Scalable Graphene-Based Membranes for Ionic Sieving with Ultrahigh

Subscriber access provided by UNIV OF CALIFORNIA SAN DIEGO LIBRARIES

Communication

Scalable Graphene-based Membranes for Ionic Sieving with Ultrahigh Charge Selectivity

Nano Letters is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.


Seunghyun Hong, Charlotte Constans, Marcos Vinicius Surmani Martins, Yong Chin Seow, Juan Alfredo Guevara Carrió, and Slaven Garaj Nano Lett., Just Accepted Manuscript • DOI: 10.1021/ acs.nanolett.6b03837 • Publication Date (Web): 22 Dec 2016 Downloaded from http://pubs.acs.org on December 26, 2016



Just Accepted

“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They a online prior to technical editing, formatting for publication and author proofing. The American Society provides “Just Accepted” as a free service to the research community to exp



dissemination of scientific material as soon as possible after acceptance. “Just Accepted” ma appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts h fully peer reviewed, but should not be considered the official version of record. They are acces readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional servi to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be



in the journal. After a manuscript is technically edited and formatted, it will be removed from Accepted” Web site and published as an ASAP article. Note that technical editing may introd changes to the manuscript text and/or graphics which could affect content, and all legal d and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible or consequences arising from the use of information contained in these “Just Accepted” ma


Ag/AgCl

1 C 2PDMS 3 4 5 6PDMS C 7 8 9b ClK+ Chigh 10 11 12 Clow 13 ~ (P P ) ∆c diffusion I diff + 14 15 16 17 18 19 20

A

Nano Oxide Lettersd Graphene

V

60

FeCl3

40 1μm

high

GO Si

1μm

low

c

Nanopore array

K

+

Cl-

Vhigh Vlow

Ionic current (nA)

a Page 1 of 16

MgCl2

20 0

KCl

-20 -40 -60

-40

drift Idrift ~ (P+ + P- ) ∆V

ACS Paragon Plus Environment

0

40

80

Applied voltage (mV)

120

Nano Letters

10

K+

c

GO nanosheet

Charged functional groups

Na+ Li+

10

Ca2+ Cl-

Cu2+

d

Fe3+

Cd2+

-6

10

100

In3+ Al3+

10

-7

10

3.0

3.5

4.0

RH (Å)

4.5

-

Hydration shell

Mg2+

Ba2+

-5

-

-

ion

5.0


p (mol∙cm-2h-1)

Rb+

-4

b

S+ (%)

p (mol∙cm-2h-1)

1 2 3 4a 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

Page 2 of 16

10 10

-4

-5

1

2

3

Cation valence

3.0

Nano Letters

2.5

p (10-6 mol∙cm-2h-1)

G0 (10-13 S)

2.7 2.0 1 0 4.0 2 1.5 -20 5.4 3 9.9 1.0 4 -40 5 0.5 11.3 6 -60 7 -100 -50 0 50 100 2 4 6 8 10 12 8 Applied voltage (mV) pH e d9 100 30 10 11 12 10 20 13 K+ 14 1 15 10 16 Cl 17 0.1 0 18 -1 -2 0 -4 -3 5 19 10 10 10 10 10 10 10 2 10 1 20 Feed molarity (M) Molarity (M) 21 22 23 24 25 26 27 28 29 30 31 32 ACS Paragon Plus Environment 33 34 35

c

60

p (10- 6 mol∙cm-2h-1)

Ionic current (nA)

20

b

K+

50 40 30

Cl -

20 10 2

f

4

6

pH

8

10

100

S+ (%)

40

Page 3 of 16

G0 (10-13 S)

a

90

80 10-2

10-1

Feed molarity (M)

12

Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

Scalable Graphene-based Membranes for Ionic

2

Sieving with Ultrahigh Charge Selectivity

3

Seunghyun Hong1, Charlotte Constans1,2,, Marcos Vinicius Surmani Martins1,3, Yong Chin Seow1, Juan

4

Alfredo Guevara Carrió1,4, and Slaven Garaj1,2,5,6 *

Page 4 of 16

5 6 7 8 9 10 11 12

1

13

Nanostructured graphene-oxide (GO) laminate membranes, exhibiting ultra-high water flux, are excellent

14

candidates for next generation nanofiltration and desalination membranes, provided the ionic rejection could be

15

further increased without compromising the water flux. Using microscopic drift-diffusion experiments, we

16

demonstrated the ultra-high charge selectivity for GO membranes, with more than order of magnitude

17

difference in the permeabilities of cationic and anionic species of equivalent hydration radii. Measuring diffusion

18

of a wide range of ions of different size and charge, we were able to clearly disentangle different physical

19

mechanism contributing to the ionic sieving in GO membranes – electrostatic repulsion between ions and

20

charged chemical groups; and the compression of the ionic hydration shell within the membrane’s nanochannels,

21

following the activated behavior. The charge-selectivity allows us to rationally design membranes with

22

increased ionic rejection, and opens up the field of ion exchange and electrodialysis to the GO membranes.

23

24

KEYWORDS Graphene Oxide Membranes, Ionic Permeability, Surface Charges, Ion Exchange, Ionic Sieving

25

26

27

28

Centre for Advanced 2D Materials, National University of Singapore, Singapore 117542 Department of Physics, National University of Singapore, Singapore 117551 3 Department of Materials Science and Engineering, National University of Singapore, Singapore 117575 4 Mackgraphe - Graphene and Nano-Material Research Center, Engineering School, Presbyterian University Mackenzie, Brazil 01397-001 5 NUS Nanoscience & Nanotechnology Institute, National University of Singapore, Singapore 117581 6 Department of Biomedical Engineering, National University of Singapore, Singapore 117583 2

1


Page 5 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

Nano Letters

1, 2

2-8

Graphene-based membranes with ultra-high water flux and ionic sieving properties attracted recently 9, 10

2

significant attention, as a severe strain on the fresh water supply

3

new materials for water purification and desalination. Nanostructured graphene-oxide (GO) membranes

4

– scalable, inexpensive, thermally and chemically robust, and integratable with current technologies

5

particularly enticing candidates for the next-generation, high-performance separation membranes

6

GO membranes consist of stacked layers of impermeable graphene sheets, 𝐿 = 1 − 10 µm in size, spaced by

7

𝑑 = 0.9 − 1.2 nm via functionalized, mostly oxygen-carrying groups

8

into nanoscale domains, delimiting a percolative network of pristine graphene channels, which could

9

accommodate a few layers of water exhibiting frictionless flow

precipitated a strong research interest in

3, 13

1, 3, 11-13

14-18

– are

10, 19-21

. The

. The chemical groups are coalesced

1, 22

. Previous experiments

3, 15, 16, 23-25

, measuring

10

salt diffusion through centimeter-scale membranes over a period of hours, showed no permeation for ions

11

with hydration rates above size cut-off of 𝑅/ ≈ 4.5 Å and mostly unvarying permeation rate for smaller ions.

12

Those experiments, due to their nature, are ineffective in disentangling all the physical mechanisms

13

contributing to the permeability, are unable to distinguish permeability of different constituting ions in the salt,

14

and could be prone to artifacts due to external defects and tears over larger areas of the membrane. To

15

understand intrinsic membrane properties, we implemented a highly sensitive drift-diffusion technique,

16

revealing ultra-high charge-selectivity of the GO membranes.

17

We measured the ionic permeability of a 3 µm thick GO membrane, mounted across an array of

18

200×200 nm5 apertures in a 300 nm thick, free-standing, insulating SiNX layer on a Si substrate chip (Figure

19

1a). By limiting the exposed membrane area to ~5 µm5 and keeping it relatively thick, we ensured there are

20

no unintended cracks and defects that would skew the results . The GO membrane and its constituting GO

21

crystallites were extensively characterized using atomic force microscopy, X-ray diffraction, Fourier transform

22

infrared spectroscopy, etc. (see Supporting Information). The membrane chip was inserted in a custom-build

23

fluidic cell, so that it separated two compartments, each subsequently filled with ionic solutions electrically

24

contacted with Ag/AgCl electrodes. The electrodes were connected to a sensitive patch-clamp amplifier

25

(Axopatch 200B), sourcing voltage at a sweep rate of 5 mV/5 s (step function) across the membrane and

26

measuring ionic currents with 10 pA precision (no hysteresis was observed for such low rates). The

27

polydimethylsiloxane (PDMS) gasket seal precluded ionic solution from leaking around the edges of the

3

2


Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

Page 6 of 16

membrane.

2

To discern the separate permeabilities of cations (𝑃8 ) and anions (𝑃; ) in the salt, we implemented the

3

drift-diffusion technique to measure ionic currents driven by both the voltage and the concentration gradient

4

(Figure 1b). The fluidic compartments were filled with different concentrations of a salt, and we could measure

5

diffusive current across the membrane for zero applied voltage 𝐼diff ~ 𝑃8 − 𝑃; ∙ Δ𝑐. As we applied a voltage

6

difference ∆𝑉 across the membrane, the added electrophoretic component to the overall current is

7

𝐼drift ~ 𝑃8 + 𝑃; ∙ Δ𝑉 (Figure 1c). Measuring the two current components, we could deduce both 𝑃8 and 𝑃;

8

permeabilities. Figure 1d shows representative current-voltage ( 𝐼 − 𝑉 ) curves, measured at a fixed

9

concentration gradient: the slope of the curve is indicative of 𝐼drift ; whereas membrane potential 𝑉m = 𝑉(𝐼 =

10

0) is indicative of 𝐼diff . More precisely, we extract the individual permeabilities by modeling the total current

11

density 𝐽 ∆𝑐, ∆𝑉 across the membrane using the equation:

26

12

𝐽=

J

𝑃J 𝑧J5

𝑧J 𝐹 ∙ Δ𝑉 𝐹 5 ∙ Δ𝑉 𝑋 f − 𝑋 p exp 𝑅𝑇 ∙ ∙ 𝑧J 𝐹 ∙ Δ𝑉 𝑅𝑇 1 − exp 𝑅𝑇

13

For each ionic species X in the solution, 𝑃J is membrane permeability, 𝑧J is the valence, and 𝑋 R and 𝑋 S

14

are the ionic concentrations in the feed and permeate chambers, respectively. Potential across the membrane

15

∆V was adjusted for the electrodes’ redox potential; R is the universal gas constant; F is Faraday’s constant;

16

and T is the temperature. For details on the model and the method, see Supporting Information.

17

To elucidate the ionic selectivity of the GO membranes, we investigated the permeability of a wide

18

selection of aqueous salt ions, with varying ionic charges and spanning a wide range of effective hydrated ionic

19

volumes. Figure 2a depicts the permeation rates (p) of different cations (circle) and their corresponding Cl

20

counter ions (squares) as a function of the cation’s hydration radii

21

cation permeability decreases exponentially with increased hydration radius, followed by the sharp cutoff at

22

𝑅H ≈ 4.6 Å; and (b) permeability of the negatively charged Cl ion is suppressed by an order of magnitude

23

compared to the positive K and Rb ions, despite all those ions having very similar hydration volumes. We

24

conclude that the two dominant mechanisms for the ion rejection in GO membranes are size exclusion due to

25

compression of the ionic hydration shell in narrow channels

-

27, 28

. Two general trends are revealed: (a)

-

+

+

8, 29

, and electrostatic repulsion due to membrane

3


Page 7 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

3, 15, 16, 23-25

1

surface charge (Figure 2b,c). The earlier diffusion experiments

2

of all the salt ions, which is determined by the value for the least permeable species in a salt – for monovalent

3

salts they were actually measuring permeability of the chlorine counter-ion, not cations. This led to apparent

4

size-independent permeability for ions with hydration radii below the cut-off size defined by the channel

5

height (implying rigid hydration shells around ions). Instead, by properly separating cations and anions, we

6

observe the exponential dependence of the permeability on an ion’s hydration radius, consistent with the

7

compressible hydration shell model, where coordinated water molecules could rearrange or detach

8

themselves to allow passage of the hydrated ion through a narrow channel

measured the combined permeability

8, 29

.

9

We postulate that the high charge selectivity of the GO membranes is a result of the negatively charged

10

nanochannels in a GO membrane, due to the protonable oxygen groups. This leads to the expulsion of the

11

negatively charged Cl ions from nanochannels, and suppression of the anionic permeability, as predicted by

12

the electric double layer (EDL) model . Permeability of Cl ions in monovalent salts remained independent of

13

counterions (Rb , K , Na , Li ); and the cation selectivity 𝑆8 = 𝑃8

14

(Figure 2d). Interestingly, the EDL model breaks down in the case of chloride salts with divalent and trivalent

15

cations, and P(Cl ) reverts to the value predicted for uncharged channels (Figure 2a,d). We attribute this effect

16

to correlation-induced charge inversion , where multivalent ions overcompensate monovalent surface groups,

17

leading to a sharp drop, or even an inversion, of the effective surface charge. A similar effect has been

18

observed previously in highly charged protein channels

19

channels .

-

27

+

+

+

-

+

𝑃8 + 𝑃; reached values in excess of 95%

-

30

31-33

, such as bacterial porin OmpF, and in narrow silica

34

20

To further investigate the ionic selectivity of GO membranes, we performed a series of drift-diffusion and

21

ionic conductivity measurements using KCl aqueous solutions for a range of pH and molarity values. Figure 3a

22

shows current-voltage (I-V) curves at same salt concentration on both sides, 𝑐KCl = 10 mM, measured for

23

different pH values (see also Figure S3a). At this low molarity, nonlinear nature of the I-V curves at larger

24

voltages is likely due to overlimiting currents driven by the concentration polarization at the surface of the

25

membrane . The ionic conductance of the membrane was calculated from the slopes of the I-V curves in the

26

Ohmic regime at low voltage (Figure 3b). The increase in pH (reduction in hydronium concentration) leads to

27

increased dissociation of the carboxyl and hydroxyl groups within the GO sheets:

35

4


Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 16

1

Graphene-OH ⇄ Graphene-O; + H8

2

This leads to an increase in negative surface charge density in the graphene nanochannels, and is reflected in

3

an increased conductance and current rectification. The ionic currents associated with the excess hydronium

4

(H3O ) or hydroxide (OH ) ions are subtracted as shown in Figure S4a. At higher pH, we also observe an increase

5

in 𝑃 K 8 , a decrease in 𝑃 Cl; and an increase in cation selectivity 𝑆8 (Figure 3c), all consistent with the

6

increase in the nanochannels’ charge.

+

-

7

The strong surface charge effects were revealed in the membrane’s conductance 𝐺[ variation with the

8

electrolyte concentration c (Figure 3d). Starting from 𝑐 = 1 M, the observed 𝐺[ immediately deviates from

9

the expected linear regime for a charge-neutral membrane (black solid line), indicating the compression of the

10

EDL in the nanochannels even at high ionic strengths. In contrast, the charge effects were previously observed

11

to dominate the conductance in solid-state constrictions only at much lower salt concentrations

12

that the cation selectivity, as deduced from ionic permeabilities, could reach as high a value as 𝑆8 = 96% at

13

low salt concentration (Figure 3e,f).

36-38

. We note

14

To gain insight into the surface charge-driven ionic transport, we applied mean-field theoretical model

15

based on the Poisson-Boltzmann and Navier-Stokes equations (see the Supporting Information for more

16

details). The model fits the observed pH and molarity dependence of both the conductivity and the charge

17

selectivity well (Figure 3), assuming the ions flow in pristine graphene nanochannels with an effective height of

18

ℎG = 0.9 nm, an effective width in the range of 𝑤G ~50 nm, an effective channel length of 𝐿eff = 0.4 mm

19

and a constant density of active site on the sidewalls corresponding to one protonable charged site per 2 nm

20

(Figure S6). A crucial assumption of the model is the infinite-slip boundary condition for the water flow at the

21

top and bottom graphene surfaces, and no-slip condition at the oxidized sidewalls. The large slip-length is

22

consistent with the effect of frictionless water flow, as reported in GO membranes . The other possible

23

geometries could not replicate the observed pH and molarity dependence of the conductance (see Supporting

24

Information). We employed the same set of parameters to concurrently simulate all the independent

25

experiments. The parameters deduced from the model are within the range expected for the GO membrane,

26

despite crude the approximations. Although this continuous-media model has a limited scope at nanometer

27

length scales, it has been shown to capture the relevant physics and to give sufficient semi-quantitative insight,

1

5


Page 9 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

1

where the intermolecular and steric interactions are renormalized into the effective hydrodynamic

2

dimensions

36, 39

.

3

In conclusion, we have shown that the ion-rejection in graphene-oxide membranes is driven as much by

4

the electrostatic repulsion (defined by the nanochannel surface charge) as it is by the activated size-exclusion

5

(defined by the nanochannel height). Hence, the engineering of the surface charge of the membrane offers a

6

new venue for increasing the overall salt rejection, without constraining the water flux. We have demonstrated

7

that the GO membranes exhibit ultra-high charge selectivity, reaching up to 96%, driven by the negative surface

8

charge of the oxygen-carrying functional groups in the membrane’s nanochannels. Coupled with their high-

9

durability and scalability, the GO membranes are well positioned for applications in high-performance ion

10

exchange and electrodialysis technologies.

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

6


Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

2

3

4

5

Page 10 of 16

6

7

Figure 1 The drift-diffusion experiment. (a) Schematics of the experimental setup: the graphene oxide

8

membrane was mounted on a freestanding SiNx membrane with an 12×12 array of square-shaped windows,

9

separating two electrolyte-filled reservoirs; Ag/AgCl electrodes in each reservoir are used to apply an electric

10

potential across the GO membrane and to measure the ionic currents flowing through the membrane. (b and c)

11

Depiction of the ionic flow across the membrane driven by the concentration gradient (diffusion), and by the

12

voltage difference (drift), respectively. (d) The ionic current-voltage characteristic of the membrane for

13

different salts, measured under the concentration gradient 0.1M/0.01M across the membrane.

14

15

16

17

18

19

20

21

7


Page 11 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

1

2

3

4

5

6

Figure 2 Charge-selective permeability. (a) Permeation rates (p) for different cations (circles) and

7

corresponding chloride counter-ions (open and filled squares) as a function of hydrated radius (RH) of the

8

cations. The filled square represents the chloride permeability when in RbCl solution, where the hydration radii

9

are very similar for both ions – the two-headed arrow shows the permeation difference resulting purely from

10

the charge-rejection effects. The solid blue line is a guide to eye. (b and c) Schematics of the dominant ion

11

rejection mechanisms: size exclusion (b) and electrostatic repulsion (c). (d) The cationic selectivity of GO

12

membranes for different salts, reaching values in excess of 90%. Inset: the permeation rates of chloride ions as

13

a function of the valence of the position counter-ion in the salt, revealing the effect of the correlated charge

14

inversion in the sub-nanometer channels.

15

16

17

18

19

20

8


Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1

2

3

4

5

Page 12 of 16

6

7

Figure 3 Molarity and pH dependence of conductance and ionic permeation. (a) Current-voltage (I-V) curves

8

across the membranes at KCl salt concentration 𝑐KCl = 10 mM, measured for different pH values. (b)

9

Conductance vs pH. (c) Permeation rates for potassium and chloride ions for different pH values. (d) The ionic

10

conductance vs molarity (circles) deviates from the Ohmic behavior (full line), even at high salt concentrations,

11

due to sub-nanometer channel heights. (e and f) Molarity dependence for the permeation rates (e), and for

12

the cation selectivity (f). Dashed curves in all the graphs are fit to the mean-field model, discussed in the text.

13

14

15

16

17

18

9


Page 13 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

1

▪ ASSOCIATED CONTENT

2

Supporting Information

3

The Supporting Information is available free of charge on the ACS Publication website at DOI:

4 5 6 7 8 9 10 11 12

Physiochemical characterizations of graphene oxide nanosheets; Interplanar spacing expansion of graphene oxide membranes in water; Quantitative analysis of ion selectivity across the membranes; Effect of SiNx substrate on the ion permeation; Calculation of ionic conductance and surface charge density; pH-dependent ionic conductances and surface charge densities; Effects of excess hydronium or hydroxide ions; pH-dependent drift-diffusion measurements; Mean field model for ion transport in the nanochannels; Validation of the analytical continuum models; Ion strength-dependent ionic conductance and cation permselectivity ▪ AUTHOR INFORMATION

13

Corresponding Author

14

* E-mail: [email protected]

15

Author Contribution

16

H.S. and S.G. conceived the concept of the study. H.S. performed the experiments and analyzed the data

17

together with C.C. and J.A.G.C. H.S., M.V.S.M., Y.C.S. and J.A.G.C. fabricated and characterized the membranes.

18

The continuum model analysis was performed by C.C. The manuscript was written by H.S. and S.G. with

19

comments and input from all authors.

20

Notes

21

The authors declare no competing financial interest.

22

▪ ACKNOWLEDGEMENTS

23

We acknowledge support from the National Research Foundation, Prime Minister’s Office, Singapore, under

24

the NRF Fellowship Program (Award No. NRF-NRFF2012-09) and Competitive Research Program (Award No.

25

NRF-CRP13-2014-03). The authors are grateful to Dr. Eugene Choo of ZEISS Advanced Imaging Centre

26

(Singapore) for assisting the FIB preparation of nanopores.

27

▪ REFERENCES

28

1.

Nair, R. R.; Wu, H. A.; Jayaram, P. N.; Grigorieva, I. V.; Geim, A. K. Science 2012, 335, (6067), 442-444.

29

2.

Cohen-Tanugi, D.; Grossman, J. C. Nano Lett. 2012, 12, (7), 3602-3608.

30

3.

Joshi, R. K.; Carbone, P.; Wang, F. C.; Kravets, V. G.; Su, Y.; Grigorieva, I. V.; Wu, H. A.; Geim, A. K.; Nair,

31

R. R. Science 2014, 343, (6172), 752-754. 10


Nano Letters

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 16

1

4.

2

190-3.

3

5.

4

T.; Atieh, M.; Karnik, R. ACS Nano 2012, 6, (11), 10130-10138.

5

6.

6

G. Science 2014, 344, (6181), 289-92.

7

7.

8

Nanotech. 2015, 10, (5), 459-464.

9

8.

Sint, K.; Wang, B.; Kral, P. J. Am. Chem. Soc. 2008, 130, (49), 16448-16449.

10

9.

Service, R. F. Science 2006, 313, (5790), 1088-1090.

11

10.

Elimelech, M.; Phillip, W. A. Science 2011, 333, (6043), 712-717.

12

11.

Li, H.; Song, Z.; Zhang, X.; Huang, Y.; Li, S.; Mao, Y.; Ploehn, H. J.; Bao, Y.; Yu, M. Science 2013, 342,

13

(6154), 95-98.

14

12.

15

Kwon, S.; Choi, J.-Y.; Park, H. B. Science 2013, 342, (6154), 91-95.

16

13.

Raidongia, K.; Huang, J. J. Am. Chem. Soc. 2012, 134, (40), 16528-16531.

17

14.

Qiu, L.; Zhang, X.; Yang, W.; Wang, Y.; Simon, G. P.; Li, D. Chem. Commun. 2011, 47, (20), 5810-5812.

18

15.

Han, Y.; Xu, Z.; Gao, C. Adv. Funct. Mater. 2013, 23, (29), 3693-3700.

19

16.

Hu, M.; Mi, B. Environ. Sci. Technol. 2013, 47, (8), 3715-3723.

20

17.

Dikin, D. A.; Stankovich, S.; Zimney, E. J.; Piner, R. D.; Dommett, G. H. B.; Evmenenko, G.; Nguyen, S. T.;

21

Ruoff, R. S. Nature 2007, 448, (7152), 457-460.

22

18.

Eda, G.; Chhowalla, M. Adv. Mater. 2010, 22, (22), 2392-2415.

23

19.

Pendergast, M. M.; Hoek, E. M. V. Energy Environ. Sci. 2011, 4, (6), 1946-1971.

24

20.

Liu, G.; Jin, W.; Xu, N. Chem. Soc. Rev. 2015, 44, (15), 5016-5030.

25

21.

Lee, A.; Elam, J. W.; Darling, S. B. Environ. Sci.: Water Res. Technol. 2016, 2, (1), 17-42.

26

22.

Boukhvalov, D. W.; Katsnelson, M. I.; Son, Y.-W. Nano Lett. 2013, 13, (8), 3930-3935.

27

23.

Sun, P.; Liu, H.; Wang, K.; Zhong, M.; Wu, D.; Zhu, H. J. Phys. Chem. C 2014, 118, (33), 19396-19401.

28

24.

Sun, P.; Zhu, M.; Wang, K.; Zhong, M.; Wei, J.; Wu, D.; Xu, Z.; Zhu, H. ACS Nano 2013, 7, (1), 428-437.

29

25.

Sun, P.; Zheng, F.; Zhu, M.; Song, Z.; Wang, K.; Zhong, M.; Wu, D.; Little, R. B.; Xu, Z.; Zhu, H. ACS Nano

30

2014, 8, (1), 850-859.

31

26.

Hille, B., Ionic channels of excitable membranes Ch. 10. Sinauer: Sunderland, Mass., 1984.

32

27.

Israelachvili, J. N., Intermolecular and surface forces : with applications to colloidal and biological

33

systems. Academic: London, 1985.

34

28.

Marcus, Y. Biophys. Chem. 1994, 51, (2-3), 111-127.

35

29.

Zwolak, M.; Lagerqvist, J.; Di Ventra, M. Phys. Rev. Lett. 2009, 103, (12), 128102.

36

30.

Shklovskii, B. I. Phys. Rev. E 1999, 60, (5), 5802-5811.

Garaj, S.; Hubbard, W.; Reina, A.; Kong, J.; Branton, D.; Golovchenko, J. A. Nature 2010, 467, (7312),

O’Hern, S. C.; Stewart, C. A.; Boutilier, M. S. H.; Idrobo, J.-C.; Bhaviripudi, S.; Das, S. K.; Kong, J.; Laoui,

Celebi, K.; Buchheim, J.; Wyss, R. M.; Droudian, A.; Gasser, P.; Shorubalko, I.; Kye, J. I.; Lee, C.; Park, H. Surwade, S. P.; Smirnov, S. N.; Vlassiouk, I. V.; Unocic, R. R.; Veith, G. M.; Dai, S.; Mahurin, S. M. Nat.

Kim, H. W.; Yoon, H. W.; Yoon, S.-M.; Yoo, B. M.; Ahn, B. K.; Cho, Y. H.; Shin, H. J.; Yang, H.; Paik, U.;

11


Page 15 of 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Nano Letters

1

31.

Aguilella, V. M.; Queralt-Martin, M.; Aguilella-Arzo, M.; Alcaraz, A. Integr. Biol. 2011, 3, (3), 159-172.

2

32.

García-Giménez, E.; Alcaraz, A.; Aguilella, V. M. Phys. Rev. E 2010, 81, (2), 021912.

3

33.

Alcaraz, A.; Nestorovich, E. M.; López, M. L.; García-Giménez, E.; Bezrukov, S. M.; Aguilella, V. M.

4

Biophys. J. 2009, 96, (1), 56-66.

5

34.

6

224502.

7

35.

Yossifon, G.; Mushenheim, P.; Chang, Y.-C.; Chang, H.-C. Physical Review E 2009, 79, (4), 046305.

8

36.

Hoogerheide, D. P.; Garaj, S.; Golovchenko, J. A. Phys. Rev. Lett. 2009, 102, (25), 256804.

9

37.

Stein, D.; Kruithof, M.; Dekker, C. Phys. Rev. Lett. 2004, 93, (3), 035901.

10

38.

Smeets, R. M. M.; Keyser, U. F.; Krapf, D.; Wu, M.-Y.; Dekker, N. H.; Dekker, C. Nano Lett. 2006, 6, (1),

11

89-95.

12

39.

13

▪ Table of Contents

van der Heyden, F. H. J.; Stein, D.; Besteman, K.; Lemay, S. G.; Dekker, C. Phys. Rev. Lett. 2006, 96, (22),

Garaj, S.; Liu, S.; Golovchenko, J. A.; Branton, D. Proc. Natl Acad. Sci. 2013, 110, (30), 12192-6.

14

12


grapehe-oxide layers

1 2 3 4

Nano Letters 16 hydration charged Page functional shell groups

-

ion


Size selectivity

of 16

-

-

ion

Charge selectivity

Scalable Graphene-Based Membranes for Ionic Sieving with Ultrahigh

Recommend Documents