New Insight into the Aggregation of Graphene Oxide Using Molecular

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New Insight into the Aggregation of Graphene Oxide Using Molecular Dynamics Simulations and Extended Derjaguin-Landau-Verwey-Overbeek Theory Huan Tang, Ying Zhao, Xiaonan Yang, Dongmei Liu, Penghui Shao, Zhigao Zhu, Sujie Shan, Fuyi Cui, and Baoshan Xing Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b01668 • Publication Date (Web): 03 Aug 2017 Downloaded from http://pubs.acs.org on August 3, 2017

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Environmental Science & Technology

1

New Insight into the Aggregation of Graphene Oxide Using Molecular Dynamics

2

Simulations and Extended Derjaguin-Landau-Verwey-Overbeek Theory

3

Huan Tang

4

Zhu a,b, Sujie Shan a,b, Fuyi Cui a,b,*, and Baoshan Xing c,*

5

a

6

b

7

Harbin 150090, China

8

c

a,b,c

, Ying Zhao

a,b

, Xiaonan Yang

a,b

, Dongmei Liu

a,b

, Penghui Shao

a,b

, Zhigao

State Key Laboratory of Urban Water Resource and Environment, Harbin 150090, China School of Municipal and Environmental Engineering, Harbin Institute of Technology,

Stockbridge School of Agriculture, University of Massachusetts, Amherst, MA, 01003, USA

9

1

ACS Paragon Plus Environment


Table of Contents (TOC) Image Amount of H-bond

10

400 Lower pH

Higher pH

320

0

Interaction Energy (mJ/m2)

11

12

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5000 Time (ps)

10000

XDLVO

0 pH=3 pH=6 pH=9

-20 0

2 4 Separation distance (nm)

13

2


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14

ABSTRACT

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A comparative experimental and molecular dynamics (MD) simulation study was carried out

16

to investigate the aggregation of graphene oxide (GO). Mechanisms behind the effects of

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solution chemistries (pH, metal ions, and tannic acid (TA)) and GO topology (carboxyl

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content, GO size, and GO thickness) were uncovered. For example, MD results showed that

19

more hydrogen bonds formed between GO and water at higher pH, according well with the

20

increased hydrophilicity of GO calculated based on contact angle measurements. Radial

21

distribution functions analysis suggested Ca2+ interacted more strongly with GO than Na+,

22

which explained the experimental observations that Ca2+ was more effective in accelerating

23

the aggregation process than Na+. The adsorption-bridging and steric effects of TA were

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simulated, and TA was found to be unfolded upon wrapping on GOs, leading to an increased

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capacity for ion and solvent binding. The evaluations of contributions to GO hydrophilicity,

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electrostatic energy, and intensities of interactions with metal ions indicated carboxyl group is

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the essential functional group in mediating the stability of GO. Overall, by combining MD

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simulations with experimental measurements, we provided molecular-level understandings

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towards the aggregation of GO, indicating MD, if used properly, can be applied as a useful

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tool to obtain insights into the aggregation of nanomaterials.

31

INTRODUCTION

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Graphene oxide, abbreviated as GO, has been receiving increasing attention due to its

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exceptional properties.1, 2 GOs are widely used in the field of electronics, composite materials,

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and biomedical applications.3 With many promising applications, there are growing concerns

35

that GOs will enter natural water bodies throughout their life cycle. Recent studies have 3



5

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shown GOs are cytotoxic toward human cells,4,

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understand their fate in water and evaluate their environmental risks. Since the aggregation of

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nanoparticles (including GO) is one of the most important factors that ultimately control their

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fate,6 it is necessary to explore the aggregation of GOs in water.

demonstrating the research need to

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Aggregation of GOs in aquatic environments has been studied extensively in recent

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years.7-10 Findings from these studies illustrated that the aggregation of GO followed

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Derjaguin - Landau - Verwey - Overbeek (DLVO) theory; however, hydrophobic force was

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not considered in DLVO theory, and extended DLVO (XDLVO) theory should be employed

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to fully understand the aggregation of GOs. The response of hydrodynamic diameters (Dh) to

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different solution chemistries were measured to investigate the hydrodynamic properties of

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GO, and electrophoretic mobility (EPM) comparisons were employed to understand the

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effects of pH and ionic strength (IS). The increased stability at high pH was attributed to the

48

increased electrostatic repulsion between GOs, however, Wu et al. claimed it was not

49

sufficient to explain the GO stabilities under different pH regimes by using EPM

50

measurement alone.10 In addition, previous investigations mainly focused on macroscopic

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experiments, elucidating the roles of pH, IS, and natural organic matter (NOM). Limited

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efforts have been devoted to illustrate how these physiochemical conditions affect the

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behavior of GO from a microscopic perspective. Furthermore, carboxyl group was found to

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play an important role in determining the properties of GO in the field of materials synthesis,

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and limited published research has been conducted to evaluate the contributions of carboxyl

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groups on GO aqueous stability.11 GO sheet is essentially a network of hydrophobic benzene

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rings, bearing hydroxyl, epoxy and carboxyl groups on the basal plane and sheet edge.12 4


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Therefore, evaluating the effects of different groups is important in investigating the behavior

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of GO.

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Atomic-scale investigations with molecular dynamics (MD) simulations could contribute

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significantly to understanding microscopic processes and furnish many details that are not

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accessible experimentally.13-16 By utilizing MD, the microscopic aggregation of GO was

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found to be a point-line-plane process, and dominant forces including van der Waals (vdWs)

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attraction, electrostatic interaction, hydrogen bonds (H-bonds) interaction, π-π stacking, and

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hydrophobic interaction were found to be different in respective stages.17 MD simulations

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further suggested that the aggregates exhibit a GO-water-GO structure,18 and intra-layer and

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inter-layer configurations of H-bonds forming between GO and water were put forward.19

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However, these simulations were all carried out in pure water without containing ions or

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NOM, which are ubiquitous in real natural water.

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In addition to enhance the fundamental understanding of microscopic process, MD is also

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essential to make the link between experiment and theory; for example, in exploring the

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destructive extraction of phospholipids from Escherichia coli membranes by graphene

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nanosheets, transmission electron microscopy was employed to show the rough stages of

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extraction, and MD simulations to reveal the atomic details of the process.20 Gray et al.

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studied the membrane fouling using Liquid Chromatography UV254, and the results were

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supported by MD results.21 Liu et al. investigated uranyl and uranyl carbonate adsorption on

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aluminosilicate surfaces by performing MD simulations and the structures of the adsorbed

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complexes compared favorably with X-ray absorption spectroscopy results.13 Therefore, it is

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reasonable and important to explore the aggregation of GO combining experiment 5



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measurements and MD simulations.

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With the aforementioned discussion, no studies have been conducted to uncover the

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mechanisms behind the effects of solution chemistries and GO topologies on the aggregation

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of GOs, and no xDLVO calculations of the aggregation of GO were available. Therefore, we

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investigated the aggregation processes of GO using MD simulations and xDLVO calculations,

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and the effect of GO topology was also evaluated.

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MATERIALS AND METHODS

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Preparation of GO and Carboxylated GO Suspensions

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GO was synthesized through the reaction of graphite powder (Nanjing XFNANO Materials

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Tech Co., Ltd) with KMnO4 in a concentrated H2SO4 solution (the Hummers method).22

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NaOH and ClCH2COONa were used to convert GO to carboxylated GO (GO-COOH).23

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Detailed preparing methods were shown in Supporting Information Part One (SI1).

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Characterization of GO

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Physical dimensions of GO and GO-COOH were measured by AFM. XPS and FTIR were

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utilized to determine surface functionalities of GO and GO-COOH. The area under peaks was

95

used for quantifying the relative concentration of functional groups. The contents of different

96

functional groups were calculated from the XPS spectra.

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Aggregation Kinetics of GO

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Electrophoretic mobilities (EPM) and zeta potential were measured with a Zeta Sizer Nano

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ZS (Malvern Instrument, Worcestershire, U.K.). Changes of GO and GO-COOH

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hydrodynamic diameters (Dh) as a function of IS, pH, and the presence of NOM were

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measured by DLS. Because of the special geometrical structure of GO (a one-atom-thick 6


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sheet with a lateral size of micrometers), it appears that the DLS technique is not

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quantitatively reliable. Lotya and co-authors showed the mean nanosheet length of GO is

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proportional to Dh of GO measured by DLS.24 Therefore, the DLS analysis presented here

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should be viewed only as a qualitative indicator to shed light on the aggregation of GO, and

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DLS has been widely used in exploring the hydrodynamic properties of non-spherical

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particles (including GO).7, 9, 18, 25-30

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The GO concentration of 25 mg/L provided a strong DLS signal and was therefore used in

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all aggregation studies. The initial aggregation period was defined as the time period from

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experiment initiation (t=0) to the time when measured Dh values exceeded 1.50 Dh,initial. The

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particle attachment efficiency (α) was used to quantify particle aggregation kinetics：α =

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() ( ) → () ( ) , →,

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concentrations (CCC) of GO and GO-COOH were determined from the intersection of

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extrapolated lines through the diffusion and reaction limited regimes.

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Setup of the Simulation System

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Although multiple models for the structure of GO have been proposed, the most widely

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accepted is Lerf−Klinowski model, which suggests epoxy and hydroxyl groups are located on

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the basal plane (both sides), and carboxyl groups are attached to the carbon atoms on the

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edge.31, 32 Oxidized groups distribute randomly on either side of the basal plane.31 In order to

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quantify the oxygen content and proportion of these oxygen-containing functional groups,

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XPS characterization was employed. Based on our XPS characterization results (Table S3)，

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the model of GO (Figure 1(a)) was set to be C20O2(OH)2(COOH)1, and similar models were

123

employed by other researchers.33-35 The structure and chemical composition of tannic acid

, where N0 is the initial particle concentration.26 Critical coagulation

7



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124

(TA) is known and has been used as a NOM surrogate in the literature,36 therefore, TA was

125

employed to represent NOM in our studies. The model of TA is shown in SI2. Initially, two

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GO sheets were well separated (Figure 1 (b) and (c)), and the initial distance between the

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geometric center of each adjacent molecule was 2 nm. The GOs were then solvated in a cubic

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periodic box with the distance between the solutes and box boundary at least 10 Å. To study

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the effects of solution chemistries and different functional groups on the aggregation of GO,

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different simulation systems were employed and the details were provided in SI3. To make

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the simulation results more convincing, a statistical approach was employed: four sets of MD

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simulations were performed with different GO sizes, system sizes, water models, GO models,

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and GO layers. Details of each set of MD simulations are shown in SI3, and the detailed

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simulation methods are provided in SI4.

135 136

Figure 1. Setup of the simulation system. (a) The model of GO. (b) System setup for the aggregation of

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GO with the presence of metal ions. (c) System setup for the aggregation of GO with the presence of

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metal ions and tannic acids. H in white, O in red, C in black, the blue balls represent metal ions, the

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tiny red lines represent water molecules, the two sheers represent GOs, and the three smaller molecules

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represent tannic acids. The initial distance between each adjacent molecule was 2 nm.

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XDLVO Theory

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According to the XDLVO theory,37 the aggregation of GO (plate-plate system) is determined

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by electrostatic double layer (EDL) interactions, vdWs interactions, and Lewis acid-base (AB) 8


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144

interactions, which can be calculated using the following equations: 38, 39

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ΦEDL = ε ε ψ 2 [ () + 1 - coth (kh)]

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ΦvdW = -

147

ΦAB = ∆G!" exp (

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The total interaction energy (Φ) between GOs: Φ = ΦEDL + ΦvdW + ΦAB

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Permittivity of free space (ε0) and the dielectric constant of water (ε) were 8.854×10-12 C/V•

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m and 78.5;7 zeta potential value was used in the place of surface potential ψ; h is the

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separation distance between GOs. λ is the characteristic decay length of AB interactions in

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water, whose value is between 0.2 and 1.0 nm, and a commonly used value of λ for aqueous

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systems is 0.6 nm. 38, 39 h0 represents the minimum equilibrium cut-off distance and is usually

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assigned a value of 0.157nm.40, 41 k (nm-1) is the inverse of Debye length and was calculated

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using the following equation: 39

156

# = &*

157

where kB is Boltzmann’s constant (1.38064852×10−23 J/K) 42, T is absolute temperature (300K

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was employed in our study), NA is the Avogadro number (6.022140857×1023 mol−1)

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ionic strength (mol/L) and e is the electron charge (1.6021766208×10−19 C) 44. Based on these

160

values, (5-1) can be transformed to:

161

≈ 3.28√I

162

A represents the Hamaker constant and was calculated using:45

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&1 45 45 2 A=24 π ℎ ( 23 − &15 )

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∆G!" is the acid-base free energy per unit area and was calculated using: 45

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9 9 # ∆G!" = 2 [7189 (27123 − 718# ) +718#(27123 − 7189 ) −2 7γ# ;< γ;< ]

166

To obtain the value of A andΔGAB, the contact angles (θ) of three probing liquids (water,

167

glycerol, and formamide) (3 µL) were acquired with a contact angle goniometer (Kino

168

SL200B) using thin GO films produced by drying concentrated GO suspensions on clean

169

glass slides. As the surface interfacial tension parameters of the selected probing liquids were

(1) (2)

# ) $

(3)

' '( ) +, -

(4)

(5-1)

43

, I is

(5)

(6)

(7)

9



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9 45 # known, the vdWs (123 ), electron-accepting (123 ), and electron-donating (123 ) interfacial

171

tension values for GO could be determined through the following equations:46

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9 45 # 1=4 (1+cosθ) = 2&1=45 123 + 271=9 123 + 271=# 123

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where i represent water, glycerol, and formamide, and the values of 1=∗ are shown in TableS4.

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RESULTS AND DISCUSSION

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Characterization of GO and GO-COOH Sheets

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Physical dimensions of GO and GO-COOH measured by AFM are shown in Figure S4. The

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GO and GO-COOH sheets are single-layered in the absence of ions. The average thickness of

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GO and GO-COOH are determined to be 0.70 ± 0.14 nm, consistent with typical GO

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samples.47 FT-IR and XPS results are summarized in SI5.

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Electrokinetic and Hydrodynamic Properties under Different pH Regimes

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As shown in Figure S6 (a), the EPMs of GO remained negative over the pH range from 0.3 to

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12. As pH increased, the EPMs decreased sharply from about -(0.52±0.14)×10−8m2V−1s−1 to

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-(3.5±0.01)×10−8m2V−1s−1. The changes of EPM at different pH conditions were caused by the

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dissociable functional groups on GO.27 GO Dh measured after 15 minutes at different pH

185

levels are presented in Figure S6(b). The response of Dh to varying pH was similar to that of

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EPM, with GO Dh being constant (∼150 nm) from pH 12 to 4, and then increasing sharply as

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pH decreased. The increasing stability at higher pH was also observed for other

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oxygen-containing functional group rich nanomaterials, and was attributed to a larger

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electrostatic repulsive force as inidcated by EPM measuremenrs.48 However, EPM

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measurements alone may have limitations in describing particle stability7,

191

simulations and XDLVO calculations were performed to further interpret the effect of pH on

(8)

49

, and MD

10


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192

the behavior of GO.

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The Aggregation of GO under Different pH Regimes

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of carboxylic group, and 9.8 corresponding to the ionization of the hydroxyl group.50 The

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range of pH usually observed in aquatic environment is from 5 to 9 7, indicating only

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carboxylic groups in GO are deprotonated, while the hydroxyl groups are protonated.

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Therefore, two GO models were employed: a) 90% of the carboxylic groups were protonated

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(C20O2(OH)2(COOH)0.9(COO-)0.1) to simulate the GO at lower pH values, b) 90% of the

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carboxylic groups were deprotonated (C20O2(OH)2(COOH)0.1(COO-)0.9) to simulate the GO at

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higher pH values. (a)

6

0 3

distance 0

202

1

L-J Potential

10000 Time (ps)

-1 20000

4

(b) 0

3 -80 2 0

distance L-J potential 10000 20000 Time (ps)

(c) Amount of H-bond

Distance (nm)

9

Potential Energy (kJ/mol)

The pKa values of GO are 4.3, 6.6, and 9.8, with 4.3 and 6.6 corresponding to the ionization

Potential Energy (kJ/mol) Distance (nm)

194

400

Higher pH

320

0

Lower pH

10000 Time (ps)

20000

203

Figure 2. Molecular dynamics simulation results. (a) Distance and L-J potential energy between GOs

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at higher pH values. (b) Distance and L-J potential energy between GOs at lower pH values. (c)

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Amount of H-bonds forming between GOs and water at lower or higher pH values. The initial distance

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between GOs was 2.0 nm. "Distance" here means the distance between the geometric centers of GOs.

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Negative potential value implies attraction between GOs, and positive value implies repulsion. Blue

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and purple dotted lines are used to distinguish the early aggregation stage and the aggregation stage.

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At higher pH (Figure 2 (a) and video S1), the distance between GOs kept increasing and no

210

aggregation was observed during the simulation of 20 ns. As the distance was beyond the

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scope (1.0nm) of vdWs interaction throughout the aggregation process, L-J potential energy

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kept constant at 0 kJ / mol. 11



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At lower pH (video S2), the equilibrium state was obtained within about 5000 ps (Figure 2

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(b)). Two distinctive representative stages for the aggregation are identified (although the

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detailed time scales may different in different simulations, the overall trend is consistent in all

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of them). (1) early aggregation stage (~0-2450 ps, blue dotted line): L-J potential energy and

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electrostatic potential energy kept constant at 0 kJ/mol, with GO diffused freely in the solvent

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and adjusted their motion direction. (2) aggregation stage (~2450 ps-4700ps, purple dotted

219

line): L-J potential energy kept negative and decreased to the minimum value, with GOs

220

aggregated quickly. It can be speculated that whether GOs can aggregate was governed by the

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first stage. In this stage, GOs may separate from each other or approach to each other. If GOs

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kept separating from each other, they would disperse in water and had no opportunity to

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aggregate. If GOs approached one another at the end of this stage, then the subsequent

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aggregation stage started. The initial distance between geometric centers of GOs was 2 nm,

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which was beyond the scope of short-range forces (cut off for vdWs:1 nm, H-bond interaction:

226

0.35 nm

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approaching was hydrophobic interaction53. Therefore, hydrophobic interaction played

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dominant roles in the aggregation, which controls both the kinetics and thermodynamics.

51

, and π-π stacking: 0.35 nm

52

), indicating the driving force that accelerated the

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GO is amphiphilic54, and the hydrophilicity of GO can be measured by the ability to form

230

H-bonds with water. As shown in Figure 2(c), at higher pH, more H-bonds formed between

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GO and water, causing GO to favor the aqueous medium and decreasing the aggregation

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efficiency. The acid-base interfacial free energy △ G!" is also a measure of

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hydrophilicity/hydrophobicity; when △ G!" >0, the material immersed in water is

234

considered hydrophilic, and when △ G!"

New Insight into the Aggregation of Graphene Oxide Using Molecular

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