Distorted Graphene Sheet Structure-Derived Latent Nanoporosity

May 23, 2016 - Department of Physical Chemistry and Materials Science, Budapest University of Technology and Economy, Budapest, Hungary...
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Distorted Graphene Sheet Structure-Derived Latent Nanoporosity Shuwen Wang,† Dániel Á brahám,§ Fernando Vallejos-Burgos,† Krisztina László,§ Erik Geissler,∥ Kenji Takeuchi,‡ Morinobu Endo,‡ and Katsumi Kaneko*,† †

Center for Energy and Environmental Science and ‡Institute of Carbon Science, Shinshu University, Wakasato, Nagano 380-8553, Japan § Department of Physical Chemistry and Materials Science, Budapest University of Technology and Economy, Budapest, Hungary ∥ Laboratoire Interdisciplinaire de Physique, Université Grenoble Alpes and CNRS, 38402 Grenoble, Cedex, France S Supporting Information *

ABSTRACT: High surface area graphene monoliths consist mainly of single graphene layers wider than 10 nm. The interlayer porosity of high temperature treated nanoporous graphene monoliths with tuned intergraphene layer structures is evaluated by hybrid analysis of Ar adsorption at 87 K, N2 adsorption at 77 K, high resolution transmission electron microscopic observation, and small-angle X-ray scattering (SAXS) measurements. SAXS analysis results in surface areas that are 1.4 and 4.5 times larger than those evaluated by Ar adsorption for graphene monoliths nontreated and treated at 2273 K, respectively. A distorted graphene sheet structure model is proposed for the high surface area graphene monoliths on the basis of the hybrid analysis.



INTRODUCTION The surface area of ideal graphene, where carbon atoms occupy both surfaces of the same sheet, is 2630 m2/g, and thus basically graphene-based materials display ultrahigh surface area.1 Graphene also exhibits high electrical and thermal conductivities. Much effort has been devoted to the development of highly porous graphene-based materials having high electrical and thermal conductivities to obtain outstanding surface-active materials.2−7 Recent studies show that KOH activation of nanographenes from graphene oxide colloids yields highly porous graphene with a BET surface area exceeding 2000 m2/ g,8,9 although a rigorous correction must be made for the significant overestimation arising from enhanced filling in the micropores during evaluation of the BET surface area.10 As highly porous graphene materials are prepared by reduction of partially stacked graphene oxide colloids, the graphene sheets should be wrinkled to form loosely stacked graphene structures, providing interstices that are too small to be detected by gas adsorption; there should be abundant inaccessible pores. These inaccessible pores of porous graphene materials affect the physical properties such as electrical conductivity, thermal conductivity, and mechanical properties. The interaction between the wrinkled graphene nanosheets, however, is weak enough for the intergraphene spaces to expand under an external stimulus and to become accessible for molecules. In this case the inaccessible pores give an explicit effect on chemical properties of the porous graphene materials. For example, a strong interaction between the nanographene and solvent molecules opens the inaccessible pores for solvent © XXXX American Chemical Society

molecules, which is plausible in electrode applications of nanoporous carbons.11 Consequently, the inaccessible pores in highly nanoporous graphenes should have potentially open nature. Ruike et al.12 used N2 adsorption, small-angle X-ray scattering (SAXS), X-ray diffraction, and density measurements to obtain a quantitative evaluation of inaccessible pores in activated carbon fiber. This study introduced the concept of latent pores, whose accessibility for molecules varies depending on the surrounding conditions. Thus, the latent porosity of highly porous graphenes must be characterized. Recent studies show that evaluation of microporosity with Ar adsorption at 87 K is more reliable than with N2 adsorption at 77 K.13−15 In this article, we do a hybrid analysis of Ar adsorption at 87 K, N2 adsorption at 77 K, and synchrotron X-ray scattering to evaluate the inaccessible porosity of high surface area graphene monoliths consisting of poorly crystallized graphene sheets.



EXPERIMENTAL SECTION

Graphene oxide was prepared from graphite (Bay Carbon Inc., Bay City, MI) by an improved oxidation method using KMnO4, H2SO4, and H3PO4. The graphene oxide suspension was mixed with KOH in the weight ratio KOH/C = 8. The graphene oxide monoliths mixed with KOH were prepared using a unidirectional freeze-drying method.9 The mixture of graphene oxide monolith and KOH was heated to 573 K in Ar, resulting in almost perfect reduction of Received: February 14, 2016 Revised: May 11, 2016

A

DOI: 10.1021/acs.langmuir.6b00483 Langmuir XXXX, XXX, XXX−XXX

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Langmuir graphene oxide, as confirmed previously by X-ray photoelectron spectroscopy.16 The graphene monolith with KOH was then heated to 1073 K for 1 h and washed to remove KOH. Removal of KOH in the graphene monolith with water was verified by the electrical resistivity of the supernatant. The resulting KOH-free activated graphene monolith was heated from room temperature to 2273 K at a rate of 5 K/min under 1 L/min Ar flow. We heat-treated activated graphene monoliths at 1673, 2073, and 2273 K.9 The porous graphene monolith without the heat treatment is denoted PGM-0; the porous graphene monolith heat-treated at T K is designated PGM-T. The pore structures of nanoporous graphene monoliths were evaluated by N2 adsorption at 77 K and Ar adsorption at 87 K with a Micromeritics ASAP 2020 surface analyzer after grinding and preevacuating at 473 K for 3 h. The total surface area Sαs and external surface area Sext were obtained using the SPE method with the high resolution αS plot, which enables the overestimation of the surface area to be eliminated.10 Here, the error in total surface area determination with gas adsorption is less than 3% and 5% for surface areas either greater than 500 m2 g−1 or less than 100 m2 g−1, respectively. The percentage error in the external surface area determination is about 20%. The pore size distribution was obtained for Ar adsorption isotherms using QS-DFT.17 SAXS measurements were made on beamline BM02 at the European Synchrotron Radiation Facility, Grenoble, France, with an incident energy of 18 keV in the transfer wave vector range 0.008 ≤ q ≤ 2.2 Å−1. After correction for grid distortion in the indirectly illuminated CCD detector, the intensity curves were averaged azimuthally. Corrections were made for dark current, sample transmission, and scattering of the empty cell. Intensities were normalized with respect to a standard sample (Lupolen). The high-resolution transmission electron micrographs (HR-TEM) were obtained with a JEOL JEM-2100F microscope. Computer models were rendered using VMD18 and Tachyon.19

Figure 1. Ar adsorption isotherms of porous graphene monoliths treated at different temperatures before (a) and after (b) normalization by the adsorbed amount at the closure point of the adsorption hysteresis.



RESULTS AND DISCUSSION Figure 1 shows Ar adsorption isotherms of porous graphene monoliths treated at different temperatures before (a) and after (b) normalization by the adsorption amount at the closure point of the adsorption hysteresis. Here, the normalized expression of the adsorption isotherms is useful to compare the pore structure of PGM samples having largely different porosity. The adsorbed Ar amount decreases markedly with elevation of heating temperature; all adsorption isotherms are a combination of IUPAC types I and IV(a).15 The adsorption isotherms exhibit a distinct hysteresis loop. The N2 adsorption isotherms, like the Ar adsorption isotherms, depend on the temperature of the heat treatment, as shown in Figure S1. These adsorption data indicate the presence of both micropores and mesopores. The normalized data show that PGM-2273 has a rectangular shaped adsorption isotherm below P/P0 = 0.1, indicating that the micropores of PGM-2273 have the sharpest pore size distribution in all samples, although PGM-2273 has the smallest absolute porosity. On the other hand, the adsorption hysteresis loop of the normalized adsorption isotherm of PGM-2273 considerably resembles those of other PGM samples; the basic mesopore structure of PGM-2273 should be close to that of other PGM samples. The high resolution αS plots for Ar adsorption isotherms are shown in Figure 2. As the solid lines from the origin are αS plots without enhancement effects by micropores (αS < 0.5) and mesopores (α S > 0.5) 10 and there are two upward deviations corresponding to enhanced adsorption in micropores and mesopores, all these samples have both micropores and mesopores. The pore size distribution profiles of PGM samples explicitly show the presence of mesopores and micropores the peak values of which are 0.89 ± 0.01 and 2.8 ± 0.1 nm, respectively (Figure S3), although the microporosity of PGM-

Figure 2. αS plots for Ar adsorption isotherms of porous graphene monoliths.

2273 is too small compared with the mesoporosity. The Sext values except for PGM-2273 are much smaller than the total SPE surface area (see Table 1), indicating that PGM-0, PGM1673, and PGM-2073 are highly porous. The SPE surface area from N2 adsorption almost coincides with that of Ar adsorption, but the BET surface area overestimates the surface area by 15−30%. For SAXS profiles in PGM-0, PGM-1673, and PGM-2073 samples (see Figure 3) the power law slope in the low q range is −2.8, i.e., a volume fractal corresponding to a densely filled structure, but with no evidence of surface scattering. In the intermediate q range an unresolved plateau is visible, B

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Langmuir Table 1. Surface Areas Determined from αS Plots and BET Method from Ar Adsorption at 87 K and N2 Adsorption Isotherms at 77 K SαS [m2 g−1]

PGM-0 PGM-1673 PGM-2073 PGM-2273

Sext [m2 g−1]

Equation 3 assumes absence of a long-range order.22 The fairly low degree of order observed in sample PGM-2247 is unlikely to affect seriously the evaluation of SSAXS. In eq 3, the quantity

SBET [m2 g−1]

Ar (87 K)

N2 (77 K)

Ar (87 K)

N2 (77 K)

Ar (87 K)

N2 (77 K)

1580 1280 510 90

1560 1270 560 94

50 60 50 18

30 30 30 13

1790 1400 565 108

1890 1480 645 120

Q=

∫q



[I(q) − b]q2 dq (4)

min

is the second moment of the scattering curve, and dHe and Vtot are the helium density and the total pore volume of the sample, respectively. The upper limit of the integral in eq 4 follows trivially from eq 1. Figure 4 illustrates the procedure used for

Figure 3. SAXS profiles of the powdered nanoporous graphene monoliths. For clarity, the intensities of the successive responses are shifted vertically by a factor of 10.

Figure 4. Plot of Iq4 vs q4 for the two extreme samples PGM-0 and PGM-2273 for the data from the power law region q ≥ 0.2 Å in Figure 3; continuous curves are fits to eq 5. Dashed lines are linear fits to eq 2 of the data from the more restricted range 0.2 ≤ q4 ≤ 1 Å−4. The inset is an enlargement of the response at the lower q end of the figure.

characteristic of empty pores. The slope −3 in the low q profile of PGM-2273 implies a completely disordered surface. Moreover, this sample displays intermediate range order, in the form of a peak at q = 1.84 Å−1, plus a much weaker peak at 2.05 Å−1. The former feature defines an interlayer spacing of 3.41 Å, being close to that of turbostratic stacking structure of graphite (3.44 Å).20 The width of this line, approximately 9 mrad, together with the Scherrer equation, yields for the spatial order of a range of approximately 70 Å.21 The weak feature at 2.05 Å−1, by contrast, has no counterpart in graphite. The surface area from all interfaces in the PGM samples was evaluated as follows. The SAXS response at low q (q < 1 Å−1) is dominated by surface scattering, where the intensity varies as22,23

calculating the parameters κ and b in eqs 1 and 2. The lower limit is estimated from the extrapolation I(q → qmin), where qmin is defined by a nominal grain size, estimated to be d = 1 μm = 1/qmin. This approach to Porod scattering, however, may be contested from two standpoints, namely the reality of a discontinuous boundary condition23 and an alternative interpretation of surface fractal structure25 in terms of an electron density gradient normal to the interface.26,27 As the discontinuous boundary approximation is likely to affect estimation of the surface area only in a q range above about 2π/ϕ, where ϕ is the diameter of the constituent carbon atoms, i.e., above the q range of Figure 4, its effect on the second moment Q in eq 4 might be expected to be small. The second criticism stems from the concept of an electron density gradient perpendicular to an interface, which yields an additional term in the scattering intensity that is proportional to 1/q2 and decays according to E2(q2σ2/2).26 Here, E2 is the exponential integral of order 2, and σ is the width of the smoothing distribution at the surface. For the continuous curves in Figure 4 a simplified expression is used to fit the full data range

I(q) = κq−4 + b

(1)

Here κ is the Porod final slope. The constant signal b arises from the disorder of the carbon atoms in the amorphous sample and is of the same nature as the concentration fluctuations found in liquids and glasses in the q range below the amorphous peak. The values of κ and b are determined by plotting I(q)q4 vs q4. Thus I(q)q 4 = κ + bq 4

Iq 4 = κ + (aq2) exp[−q2σ 2/2] + bq 4

where the Gaussian factor replaces E2, and κ, a, and b are adjustable parameters. In Figure 4, the lower limit of the plotted data is defined by the lower limit of apparent power law behavior in Figure 3, q ≈ 0.2 Å−1. The values found in this way for σ are 2.0 and 2.2 Å, respectively, while κ is significantly smaller than that obtained from the linear fit on the basis of eq

(2) 24

The scattering surface area SSAXS is then obtained from SSAXS =

Vtot πκ Q 1 + VtotdHe

(5)

(3) C

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Langmuir 2. In the case of sample PGM-0 this would yield a value of SSAXS about 50% smaller than SBET. This unsatisfactory solution leads us to reexamine the underlying assumption of the Ruland model. Although at low resolution the concept of a structurefree electron density gradient at the surface is acceptable, when seen at higher resolution, it is harder to imagine that the landscape at the surface remains continuous. It would be more convincing to picture the surface as a chaotic field of craters and prominences having the same large scale height distribution as the concentration gradient. In this more physical picture the total surface scattering intensity must include the extra contribution from these nanostructured surfaces. The acceptable value of κ is therefore that found in the asymptotic regime from eq 2. Figure 4 demonstrates that in these samples the validity of eq 2 extends beyond q4 = 1 Å−4. It is notable that even with PGM-0, where the amorphous structural peak around 1.8 Å−1 is broad, deviations from linearity in the higher q range due to overlap from this feature are hardly noticeable. These observations support the validity of eq 3 in evaluating the surface area from SAXS data. The error of the surface area determined using the above procedure is less than 5%, which comes mainly from the choice of lower cutoff value for q in the calculation of the second moment. Table 2 lists the SPE surface area from Ar adsorption, surface area from SAXS, and surface area difference SSAXS − SαS. SSAXS is

graphene sheets, thereby leaving inaccessible interstices between graphene layers. The observed discrepancy of SSAXS − SαS is inherent to nanoporous graphene monoliths reorganized from nanographenes. We can estimate the average graphene layer number from the surface area from SAXS using 2630 m2 g−1 as the surface area of a perfect single graphene, as shown in Table 2. Nontreated porous graphene PGM-0 must consist mainly of single graphene layers, and higher temperature treatment leads to stacking among nanographene layers. HR-TEM images (see Figure 5) reveal explicitly the presence of nanoscale deformed graphene sheets irrespective of the heat treatment. Also, they indicate the presence of poorly stacked structures. Figure 6 shows a plausible model of nanoporous graphenes before high-temperature treatment, corresponding to PGM-0. The slightly distorted graphene sheets are mutually stacked on each other. However, the distorted sheets cannot stack perfectly to form graphitic periodicity, leaving many interstices in which Ar and N2 molecules cannot access. Only SAXS can evaluate the total surface area coming from the interstices between the distorted graphene layers, giving a larger surface area than that from Ar adsorption. The interstices between the distorted graphene sheets decrease with the heat treatment at higher temperature as shown in Table 2. The proposed structure model should be helpful to understand surface chemical properties of nanoporous graphene materials.



Table 2. Surface Areas Determined from the SPE Method Using αs Plots for Ar Adsorption Isotherms at 87 K and Determined from SAXS and the Percent of Single Graphene Structures

PGM-0 PGM-1673 PGM-2073 PGM-2273

SαS (m2 g−1)

SSAXS (m2 g−1)

SSAXS − SαS (m2 g−1)

single graphene (%)

1580 1280 510 90

2155 1875 1030 400

735 675 550 200

82 70 40 15

CONCLUSION

Evaluation of inaccessible interstices is necessary for designing an optimum porous carbon with the target performance. This is because the inaccessible interstices can change their accessibility easily under external stimuli, depending on the nanoscale chemical environment. In particular, electrochemical applications of porous graphenes must take into account the inaccessible intergraphene sheet spaces because application of an electric potential can give enough energy to insert selected solute molecules and/or partially desolvated ions.28−30 However, we should be cautious in applying SAXS analysis routinely to evaluate the porosity, since the SAXS analysis depends sensitively on the theoretical model. Consequently, we must introduce hybrid reverse Monte Carlo simulation to SAXS studies combined with Ar adsorption at 87 K in order to obtain the most reliable pore structure information in future.

larger than SαS for all samples. The surface area difference amounts to about 35% for PGM-0 and PGM-1573 and 50% for PGM-2073 and PGM-2273. This difference stems from the inaccessible interstices between less-crystalline graphene layers. As graphene sheets are necessarily partially wrinkled, even the high-temperature treatment does not lead to regular stacking of

Figure 5. HR-TEM images of PGM-0 (a) and PGM-2073 (b). D

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Figure 6. Model for nanoporous graphene: (a) general view; (b, c) cross section in two different directions.



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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.langmuir.6b00483.



N2 adsorption isotherms at 77 K, αS plots for N2 at 77 K, and pore size distribution for Ar at 87 K (PDF)

AUTHOR INFORMATION

Corresponding Author

*E-mail [email protected] (K.K.). Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The authors are thankful to Concert-Japan: Efficient Energy Storage and Distribution, JST, and partial supports by the Grant-in-Aid for Scientific Research (A) (24241038) and the Center of Innovation Program from Japan Science and Technology Agency, JST. We gratefully acknowledge the European Synchrotron Radiation Facility, Grenoble, France, for access to the French CRG beamline BM02 and the support of the Hungarian National Fund OTKA (NN110209).



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DOI: 10.1021/acs.langmuir.6b00483 Langmuir XXXX, XXX, XXX−XXX