Page 1. 1. Supporting Information for: Graphene Oxide Thin Films: Influence of the Chemical Structure and. Deposition Methodology. R.S. Hidalgo, D.
Supporting Information for:
Graphene Oxide Thin Films: Influence of the Chemical Structure and Deposition Methodology
R.S. Hidalgo, D. López-Díaz, M. Mercedes Velázquez* Departamento de Química Física, Facultad de Ciencias Químicas. Universidad de Salamanca, E-37008-Salamanca, Spain.
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1. NANOPLATELET SIZE DETERMINED FROM DLS MEASUREMENTS. We use Dynamic Light Scattering measurements to obtain information about the effect of the purification procedure on the nanoplatelet size. It is necessary to consider that the DLS equipment uses the spherical geometry to obtain the hydrodynamic radius while graphene oxide flakes do not present this geometry; therefore, our results are just a raw estimation that acceptably agrees with the size values estimate from the SEM images, see below. All the DLS experiments present non-exponential correlation functions, Fig.S1, that when analyzed using regularized inverse Laplace transforms, (ILT) CONTIN, give complex distribution functions. Insets of Fig. S1 present the distribution functions on app
the apparent hydrodynamic diameter scale ( dH ). As can be seen, the distribution curves are asymmetric and very broad; this is signature of populations of different size.
Figure S1. Time Autocorrelation Functions (ACF) and Relaxation times distribution peaks of different graphene oxide samples obtained by DLS measurements. For comparison lines represent values calculated from mono-exponential functions.
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2. NANOPLATELET SIZE DETERMINED FROM SEM IMAGES In order to estimate the size of nanoplatelets deposited onto the solid substrate, SEM images have been analyzed by using the free ImageJ software. The procedure used consists in which the area occupied by the particles is distinguished from the background using a cutoff at an adequate threshold of intensity. Then, the ImageJ software of the program selects the nanoplatelet and calculates the area. To illustrate the procedure followed Figure S2 shows the SEM image (left) and the generated image from ImageJ used to calculate the nanoparticle area (right). The results presented in Figure S2 correspond to GO but similar images were employed for the rest of samples. For the sake of clarity, images in Figure S2 correspond to dilute regions, but the final values of particle size are the average from at least 200 nanoplatelets.
Figure S2. SEM image of GO nanoplatelets deposited onto Si/SiO2 (left) and area of nanoplatelets calculated by using the Image J software.
In order to compare results obtained from DLS and SEM measurements, the area of the sheets was expressed in terms of diameter by assuming that all nanoplatelets are circular. Despite this is an approximate method because nanoplatelets do not present a circular section, we believe that is good approximation to compare the size of graphene 3
oxide samples dissolved in water and deposited onto solids. Comparison between the frequency analysis of the sheets and the DLS curves, red lines in Fig. S3 shows good correspondence between the size obtained by the two methodologies, DLS and SEM. This gives a strong support to the values of nanoparticle size determined by DLS measurements and proves that there are not changes on the nanoplatelet size during the transfer processes. 60 Particle Number Distribution
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GO
30 NGO
30 40
20
20 20
20
10
0 0
2000
0 6000
4000
10
10
0 0
2000
0 6000
4000
D / nm
D / nm
Particle Number Distribution
PGO
40
30
50
PNGO
30
40 30 20
20
30
20 20 10
10
10
0 0
2000
4000
0 6000 D / nm
10 0 0
2000
4000
0 6000 D / nm
Figure S3. Size Frequency analysis of different samples (column bar) obtained from SEM images. The black line corresponds to the fit of the frequency analysis data to a Gaussian function. The red lines represent the distribution functions obtained by DLS measurements.
3. ISOTHERMS OF GRAPHENE OXIDE AT DIFFERENT pH SUBPHASES To study the role of the carboxylic acids on the interaction between nanoplatelets, we have analyzed the effect of the pH on the morphology of the isotherms and on the values of parameters of the Volmer model. Taking into account the pK values reported for graphene oxide, 4.3, 6.6 and 9.8 we have selected the pH range of 2-14; however, monolayers at pH ≥ 9 present high solubility in the subphase and isotherms do not reproducible. Therefore, we present results corresponding to stable monolayers, pH ≤ 9. On the other hand, to minimize the GO dissolution in the aqueous 4
subphase, we have chosen graphene oxide synthesized from graphite because it renders the most stable Langmuir monolayer. This is because it presents the most accurate charge/size ratio to remain pinned at the interface.1, 2 The isotherm of GO adsorbed on aqueous subphases of different pH are shown in figure S4. For clarifying, isotherms corresponding with pH=3 and pH=7 have been removed from the graph in order to avoid overlapping of experimental data. Lines in Figure S4 were calculated from eq S1 and the best fit parameters obtained in the fit procedure of the experimental data to eq. S1. These parameters are collected in Table S1. kT ( ω / A )
60 Π / mNm-1
− Π coh .
ω0 1 − ( ω / A )
pH=2 pH=4 pH=6 pH=8
40
Πcoh / mNm-1
Π=
(S1)
8 pK2= 6,6
6 4 2 pK1= 4,3
0
0
2
4
6
8 pH
20
0 20
40
60
80 Α / cm2
Figure S4. Surface pressure isotherms for GO at different pH obtained at 293 K. Solid lines represent the values calculated from Volmer equation and parameters collected in Table S1.
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A good correspondence between experimental and results calculated from the Volmer equation3 has been found. This fact indicates that the Volmer model can be used to interpret the isotherms of graphene oxide inside the Liquid Expanded state, LE.
Table S1. Parameters obtained from the fit of experimental isotherms to eq 2, see text for details.
pH
ω / cm2
ω0 / nm2
Пcoh / mN m-1
2
13.6 ± 0.1
0.10 ± 0.01
7.7 ± 0.1
3
23 ±1
0.22 ±0.03
7.6 ± 0.2
4
13.3 ± 0.5
0.15± 0.03
4.6 ± 0.8
6
7.7 ± 0.4
0.28 ± 0.1
3.1 ± 0.8
7
52 ± 2
0.5 ± 0.1
3.2 ± 0.6
8
9.4 ±0.2
0.22 ± 0.08
2.1± 1
Results clearly show that Пcoh decreases when the pH of the aqueous surface increases. According to pK values of the carboxylic groups, 4.3 and 6.6, respectively,4 when the pH increases the carboxylic group percentage decreases, decreasing the hydrogen bonds between graphene oxide sheets and as a consequence, the Пcoh value also decreases. On the other hand, when the pH value increases, the carboxylate anions also increase providing electric negative charge to sheets. In this situation repulsions between sheets can also contribute to the decrease of the Пcoh value.
4. DETERMINATION OF THE SOLID COVERAGE FROM SEM IMAGES To obtain the coverage of different samples of graphene oxide, at least twenty SEM images at different scales have been employed. The images were changed from 8 bit to black-white adjusting the threshold in order to both images, SEM and transformer 6
threshold image were very similar. In this case the black areas correspond to coverage areas while white areas are attributed with the substrate. An example of the procedure is shown in figures S5-S8. We used the software package ImageJ to obtain the solid coverage.
Figure S5. SEM images and respective image mask produced by applying an intensity threshold to separate the background from the nanoplatelets of GO (a,b) and NGO (c,d) films built by the LB methodology.
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Figure S6. SEM images and respective image mask produced by applying an intensity threshold to separate the background from the nanoplatelets of PGO (a,b) and PNGO (c,d) films built by the LB methodology.
Figure S7. SEM images and respective image mask produced by applying an intensity threshold to separate the background from the nanoplatelets of GO (a,b) and NGO (c,d) films built by the LS methodology.
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Figure S8. SEM images and respective image mask produced by applying an intensity threshold to separate the background from the nanoplatelets of PGO (a,b) and PNGO (c,d) films built by the LS methodology.
REFERENCES 1. Lopez-Diaz, D.; Velazquez, M. M.; Blanco de La Torre, S.; Perez-Pisonero, A.; Trujillano, R.; Garcia Fierro, J. L.; Claramunt, S.; Cirera, A. The role of oxidative debris on graphene oxide films. Chemphyschem 2013, 14 (17), 4002-9. 2. Imperiali, L.; Liao, K.-H.; Clasen, C.; Fransaer, J.; Macosko, C. W.; Vermant, J. Interfacial Rheology and Structure of Tiled Graphene Oxide Sheets. Langmuir 2012, 28 (21), 7990-8000. 3. Fainerman, V. B.; Kovalchuk, V. I.; Lucassen-Reynders, E. H.; Grigoriev, D. O.; Ferri, J. K.; Leser, M. E.; Michel, M.; Miller, R.; Möhwald, H. Surface-Pressure Isotherms of Monolayers Formed by Microsize and Nanosize Particles. Langmuir 2006, 22 (4), 1701-1705. 4. Konkena, B.; Vasudevan, S. Understanding Aqueous Dispersibility of Graphene Oxide and Reduced Graphene Oxide through pKa Measurements. The Journal of Physical Chemistry Letters 2012, 3 (7), 867-872.
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