Deciphering the Impact of Surface Defects and Functionalization on

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C: Surfaces, Interfaces, Porous Materials, and Catalysis

Deciphering the Impact of Surface Defects and Functionalization on the Binding Strength and Electronic Properties of GraphenePolypyrrole Nanocomposites: A First-Principles Approach Pabitra Narayan Samanta, and Kalyan Kumar Das J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b11173 • Publication Date (Web): 14 Feb 2019 Downloaded from http://pubs.acs.org on February 19, 2019

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The Journal of Physical Chemistry

Deciphering the Impact of Surface Defects and Functionalization on the Binding Strength and Electronic Properties of Graphenepolypyrrole Nanocomposites: A First-Principles Approach

Pabitra Narayan Samantaa*and Kalyan Kumar Dasb* aDepartment

of Chemistry & Biochemistry, Jackson State University, Jackson, MS 39217, USA

bDepartment

of Chemistry, Physical Chemistry Section, Jadavpur University, Kolkata 700 032, India

ABSTRACT: The distinct effectiveness of graphene-based nanostructures including pristine graphene, graphene with Stone-Wales defects, graphene oxides, and multi-layered graphene materials toward the development of mechanically robust graphene-polypyrrole nanocomposites are explored within the framework of DFT computations employing long-range corrected hybrid M06-2X functional. The essence of interface interactions is derived from the finite models of graphene-polymer systems by computing thermochemical properties, IR stretching frequencies, Raman scattering activities, global chemical reactivity descriptors, electronic properties via molecular orbital analysis as well as charge density distribution of each of the nanocomposites.The binding affinity is also evaluated by executing DFT-D3 and MP2 based computations to account for interaction energies with a reasonable accuracy. The adsorption energy due to the attachment of polypyrrole entity on the pristine graphene surface is estimated to be about -25 kcal/mol at the M06-2X-D3 level; which is further enhanced to -28 kcal/mol and -34 kcal/mol, respectively with the introduction of Stone-Wales defect and epoxy groups on the graphene surface. The subtle interplay of non-covalent interactions has been ascertained from the electrostatic potential maps, the Becke isosurface maps, and the reduced density gradient isosurfaces of the hybrid complexes. The weak attractive interactions within local areas between pyrrole units and modified graphene surface involving π-π stacking, lone pair-π, and H-bond interactions together accommodate the auxiliary binding strength of the hybrid complexes. The present findings bestow the formation-mechanism and stabilizing factors in the integral structure of graphene-polymer nanocomposites.

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1. INTRODUCTION Graphene, which consists of an atom-thick layer arranged in a honeycomb lattice, is considered to be one of the most important materials because of its attractive properties such as electronic mobility, thermal conductivity, mechanical strengths, and chemical stability.1-5 It has also been applied as toxic gas sensor and hydrogen storage material.6 Graphene was found to be very stable even after the adsorption of molecules like NO, NO2, CO2, amino acids or deoxyribonucleic acids.7-10 However, the large scale commercial applications of graphene as an adsorbent are not cost effective. Alternatively, graphene oxide (GO) can be easily prepared from graphite. The presence of the reactive oxygen functional group promotes the adsorption on GO. It has been found that GO or chemically modified graphene performs as a better molecular sensor. The active defective sites created due to the residual oxygen or hydroxyl groups during the reduction of GO improve the adsorption capability of GO which may enhance the sensor activity. The inherently conducting polymers, if incorporated into graphene, improve the electrochemical stability as well as the specific capacitance.11,12 The chemical polymerization of pyrrole in presence of graphite oxide followed by reduction produces polypyrrole/graphene composite.13 GO is also used to prepare chemically or electrochemically reduced graphene and chemically functionalized GO.14 Because of the presence of epoxy, hydroxyl, and carboxyl groups, it is possible to make GO as the dopant during its incorporation into conducting polymers. Yang et al

15

have synthesized polyaniline doped GO. In a

recent work, GO has been electro-deposited with pyrrole monomer forming a polypyrrole (PPy)/GO film which was electrochemically reduced to PPy/r-GO composite.16 A very similar study on the electrochemical preparation of PPy/GO composite film that was subsequently reduced, was reported by Chang et al.17 In another study,18 one-step co-electrodeposition method was employed to synthesize successfully the GO/PPy nanocomposite film using GO and Py monomers as the starting materials and then characterized by SEM, XPS, XRD, and FTIR analysis. GO/PPy was found to exhibit good electrochemical properties with the possibility of fabricating inexpensive and high-performance supercapacitors. Later on, de Oliveira et al 19 showed that a strong interaction between polypyrrole and modified graphene could generate an enhanced capacitance of device formed by the PPy-modified graphene nanocomposite. Sodium alginate-assisted in-situ polymerization of pyrrole has been adopted by Sahoo et al

20

to synthesize the graphene/PPy nanocomposite which exhibited improved charge

transformation and ion transportation through - stacking interaction between graphene and PPy. Like


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PPy, polyfuran (PF) nanotube can form a composite with r-GO. Based on r-GO/PF nanohybrids, a new type of field effect transistor sensor was recently developed.21 Over the last few years, theoretical studies of the interaction of small molecules like NO, NO2, heterocyclic compounds, amino acids etc. onto the surfaces of graphene and GO have been carried out to understand the type of interactions.7-10,

22-24

Non-covalent interactions of graphene with linear

imidazophenazine and its derivatives have been computed very recently23 at the M05-2X/6-31G(d) level. First principles based DFT calculations were carried out for investigating the strength to which glycine, histidine, and phenylalanine interact with the monolayers of perfect graphene, graphene with defect, and oxidized graphene.24 Interaction energies of benzene with pristine graphene and graphene with defect have also been estimated from the DFT calculations. It has been shown that the binding of graphene with polymers via dispersion forces is not much affected by the defects of low density present in graphene.25 DFT calculations at the PBE-D/DZP level of theory have suggested that the functionalized graphenes or N, B-doped graphenes are better adsorbents of 4-chlorophenol, a potent cancer producing pollutant compared to the pristine graphene.26 The usefulness of graphene and GO as sensors for the detection of NH3 has also been explored from the first principles study.27 DFT calculations with GGA/PBE approximations revealed that H2 can be strongly adsorbed on Mg-doped GO with a binding energy of 0.38 eV per H2.28 Albeit a number of theoretical studies addressing the nature of interaction between the aromatic molecules and graphene-based materials are accessible, the atomistic modeling of graphene-polymer composite with the recognition of the nature of molecular interactions and their quantitative estimation is still elusive. In the present investigation, we have explored the impact of surface irregularities and chemical functionalization of graphene-based nanostructures on the electronic stabilities of diverse graphene-polypyrrole nanocomposites. To unravel the delicate interplay of dispersion interactions between the polymer subunits and the graphene surface, a comparative study of the energetics of composite systems has been carried out within the DFT, DFT-D3, and MP2 approach. The magnitudes of adsorption energies and changes in thermodynamic quantities such as enthalpy and Gibbs free energy have been calculated for each hybrid complex. Stabilities of these polypyrrole-adsorbed complexes are justified from the computed values of chemical descriptors such as chemical potential, global hardness, and electrophilicity index. The notable changes occurred due to the said adsorption are analyzed by comparing the computed IR, Raman, and DOS spectra of the individual and the composite systems. The nature of interactions between PPy and the graphene moieties is further analyzed from the isosurfaces 3 ACS Paragon Plus Environment


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of the frontier orbitals, the electrostatic potential (ESP) maps, the Becke isosurfaces, and the reduced density gradient (RDG) based isosurfaces. We have also considered the plots of RDG against the electron density to have a clear picture of the strength of interactions.

2. COMPUTATIONAL DETAILS Ab initio based DFT calculations using M06-2X functional29 were performed to optimize the geometries of PPy, pristine graphene (G), graphene with defects (DG), multilayered graphene (MLG), and graphene oxides of three different types represented by GO1, GO2, GO3 (Figure 1). M06-2X is a parameterized semi-empirical meta-hybrid functional with double amount of nonlocal exchange energy, and found to be a decent basis for the prediction of atomistic structure and properties of materials such as thermochemistry, reaction pathways, IR stretching frequencies, valence and Rydberg excitations as well as Raman intensities.30 The said functional generally works well in ascertaining the electronic structure and properties of molecules which involve non-covalent interactions. The efficiency and robustness of this hybrid functional are further demonstrated by Lazar et al 31 to assess the adsorption enthalpies due to the attachment of small organic molecules on the graphene surface. Apart from that, the M06-2X functional has been found to be an effective DFT method for the evaluation of dispersion interactions as well as electron polarization density in the hybrid complexes of aromatic molecules adsorbed onto the surface of carbon allotropes such as graphene, C60, and single-walled nanotubes. On the basis of quantitative estimations of interaction-energy components using diverse dispersion corrected exchange-correlation (XC) functionals for the attachment of pyridine molecule on the surface of finite cluster models of graphene sheets, the M06-2X functional has been ascertained to rectify the dispersion interaction without altering the remainder components including electrostatic, Pauli, and induction relative to the other XC functionals viz. B97-D, BLYP-D, B3LYP-D, and wB97X-D.32 In the present computations, we have employed 6-31G(d) basis sets for all the atoms involved in the systems. This particular basis set has been widely used in the study of different carbon nanostructures, especially the graphene-based hybrid systems.23,30,33 In another study, Ershova et al

34

have demonstrated that the

computed binding energies for the adsorption of polycyclic aromatic hydrocarbons on the graphene surface using the long-range corrected hybrid XC functional and empirical dispersion corrected (wB97XD) and 6-31G(d) basis set corroborate well with the experimental values. Later on, an intensive effort has been paid by Hobza 35 to recognize the efficient wave function theory (WFT)-based method for the computations of non-covalent interactions in large complexes. As evident from the benchmark 4 ACS Paragon Plus Environment

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interaction energies, the MP2.5 and MP2.X/6-31G(d) methods are supposed to be reliable methods to produce highly accurate interaction energies. However, such WFT-based methods are computationally too expensive for modeling large cluster molecules consisting of more than 100 atoms. In the present study, the binding strengths between the PPy and graphene-based materials are further assessed by conducting MP2 calculations. Moreover, to validate the level of theory and size of the basis functions deployed in the present study, the computed structural, electronic, and spectral properties of the pristine graphene-based nanostructures and PPy-induced hybrid composites are compared with those of the earlier experimental and theoretical results. Two types of defects were created on the hexagonal network of the graphene sheet. These are straight Stone-Wales defect (DG1) and slanted Stone-Wales defect (DG2). These defects were generated by rotating the C1–C2 bond by 90 within four associated hexagons as shown in Figure S1. In order to inspect the impact of orientation of polymer chain on the adsorption properties, we have placed the PPy molecule on the surface of each graphene sheet at all possible orientations namely T-shape, sandwich, and parallel displaced; and allowed to relax. The optimized geometries of PPy–adsorbed hybrid complexes are reported here. During the geometry optimization, no symmetry constraint was imposed, and the SCF convergence limit was set to 10-6 a.u. on energy and density. Harmonic vibrational frequency analysis has been made to confirm the stationary points on the potential energy surfaces. All the DFT calculations were performed by using Gaussian 09 suite of program.36 The zero-point energy (ZPE) corrected total energies obtained from M06-2X/6-31G(d) calculations were used to estimate the adsorption energies (Ea) for the adsorption of PPy on G, DG1, DG2, GO1, GO2, GO3, and MLG. 𝐸𝑎 = 𝐸(𝑃𝑃𝑦 ― 𝑎𝑑𝑠𝑜𝑟𝑏𝑒𝑑 𝑐𝑜𝑚𝑝𝑙𝑒𝑥) ― [𝐸(𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒) + 𝐸(𝑃𝑃𝑦)]

(1)

where E(PPy), E(substrate), and E(PPy-adsorbed complex) are the total energies of PPy, substrate (graphene / graphene with defects / graphene oxide) and PPy-adsorbed complex, respectively. For each PPy-adsorbed hybrid complex of graphene derivatives, we also estimated the basis set superposition error (BSSE) using counterpoise technique of Boys and Bernardi

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in which the PPy and the graphene-

based nanostructures were considered as two separate fragments. Thermochemical properties such as enthalpy of adsorption (∆Ha) and Gibbs free energy changes (∆Ga) were calculated in a similar way for checking the thermodynamic favorability of PPy to adsorb on graphene moieties. ∆𝐻𝑎 = 𝐻(𝑃𝑃𝑦 ― 𝑎𝑑𝑠𝑜𝑟𝑏𝑒𝑑 𝑐𝑜𝑚𝑝𝑙𝑒𝑥) ― [𝐻(𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒) + 𝐻(𝑃𝑃𝑦)]


(2)


∆𝐺𝑎 = 𝐺(𝑃𝑃𝑦 ― 𝑎𝑑𝑠𝑜𝑟𝑏𝑒𝑑 𝑐𝑜𝑚𝑝𝑙𝑒𝑥) ― [𝐺(𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒) + 𝐺(𝑃𝑃𝑦)]

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(3)

Thermal energy corrections were included while computing free energies of each system at 298.15K and 1 atm. The ideal gas, rigid rotor, and harmonic oscillator approximations were respectively employed in deriving the translational, rotational, and vibrational contributions to the Gibbs free energy. Three chemical reactivity descriptors: chemical potential (µ), global hardness (η), and electrophilicity index (ω) were calculated using Koopmans’ method to check the stabilities and reactivities of the PPy-adsorbed complexes. For an accurate description of intermolecular interaction energies, we further emphasize on the estimation of weak van der Waals (vdW) interactions by performing dispersion-corrected DFT calculations on each graphene-polymer composite as well as the pristine material. By conducting benchmark studies on a set of large dispersion-stabilized non-covalent complexes, Hobza and coworkers

38

have demonstrated that the M06-2X functional coupled with zero damping form of the D3

correction provides a better description of non-covalent interactions compared to the unrhetorical M062X functional. In that study, the relative RMSD values corresponding to the total binding energies of the complexes derived from M06-2X-D3 and M06-2X methods were estimated to be 2.2 kcal/mol and 5.3 kcal/mol, respectively. In the present computational study, dispersion corrections were added to the self-consistent electronic energy through the DFT-D3 correction method proposed by Grimme et al.39 Finally, the adsorption energies are estimated by 𝐸𝑎, 𝐷𝐹𝑇 ― 𝐷3 = 𝐸𝑎 + ∆𝐸𝑑𝑖𝑠𝑝 = 𝐸𝑎 + (𝐸𝑑𝑖𝑠𝑝[𝑃𝑃𝑦 ― 𝑎𝑑𝑠𝑜𝑟𝑏𝑒𝑑 𝑐𝑜𝑚𝑝𝑙𝑒𝑥] ― (𝐸𝑑𝑖𝑠𝑝[𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒] + 𝐸𝑑𝑖𝑠𝑝[𝑃𝑃𝑦]))

(4)

3. RESULTS AND DISCUSSION To mitigate the thriving edge interaction effects caused by a miniature model of graphene sheet with outstretched polymer chains, and to attain the highest possible degree of interaction between the graphene surface and the polymer building blocks, we have considered a finite PPy oligomer which consists of three Py subunits and bears a permanent electric dipole moment of 2.38 D along the transversal direction of the polymer chain obtained at M06-2X/6-31G(d) level of theory. The impact of diverse polymer-induced dipole moments on the work-function and the Dirac point of the graphene


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have been assessed by Lee et al

40

using DFT based calculations. Polymers carrying the intrinsic dipole

moments have been predicted to suppress the work-function at the graphene-polymer interface. The dipole layer-induced graphene doping using asymmetric polymer chains is considered an effective approach to improve the efficiency of organic electronic devices. In the relaxed molecular geometries of Py oligomer, three pyrrole rings are linked together through C – C bonds, each of length 1.45 Å to make a model of PPy. The fully optimized structure of PPy at the M06-2X/6-31G(d) level of calculation shows that each of three pyrrole rings are oriented in antigauche form with respect to the each other. The two outer ring planes make 4– 5 angle with the middle one to avoid any steric hindrance. The computed torsion angle between two successive Py subunits is found to be 151°, which agrees well with the previously reported value of 153° estimated for n-Py neutral oligomers at the BPW91/6-311G level of theory.41 To unveil the nature of non-covalent interactions between aromatic molecules and graphene sheet, the finite graphene fragment has been deployed as has been done in numerous theoretical investigations.42-45 The pristine graphene sheet used here consists of twenty hexagonal rings with 20 terminating H atoms satisfying the residual valence. We have also optimized the structure of the double layered graphene, each having the same number of hexagons and H atoms. After full geometry optimization, both the layers take the shape of shallow cup and are shifted one against the other like half-staggered (Figure 1(c)). The interlayer distance is about 3.35 Å in accordance with the previous findings.46-48 It is known that GO constitutes a hexagonal carbon network with oxygen atoms in a three-member C–O–C ring and a hydroxyl group. DFT calculations based on first principles

49

predicted that in the

energetically most stable state of GO, the oxygen atoms form 1,2-ether groups (epoxides) on the carbon grid and the hydroxyl groups are attached to a carbon atom directly adjacent to the epoxy oxygen but in the opposite side of the carbon plane. The present DFT optimization also leads to a similar type of epoxide ring and –OH formation on the graphene sheet. Three models of GO were constructed here by adding two, three, and four pairs of –OH and epoxide on the graphene sheet. These are designated as GO1, GO2, and GO3, which form stable geometries. The C–O–H bond angles lie in between 106 and 107, and the computed average O–H bond distance is about 0.975 Å. It is also of our interest to see how the nature of the adsorption of PPy on the graphene surface changes if there are naturally occurring defects on the surface. It has been found that such structural defects can play an important role in the transformation and electrical properties of carbon nanostructures. We have thus incorporated Stone-Wales defects on the hexagonal network of the planar graphene forming DG1 and 7 ACS Paragon Plus Environment


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DG2 as shown in Figures S1(a) and (b), respectively. So, the surface of graphene produces two heptagons and two pentagons in place of four hexagons. After full geometry optimization, DG1 and DG2 remain almost in the planar configurations. The PPy molecule having three pyrrole units is placed on the surface of the optimized G with 20 hexagons at different orientations. The M06-2X/6-31G(d) optimized structure in the ground state shows that the most stable configuration is the one in which the pyrrole rings of PPy are aligned parallel to the graphene layer through vdW interactions (Figure 2(a)). The adsorbed PPy moiety is about 3Å distance away from the graphene plane. The measured adsorption distance reveals a close resemblance to that of bipyrrole-adsorbed graphene composite reported by Özkayaa et al 50 using the projector augmented wave (PAW)-based DFT calculations together with optB86b-vdW functional. The relative angular orientations of three pyrrole rings in the adsorbed complex are about 10 avoiding any steric hindrance. The positions of the PPy molecule adsorbed on the graphene with defects such as DG1 and DG2 are confined over the heptagon rings through similar vdW type interactions (Figures 2(b) and (c)). The planarity of the DG sheet is lost only marginally. Due to the π-π interaction between the ring clouds of PPy and graphene surface, the torsion angles created by the neighboring Py units in the pristine PPy oligomer further relax to reduce the ring puckering. The computed torsion angles vary between 164° and 173° owing to the attachment of PPy on the surfaces of pristine G and graphene with defects. Conversely, the adsorption of bipyrrole on the G surface leads to the additional reduction of ring puckering lying in the range 174.5 - 179° as computed by employing PAW-based DFT computations.

50

The adsorption of PPy on the concave side of the curved double layered graphene also takes place in a similar way. Figures 3(a-c) display the optimized structures of the complexes (both top and side view) in which the PPy molecule gets adsorbed over GO1, GO2, and GO3, respectively. In all three cases, the energetically favorable conformations accommodate PPy on the epoxy side of the graphene surface. However, the planarity of the PPy molecule is lost after adsorption. Two consecutive pyrrole rings in the GO1–PPy complex remain in plane, while the third or the terminal one is out of plane. This is further substantiated by the estimated torsion angles of ~ 179° and ~ 158° between the two consecutive Py subunits in the GO1-PPy composite. In case of GO2-PPy adduct, the plane is twisted in a particular direction as shown in Figure 3. The present optimization shows that after the adsorption of PPy on GO3, the middle pyrrole ring becomes out of plane, while the two terminal rings remain almost in the same


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plane with the graphene oxide sheet. With the enhancement of epoxy groups, the adsorption of PPy molecule on the GO surface is facilitated by negligible alteration of ring puckering. The calculated torsion angles fluctuate between 150° and 160° in the optimized geometries of GO2-PPy and GO3-PPy composites. To assess the binding strength of the hybrid complexes, we next delve into a quantitative analysis of the non-covalent interactions owing to the attachment of the PPy molecule onto the surface of graphene-based nanostructures. The computed ZPE corrected adsorption energies (Ea) for all the complexes except the large model structure of PPy-adsorbed MLG are reported in Table 1. The binding affinity is enhanced by as much as 3 kcal/mol in case of DG compared to the pristine G; while the estimated Ea values for GO-PPy adsorbed complexes unveil further increment by 9 kcal/mol as computed in case of GO3-PPy adduct. The structural defects thus play a crucial role in the escalation of the interaction between two entities. The creation of slanted Stone-Wales defect (DG2) on the G surface improves the binding strength by lowering the Ea value of about 1.5 kcal/mol relative to the straight Stone-Wales defect (DG1) structure. The computed data for three different GO-PPy composites indicate that the adsorption affinity is significantly perturbed by the number of epoxide rings and the orientations of polymer chains in the model systems. The predicted BSSE for G-PPy and DG-PPy heterostructures lies in the range of 7.3 – 7.5 kcal/mol, whereas it varies between 9.0 and 9.3 kcal/mol in case of PPy-adsorbed GO complexes. It is to be mentioned here that, after BSSE correction, the relative trends in adsorption affinity of G-based materials toward PPy remain unaffected. The estimated large binding affinity for the adsorption of PPy on the surface of MLG compared to the pristine G stems from the large contact area exhibited by the MLG surface. In order to describe the energetics of non-covalent interactions with higher accuracy, the adsorption energies for each graphene-PPy nanocomposite are additionally evaluated by employing the DFT-D3 correction method as well as the correlated wave function based method like MP2. The computed adsorption energies at the M06-2X-D3 and MP2 level of theory are also displayed in Table 1. Owing to the inclusion of DFT-D3 correction, the adsorption energy is further lowered by about 3 kcal/mol in cases of pristine G and DG systems; while the estimated Ea value is found to be reduced by about 1 kcal/mol in case of graphene oxide material with a maximum number of epoxy groups on the surface. The dispersion correction energy difference (ΔEdisp) due to the adsorption of PPy on the MLG surface is computed to be about 6 kcal/mol implying that dispersion contributions play a major role in 9 ACS Paragon Plus Environment


such multi-layered systems. Albeit the predicted trends in adsorption affinity extracted from M06-2X-D3 level closely resemble to those obtained from M06-2X, the dispersion correction seems to be reasonable for the refinement of DFT-derived adsorption energies where the interactions between two molecular entities are predominantly controlled by vdW type π-π stacking. The comparative studies of adsorption energetics of diverse PPy-adsorbed graphene derivatives within meta-hybrid GGA based DFT calculations and MP2 approach clearly demonstrate that MP2 predicts enormous intermolecular attraction energy which probably emanates from the explicit dispersion term and the increased polarizabilities of the interacting species.51 To unravel the thermo-chemical behavior of the molecule-surface interaction, we further emphasize on the analysis of thermodynamic data associated with enthalpies of adsorption (ΔHads) and Gibbs free energy changes (ΔGads) due to the adsorption of polymer chain on the pristine G, DG, and functionalized G surfaces. The computed ΔHads and ΔGads for each surface adsorption process are presented in Table 1. The negative values of ΔHads anticipate that the adsorption of PPy on each adsorbent surface is exothermic in nature. The thermodynamic favorability of each molecule-surface interaction except GO2-PPy is further substantiated by the calculated negative ΔGads values at 298.15K, implying that the adsorption of polymer on each graphene-based material is exergonic. A closer inspection of the computed energetics associated with Ea values as well as thermochemical properties such as ΔGads for different GO-PPy model systems further indicate that the adsorption of the PPy chain on the GO edge site is the most preferred orientation compared to that on the center of the GO surface. Figures S2 and S3 respectively show the comparative IR and Raman spectra of PPy, adsorbent, and the adsorbed complexes that include all six adsorbents such as G, DG1, DG2, GO1, GO2, and GO3. In the pure PPy, three N–H stretching vibrations are found to be around 3685 cm-1 and C-H stretching vibrations of Py subunits are predicted to vary between 3264 and 3284 cm-1. The calculated IR modes for the Py-trimer oligomer are in well agreement with the previously simulated IR-active spectrum of bipyrrole at the BPW91/6-311G level of theory. 41 For the anti-gauche isomer of the bipyrrole, the N-H stretching frequency was computed to be 3697 cm-1 and three C-H stretching frequencies were found to lie in the range of 3246-3286 cm-1. After its adsorption on pure G as well as on DGs, these N–H vibration bands are red-shifted by a maximum of 15 cm-1. Since the surroundings of the surfaces of three graphene oxides are quite different, the N–H stretching vibrational frequencies of 3 N–H bonds of PPy adsorbed on graphene oxides are also red-shifted but to a larger extent compared to graphene or 10 ACS Paragon Plus Environment

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graphene with defects. The largest red-shift of about 100 cm-1 has been noted in case of GO3, where there are four sets of epoxy bonds. In the exfoliated graphene or pristine graphite, the conjugated double bonds are characterized by intense Raman signals. Experimentally,52 there exist a D band at 1338 cm-1, a G band at 1578 cm-1, a D’ band at 1615 cm-1, and a 2D band at 2668 cm-1. In the present computation, the bands obtained in graphene (Figure S3(a)) around 1368 and 1656 cm-1, respectively resemble the observed D and G bands. Theoretical Raman activity spectrum of PPy shows two distinct bands near 1578 and 1691 cm-1. After non-covalent interactions, positions of D and G bands of graphene remain more or less unchanged and their intensity ratio (ID/IG) is enhanced from 0.45 to 0.73. It has been found that the Raman spectra can probe disorder in graphene through defect-activated peaks. The peak positions of D, G, D’, and 2D’ bands depend on the type of vacancy created in the graphene sheet and the ratio (ID/IG) varies accordingly. Figures S3(b) and (c) show the Raman spectra of DG1 and DG2, and those after their non-covalent interactions with PPy. The present calculations show that in case of straight Stone-Wales defect, the position of the calculated D band lies at 1648 cm-1, while in case of slanted one it is around 1689 cm-1. Once the non-covalent interactions with PPy take place, the D band of DG1 remain more or less unchanged, while that of DG2 diminishes its intensity. The most intense Raman bands in GO1, GO2, and GO3 are obtained at 1475, 1464, and 1582 cm-1, respectively. Figures S3(d) – (f) display how the Raman spectra change after the formation of complexes with PPy. Density of states (DOS) spectra of the isolated PPy, graphene, graphene with defects, graphene oxides, and their complexes are shown in Figures 4(a) – (f). The dotted vertical line in each set of spectra represents the position of the HOMO in the complex. The HOMO – LUMO gap in the isolated PPy is large compared to that of G or DG or GO. The spectra reveal that the positions of HOMO and LUMO peaks in the DOS spectra of the hybrid complexes remain more or less unchanged, thereby suggesting weak binding strength of PPy on the graphene surfaces. The isosurfaces of HOMO and LUMO of PPy adsorbed complexes are depicted in Figures S4(a) – (f) obtained by using an isovalue of 0.02. In case of hybrid complexes, the frontier orbitals are mainly dominated by the graphene moieties. However, in GO2–PPy and GO3–PPy complexes, the involvement of PPy is significant. Figures S5(a) – (f) display the top view of the ESP maps of PPy-adsorbed complexes of graphenes and their oxides. These maps add to the knowledge of interactions between PPy and the graphene moieties. The red areas of the maps indicate 11 ACS Paragon Plus Environment


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the accumulation of electronic charges, while the blue patches appear for the cationic environment. The ESP maps of pristine G and DG surfaces unveil a uniform distribution of the electrostatic potential, while an intense asymmetry induced by surface functionalized groups, –OH and epoxide is observed on each GO surface. Owing to the high electronegativity of oxygen compared to carbon, the presence of epoxide groups on the graphene surface enables more electron-sufficient sites fostering intermolecular nonbonded interactions with positive centers, and thereby leading to the enhancement of physisorption of the polar adsorbate by hydrogen bond interactions. Since graphene is a strong electron acceptor, the molecule-surface interaction transpires through the negatively charged site of the PPy adsorbate. The ESP maps of the composite systems as depicted in Figure S5 elucidate that the distribution of electrostatic potential is not significantly perturbed by the attachment of the PPy molecule on the Gbased nanostructured surfaces. For all the PPy adsorbed complexes the electrostatic potential distributions are of the order of 10-2 e.s.u, indicating that the surface adsorption processes are not driven by the charge-transfer interactions and are weak in nature. The global reactivity descriptors estimated by using Koopmans’ method

53-55

are further analyzed

to comprehend the stability and chemical reactivity of different G-based materials as well as hybrid Gpolymer composites. The computed three chemical reactivity descriptors μ, η, and ω along with dipole moment (D) and HOMO-LUMO energy gap (Eg) for PPy, each of the G-based nanostructured materials and their adsorbed complexes are reported in Table 2 and 3, respectively. The surfaces of pristine G and Stone-Wales defect-induced G are non-polar in nature; while the inclusion of epoxide and –OH groups tends to increase the polarity of the G surface. The calculated D values as reported in Table 3 anticipate that the adsorption of PPy further enhances the polarity of each composite material. Moreover, the augmentation of polarity manifests the possible solubility of these 2D nanomaterials in the presence of PPy polymer. As expected, the GO–PPy complexes have more polarizations, which are supported by the computed larger dipole moments of these complexes. However, in the GO3-PPy adduct, the estimated D value is found to closely resemble to that of the isolated PPy molecule. This indicates that the magnitude of D and especially their x, y, z components essentially depend on the orientation of the PPy molecule on the GO surface. The Eg value for the PPy molecule is predicted to be 6.72 eV; while the calculated Eg values for all the graphene derivatives lie in the range 1.84-2.44 eV. As demonstrated by Kheirabadi et al,

56

the HOMO-LUMO energy gap of the pristine G has been found to decline with the

increase of the number of carbon atoms. Markedly, the zero band gap nature of the bulk G system is retained for an extensive cluster model of the graphene sheet that consists of about 500 carbon atoms. 12 ACS Paragon Plus Environment

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In the present computational study, the semi-metal characteristic of pure G is significantly perturbed by the strong quantum effect emanating from the miniature cluster model. The estimated larger Eg values are further attributed to the inclusion of augmented Hartree-Fock (HF) exchange term (~54%) in the M06-2X functional which in turn lowers the HOMO energy to a greater extent compared to the other GGA based functional such as B3LYP.33 The narrow HOMO-LUMO gap of the isolated G-based system is more or less retained in each G-polymer hybrid material. This corroborates well with the calculated DOS spectra as displayed in Figure 4. It, therefore, confirms that all these molecule-surface interactions are weak in nature, and the characteristic electronic properties of pristine materials do not alter appreciably. As evident from the computed μ, η, and ω values, the creation of Stone-Wales defects does not modify the global reactivity indexes of pristine G significantly. Functionalization with more acceptor groups facilitates the dissipation of the electrical charge from the G surface, and thereby raises the electrophilic character of the GO based materials. The results clearly demonstrate that with the increase of epoxide and –OH groups on the G surface, ω experiences an increment of 1.28 eV as obtained in case of GO3 compared to the pristine G, while η changes negligibly, which in turn promotes the adsorption sensitivity of GO3 towards the PPy molecule. In order to resolve the essence of interactions between graphene moieties and the PPy molecule, we subsequently perform the Becke surface analysis. Figures 5(a) – (f) show the mapping of two real space functions such as electron density and normalized contact distance (dnorm) onto the Becke surface. These reveal the insight into the intermolecular binding-site region of the complex. dnorm for each point on the Becke isosurface is defined as dnorm =

𝑑𝑖 ― 𝑟𝑣𝑑𝑊 𝑖 𝑟𝑣𝑑𝑊 𝑖

+

𝑑𝑒 ― 𝑟𝑣𝑑𝑊 𝑒 𝑟𝑣𝑑𝑊 𝑒

where di is the distance from a point on the surface to the nearest nucleus inside the surface and de represents the distance from the point to the nearest nucleus external to the surface. 𝑟𝑣𝑑𝑊 and 𝑟𝑣𝑑𝑊 𝑖 𝑒 denote van der Waals (vdW) radii of the two corresponding atoms. A close intermolecular contact, which implies a strong interaction, is represented by a small value of dnorm. In Figure 5 (right column), dnorm displays the surface with a blue-white-red color scheme. The blue regions refer to the close contacts between fragments, while the white areas indicate contacts around the vdW separation. The red regions signify no close contacts. Therefore, the Becke isosurfaces mapped with dnorm confirm that the attachment of PPy on the surfaces of graphenes and their oxides is governed by vdW type interactions. When the electron density is mapped onto the Becke surface as delineated in Figure 5 (left



column), the bright red spots on the Becke isosurface signify high electron density region corresponding to the close intermolecular contact sites between PPy and graphene derived materials. These isosurface plots demonstrate that, in addition to the vdW type π-π interaction between the ring clouds of PPy and graphene surface, the molecule-surface interactions also experience lone pair-π interactions which emanate from the attraction between delocalized π-electrons of the hexagonal rings of the pristine G as well as DG and the amine group (-NH) of the PPy molecule. The increase of the lone pair-π interaction in the DG2-PPy composite leads to the onset of higher binding strength compared to the pristine G. Such type of interaction is absent in case of GO-PPy systems. However, the estimated higher adsorption energy in case of GO3-PPy hybrid material is attributed to the strong CH-O and NH-O interactions involving the Py moiety and the epoxy O atoms of the GO surface. The characteristics of the non-covalent interactions between the graphene moieties and the PPy molecule are additionally examined in real space based on electron density (ρ) and its derivatives (ρ).57, 58 The reduced density gradient can be computed from these two parameters. RDG =

1 1 2 3

·

| 𝜌(𝑟) | 𝜌(𝑟)4/3

(2(3𝜋 ) )

The regions with small RDG and ρ values in the plot of RDG vs ρ indicate the weak vdW interactions, while those corresponding to the steric clashes and H-bonds have comparatively larger ρ and overlap. When the sign of the second Hessian eigenvalue (λ2) is included, the attractive and repulsive interactions are separated. Therefore, studying the plots of RDG against [Sign(λ2(r))ρ(r)] will provide some idea about the type of non-covalent interactions. Figures S6 and S7, respectively show the color-filled RDG isosurfaces and scatter plots of RDG as a function of [Sign(λ2)ρ] for the binding of PPy with graphene, graphene with defects, and graphene oxides. The isosurfaces (Figure S6) are colored on a Blue-GreenRed scheme that depends on the values of [Sign(λ2)ρ]. Its large negative value as shown by blue color is an indication of stronger attractive interactions, while a large positive value is represented by red color, which indicates the repulsive nature of the interaction. The weak vdW interactions are indicated by values near zero as marked by green or light brown color in the isosurfaces. In the scatter plot (Figure S7), the spikes are found in the low-density and low-gradient regions indicating the weak non-covalent interactions. Both the isosurface map and the scatter plot of RDG reveal that the interaction between PPy and graphene based materials are mainly governed by weak vdW type interactions. In addition to the π-π interactions, the σ-π interactions through the formation of CH-O play a crucial role to the enhancement of the composite strength in case of the GO3-PPy system. These CH-O interactions are 14 ACS Paragon Plus Environment

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evident from the appearance of several peaks at the negative values of [Sign(λ2(r))ρ(r)] (Figure S7 (f)). A closer inspection of the RDG isosurface plot also manifests that, the reduction in adsorption energy for GO2-PPy emanates from the suppression of π-π interactions caused by the steric hindrance provided by surface epoxy oxygen atoms. This corroborates well with the previous theoretical prophecy determined for the interactions of polymers with the reduced graphene oxide using dispersion-corrected DFT-based methods.59 Next, we have computed different electronic properties of the MLG-PPy composite system in which PPy is adsorbed on the convex side of the double layered graphene surface. The weak binding of PPy on MLG is reflected in the DOS spectra as shown in Figure 6(a). The predicted semiconductor characteristic of the pristine MLG is retained in the MLG-PPy composite, which is further substantiated by the density distribution of the frontier MOs viz. HOMO and LUMO of the complex over the MLG moiety as delineated in Figures 6(b) and (c). The uniform distribution of the electrostatic potential on the PPy molecule (Figure 6(d)) anticipates weak adsorption on the MLG surface. Two Becke surfaces of the complex, one mapped with electron density and the other with dnorm are displayed in Figures 6(e) and (f), respectively. The RDG isosurface and the scattered plot of RDG as a function of Sign(λ2)ρ in Figures 6(g) and (h) are indicative of weak non-covalent interactions of PPy on the double graphene layer. The results clearly demonstrate that the adsorption of PPy on the MLG surfaces is mainly governed by the π-π type interactions between the ring clouds of PPy and MLG.

4. CONCLUSIONS First-principles based quantum chemical calculations within the framework of DFT employing longrange corrected hybrid M06-2X functional are performed to assess the impact of surface morphology of the pristine graphene, graphene with defects, and functionalized graphene-allied materials on the binding characteristics of polypyrrole-graphene composites. The estimated ZPE corrected adsorption energy for the attachment of small chain polymer of pyrrole on the pristine graphene surface is about -20 kcal/mol at the M06-2X/6-31G(d) level of theory, which is enhanced approximately by 3 kcal/mol due to the slanted Stone-Wales defect on the graphene surface and by 9 kcal/mol in case of graphene oxide with four sets of epoxy groups on the surface. The inclusion of dispersion correction via the DFTD3 approach improves the interaction energy acquired from meta-hybrid GGA functional based DFT calculation itself but does not change the relative trend of the interaction between the polymer subunits 15 ACS Paragon Plus Environment


and the graphene derivatives. DFT calculations on the finite model systems of polypyrrole-adsorbed graphene oxide composites reveal a strong dependence of molecule-surface interactions on the number of functionalized surface epoxy groups as well as the layout of polymer building blocks on the graphene surface. The relative effectiveness of different surface irregularities to the escalation of binding strength of graphene-polymer hybrid materials is further substantiated by the computed Gibbs free energy changes for each case. The DFT derived thermochemical data demonstrate that the surface adsorption processes are commonly exothermic and exergonic in nature. After the adsorption of polypyrrole on the surfaces of pristine and modified graphene materials, the N-H stretching frequencies of pyrrole units remain almost unchanged. Because of the weak interactions between polypyrrole and graphene derivatives, only a few new peaks of low intensities appear in the low frequency region. The positions of D and G bands of all the isolated graphene-based materials are not significantly modified by the molecule-surface interactions in the corresponding polypyrrole-adsorbed hybrid materials. The semiconducting properties of the pristine graphene, graphene with defects, and their oxide counterparts are retained in the polymer-adsorbed complexes as revealed by the computed HOMO-LUMO energy gap and the DOS spectra of the graphene-polymer composites. The estimated global chemical reactivity descriptors unveil an exiguous perturbation of the chemical reactivity during the adsorption process relative to the pristine materials. The constitutive roles of non-covalent π-π, lone pair-π, and H-bond interactions in stabilizing the graphene-polymer composites are further elucidated by analyzing ESP maps, Becke isosurface maps, and RDG isosurfaces. The adsorption of polypyrrole on the graphene with defects is facilitated by both π-π stacking and lone pair-π interactions; while the enhancement of adsorption affinity of the polymer on the graphene oxide surface stems from the H-bond interactions involving –(CH-O) and –(NH-O) interactions between pyrrole sub-units and epoxy groups. The present findings could pave the way for guiding and designing high-performance low-dimensional nano-composites with integrated mechanical and optoelectronic properties. 

ASSOCIATED CONTENT Supporting Information The supporting information is available free of charge on the ACS Publication website at DOI: ……… Figure S1 showing the optimized structures of graphenes with defects (DG1 and DG2); Figure S2 depicting the comparison of IR spectra obtained at the M06-2X/6-31G(d) level of theory for PPy, pristine graphene based nanomaterials and composite materials such as G-PPy, DG1-PPy, DG216 ACS Paragon Plus Environment

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PPy, GO1-PPy, GO2-PPy and GO3-PPy; Figure S3 showing the comparison of Raman spectra of these systems; Figure S4 displaying the isosurfaces of the frontier orbitals of the composite materials; Figure S5 showing the electrostatic potential maps of all six composite materials; Figure S6 displaying their reduced density gradient (RDG) based non-covalent interaction isosufaces; Figure S7 depicting the plots of RDG against the electron density for these composite materials. 

AUTHOR INFORMATION

Corresponding Author *E-mail: a [email protected] [email protected]

ORCID Pabitra Narayan Samanta: 0000-0001-7300-4959 Kalyan Kumar Das: 0000-0003-4697-6466 Notes The authors declare no competing financial interest. 

ACKNOWLEDGMENTS

The financial assistance provided by the Office of Naval Research, ONR (Grant N00014171306), USA; DST-FIST (Govt. of India) and UGC-CAS (Govt. of India) is gratefully acknowledged. 

REFERENCES

(1) Geim, A. K.; Novoselov, K. S. The Rise of Graphene. Nature Mat. 2007, 6, 183 – 191. (2) Lee, C.; Wei, X.; Kysar, J. W.; Hone, J. Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene. Science 2008, 321, 385 – 388. (3) Balandin, A. A.; Ghosh, S.; Bao, W.; Calizo, I.; Teweldebrhan, D.; Miao, F.; Lau, C. N. Superior Thermal Conductivity of Single-Layer Graphene. Nano Lett. 2008, 8, 902 – 907. (4) Allen, M. J.; Tung, V. C.; Kaner, R. B. Honeycomb Carb: A Review of Graphene. Chem. Rev. 2009, 110, 132 – 145. (5) Singh, V.; Joung, D.; Zhai, L.; Das, S.; Khondaker, S. I.; Seal, S. Graphene Based Materials Past, Present and Future. Prog. Mater. Sci. 2011, 56, 1178 – 1271.



(6) Du, A.; Zhu, Z.; Smith, S. C. Multifunctional Porous Graphene for Nanoelectronics and Hydrogen Storage: New Properties Revealed by First Principles Calculations. J. Am. Chem. Soc. 2010, 132, 2876 – 2877. (7) Gao, H.; liu, Z. DFT Study of NO Adsorption on Pristine Graphene. RSC Adv. 2017, 7, 13082 – 13091. (8) Choudhuri, I.; Patra, N.; Mahata, A.; Ahuja, R.; Pathak, B. B-N@graphene: Highly Sensitive and Selective Gas Sensor. J. Phys. Chem. C 2015, 119, 24827 – 24837. (9) Singla, P.; Riyaz, M.; Singhal, S.; Goel, N. Theoretical Study of Adsorption of Amino Acids on Graphene and BN Sheet in Gas and Aqueous Phase with Empirical DFT Dispersion Correction. Phys. Chem. Chem. Phys. 2016, 18, 5597 – 5604. (10) Alshehri, M. H.; Cox, B. J.; Hill, J. M. DNA Adsorption on Graphene. Eur. Phys. J. D. 2013, 67:226. (11) Yan, J.; Wei, T.; Shao, B.; Fan, Z.; Qian, W.; Zhang, M.; Wei, F. Preparation of a Graphene Nanosheet/Polyaniline Composite with High Specific Capacitance. Carbon 2010, 48, 487–493. (12) Zhang, K.; Zhang, L. L.; Zhao, X. S.; Wu, J. Graphene/Polyaniline Nanofiber Composites as Supercapacitor Electrodes. Chem. Mater. 2010, 22, 1392–1401. (13) Bose, S.; Kuila, T.; Uddin, M. E.; Kim, N. H.; Lau, A. K. T.; Lee, J. H. In-situ Synthesis and Characterization of Electrically Conductive Polypyrrole / Graphene Nanocomposites. Polymer 2010, 51, 5921–5928. (14) Xu, J.; Wang, K.; Zu, S. –Z.; Han, B. –H.; Wei, Z. Hierarchical Nanocomposites of Polyaniline Nanowire Arrays on Graphene Oxide Sheets with Synergistic Effect for Energy Storage. ACS Nano 2010, 4, 5019–5026. (15) Yang, N.; Zhai, J.; Wan, M.; Wang, D.; Jiang, L. Layered Nanostructures of Polyaniline with Graphene Oxide as the Dopant and Template. Synth. Met. 2010, 160, 1617–1622. (16) Yang, Y.; Wang, C.; Yue, B.; Gambhir, S.; Too, C. O.; Wallace, G. G. Electrochemically Synthesized Polypyrrole/Graphene Composite Film for Lithium Batteries. Adv. Energy Mater. 2012, 2, 266 – 272. (17) Chang, H. –H.; Chang, C. -K.; Tsai, Y. -C.; Liao, C. -S. Electrochemically Synthesized Graphene / Polypyrrole Composites and their Use in Supercapacitor. Carbon 2012, 50, 2331–2336. (18) Zhu, C.; Zhai, J.; Wen, D.; Dong, S. Graphene Oxide/ Polypyrrole Nanocomposites: One-step Electrochemical Doping, Coating and Synergistic Effect for Energy Storage. J. Mater. Chem. 2012, 22, 6300 – 6306. (19) de Oliveira, H. P.; Sydlik, S. A.; Swager, T. M. Supercapacitors from Free-Standing Polypyrrole / Graphene Nanocomposites. J. Phys. Chem. C 2013, 117, 10270–10276.


Page 18 of 31

Page 19 of 31 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


(20) Sahoo, S.; Dhibar, S.; Hatui, G.; Bhattacharya, P.; Das, C. K. Graphene/polypyrrole Nanofiber Nanocomposite as Electrode Material for Electrochemical Supercapacitor. Polymer 2013, 54, 1033– 1042. (21) Park, J. W.; Park, S. J.; Kwon, O. S.; Lee, C.; Jang, J. High-performance Hg2+ FET-type Sensors Based on Reduced Graphene Oxide–Polyfuran Nanohybrids. Analyst 2014, 139, 3852 – 3855. (22) Hou, M.; Cen, W.; Zhang, H.; Liu, J.; Yin, H.; Wei, F. Adsorption and Oxidation of NO on Graphene Oxides: A Dispersion Corrected Density Functional Theory Investigation. Applied Surface Science 2015, 339, 55–61. (23) Zarudnev, E.; Stepanian, S.; Adamowicz, L.; Karachevtsev, V. Noncovalent Interaction of Graphene with Heterocyclic Compounds: Benzene, Imidazole, Tetracene, and Imidazophenazines. ChemPhysChem 2016, 17, 1204–1212. (24) Larijani, H. T.; Ganji, M. D.; Jahanshahi, M. Trends of Amino acid Adsorption onto Graphene and Graphene Oxide Surfaces: A Dispersion Corrected DFT Study. RSC Adv. 2015, 5, 92843 – 92857. (25) Hassan, M.; Walter, M.; Moseler, M. Interactions of Polymers with Reduced Graphene Oxide: van der Waals Binding Energies of Benzene on Graphene with Defects. Phys. Chem. Chem. Phys. 2014, 16, 33-37. (26) Arriagada, D. C.; Sanhueza, L.; Wrighton, K. Removal of 4-chlorophenol Using Graphene, Graphene Oxide, and A-Doped Graphene (A = N, B): A Computational Study. Int. J. Quant. Chem. 2013, 113, 1931–1939. (27) Peng, Y.; Li, J. Ammonia Adsorption on Graphene and Graphene Oxide: A First Principles Study. Front. Environ. Sci. Eng. 2013, 7, 403 – 411. (28) Chen, C.; Zhang, J.; Zhang, B.; Duan, H. M. Hydrogen Adsorption of Mg-Doped Graphene Oxide: A First-Principles Study. J. Phys. Chem. C 2013, 117, 4337–4344. (29) Zhao, Y.; Truhlar, D. G. The M06 Suite of Density Functionals for Main Group Thermochemistry, Thermochemical Kinetics, Noncovalent Interactions, Excited States, and Transition Elements: Two New Functionals and Systematic Testing of Four M06-class Functionals and 12 Other Functional. Theor. Chem. Acc. 2008, 120, 215–241. (30) Zhao, Y.; Truhlar, D. G. Applications and Validations of the Minnesota Density Functionals. Chem. Phys. Lett. 2011, 502, 1–13. (31) Lazar, P.; Karlický, F.; Jurečka, P.; Kocman, M.; Otyepková, E.; Šafářová, K.; Otyepka, M. Adsorption of Small Organic Molecules on Graphene. J. Am. Chem. Soc. 2013, 135, 6372−6377.



(32) Ramos-Berdullas, N.; Pérez-Juste, I.; Van Alsenoy, C.; Mandado, M. Theoretical Study of the Adsorption of Aromatic Units on Carbon Allotropes Including Explicit (empirical) DFT Dispersion Corrections and Implicitly Dispersion-Corrected Functionals: the Pyridine Case. Phys. Chem. Chem. Phys. 2015, 17, 575-587. (33) Samanta, P. N.; Das, K. K. Structural and Electronic Properties of Covalently Functionalized 2Aminoethoxymetallophthalocyanine–Graphene Hybrid Materials: A Computational Study. RSC Adv. 2015, 5, 85730–85740. (34) Ershova, O. V.; Lillestolen, T. C.; Bichoutskaia, E. Study of Polycyclic Hydrocarbons Adsorbed on Graphene Using Density Functional Theory with Empirical Dispersion Correction. Phys. Chem. Chem. Phys. 2010, 12, 6483-6491. (35) Hobza, P. Calculations on Noncovalent Interactions and Databases of Benchmark Interaction Energies. Acc. Chem. Res. 2012, 45, 663-672. (36) Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; et al Gaussian 09, Revision D.01; Gaussian, Inc.: Wallingford, CT, 2009. (37) Boys, S. B.; Bernardi, F. The Calculation of Small Molecular Interactions by the Differences of Separate Total Energies, Some Procedures with Reduced Errors. Mol. Phys. 1970, 19, 553–566. (38) Sedlak, R.; Janowski, T.; Pitoňák, M.; Řezáč, J.; Pulay, P.; Hobza, P. Accuracy of Quantum Chemical Methods for Large Noncovalent Complexes. J. Chem. Theory Comput. 2013, 9, 3364-3374. (39) 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. (40) Lee, S. K.; Yang, J. W.; Kim, H. H.; Jo, S. B.; Kang, B.; Bong, H.; Lee, H. C.; Lee, G.; Kim, K. S.; Cho, K. Inverse Transfer Method Using Polymers with Various Functional Groups for Controllable Graphene Doping. ACS Nano 2014, 8, 7968-7975. (41) Dai, Y.; Blaisten-Barojas, E. Energetics, Structure, and Charge Distribution of Reduced and Oxidized n-Pyrrole Oligomers: A Density Functional Approach. J. Chem. Phys. 2008, 129, 164903. (42) Grimme, S.; Mück-Lichtenfeld, C.; Antony, J. Noncovalent Interactions between Graphene Sheets and in Multishell (Hyper) Fullerenes. J. Phys. Chem. C 2007, 111, 11199–11207. (43) Cho, Y.; Min, S. K.; Yun, J.; Kim, W. Y.; Tkatchenko, A.; Kim, K. S. Noncovalent Interactions of DNA Bases with Naphthalene and Graphene. J. Chem. Theory Comput. 2013, 9, 2090–2096.


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(44) Wang, W.; Zhang, Y.; Wang, Y.-B. Noncovalent π⋅⋅⋅π Interaction between Graphene and Aromatic Molecule: Structure, Energy, and Nature. J. Chem. Phys. 2014, 140, 094302. (45) Mollenhauer, D.; Brieger, C.; Voloshina, E.; Paulus, B. Performance of Dispersion-Corrected DFT for the Weak Interaction between Aromatic Molecules and Extended Carbon-Based Systems. J. Phys. Chem. C 2015, 119, 1898–1904. (46) Ruuska, H.; Pakkanen, T. A. Ab Initio Study of Interlayer Interaction of Graphene: BenzeneCoronene and Coronene Dimer Two-Layer Models. J. Phys. Chem. B 2001, 105, 9541 – 9547. (47) Avramov, P. V.; Sakai, S.; Entani, S.; Matsumoto, Y.; Naramoto, H. Ab Initio LC-DFT Study of Graphene, Multilayer Graphenes and Graphite. Chem. Phys. Lett. 2011, 508, 86 – 89. (48) Fokin, A. A.; Gerbig, D.; Schreiner, P. R. σ/σ- and π/π- Interactions are Equally Important: Multilayered Graphenes. J. Am. Chem. Soc. 2011, 133, 20036 – 20039. (49) Lahaye, R. J. W. E.; Jeong, H. K.; Park, C. Y.; Lee, Y. H. Density Functional Theory Study of Graphite Oxide for Different Oxidation Levels. Phys. Rev. B 2009, 79, 125435. (50) Özkayaa, S.; Blaisten-Barojas, E. Polypyrrole on Graphene: A Density Functional Theory Study. Surf. Sci. 2018, 674, 1-5. (51) Sinnocrot, M. O.; Valeev, E. F.; Sherrill, C. D. Estimates of the Ab Initio Limit for π-π Interactions: The Benzene Dimer. J. Am. Chem. Soc. 2002, 124, 10887-10893. (52) Rao, K. S.; Senthilnathan, J.; Liu, Y. –F.; Yoshimura, M. Role of Peroxide Ions in Formation of Graphene Nanosheets by Electrochemical Exfoliation of Graphite. Sci. Rep. 2014, 4, 4237 – 4242. (53) Parr, R. G.; Donnelly, R. A.; Levy, M.; Palke, W. E. Electronegativity: The Density Functional Viewpoint. J. Chem. Phys. 1978, 68, 3801–3807. (54) Janak, J. F. Proof that ∂E/∂ni = in Density-Functional Theory. Phys. Rev. B 1978, 18, 7165–7168. (55) Parr, R. G.; Szentpaly, L.; Liu, S. Electrophilicity Index. J. Am. Chem. Soc. 1999, 121, 1922–1924. (56) Kheirabadi, N.; Shafiekhani, A. The Ground State of Graphene and Graphene Disordered by Vacancies. Physica E 2013, 47, 309–315. (57) Johnson, E. R.; Keinan, S.; Mori-Sánchez, P.; Contreras-Garcia, J.; Cohen, a. J.; Yang, W. Revealing Noncovalent Interactions. J. Am. Chem. Soc. 2010, 132, 6498 – 6506. (58) Lu, T.; Chen, F. Multiwfn: A Multifunctional Wavefunction Analyzer. J. Comput. Chem. 2012, 33, 580–592. (59) Hassan, M.; Walter, M.; Moseler, M. Interactions of Polymers with Reduced Graphene Oxide: van der Waals Binding Energies of Benzene on Graphene with Defects. Phys. Chem. Chem. Phys. 2014, 16, 33-37. 21 ACS Paragon Plus Environment


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Table 1. Computed adsorption energies (Ea), ZPE corrected (Ea,ZPE) and –D3 corrected (Ea,D3) adsorption energies, enthalpies of adsorption (ΔHads), and Gibbs free energy changes (ΔGads) for the adsorption of PPy on the surface of pristine graphene, graphene with defects, and graphene oxide materials using DFT and MP2 approaches with 6-31G(d) basis set. All the values are in kcal/mol unit. System

Ea

Ea,ZPE

Ea,D3

Ea

ΔHads

ΔGads

Level of Theory G-PPy

M06-2X

M06-2X

M06-2X-D3

MP2

M06-2X

M06-2X

-22.22

-20.15

-25.53

-33.78

-19.78

-7.22

DG1-PPy

-24.00

-21.66

-26.92

-35.23

-21.27

-6.87

DG2-PPy

-25.03

-23.13

-28.18

-36.29

-22.69

-8.28

GO1-PPy

-24.85

-21.38

-26.83

-32.67

-21.31

-5.28

GO2-PPy

-14.26

-12.88

-18.00

-20.43

-12.33

0.46

GO3-PPy

-33.49

-28.79

-34.38

-39.69

-28.83

-12.65

MLG-PPy

-23.45a

----

-29.01

-37.00

----

----

aOptimized

without ZPE

Table 2. Calculated dipole moment (D), HOMO-LUMO energy gap (Eg), chemical potential (µ), global hardness (η), and electrophilicity index (ω) for the PPy, pristine graphene, graphene with defects, graphene oxides, and multi-layered graphene materials at the M06-2X/6-31G(d) level of theory.

PPy

D (Debye) 2.38

Eg (eV) 6.72

µ (eV) -2.37

η (eV) 3.36

ω (eV) 0.83

G

0.00

1.85

-3.81

0.92

7.85

DG1

0.36

1.93

-3.72

0.96

7.17

DG2

0.00

1.93

-3.86

0.97

7.72

GO1

2.27

2.34

-3.90

1.17

6.50

GO2

4.59

2.44

-4.11

1.22

6.92

GO3

4.98

1.96

-4.23

0.98

9.13

MLG

2.93

1.84

-3.66

0.92

7.28

System


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Table 3. Computed dipole moment (D), HOMO-LUMO energy gap (Eg), chemical potential (µ), global hardness (η), and electrophilicity index (ω) for the PPy-adsorbed hybrid complexes of pristine graphene, graphene with defects, graphene oxides, and multilayered graphene materials at the M062X/6-31G(d) level of theory.

G-PPy

D (Debye) 1.64

Eg (eV) 1.81

µ (eV) -3.81

η (eV) 0.90

ω (eV) 8.02

DG1-PPy

1.03

1.93

-3.72

0.96

7.17

DG2-PPy

0.82

1.94

-3.86

0.97

7.68

GO1-PPy

2.80

2.37

-3.84

1.18

6.22

GO2-PPy

6.23

2.11

-4.02

1.05

7.66

GO3-PPy

2.40

2.15

-4.00

1.07

7.44

MLG-PPy

3.14

1.82

-3.65

0.91

7.32

System



FIGURE CAPTIONS Figure 1. M06-2X/6-31G(d) optimized geometries of (a) PPy, (b) G, (c) MLG, (d) GO1, (e) GO2, (f) GO3. Figure 2. Equilibrium geometries of PPy-adsorbed composite materials of (a) G, (b) DG1, (c) DG2, and (d) MLG; viewed from top as tube forms and from top and side as space-fill forms (VDW radii), respectively. Figure 3. Optimized structures of PPy-adsorbed hybrid complexes of (a) GO1, (b) GO2, and (c) GO3; viewed from top as tube forms and from top and side as space-fill forms (VDW radii), respectively. Figure 4. DOS spectra of (a) G-PPy, (b) DG1-PPy, (c) DG2-PPy, (d) GO1-PPy, (e) GO2-PPy, and (f) GO3-PPy (Vertical-dotted line represents the position of HOMO). Figure 5. Becke surfaces mapped with electron density (ρ) and normalized contact distance (dnorm), respectively, for (a) G-PPy, (b) DG1-PPy, (c) DG2-PPy, (d) GO1-PPy, (e) GO2-PPy, and (f) GO3-PPy. Figure 6. Plots of different electronic properties for MLG-PPy composite: (a) PDOS, (b) HOMO, (c) LUMO, (d) ESP map, (e) Becke surface mapped with ρ, (f) Becke surface mapped with dnorm, (g) RDG isosurface, and (h) RDG versus sign(λ2)ρ.


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Table of Content



Figure 1

ACS Paragon Plus Environment

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Figure 2



Figure 3


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Figure 4 ACS Paragon Plus Environment


Figure 5 ACS Paragon Plus Environment

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Figure 6


Deciphering the Impact of Surface Defects and Functionalization on

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