of Pt (25 μm) during C2H4 (∼10–4 mbar) exposure at 900 °C, acquired 0 s (A),
150 s (B), 1500 s (C), or 6000 s (D) after precursor introduction.
The approximate orientations of the Pt grains determined by EBSD analysis
are indicated within the respective grains in (A). (E) Plot of the
areal coverage of graphene, A, with C2H4 exposure time, t, for the regions
marked with red and green boxes in (A). Inset: The same data plotted
in terms of Avrami coordinates, ln(−ln(1 – A)) vs ln(t).For any given Pt grain, after the first graphene domain appears,
the nucleation of other domains occurs within a relatively short time
frame (<60 s). The first nuclei typically form near the center
of a Pt grain away from grain boundaries, and the nucleation density
is also observed to be lower close to Pt grain boundaries (see, for
example, Figure B). Figure E considers a single
Pt grain (indicated by the red polygon in Figure A) and plots the areal graphene coverage, A, with time, t, for the entire grain (red)
and for a region close to the center of the Pt grain (green square
in Figure A). In both
cases, A rises rapidly following the incubation period,
but the rate of increase in A reduces over time,
and complete single-layer graphene coverage is only slowly approached.
The JMAK equation is widely applied to describe nucleation and growth
during phase transformations[29,37] and has previously
been used to interpret ex situ graphene growth results on polycrystalline
Cu.[22] The inset of Figure E therefore plots the evolution of graphene
areal coverage in terms of Avrami coordinates, ln (−ln (1 – A)) versus ln (t); however, the clearly
nonlinear shape confirms that the JMAK equation does not adequately
describe the increase in the area fraction with time.In interpreting
the observed growth behavior, it is instructive to consider the key
processes involved in the growth of graphene on polycrystalline catalyst
surfaces during CVD, as outlined in Figure . The dissociation of the precursor delivers
carbon to the catalyst surface (Process 1), which can readily diffuse
on the surface (Process 2). This carbon can attach to a graphene domain
it encounters contributing to growth (Process 3) or can be removed
from the surface by diffusion into the bulk (Process 4) or grain boundaries
(Process 5), which serve as more rapid pathways for diffusion.[11,38,39] While Processes 4 and 5 can also
contribute to delivering carbon to the growing graphene domain, the
lower activation barrier for surface diffusion means Process 2 is
expected to dominate.[40,41]Figure indicates the net directions of mass transport
associated with these processes for typical graphene CVD conditions,
as used herein, where the catalyst bulk is not initially filled with
carbon and a net flux of carbon is delivered to the catalyst surface
by precursor exposure. We note, however, that the net directions of
mass transport associated with each of the processes can also be reversed
depending on the processing conditions, corresponding to removal of
surface carbon into the gas phase by etching, shrinking of graphene
domains due to carbon removal, and the diffusion of carbon out from
the bulk or grain boundaries.
Figure 2
Graphene growth processes on a polycrystalline
catalyst. Process 1: precursor dissociation supplies carbon to the
catalyst surface. Process 2: surface diffusion transports carbon across
the catalyst surface. Process 3: carbon attaches to the edge of a
growing graphene domain. Process 4: carbon diffusion into the bulk
of the catalyst removes carbon from the surface. Process 5: grain
boundary diffusion serves as a more-rapid pathway for carbon removal
from the surface.
Graphene growth processes on a polycrystalline
catalyst. Process 1: precursor dissociation supplies carbon to the
catalyst surface. Process 2: surface diffusion transports carbon across
the catalyst surface. Process 3: carbon attaches to the edge of a
growing graphene domain. Process 4: carbon diffusion into the bulk
of the catalyst removes carbon from the surface. Process 5: grain
boundary diffusion serves as a more-rapid pathway for carbon removal
from the surface.While the JMAK equation
is found to be inadequate in describing the behavior observed in Figure E, the evolution
of A within an individual catalyst grain qualitatively
resembles that obtained by consideration of an idealized single-crystalline
surface with a semi-infinite bulk on which graphene growth is fed
by the net flux arising from the supply and removal of carbon by Processes
1 and 4, respectively.[7,9] The supply of carbon by Process
1 can be modeled based on the kinetic theory of gases, as being constant
for a given grain orientation, precursor partial pressure, and temperature
but reducing in proportion to the bare catalyst area (1 – A) as graphene coverage isolates the catalyst from the precursor
supply. The removal of carbon by Process 4 can be modeled based on
1D Fickian diffusion perpendicular to the catalyst surface.[7] This yields the following general behavior for
a catalyst whose bulk is not initially filled with carbon: Upon the
introduction of the precursor, the supply of carbon to the surface
is matched by bulk diffusion, leading to an incubation period during
which the carbon concentration close to the catalyst surface increases
until the solubility limit is reached and a local supersaturation
develops. This supersaturation feeds the nucleation and subsequent
growth of graphene domains and is maintained by precursor dissociation
on bare areas of the catalyst. As the graphene coverage increases,
the supply of carbon to the surface by precursor dissociation is reduced
while diffusion into the catalyst bulk still continues, meaning that
growth slows and complete coverage is only gradually approached.The dependence of the area fraction on time for the entire grain
(red; Figure E) deviates
slightly from that obtained from just the central region (green; Figure E), showing a slower
initial growth rate and with full coverage approached more slowly.
This is attributed to the contribution of Process 5 in which grain
boundaries serve as pathways for rapid diffusion of carbon away from
the catalyst surface. This additional pathway for carbon removal also
reduces the supersaturation that develops in these areas, which accounts
for the lower nucleation densities observed close to grain boundaries.
Notably lower nucleation densities are observed close to the grain
boundaries toward the top left of the grain compared to those toward
the bottom right (see Figure B), consistent with the dependence of grain boundary diffusion
coefficient on the structure of the grain boundary.[42]While consideration of the balance of fluxes between
Processes 1, 4, and 5 is useful in describing how the overall graphene
coverage evolves within a platinum grain, i.e., the collective contribution
of many graphene domains, this assumes Process 1 to be the rate-limiting
step in growth and thus does not take Processes 2 and 3 into account,
nor does it provide insights into the localized behavior of individual
graphene domains such as how their shape and growth rate evolve. In
modeling these processes, we consider the edge of a single graphene
domain growing on the Pt surface where there exists a flux of carbon
from the Pt surface to the graphene domain, Jsg, and vice versa, Jgs. This yields
a net flux J that feeds the growth of the graphene
edge, which by conservation of mass is related to the growth velocity
normal to this edge, V:cg is the concentration of carbon in
graphene, and cI is the carbon concentration
at the interface between the growing graphene domain and the bare
Pt surface. Considering that attachment of carbon to the graphene
edge is impeded by an energy barrier, Δa, and that for growth to proceed there must
be a driving force, Δ, for
carbon attachment, we obtain the following expression (see the Supporting Information for detailed derivation):M(θ,ϕ) is the interfacial mobility and incorporates the energy
barrier associated with carbon attachment, which can depend on the
angle of the edge relative to the graphene lattice, θ, and to
the orientation of the underlying metal substrate, ϕ, as we
will discuss further below. μs(cI) and μg are, respectively, the carbon
chemical potentials of the Pt surface at the edge of the graphene
domain and the graphene itself. For the case in which μs(cI) ≫ μg, eq reveals that J → M(θ,ϕ) and, therefore,
growth is interface-attachment-limited. This situation arises when
a large supersaturation exists, such as immediately following nucleation.
When M(θ,ϕ) is small, J is also small, and initially the supersaturation
close to the growing edge can be readily replenished, such that cI is maintained near its far-field value, and
growth remains interface-attachment-limited. Thus, it follows from eq that V remains constant. When M(θ,ϕ) is large, however, the supersaturation
near the growing edge is quickly depleted and cannot be replenished
fast enough to maintain cI near its far-field
value, and thus, μs(cI) → μg and local equilibrium is approached.
The driving force for growth is reduced, such that , with cI determined
by diffusion of carbon across the catalyst surface and growth becoming
diffusion-limited. V is therefore now time-dependent,
varying as a function of cI. To precisely
determine this variation in V, the carbon diffusion
field around the graphene domain would need to be calculated (e.g.,
via the phase field method);[43] however,
we can nevertheless consider its general trend at different stages
of growth. When the graphene domain is small, the concentration gradients
around the domain are steep, and as the domain becomes larger, these
gradients become smaller, meaning V will decrease
with time in the diffusion-controlled limit.[44,45]In the context of this model, and by measuring the interfacial
velocities from the real-time data, we now consider the growth evolution
of individual graphene domains in a region of the same Pt grain. Figure A shows how the graphene
domains evolve across several time steps (160, 170, 180, and 190 s)
for a region within the green square indicated in Figure A. The domains adopt a trapezoidal
shape, with four major facets clearly identifiable. The growth velocities
of facets growing toward the top left (colored cyan) are notably slower
than those growing toward the bottom right (colored red), as is apparent
from the different spacing of facets between isochrones. Figure B shows a histogram
weighted according to facet length, revealing the angular distribution
of the facets at a growth time of 170 s. The four major facets are
aligned with ∼0°, ∼ 110°, ∼ 220°,
and ∼290° and are found to remain dominant even as the
graphene domains merge, although the histogram intensities vary somewhat,
and thus, the domain morphology is self-similar between time stamps
(see Video S1). Most significantly, the
differences between the facet angles are not multiples of 30°,
as might be expected if the graphene domain shapes were primarily
determined by zigzag, armchair, or some other intermediate termination
of the edges being most energetically favorable.[12,46−48] Therefore, as the faceted shapes of the graphene
domains cannot be attributed to the edge termination alone, the role
of the underlying substrate must be considered. Electron backscatter
diffraction (EBSD) patterns collected postgrowth reveal the bulk orientation
of the underlying Pt grain whose surface lies close to the (52̅2)
crystallographic plane. Previous LEED studies reveal that similarly
oriented surfaces remain stable, maintaining their nominal structure
when clean and under vacuum conditions and when covered with graphitic
carbon following precursor exposure.[49]Figure C therefore shows
a ball model of the corresponding unreconstructed Pt surface consisting
of (111) terraces with (100)-like steps, with the step edges indicated
by dashed red lines and the uphill direction indicated with an arrow.
While these (111) terraces are not expected to reconstruct under the
growth conditions used herein,[50,51] we note that reconstruction
of Pt(111) surfaces has been reported under certain conditions, albeit
while maintaining hexagonal symmetry.[50,51,54,55] For other Pt grain
orientations, faceting, reconstruction of the surface, including changes
in symmetry, or both may occur as for Pt(100), which is known to undergo
a hexagonal reconstruction.[52,53]
Figure 3
Growth kinetics of multiple
graphene domains within a single Pt grain. (A) Sequence of overlaid
isochrones extracted from SEM images taken 160, 170, 180, and 190
s after C2H4 introduction, showing domain edges
for a region within the green box marked in Figure A. The orientations of the facet normals
(defined as pointing out from the graphene domain to the substrate)
are indicated by the line color. (B) Plot of the angular distribution
of the graphene facet normals corresponding to the image taken after
170s in (A). (C) Ball model of the unreconstructed (52̅2) surface
orientation of the underlying Pt grain, determined by EBSD measurements.
Arrows indicate the six <111> directions that lie closest to
the plane of the surface (see Figure S2A for other directions), with the four colored arrows corresponding
to the similarly colored dominant graphene facet directions in (A).
Red dashed lines highlight the step edges, with the uphill direction
indicated by the labeled arrow.
Growth kinetics of multiple
graphene domains within a single Pt grain. (A) Sequence of overlaid
isochrones extracted from SEM images taken 160, 170, 180, and 190
s after C2H4 introduction, showing domain edges
for a region within the green box marked in Figure A. The orientations of the facet normals
(defined as pointing out from the graphene domain to the substrate)
are indicated by the line color. (B) Plot of the angular distribution
of the graphene facet normals corresponding to the image taken after
170s in (A). (C) Ball model of the unreconstructed (52̅2) surface
orientation of the underlying Pt grain, determined by EBSD measurements.
Arrows indicate the six <111> directions that lie closest to
the plane of the surface (see Figure S2A for other directions), with the four colored arrows corresponding
to the similarly colored dominant graphene facet directions in (A).
Red dashed lines highlight the step edges, with the uphill direction
indicated by the labeled arrow.Consideration of the low-index crystallographic directions
of the Pt surface reveals a clear relationship with the dominant graphene
facet orientations, which all lie normal to <111> directions.
Under kinetic control, the domain shape will be dominated by the slowest
growth directions. Given the dependence of V on M(θ,ϕ) and cI exemplified in eqs and 2, these <111>
directions are therefore expected to correspond to directions of low
interfacial mobility,[56] slow surface diffusion,[57,58] or both. It is also apparent that the growth of the slower velocity
facets toward the top left of the images (colored cyan) corresponds
with growth in the uphill direction. This slow uphill growth is consistent
with various surface science studies of graphene growth on low-index
surfaces of single-crystalline substrates, which reveal that the uphill
graphene facets can be embedded in the step edge and thus grow by
a metal-etching mechanism.[19,30,59−61] The slow velocity of these uphill facets accounts
for the trapezoidal shape of the graphene domains, as they will dominate
over the facets perpendicular to the two adjacent <111> directions
(black arrows in the inset of Figure C).This difference in uphill and downhill growth
rate cannot be attributed to the delivery of carbon across the catalyst
surface, as it persists even as the uphill and downhill facets of
different domains approach one another, and an asymmetry in the uphill
and downhill diffusivity of carbon species would violate the Onsager
principle of microscopic reversibility, which holds for transport
properties such as diffusion.[62,63] Instead, it is attributable
to a larger barrier for attachment to embedded facets, which presumably
relates to the need to eject metal atoms from the step for carbon
to be incorporated.[19,30,59−61] This confirms that the interfacial mobility, M(θ,ϕ), varies
between different facets and must be considered a function of both
the facet direction relative to the graphene lattice, θ, and to the substrate orientation, ϕ. This
can account for the more-diverse (including nonsymmetric) domain shapes
that are experimentally observed, in contrast to previous models that
typically assume an epitaxial alignment between the graphene lattice
and substrate orientation and thus predict domain shapes with at least
2-fold rotational symmetry.[43,64,65]Given the anisotropy in interfacial mobility that we have
observed, it is insightful to consider the kinetics of each facet
individually. Figure A shows the growth evolution of a single graphene domain that was
grown under conditions of higher growth temperature and lower precursor
partial pressure and maintains an irregular hexagonal shape throughout
(see Video S2). The slow growth rate and
large size of this domain, which results from the growth conditions,
gives the necessary spatial and temporal resolution to more precisely
consider the growth kinetics of each facet individually. A total of
six major facets colored blue, navy, red, orange, green, and cyan
(clockwise from the top facet) are apparent from early on and persist
throughout the ensuing growth period. Figure B shows the variation in velocity of each
of these facets with time based on the analysis of ∼100 frames
that were acquired ∼9.5 s apart (see the Methods section). The velocities of the red and orange facets are seen to
be constant throughout the growth period, indicating that their growth
is interface-attachment-limited and independent of domain size. Conversely,
the velocities of the blue and navy facets reduce over time as the
particle grows, indicating that the growth of these facets is instead
diffusion-limited. The cyan and green facets initially show constant
growth velocities, but after some time, their velocities start to
reduce, indicating that they transition from interface-attachment-limited to diffusion-limited growth.
This clearly highlights that different facets within a single grain
can show different rate-limiting steps that may evolve during growth.
Figure 4
Facet-dependent
growth kinetics for a single graphene domain. (A) Sequence of isochrones
(spaced by ∼47.5 s) of the domain edges obtained from SEM images
of Pt (25 μm) during C2H4 (∼10–5 mbar) exposure at 1000 °C, colored according
to the orientations of the facet normals (defined as pointing out
from the graphene domain to the substrate). (B) Plot of the facet
velocities with time for the six major facet orientations apparent
in A. (C) Ball model showing the unreconstructed (63̅5) surface
orientation of the underlying Pt grain, determined by EBSD measurements.
Arrows indicate the six <111> directions that lie closest to
the plane of the surface (see Figure S2B for other directions) with the four colored arrows corresponding
to the similarly colored dominant graphene facet directions in (A).
Red dashed lines highlight the step edges, with the uphill direction
indicated by the labeled arrow.
Facet-dependent
growth kinetics for a single graphene domain. (A) Sequence of isochrones
(spaced by ∼47.5 s) of the domain edges obtained from SEM images
of Pt (25 μm) during C2H4 (∼10–5 mbar) exposure at 1000 °C, colored according
to the orientations of the facet normals (defined as pointing out
from the graphene domain to the substrate). (B) Plot of the facet
velocities with time for the six major facet orientations apparent
in A. (C) Ball model showing the unreconstructed (63̅5) surface
orientation of the underlying Pt grain, determined by EBSD measurements.
Arrows indicate the six <111> directions that lie closest to
the plane of the surface (see Figure S2B for other directions) with the four colored arrows corresponding
to the similarly colored dominant graphene facet directions in (A).
Red dashed lines highlight the step edges, with the uphill direction
indicated by the labeled arrow.The bulk orientation of the underlying Pt grain is determined
from postgrowth EBSD patterns, revealing that the surface lies close
to the (63̅5) crystallographic plane, which again corresponds
to a surface orientation that is not expected to facet or undergo
a surface reconstruction either when clean and under vacuum or when
covered with graphitic carbon.[49] A sketch
of the corresponding unreconstructed surface is therefore shown in Figure C, with the step
edges indicated by red dashed lines. This reveals a close alignment
of four of the domain’s facets (green, navy, cyan, and red)
perpendicular to certain <111> directions (similarly colored
arrows in the inset of Figure C), similar to that noted earlier for the multiple domain
growth of Figure .
These facets also happen to align with the step edges on the surface.
We again observe a lower growth velocity for those facets growing
uphill (green and cyan), i.e., the facets expected to be embedded
in Pt steps, compared to those growing downhill (red and navy).The navy facet is the fastest growing at the start of growth and
thus corresponds to the highest mobility facet. Its diffusion-limited
behavior throughout growth is consistent with the local carbon supersaturation
ahead of it being rapidly depleted. The uphill growing facets (green
and cyan) show much lower growth velocities at the start of growth
and have correspondingly lower mobilities consistent with there being
a larger barrier for attachment to embedded graphene facets. They
thus remain interface-attachment-limited for a longer time, with the
carbon supersaturation developed prior to nucleation feeding their
growth, and transition to diffusion-limited growth as this supersaturation
becomes depleted. Interestingly, the red and orange facets toward
the bottom of the domain have higher mobilities but show interface-attachment-limited
behavior throughout growth, suggesting that a relatively high local
carbon supersaturation is maintained. Conversely, the blue facet toward
the top of the domain has the lowest growth velocity and yet shows
a diffusion-limited growth behavior consistent with the local carbon
supersaturation being rather low. While SEM does not directly reveal
the carbon supersaturation around the graphene domain, lower-magnification
SEM images (not shown) show that no other domains nucleate near the
top-left of the domain of interest, while other domains do nucleate
toward the bottom-right. This would be consistent with a gradient
in carbon supersaturation existing across the Pt grain increasing
from the top-left to the bottom-right, which may relate to variations
in the rates of carbon removal by different grain boundaries, differences
in the precursor dissociation rates between adjacent Pt grains, or
both. Alternatively, such differences in local carbon supersaturation
could arise due to the shape of the graphene domain itself, as the
local carbon supersaturation experienced by a facet is not only influenced
by its own growth but also by the growth of neighboring facets.Having considered the growth behavior of graphene domains within
Pt grains, we now focus on the growth across grain boundaries, which
is key to forming a continuous graphene layer over a polycrystalline
catalyst surface. Figure shows two sequences of SEM images (A–E and F–J)
in which graphene domains that have nucleated on different Pt grains
grow across Pt grain boundaries onto different areas of the same Pt
grain, whose surface orientation is determined as (43̅1̅)
by ex situ EBSD measurements. For both sequences, as the initially
sharp apexes of each graphene domain (Figure A,F) approach the Pt grain boundaries, they
are seen to drastically widen in the directions parallel to the grain
boundaries (see, for example, Figure C,H), leading to a change in the facet directions even
before the grain boundaries have been crossed. After crossing the
grain boundary, the growing domains both adopt new facet orientations,
as indicated by the dotted lines in Figure E,J. Notably, the facet orientations adopted
by both domains after crossing onto the same Pt grain are closely
aligned (compare the red, green, and blue dotted lines) despite the
two domains nucleating on differently oriented Pt grains and thus
presumably having different crystallographic orientations, θ.
This similarity in graphene domain shapes cannot be attributed to
the orientation of graphene lattice, i.e., any epitaxial relationship,
but instead indicates that their shapes are predominantly determined
by the underlying structure of the catalyst grain on which they both
end up. Many of the facet normals again appear to align with certain
<111>
directions of the catalyst grains both before and after crossing the
grain boundary, as indicated by the arrows colored orange in Figure A, purple in Figure F, and green and
blue in Figure E,J.
This highlights the importance of the substrate in influencing both
interfacial mobility and diffusion of carbon species, with these <111>
directions again expected to correspond to directions of low mobility,
slow diffusion, or both. It is also apparent from Figure that apexes of the graphene
domains coincide with the positions of the Pt grain boundaries, indicating
fast diffusion directions parallel to these boundaries. The grain
boundaries are clearly visible in all images during growth due to
the topographic contrast resulting from their high local curvature.
This curvature corresponds to a high density of step edges close to
the grain boundary, which run approximately parallel to it, as indicated
in Figure K. The lower
barrier to diffusion along the terraces compared to that of crossing
step edges leads to anisotropic surface diffusion, which increases
as the density of step edges increases (see Figure K). This increased anisotropy in surface
diffusion accounts for the drastic widening of the graphene domains
parallel to the grain boundary as it is approached. We note that for
Pt, which has an fcc crystal structure, no anisotropy in bulk diffusivity
is expected, and thus, these observations again highlight the dominant
role of surface diffusion in determining domain shape. This higher
density of step edges could also lead to a local increase in hydrocarbon
dissociation rate; however, while we do not exclude this, we note
that this alone cannot account for the faster growth rate parallel
to the grain boundary, and in any case, the rapid removal of carbon
by grain boundary diffusion is likely to dominate.
Figure 5
Graphene growth across
grain boundaries. (A–E) Sequence of SEM images of a graphene
domain (facets indicated with orange dotted lines in (A) that nucleated
on a Pt grain with a (512̅) oriented surface, showing its growth
across a grain boundary onto a Pt grain with a (43̅1̅)
orientated surface. (F–J) Sequence of SEM images of a graphene
domain (facets indicated with purple dotted lines in F) that nucleated
on a Pt grain with a (632̅) oriented surface, showing its growth
across a grain boundary onto a different region of the same (43̅1̅)
orientated Pt grain as identified in (A) (surrounded by cyan dashed
lines in (A) and (F)). The red, green, and blue dotted lines in (E)
and (J) indicate similar facet orientations established on this Pt
grain after the graphene domains have crossed from the differently
oriented Pt grains where they nucleated. Pt grain orientations are
assigned on the basis of postgrowth EBSD patterns. Arrows indicate
the <111> directions of each catalyst grain (see Figure S2C–E), with the colored arrows
corresponding to those <111> directions that lie normal to highlighted
graphene facets. The growth conditions are identical to those of Figure . (K) Schematic of
graphene growth across grain boundaries: (1) the higher barrier to
surface diffusion of carbon across step edges than along terraces
leads to an anisotropy in surface diffusion. (2) As a grain boundary
is approached, the much-higher density of step edges increases this
anisotropy in surface diffusion. (3) Grain boundary diffusion serves
as a rapid pathway for carbon removal from the surface, reducing the
local carbon concentration and slowing the growth rate of the graphene
domain as the grain boundary is approached.
Graphene growth across
grain boundaries. (A–E) Sequence of SEM images of a graphene
domain (facets indicated with orange dotted lines in (A) that nucleated
on a Pt grain with a (512̅) oriented surface, showing its growth
across a grain boundary onto a Pt grain with a (43̅1̅)
orientated surface. (F–J) Sequence of SEM images of a graphene
domain (facets indicated with purple dotted lines in F) that nucleated
on a Pt grain with a (632̅) oriented surface, showing its growth
across a grain boundary onto a different region of the same (43̅1̅)
orientated Pt grain as identified in (A) (surrounded by cyan dashed
lines in (A) and (F)). The red, green, and blue dotted lines in (E)
and (J) indicate similar facet orientations established on this Pt
grain after the graphene domains have crossed from the differently
oriented Pt grains where they nucleated. Pt grain orientations are
assigned on the basis of postgrowth EBSD patterns. Arrows indicate
the <111> directions of each catalyst grain (see Figure S2C–E), with the colored arrows
corresponding to those <111> directions that lie normal to highlighted
graphene facets. The growth conditions are identical to those of Figure . (K) Schematic of
graphene growth across grain boundaries: (1) the higher barrier to
surface diffusion of carbon across step edges than along terraces
leads to an anisotropy in surface diffusion. (2) As a grain boundary
is approached, the much-higher density of step edges increases this
anisotropy in surface diffusion. (3) Grain boundary diffusion serves
as a rapid pathway for carbon removal from the surface, reducing the
local carbon concentration and slowing the growth rate of the graphene
domain as the grain boundary is approached.Our data reveal that Processes 1–5 identified in Figure all play an influential
role in determining the final growth outcome during graphene CVD.
We therefore outline the following consistent picture of how these
processes contribute to the growth behavior on realistic polycrystalline
catalyst surfaces observed herein, as summarized in Figure : carbon is delivered to the
catalyst surface by precursor dissociation, whose rate may vary across
differently oriented, or reconstructed catalyst grains. This carbon
supply is initially matched by diffusion into the catalyst bulk, giving
a notable incubation time during which the catalyst becomes locally
filled with carbon close to the surface, and a supersaturation then
starts to develop (Figure B).[7] Grain boundaries serve as
rapid pathways for the diffusion of carbon away from the catalyst
surface, leading to a lower supersaturation developing close to grain
boundaries. The carbon supersaturation feeds the nucleation of graphene
domains, with higher nucleation densities occurring in regions of
higher supersaturation, such as the middle of catalyst grains (Figure C). Initially, the
ready supply of carbon from the supersaturation results in growth
of the nucleated domains being interface-attachment-limited, with
facets growing at constant velocities determined by the attachment
barrier (Figure D).
The shape of the graphene domains is thus determined by the interfacial
mobility, which is a function of both the orientation of the graphene
lattice and the underlying catalyst, with the lowest mobility facets
persisting. Over time, the local carbon supersaturation in front of
a growing facet can become depleted if it is not sufficiently replenished,
and growth will then transition toward being diffusion-limited (Figure E).[66] In this regime, the interfacial mobility will still influence
the growth velocity in a given direction; however, the role of any
anisotropy in surface diffusion will be increasingly dominant, and
the domain shape can evolve toward having facet normals aligned with
slow diffusion directions. This is exemplified close to catalyst grain
boundaries where the local curvature of the surface results in a high
density of step edges aligned with the grain boundary, which are barriers
to surface diffusion, leading to rapid diffusion parallel to the boundary
and the dramatic widening of the graphene domain in this direction
(Figure K). As growth
proceeds and neighboring graphene domains grow close to one another,
their diffusion fields overlap, and the bare catalyst surface available
for precursor dissociation reduces, leading to growth of facets becoming
dissociation-limited (Figure F).
Figure 6
Summary of graphene growth on a polycrystalline catalyst. (A–C)
On the initially clean catalyst surface (A), carbon precursor dissociation
delivers a flux of carbon, which is initially matched by diffusion
into the catalyst bulk (as indicated by red arrows), giving a notable
incubation time (B). As exposure continues, the catalyst becomes locally
filled with carbon close to the surface and a supersaturation develops,
which feeds the nucleation of graphene domains (C). Red arrows illustrate
the fluxes of carbon arriving at the catalyst surface and diffusing
into the bulk and grain boundaries. Rapid grain boundary diffusion
(large red arrows) lowers the supersaturation and, thus, nucleation
density close to grain boundaries. (D–F) The supersaturation
developed prior to nucleation provides a ready supply of carbon that
results in domain growth initially being interface-attachment-limited
(D), but as this supersaturation is locally depleted in front of a
growing facet, surface diffusion becomes rate-limiting (E). As the
graphene domains grow further and begin to merge, the catalyst surface
available for precursor dissociation diminishes and growth becomes
dissociation-limited (F). The colored arrows represent precursor dissociation,
surface diffusion, and interface attachment (Processes 1–3
identified in Figure ), with the red arrows indicating which of these processes is rate-limiting
at each stage.
Summary of graphene growth on a polycrystalline catalyst. (A–C)
On the initially clean catalyst surface (A), carbon precursor dissociation
delivers a flux of carbon, which is initially matched by diffusion
into the catalyst bulk (as indicated by red arrows), giving a notable
incubation time (B). As exposure continues, the catalyst becomes locally
filled with carbon close to the surface and a supersaturation develops,
which feeds the nucleation of graphene domains (C). Red arrows illustrate
the fluxes of carbon arriving at the catalyst surface and diffusing
into the bulk and grain boundaries. Rapid grain boundary diffusion
(large red arrows) lowers the supersaturation and, thus, nucleation
density close to grain boundaries. (D–F) The supersaturation
developed prior to nucleation provides a ready supply of carbon that
results in domain growth initially being interface-attachment-limited
(D), but as this supersaturation is locally depleted in front of a
growing facet, surface diffusion becomes rate-limiting (E). As the
graphene domains grow further and begin to merge, the catalyst surface
available for precursor dissociation diminishes and growth becomes
dissociation-limited (F). The colored arrows represent precursor dissociation,
surface diffusion, and interface attachment (Processes 1–3
identified in Figure ), with the red arrows indicating which of these processes is rate-limiting
at each stage.Importantly for polycrystalline
catalysts, the variations in precursor dissociation rate with grain
orientation and the rate of carbon removal at different grain boundaries
lead to an inhomogeneous carbon distribution across the catalyst surface,
meaning that the rate-limiting growth process not only varies with
time but can vary across different regions of the catalyst. This is
observed even on very local scales, for different graphene domains
within a catalyst grain, and even for individual graphene domains
where the growth of different facets can show different rate-limiting
steps. This has wider implications for the interpretation of growth
dynamics, where it cannot necessarily be assumed that a certain process
will be rate-limiting throughout growth or even across the catalyst
surface. Therefore, care must be taken when using global metrics (e.g.,
areal growth rate)[23,66] to quantify growth dynamics as
the contributions of facets with different rate-limiting steps may
be convolved, and the underlying origin of the growth behavior may
only be apparent from more local measures.The inhomogeneous
carbon distribution on the catalyst surface and the dependence of
interfacial mobility on graphene lattice and catalyst orientation
violates major assumptions of the established JMAK equation for crystal
growth, including that the nucleation rate must remain constant and
homogeneous across the surface and that the growth rate must be constant
and isotropic. Indeed, our results show that even for selected regions
of the catalyst surface, the JMAK equation does not adequately describe
growth. We therefore suggest that in modeling CVD graphene growth
on polycrystalline catalysts, orientation-dependent precursor dissociation,
grain boundary diffusion, and the different rate-limiting steps that
can exist during growth must all be taken into account.While
our results herein relate to polycrystalline Pt, which has a notable
carbon solubility (∼1.1 atom % at 1000 °C)[67] at the growth temperatures used, polycrystalline
Cu remains the most widely used catalyst for graphene CVD and has
a much lower bulk solubility (0.0007–0.0280 atom % at 1000
°C).[68,69] For both catalysts, isothermal graphene
growth is observed,[70] with the supply of
carbon by precursor dissociation filling the catalyst with carbon
close to its surface until a supersaturation develops that feeds graphene
nucleation. The associated incubation time will depend on the catalyst’s
carbon solubility, the rate of carbon supply by precursor dissociation,
and the rate of carbon removal into the catalyst, determined by its
permeability (the product of solubility and diffusivity).[7] Despite the low solubility of carbon in Cu, recent
literature suggests a relatively large carbon diffusivity,[71] and thus, the permeability and therefore the
rate of carbon removal from the surface of Cu may not be so drastically
different from that of Pt. Nevertheless, for all catalyst surfaces,
a carbon supersaturation will develop prior to graphene nucleation,
which feeds subsequent growth. The surface carbon concentration close
to a graphene facet will therefore decrease with time as the facet
grows, leading to time-dependent interfacial velocities and, thus,
violation of a key assumption of the JMAK equation. For Cu in particular,
the numerous observations of nonisotropic graphene domain shapes[2,12−14,16,20,22,23,43,56,66] further highlights that the JMAK equation is inappropriate
for describing growth. Instead, we emphasize that in modeling growth
on Cu, grain boundary and surface diffusion are expected to play important
roles regardless of the precise extent of carbon removal through bulk
diffusion, and thus, their influence on surface carbon distribution
should be carefully considered.
Conclusions
In
conclusion, we have shown that for polycrystalline catalyst foils
under realistic graphene CVD conditions, the rate-limiting steps in
growth can vary throughout the process and across different regions
of the catalyst surface. The dependence of precursor dissociation
on catalyst grain orientation and the different diffusion pathways
(surface, grain boundary, and bulk) that exist on polycrystalline
samples are found to play key roles in the observed growth behavior,
affecting the distribution of carbon species across the surface and,
thus, the rate-limiting growth process. The supersaturation developed
prior to graphene domain nucleation feeds an initial interface-attachment-limited
growth period, which transitions to diffusion-limited growth as this
supersaturation is depleted. As the domains begin to approach one
another and the available bare catalyst diminishes, precursor dissociation
becomes limiting. When growth is interface-attachment-limited, the
graphene domain shape is defined by the interfacial mobility, which
can vary as a function of both graphene lattice orientation and the
catalyst grain orientation. In diffusion-limited growth, surface diffusion
plays a more-dominant role in determining domain shape and is influenced
by the catalyst surface morphology, including the presence of step
edges and grain boundaries. This highlights that controlling the catalyst
texture and surface morphology is key to controlling the domain structure
of the graphene film produced. Our observations and analysis provide
new insights into how the structure of CVD graphene films is intimately
linked to that of the underlying catalyst, and the concepts developed
can serve as a general framework for understanding the growth of 2D
materials on polycrystalline transition metal catalysts.
Methods
In situ SEM experiments are performed using a commercial environmental
SEM (FEI Quantum 200, base pressure of ∼10–6 mbar) with a custom IR laser heating stage and with gas supplied
through a leak valve. Temperatures were measured with a type-K thermocouple
spot-welded to the sample and have an estimated uncertainty of ±50
°C. Samples were imaged using an Everhart–Thornley detector
and an acceleration voltage of 5.0 kV during pretreatment and growth,
while the CVD atmosphere was monitored by a mass spectrometer (Pfeiffer
OmniStar). Each full-image frame is acquired by raster scanning from
top left to bottom right and takes ∼9.5 s to acquire. The image
sequences analyzed in Figures –4 correspond to smaller regions
taken from full-image frames and thus have scan times of ∼1,
∼2, and ∼0.5 s, respectively. Low-magnification images
of the samples taken at several points during each growth experiment
show that regions around the imaged area have similar extents of growth,
indicating that the contribution of electron-beam induced effects
does not overwhelm the dominant CVD growth behavior.The assignment
of single-layer graphene based on in situ SEM contrast is confirmed
by extensive growth calibrations in which ex situ SEM (Zeiss SigmaVP,
1–2 kV, in-lens detector) images of the as-grown graphene on
Pt[72] are correlated with optical microscopy
and Raman spectroscopy (Renishaw Raman InVia Microscope, 532 nm excitation;
see Figure S3) measurements following transfer
to SiO2 (300 nm)/Si substrates using an electrolysis-based
bubbling technique, as previously described elsewhere.[7,48]EBSD measurements were performed ex situ in a FEI Helios dual-beam
microscope (5–15 kV, current of ∼5.5 nA, working distance
of 5.0–6.5 mm, and sample tilt of ∼60° with respect
to the electron beam) with an Oxford Instruments HKL EBSD Nordlys
II detector in spot mode using Channel 5 software.For quantitative
analysis, the SEM images were first binarized with an appropriate
threshold. Domain areas were determined by summing over those pixels
belonging to the graphene domains. A pair of copies were made of each
binary image, and these were then stacked upon one another to create
a pseudo-3D structure. The “height” of this structure
measured one unit, while the length and width were given by the image
dimensions. Then, the 3D structure was meshed (represented by a sequence
of triangles and vertices). To remove any “staircasing”
artifacts, the mesh was smoothed by a minimal number of iterations
of mean curvature flow.[73] The normal of
a given mesh triangle was given by the curl of its edge vectors, and
its velocity was calculated using the nearest-neighbor approach.[74] All codes were written in MATLAB R2015b and
executed on a Mac Pro 3.5 GHz, 12 core Intel Xeon system with 64 GB
of RAM.
Authors: Yufeng Hao; Lei Wang; Yuanyue Liu; Hua Chen; Xiaohan Wang; Cheng Tan; Shu Nie; Ji Won Suk; Tengfei Jiang; Tengfei Liang; Junfeng Xiao; Wenjing Ye; Cory R Dean; Boris I Yakobson; Kevin F McCarty; Philip Kim; James Hone; Luigi Colombo; Rodney S Ruoff Journal: Nat Nanotechnol Date: 2016-02-01 Impact factor: 39.213
Authors: Robert S Weatherup; Hakim Amara; Raoul Blume; Bruno Dlubak; Bernhard C Bayer; Mamadou Diarra; Mounib Bahri; Andrea Cabrero-Vilatela; Sabina Caneva; Piran R Kidambi; Marie-Blandine Martin; Cyrile Deranlot; Pierre Seneor; Robert Schloegl; François Ducastelle; Christophe Bichara; Stephan Hofmann Journal: J Am Chem Soc Date: 2014-09-19 Impact factor: 15.419
Authors: Piran R Kidambi; Bernhard C Bayer; Raoul Blume; Zhu-Jun Wang; Carsten Baehtz; Robert S Weatherup; Marc-Georg Willinger; Robert Schloegl; Stephan Hofmann Journal: Nano Lett Date: 2013-09-24 Impact factor: 11.189
Authors: Andrea Cabrero-Vilatela; Robert S Weatherup; Philipp Braeuninger-Weimer; Sabina Caneva; Stephan Hofmann Journal: Nanoscale Date: 2016-01-28 Impact factor: 7.790