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High-Efficiency Production of Graphene by Supercritical CO2 Exfoliation with Rapid Expansion Ying Wang,*,† Zhuo Chen,‡ Zhijian Wu,† Yun Li,‡ Wang Yang,‡ and Yongfeng Li*,‡ †

State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, P. R. China ‡ State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Changping, Beijing 102249, P. R. China

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S Supporting Information *

ABSTRACT: In this study, direct nonequilibrium molecular dynamics simulations based on the density-functional tightbinding potential were performed to investigate the mechanism of graphite exfoliation by supercritical CO2 in the depressurization process. We found that the graphite peeling rate and the graphene yield depended on the number of inserted CO2 molecules in our simulations, and the appropriate pressure or density of CO2 is a prerequisite to achieve graphite exfoliation. Our theoretical results proposed that the graphite peeling occurred till the pressure or the density of CO2 was larger than 12.2 MPa or 0.21 g/cm3. This is confirmed by the experimental observations. Furthermore, we declared that the essential effect of the pressure or density of CO2 was attributed to the competition between the van der Waals attraction in the graphite interlayer and repulsion of CO2 and graphite, which resulted from the steric hinder effect. The current theoretical observations provide potential scientific evidence to control graphite exfoliation by supercritical CO2.

1. INTRODUCTION Graphene has been the focus of much scientific research interest because of its preeminent properties and potential technological applications since its discovery by Novoselov and Geim in 2004.1,2 Owing to the outstanding properties of graphene, it can be used in the fields of sensitive sensors,3 electric power resonators,4 hydrogen storage,5 and so forth. As a kind of ideal nanomaterial, the application of graphene is often hindered by the thickness and amount obtained by different preparation methods. To the best of our knowledge, the preparation of graphene can be divided into two categories, top-down and bottom-up. The discovery of graphene by peeling off the graphite with a scotch tape is one kind of topdown method leading to single-layer graphene with high quality.2 The bottom-up method, such as the chemical vapor deposition (CVD)6 method, is also used to fabricate single- or few-layer graphene for applying directly. However, the amount of graphene obtained by the peel-off process or CVD is unsuitable for commercial applications. Currently, the industrial method for the mass production of graphene is the solution exfoliation of graphite oxide (GO) and reduction of GO.7,8 However, the production process causes lot of pollution, and the structure of the obtained graphene is severely damaged. From the perspective of sustainable development, the loss outweighs the gain. In the last decades, supercritical fluid (SCF) exfoliation technology has been in use because of many advantages, such as the simple setup, less toxic, and mass production. It has been © XXXX American Chemical Society

regarded as an efficient method to get large amount of graphene nanosheets (GNs).9−13 Currently, carbon dioxide (CO2),12−21 ethanol,10 and N,N-dimethylformamide11 are commonly used as the SCF media. By far, supercritical CO2 (scCO2) is the most promising SCF in graphene-based material processing because of its environmentally friendly nature and easily accessible critical conditions. It has been reported that CO2 can be diffused easily into graphene layers, with the molecular size (0.23 nm) similar to the layer distance (0.34 nm).12,22 The scCO2 exfoliation has been developed, assisted by several methods such as ultrasonic,14,23 shear force,21 and ball milling.19,24 The supercritical conversion of layered graphite to graphene sheet is a multistep process and can be separated into three stages: (1) pretreatment of graphite chunk; (2) SCF intercalation, and (3) exfoliation.13 The pretreatment step affects the intercalation degree of SCFs, and the intercalation degree of SCFs has great impact on the exfoliation efficiency of the subsequent exfoliation step. In the exfoliation step, rapid expansion is the common method to exfoliate graphene sheets from intercalated graphite. Many studies13,15 have focused on the influences of temperature, pressure, shock velocity,21 scCO2 density,25 colloid aggregation,26 aqueous solution content ratio, and ultrasonic power23 during the graphite exfoliation process. Received: March 30, 2018 Revised: May 14, 2018

A

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Langmuir However, until now, the exfoliation mechanism in the depressurization process of scCO2 has not been well-explored. It is well-known that the rapid depressurization process can reduce the pressure of the reaction system from a high to low in seconds. The volume of the CO2 molecule expanded in the depressurization process and the distance between layers was broadened, so that graphite can be exfoliated efficiently. Therefore, the depressurization process plays a key role for exfoliating graphite. In this work, molecular dynamics (MD) simulations were carried out to find out the behaviors of CO2 and graphite in the depressurization process of scCO2 as well as the interactions between CO2 and graphite layers. Some fundamental issues, such as the dynamic graphite peeling process, the effects of CO2 density, and the competition between the van der Waals (vdW) attraction in the graphite interlayer and repulsion of CO2 and graphite have been addressed. We expect these atomic scale simulations to explain the critical role of supercritical density in the depressurization process and provide useful information for effective graphite exfoliation.

believe that SCC-DFTB is a proper method to study the graphite exfoliation mechanism by CO2. 2.1.2. Model System. In this study, a larger model of double-layer 6 × 6 supercell graphite with an interlayer distance of 0.34 nm was established (totally, 72 × 2 = 144 carbon atoms). Following that, one, two, or five CO2 molecules were randomly inserted into one or two interlayers of graphite, denoted as G-n-0-CO2 or G-n-CO2 (n = 1, 2, and 5), as shown in Figure 1. The former corresponds to

2. COMPUTATIONAL AND EXPERIMENTAL SECTION

Figure 1. Illustration of simulation systems. (a) Graphite alternatively surrounded by one CO2 and zero CO2 molecules (G-1-0-CO2); (b) graphite surrounded by one CO2 molecule in each interlayer (G-1CO2); (c) graphite alternatively surrounded by two CO2 and zero CO2 molecules (G-2-0-CO2); (d) graphite surrounded by two CO2 molecules in each interlayer (G-2-CO2); and (e) graphite alternatively surrounded by five CO2 and zero CO2 molecules (G-5-0-CO2). The atoms of C and O were decorated with cyan and red. a1 and a2 are the interlayer distances and the sum of a1 and a2 are 6.8 Å.

2.1. Computational Method. 2.1.1. Quantum Chemical MD (QM/MD) Simulations. All simulations were carried out based on the self-consistent-charge density functional tight binding (SCC-DFTB)27 method, as implemented in the DFTB+ program. DFTB is a Born− Oppenheimer MD technique and can bridge the gap between the classical and first-principles MD simulations because of the balance of the accuracy and computational time. A finite electronic temperature (Te = 2000 K) approach28,29 was chosen to improve the convergence of the DFTB equations. The electronic temperature allows the occupancy of each molecular orbital to change smoothly from 2 to 0 depending on its energy, and then it could effectively incorporate the open-shell nature of the system. This method of SCC-DFTB with Te has been successfully applied to single-wall carbon nanotube growth and graphene growth.30−34 The vdW correction was included by using the dispersion term with the universal force field (UFF) method. In the nonequilibrium MD (QM/MD), the velocity Verlet integrator35 was used to integrate the equations of motion of nuclei with a time step of 1 fs. MD simulations were performed in the canonical ensemble (NVT). The nuclear temperature (Tn = 310 K) was controlled by connecting the Nose−Hoover chain thermostat.36 The mio-0-1 parameter sets were employed in our study. To evaluate the reliability of the SCC-DFTB method for our modeling systems, the interaction energies of graphite, one or two CO2 molecules with graphite, were calculated by both density functionary theory (DFT) and SCC-DFTB methods. To save the computational resources, a double-layer 4 × 4 supercell graphite consisting of 64 carbon atoms with the size of 9.84 Å × 8.52 Å was employed. In DFT calculations, Perdew, Burke, and Ernzerhof (PBE37) was used, and all calculations were implemented by the Vienna ab initio simulation package.38−41 A kinetic energy cutoff of 400 eV was used with a plane-wave basis set. The integration of the Brillouin zone was conducted using a 3 × 3 × 1 Monkhorst−Pack grid.42 All atoms were fully relaxed and optimized until the total energy was converged to 1.0 × 10−4 eV/atom and the force was converged to 0.05 eV/Å. A sufficiently large vacuum of 20.0 Å was taken along the z-axis to avoid image interactions. Spin polarization and vdW interaction with a semiempirical DFT-D243,44 force-field approach were also considered. The interaction energies at the DFT and SCC-DFTB levels of theory are listed in Table S1. As can be seen in Table S1, the SCC-DFTB method can reproduce the firstprinciples (PBE) results very well. The absolute errors in the interaction energies are less than 0.07 eV. Thus, it is fair to say that direct MD simulations based on the current SCC-DFTB method are of comparable quality to first-principles MD simulations. Also, we

inhomogeneous intercalation and the latter is related to uniform insertion. In our MD simulations, we first optimized these five models and then equilibrated these structures at 310 K for 10 ps. The total energy plots as a function of the equilibration time are shown in Figure S1. Second, three structures for each model were randomly chosen from the NVT equilibration simulations between 5 and 10 ps. On the basis of these 15 initial structures, the annealing simulations were carried out until 100 or 10 ps for the systems of G-1-0-CO2, G1-CO2, G-2-0-CO2, G-2-CO2, and G-5-0-CO2 at the same nuclear temperature. The periodical boundary condition (PBC) was considered. In the optimization and 10 ps equilibrium processes, the PBC in the z matrix was imposed as 6.8 Å. In the depressurization process, it was enlarged to 100 Å to promise enough space for graphite separation. Because PBC is involved, each model can be imaged in three directions to construct a huge system. Furthermore, by intercalating one-two-five CO2 molecules, the different density effects of CO2 could be well considered. Therefore, the current models are suitable to describe graphite peeling under supercritical conditions in the depressurization process. To investigate the effect of CO2 density or pressure, the interaction energy of CO2 with graphite (Eint) was calculated based on the following equation Eint = EG + CO2 − EG − nECO2

(1)

where EG+CO2, EG, and ECO2 are the total energies of graphite with CO2, graphite, and isolated CO2 and n is the number of CO2 molecules. The positive energy indicates a repulsive interaction. The vdW of each graphite layer (Ev‑g) was estimated by the following equation Ev ‐ g = Ev ‐ dg − 2Ev ‐ sg

(2)

where Ev‑dg and Ev‑sg are the energies of 6 × 6 double-layer graphite and single-layer graphene with UFF dispersion correction. Here, the z-direction was set as 100 Å to avoid the interaction of other image layers. B

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Langmuir 2.2. Experimental Method. 2.2.1. Materials. Graphite flakes were obtained from Xinjiang, China. Carbon dioxide, anhydrous ethanol, and other materials were used as received without further purification. 2.2.2. Preparation of GNs. The experiment was performed on a self-developed SCF apparatus consisting of a gas cylinder, chiller, compressor, pump, and reactor. The typical process is as follows: 10 g of pristine graphite was directly put into the reactor (250 mL) with a heating jacket and a temperature controller. The reactor was sealed and heated to a set temperature (60 °C). CO2 was injected into the reactor with the pump to a set pressure (16 MPa). After 1 h of exfoliation, the valve was opened, and the system pressure was dropped from 16 to 4 MPa in a few seconds. Then, the GN powder was collected. 2.2.3. Characterization. The morphology and structure of the samples were obtained by field emission scanning electron microscopy (SEM, Hitachi SU8010), high-resolution transmission electron microscopy (TEM, FEI Tecnai G2 F20), and scanasyst-mode atomic force microscopy (AFM, Bruker Multimode 8). Raman spectroscopy was performed on a Horiba Xplora Plus microscope with the laser wavelength of 532 nm.

3. RESULTS AND DISCUSSION 3.1. Graphite Exfoliation Kinetics. It is well-known that SCFs feature outstanding wetting of surfaces, low interfacial tension, low viscosity, and high diffusion coefficients, so that it will easily accomplish penetration and exfoliation.11 In experiments, it has been proved that following 30 min of immersion in the SCF, scCO2 diffused into the layers of graphite.12 Also, previous MD studies declared that at a higher scCO2 fluid density, there are more confined CO2 molecules within the interpolate regions.25 Therefore, in our current study, we assume that the solvent intercalation (step 2) within the layer of graphite is ready under extremely high-pressure conditions and only consider the effect of CO2 density on the rate or efficiency for exfoliation during the depressurization process (step 3). In this study, both inhomogeneous intercalation (G-n-0-CO2) and uniform insertion (G-n-CO2, n = 1, 2, and 5, see Figure 1) are considered. Figures 2−6 depict the snapshots of 15 trajectories at different densities of interlayer CO2. For the model of G-1-0CO2 (inhomogeneous intercalation, Figure 2), the interlayer distances of three initial structures (0 ps), which were randomly selected from the 10 ps equilibrium simulations, were almost same with the value of ∼3.60 Å. This indicated that our 10 ps MD annealing simulations reached the equilibrium states, confirmed by the small floating of the Mermin free energy (Figure S1a) during 5−10 ps. After 100 ps annealing simulations at 310 K, we found that the inserted CO2 molecule continually rotated and collated with the carbon atoms in the graphite layers. The interlayer distances were enlarged slightly, such as, at 1 ps, the interlayer distances of graphite were increased by ∼0.3 Å (3.91, 3.98, and 3.87 Å for three trajectories) compared to the initial structures. Furthermore, we found that the graphite layers fluctuated and moved gradually in the lateral direction, which is consistent with the previous observations.10 This kind of movement consumed the kinetic energy and potential energy of the system. Thus, the residual energy was not enough to overcome the vdW interaction between the graphite layers, and the graphite failed to be exfoliated. At 100 ps, the interlayer distances of graphite were still ∼3.88, 3.69, and 3.81 Å, respectively. For the model of G-1-CO2 (uniform insertion), similar situations were observed. The graphite expanded first and then

Figure 2. Time evolution of graphite exfoliation for model G-1-0CO2. (a−c) Correspond to the three trajectories.

Figure 3. Time evolution of graphite exfoliation for model G-1-CO2. (a−c) Correspond to the three trajectories.

resumed, as shown in Figure 3. No graphite exfoliation was achieved. Also, we found that the CO2 in the upper layer flew away immediately, once the vertical direction (z-matrix) was enlarged to 100 Å from 6.80 Å during the pressure releasing process. Compared with G-1-0-CO2, the initial interlayer distance was shortened to be ∼3.40 Å in G-1-CO2, which is close to the interlayer distance of perfect graphite because of C

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Figure 6. Time evolution of graphite exfoliation for model G-5-0CO2. (a−c) Correspond to the three trajectories.

Figure 4. Time evolution of graphite exfoliation for model G-2-0CO2. (a−c) Correspond to the three trajectories.

of the graphite layer. Meanwhile, the lateral movement and the fluctuation of graphite as well as the rotation and collation of CO2 in G-1-CO2 was also more substantial than in G-1-CO2. Therefore, more redundant energies were exhausted and resulted in graphite peeling failure. At 100 ps, the interlayer distance of graphite returned to 3.80−3.90 Å. With the number of intercalated CO2 increasing, graphite peeling occurred, as shown in Figures 4−6. Figures 4 and 6 correspond to CO2 inhomogeneous intercalation (G-0-2-CO2 and G-0-5-CO2), where CO2 was alternatively inserted into graphite interlayers (the upper layer without CO2 and the lower layer with n CO2, see Figure 1c,e). Figure 5 is related to the uniformed two CO2 insertions (G-2-CO2, see Figure 1d). From Figures 4 and 6, we can see that the initial interlayer distances of the lower layer in the models G-2-0-CO2 and G-50-CO2 (a1 = ∼3.70 and ∼3.98 Å) were larger than the one in model G-1-0-CO2 by 0.10 and 0.38 Å, respectively. This is attributed to the larger steric hindrance effect by more CO2 insertion. At the same time, the distance in the upper layer (a2, without CO2) decreased to ∼3.10 and ∼2.82 Å as the total distance was restricted as 6.8 Å (a1 + a2 = 6.8 Å, see Figure 1). These results showed that the CO2 molecules played a “wedge” role in the exfoliation process, which is in good agreement with the previous observations.17 Furthermore, the gradually reduced space with the increasing number of CO2 led to a stronger repulsive interaction, which further resulted in rapid graphite peeling25,26 during the depressurization process. At 1 ps, the exfoliation has already occurred for the models G-2-0CO2 and G-5-0-CO2, and the averaged interlayer distances from the three trajectories were 8.93 and 12.98 Å, respectively. At 10 ps, graphite was fully exfoliated with an extremely larger expanded interlayer distance of 30−40 Å. In addition, for G-2-CO2, in which four CO2 molecules were randomly filled into the two interlayers, the calculated interlayer distance was comparable to that of G-1-CO2 as

Figure 5. Time evolution of graphite exfoliation for model G-2-CO2. (a−c) Correspond to the three trajectories.

the uniform distribution of CO2 in each interlayer (see Figure 1b). When the z-direction was expanded, the interlayer distance of graphite was enlarged more significantly in G-1CO2, such as, at 1 ps, the interlayer distances were 5.64, 4.73, and 5.99 Å, which were larger than the ones in G-0-1-CO2 by ∼1.5 Å, indicating that uniform insertion of CO2 (here, each layer one CO2) could more effectively weaken the interactions D

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more seriously than G-1-0-CO2. This can also be reflected by the snapshots in Figures 2 and 3. For G-2-0-CO2, G-2-CO2, and G-5-0-CO2, with the number of CO2 molecules increasing, the interlayer distance increases faster and faster. The increasing rates (slopes) for G-2-0-CO2, G-2-CO2, and G-50-CO2 are 3.49, 5.16, and 7.53 Å/ps. This suggested that a higher density of CO2 would lead to an easier and faster formation of graphene sheets, which is consistent with the previous results.25 Furthermore, if we added more pressure to the system, CO2 molecules could be inserted and accumulated more in the interlayers of graphite because of good compressibility of scCO2. Thus they would generate a much stronger repulsive energy and further expand the spaces between the interlayers. Therefore, higher pressure can increase the speed and efficiency of peeling and is beneficial to graphite exploitation under scCO2 conditions. 3.3. Essence of Graphite Exfoliation by scCO2. As we know, the interlayer distance of graphite is about 3.4 Å, which is larger than the size of the CO2 molecule (2.3 Å) by 1.2 Å. Therefore, there is enough space for the CO2 molecule to diffuse into the interlayers of graphite, especially at higher pressure. Following CO2 molecules intercalation, we systematically investigated the exfoliation process during depressurization. We found that the entered CO2 molecules not only expanded the interlayer distance because of the steric hindrance effect but also produced a repulsive energy between graphite and CO2 molecules. Both of them reduce the attraction of the graphite interlayer and benefit graphite exfoliation. In principle, the prerequisite for graphite exfoliation was the repulsive energy resulting from the molecular insertion being enough to overcome the vdW interaction between the graphite interlayers.25,26 Therefore, in this study, we evaluated the interaction energies (Eint) and vdW contribution of each layer based on our 6 × 6 double-layer graphite model (Ev‑g), as listed in Table 2. It shows that all interaction energies (Eint) were positive due to the space hinder effect, indicating there was a strong repulsive integration between CO2 and graphite. Furthermore, to declare the essence of graphite exfoliation, the averaged repulsive energy in each layer was calculated as 3.10, 3.32, 5.76, 5.94, and 13.47 eV for G-1-0-CO2, G-1-CO2, G-2-0-CO2, G-2-CO2, and G-5-0-CO2, respectively. It is clearly seen that Eint‑a in the two former systems was less than the absolute value (3.97 eV) of Ev‑g, indicating that a small amount of CO2 was not enough to expand the interlayer spacing; and thus, no graphite exfoliation was observed. Contrarily, for more CO2 cases (G-2-0-CO2, G-2-CO2, and G-5-0-CO2), a stronger repulsive energy (Eint‑a is higher than Ev‑g) resulted in graphite peeling. Moreover, Eint‑a gradually increased with more and more CO2 molecules accumulating in the graphite interlayers, caused by the gradually narrowed interlayer distance in the optimized structures (d, see Table 2). This suggested that the higher the CO2 density (or the high pressure), the stronger the repulsion, and further more quick exfoliation. This revealed the essence of pressure effect, as discussed in section 3.2. Furthermore, our simulation results showed that efficient graphite peeling occurred until the density of CO2 or pressure was larger than 0.21 g/cm3 or 12.2 MPa (see Table 2); otherwise, the graphite peeling failed. We hope our theoretical observation can provide a reference for further experiments or industrial applications. 3.4. Characterization of GNs. To confirm our prediction, the experiments was performed at 16 MPa, which is slightly

well as to that of perfect graphite, owing to the uniformly distributed CO2 and the space restriction of 6.8 Å along the zdirection. Similar to G-1-CO2, in the depressurization process, that is, when the PBC box was expanded to 100 Å in the zdirection, the two CO2 molecules in the upper layer were quickly released to the larger vacuum. On the other hand, the lower layer graphite was separated by the pressure relieved CO2. For example, at 1 and 10 ps, the interlayer distances have already been ∼10.8 and 51 Å, indicating that graphite is fully exfoliated, as shown in Figure 5. 3.2. Pressure Effect. It is well-known that pressure is a crucial parameter for the exfoliation of graphite into graphene. In this study, the influence of pressure on the graphene yield was investigated by changing the number (or density) of CO2 molecules in between graphite layers. First, we analyzed the graphite separation time for each model, as listed in Table 1. Here, the interlayer distance being Table 1. Exfoliation Time (in ps) for Graphite by CO2a G-1-0-CO2 G-1-CO2 G-2-0-CO2 G-2-CO2 G-5-0-CO2

Tra1

Tra2

Tra3

averaged

  0.55 0.45 0.25

  0.60 0.45 0.30

  0.65 0.45 0.30

  0.60 0.45 0.28

a

Noted that the distance between two layers being larger than 7 Å is denoted as graphite separation. “” indicates that graphite is not separated.

larger than 7.0 Å was regarded as graphite exfoliation. From Table 1, we can see that for G-1-0-CO2 and G-1-CO2, the graphite failed to peel, so there is no exfoliation time available. As for G-2-0-CO2, G-2-CO2, and G-5-0-CO2, the averaged exfoliation time from three trajectories was 0.60, 0.45, and 0.28 ps, respectively, indicating the exfoliation speed increasing with the increasing number of intercalated CO2. Furthermore, we did not find the restacking of separated graphene sheets, suggesting that the aggregation was obstructed by the confined CO2 molecules with an efficient exfoliation. This agrees well with the previous experimental and theoretical results.20,45 To see the pressure effect more clearly, we also plot the averaged (averaged from 3 trajectories) interlayer distance as a function of time for the five models, as shown in Figure 7. The same plots for the individual trajectories are shown in Figure S2. From the inset figure, we can see that during the first 20 ps, the distance of the graphite interlayer constantly fluctuated for the models G-1-0-CO2 and G-1-CO2, and G-1-CO2 fluctuated

Figure 7. Averaged interlayer distance for the five models. The inset is the enlarged figure of distance vs time for the models of G-1-O-CO2 and G-1-CO2. Averaged from three trajectories. E

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Table 2. Density of CO2 (ρ), Pressure of CO2 (P), and the Interlayer Distance (d) in the Optimized Graphite with Different Number of CO2 Molecules. Here, a1 and a2 (a1 + a2 = 6.8 Å) Are the Interlayer Distances, as Defined in Figure 1. Eint is the Interaction Energy between CO2 and Graphite, Eint‑a is the Averaged Eint in Each Interlayer, and Ev‑g is the vdW Contribution in Each Interlayer of Graphitea G-1-0-CO2 G-1-CO2 G-2-0-CO2 G-2-CO2 G-5-0-CO2

ρ

P

d (a1/a2)

Eint

Eint‑a

Ev‑g

0.11/0 0.11/0.11 0.21/0 0.23/0.23 0.49/0

6.28/0 6.69/6.65 12.2/0 13.5/13.2 28.5/0

3.61/3.19 3.39/3.41 3.72/3.08 3.36/3.44 3.97/2.83

3.10 6.65 5.76 11.88 13.47

3.10 3.32 5.76 5.94 13.47

−3.97

a

The data before and after slash (/) are for the lower and upper layers. The units of density, pressure, energy, and distance are in g/cm3, MPa, eV, and Å, respectively.

Raman spectra (Figure 8e,f) after the exfoliation process. This shows that the GNs have a smaller crystallite size compared with the pristine graphite and have a little damage to the crystal.46 A large red shift in the 2D band (from 2720 to 2702 cm−1) is observed, and it proves that graphite has been successfully exfoliated in scCO2. In addition, the shape of the 2D band becomes more symmetric, which also can confirm the reduction of the layer number. AFM is also used to determine the thickness of graphene sheets (Figure 9). We find that the height is about 1 nm, larger

larger than our predicted values (12.2 MPa). The morphological and structural characterizations of pristine graphite and GNs were performed by SEM, TEM, and Raman (Figure 8).

Figure 9. (a,b) AFM images of graphene sheets on mica substrates, corresponding height profile along the lines, with height of closing to 1, 3 and 4.4 nm, respectively.

than the theoretical thickness of monolayer graphene. Considering the residue of the solvent on graphene, the product can be defined as monolayer graphene. Moreover, the heights of the stacked graphene layers are about 3 and 4.4 nm, indicating the existence of few-layer graphene. To further confirm the yield of graphene sheets, AFM measurement was performed on randomly selected 100 GNs, and the histogram of the layer distribution is shown in Figure 10. From the layer distribution, we can clearly see that more than 76% of the graphene sheets have fewer than five layers. All results are consistent with our theoretical simulations. Compared with previous reports, the advantages of ours are they are free of surfactants and organic solvents and does not require posttreatment. After the exfoliation process, the layers may restack together without the CO2 intercalation; but the interaction

Figure 8. (a,b) SEM images of graphite and GNs; (c,d) TEM images of graphite and GNs; and (e,f) Raman spectra of graphite and GNs.

The pristine graphite showed a typical smooth graphite surface in which graphite layers were stacked densely (Figure 8a). Wrinkles were clearly observed after the exfoliation process in the SEM image (Figure 8b), indicating that graphite has been exfoliated into few-layer GNs. From the TEM images (Figure 8c,d), it can be seen that the layer number before and after the exfoliation process clearly decreased, which is consistent with the SEM results. We also found that the D band (around 1351 cm−1) was slightly enhanced and ID/IG was increased in the F

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Langmuir *E-mail: yfl[email protected] (Y.L.). ORCID

Zhuo Chen: 0000-0002-0669-0044 Yongfeng Li: 0000-0003-0855-7949 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work is supported by the National Key Research and Development Program of China (2016YFA0602901), the National Natural Science Foundation of China (21673220, 21503210, 21521092, 21733004, 21576289, and 21776308), the Jilin Province N atural S cience Foundation (20150101012JC), and the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase). Part of the computational time is supported by the Performance Computing Center of Jilin University, Changchun Normal University, the High Performance Computing Center of Jilin Province, the Science Foundation of China University of Petroleum, Beijing (grant no. C201603), the Science Foundation Research Funds Provided to New Recruitments of China University of Petroleum, Beijing (grant no. 2462014QZDX01), and the Thousand Talents Program.

Figure 10. Histogram of the number of visual observation of flakes as a function of the number of layers of graphene per sheet made by AFM.

between layers may not be fixed as close as the vdW attraction and can be easily broken up.

4. CONCLUSIONS In this work, we performed nonequilibrium QM/MD simulations based on the DFTB potential to explore the mechanism of graphite exfoliation in the presence of scCO2 during the depressurization process. The dynamic process of graphite peeling was depicted, and the pressure effect was declared by inserting different numbers of CO2 molecules into graphite interlayers. The role of CO2 was also predicted. The simulation results highlighted that the fundamental driving force for graphite exfoliation is the repulsive interaction between CO2 and graphite because of the space hinder effect, attributed to the compressed (or inserted) CO2 molecules. On the other hand, the vdW interaction between the graphite interlayers is the major resistance for graphite exfoliation. Our calculated results showed that if the repulsive energy is not enough to overcome the vdW interaction, the graphite peeling will fail. Conversely, once the repulsive energy is larger than the vdW interaction, graphite exfoliation will occur. Furthermore, the higher the density of CO2, the quicker and more efficient is the exfoliation. Meanwhile, during the graphite exfoliation process the graphite could move along both lateral and vertical directions, fluctuated continually, and the inserted CO2 rotated and vibrated ceaselessly in between the layers of graphite. These movements consumed the remainder energy of the systems. We proposed that the prerequisite of graphite exfoliation was the pressure or density of CO2 being larger than 12.2 MPa or 0.21 g/cm3. This is verified by our experiments. In our experiment, the layer number of GNs has been obviously reduced and the yield of few-layer GNs has been enhanced. The current theoretical observation provides potential scientific evidence to control the graphite exfoliation by scCO2.

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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.8b01030. Interaction energies, total Mermin free energy, and the interlayer distance (PDF)

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REFERENCES

(1) Geim, A. K.; Novoselov, K. S. The Rise of Graphene. Nat. Mater. 2007, 6, 183−191. (2) Novoselov, K. S.; Geim, A. K.; Morozov, S. V.; Jiang, D.; Zhang, Y.; Dubonos, S. V.; Grigorieva, I. V.; Firsov, A. A. Electric Field Effect in Atomically Thin Carbon Films. Science 2004, 306, 666−669. (3) Schedin, F.; Geim, A. K.; Morozov, S. V.; Hill, E. W.; Blake, P.; Katsnelson, M. I.; Novoselov, K. S. Detection of Individual Gas Molecules Adsorbed on Graphene. Nat. Mater. 2007, 6, 652−655. (4) Bunch, J. S.; Van Der Zande, A. M.; Verbridge, S. S.; Frank, I. W.; Tanenbaum, D. M.; Parpia, J. M.; Craighead, H. G.; McEuen, P. L. Electromechanical Resonators from Graphene Sheets. Science 2007, 315, 490−493. (5) Patchkovskii, S.; Tse, S. T.; Yurchenko, S. N.; Zhechkov, L.; Heine, T.; Seifert, G. Graphene Nanostructures as Tunable Storage Media for Molecular Hydrogen. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 10439−10444. (6) Li, X.; et al. Large-Area Synthesis of High-Quality and Uniform Graphene Films on Copper Foils. Science 2009, 324, 1312−1314. (7) Boukhvalov, D. W.; Katsnelson, M. I. Modeling of Graphite Oxide. J. Am. Chem. Soc. 2008, 130, 10697−10701. (8) Hummers, W. S., Jr; Offeman, R. E. Preparation of Graphitic Oxide. J. Am. Chem. Soc. 1958, 80, 1339. (9) Rangappa, D.; Sone, K.; Wang, M.; Gautam, U. K.; Golberg, D.; Itoh, H.; Ichihara, M.; Honma, I. Rapid and Direct Conversion of Graphite Crystals into High-Yielding, Good-Quality Graphene by Supercritical Fluid Exfoliation. Chem.Eur. J. 2010, 16, 6488−6494. (10) Hadi, A.; Karimi-Sabet, J.; Moosavian, S. M. A.; Ghorbanian, S. Optimization of Graphene Production by Exfoliation of Graphite in Supercritical Ethanol: A Response Surface Methodology Approach. J. Supercrit. Fluids 2016, 107, 92−105. (11) Liu, C.; Hu, G.; Gao, H. Preparation of Few-Layer and SingleLayer Graphene by Exfoliation of Expandable Graphite in Supercritical N,N-Dimethylformamide. J. Supercrit. Fluids 2012, 63, 99− 104. (12) Pu, N.-W.; Wang, C.-A.; Sung, Y.; Liu, Y.-M.; Ger, M.-D. Production of Few-Layer Graphene by Supercritical Co2 Exfoliation of Graphite. Mater. Lett. 2009, 63, 1987−1989. (13) Gao, H.; Hu, G. Graphene Production Via Supercritical Fluids. RSC Adv. 2016, 6, 10132−10143.

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DOI: 10.1021/acs.langmuir.8b01030 Langmuir XXXX, XXX, XXX−XXX

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Langmuir (14) Gao, Y.; Shi, W.; Wang, W.; Wang, Y.; Zhao, Y.; Lei, Z.; Miao, R. Ultrasonic-Assisted Production of Graphene with High Yield in Supercritical CO2 and Its High Electrical Conductivity Film. Ind. Eng. Chem. Res. 2014, 53, 2839−2845. (15) Gomez-Ballesteros, J. L.; Callejas-Tovar, A.; Coelho, L. A. F.; Balbuena, P. B. Molecular Dynamics Studies of Graphite Exfoliation Using Supercritical CO2. Design and Applications of Nanomaterials for Sensors; Springer: Netherlands, 2014; pp 171−183. (16) Gai, Y.; Wang, W.; Xiao, D.; Zhao, Y. Ultrasound Coupled with Supercritical Carbon Dioxide for Exfoliation of Graphene: Simulation and Experiment. Ultrason. Sonochem. 2018, 41, 181−188. (17) Xu, X.; Cai, L.; Zheng, X.; Xu, Q. Molecular Dynamics Simulations of Solvent-Exfoliation and Stabilization of Graphene with the Assistance of Compressed Carbon Dioxide and Pyrene-Polyethylene Glycol. Phys. Chem. Chem. Phys. 2017, 19, 16062−16070. (18) Shang, T.; Feng, G.; Li, Q.; Zheng, Y. Production of Graphene Nanosheets by Supercritical Co2 Process Coupled with Micro-Jet Exfoliation. Fullerenes, Nanotubes, Carbon Nanostruct. 2017, 25, 691− 698. (19) Chen, Z.; Miao, H.; Wu, J.; Tang, Y.; Yang, W.; Hou, L.; Yang, F.; Tian, X.; Zhang, L.; Li, Y. Scalable Production of Hydrophilic Graphene Nanosheets Via in Situ Ball-Milling Assisted Supercritical Co2 Exfoliation. Ind. Eng. Chem. Res. 2017, 56, 6939−6944. (20) Song, N.; Jia, J.; Wang, W.; Gao, Y.; Zhao, Y.; Chen, Y. Green Production of Pristine Graphene Using Fluid Dynamic Force in Supercritical CO2. Chem. Eng. J. 2016, 298, 198−205. (21) Li, L.; et al. Preparation of Graphene Nanosheets by ShearAssisted Supercritical CO2 Exfoliation. Chem. Eng. J. 2016, 284, 78− 84. (22) Cazorla-Amorós, D.; Alcaniz-Monge, J.; De la Casa-Lillo, M. A.; Linares-Solano, A. Co2 as an Adsorptive to Characterize Carbon Molecular Sieves and Activated Carbons. Langmuir 1998, 14, 4589− 4596. (23) Gao, H.; Xue, C.; Hu, G.; Zhu, K. Production of Graphene Quantum Dots by Ultrasound-Assisted Exfoliation in Supercritical CO2/H2O Medium. Ultrason. Sonochem. 2017, 37, 120−127. (24) Jeon, I.-Y.; et al. Edge-Carboxylated Graphene Nanosheets Via Ball Milling. Proc. Natl. Acad. Sci. U.S.A. 2012, 109, 5588−5593. (25) Wu, B.; Yang, X. A Molecular Simulation of Interactions between Graphene Nanosheets and Supercritical CO2. J. Colloid Interface Sci. 2011, 361, 1−8. (26) Shih, C.-J.; Lin, S.; Strano, M. S.; Blankschtein, D. Understanding the Stabilization of Liquid-Phase-Exfoliated Graphene in Polar Solvents: Molecular Dynamics Simulations and Kinetic Theory of Colloid Aggregation. J. Am. Chem. Soc. 2010, 132, 14638. (27) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, T.; Suhai, S.; Seifert, G. Self-Consistent-Charge DensityFunctional Tight-Binding Method for Simulations of Complex Materials Properties. Phys. Rev. B: Condens. Matter Mater. Phys. 1998, 58, 7260−7268. (28) Weinert, M.; Davenport, J. W. Fractional Occupations and Density-Functional Energies and Forces. Phys. Rev. B: Condens. Matter Mater. Phys. 1992, 45, 13709−13712. (29) Wentzcovitch, R. M.; Martins, J. L.; Allen, P. B. Energy Versus Free-Energy Conservation in First-Principles Molecular Dynamics. Phys. Rev. B: Condens. Matter Mater. Phys. 1992, 45, 11372−11374. (30) Jiao, M.; Qian, H.; Page, A.; Li, K.; Wang, Y.; Wu, Z.; Irle, S.; Morokuma, K. Graphene Nucleation from Amorphous Nickel Carbides: Qm/Md Studies on the Role of Subsurface Carbon Density. J. Phys. Chem. C 2014, 118, 11078−11084. (31) Wang, Y.; Gao, X.; Qian, H.-J.; Ohta, Y.; Wu, X.; Eres, G.; Morokuma, K.; Irle, S. Quantum Chemical Simulations Reveal Acetylene-Based Growth Mechanisms in the Chemical Vapor Deposition Synthesis of Carbon Nanotubes. Carbon 2014, 72, 22−37. (32) Wang, Y.; Page, A. J.; Li, H.-B.; Qian, H.-J.; Jiao, M.-G.; Wu, Z.J.; Morokuma, K.; Irle, S. Step-Edge Self-Assembly During Graphene Nucleation on a Nickel Surface: Qm/Md Simulations. Nanoscale 2014, 6, 140−144.

(33) Wang, Y.; Page, A. J.; Nishimoto, Y.; Qian, H.-J.; Morokuma, K.; Irle, S. Template Effect in the Competition between Haeckelite and Graphene Growth on Ni(111): Quantum Chemical Molecular Dynamics Simulations. J. Am. Chem. Soc. 2011, 133, 18837−18842. (34) Page, A. J.; Wang, Y.; Li, H.-B.; Irle, S.; Morokuma, K. Nucleation of Graphene Precursors on Transition Metal Surfaces: Insights from Theoretical Simulations. J. Phys. Chem. C 2013, 117, 14858−14864. (35) Swope, W. C.; Andersen, H. C.; Berens, P. H.; Wilson, K. R. A Computer Simulation Method for the Calculation of Equilibrium Constants for the Formation of Physical Clusters of Molecules: Application to Small Water Clusters. J. Chem. Phys. 1982, 76, 637− 649. (36) Martyna, G. J.; Klein, M. L.; Tuckerman, M. Nosé−Hoover Chains: The Canonical Ensemble Via Continuous Dynamics. J. Chem. Phys. 1992, 97, 2635−2643. (37) Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865−3868. (38) Kresse, G.; Furthmüller, J. Efficiency of Ab-Initio Total Energy Calculations for Metals and Semiconductors Using a Plane-Wave Basis Set. Comput. Mater. Sci. 1996, 6, 15−50. (39) Kresse, G.; Hafner, J. Ab Initio Molecular Dynamics for Liquid Metals. Phys. Rev. B: Condens. Matter Mater. Phys. 1993, 47, 558−561. (40) Kresse, G.; Hafner, J. Ab Initio Molecular-Dynamics Simulation of the Liquid-Metal−Amorphous-Semiconductor Transition in Germanium. Phys. Rev. B: Condens. Matter Mater. Phys. 1994, 49, 14251−14269. (41) Kresse, G.; Furthmüller, J. Efficient Iterative Schemes for Ab Initio Total-Energy Calculations Using a Plane-Wave Basis Set. Phys. Rev. B: Condens. Matter Mater. Phys. 1996, 54, 11169−11186. (42) Monkhorst, H. J.; Pack, J. D. Special Points for Brillouin-Zone Integrations. Phys. Rev. B: Solid State 1976, 13, 5188−5192. (43) Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. A Consistent and Accurate Ab Initio Parametrization of Density Functional Dispersion Correction (DFT-D) for the 94 Elements H-Pu. J. Chem. Phys. 2010, 132, 154104. (44) Grimme, S. Semiempirical Gga-Type Density Functional Constructed with a Long-Range Dispersion Correction. J. Comput. Chem. 2006, 27, 1787−1799. (45) Sasikala, S. P.; Poulin, P.; Aymonier, C. Prospects of Supercritical Fluids in Realizing Graphene-Based Functional Materials. Adv. Mater. 2016, 28, 2663−2691. (46) Cançado, L. G.; Takai, K.; Enoki, T.; Endo, M.; Kim, Y. A.; Mizusaki, H.; Jorio, A.; Coelho, L. N.; Magalhães-Paniago, R.; Pimenta, M. A. General Equation for the Determination of the Crystallite Size La of Nanographite by Raman Spectroscopy. Appl. Phys. Lett. 2006, 88, 163106.

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DOI: 10.1021/acs.langmuir.8b01030 Langmuir XXXX, XXX, XXX−XXX