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Differential Response of Doped/Defective Graphene and Dopamine to Electric Fields: A DFT Study Josue Ortiz-Medina, Florentino Lopez-Urias, Humberto Terrones, Fernando Jaime Rodríguez-Macías, Morinobu Endo, and Mauricio Terrones J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.5b04165 • Publication Date (Web): 27 May 2015 Downloaded from http://pubs.acs.org on June 4, 2015

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

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The Journal of Physical Chemistry

Differential Response of Doped/Defective Graphene and Dopamine to Electric Fields: A DFT Study J. Ortiz-Medina1,2, F. López-Urías2*, H. Terrones3, F. J. Rodríguez-Macías2,4, M. Endo5, M. Terrones1,5,6 1

Research Center for Exotic Nanocarbons (JST), Wakasato 4-17-1, Nagano 380-8553, Japan. Advanced Materials Department, IPICYT Camino a la Presa San José 2055, Col. Lomas 4ª sección, San Luis Potosí S.L.P., 78216, México. 3 Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy 12180, USA 4 Department of Fundamental Chemistry, Universidade Federal de Pernambuco, Av.Prof. Luiz Freire, Recife, PE, 50740-540, Brazil 5 Institute of Carbon Science and Technology, Shinshu University, 4-17-1 Wakasato, Nagano 380-8553, 2

Japan 6

Department of Physics, Chemistry, Materials Science and Engineering, Center for 2-Dimensional and Layered Materials and Materials Research Institute. The Pennsylvania State University, 104 Davey Lab., University Park, PA 16802-6300.

Keywords: doped graphene, dopamine, DFT, electric-field.

Abstract First-principles Density Functional Theory (DFT) calculations are performed on dopamine (DA)-graphene systems in the presence of an external electric field. The graphene lattice is also modified via substitutional boron- and nitrogen-doping, and via the introduction of defects (monovacancy and Thrower-Stone-Wales). Geometry optimization, electronic density of states, cohesive energy, electronic charge density, and wave functions are analyzed. Our results revealed that dopamine is anchored on the surface of graphene via a physisorption mechanism, and the cohesive strength varies as B-doped > N-doped > Vacancy defect > Thrower-StoneWales defect. Boron-doped graphene exhibits valence states with dopamine molecules, furthermore this system showed the strongest cohesive energy. When an electric field is applied, 1

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we observed shifts in the valence states near the Fermi level producing a decrease in the molecule-layer interaction. We envisage that the present contribution could help developing novel biosensors based on doped/defective graphene FET devices.

1. Introduction Graphene-based devices possess important advantages for detection of specific molecules. Several reports on theoretical1–3 and experimental4–9 research have demonstrated that graphene has outstanding properties such as high electrical conductivity, quantum Hall effect, and a band gap tunable by chemical and physical doping, including the application of external electric fields. Based on electrostatic interactions between different chemical species and graphene it is possible to efficiently sense molecules within graphene Field Effect Transistors (FET).10–12 In this context, Schedin et al.13 reported graphene-based sensors capable of detecting individual gas molecules. Such extremely high sensitivity has been attributed to charge transfer phenomena occurring at the graphene surface, combined with the large changes in carrier density caused by the injection of electrons or holes. Alternate explanations of the sensitivity of graphene consider chemical doping processes driven by electrostatic interactions between the graphene surface and charged sections of adsorbed molecules. For example, Nistor et al.14 refer to the 2D surface-induced electronegativity equalization produced by the conductive nature of graphene and special alignments between the adsorbate-graphene highest-occupied and lowest-unoccupied molecular orbitals (HOMO-LUMO).

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The doping of graphene and other carbon nanomaterials can be a practical route to tailor some of their properties,15 as it can alter the available charge density by the incorporation of noncarbon atoms with excess electrons (e.g. nitrogen, for n-type doping) or electron deficiency (e.g. boron, for p-type doping).6,16–18 Doping of carbon nanomaterials also increases chemical activity near the doped sites due to localization of electronic states and reduced charge mobility caused by electron scattering, which can be useful in FET devices for high sensitivity detectors.19,20 Moreover, the electronic properties of graphene can also be changed when introducing defects within its lattice.21,22 For example, graphene lattice vacancies induce strong localization of electronic states close to the Dirac point,23 thus enhancing chemical reactivity similar to doping. In addition, theoretical studies show that 5-7 defects boundaries (i.e. geometrical flat arrangements of carbon atoms, consisting in consecutive pentagons and heptagons) in between two regular graphene hexagonal lattices exhibit different electronic, magnetic and spin dependent conductance properties.24

Further advancements on graphene-based sensors development can greatly benefit from a thorough understanding of how analytes interact with doping or point defect on graphene. Such understanding could even enable tailoring the response of graphene sensors by controlling its electronic properties via defect/doping engineering. It could be argued that interactions with different substances produce different effects on the graphene electronic behavior depending on how doping or defects change its electronic properties. This in turn could be advantageous in detection of biomolecules, since such chemical species are more complex when compared to simple gaseous molecules. The feasibility of biosensors based on carbon nanomaterials has been

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demonstrated by reports on interactions between graphene or carbon nanotubes with biomolecules such as aminoacids,25,26 neurotransmitters27,28 and drugs,29,30 but the use of doping and defect structures in such sensors has not yet been studied in detail.

In this work, we investigate the interactions of dopamine (DA) with pure (undoped), boron (B), and nitrogen (N) doped graphene, as well as defects including monovacancies and 5775 defects (or Thrower-Stone-Wales (TSW) defects) within the graphene sheet. We selected DA because it is an important biomolecule with strong regulation effects on a wide range of biological processes, including neural processes.31 In addition, DA is also representative of catecholamines, fundamental biomolecules with structures based on benzene rings with two hydroxyl groups and an amino-terminal side-chain. Dopamine is one of the most important neurotransmitters, implicated in several neurological disorders, including Parkinson’s disease, depression and addictions. Thus, reliable detection of DA is of great clinical importance. Several studies have used graphene based materials, including N-doped graphene, for electrochemical detection of dopamine, as recently reviewed.32 More recent reports33 show that nitrogen doped “graphene foam” 3D-nanostructures can result in highly efficient sensing of DA, down to nanomolar levels and with good selectivity. Studies for detection of dopamine via electrochemical techniques have shown that the HOPG surface may be active in oxidizing DA, even though it was previously believed that DA would only interact with edge sites during electrochemical reactions.34 This stresses the importance of understanding how DA interacts with graphene, and points to the need to assess whether electric fields enhance such interactions. In order to address this, we studied systematically the effect of

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different doping and defect types on graphene-DA interactions, with and without an external electric field. To the best of our knowledge, this is the first study explore the combination of perpendicular E-fields with doped/defective graphene in order to follow biomolecule interactions, important when developing carbon-based biosensors, as well as to contribute towards the understanding of field effect transistor (FET) based biomolecule sensors using graphene.

2. Computational methods Electronic calculations of the interaction between dopamine and graphene were performed using density functional theory (DFT)35,36 in the framework of the general gradient approximation (GGA) within the Perdew-Burke-Ernzerhof (PBE) approach37 with a basis of linear combination of atomic orbitals (LCAO) as implemented in the SIESTA code.38,39 We used a double-ζ basis set plus polarization orbitals (DZP), the real-space grid used for charge and potential integration is equivalent to a plane wave cut-off energy of 250 Ry and the pseudo-potentials (pp) were built from 1, 3, 4, 5, and 6 valence electrons for the hydrogen (H: 1s1), boron (B: 2s22p1), carbon (C: 2s22p2), nitrogen (N: 2s22p3), and oxygen (O: 2s22p4) atoms respectively. The different systems were constructed using a 6x6 graphene supercell with minimum vertical cell dimension of 40 Å to avoid graphene layers interactions. All the calculations were performed using a MonkhorstPack grid of 25×25×1 k-points, and relaxed by conjugate gradient minimization until the maximum forces were lower than 0.06 eV Å-1, including control calculations using auxiliary Grimme potentials for accounting dispersion interactions (see Supporting Information). We also analyzed

the

electronic

structure

of

the

dopamine

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molecule,

(2-(3,4-


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dihydroxyphenyl)ethylamine, C8H11NO2 figure 1a), which has two hydroxyl groups and an ethylamine (-CH2-CH2-NH2) joined to a benzene aromatic ring. Figures 1b-f show the supercells of pristine-, doped-, and defective-graphene structures. The dopamine molecule is placed on the different graphene structures as illustrated in figure 1g. Finally, for analyzing the effects of perpendicular electric fields, a static and uniform external potential was defined for all the systems, with electric field oriented perpendicularly to the graphene surface (as indicated in figure 1g) with a magnitude of 0.1 V Å-1.

3. Results and discussion Figure 2 depicts the density of states (DOS) and wave functions around the Fermi level (EF) for DA, with the highest-occupied molecular orbital (HOMO, the molecule's valence orbitals) at 2.815 eV, whereas the lowest-unoccupied molecular orbital (LUMO) is located at 1.219 eV. Wave function isosurface plots corresponding to the HOMO-1, HOMO, LUMO, and LUMO+1 energy levels are also shown in figure 2, where it can be observed that the amino group shows electronic states mainly in the valence levels. It is noteworthy that the benzene ring possess states in both occupied and unoccupied levels that related to the π and π* states arising from its aromaticity, and are in fact the main source for the different interactions and charge transfer events with the graphene layer (see below).

In order to analyze the stability of the interactions between DA and the different doped/defective graphene layers, the systems were relaxed using a conjugated gradient algorithm. After geometry optimization, total energy and different electronic properties were calculated. The

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cohesive energy (Ec) was calculated as: Ec = EG–DA– EDA– EG, where EG–DA is the energy for the complex system (graphene and dopamine), EDA for the isolated single dopamine molecule, and EG the energy of the undoped or doped graphene used in the calculations. The counterpoise correction for the basis set superposition error was applied for all the systems and considered in the energy calculations.40,41 Figure 3 shows the results for each particular system and when applying an E-field noticeable differences appear on the cohesion energy, which can be attributed to alterations in the electronic local distribution at the doping/defect sites resulting in different configurations of occupied states in which DA valence orbitals can interact. For systems analyzed without an E-field, B-doped graphene has the most stable interaction with DA (Ec = –436 meV), while N-doped graphene exhibits weaker DA physisorption (Ec = –192 meV). Less energetically favorable interactions occur between DA and vacancy defective graphene (Ec = –111 meV), and the most favorable defective graphene possess TSW defects (Ec = –55 meV). These defects disrupt π-π interactions between the aromatic ring of DA and the graphene sheet. An external E-field produces significant changes (ca. 140 meV) in Ec between DA with pristine or B-doped graphene. For N-doping the difference with or without E-field is negligible (Ec ≈ – 190 meV). Finally, for DA and graphenes with structural defects, monovacancy produces slight stability changes as a function of the E-field (∆Ec ≈ 67 meV) and much smaller ones for TSW defects (20 meV). Our results are comparable with published data on interactions between graphene and other biomolecules. For example, theoretical studies establish that for L-leucine, the adsorption energies (equivalent to our cohesion energies) can go from -170 to -310 meV, depending on the orientation of the aminoacid molecule over the graphene sheet,12 whereas for other organic molecules such as tetracyanoquinodimethane, these energies range from -151 to -

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635 meV.10 Moreover, we show here how these cohesion energies can be tuned by applying an external E-field, especially for the undoped and B-doped graphene, an effect which has not been studied before.

In order to evaluate the relaxed structures of DA adsorbed on graphene, we calculated perpendicular distances from nitrogen (labeled as dN) and oxygen atoms (labeled as dO1 and dO2) to the graphene basal plane for all systems (see the model in figure 4). The distances are listed on table 1, where the effects of E-field can be compared. Distance changes are well related with cohesive energies: the B-doped graphene case, which was the most stable system, also shows the closest approach (0.7 Å) to graphene when the E-field is applied. However, N-doped and TSW-defected cases, which are insensitive to E-field, also show no DA-graphene distance variations. All these results could be explained by the fact that any effective interaction between DA and graphene involves a certain amount of charge transfer, which polarizes the system and produces local electrostatic repulsive-attractive forces.

Figure 5 shows the calculated DOS for undoped (a-b), B- (c-d) and N-doped (e-f) graphene with DA systems, with and without an applied E-field. The filled plots correspond to pure DA states, whereas the line plots represent the whole system (i.e. DA + graphene) states. Figure 6 depicts the corresponding molecular models with and without an applied E-field, including electron density isolines for each case: (a-b) undoped, (c-d) B-doped and (e-f) N-doped graphenes + DA. Only the electron density isolines for states ±0.25 eV around DA HOMO are shown for the sake of clarity. From DOS plots and electronic density distribution, it is clear that interactions

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between DA and B-doped graphene are stronger when compared with N-doped or undoped graphene in terms of orbital mixing, even though both B-doped and undoped graphene upshift DA to energetic levels close to EF. The local electron deficiency produced by B-doping promotes charge transfer (see table 2) from DA to graphene, thus the electronic states spread as depicted in the DOS plots and in the overlapping electron density cloud in figs. 6c and d.

The DOS and electronic density isolines for defected graphene systems (figures 7 and 8) show that vacancy defects shift DA states closer to EF when compared to TSW defects (compare figures 7a-b against 7c-d), inducing some degree of orbital mixing, visible on figure 8a. Nevertheless, such interactions are smaller than with B-doping, since charge transfer is considerably smaller (0.13 vs 0.04 e-), and only when an E-field is applied (see table 2). For the TSW-defected graphene, as well as for undoped and N-doped cases, there is neither orbital mixing nor significant charge transfer, since DA states are too far from EF to promote strong electronic interactions.

Table 2 also shows how the E-field changes the intrinsic DA energy gap (∆Eg), i.e. the energy difference between DA HOMO and LUMO. While B-doped and vacancy-defected graphene reduce Eg of adsorbed DA molecules; pristine, N-doped and TSW-defected graphene increase it when the perpendicular E-field is applied. Table 2 also shows that pristine, N-doped and TSWdefected graphene produce the largest upshifts in DA HOMO energy when the electric field is applied. These differential effects on the electronic structure of adsorbed DA suggest an additional route for optical detection,42 since graphene doping appears to improve the optical

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gap tuning of adsorbed molecules. In this case, for example, B-doping produces significant gap reduction when an E-field is applied, reducing the DA optical gap (found in the UV range) by 60 meV.

It is important to note that topological defects have been observed in graphene membranes,39 and we show here that such features can have an important effect in the interaction of graphene with organic molecules. Our calculations of DA adsorbed on graphene systems, with and without an applied electric field, display unique results not shown in previous studies where different types of organic molecules are placed in the surroundings of graphene sheets. For example, most of the reports that have addressed the changes occurring in the graphene’s electronic properties by electric fields focus on pure or doped graphene, with one or two layers typically2 and without studying the interaction with other molecules. The effects of applied electric fields over doped graphene systems towards adsorption/desorption have so far only been reported for simple molecules such as CO and H2.43,44 Different studies addressing biomolecules adsorption in graphene are commonly limited to the analysis of the interaction energies and changes in graphene properties.45–47 In here, we demonstrate that the use of electric fields, in combination with different type of doping or defect sites in graphene, has significant effects on the sensitivity for specific molecules, and the adsorption strength of molecules on the active sites, which can affect the performance of high sensitivity sensors.

4. Conclusions Our findings show that both doping and structural defects have important effects in the

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interaction of graphene with biomolecules. This could be important in experimental studies where it is commonly assumed that the graphene sheets are free from defects, and also points the way to a potentially simple way of controlling the selectivity and sensitivity of graphene sensors via defect engineering. In summary, using DFT-calculations we investigated the dopamine molecule (DA) interacting with pristine-graphene, B-, N-doped graphene, vacancy- and TSW-defects within graphene. The electric field effects on the adsorption energy were analyzed. Our DFT results revealed a physisorption mechanism for DA over the different graphene sheets, attributable to relatively stable interactions between π electrons of the DA aromatic ring and the graphene's surface. Interestingly, the DA-graphene interaction can be controlled by an external E-field, especially for pristine and B-doped graphene, whereas N-doped graphene-DA interactions are insensitive to it. Defective graphene can be utilized as well for energetically stable adsorption of DA, with a smaller sensitivity to E-fields when compared to doped graphene. All these phenomena are related to the way DA valence levels mix with graphene's valence band, which is stronger when localized electronic states are available below the graphene EF. These results also demonstrate the feasibility of using doped and defective graphene based FET or optical devices for the development of biosensors, for DA and potentially other biomolecules.

Corresponding Author *To whom correspondence should be addressed: [email protected]. Tel/Fax: +52 4448342000 (ext. 7238)/+52 4448342040 Acknowledgments 11



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This work was sponsored by the JST-Japan by funding the Research Center for Exotic Nanocarbons, under the Japanese regional Innovation Strategy Program by the Excellence. M.T. acknowledges the financial support from the MURI project award No. FA9550–12–1–0471. FLU acknowledges the partial support by CONACYT-México grant 60218-F1. FJRM acknowledges CONACYT-Mexico grant CB-2008-SEP-107082 for parts of this work made at IPICYT and the support of Rede NANOBIOTEC-Brasil (Edital 04/CII-2008 CAPES/MEC), and of FACEPE (BFP-0132-1.06/13) for a stay as visiting professor at UFPE, as well as IPICYT for the leave of absence granted for this stay.

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Note: For BSSE correction, additional energy calculations are performed considering ghost orbitals for individual dopamine and graphene systems, which prevents the orbital superposition error. Specifically, an extra energy term is subtracted to the typical cohesion energy calculation: Ec = EG-DA – EDA – EG - Ecc, where Ecc equals to the sum of the differences between energies of individual dopamine or graphene with and without ghost orbitals.

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FIGURES AND CAPTIONS Figure 1: J. Ortiz-Medina et al.

Figure 1: (a) Dopamine molecule. Unit cell representations for: (b) pristine or undoped graphene, (c) boron-doped graphene, (d) nitrogen-doped graphene, (e) vacancy-defect into graphene, and (f) Thrower-Stone-Wales (TSW) defect into graphene. (g) Optimized structure of adsorbed dopamine molecule on pristine graphene under the presence of an external electric field

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Figure 2: J. Ortiz-Medina et al.

Figure 2: Electronic density of states (DOS) showing the energies distribution for an isolated dopamine (DA) molecule. Right side depicts the isosurfaces plots of wave functions corresponding to HOMO-1, HOMO, LUMO and LUMO+1.

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Figure 3: Cohesion energy (in meV) of the different systems studied with an applied electric field, perpendicular to the graphene plane with a magnitude of 0.1 V Å-1, (red squared marks) and without applied E-field (blue rounded marks). Top panels depict the corresponding relaxed structures.

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Figure 4: Lateral and front molecular model views of dopamine (DA) molecule anchored on graphene systems. The different distances (dO1, dO2, dN) represent the separation between DA molecule (from O and N) and graphene basal plane. The indicated distances are reported table 1.

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Figure 5: Density of states (DOS) for dopamine (DA) molecule anchored on (a) pristine (pure), (c) B-doped and (e) N-doped graphene systems. For each system, results with an external applied electric field are also shown (b, d, f, respectively). The states for isolated DA are highlighted by the shaded DOS plot, where differential shiftings towards EF as the E-field is applied can be observed.

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Figure 6: Contour lines for electron density of (a, b) pure graphene and dopamine (DA) molecule, (c, d) B-doped graphene and DA, and (e, f) N-doped graphene and DA. The models show differential electron density distribution without electric field (a, c, and e) and with electric field applied (b, d, and f). The white arrows indicate the sites of the boron doping (c and d) and N doping (e and f) in the graphene lattice.

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Figure 7: Density of states (DOS) for dopamine (DA) molecule and (a) vacancy defected graphene and (c) Thrower-Stone-Wales defected graphene systems. The corresponding DOS plot for each system under an applied electric field is presented as well (b, and d, respectively). The DA states are highlighted by the shaded DOS plot, where differential shiftings towards EF are observed with the application of the E-field.

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Figure 8: Contour lines for electron density of (a, b) vacancy defected graphene and dopamine (DA), and (c, d) Thrower-Stone-Wales defected graphene and DA. The models show differential electron density distribution without electric field (a and c) and with electric field (b and d). The white arrows indicate the site of the vacancy (a and b) and Thrower-Stone-Wales defect (c and d) into the graphene lattice.

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TABLES AND CAPTIONS

Table 1: J. Ortiz-Medina et al. dO1 (Å)

dO2 (Å)

dN (Å)

System

Without Field

With E-Field

Without E-Field

With E-Field

Without E-Field

With E-Field

Undoped

2.84

2.87

2.9

2.88

4.87

4.93

B-doped

2.83

2.76

2.94

2.87

4.46

4.41

N-doped

2.87

2.91

2.91

2.92

4.69

4.69

Vacancy-defected

2.95

3.01

2.71

2.77

4.75

4.61

TSW-defected

2.86

2.87

2.85

2.86

4.85

4.85

Table 1: Distances (in Å) for three heteroatoms from dopamine (DA) molecule to graphene after geometry relaxation, measured perpendicularly to graphene basal plane (see figure 4). The distances are presented for each system, and compared with and without applied E-field.

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Table 2: J. Ortiz-Medina et al. System

Charge transfer DA→graphene (e-)

∆Eg (meV)

HOMO Upshiftings (meV)

without field

with E field

Undoped

-0.01

(*)

63

291

B-doped

0.15

0.13

-60

30

N-doped

(*)

0.01

90

270

Vacancy-defected

(*)

0.04

-15

120

TSW-defected

0.01

0.03

24

203

Table 2: Calculated results for electronic interaction between DA and graphene films. For the charge transfer (in e-) from dopamine (DA) molecule to graphene (*) indicates a negligible (

Defective ... - ACS Publications

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