From a systematic study of the concentration driven diffusion of positive and negative ions across porous 2D membranes of graphene and hexagonal boron nitride (h-BN), we prove their cation selectivity. Using the current-voltage characteristics of graphene and h-BN monolayers separating reservoirs of different salt concentrations, we calculate the reversal potential as a measure of selectivity. We tune the Debye screening length by exchanging the salt concentrations and demonstrate that negative surface charge gives rise to cation selectivity. Surprisingly, h-BN and graphene membranes show similar characteristics, strongly suggesting a common origin of selectivity in aqueous solvents. For the first time, we demonstrate that the cation flux can be increased by using ozone to create additional pores in graphene while maintaining excellent selectivity. We discuss opportunities to exploit our scalable method to use 2D membranes for applications including osmotic power conversion.
From a systematic study of the concentration driven diffusion of positive and negative ions across porous 2D membranes of graphene and hexagonal boron nitride (h-BN), we prove their cation selectivity. Using the current-voltage characteristics of graphene and h-BN monolayers separating reservoirs of different salt concentrations, we calculate the reversal potential as a measure of selectivity. We tune the Debye screening length by exchanging the salt concentrations and demonstrate that negative surface charge gives rise to cation selectivity. Surprisingly, h-BN and graphene membranes show similar characteristics, strongly suggesting a common origin of selectivity in aqueous solvents. For the first time, we demonstrate that the cation flux can be increased by using ozone to create additional pores in graphene while maintaining excellent selectivity. We discuss opportunities to exploit our scalable method to use 2D membranes for applications including osmotic power conversion.
Ion selective
membranes are
key targets for the advancement of separation-based technologies with
the aim to reduce their flow resistance while maintaining high selectivity.
In battery design, a low resistance separation membrane would reduce
internal resistance[1] with very similar
aims for separators in fuel cells or supercapacitors.[2,3] Likewise, ion selective membranes are attractive for applications
in osmotic power generation based on salinity gradients.[4] The prospect of using two-dimensional (2D) materials
like graphene as selective membranes has generated considerable excitement,
as an atomically thin material presents an obvious opportunity to
reduce the flow resistance.[5] All of these
applications require a membrane with excellent selectivity for positive
ions over negative ions while maximizing ionic transport.Significant
progress has been made in the scalable manufacture
of 2D materials; in particular, chemical vapor deposited (CVD) mono-
and few-layer films are ideally suited to address the technological
needs for atomically thin, functional membranes.[6] While single-crystal monolayer graphene has been shown
to be intrinsically impermeable to gases,[7] technologically relevant large-area (>few cm2) 2D
CVD
films typically exhibit a range of defects through which ions can
pass in solution, indicating a pathway toward their use as ion selective
membranes.[8] Critical to membrane applications
is the combination of high selectivity and high permeance.A
number of methods have been demonstrated to control perforation
of graphene membranes including ion bombardment, ozone treatment,
and oxidative etching.[9−11] Atomic and molecular transport through the pores
has been characterized by ionic current as well as optical and conductivity
measurements.[8,12,13] Despite these positive results, it remains unclear how selectivity
arises, exemplified by the lack of established methods for controlling
selective permeance.[14] A fundamental understanding
of selectivity is required for engineering new 2D materials into functional
membranes.[15]Furthermore, recent
literature has attributed the selective flux
to drilled or etched pores in graphene membranes without characterizing
the contribution from the intrinsic defects present across all CVD
graphene membranes. Consequently, it is hard to distinguish the contribution
to selectivity and leakage currents from both the engineered pore
and the defects.Since the selectivity of extrinsic material
systems like graphene
could arise due to charges on the pores, their size or a combination
of both[16,17] highly controlled experiments are crucial.
It was suggested that for desalination by size, physical control of
the pore size is required down to the sub-angstrom level.[16] Alternatively, high selectivity could be achieved
by exploiting charge effects to exclude co-ions from the pore and
only allow the passage of counterions.[18−20]Here, we set out
to understand transport and selectivity through
CVD-grown 2D membranes in aqueous solutions, focusing first on the
contribution of intrinsic defects to selectivity. These are unavoidable
in industrially relevant large-area membranes, so their effect must
be well characterized. By investigating the current–voltage
(I–V) curves of graphene
and hexagonal boron nitride (h-BN) membranes, we first prove selectivity
to cations and confirm that it mainly arises due to charge selective
pores. We propose a mechanism for how charge selectivity arises in
these pores and demonstrate a pathway to maximize ion flux while maintaining
excellent selectivity.In order to acquire large data sets with
minimal experimental overheads,
we use our established setup based on glass capillaries.[8,21] We measure the selectivity of 2D membranes by sealing the layers
across the tips of glass nanocapillaries with typical diameters of
180 nm, unless otherwise stated. Using electrodes inside the reservoir
and the capillary, we apply a voltage and measure the selective current.
We have previously shown that the resistance is a direct measure of
the defect density in graphene,[8] and selectivity
can be directly extracted from the I–V curves.[21] In brief, when the
concentration in the reservoir is lower than that in the capillary
and the membrane allows positive ions to cross more easily than negative
ions, then diffusion will cause a net current to flow even at V = 0 (green square in Figure a). The voltage needed to stop the diffusive
flow is called the reversal potential (red circle in Figure a). The reversal potential
(Vrev) depends on the concentration gradient
and for a perfectly selective membrane is predicted by the Nernst
equation[22]where R denotes the gas constant, T the absolute
temperature, z the ion valency, F is Faraday’s constant, and Co,i are the ion concentrations on either side of the membrane.
We use concentrations rather than activities as most of our solutions
are dilute, and this provides a conservative estimate of the selectivity.
For z = 1 at 10× difference in concentration,
one expects a reversal potential of 58 mV. All our results are benchmarked
with control measurements using “bare” capillaries and
Nafion as a positive control (see Supporting Information).[23]
Figure 1
(a) Typical I–V curves
for a capillary (180 nm) sealed with a monolayer CVD graphene membrane.
The solution in the capillary is 0.1 M KCl, and the reservoir solution
is varied from 0.001 to 1 M (all solutions at pH 6). When the concentration
in the reservoir is lower, diffusion causes a positive current (B)
to flow, indicating that the K+ ions cross the membrane
more easily. The voltage to stop this current is indicated by red
circles (A). (b) Representative Raman spectrum of the CVD graphene
used in this work. Acquired after transfer onto SiO2. It
indicates high-quality monolayer graphene.
(a) Typical I–V curves
for a capillary (180 nm) sealed with a monolayer CVD graphene membrane.
The solution in the capillary is 0.1 M KCl, and the reservoir solution
is varied from 0.001 to 1 M (all solutions at pH 6). When the concentration
in the reservoir is lower, diffusion causes a positive current (B)
to flow, indicating that the K+ ions cross the membrane
more easily. The voltage to stop this current is indicated by red
circles (A). (b) Representative Raman spectrum of the CVD graphene
used in this work. Acquired after transfer onto SiO2. It
indicates high-quality monolayer graphene.While most work across the literature so far has focused
on graphene,
our study here extends to CVD-grown monolayer h-BN[24−26] which, while
isostructural to graphene, has distinctive properties. h-BN is a wide
band gap semiconductor[27] exhibiting polar
bonding/edges. The differences between h-BN and graphene allow us
to establish if selectivity is material-specific or dominated by external
parameters.
Results
We
first focus on the cation selectivity arising from the small
number of defects inherently present in the 2D membranes we studied.
The preferred monovalent system is KCl, as the hydration radii of
K+ and Cl– and thus mobilities are similar
for co- and counterions.[28] A set of typical I–V curves for a graphene membrane
separating a capillary containing 0.1 M KCl and reservoirs of different
KCl concentrations is shown in Figure a. It is clear that the I–V curves shift and change as the concentration is varied,
indicating selectivity; when there is a 10× difference in concentration
across the membrane, the reversal potential is shifted by 48 mV, and
at 100× difference, the shift is 74 mV. The extent of the selectivity
can be quantified by plotting the value of the reversal potential
(marked by a red circle) against the logarithm of the reservoir concentration
(Figure a). In the
range of 0.001 to 0.1 M, we observe a clear linear dependence on reservoir
salt concentration for three concentrations in the capillary of 0.01,
0.1, and 1 M. For the lowest concentration in the capillary (0.01
M, light blue line in Figure a), we extract a gradient of 43.3 mV/log(M), approaching the theoretical limit. Increasing the capillary concentration
to 0.1 M KCl reduces the gradient to 35.9 mV/log(M) (blue line Figure a) and even further to 32.0 mV/log(M) at 1 M (navy
line Figure a). Our
results prove that K+ passes through the membrane more
easily than Cl–, and hence the graphene membranes
are cation selective. However, the reversal potential is only one
measure, and the diffusive current is actually more important in practice.
Figure 2
Measurements
to determine the selectivity of monolayer CVD graphene
to KCl. (a) Voltage offsets and (b) current offsets extracted from
the I–V curves as the reservoir
concentration is varied from 1 mM to 2 M KCl for experiments with
0.01, 0.1, and 1 M KCl in the capillary (all solutions unbuffered
at pH 7). The legend indicates the Debye length in the capillary.
To account for the different solution conductivities, the current
offsets have been normalized to the conductivity for 0.1 M solution;
for a non-normalized version, see Supporting Information. For 0.01 M in the capillary, from the gradient of the fitted line,
the voltage offset is 43.3 mV/log(M) and the normalized
current offset is −0.2 nA/log(M). The values
for 0.1 M in the capillary are 35.1 mV/log(M) and
−0.02 nA/log(M). For 1 M in the capillary,
the values are 32.0 mV/log(M) and −0.003 nA/log(M).
Measurements
to determine the selectivity of monolayer CVD graphene
to KCl. (a) Voltage offsets and (b) current offsets extracted from
the I–V curves as the reservoir
concentration is varied from 1 mM to 2 M KCl for experiments with
0.01, 0.1, and 1 M KCl in the capillary (all solutions unbuffered
at pH 7). The legend indicates the Debye length in the capillary.
To account for the different solution conductivities, the current
offsets have been normalized to the conductivity for 0.1 M solution;
for a non-normalized version, see Supporting Information. For 0.01 M in the capillary, from the gradient of the fitted line,
the voltage offset is 43.3 mV/log(M) and the normalized
current offset is −0.2 nA/log(M). The values
for 0.1 M in the capillary are 35.1 mV/log(M) and
−0.02 nA/log(M). For 1 M in the capillary,
the values are 32.0 mV/log(M) and −0.003 nA/log(M).In Figure b, we
plot the diffusive current (green square, B, in Figure a). The obvious negative gradient provides
more evidence for selectivity for a capillary concentration of 0.01
M. However, the selective current is greatly reduced for higher salt
concentrations in the capillary (>0.1 M) (Figure b), strongly suggesting that the Debye screening
length on the high concentration side plays an important role. The
dependence on Debye screening length strongly points toward charge
selectivity; that is, negatively charged pores in the graphene are
the dominating cause.Ions have different diameters, and in
aqueous solution, both the
size of the hydration shell and the strength it is bound with need
to be considered.[28] These differences may
influence selective transport.[29] To determine
if the type of ion affects the selectivity, we repeated our experiments
with NaCl, LiCl, and MgCl2. Summarizing the reversal potential
and diffusive current in Figure a, it can be seen that all three ions show significant
selectivity for the positive ion over the Cl–. The
Li+ was selected for most strongly, whereas for Mg2+, selectivity was much lower. This is surprising as Mg2+ is larger than Li+. With this result, we can
exclude ion radii as the primary cause of selectivity. If charge selectivity
is dominating, then Mg2+ as a divalent ion will more effectively
screen the charge of the pore, leading to a shorter Debye screening
length and thus reduce the charge selective effect, as observed. Our
results indicate that selectivity arises primarily through charges
on the graphene layers.
Figure 3
Investigating the selectivity of monolayer graphene
to different
ions. (a) Voltage offsets (A) and current offsets (B) for a 0.1 M
capillary and reservoir concentrations of 0.001 to 1 M for LiCl, NaCl,
KCl, and MgCl2 (all solutions unbufffered at pH 7). All
show evidence for selectivity. (b) Percent of the maximum selectivity
for each condition plotted against the Debye length on the high concentration
side of the membrane. The exponential dependence of selectivity on
Debye length shows that selectivity is due to charge and is controlled
by the highest ion concentration.
Investigating the selectivity of monolayer graphene
to different
ions. (a) Voltage offsets (A) and current offsets (B) for a 0.1 M
capillary and reservoir concentrations of 0.001 to 1 M for LiCl, NaCl,
KCl, and MgCl2 (all solutions unbufffered at pH 7). All
show evidence for selectivity. (b) Percent of the maximum selectivity
for each condition plotted against the Debye length on the high concentration
side of the membrane. The exponential dependence of selectivity on
Debye length shows that selectivity is due to charge and is controlled
by the highest ion concentration.Our selectivity data indicate a fundamental difference of
2D membranes
when compared to that of traditional materials like Nafion (see Supporting Information). Usually, one expects
that selectivity is controlled by the lowest ion concentration. In
contrast, for graphene, the decisive role of the shortest Debye screening
length is shown by the exponential dependence of the selectivity (Figure b). Clearly, the
higher ion concentration controls the selectivity, regardless of whether
it is the reservoir or the capillary (see Supporting Information). We attribute this to the atomic thickness of
the graphene; that is, the entrance to the pore is the dominating
source of selectivity because the effective length of the selective
channel is negligible.[30]Having established
that the selectivity depends on the Debye screening
length, we can determine the pore size.[19] For a 2 nm Debye layer, the selectivity is 50% whereas it increases
to 100% at 10 nm (Figure b). Given that Debye overlap is essential for selectivity,
we can conclude that the pores are probably between 0.4 and 3 nm in
diameter, in line with previous literature.[8,9,31−33] Because we see no significant
selectivity due to ion size, this suggests that the precise diameter
of the pores is not significant for controlling selectivity, and many
intrinsic pores are larger than 1 nm. Individual defects in graphene
membranes have been imaged using transmission electron microscopy
(TEM),[13,31,34] demonstrating
that different atomic arrangements are found. However, our results
suggest that the exact defect shape is not critical for selectivity
as it arises from charge effects. This is in contrast to the transport
of gases through graphene nanopores for which it has been suggested
that small differences in the atomic structure of the pore can change
the permeance.[35] In our experiments in
aqueous solution, the charge effects are much longer ranged than such
steric effects and therefore dominate the behavior.At first
glance, it is surprising that CVD graphene is cation selective.
For the development of full control over charge selectivity, it is
important to determine its origin. A negatively charged graphene surface
is the obvious explanation. We tested this hypothesis by changing
the pH, maintaining the same pH in the capillary and the reservoir.
As before, we identify reversal potentials from I–V curves to assess how selectivity depends
on pH (Figure ). At
pH >5, graphene shows a high selectivity, becoming gradually nonselective
at a pH less than 3 (red line, Figure ).
Figure 4
Effect of pH on selectivity for K+ over Cl– for graphene and h-BN. The capillary concentration
was 0.1 M, and
the reservoir varied from 1 to 100 mM. The pH of the reservoir and
the capillary was set using HCl and KOH. The graphene membrane and
h-BN both demonstrate increasing selectivity as pH increases to pH
6. For control measurements, see Supporting Information.
Effect of pH on selectivity for K+ over Cl– for graphene and h-BN. The capillary concentration
was 0.1 M, and
the reservoir varied from 1 to 100 mM. The pH of the reservoir and
the capillary was set using HCl and KOH. The graphene membrane and
h-BN both demonstrate increasing selectivity as pH increases to pH
6. For control measurements, see Supporting Information.In order to clarify the molecular
origin of this pH-dependent charge,
we compared membrane materials with very different characteristics. Figure depicts the selectivity
for graphene and h-BN (positive control measurements for Nafion are
shown in the Supporting Information). We
observe no significant difference in selectivity between the 2D materials
over the entire pH range. Since h-BN and graphene behave almost the
same, we propose that selectivity arises as a result of external factors.
The different chemical composition of graphene and h-BN makes it unlikely
that negative surface charge arises due to edge chemistry alone. Likewise,
the different electrical properties, where graphene is conducting
and h-BN is insulating, suggest that the glass surface charge is not
transferred to the pores.Previous studies of the selectivity
of defects in graphene membranes
have largely focused on the chemical functionalization of the pores[18] or the precise pore size.[16] However, it is well-known that properties of 2D materials
like electron mobility are often strongly dependent on the substrate.[36] For 2D membranes submerged in aqueous solution,
adsorption of OH– ions was suggested recently as
the origin of both selectivity of BN[4] and
carbon nanotubes.[37] We also observe slight
shifts in the peaks and changes of the G to 2D ratio and fwhm of the
peaks in the Raman spectra for graphene floating on water compared
to graphene on SiO2, which correspond with the graphene
acquiring charge in solution (see Supporting Information).[38] The exact origin of charge at the
liquid–2D interface is still under debate. Any surface exposed
even briefly to air may acquire hydrocarbon molecules, reactions of
which can contribute to negative surface charge.[39−42] The impact of adsorbed molecules
is much more significant on 2D materials as they are composed almost
entirely of interfaces. Interestingly, our explanation is also supported
by the recent work of Rollings et al.,[43] who have studied single graphene nanopores fabricated
by voltage breakdown. They found that 2–20 nm engineered pores
are cation selective with a similar dependence on pH. OH– absorption is fully consistent with our observation that at low
pH the high concentration of H+ will passivate the charges
and hence reduce selectivity for both h-BN and graphene.Having
established the source of selectivity for 2D membranes to
be surface charge, we now focus on the technologically important question:
how flux can be increased while maintaining high selectivity. One
method of opening new pores in graphene is brief exposure to ozone.[8] We investigated graphene that had been exposed
to ozone at 200 °C for 5 and 20 s. As a reference, we compare
these samples to one decorated with Al2O3. Atomic
layer deposition (ALD) of Al2O3 directly on
graphene[44−47] with tightly controlled nucleation behavior significantly reduces
the size of defects due to the poor wetting of the precursors.[10,21] We have previously shown that the Al2O3 treatment
decreases the current flowing through the defects by at least an order
of magnitude, while ozone treatments controllably create new defects,
resulting in higher current flows.[8,21]Figure a shows
the reversal potentials associated with each of these samples. All
the samples are selective to positive ions with selectivity in the
range of 31–34 mV/log(M). However, this measure
does not capture the significant differences in the current flowing
through each of these membranes. Figure b shows the magnitude of the selective current
dramatically increasing with the number of defects. This crucial result
of enhanced diffusive current while maintaining high reversal potential
shows that the ozone treatment on this short time scale has predominately
created new pores which are as selective as the intrinsic defects.
The Al2O3-decorated graphene has a much lower
current due to diffusion, even though the selectivity is maintained.
This demonstrates that the defects blocked by the Al2O3 are the selective pathways.
Figure 5
Effect of blocking and creating defects
on selectivity to KCl.
The defects in a graphene sample were blocked by depositing 2 nm of
Al2O3 and created by exposing the graphene to
ozone. These are compared with a sample of as-grown monolayer graphene
(MLG). The capillary (180 nm) is at 0.1 M KCl, and the reservoir varied
between 1 mM and 0.1 M (all solutions unbuffered at pH 7). (a) All
four membranes show a positive voltage offset, indicating they are
selective to the positive ion. The gradients are 31.7, 32.8, 32.8,
and 34.4 mV/log(M). (b) Current due to diffusion
at 0 V when there is 100× concentration difference across the
membrane. This demonstrates that the ozone treatment creates new defects
which are as selective as the intrinsic defects in graphene. (c) Voltage
offsets showing how the selectivity of a graphene sample to K+ over Cl– changes as it is etched in acidic
KMnO4. The capillary (180 nm) is 0.1 M KCl, and the reservoir
is 1 mM and 0.1 M. Initially, the selectivity is 52.4 mV/log(M); after 10 min of etching, the selectivity is 23.0 mV/log(M), and after 20 min, the selectivity has reduced to 14.4
mV/log(M).
Effect of blocking and creating defects
on selectivity to KCl.
The defects in a graphene sample were blocked by depositing 2 nm of
Al2O3 and created by exposing the graphene to
ozone. These are compared with a sample of as-grown monolayer graphene
(MLG). The capillary (180 nm) is at 0.1 M KCl, and the reservoir varied
between 1 mM and 0.1 M (all solutions unbuffered at pH 7). (a) All
four membranes show a positive voltage offset, indicating they are
selective to the positive ion. The gradients are 31.7, 32.8, 32.8,
and 34.4 mV/log(M). (b) Current due to diffusion
at 0 V when there is 100× concentration difference across the
membrane. This demonstrates that the ozone treatment creates new defects
which are as selective as the intrinsic defects in graphene. (c) Voltage
offsets showing how the selectivity of a graphene sample to K+ over Cl– changes as it is etched in acidic
KMnO4. The capillary (180 nm) is 0.1 M KCl, and the reservoir
is 1 mM and 0.1 M. Initially, the selectivity is 52.4 mV/log(M); after 10 min of etching, the selectivity is 23.0 mV/log(M), and after 20 min, the selectivity has reduced to 14.4
mV/log(M).To further increase the flux, the size of defects could be
increased,
though this may cause selectivity to decrease. We etched our samples
with acidic potassium permanganate (2 mM KMnO4·0.5
M H2SO4) to grow the defects (Figure c). It has been established
by us and others that acidic KMnO4 attacks defects.[9] Over a period of up to 20 min, we observed the
resistance of the membrane decrease by a factor of 4. At regular intervals,
we stopped the etching process and exchanged the reservoir solution
to determine the selectivity. We observed a decrease in selectivity
from 52 mV/log(M) initially to 14 mV/log(M) after 20 min. By assuming that the defect density remains
constant, we can estimate the change in defect size from the change
in resistance. From this calculation, we estimate the defects to be
1–6 nm when selectivity is removed after 20 min of etching.
Recent work by Rollings et al.(20) has suggested that pores drilled in graphene are selective
up to 20 nm diameter; this may highlight the importance of intrinsic
defects.While the ozone treatment creates new defects that
are clearly
selective, etching using KMnO4 allows for fine-tuning of
the resulting pore diameter. Thus, optimization of the membrane permeability
and selectivity to specific types of ions should be achievable. Combining
ozone and etching treatments is a potential pathway to maximize the
selective flux. Importantly, brief ozone treatments are industrially
relevant as they can be applied to large areas to create many pores.
Parallel fabrication of pores has distinct advantages over methods
relying on drilling pores using TEM or voltage-induced etching.[20] Due to the charge selective nature of the defects,
precise control over the pore size is not required.[16] This remarkable finding also strengthens our interpretation
that we see transport through intrinsic defects in graphene membranes
and that leakage currents are negligible.The high flux through
our selective membranes could be utilized
within energy generation. A promising approach is the osmotically
driven current created from salinity gradients. We calculate that
at pH 7 the osmotically driven current through the ozone-treated graphene
equates to a power of 700 Wm–2 compared to 500 Wm–2 for Nafion. We note that 1100 Wm–2 has been demonstrated for a boron nitride nanotube. However, the
BN nanotube samples require more complex fabrication.[4] Given the scalability of CVD graphene and the ozone process
used, porous 2D materials could be used for renewable energy generation
or desalination if anion selectivity is demonstrated.
Conclusions
In summary, we have carried out a comprehensive study of the selectivity
of CVD-grown two-dimensional membranes to different ions. Our results
have shown that charge selectivity is the dominant effect. It follows
that precise control of the pore size is not required to create an
ion selective membrane. We found that at high pH, positive ions are
strongly selected for, but selectivity decreases as pH decreases.
Given that this is observed in different 2D materials, clearly extrinsic
factors due to the aqueous environment such as adsorbed OH– are the likely cause of the negative surface charge. Our results
demonstrate that ozone and etching treatments can increase the number
of pores, thus greatly enhancing flux while maintaining high selectivity
of the 2D membranes.
Methods
Glass
nanocapillaries are pulled using a laser capillary puller
(Sutter P2000) to give 180 nm tips. These are filled with the appropriate
salt solution.Graphene is grown by chemical vapor deposition
in an Aixtron BM
Pro (4 in.) reactor, using 25 μm thick Cu foil (Alfa Aesar,
99.8%) as the catalyst and CH4 (diluted in Ar and H2) as the precursor at 1050 °C.[6] Hexagonal boron nitride is grown by chemical vapor deposition on
an Fe catalyst using HBNH3 at a temperature of 940 °C
and a pressure of 1 × 10–3 mbar.[25]After growth, it is transferred to a single
salt crystal using
a standard PMMA wet transfer process.[48] The 2D material is floated on the surface of a water reservoir by
placing the salt crystal carrying the material into the reservoir
and allowing it to dissolve. As it dissolves, the material is released
so that it is floating freely on the surface.[8]The nanocapillary is mounted on a micromanipulator, and Ag/AgCl
electrodes in the capillary and reservoir connect to a patch clamp
amplifier (Axopatch 200B) to apply voltages and measure currents.
The capillary is lowered slowly onto the graphene so that it forms
a seal which can be assessed using the I–V characteristic. A coated electrode is used to maintain
the reservoir electrode at a constant potential, and the amplifier
offset is set to zero when the solution in the reservoir matches the
capillary. The reservoir electrode is coated in agarose made up in
0.1 M of the solution under test, usually KCl. The reservoir solution
is then exchanged and an I–V curve obtained for each from which the reversal potential is extracted.[21]The short ozone treatments are carried
out in a Cambridge Nanotech
Savannah system at 200 °C.[45] A constant
flow of N2 (20 sccm) provides a background pressure of
6 × 10–1 mbar to which ozone pulses of ∼200
mbar and 0.5 s duration are added with 20 s purges between them.[46] The ozone is generated using a Del Ozone LG-7
corona discharge ozone generator. Total ozone exposure times of 5
and 20 s are used, and the resulting increase in defect density can
be observed in Raman spectroscopy and as a decrease in the resistance
of the membrane.[8] CVD graphene is decorated
with 2 nm of Al2O3 by atomic layer deposition
using a 20 cycle process at 200 °C in a Cambridge Nanotech Savannah
ALD system. The cycles consist of alternating pulses of trimethylaluminum
and water both carried in N2 (20 sccm) separated by 8 s
purges between them.[45,47] This would typically yield a
2 nm thick film on Si with a native oxide. However, this relatively
high-temperature, water-based process leads to preferential decoration
at defects because of the poor wetting of the Al2O3 on graphene.[44−46,49]The potassium
permanganate etching is conducted by immersing the
tip of the graphene-coated capillary in 0.5 M H2SO4 and 2 mM KMnO4 for a timed period.[9] This causes the resistance of the membrane to decrease
as well as the selectivity change shown above.
Authors: S Hu; M Lozada-Hidalgo; F C Wang; A Mishchenko; F Schedin; R R Nair; E W Hill; D W Boukhvalov; M I Katsnelson; R A W Dryfe; I V Grigorieva; H A Wu; A K Geim Journal: Nature Date: 2014-11-26 Impact factor: 49.962
Authors: Adrianus I Aria; Piran R Kidambi; Robert S Weatherup; Long Xiao; John A Williams; Stephan Hofmann Journal: J Phys Chem C Nanomater Interfaces Date: 2016-01-07 Impact factor: 4.126
Authors: Marie-Blandine Martin; Bruno Dlubak; Robert S Weatherup; Heejun Yang; Cyrile Deranlot; Karim Bouzehouane; Frédéric Petroff; Abdelmadjid Anane; Stephan Hofmann; John Robertson; Albert Fert; Pierre Seneor Journal: ACS Nano Date: 2014-08-26 Impact factor: 15.881
Authors: Mustafa Caglar; Inese Silkina; Bertram T Brown; Alice L Thorneywork; Oliver J Burton; Vitaliy Babenko; Stephen Matthew Gilbert; Alex Zettl; Stephan Hofmann; Ulrich F Keyser Journal: ACS Nano Date: 2020-01-08 Impact factor: 15.881