Gas transport through graphene-derived membranes has gained much interest recently due to its promising potential in filtration and separation applications. In this work, we explore Kr-85 gas radionuclide sequestration from natural air in nanoporous graphene oxide membranes in which different sizes and geometries of pores were modeled on the graphene oxide sheet. This was done using atomistic simulations considering mean-squared displacement, diffusion coefficient, number of crossed species of gases through nanoporous graphene oxide, and flow through interlayer galleries. The results showed that the gas features have the densest adsorbed zone in nanoporous graphene oxide, compared with a graphene membrane, and that graphene oxide was more favorable than graphene for Kr separation. The aim of this paper is to show that for the well-defined pore size called P-7, it is possible to separate Kr-85 from a gas mixture containing Kr-85, O
2
and N
2
. The results would benefit the oil industry among others.
1. Introduction
Kr-85 is a radioactive gas released to the atmosphere by nuclear explosions, nuclear power plants, volcanoes, and earthquakes. The major source of Kr-85 is nuclear fission in nuclear reactors and nuclear weapon tests. It is worth mentioning that, as a result of nuclear weapon tests from 1945 through 1962, an estimated 5 million curies of Kr-85 were released to the atmosphere. This radionuclide is odorless, colorless, and tasteless; and emits low levels of both gamma and beta radiation
[1]
. It is used in gas mixtures with argon or xenon to improve ionization in light bulbs by reducing their starting voltage. This radionuclide is also used in plasma displays, spark gaps, and leak detection. The most important concerns occur when a very small amount of Kr-85 is taken into the body, dissolved in the blood stream, and distributed to the organs and tissues throughout the whole body. The tissue most affected by beta particles emitted from Kr-85 radioactive decay, is the skin. Unfortunately, Kr-85 does not generally participate in any chemical separation processes due to its fully occupied electronic valance shell. Separation of such an important gas is an interesting subject for scientific investigation.
Separation of gas mixtures using nanoporous materials is an emerging field of research with great potential such as gas sensor and gas purification applications. The materials that are currently being investigated for these applications include zeolites
[2]
, silica
[3]
, carbon
[4]
, and polymers
[5]
. These membranes all have the key properties of chemical resistance and thermal stability. Graphene, an atomically thin single sheet of graphite comprising sp
2
-bonded carbon atoms arranged in a hexagonal lattice
[6], holds significant promise for gas
separation due to its unique properties. Pristine graphene has been shown to be impermeable to gases
[7]
. However, several studies have suggested that graphene has the potential to induce highly selective transport by generation of pore defects
[8
-
14]
, in which atoms can be removed from the graphene lattice to create pores of specific size and geometry.
Despite the simple architecture of such molecular sieves, the experimental set-up remains challenging. Drilling such delicate nanopores on single graphene sheets is one of the challenges in current research on molecular sieves, as is detection of single molecules (e.g., for DNA sequencing)
[15]
. For example, UV-induced oxidative etching
[16]
can create pores in micrometersized graphene membranes and the resulting membranes could be used as molecular sieves. Jiang et al.
[10]
designed two one-atom-thin porous membranes for gas separation by simulation and modeling, and computed diffusion barriers. They estimated H
2
/CH
4
selectivity on the order of 10
8
and 10
23
for the N-functionalized, and all-H pores, respectively. First principles molecular dynamics simulations indicate a high flux of H
2
through the N-functionalized pores in a graphene membrane, which is in accord with the relatively low H
2
diffusion barriers. Blankenburg et al.
[13]
proposed and characterized a one-atom-thick membrane for atmospheric gas separation. They performed simulation and modeling calculations for different atmospheric gas molecules entering the membrane pores. The determined separabilities for hydrogen and helium ranged from 10
3
up to 10
23
at room temperature, with a permeance greater than 10
−6
m
−2
s
−1
Pa
−1
, which is superior to those of classical membranes. They proposed that such membranes show high hydrogen and helium selectivity and could be useful for membranes in fuel cells or gas sensors, for separation of CO, CO
2
, or ammonia, as well as for extraction of helium.
After that; Koenig et al.
[17]
investigated the transport of a variety of gases (H
2
, CO
2
, Ar, N
2
, CH
4
, and SF
6
) through the pores and compared their results with those of Blankenburg et al.
[13]
and Jiang et al.
[10]
Koenig et al.
[17]
found a H
2
leakrate on the order of ~10
−20
mol s
−1
Pa
−1
for a H-passivated pore in graphene consisting of two missing benzene rings at room temperature. The similarity in the H
2
leakage reported in the previously mentioned work suggests a H
2
energy barrier to pore entry
Recent advances in molecular simulation make it possible to study these systems at atomic resolutions. Based on the aforementioned reasons, at the moment, we suppose that validating the results of such delicate simulations is impossible by experiment; however, we expect that our results might motivate experimental research to validate these results in the near future.
Graphene oxide (GO) is a chemically modified graphene with oxygen-containing functional groups (e.g., hydroxyl, carbonyl, epoxy, and carboxyl groups) on the graphene basal plane
[18]
. In recent years, it has become one of the most studied nanomaterials
[19
-
24]
. GO has a long history, dating back to at least 1859, when Brodie reported its synthesis
[19]
. Despite this history, the structure of GO is still under debate. GO based materials have generated incredible interest for energy-related applications because of its multifunctional flexibility
[25
,
26]
. Moreover, GO has recently been studied for various biological applications
[27]
, and has been applied in areas such as fabrication of intercalated GO composites
[28]
. Recent studies showed that successful separation of gas mixtures using GO-based membranes, represents remarkable potential of GO in the field of gas separation
[29
-
33]
. Considering the theoretical surface area of graphene (2630 m
2
/g)
[34]
and the hydrophilic surface of GO, it is expected to have huge space in which to store polar and hydrophilic gas molecules. This space could be used for storage and separation of hydrophilic gas. Despite the enormous potential for applications of GO, improvements in porosity and surface area are rarely found for gas separation applications. Separation processes based on membranes, depend on several properties, including pore size, stable structure, and appropriate permeability. The porosity and accessible surface area can easily be tuned for electrochemical, gas storage/separation, and catalytic ability by changing the spacing in the graphene layer, or by functionalizing with various chemical groups. For example Kim et al.
[31]
reported highly permeable and selective GO membranes for separating mixtures of gases of industrial relevance. They focused on the gas-transport properties of thin defective graphene and GO membranes, and reported that graphene itself displays outstanding gas separation properties. However, to the best of our knowledge, molecular sieving of radionuclide gas by nanoporous GO (NPGO) has never been reported. Demonstration of this capability is fundamental knowledge for further application of NPGO for gas separation. A popular structural model of GO, shown in
Fig. 1
, was proposed by Guo et al.
[35]
: an equilateral triangle formed by three C
8
O
2
(OH)
2
units. In this model the C
8
O
2
(OH)
2
units are homogeneously distributed on the carbon sheet. Each C
8
O
2
(OH)
2
unit contains two para-epoxy groups at opposite sides of the carbon plane, and two para-hydroxyl groups above the plane of the carbons.
Right side: cross-sectional view, left side: lateral view of graphene oxide. Colors assigned to each molecule: green (carbon); red (oxygen), white (hydrogen).
2. Simulation Details and Methods
Molecular permeation of three different gases (namely Kr-85, O
2
, and N
2
) through NPGO with different pore sizes was simulated based on a molecular dynamic approach. For simplicity, hereafter Kr is used to represent
85
Kr. All molecular dynamic simulations were performed using the large-scale atomic/molecular massively parallel simulator (LAMMPS) package
[36]
and structures were visualized using the visual molecular dynamics (VMD) package
[37]
. The all-atom optimized potentials for liquid simulations (OPLS-AA) was used for GO, which is able to capture essential many-body terms in inter-atomic interactions (i.e., bond stretching, bond angle bending, van der Waals, electrostatic interactions, and partial charges)
[38]
. All molecular dynamic simulations were performed in an NVT ensemble for 10 ns. The Nose-Hoover barostat and thermostat
[39]
were applied to maintain the pressure and temperature at 1 atm and 300 K, with damping coefficients 1 ps
−1
and 0.1 ps
−1
, respectively, and time steps of 0.5 fs were used during all molecular dynamic simulations. Energy minimization was performed to find the thermally stable morphology and to achieve a conformation with the minimum potential energy for all molecules. Non-bonded van-der-Waals interactions were modeled in terms of 12-6 Lennard-Jones famous potentials
[40]
with a cut-off distance of 1.2 nm, that is:
The parameters used for non-bond interactions are given in
Table 1
[41
,
42]
. The SHAKE algorithm was applied for the stretching terms between oxygen and hydrogen atoms of GO to reduce high-frequency vibrations that require shorter time steps
[43]
. The particle mesh Ewald (PME)
[44]
method with a 10.0 Å real-space cutoff, 1.5 Å reciprocal space gridding, and splines on the order of ‘4’ with a 10
-5
tolerance was implemented to compute the electrostatic interactions. A simulation box with the dimensions of 30 × 30 × 80 Å was constructed and a NPGO membrane was placed in the middle of the box at Cartesian coordinate origin (0, 0, 0) as the separator, dividing the simulation box with the height of 4 nm into two equal volume chambers, right and left chambers for all molecular dynamic simulation (
Fig. 2
). Initially, an equal number of 15 species of gases of Kr, O
2
and N
2
were loaded into the right chamber (see
Fig. 2
), while the other side (left chamber) was vacuum for all molecular dynamic simulations.
Parameters used for nonbonding interactions
Data are given from a)[42] and b)[41].
(a) Initial MD snapshot of the gases loaded into the right chamber and structures of the nanopores employed in the simulation, (b) P-5, (c) P-7, (d) P-10, (e) P-12. Colors assigned to each molecules/atoms: red (O2), yellow (Kr), blue (N2), green (C), and black (H).
To construct the NPGO membrane, four pores on the GO sheet were regarded as a unit cell, and the NPGO model had three C
8
O
2
(OH)2 units on the carbon plane, as can be seen in
Fig. 3
. Reflective boundary conditions were applied in the z-direction of the simulation box (normal to the graphene plane) while periodic boundary conditions were considered in the other two directions
[45]
. To avoid vertical displacement of the entire NPGO membrane, the NPGO was frozen during the simulation. Nanopores were created by selectively removing atoms from the GO sheet. Various sizes of pores were considered, which were called by the number of graphene ring units removed or partially opened (i.e., P-5 (P-5), P-7, P-10 and P-12; see
Fig. 2
). As shown in
Fig. 2b
-
e
, some carbon atoms of the single layer GO were arbitrarily removed to generate an axially symmetric shape of the nanopores. Some pores (P-7 and P-10) were fabricated by removing carbon atoms whose coordinates fulfilled the condition
, circle equation, where “r” is the radius of the pore. Moreover, x, and y are the Cartesian coordinates of atoms, with respect to the origin of the coordinate system. The other pores were constructed by removing carbon atoms to build the noted pore, without any specific equation. The fabrication procedure for all nanopores was conducted using the VMD package
[37]
.
The nanoporous graphene oxide (GO) model with three C8O2 (OH)2 units on the carbon plane. The blue dotted lines indicate the unit cell of the porous GO, and the red dotted lines show the equilateral triangle formed by three C8O2 (OH)2 units.
3. Results and Discussion
- 3.1. The mean-squared displacement analysis
The results of mean-squared displacement (MSD) calculations pertaining to the titled gases at P-5, P-7, and P-10 GO pore sizes are displayed in
Figs. 4
-
6
, respectively. As can be seen, none of the species of the gases could cross the NPGO membrane through P-5, because the size of these pores was smaller than the kinetic diameter of all species of gases (
Fig. 4
). Because the pore size was very small, three gases were confined to the right chamber. They have some non-zero value for MSD.
Calculated mean-squared displacement in relation to time for Kr, N2, and O2 in the P-5 graphene oxide membrane.
Calculated mean-squared displacement in relation to time for Kr, N2, and O2 in the P-7 graphene oxide membrane.
Calculated mean-squared displacement in relation to time for Kr, N2, and O2 in the P-10 graphene oxide membrane.
Fig. 5
shows the calculated MSD versus time in the P-7 GO membrane. As can be seen obviously in
Fig. 7
, only Kr could cross the nanoporous graphene membrane through P-7 due to a pore size adequate for the entry of Kr atoms. For NPGO with this pore size, it can be concluded that molecular sieving occurred and that Kr gas was separated selectively from the gas mixture, whereas the size and shape of the pores restricted the permeation of the nitrogen and oxygen molecules. The corresponding simulation snapshots of molecular sieving of Kr atoms are shown in
Fig. 7
.
Fig. 6
shows the calculated MSD versus time in a P-10 GO membrane. As expected, increasing the pore size to P-10, removed the restrictions and all the gases were able to pass through the graphene membrane.
Snapshot of the gases passing through P-7 nanoporous graphene oxide, colors assigned to each molecule/atom: red (O2), yellow (Kr), blue (N2), green (C), and black (H).
- 3.2. The comparison of diffusion coefficients
Using MD trajectories, the diffusion coefficients of Kr and di-atomic gases through the various rings of the NPGO membrane could be calculated from the limiting slope of the MSD curve against time using the Einstein relation
[46]
. This equation relates the long-time (t) limit of MSD of the particles to diffusivity, D, through
Where
M
SD
(
t
) = <|
ri
(
t
) −
ri
(0)
2
|>. In this equation, the angular brackets indicate an ensemble average over atoms in the system and over time origins, and
ri
is the center of the mass coordinates of NPGO. Diffusion coefficients (Å
2
/ps) for titled gases can be calculated using MSD versus time graphs. These quantities are summarized in
Table 2
. The results showed that: 1) no gases passed through the NPGO membrane with P-5, which was in contrast to the case of P-10, 2) P-7 was preferable to P-10 for separation of Kr. These values indicate that P-7 GO membranes are good candidates for the selective separation of Kr from other air components.
Calculated coefficient diffusions for Kr, N2and O2at various pore sizes
Calculated coefficient diffusions for Kr, N2 and O2 at various pore sizes
- 3.3. Number of species of gases passed through the NPGO membrane
To find the effect of the pore size on the number of gas species passing through the NPGO membrane, the number of gases passing the NPGO membrane was calculated.
Fig. 8
shows the total number of gases crossed, versus time, for Kr, N
2
, and O
2
through a P-5 NPGO membrane.
Total number of gases crossed through the nanoporous graphene oxide membrane in relation to time for Kr, N2, and O2 in the P-5 membrane.
Graphene is an excellent starting point for developing size selective membranes
[47]
because of its atomic thickness and impermeability to all gases
[48
,
49]
. However, this means that pores that can exclude larger molecules, but allow smaller molecules to pass through, have to be introduced into the material. In
Fig. 8
, the size of the pores is much smaller than the molecular size of all the investigated gases. Therefore, none of the species of gases could cross the P-5 NPGO membrane, and both the fluctuations and the value of graphs are zero.
When the pore size was increased to P-7, O
2
and N
2
molecules could not cross the membrane.
Fig. 9
shows the total numbers of crossed gases versus time for Kr, N
2
, and O
2
for P-7 NPGO.
Fig. 10
shows the typical trajectory of gas separation; and finally, molecular sieving of Kr occurred for P-7 NPGO during 10 000 ps of simulation time.
Fig. 11
shows the total number of crossed gases versus time for Kr, N
2
and O
2
in the P-10 NPGO. For pores at the size of P-10, all three gases could cross the NPGO membrane; whereas, P-7 only allowed Kr atoms to permeate. In the case of O
2
and N
2
, the restriction of the molecular orientation largely prohibited permeation. When nitrogen and oxygen molecules were not blocked by the size of the pores (i.e., P-10), more oxygen molecules passed through the NPGO membrane than nitrogen molecules. This might be related to a lower potential barrier of permeation for oxygen molecules. Permeation events were calculated in
Table 3
.
Total number of gases crossed through nanoporous graphene oxide membrane in relation to time for Kr, N2, and O2 in the P-7 membrane.
Typical trajectory of gas separation with final molecular sieving of Kr for the P-7 nanoporous graphene oxide, during 10 000 ps of simulation time.
Total number of gases crossed through the nanoporous graphene oxide membrane in relation to time for Kr, N2, and O2 in the P-10 membrane.
Pore size, pore area, and number of gases passing through NPGO
NPGO: nanoporous graphene oxide.
As shown in
Table 3
, no gas was observed to permeate through P-5 during 10 ns simulation, while Kr atoms of P-7 went through the pores. This issue was completely due to the pore size restriction as P-7 pores were too small for nitrogen and oxygen to get through, but large enough for Kr. In this way, Kr atoms can be completely separated from nitrogen and oxygen molecules by P-7 NPGO. For pore size P-10, during 10 ns of simulation, thirteen Kr atoms passed through pores, while the corresponding number of oxygen and nitrogen molecules was five and three, respectively. For pore size P-12, more nitrogen and oxygen molecules, and fewer Kr molecules, permeated than with P-10. Moreover, the number of oxygen molecules permeating the P-12 membrane increased and exceeded that of nitrogen molecules. For pore size P-12, still more oxygen molecules permeated the membrane than did nitrogen. Also, the configurations of oxygen and nitrogen molecules placed at the center of the pore were different. The permeation ratio, defined as the ratio of the numbers of permeation events of the two types of gas molecules, could be used to describe the selectivity of the membrane. Here, the permeation ratio is reported as Kr/O
2
and Kr/N
2
permeations. A higher permeation ratio means better selectivity of the NPGO membrane. If the permeation ratio is equal to one, there is no selectivity. Maximum Kr/O
2
and Kr/N
2
permeation ratios were observed for P-7 membranes. The Kr/O
2
and Kr/N
2
ratios decreased as the pore size increased, until P-12.
Fig. 12
shows proportional selectivity of Kr from the gas mixture. As
Fig. 12
shows, when the well-defined pore size P-7 was selected, Kr yield and selectivity were remarkable (to the maximum of 100%). With larger pore sizes, Kr yield and selectivity decreased according to pore size such that for P-10 and P-12, with pore area of 46.84 and 56.20 (Å
2
), the Kr yield and selectivity were 62% and 43%, respectively.
Proportional selectivity of Kr from the gas mixture.
Preliminary results indicate an additional approach might further increase Kr gas separation.
Fig. 12
indicates that there is discrimination between Kr gas and the O
2
/N
2
mixture, as applied gases which contribute to higher separation selectivity in P-7. It is concluded that more carefully defined pore size could intensify separation of Kr gas from the mixture. Thus the proper pore size actually plays a key role in the enhancement of selectivity for Kr.
- 3.4. Calculating the flow of gases
The flow is used to characterize the membrane permeability quantitatively, and is defined as:
Where N is the moles of gases that permeated through the NPGO membrane, S refers to the total area of the nanoporous membrane, and T is the time. The flow of Kr, O
2
, and N
2
was calculated for the various pore-size models, as shown in
Fig. 13
. There was a prodigious increase in the flow of Kr atoms near the pore size of P-7, where restrictions related to the size and shape of the pores to Kr permeation began to vanish. At larger pore sizes, the flow of Kr atoms became reduced. In the case of the nitrogen and oxygen molecules, flow increased as the pore area increased.
Flow of gases passing through the nanoporous graphene oxide membranes for pores of different area.
- 3.5. Van der Waals interaction
The van der Waals interactions between gas molecules and the atoms at the edges of pores in the NPGO membrane were also calculated, and are shown in
Fig. 14
. As shown there, the VDW energy between the Kr gases and edge atoms of the P-7 NPGO was more negative than for oxygen and nitrogen. This caused transit of Kr gases through the NPGO membrane, which resulted in more Kr-permeation events than for oxygen and nitrogen.
VDW energy between the gas species and edge atoms of P-7 pores in nanoporous graphene oxide membranes.
- 3.6. Compare porous graphene and GO nanopores
Results of simulation showed that N
2
gas is strongly adsorbed onto NPGO, thus forming an adsorbed layer that can contribute to comparison of graphene and GO membranes.
Fig. 15
shows schematic adsorption onto the NPGO surface as a function of the distance from the membrane GO nanopore (z = 0). Nitrogen features strong adsorption layers, while oxygen and krypton are significantly less attracted by the NPGO membrane. In order to analyze the relative contribution of the bulk (gas phase) and adsorbed layer to compare graphene and NPGO membranes, we divided each chamber into two different zones along the z-direction, namely the adsorption and the bulk zone (gas phase). We defined the adsorption zones as the regions 2 Å < |z| < 7 Å and the bulk zones as the regions 7 Å < |z| < 40 Å, as shown in
Fig. 15
. To compare graphene and GO membranes, the probability density of finding molecules of each of the gases involved in this study, was calculated as a function of the distance from the membrane.
Schematic adsorption onto the graphene oxide surface as a function of the distance from the membrane graphene oxide nanopore (z = 0).
Regarding the placement of C
8
O
2
(OH)
2
on the graphene sheet; two C
8
O
2
(OH)
2
molecules are close to two pores while the other C
8
O
2
(OH)
2
is in the middle of the other two pores. Thus, two pores are influenced by C
8
O
2
(OH)
2
while the other two pores are without such influence. As a whole, the results showed that the gas features involved in this study have the densest adsorbed zone in NPGO, compare with a graphene membrane. The adsorbed zone is defined as the number of gas particles divided by the volume of the simulation box. The gas density was calculated by considering only the particles in the adsorption zone (2 Å < |z| < 7 Å) and the volume available to them. The probability density by simulation was 1.6%, 14.4%, and 18.2% (for, Kr, O
2
, and N
2
respectively for graphene); and 2.1%, 27.4%, and 39.5% (for Kr, O
2
, and N
2
respectively for GO). This means that more molecules cross through NPGO than through porous graphene.
4. Conclusions
Using simulations of molecular dynamics, we showed that NPGO membranes could be applied to separate Kr-85 gas radio-nuclides from natural air. The results of the simulation showed that separation of Kr-85 from air could best be achieved using pore size P-7, which was barely larger than the Kr-85 gas radio-nuclides, and was smaller than the nitrogen and oxygen molecules. Thus P-7 pores were too small for nitrogen and oxygen molecules to get through, but large enough for Kr-85 to permeate. In this way, Kr-85 gas radionuclides could be completely separated from nitrogen and oxygen molecules by P-7 NPGO membranes. When the pore size was P-10, thirteen Kr-85 molecules permeated through the pores during 10 ns simulation and the corresponding numbers of oxygen and nitrogen molecules were five and three, respectively. When the pore size was P-12, nitrogen and oxygen molecules permeated the nanoporous graphene. When nitrogen and oxygen molecules were not blocked by the pores (i.e., for P-10 or larger), there were more oxygen molecules permeating through the NPGO membrane than nitrogen molecules.
Cimbák Š
,
Povinec P
1985
85Kr atmospheric concentration in Bratislava from 1980 to 1983
Environ Int
http://dx.doi.org/10.1016/0160-4120(85)90103-5
11
65 -
DOI : 10.1016/0160-4120(85)90103-5
Yu M
,
Noble RD
,
Falconer JL
2011
Zeolite membranes: microstructure characterization and permeation mechanisms
Acc Chem Res
http://dx.doi.org/10.1021/ar200083e
44
1196 -
DOI : 10.1021/ar200083e
De Vos RM
,
Verweij H
1998
High-Selectivity, High-flux silica membranes for gas separation
Science
http://dx.doi.org/10.1126/science.279.5357.1710
279
1710 -
DOI : 10.1126/science.279.5357.1710
Shiflett MB
,
Foley HC
1999
Ultrasonic deposition of high-selectivity nanoporous carbon membranes
Science
http://dx.doi.org/10.1126/science.285.5435.1902
285
1902 -
DOI : 10.1126/science.285.5435.1902
Park HB
,
Jung CH
,
Lee YM
,
Hill AJ
,
Pas SJ
,
Mudie ST
,
Van Wagner E
,
Freeman BD
,
Cookson DJ
2007
Polymers with cavities tuned for fast selective transport of small molecules and ions
Science
http://dx.doi.org/10.1126/science.1146744
318
254 -
DOI : 10.1126/science.1146744
Novoselov KS
,
Geim AK
,
Morozov SV
,
Jiang D
,
Zhang Y
,
Dubonos SV
,
Grigorieva IV
,
Firsov AA
2004
Electric field effect in atomically thin carbon films
Science
http://dx.doi.org/10.1126/science.1102896
306
666 -
DOI : 10.1126/science.1102896
Bunch JS
,
Verbridge SS
,
Alden JS
,
van der Zande AM
,
Parpia JM
,
Craighead HG
,
McEuen PL
2008
Impermeable atomic membranes from graphene sheets
Nano Lett
http://dx.doi.org/10.1021/nl801457b
8
2458 -
DOI : 10.1021/nl801457b
Schrier J
2010
Helium separation using porous graphene membranes
J Phys Chem Lett
http://dx.doi.org/10.1021/jz100748x
1
2284 -
DOI : 10.1021/jz100748x
Du H
,
Li J
,
Zhang J
,
Su G
,
Li X
,
Zhao Y
2011
Separation of hydrogen and nitrogen gases with porous graphene membrane
J Phys Chem C
http://dx.doi.org/10.1021/jp206258u
115
23261 -
DOI : 10.1021/jp206258u
Jiang D
,
Cooper VR
,
Dai S
2009
Porous graphene as the ultimate membrane for gas separation
Nano Lett
http://dx.doi.org/10.1021/nl9021946
9
4019 -
DOI : 10.1021/nl9021946
Tao Y
,
Xue Q
,
Liu Z
,
Shan M
,
Ling C
,
Wu T
,
Li X
2014
Tunable hydrogen separation in porous graphene membrane: first-principle and molecular dynamic simulation
ACS Appl Mater Interfaces
http://dx.doi.org/10.1021/am4058887
6
8048 -
DOI : 10.1021/am4058887
Lei G
,
Liu C
,
Xie H
,
Song F
2014
Separation of the hydrogen sulfide and methane mixture by the porous graphene membrane: effect of the charges
Chem Phys Lett
http://dx.doi.org/10.1016/j.cplett.2014.03.040
599
127 -
DOI : 10.1016/j.cplett.2014.03.040
Blankenburg S
,
Bieri M
,
Fasel R
,
Müllen K
,
Pignedoli CA
,
Passerone D
2010
Porous graphene as an atmospheric nanofilter
Small
http://dx.doi.org/10.1002/smll.201001126
6
2266 -
DOI : 10.1002/smll.201001126
Sun C
,
Boutilier MSH
,
Au H
,
Poesio P
,
Bai B
,
Karnik R
,
Hadjiconstantinou NG
2014
Mechanisms of molecular permeation through nanoporous graphene membranes
Langmuir
http://dx.doi.org/10.1021/la403969g
30
675 -
DOI : 10.1021/la403969g
Freedman KJ
,
Ahn CW
,
Kim MJ
2013
Detection of long and short DNA using nanopores with graphitic polyhedral edges
ACS Nano
http://dx.doi.org/10.1021/nn4003665
7
5008 -
DOI : 10.1021/nn4003665
Huh S
,
Park J
,
Kim YS
,
Kim KS
,
Hong BH
,
Nam JM
2011
UV/ozoneoxidized large-scale graphene platform with large chemical enhancement in surface-enhanced Raman scattering
ACS Nano
http://dx.doi.org/10.1021/nn204156n
5
9799 -
DOI : 10.1021/nn204156n
Koenig SP
,
Wang L
,
Pellegrino J
,
Bunch JS
2012
Selective molecular sieving through porous graphene
Nat Nanotechnol
http://dx.doi.org/10.1038/nnano.2012.162
7
728 -
DOI : 10.1038/nnano.2012.162
Bagri A
,
Mattevi C
,
Acik M
,
Chabal YJ
,
Chhowalla M
,
Shenoy VB
2010
Structural evolution during the reduction of chemically derived graphene oxide
Nat Chem
http://dx.doi.org/10.1038/nchem.686
2
581 -
DOI : 10.1038/nchem.686
Dreyer DR
,
Park S
,
Bielawski CW
,
Ruoff RS
2010
The chemistry of graphene oxide
Chem Soc Rev
http://dx.doi.org/10.1039/B917103G
39
228 -
DOI : 10.1039/B917103G
Kim JE
,
Han TH
,
Lee SH
,
Kim JY
,
Ahn CW
,
Yun JM
,
Kim SO
2011
Graphene oxide liquid crystals
Angew Chem Int Ed
http://dx.doi.org/10.1002/anie.201004692
50
3043 -
DOI : 10.1002/anie.201004692
Chen D
,
Feng H
,
Li J
2012
Graphene oxide: preparation, functionalization, and electrochemical applications
Chem Rev
http://dx.doi.org/10.1021/cr300115g
112
6027 -
DOI : 10.1021/cr300115g
Zhu Y
,
James DK
,
Tour JM
2012
New routes to graphene, graphene oxide and their related applications
Adv Mater
http://dx.doi.org/10.1002/adma.201202321
24
4924 -
DOI : 10.1002/adma.201202321
Kuila T
,
Mishra AK
,
Khanra P
,
Kim NH
,
Lee JH
2013
Recent advances in the efficient reduction of graphene oxide and its application as energy storage electrode materials
Nanoscale
http://dx.doi.org/10.1039/c2nr32703a
5
52 -
DOI : 10.1039/C2NR32703A
Smith SC
,
Ahmed F
,
Gutierrez KM
,
Frigi Rodrigues D
2014
A comparative study of lysozyme adsorption with graphene, graphene oxide, and single-walled carbon nanotubes: potential environmental applications
Chem Eng J
http://dx.doi.org/10.1016/j.cej.2013.11.030
240
147 -
DOI : 10.1016/j.cej.2013.11.030
Dreyer DR
,
Jia HP
,
Bielawski CW
2010
Graphene oxide: a convenient carbocatalyst for facilitating oxidation and hydration reactions
Angew Chem Int Ed
http://dx.doi.org/10.1002/anie.201002160
49
6813 -
DOI : 10.1002/anie.201002160
Burress JW
,
Gadipelli S
,
Ford J
,
Simmons JM
,
Zhou W
,
Yildirim T
2010
Graphene oxide framework materials: theoretical predictions and experimental results
Angew Chem Int Ed
http://dx.doi.org/10.1002/anie.201003328
49
8902 -
DOI : 10.1002/anie.201003328
Chung C
,
Kim YK
,
Shin D
,
Ryoo SR
,
Hong BH
,
Min DH
2013
Biomedical applications of graphene and graphene oxide
Acc Chem Res
http://dx.doi.org/10.1021/ar300159f
46
2211 -
DOI : 10.1021/ar300159f
Diggikar RS
,
Late DJ
,
Kale BB
2014
Unusual morphologies of reduced graphene oxide and polyaniline nanofibers-reduced graphene oxide composites for high performance supercapacitor applications
RSC Adv
http://dx.doi.org/10.1039/C3RA47834C
4
22551 -
DOI : 10.1039/c3ra47834c
Mi B
2014
Graphene oxide membranes for ionic and molecular sieving
Science
http://dx.doi.org/10.1126/science.1250247
343
740 -
DOI : 10.1126/science.1250247
Joshi RK
,
Carbone P
,
Wang FC
,
Kravets VG
,
Su Y
,
Grigorieva IV
,
Wu HA
,
Geim AK
,
Nair RR
2014
Precise and ultrafast molecular sieving through graphene oxide membranes
Science
http://dx.doi.org/10.1126/science.1245711
343
752 -
DOI : 10.1126/science.1245711
Kim HW
,
Yoon HW
,
Yoon SM
,
Yoo BM
,
Ahn BK
,
Cho YH
,
Shin HJ
,
Yang H
,
Paik U
,
Kwon S
,
Choi JY
,
Park HB
2013
Selective gas transport through few-layered graphene and graphene oxide membranes
Science
http://dx.doi.org/10.1126/science.1236098
342
91 -
DOI : 10.1126/science.1236098
Li H
,
Song Z
,
Zhang X
,
Huang Y
,
Li S
,
Mao Y
,
Ploehn HJ
,
Bao Y
,
Yu M
2013
Ultrathin, molecular-sieving graphene oxide membranes for selective hydrogen separation
Science
http://dx.doi.org/10.1126/science.1236686
342
95 -
DOI : 10.1126/science.1236686
Nair RR
,
Wu HA
,
Jayaram PN
,
Grigorieva IV
,
Geim AK
2012
Unimpeded permeation of water through helium-leak–tight graphene-based membranes
Science
http://dx.doi.org/10.1126/science.1211694
335
442 -
DOI : 10.1126/science.1211694
Peigney A
,
Laurent C
,
Flahaut E
,
Bacsa RR
,
Rousset A
2001
Specific surface area of carbon nanotubes and bundles of carbon nano-tubes
Carbon
http://dx.doi.org/10.1016/S0008-6223(00)00155-X
39
507 -
DOI : 10.1016/S0008-6223(00)00155-X
Guo YN
,
Lu X
,
Weng J
,
Leng Y
2013
Density functional theory study of the interaction of arginine-glycine-aspartic acid with graphene, defective graphene, and graphene oxide
J Phys Chem C
http://dx.doi.org/10.1021/jp310088e
117
5708 -
DOI : 10.1021/jp310088e
Plimpton S
1995
Fast parallel algorithms for short-range molecular dynamics
J Comput Phys
http://dx.doi.org/10.1006/ jcph.1995.1039
117
1 -
DOI : 10.1006/jcph.1995.1039
Shih CJ
,
Lin S
,
Sharma R
,
Strano MS
,
Blankschtein D
2012
Understanding the pH-dependent behavior of graphene oxide aqueous solutions: a comparative experimental and molecular dynamics simulation study
Langmuir
http://dx.doi.org/10.1021/la203607w
28
235 -
DOI : 10.1021/la203607w
Hoover WG
1985
Canonical dynamics: equilibrium phase-space distributions
Phys Rev A
http://dx.doi.org/10.1103/PhysRevA.31.1695
31
1695 -
DOI : 10.1103/PhysRevA.31.1695
Cervellera VR
,
Albertí M
,
Huarte-larrañaga F
2008
A molecular dynamics simulation of air adsorption in single-walled carbon nanotube bundles
Int J Quantum Chem
http://dx.doi.org/10.1002/qua.21590
108
1714 -
DOI : 10.1002/qua.21590
Foroutan M
,
Taghavi Nasrabadi A
2011
Adsorption and separation of binary mixtures of noble gases on single-walled carbon nanotube bundles
Physica E
http://dx.doi.org/10.1016/j.physe.2010.10.011
43
851 -
DOI : 10.1016/j.physe.2010.10.011
Darden T
,
York D
,
Pedersen L
1993
Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems
J Chem Phys
http://dx.doi.org/10.1063/1.464397
98
10089 -
DOI : 10.1063/1.464397
Wang JC
,
Fichthorn KA
2000
A method for molecular dynamics simulation of confined fluids
J Chem Phys
http://dx.doi.org/10.1063/1.481430
112
8252 -
DOI : 10.1063/1.481430
Arora G
,
Wagner NJ
,
Sandler SI
2004
Adsorption and diffusion of molecular nitrogen in single wall carbon nanotubes
Langmuir
http://dx.doi.org/10.1021/la036432f
20
6268 -
DOI : 10.1021/la036432f
Suk ME
,
Aluru NR
2010
Water transport through ultrathin graphene
J Phys Chem Lett
http://dx.doi.org/10.1021/jz100240r
1
1590 -
DOI : 10.1021/jz100240r
Schrier J
,
McClain J
2012
Thermally-driven isotope separation across nanoporous graphene
Chem Phys Lett
http://dx.doi.org/10.1016/j.cplett.2011.11.069
521
118 -
DOI : 10.1016/j.cplett.2011.11.069
Li Y
,
Zhou Z
,
Shen P
,
Chen Z
2010
Two-dimensional polyphenylene: experimentally available porous graphene as a hydrogen purification membrane
Chem Commun
http://dx.doi.org/10.1039/B926313F
46
3672 -
DOI : 10.1039/b926313f