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Revealing Factors Governing Self-Assembly Morphology of Fatty Acid on Graphene Synthesized by SurfactantAssisted LPE: A Joint MD, SAPT(DFT) and Experimental Study Soheila Javadian, and Mahnaz Khosravian J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b05057 • Publication Date (Web): 28 Aug 2018 Downloaded from http://pubs.acs.org on September 1, 2018

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The Journal of Physical Chemistry

Revealing Factors Governing Self-Assembly Morphology of Fatty Acid on Graphene Synthesized by Surfactant-Assisted LPE: A Joint MD, SAPT(DFT) and Experimental Study Soheila Javadian∗ and Mahnaz Khosravian Department of Chemistry, Tarbiat Modares University, P.O. Box 14115-175, Tehran, Iran E-mail: javadian [email protected]

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Abstract The production of graphene nanosheets from graphite with the assistance of biological molecules in water medium as well as understanding the morphology of the resulted self-assembly are important in fields of drug delivery, cellimaging and photothermal therapy. Hence, in this contribution, we have applied Docosahexaenoic acid (DHA) fatty acid to disperse graphite. The morphology of self-assembly on the graphene surface and the factors tailoring the morphology were surveyed in light of classical molecular dynamic (MD) and symmetry-adapted perturbation theory (SAPT). The factors such as surface density, environment pH, substrate size and number of layer were taken into account. The results show that the decrease in pH transmutes the nature of the classical electrostatic interaction between the surfactants from repulsion to attraction, leading to a decline in the stability of the colloidal systems. When the lateral size of the graphene sheet is three times larger than the length of DHA, hemicylinder structures with a 3.5-4 nm width are formed, which is in an excellent agreement with AFM result. The simulation of the effect of number layer reveals that the LPE cannot be initiated without ultrasonic assistant. An arsenal of experimental methods including HR-TEM, TEM, AFM, XPS, UV-Vis and zeta potential confirms the existence of colloidal systems with graphene sheet. The dispersion of graphene using DHA largely preserves the intrinsic chemical structure of graphene. This combined experimental and computational study will be a valuable contribution to the dispersion of graphene by means of fatty acids, which could be utilized in medical purposes.

Introduction Graphene as one of the carbon allotropes, having hexagonal network of sp2 carbon atoms, has gained massive attention due to its unique properties such as outstanding electrical and thermal conductivities. 1–3 However, the production of few layer graphene is of paramount importance to get most of graphene advantageous. To this end , two general strategies have been proposed to achieve single and few-layer graphene, called bottom-up (BU) and top-down 2


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(TD) methods. 4–6 These two strategies follow two different paths to reach few layer graphene. In BU methods, the aim is to gain graphene from smaller carbon building blocks, 5 while in TD methods, which are nano-fabrication, graphene is cut out from the larger species, i.e., graphite. 4 The detailed explanation as well as their advantageous and limitations may be found in ref 4 and ref. 6 Generally specking, simplicity, cost, scalability and the uniformity of the product direct attention to TD methods. To transform graphite to graphene, the attractive London forces (dispersion forces) between the pile of graphene layers in the graphite structure should be counterbalanced by an opposite potential. 7 Liquid-phase exfoliation method (LPE) technique, 4,7–11 which is categorized as TD strategy, may provide necessary forces to break down the attractive interactions between the graphene layers. 7 The utilization of a proper solvent as a medium is a key in LPE technique. 12 When the desire is to use the dispersed graphene in bio-systems, water is an ideal choice due to its high compatibility as well as non-toxicity. Nevertheless, the hydrophobic character of graphite and graphene prevents them to dissolve in water. 13,14 In addition, the water-graphene interactions 15,16 are not able to overcome π-π stacking interactions 17 between graphene layers. Hence, to conquer the barriers to use water, the utilization of surfactants as stabilizer and dispersing agents is a wise selection. 9 Since the surfactants directly cover the surface of graphene during LPE procedure in a non-covalent fashion 18 without damaging sp2 carbon network of graphene, they may bring new functionality to the graphene. Therefore, needless to say that the choice of biosurfactant or biomolecules is a smart selection because it provides opportunity to apply graphene in biological systems. 19 For instance, heparin, 20 dopamine, 21,22 tryptophane, 23 hemin, 24 PEG 25 and DNA 26 were applied for non-covalent functionalization of graphene. Graphene can be used as platform for drug delivery in therapeutic protocol. 27 Ramisol with antimicrobial and antioxidant activity as drug can be attached to graphene. 28 In addition, noncovalently functionalized graphene with biomolecule may be used as biosensore, cellimaging, 29–32 photothermal therapy. 19

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Due to the vast applications of the covered graphene with biomolecules as well as interest in this field of research, herein, the exfoliation of graphene by docosahexaenoic acid (DHA) in water is studied. DHA as polyunsaturated fatty acid is a structural component of neuronal membranes, which its presence in diet prevents human disorders including cardiovascular disease and cancer. 33 DHA can form vecicles, what makes it a suitable candidate for drug delivery. 34 The experimental methods were utilized to confirm the dispersion of graphene. However, the self-assembly morphology of DHA depends on pH. Therefore, the study of morphology on a molecular level in different pH can be helpful to deepen our knowledge about the dispersion process. For this purpose, with the help of MD simulation, the morphology of self-assembly has been studied by changing parameters such as density surface, pH, lateral size and number of layer for graphene. Additionally, SAPT(DFT) 35–38 was utilized to furnish the information on the forces which govern DHA assembly behaviour, where SAPT(DFT) tells us the critical role of classical electrostatic energy in the morphology. Our results from theoretical and experimental both confirm that it is possible to prepare few layers graphene coated with DHA, which may be utilized in biological applications.

Method Outline Computational Details The DHA molecules, Na+ and graphene sheet were accommodated in simulation box contained water molecules by means of VMD program. 39 The graphene carbon atoms were considered as uncharged Lennard-Jones spheres, where the graphene sheet was kept rigid and fixed in the center of the box. The carbon atoms on the edge of the graphene sheet are the same as the central carbon atoms. 40 The TIP3P moldel was used to model water molecules. 41 The DHA molecules were positioned perpendicularly to the graphene sheet. 42,43 The anionic form of DHA and Na+ were modeled utilizing CHARMM27 force field, 44 while CHARMM General Force Field (CGenFF) was used for neutral DHA. 45 Periodic boundary 4


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conditions were considered in three direction x,y and z, and long range electrostatic forces were computed using Particle Mesh Ewald(PME) . 46 Nonbonded interactions between the particles were described by Lennard-Jones potential, where van der Waals attraction and steric repulsion were computed with cut off 10˚ A. 47 The box size of the various system are presented in Table ST1 of the supporting of information. In order to achieve the equilibrium volume of the systems, the simulations were initially performed in NPT ensemble T = 300k, P = 1atm with time step 1fs for 1ns, and then the simulations were continued in NVT ensemble for 40ns. The simulations were carried out by means of NAMD. 48,49 To gain a physical insight into the forces governing the interactions between DHA molecules, SAPT(DFT) 35–37,50 was applied, where the monomers were described by means of asymptotically corrected PBE0 (PBE0AC) functional. 51,52 To obtain AC, G¨ urling et al. method 53 was used. SAPT(DFT) provides the interaction energies between two species as physically meaningful contributions: electrostatic, induction, dispersion and their exchange counterparts as below: SAPT(DFT)

Eint

(1)

(1)

(2)

(2)

(2)

(2)

= Eelst + Eexch + Eind + Eexch−ind + Edisp + Eexch−disp + δEHF .

(1)

The δEHF 54 is an estimation of third and higher order exchange and induction terms. It has been shown that SAPT(PBE0AC) provides the interaction energies comparable with state-of-art CCSD(T) 38,55,56 and SAPT(CCSD) 57 methods. Among the SAPT(DFT) terms, (2)

(2)

Edisp and Eexch−disp contributions exhibit the slowest convergence. 58–60 Hence, to saturate them, it is quite necessary to utilize basis set with large cardinal number enriched by diffuse functions. 60 However, the utilization of large basis set for large systems almost is not possible. Therefore, Heßelmann and Korona 60 have proposed a short-cut route to saturate the terms (1)

(1)

(2)

(2)

in the framework of two-point extrapolation. In their scheme, Eelst , Eexch , Eind and Eexch−ind (2)

(2)

are calculated in cc-pVTZ basis set, while the Edisp and Eexch−disp are estimated by means of cc-pVDZ→cc-pVTZ extrapolation scheme 61,62 scaled by a factor 1.08. The 1.08 factor is

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used to compensate the lack of the diffuse functions in the basis sets. It has been shown that this strategy provides the interaction energies with aug-cc-pVQZ quality. 60,63 Therefore, we have: SAPT(DFT)

Eint

(CBS) ≈ ESAPT(DFT) (VTZ) noncorr

(VDZ→VTZ)×1.08, +ESAPT(DFT) corr

(2)

The 1s orbitals of carbon and oxygen atoms were frozen. 64 The SAPT(DFT) calculations were performed using Molrpo. 65

Experimental Details The graphite powder, Na3 PO4 and DHA were purchased from Sigma Aldrich. Doubly distilled method was used to make solution. UV-Vis spectra were recorded using a Shimatzu 2100 UV-Vis spectrophotometer in 200-800 nm. Zeta potential was measured by means of Molvern zeta sizer (model nano-zs). Transmission electron microscopy (TEM) and its high-resolution varient, i.e., HR-TEM, were carried out using ZEISS electron microscopy (CM30 300K) and JEOL, JEM-2100F, 200KV TEM respectively. X-ray photoelectron spectroscopy (XPS) was performed by Thermo scientific, ESCLAB 250Xi , and finally, atomic force microscopy (AFM) analyses were done with (spm VEECO). In order to disperse the graphite, the required mass of graphite at a specific pH was added to a certain concentration of the DHA solution. The concentration of surfactant, CSur , initial concentration of graphite , CGi , pH, and ultrasonic time at 90 w, t, are the parameters which are usually considered in the process of dispersion. Hence, after a through examinations, the CGi = 1mg/ml, CSur = 9 × 10−2 mM or critical micelle concentration (CMC), t = 14h and pH = 11.5 were chosen as the standard parameters. To separate the large particles of graphene, the resulted solution was centrifuged for 20 min with 3000 rpm. The supernatant was used for the analyses.

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Result and discussion This part is categorized in two sections: first, the results from the MD simulations and SAPT(DFT) calculations are discussed, and then the experimental results are presented.

MD and SAPT(DFT) calculations Density surface In the surfactant-based dispersion of graphene, the solution should be sonicated to overcome van der Waals forces holding the graphene sheets together, 66 however, the sonication leads to a random distribution of the surfactant molecules in the bulk. Therefore, a deep understanding of the adsorption and self-assembly process of the surfactants over the graphene sheet is quite necessary to perform an effective dispersion. 67 Hence, in this contribution, we will study the self-assembly process of DHA anion on graphene sheet. Due to the lack of experimental data on the surface density of DHA on the graphene surface, we have investigated the surface densities of 1.24 (48 DHA), 1.06 (56 DHA), 0.53(112 DHA), and 0.40(148DHA) nm2 /molecule. 68 To study the surface density, we used a graphene with dimension of 5.5×5.4 nm2 . In all the cases, the surfactants were perpendicularly positioned in a certain distance from the graphene surface. 42,43 The DHA molecules are flexible in the water bulk due to the long hydrophobic tail. 69 Hence, to figure out the self-assembly of surfactants in the equilibrium, we used the numeric value of root-mean-square-deviation, RMSD, which is defined as below: 39

RMSD(t) = [1/Natoms

NX atoms

|ri (t) − ri (0)|2 ]1/2

(3)

i=1

Where ri (t) represents the position of atom i at time (t) which is compared to its initial position, , i.e., ri (0). It should be kept in mind that the values of RMSD depend on the initial structure of molecules, 70,71 and consequently the RMSD values were utilized to achieve the

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equilibrium, not to analyze the structures. In general, RMSD analyzes have been performed to accommodate the mobility and displacement of the desired components of the systems with respect to the initial state. 70 When there is no significant change in the value of RMSD, the system meets its equilibrium, and the simulation will finish. In general, if RMSD of atomic coordinates fluctuates between 0.5-3 ˚ A relative to the average or experimental values, 72–74 the desired components reach the equilibrium. Herein, the standard deviation of RMSDs is less than 1 ˚ A, unless otherwise mentioned. The values of RMSD of the simulation time as well as average RMSD, av.RMSD, are shown in Figure 1a. As seen from Figure 1a, the system including 112 molecules DHA has the lowest av.RMSD value. It is helpful to take a look at the interaction energy between surfactants and the graphene surface. As seen from Figure 1b, the interaction energy increases slightly after the 56DHA system. 67,75,76 This could indicate that the surface of graphene has been already covered with 56 DHA molecules, and its morphology is monolayer, where the first layer molecules have in absolute values the largest interaction energy with the surface of graphene. In order to provide a proof for the statement, we should pay attention to the density profile for various density surface. In the density profile of the water without the DHA molecules as depicted in Figure 1c, a sharp peak of water is observed at 4 ˚ A2 which indicates the presence of water molecules adjacent to the graphene sheet. 68 In the same figure, for the 56DHA systems, we do not observe the sharp peak, showing the coverage of the graphene surface by the DHA molecules. Furthermore, the density profile of head group for the 56DHA system depicted in Figure 1d shows the monolayer structure, where the half of the head groups point at the graphene surface and the rest point at the water bulk, however, their values decline to zero at a distance of 14˚ A from the surface. This profile shows that the thickness of the layer is 14˚ A and since the thickness of graphene sheet is 4˚ A, it can be concluded that the morphology thickness formed on the graphene sheet is 12˚ A. In this surface density, the density of tail group decreases to zero at z=10˚ A (see Figure 1f), indicating about 4˚ A of the morphology thickness is formed due to the arrangement of the head group. This arrangement adds 4˚ A

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to the thickness of the layer. 77 Almost the same aspects are observed for the 48DHA system, however, by comparison of the first peak of water density, it can be realized that in the 48DHA system, the surface of graphene is hydrated by water molecules. Nevertheless, its intensity decreases in the 56DHA system, what can be attributed to this fact that the graphene surface is covered by DHA molecule. Figure 1d shows the head group density profile for the 112DHA system. The very close consecutive peaks give the information on the formation of hemispherical structure with a height of 22˚ A on the graphene surface. In the same figure, for the 148DHA system, as the number of DHA molecules increases, the third peak of the head group density is more spaced than the last peak of the 112DHA system. It shows that the morphology is separated from the hemispherical position, and consequently it is more extended along the z axis. As seen from Figure 1g, the sharp peaks of the density profile of Na+ are observed at the distance at which the head density is also maximum. This consistency shows that Na+ ions tend to accumulate in the vicinity of the head group. In the case of graphene monolayer, the selfassemblies on the two sides of graphene repel each other via their head groups as the density surface increases. This repulsion prevents the graphene from being encapsulated. Therefore, the graphene edge remains bare and adjacent to water. The snapshot in Figure 1e can be a visual description for the morphology. The lowest av.RMSD value for 112DHA system indicates the lowest surfactant mobility on the graphene surface, revealing formation of a stable morphology. In summary, the 56DHA system is monolayer, while 112DHA system has hemispherical structure. The trend of surface density results for the non-toxic anionic DHA surfactants on the graphene surface is consistent with SDS, 40,42 SDBS 68 and SC 77 anionic surfactants on the graphene/graphite surface. The height of monolayer morphology is different from that for the anionic surfactants, where the increase in morphological height can be attributed to the flexibility of the DHA molecule, which causes the head groups are further exposed to the water, and subsequently the tail groups better cover the hydrophobic surface of graphene. Therefore, DHA molecule similar to the other anionic surfactants can

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adsorb on the graphene sheets and disperse them.

pH effect The influence of pH on the morphology of DHA is an interesting topic which reveals how the systems respond to the environmental condition changes. Walde et al.

78

have shown

that the DHA molecules undergo a phase transition in the pH between 11.5 and 8.8, where the two points coincide with the CMC and critical vesicle concentration (CVC) of DHA, respectively. Hence, we have surveyed the effect of pH on the morphology of DHA molecules on the graphene surface between the two points 79 for all the surface densities by the help of the ratio obtained from pKa, which contained the values 1:0, 2:1 , 1:1 and 1:2 ionic form to the neutral form of the DHA molecules, 78,80 which are equal to pH of 11.5, 8.8, 8.5 and 8.2, respectively. It can be deduced from the density profile of the head groups, depicted in Figure 2a, the change in morphology is governed by the evolution in the arrangement of the head groups. 42 As seen from Figure 2a, in the density profile of head group of 112DH system, the decrease in the intensity of the peaks as well as the shift of them from 18 to 14˚ A clearly clarify that the structures gets more compact arrangement from pH 11.5 to 8.2, which also reveals that the structures are not hemispherical any longer (see Figure 2c). As previously mentioned, RMSD shows displacement of atoms relative to the initial structure. Therefore, since the initial state of the four systems were almost the same, the lowest av.RMSD confirms that atomic coordinates undergo less variation, and consequently the system will be stable earlier. Additionally, the RMSD for the four pH points (see Figure SF2a) accounts for the occurrence of the most stable morphology at pH=11.5. The radial distribution functions (RDFs) of the water molecule with head and tail groups in the different pH 81 are depicted in Figure SF2b to show how the water molecules interact with the self-assembly. As seen from Figure SF2b, the first solution shell was formed about 1.8 ˚ A from the anionic carbonyl groups, conforming the hydrogen bonding contact (O − Hδ+ · · ·Oδ− ) 82 between the water molecules and the anionic carbonyl groups. 83 In addi-

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tion, the intensity of RDF of the anionic head groups increases as pH decreases. It shows that the Na+ ions have been replaced by the water molecules in the vicinity of the head groups. 43 However, the RDF of the tail groups reveals that no obvious shell is formed around the tail groups, what is expected due to the hydrophobocity character of the tail groups. The decrease in the peak intensity of the neutral head group indicates that the neutral head groups are less exposed to water molecules compared to the anionic head groups, showing a lose in the importance of the hydrogen bonding between the head groups and water. The UV-Vis spectrum, which will be discussed in the experimental section, shows a decrease in the yield of the dispersed graphene at pH=8.8. Therefore, to furnish an appropriate reason for the blockage of the graphene dispersion at an atomistic level, we direct our attention to the interaction between the graphene and the surfactants. As seen from Figure 2b, the overall trend is: in parallel with the decrease in pH, the average of interaction energy of DHA with graphene decreases. Thus far it has been uncovered that the head groups play a guiding role in the morphology transformation. As seen from Figure 2b (av.Eint(headgroup) ), the negative charge of the head groups leads to a repulsive electrostatic interaction between them, what forces some of the head groups to be located adjacent the graphene sheet. However, for the systems containing the different ratio of the neutral form of the DHA molecules, i.e., in the low pH, the head groups tend to create a hydrogen bond linkage with the anionic form, leading to a decrease in the density of the head groups around the graphene sheet. However, it should be noticed that pointing the head groups towards the graphene sheet should not be deduced as a result of the direct attractive interaction between the head groups and the graphene sheet. As Yourdkhani and co-workers 63 shown via the dissection of the atom-atom interaction energy, there is a strong classical repulsion electrostatic interaction between the oxygen atom with sp2 hybridization and the graphene sheet, where the electron-sharing is not able to quench the repulsive force. Hence, the arrangement of some of the head groups over graphene sheet is a result of all the acting forces in the solution. Therefore, the reason for the stability

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of the surfactants over the graphene is the tail groups, which are attached to the graphene sheet via the attractive σ/σ, σ/π and π/π forces, which are mainly dispersion in nature. 84 All in all, it can be concluded that the surfactants at CVC point, i.e., at pH=8.8, tend to be less adsorbed on the graphene, making pH=8.8 a unsuitable point to perform the graphene dispersion by means of DHA. As the pH decreases, DHA molecules become neutral, and prefer to interact with the other neutral DHA molecules, resulting in a reduction in the dispersion of graphene. As discussed, the MD has attributed this behaviour to the electrostatic interaction. It is informative to consider the pH effect from the SAPT(DFT) standpoint. Figure 3 depicts the SAPT(DFT) total energies and their components for the anionic-anionic, anionic-neutral, and neutralneutral DHA dimers. The molecular graphs of the dimes are depicted in Figure ST1. It should be mentioned that in order to recover all the aspects of what occurs in the solution, the interaction energy of the DHA with graphene as well as the non-additivity effects should have been taken into account. However, due to the size of the systems, the SAPT(DFT) calculations in a flexible basis set were out of reach. From the SAPT(DFT) point of view, if one goes from the anionic dimer to the neutral DHA dimer, the strong Coulomb repulsion changes to the attractive classical Coulomb energy. In addition, the net dispersion energy, (2)

(2)

i.e., Edisp +Eexch−disp , changes from -13 to -21 kcal/mol with a cost in Pauli repulsion. Hence, the decrease in pH vanishes the electrostatic repulsion between DHA molecules. In sharp contrast to the anionic DHA molecules which strongly tend classically to repel each other, the SAPT(DFT)

neutral DHA molecule strongly attract each other (Eint

= −11.5 kcal/mol). There-

fore, it can be concluded that the convert in the nature of the classical Coulomb energy from repulsive to attractive may be a reason for the decline in graphene dispersion. It is likely that the negative electrostatic interaction enables the neutral DHA molecules to attract each other, leading to the agglomeration, and consequently the reduction in the graphene dispersion.

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Effect of substrate size Not only does the morphology of the aggregation on the graphene surface depend on the surfactant concentration, but it also shows the substrate size dependency. The different lateral size 85–87 in graphene and graphite leads to the different morphologies. 67,83,88 To better understand the effect of graphene size on the morphology, the systems with different graphene sheet size 3×3.3, 5.5×5.4 and 8×8 nm2 - which have the same surface density (0.40 molecule/nm2 ) were simulated. As depicted in Figure 4a, the peaks of the density profile may be used to interpret the morphology of the self-assembly. The several downtrend peaks in the profile of graphene 3×3.3 nm2 point at a multi-layer structure, 88 while the peaks with the same increasing intensity imply hemicylindrical structure for the 8×8 nm2 model of graphene. 43,67 The graphene sheets of 5.5×5.4 nm2 were discussed in the density surface section. Therefore, the size of graphene governs the morphology of DHA molecules. 88,89 To corroborate the MD prediction, the AFM plot is shown in Figure 4b. Interestingly, the MD shows that the width (priodicity) and height of hemicylindrical structures are about 3.5-4 and 2.2 nm, respectively, 12,90,91 what is in an excellent agreement with those from our AFM results (3.8 and 2.2 nm respectively). This agreement validates the results from our MD simulations. The comparison of the morphology of DHA with the SDS morphology on interface of water and graphene/graphite 40,42,43,88,92 shows that the double bonds of DHA leads to twisted structures, and consequently smaller priodicity. The decrease in priodicity provides perfect hemicylincal structures which decrease the contact of the hydrophobic tail and of graphene surface with water, leading to stable structures.

Effect of layer number It is interesting to find out to what extend the increase in the number of graphene layers affects the morphology. To do this, the mono-layer, bilayer and four layers 5.5×5.4 nm2 graphene sheet with AB stacking pattern were chosen, 93 however, the rest of the system conditions such as the box dimensions along x, y and z axes as well as the number of sur13



factants were fixed. 94 Figure 5a illustrates how the surfactants distribute over the graphene sheets as the number of graphene layer increases. As seen from SF3b, as the number of the layers increases, the system loses its stability. 9 Interestingly, the interaction energy between the DHA molecules and the graphene layers

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in the bilayer system is in absolute

value less than those for mono and four layers systems. To gain insight into the smaller interaction energy, the density profiles of the head groups and water molecules are depicted in Figure 5b and c, respectively. It can be seen that the head groups tend to locate at the edge of graphene, and consequently more exposure to water. This arrangement leads to the decrease in DHA-graphene repulsion. It is also almost the case for the four layers system. Therefore, from one to four layers systems, the edge tendency of the surfactants damages the hemispehrical structure, and increases the surfactant-water contact (see Figure 5d). All in all, from the results of this part as well as of pH section, the initial force for dispersion comes from sonication, and after that the head-head repulsion is the force which keeps the graphene layers apart.

Distance effect Before discussing the experimental section, it is worth emphasizing that ultrasonic has assisted the LPE method. Hence, it is expected that the ultrasonic causes the covered-DHA few layers of graphene to be positioned in different distance, d, from each other. 77 To model influence of ultrasonic, two graphene sheets having surface density 1.06 nm2 /molecule or 56 DHA were selected. 42 The graphene sheets were placed in simulation box with specified distance of 32, 25 and 18 ˚ A from each other. The simulation were done for 1ns in NPT ensemble and continued for 40ns in NVT ensemble. Figure 6a shows that as distance decrease, the self-assemblies start affecting each other. The self-assembly is not monolayer henceforth and appears as a multi-layerd wall confined between two graphene sheets. 76,77 The contour plot of water depicted in Figure 6b reveals when d≥24 ˚ A, the density of water between graphene sheet is equal to the bulk density. Hence, for d≥24˚ A, the electrostatic repulsion

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created by double layer on the outer layers of self-assemblies, prevents the agglomeration of graphene sheet. However, as distance decreases, since water molecules unlike the surfactants do not have affinity to graphene sheets, 77 migrate from the space between the two graphene sheets. For d=18˚ A, some of DHA ions desorbing from graphene surface fill the empty spaces. As shown from the contour plot DHA in outer surface of graphene (see Figure 6c), DHA monolayer has maximum value in z≤4˚ A, while this structure was disappeared between the two graphene sheet and appeared as a multi-layer wall. Hence, Na+ ions settle between the multi-layer wall screening the electrostatic repulsion of head groups. At this distance electrostatic repulsion of double layer are replaced by short-range steric repulsion effect of multi-layer confined between graphene sheets, preventing the agglomeration of graphene few layers. The increase in Pauli repulsion at short distances can be naively understood from the two-body SAPT(DFT) calculations (see Figure 3), where the more compact neutral DHA dimer leads to larger exchange energy. Therefore, the distance between graphene sheet determines which factor, i.e., the long-range electrostatic or steric repulsion, prevents agglomeration of graphene few layers. Additionally, it is expected that at short distance the short-range electrostatic energy, i.e., charge penetration, 95 would help the agglomeration.

The experimental investigation UV-Vis and XPS survey To identify the graphene in the solution, the UV-Vis spectrum of the solution in different conditions are shown in Figure 7. The distinguished peak around 268 nm is related to ππ ∗ transition as the signature of graphene structure. The change in the absorbance value at 680 nm has indicated an increase or a decrease in concentration of graphene. 79,96,97 Monitoring the dispersion process as the parameters vary reveals that the highest absorbance peak is observed when pH and DHA concentration are set to 11.5 and CMC, respectively. This finding not only confirms the MD prediction, but also shows that the optimum condition to disperse graphene by DHA is achieved at pH=11.5 and the CMC concentration. It should be parenthetically mentioned that doubling the ultrasonic 15



time doubled the UV-Vis spectrum intensity. 98 The experimental results have shown that CMC point, which corresponds to pH=11.5, is an optimum condition to perform the graphene dispersion. The yeild of graphene exfoliation, YW (%), which is obtained from the ratio of the weight of graphene dispersed to the initial weight of graphite, and is ca. 19 % . 99 As discussed in pH section, the anionic character of DHA molecules at CMC, and consequently classical repulsion between them keeps the dispersed particles apart. Nevertheless, as pH changes, other factors may affect the graphene dispersion. At CMC point, more available anionic monomers increase the probability of adsorption. Additionally, at CMC point, the created micelles in the bulk may be adsorbed into the edge of graphene, and are located as two hemimicelles on the graphene surface. 67 However, at the CVC point, the vesicles, which are created as pH drops, 34 show less tendency to adsorb into the edge of graphene. Let us look at the changes in the chemical structure of the dispersed graphene surface from XPS standpoint. The core level spectra for C1s and O1s are shown in Figure 7. The deconvolution of the C1s peak at 284.33 eV in Figure 7e reveals C=C graphitic structure, 100,101 and peak at 285.90 eV refers to sp3 -hybridized carbon atoms (C−C). 100,101 In addition, the appeared peaks at 286.56, 287.54 and 288.36 eV correspond to carbon atoms bounded to oxygen atom in alcohol, keton and carboxylic acid, respectively. 100 The peaks of carboxylic acid belong to the adsorbed DHA on the graphene surface. As shown in Figure 7e, the XPS analysis has revealed that the large contribution of C=C bonds (ca. 75%) clarifies that the intrinsic structure of graphene is largely preserved. The peaks of O1s is deconvolved into three peaks (see Figure 7f). The peak at 530.17 eV is attributed to the physisorbed oxygen molecules for the air. 102 However, the peaks at 531.57 and 534.55 eV represent the oxygens in the structures such as carbonyl, phosphate and carboxylic acid, respectively. 100,103 It is worth mentioning that the phosphate groups come from Na3 PO4 buffer and they are not chemisorbed on the graphene surface.

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Size of particles The size of nanoparticles produced by LPE method can vary between 100 nm to 2 µm. 7,104 The variation in the size depends on the dispersion condition. Our MD calculations have shown that when the lateral size of graphene is three times larger than the lenght of DHA molecule, the hemicylandrical structures are formed on the graphene surface. Interestingly, 2D AFM image in Figure 8a shows that the graphene surface is covered by the hemicylandrical structures. 105,106 As shown in Figure 4b and Figure 8c, the distance between the centers of hemicylandrical structures from the MD simulations excellently matches with that from the AFM. The 3D AFM image (Figure 8c) reveals some regions which are higher than the hemicylandrical structures. For these areas, several structure can be considered: (i) the adsorbed micelles on the hemicylandrical surface, (ii) two-point wormlike, and (iii) single-point wormlike 107 The image of AFM and size distribution histogram are presented in Figure 8. Taking into account thickness of the adsorbed DHA on the graphene surface (2.2 nm), the results in Figure 8e show that the average height is 5 − 2.2 = 2.8 nm, denoting few layer of graphene. The average lateral size of the graphene sheets in Figure 8f is 150 nm. 9,108 Figure 9a represents the TEM image of graphene few layer with latral size 0.4µm. The HR-TEM images of edges of the mono and four layers graphene depicted in Figure 9b and c show that the graphene edges are folded to decrease the surface tension, which is necessary to preserve the planarity of graphene sheet. 79 The colloid particles covered by ionic surfactants are stabilized by the repulsive force of particle, which overcomes the van der Waals forces between the graphene sheets. The charge of ionic head and diffuse cloud of the counter ion or electrical double layer can produce this repulsion. 7 The repulsion force is determined by the zeta potential. It has been shown that if the zeta potential in absolute value is larger than 25 mV, i.e., |ζ| ≥ 25 mV, 9 the system is stable. In Figure 9d, the zeta potential peak is observed at -56 mV, confirming the stability of the system.

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Summary and conclusions In this study, MD, SAPT(DFT) and experimental methods have been combined to investigate the ability of the non-toxic fatty acid DHA to disperse graphene with the help of sonication assisted LPE. The morphology and thickness of self-assemblies on the graphene surface as well as the effect of different factors such as surface density, substrate size, number of layers and pH on the dispersion of graphite and the morphology were studied. All the factors affect the self-assembly morphology. Our results show that pH plays a significant role in the dispersion process, and it strongly affects the morphology, where pH corresponds to CMC of DHA is the optimum pH to perform the graphene dispersion. SAPT(DFT) uncovered that the decrease in pH diminishes the classical electrostatic repulsion between the surfactants, what is crucial for colloid stability. The MD and experimental results both confirm that graphite can be dispersed by DHA surfactant along with preserving the intrinsic structure of graphene. We believe that not only fatty acids can be applied to disperse graphene, but also the covered graphene, which loses its toxicity, 19,109 could be utilized as nanocarriers for drug delivery, photo thermaltrapy and other medical applications. Supporting Information Available The detailed simulation box, bonded and nonbonded parameters as well as some supplementary figures have been presented in supporting information. This material is available free of charge via the Internet at http://pubs.acs.org/.

Acknowledgement The authors thank Dr. Sirous Yourdkhani for his help in performing SAPT(DFT) calculations.

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Table of Contents (TOC) Image

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(a)

(c)

(b)

(d)

(e)

(f)

(g)

Figure 1: (a) the plot of RMSD and av.RMSD with error bar, (b) the plot of Eint and av.Eint between the anionic DHA and the graphene surface, (c) density profile of water (d) density profile of head group, (e) the snapshots of four systems with 48, 56, 112 and 148 the anionic DHA molecules. Color code: dark blue, carbon atoms in anionic DHA; white, hydrogen atoms; red, oxygen atoms; yellow, graphene sheet; water molecules have been removed for more clarity, (f) density profile of tail group, and (g) density profile of N a+ .

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(a)

(b)

(c) Figure 2: (a) the density profile of head group, (b) the blue and red plots shows Eint between DHA with graphene surface and Eint head groups, (c) the snapshots of different pH 11.5, 8.8, 8.5, 8.2. Color code: light blue, carbon atoms in neutral DHA; rest of color schemes are the same as Figure 1.

Energy [kcal/mol]

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

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35 30 25 20 15 10 5 0 −5 −10 −15 −20 −25

Electrostatic Exchange Induction Dispersion Total

Anion−Anion

Anion−Neutral

Neutral−Neutral

(1)

Figure 3: The total SAPT(DFT) and its electrostatic (Eelst ), first-order exchange (1) (2) (2) (Eexch ), total induction energy, (Eind +Eexch−ind +δEHF ), and total dispersion components (2) (2) (2) (2) (Edisp +Eexch−disp ). The Edisp and Eexch−disp terms are extrapolated using (VDZ→VTZ)×1.08 extrapolation scheme. The other SAPT(DFT) terms are calculated in cc-pVTZ basis set. Energies are given in kcal/mol.

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(a)

(b)

(c) Figure 4: (a) density profile of head group, (b) the violet plot shows the height and width of self-assembly from AFM and the green plot shows density of DHA in the box x-axis from MD, (c) the snapshot of systems for the surface size (3×3.3), (5.5×5.4), (8×8) nm2 of graphene, color scheme was shown in Figure 2.

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(a)

(b)

(c)

(d) Figure 5: (a) the snapshots of graphene multi-layers, (b) the density profile of head group, (c) density profile of water, (d) RDF of head group ( ) and tail group with the water molecules (- - -).

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a)

c)

b)

d)

Figure 6: (a) snapshot of system in three distances of graphene surface, (b), (c) and (d) are the contour plots of density properties of water, DHA and Na+ , respectively

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(e)

(f)

Figure 7: The UV-Vis spectrum in different conditions, (a) CGi = 1mg/ml, pH=11.5 and t=7h are constant in all the cases, while the concentration of DHA is varied, (b) CGi = 1mg/ml and CSur = 9 × 10−2 mM is equivalent to the CMC concentration, while the rest of the parameters are the same as in above, (c) pH was chosen between 8.8 and 11.5 which are equal to the pH of CVC and CMC, respectively, while the CGi = 1mg/ml and CSur = 9 × 10−2 mM are equal to standard parameters. The increase in the intensity of absorbance peak in pH=11.5, which is the same as CMC, indicates an increase in dispersion of graphene under this condition, (d) the ultrasonic time was increased and the rest of parameter were already optimized. (e) and (f) high resolution C1s, O1s XPS spectra of the dispersed graphene, respectively.

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a)

b)

c) 90 50

80 70 Number

40 Number

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


30 20

d)

e)

50 40 30 20

10 0

60

10 0

100

200

300

400

500

0 0

600

Lateral size (nm)

f)

10

20

30

40

50

60

70

Hieght (nm)

Figure 8: Topological characteristics of the assemblies: (a) and (d) 2D AFM image, (b) 3D AFM images, (c) the plot of morphology formed on the graphene surface using AFM, (e) and (f) size distribution histogram.

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(a)

(b)

(c)

(d)

Figure 9: (a) TEM image shows a few layer of graphene, (b) and (e) HR-TEM images are close-up of the edge of graphene of four and mono layer graphene , and (d) zeta potential.

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Revealing Factors Governing Self-Assembly ... - ACS Publications

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