Article A Comparative Study of Particle Size Distribution of Graphene Nanosheets Synthesized by an Ultrasound-Assisted Method
Juan Amaro-Gahete 1,† , Almudena Benítez 2,† , Rocío Otero 2, Dolores Esquivel 1 , César Jiménez-Sanchidrián 1, Julián Morales 2, Álvaro Caballero 2,* and Francisco J. Romero-Salguero 1,*
1 Departamento de Química Orgánica, Instituto Universitario de Investigación en Química Fina y Nanoquímica, Facultad de Ciencias, Universidad de Córdoba, 14071 Córdoba, Spain; [email protected] (J.A.-G.); [email protected] (D.E.); [email protected] (C.J.-S.) 2 Departamento de Química Inorgánica e Ingeniería Química, Instituto Universitario de Investigación en Química Fina y Nanoquímica, Facultad de Ciencias, Universidad de Córdoba, 14071 Córdoba, Spain; [email protected] (A.B.); [email protected] (R.O.); [email protected] (J.M.) * Correspondence: [email protected] (A.C.); [email protected] (F.J.R.-S.); Tel.: +34-957-218620 (A.C.) † These authors contributed equally to this work.
Received: 24 December 2018; Accepted: 23 January 2019; Published: 26 January 2019
Abstract: Graphene-based materials are highly interesting in virtue of their excellent chemical, physical and mechanical properties that make them extremely useful as privileged materials in different industrial applications. Sonochemical methods allow the production of low-defect graphene materials, which are preferred for certain uses. Graphene nanosheets (GNS) have been prepared by exfoliation of a commercial micrographite (MG) using an ultrasound probe. Both materials were characterized by common techniques such as X-ray diffraction (XRD), Transmission Electronic Microscopy (TEM), Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). All of them revealed the formation of exfoliated graphene nanosheets with similar surface characteristics to the pristine graphite but with a decreased crystallite size and number of layers. An exhaustive study of the particle size distribution was carried out by different analytical techniques such as dynamic light scattering (DLS), nanoparticle tracking analysis (NTA) and asymmetric flow field flow fractionation (AF4). The results provided by these techniques have been compared. NTA and AF4 gave higher resolution than DLS. AF4 has shown to be a precise analytical technique for the separation of GNS of different sizes.
Keywords: graphene nanosheets; exfoliation; particle size distribution; nanoparticle tracking analysis; asymmetric flow field flow fractionation
1. Introduction Particle size analysis is a key element because many properties of nanomaterials are size dependent [1]. This parameter is essential since the synthesis at a small scale must be monitored for subsequent bulk production and for the control of nanotechnological products in the market. The control of size during the synthesis of nanomaterials is decisive in various industrial sectors such as nanomedicine, nanofood, nanoenergy or nanocosmetics [2–6]. It is well known that graphene has excellent properties that provide a multitude of technological applications in different fields. It is formed by a pattern of hexagonal rings of carbon atoms constituting a huge flat molecule [7]. Some of its most important properties are its high thermal and electrical
Nanomaterials 2019, 9, 152; doi:10.3390/nano9020152 www.mdpi.com/journal/nanomaterials Nanomaterials 2019, 9, 152 2 of 16 conductivity, its high elasticity, its hardness and strength and its flexibility, in that it is more flexible than carbon fibre and equally lightweight [8]. Many methods for obtaining graphene have been reported. Graphene layers can be obtained by liquid-phase exfoliation of commercial graphite in different organic solvents using the ultrasonic technique. This method requires special experimental conditions at which very high pressures and temperatures are reached in very short periods of time [9]. The colloidal graphene generated has the same surface energy as the solvent used. In this way, the free energy is negative, and the structure is broken, giving rise to fragments of graphite interspersed with solvent molecules [10]. For the successful exfoliation of graphite, different organic solvents have been used, such as N-methyl pyrrolidone (NMP), dimethylformamide (DMF), pyridine and o-dichlorobenzene (ODBC) [11,12]. By means of the ultrasound method, a maximum of 15% of individual graphene sheets is obtained. The rest is a mixture of multilayer graphene or few-layer graphene. A very important parameter for obtaining few-layer graphene is to carry out a selective centrifugation [13]. By carrying out this operation it is possible to separate the non-exfoliated graphitic particles from the exfoliated graphene sheets. This method of synthesis has different advantages with respect to conventional graphene production methods: strong oxidizing agents are not required, the synthesis time is reduced and unfunctionalized and non-oxidized graphenes are obtained in one step [14]. On the contrary, this process can have negative effects, since prolonged sonication times can facilitate the existence of defects in the surface of the graphene sheets and the reduction of the layer size [15]. For instance, these problems have been observed when DMF is used as an exfoliating liquid phase [16]. For this reason, it is very important to control the sonication times during the exfoliation process of the graphite and, above all, to choose the solvent that generates the least problems [17]. o-Dichlorobenzene is an organic solvent that has excellent properties to be used as liquid phase for the process of graphite exfoliation. It is commonly applied as a reaction medium in fullerene chemistry and it is well known that it forms very stable dispersions due to its very efficient interactions with graphene via π-π stacking [18]. On the other hand, it has a high boiling point and a surface tension suitable for the correct exfoliation [12]. Graphene-based materials have been characterized by a variety of different techniques, such as X-ray diffraction, transmission electron microscopy and Raman spectroscopy, among others [19,20]. Although these techniques can provide some information about the size of these materials, dynamic light scattering (DLS) is particularly useful to determine particle size. Thus, the use of DLS to measure the size of graphene nanosheets and exfoliated graphene oxide has been reported as a simple and fast method of characterization [21]. This technique is based on the Brownian motion of the particles in suspension causing the scattering of light at different time-dependent fluctuations intensities. These fluctuations are directly related to the diffusion coefficient of the particles in the solvent, which provides in turn the particle size using the Stokes-Einstein relationship. However, it is well known that this technique is more reliable for spherical particles than for non-spherical particles [22]. Moreover, if a sample is polydisperse, as usually happens for graphene nanomaterials prepared by most methods, DLS will exhibit some limitations to measure particle size (vide infra) [23]. Furthermore, two techniques have emerged in the last years for the characterization of nanoparticles, i.e., nanoparticle tracking analysis (NTA) and asymmetric flow field-flow fractionation (AF4). To the best of our knowledge, none of them has been used for the characterization of graphene-based materials. NTA is a relatively novel technique for the study of particle size distribution. Like DLS, NTA uses light scattering and the Brownian motion of liquid suspensions of particles to obtain the size distribution in a sample. This technique allows real-time visualization and recording of nanoparticles during the measurement by combining a charge-coupled device with laser light scattering microscopy [24]. In this way, the NTA software tracks individual particles and, using a formula derived from the Stokes–Einstein equation, provides particle size values by calculating the particle hydrodynamic diameter. In addition, it gives other parameters such as particle concentration, the range of which must be 106 to 109 particles/mL, aggregation and fluorescence [25]. The concentration Nanomaterials 2019, 9, 152 3 of 16 of particles present in the sample does not depend on the scattered light, so this technique allows an accurate and reproducible determination of the concentration of non-spherical particles as in the case of carbon nanotubes or colloids [26]. Based on these characteristics, NTA is frequently used to accurately obtain the size of protein aggregates and drug delivery nanoparticles [27]. AF4 is one of the most promising techniques for the characterization of nanoparticles due to the high precision and wide separation range it provides, as well as the great variety of nanomaterials that can be analysed. Currently, this technique is in continuous progress and shows high versatility, because it has been used to characterize many types of nanomaterials such as nanodrugs, silica nanoparticles, nanocellulose and nanoplastics, among others [28–31]. AF4 is a chromatographic technique consisting of a laminar flow of a carrier liquid combined with a transverse flow. The induced cross-flow field interacts with any molecule or particle in the channel and, in this way, size separation occurs [32]. This phenomenon gives rise to different elution times, which are inversely proportional to the diffusion coefficients of the particles in the sample, that is, to the radius of gyration. This technique is able to separate particles with sizes ranging from 2 nm to 1 µm [33]. Furthermore, it can be coupled with different types of detectors such as UV-Vis, multiangle light scattering (MALS) and/or dynamic light scattering (DLS) that would allow the complete characterization of different nanomaterials [34,35], and the determination of the molar mass distribution of macromolecules [36]. In addition, AF4 has been coupled online with ICP-MS for the selective detection of TiO2 nanoparticles [37] and in combination with UV-Vis spectroscopy and off-line HR-ICP-MS for the determination of Ag nanoparticles [38], rendering this technique very useful and versatile for analysing different types of materials. Herein, we report the synthesis of unfunctionalized, non-oxidized and isolated graphene nanosheets (GNS) applying the ultrasound-assisted method by liquid-phase exfoliation of a micrographite. The nanosheets obtained have been characterized using different techniques, particularly related to the study of particle size. Thus, besides XRD, TEM and Raman spectroscopy, three techniques, specifically oriented to the determination of particle size, i.e., DLS, NTA and AF4, were investigated. The proper choice of the parent micrographite has been essential because it has provided GNS particles measurable by all these techniques. A comparative study of the results obtained with the different characterization techniques is reported.
2. Materials and Methods
2.1. Materials Microcrystalline graphite powder (98%) was purchased from Nanostructured & Amorphous Materials Inc. (Katy, TX, USA). 1,2-dichlorobenzene (ODCB, anhydrous, 99%), dichloromethane (anhydrous, ≥99.8%, contains 40–150 ppm amylene as stabilizer) and lanthanum hexaboride (powder, 10 µm, 99%) were obtained from Sigma Aldrich (San Luis, MO, USA).
2.2. Methods
2.2.1. Synthesis of Graphene Nanosheets (GNS) 250 mg of microcrystalline graphite powder (MG) were stirred in 50 mL of o-dichlorobenzene (ODCB) for 30 min. Subsequently, the resulting dispersion was subjected to treatment with a pulsed ultrasound probe for 2 h using an Ultrasonic Homogenizer 4710 Series from Cole Parmer Instrument Co. (Vernon Hills, IL, USA) (45% amplitude, 60% duty cycle). The power supplied by the equipment was 9.96 W, according to a calorimetric calibration method [39] (see SI and Figure S1). The suspension obtained was centrifuged at 1935× g (4000 rpm) for 30 min to remove the non-exfoliated micrographite. The remaining suspension was again centrifuged at 12,096× g (10,000 rpm) to isolate the graphene nanosheets. They were washed three times with dichloromethane by successive redispersions and centrifugations to remove the ODCB. A Sorvall Super T-21 Tabletop Superspeed Centrifuge (Du Pont, Delaware, NJ, USA) was used to carry out all centrifugation processes. Dichloromethane was Nanomaterials 2019, 9, 152 4 of 16 evaporated from the resulting graphene nanosheets dispersion at room temperature for 12 h and, finally, the powdered exfoliated GNS were dried under vacuum at 80 ◦C overnight.
2.2.2. X-ray Diffraction Analysis (XRD) X-ray diffraction patterns of the micrographite and graphene nanosheets were performed using a Bruker D8 Discover (Billerica, MA, USA) with a monochromatic CuKα radiation source. The scanning conditions for structural analysis were an angular range of 15◦–80◦ (2θ), a 0.040◦ step size and 1.05 s per step. Additional measurements of X-ray diffraction were carried out using a Bruker D8 Advance. The scanning condition for this analysis were an angular range of 5◦–40◦ (2θ), a 0.002◦ step size and 9 s per step.
2.2.3. Transmission Electron Microscopy Transmission electron microscopy (TEM) images were recorded on a Jeol JEM-1400 transmission electron microscope (Akishima, Tokyo, Japan) operated at an accelerating voltage of 120 kV. The instrument has a high-contrast objective-lens polepiece, enabling high-contrast TEM image observation at all magnifications and good image quality, as well as easy handling. In addition, it has an advanced vacuum system. The digital-camera configuration includes a CCD camera that enables focusing and image verification on the operation screen. The measurement CCD camera (MC), orthogonal to the alignment camera, has a resolution of 1344 × 1024 pixel (12 bits/pixel). The measurements have been made in a magnification range between 8000× and 150,000× with an instrument resolution of 0.38 nm between points.
2.2.4. Raman Spectroscopy Raman spectra were acquired with a Renishaw Raman instrument (InVia Raman Microscope, Wotton-under-Edge, UK) equipped with a Leica microscope furnished with various lenses, monochromators and filters in addition to a CCD camera. A silicon standard sample was used as reference for calibration (520 cm−1). Spectra were obtained by excitation with green laser light (532 nm) from 150 to 3500 cm−1. A total of 32 scans per spectrum were acquired to improve the signal-to-noise ratio.
2.2.5. X-ray Photoelectron Spectroscopy (XPS) X-ray photoelectron spectroscopy (XPS) was performed through a SPECS mod. PHOIBOS 150 MCD spectrometer (Berlin, Germany) using non-monochromatic Mg Kα radiation and a multichannel detector. All spectra were fitted to Gauss–Lorentz curves to better identify the different chemical environment of the elements in each material. The binding energy values were calibrated with the adventitious carbon C 1s signal (284.8 eV).
2.2.6. Dynamic Light Scattering (DLS) Particle sizes were measured in a Zetasizer ZSP (Malvern Instrument Ltd., Worcestershire, UK) at 25 ◦C based on laser Doppler velocimetry and dynamic light scattering (DLS) techniques. Previously, the suspension was homogenized using an ultrasonication probe for a period of 5 min. The refraction index values were set at 1.33 and 2.38 for the dispersant (deionized water) and the material (carbon), respectively. The analysis was carried out by triplicate and medium and standard deviation were calculated. To obtain the hydrodynamic radius (Rh) of the GNS particles, the hydrodynamic diameter (Dh) was calculated by using the Stokes–Einstein Equation (1):
KB T Dh = (1) 3πη0Dt Nanomaterials 2019, 9, 152 5 of 16
where KB is the Boltzmann constant, T the temperature in K degrees, η0 the solvent viscosity, and Dt the translational diffusion coefficient. The intensity size distribution or the Z-average diameter was obtained from the autocorrelation function using the “general purpose mode” for the materials.
2.2.7. Nanoparticle Tracking Analysis (NTA) NTA measurements were performed in a NanoSight NS300 (Malvern Panalytical Ltd., Malvern, UK), equipped with a sample chamber and a 488 nm laser. For the NTA measurements, 1 mg of GNS was suspended in 1 mL of water. Before the analysis, the solution was homogenized for 3 min in an ultrasonic bath. The samples were injected into the chamber with sterile syringes. Many individual particles are tracked during their Brownian motion by the software, which uses the Stokes–Einstein Equation (2) to provide sample information:
2 2K T (x, y) = B (2) 3Rhπη
2 where KB is the Boltzmann constant and (x, y) is the mean-squared speed of a particle with a hydrodynamic radius of Rh in a medium of defined viscosity and temperature. All measurements were performed at room temperature.
2.2.8. Asymmetric Flow Field Flow Fractionation (AF4) An AF4 system (AF2000, Postnova Analytics, Landsberg am Lech, Germany) coupled online to a 21-angle MALS detector (PN3621, Postnova Analytics, Landsberg am Lech, Germany) and UV-Vis diode array detector (PN3241 Postnova Analytics) was used. The MALS detectors were calibrated using bovine serum albumin monomer and detectors at different angles were normalized with respect to a 90◦ detector measuring a sodium poly(styrenesulfonate) (PSS) standard. The AF4 channel was trapezoidal-shaped, 350 µm thick (defined by a spacer), 29.8 cm long (inlet to outlet) and had a maximum width of 2 cm. Particle recoveries over AF4 were tested with several commonly used membranes. The analytical parameters and characteristics of our AF4 system are presented in Table1. All injections were carried out with an autosampler in triplicate (PN5300, Postnova Analytics).
Table 1. Analytical parameters and characteristics of asymmetric flow field flow fractionation (AF4).
AF4 Parameters AF2000 System Membranes CR, PAN, PVDF Channel geometry Trapezoidal Spacer thickness 350 µm Focusing time 4 min Elution time 40 min Detector flow 0.5 mL/min Injection flow 0.2 mL/min Cross flow 1 mL/min UV-Vis 254 nm
3. Results
3.1. X-ray Diffraction (XRD) The structural properties of micrographite (MG) and graphene nanosheets (GNS) samples were examined by XRD. Figure1 shows the XRD patterns, which revealed the characteristic peaks for these materials. Both samples exhibited a strong peak at ca. 26.5◦ (2θ), which corresponded to the (002) graphite reflection [40]. Also, a weak peak at 54.5◦ (2θ), attributed to the (004) reflection, was present in the samples, especially in the micrographite. The absence of the graphite peak for graphene oxide Nanomaterials 2019, 9, 152 6 of 16
◦ θ (GO)Nanomaterials at 11 2018(2 )[, 841, x ]FOR confirmed PEER REVIEW that the graphene nanosheets preparation method did not cause partial6 of 16 oxidation of the starting graphite, as shown in the inserted image in Figure1. The higher relative intensityThe higher of relative the graphite intensity signals of indicatedthe graphite a higher signals crystallinity indicated a compared higher crystallinity to the GNS. compared The full widths to the atGNS. half-maximum The full widths of the at (002) half-maximum peak (FWHM) of the were (002) studied peak to (FWHM) determine were the studied crystallite to sizedetermine (LaB6 was the usedcrystallite as a pattern size (LaB to determine6 was used the as instrumentala pattern to broadening).determine the FWHM instrumental for GNS broadening). was higher than FWHM forMG for (seeGNS Table was2 ).higher The crystallite than for size,MG L,(see was Table calculated 2). The through crystallite the Scherrer’ssize, L, was Equation calculated (3): through the Scherrer's Equation (3): k λ L = (3) β cosk λθ L = (3) β cos θ where λ is the X-ray wavelength in nanometer (nm), β is the peak width of the diffraction peak profile atwhere half maximumλ is the X-ray height wavelength in radians, inθ nanometeris the scattering (nm), angle β is the in radians peak width and k of is athe constant diffraction related peak to crystalliteprofile at half shape, maximu takenm as height 0.9 for thein radians, (002) Bragg θ is reflection.the scattering angle in radians and k is a constant relatedThe to instrumental crystallite shape, broadening taken as effect 0.9 for on the FWHM (002) was Bragg subtracted reflection. out using Warren’s method on the assumptionThe instrumental of a Gaussian broadening peak [42 ]:effect on FWHM was subtracted out using Warren’s method on the assumption of a Gaussian peak [42]: β2 = β2 − β2 (4) β2 = sampleβ2sample − β2instrumentalinstrumental (4) where βinstrumental is isreferred referred to toLaB LaB6 and6 and equal equal to to0.130. 0.130.
(002) (002) Intensity (a.u.) Intensity Intensity / a.u. Intensity MG
GNS
5 10152025303540 2θ (degrees) (004) Intensity (a.u.) Intensity Micrographite (MG)
Graphene nanosheets (GNS)
LaB6
20 30 40 50 60 70 80 θ 2 (degrees) Figure 1. XRD patterns of micrographite (MG), graphene nanosheets (GNS) and LaB6 samples. Inset: XRD patterns of MG and GNSGNS recordedrecorded fromfrom 55°◦ toto 4040°◦ (2θ).).
Table 2. Structural parameters of the studied materials derived from their XRD patterns. Table 2. Structural parameters of the studied materials derived from their XRD patterns.
Peak d002 Crystallite Size * Samples ◦ Peak d002 FWHM Crystallite Size * Samples (2θ) (Å) FWHM (nm) ° (2θ) (Å) (nm) Micrographite 26.6 3.346 0.171 73.3 Graphene Micrographite 26.526.6 3.3563.346 0.171 0.509 16.6 73.3 nanosheets Graphene nanosheets* Parameter calculated 26.5 considering 3.356 the instrumental 0.509 broadening. 16.6 * Parameter calculated considering the instrumental broadening. Liquid-phase exfoliation by ultrasound-assisted synthesis for obtaining graphene nanosheets (GNS)Liquid-phase produced smaller exfoliation crystallite by ultrasound-assisted sizes. Moreover, synthesis the thickness for obtaining of the crystallites graphene along nanosheets c axis decreased(GNS) produced because smaller the full crystallite width at half-maximum sizes. Moreover (FWHM), the thickness of the peak of (002)the crystallites was higher along than thatc axis of thedecreased starting because micrographite the full (MG)width [at42 ,half-maximum43]. Thus, the action (FWHM) of ultrasonic of the peak waves (002) generates was higher a cavitation than that energyof the thatstarting caused micrographite an increase in(MG) the interlayer[42,43]. Thus spacing, the (d action002) due of to ultrasonic the exfoliation waves of thegenerates MG [44 a]. cavitation energy that caused an increase in the interlayer spacing (d002) due to the exfoliation of the MG [44]. In this way, the GNS sample had a smaller crystallite size and a lower average stacking height of the layered structure, confirming an effective exfoliation of the graphite by the ultrasound probe treatment.
Nanomaterials 2019, 9, 152 7 of 16
In this way, the GNS sample had a smaller crystallite size and a lower average stacking height of the layered structure, confirming an effective exfoliation of the graphite by the ultrasound probe treatment. Nanomaterials 2018, 8, x FOR PEER REVIEW 7 of 16 3.2. Transmission Electronic Microscopy (TEM) 3.2. Transmission Electronic Microscopy (TEM) The surface morphology of the original graphite and the synthesized graphene was examined by The surface morphology of the original graphite and the synthesized graphene was examined TEM images. Nanometric particles of graphite flakes are shown in Figure2A–C. Graphene nanosheets by TEM images. Nanometric particles of graphite flakes are shown in Figure 2A–C. Graphene (GNS)nanosheets were observed(GNS) were as transparentobserved as transparent layers (see Figurelayers 2(seeD–F). Figure When 2D–F). graphene When sheetsgraphene folded sheets over themselves,folded over cross-sectional themselves, cross-sectional and a few layersand a few with layers nanometric with nanometric size 200–500 size 200–500 nm could nm could be viewed. be Theviewed. folded The graphene folded graphene sheets that sheets were that placed were parallelplaced parallel to the electronto the electron beam beam were observedwere observed as several as darkseveral lines. dark However, lines. However, TEM images TEM for images graphite for showedgraphite ashowed dark spot a dark due tospot the due ordered to the stacking ordered of a largestacking number of a oflarge layers. number Also, of it layers. was verified Also, it thatwas theverified size that of the the graphite size of the particles graphite were particles several were times largerseveral than times GNS larger particles than [GNS40]. particles [40].
FigureFigure 2. 2.TEM TEM images images with with different different magnification magnification for (Afor–C )(A micrographite–C) micrographite (MG) and(MG) (D and–F) graphene(D–F) nanosheetsgraphene nanosheets (GNS) samples. (GNS) samples. 3.3. Raman Spectroscopy 3.3. Raman Spectroscopy RamanRaman spectroscopy spectroscopy was was performed performed to confirmto confir them exfoliation the exfoliation of the micrographiteof the micrographite by ultrasound by irradiation.ultrasound The irradiation. typical bandsThe typical of graphene bands of materialsgraphene materials were observed were observed in the spectra in the spectra (Figure (Figure3). The G peak3). The corresponds G peak corresponds to the phonons to the ofphonons the energy of the level energy E2g levelin the E2g Brillouin in the Brillouin zone. The zone. intensity The intensity of the D bandof the indicates D band theindicates degree the of degree disorder of disorder that the that material the material possesses, possesses, which wh isich related is related to several to several factors 2 suchfactors as functionalizationsuch as functionalization in the graphene in the graphene macromolecular macromolecular sp ring sp or,2 ring in our or, case,in our the case, ultrasonic the exfoliationultrasonic in exfoliation ODCB. In in many ODCB. studies, In many the studies, ratio of the ID ratio/IG intensities of ID/IG intensities is used is to used verify to thatverify the that material the hasmaterial undergone has undergone a structural a changestructural during change the during synthesis the processsynthesis [45 process]. In addition, [45]. In itaddition, has already it has been reportedalready thatbeen thisreported ratio isthat related this ratio to the is relate flaked size. to the Thus, flake ansize. increase Thus, an in theincrease ID/I Gin ratiothe ID indicates/IG ratio a smallerindicates sheet a smaller size because sheet size the ratiobecause of edge the ratio defects of ed isge greater defects for is smaller greater layersfor smaller [46]. layers The reference [46]. The MG hadreference ID/IG = MG 0.10 had while ID/IG this = 0.10 ratio while increased this ratio to 0.38increased for the to exfoliated 0.38 for the GNS. exfoliated These GNS. values These confirmed values the exfoliationconfirmed of the the exfoliation graphite inof ODCBthe graphite using thein ODCB ultrasound using probe,the ultrasound which caused probe, a certainwhich caused disorder a in thecertain material. disorder in the material.
Nanomaterials 2019, 9, 152 8 of 16 Nanomaterials 2018, 8, x FOR PEER REVIEW 8 of 16
G
2D
D Intensity (a.u.)
GNS
MG
400 800 1200 1600 2000 2400 2800 3200 Raman shift (cm-1)
FigureFigure 3.3. Raman spectra ofof MGMG andand GNSGNS samples.samples.
TheThe calculationcalculation of thethe numbernumber of graphenegraphene layers is very relevantrelevant in thisthis typetype ofof study.study. ManyMany investigationsinvestigations relaterelate the the position position of of the the G G peak peak with with the the number number of grapheneof graphene layers. layers. The The G peak G peak of the of GNSthe GNS was was at a Ramanat a Raman shift ofshift 1582 of cm1582−1 cmand−1 so,and applying so, applying the equation the equation proposed proposed by Wang by etWang al. [47 et], al. it can[47], be it deducedcan be deduced that this materialthat this consistedmaterial ofconsisted approximately of approximately seven layers seven of graphene layers of nanosheets. graphene Thenanosheets. 2D peak The was 2D very peak remarkable, was very whichremarkable, is the overtonewhich is the of the overtone peak D. of The the position,peak D. The the position, shape of thethe lineshape and of thethe intensityline and the of the intensity peak are of the related peak to are the related number to ofthe layers number [48 ].of Normally, layers [48]. a Normally, single layer a ofsingle graphene layer of shows graphene a band shows at 2679 a band cm− 1at. It2679 has cm been−1. It shown has been that shown in the casethat in of the multilayers case of multilayers graphene, thegraphene, 2D peak the shifts 2D towardpeak shifts higher toward Raman higher shift Raman and becomes shift and broader becomes [49]. broader In the case [49]. of In GNS, the case the 2D of bandGNS, wasthe 2D centred band at was 2716 centred cm−1, similarat 2716 tocm MG,−1, similar although to MG, there although was a clear ther differencee was a clear in peak difference intensity in betweenpeak intensity them. Itbetween is common them. to calculateIt is common the ratio to of calculate peak intensity the ratio I2D/I ofG .peak An approximate intensity I2D value/IG. An of 2approximate identifies a singlevalue of layer 2 identifies of graphene a single [50 ].layer The of original graphene micrographite [50]. The original showed micrographite an intensity showed ratio of 0.38an intensity while the ratio graphene of 0.38 nanosheets while the graphene obtained afternanosheets the ultrasonication obtained after process the ultrasonication had a higher ratioprocess of 0.55,had a thus higher confirming ratio of 0.55, the exfoliation thus confirming of graphite the exfoliation again. of graphite again.
3.4.3.4. X-rayX-Ray Photoelectron Photoelectron Spectroscopy Spectroscopy (XPS) (XPS) InIn orderorder to to study study the the composition composition of MG of andMG GNS, and XPSGNS, spectra XPS ofspectra these samplesof these weresamples measured. were Figuremeasured.4a shows Figure the 4a XPS shows survey the for XPS the survey MG and for GNS the samples.MG and BothGNS materialssamples. wereBoth composedmaterials ofwere C andcomposed O. The of presence C and O. of AlThe is presence due to the of holder Al is due where to samplesthe holder were where placed. samples The oxygenwere placed. content The in theoxygen original content graphite in the is inoriginal accordance graphite with theis in purity accordance of the sample with the and purity the presence of the ofsample noncovalently and the bondedpresence adsorbed of noncovalently oxygen [51 bonded]. The C/O adsorbed ratio for oxyg GNSen and[51]. MG The samples, C/O ratio which for isGNS inserted and MG in this samples, figure, confirmedwhich is inserted that the in GNS this figure, material confirmed underwent that a the very GNS slight material oxidation underwent upon exfoliation a very slight even oxidation though theupon difference exfoliation between even though the MG the and difference GNS ratios between was almostthe MG negligible and GNS andratios insignificant was almost comparednegligible toand a commoninsignificant graphene compared oxide to (GO)a common [52]. Thegraphene X-ray oxide photoelectron (GO) [52]. spectra The X-ray in the photoelectron C 1s region spectra of MG (Figurein the C1s4b) region and GNS of MG (Figure (Figure4c) were 4b) and fitted GNS by overlapped(Figure 4c) were peaks fitted attributed by overlapped to C–C bonds peaks (284.8 attributed eV), C–Oto C–C bonds bonds in hydroxy(284.8 eV), (286.1 C–O eV), bonds epoxy in hydroxy (287.7 eV), (286.1 carbonyl eV), epoxy (289.1 eV)(287.7 and eV), carboxyl carbonyl (290.6 (289.1 eV) eV) groups, and andcarboxyl the π →(290.6π* transition eV) groups, (shake-up and the satellite π→π* peaktransition at 292.3 (shake-up eV) [53]. satel Therefore,lite peak no at obvious 292.3 eV) changes [53]. wereTherefore, observed no obvious on the chemical changes structure were observed of pristine on MGthe andchemical GNS obtainedstructure byof thepristine ultrasound-assisted MG and GNS methodobtained according by the ultrasound-assisted to the C 1s spectra. method Therefore, according it is confirmed to the C 1s that spectra. this method Therefore, of synthesis it is confirmed allows obtainingthat this method GNS directly of synthesis from MG, allows thus obtaining avoiding GNS the synthesis directly offrom graphitic MG, thus oxide avoiding (GO). The the contributionsynthesis of ofgraphitic each component oxide (GO). is summarized The contribution in Table of3 each. The component values obtained is summarized for both samples in Table are 3. very The similar, values concludingobtained for that both this samples method ofare exfoliation very similar, of the concluding micrographite that by this the ultrasoundmethod of treatmentexfoliation causes of the a delaminationmicrographite of by the the pristine ultrasound graphite treatment avoiding causes oxidation a delamination processes. of These the pristine results graphite are in agreement avoiding oxidation processes. These results are in agreement with those reported for graphene nanosheets prepared via ultrasonic exfoliation of graphite powder in N-methyl-2-pyrrolidone [54].
Nanomaterials 2018, 8, x FOR PEER REVIEW 9 of 16
Nanomaterials 2019, 9, 152 9 of 16 with those reported for graphene nanosheets prepared via ultrasonic exfoliation of graphite powder in NNanomaterials-methyl-2-pyrrolidone 2018, 8, x FOR PEER [54]. REVIEW 9 of 16
Figure 4. (a) XPS survey for MG and GNS and XPS spectra for the C 1s photoemission peak of (b) MG and (c) GNS.
Table 3. Contribution of the six components used in fitting of the C 1s photoemission peak (in %).
Samples C–C/C=C C–O alkox C–O epox C=O O–C=O π→π* (a) MG 65.7 16.9 6.4 4.3 3.9 2.8 FigureFigure(b) 4. 4. GNS( a(a)) XPS XPS survey survey 64.2 for for MG MG and and GNS GNS 18.2 and and XPS XPS spectra spectr for8.1a for the the C 1sC photoemission1s 4.1 photoemission 3.5 peak peak of (bof) 1.9 MG(b ) andMG ( cand) GNS. (c) GNS.
3.5. ParticleTable 3. SizeContribution Distribution of the by six DLS components used in fitting of the C 1s photoemission peak (in %). Table 3. Contribution of the six components used in fitting of the C 1s photoemission peak (in %). The size distribution and intensity correlation function normalized between one and zero of the Samples C–C/C=C C–O alkox C–O epox C=O O–C=O ππ→π→π* GNS usingSamples dynamic C–C/C=C light scattering C–O (DLS) alkox are shown C–O epox in Figure C=O 5. The O–C=Oadvantage of applying* this (a)(a) MGMG 65.7 65.7 16.9 16.9 6.4 6.4 4.3 4.3 3.9 3.9 2.8 2.8 technique(b) GNS is its versatility 64.2 in terms 18.2 of fast, easy, 8.1 reproducible 4.1 and non-destructive 3.5 1.9 results. DLS provides(b) theGNS hydrodynamic 64.2 radius (R 18.2h), which is defined 8.1 as the radius 4.1 of an 3.5 equivalent 1.9 hard sphere diffusing at the same rate as the particle under observation, and so it is indicative of the apparent 3.5. Particle Size Distribution by DLS 3.5.size Particle adopted Size by Distribution the GNS in by the DLS aqueous dispersion. GNS exhibited a Gaussian peak located at 450 ± 14 Thenm.The sizesizeThe distributiondistribution measurement and and carried intensity intensity out correlation correlation for the MGfunction function material normalized normalized revealed between betweena particle one oneand size andzero outside zeroof the of the theGNSquantification GNS using using dynamic dynamic limits light of lightthis scattering technique scattering (DLS) (>1 (DLS) µm).are shown are shown in Figure in Figure 5. The5. Theadvantage advantage of applying of applying this thistechnique techniqueDLS isalso its is provides itsversatility versatility the in polydispersity interms terms of offast, fast, index easy, easy, (PDI),reproducible reproducible which indicates and and non-destructive non-destructive the width of theresults. results. particle DLS DLS size 2 providesprovidesdistribution, the the hydrodynamic hydrodynamic being calculated radiusradius as (peak(R(Rhh), which width/peak is defined defined height) as as the the. A radius radius value of ofof an anPDI equivalent equivalent < 0.1 indicates hard hard sphere sphere that the diffusingdiffusingsample at isat themonodisperse. the same same rate rate as asInstead, the the particle particle if PDI under underis between observation, observation, 0.1 < PDI and and so< 0.2, so it is itthe indicativeis sampleindicative ofwould theof the apparent have apparent a narrow size adoptedsizeparticle adopted by size the by GNSdistribution. the inGNS the in aqueous theIn the aqueous dispersion.case ofdispersion. GNS, GNS PDI exhibitedGNS was exhibited 0.36, a Gaussian value a Gaussian betw peakeen located peak 0.2
indicates that the sample has a wide particle size distribution0.6 according to the results reported by J. Lohrke10 et al. [55].
Intensity (%) 0.4 20 1.0 5 a) Coefficent Correlation 0.2 b)
15 0.8 0 1 10 100 1000 10000 0.0 10-1 100 101 102 103 104 105 106 107 108 109 Hydrodynamic ratio (nm) 0.6 10 Time (μs)
FigureIntensity (%) 5. (a) Dynamic light scattering (DLS) size distribution0.4 curve of GNS and (b) normalized intensity Figure 5. (a) Dynamic light scattering (DLS) size distribution curve of GNS and (b) normalized correlation5 function of the scattered light intensity of GNS. Coefficent Correlation intensity correlation function of the scattered light intensity0.2 of GNS.
DLS0 also provides the polydispersity index (PDI), which indicates the width of the particle size 1 10 100 1000 10000 0.0 3.6. Particle Size Distribution by NTA 102-1 100 101 102 103 104 105 106 107 108 109 distribution, beingHydrodynamic calculated ratio (nm) as (peak width/peak height) . A value of PDI < 0.1 indicates that the Time (μs) sampleIn is order monodisperse. to further Instead, define the if PDI size is of between the grap 0.1hene < PDI nanosheets, < 0.2, the samplenanopart wouldicle tracking have a narrow analysis particle(NTA)Figure size was 5. distribution. used (a) Dynamic (Figure Inlight6). theThis scattering case technique of GNS,(DLS) provides PDIsize distribution was individual 0.36, valuecurve particle betweenof GNS sizing, and 0.2 (intensity Nanomaterials 2019, 9, 152 10 of 16 3.6. Particle Size Distribution by NTA Nanomaterials 2018, 8, x FOR PEER REVIEW 10 of 16 In order to further define the size of the graphene nanosheets, nanoparticle tracking analysis (NTA)and approximate was used (Figure concentrations6). This technique (Figure S2). provides Different individual particle sizes particle ranging sizing, from intensity 40 to 400 distribution nm were andobserved. approximate The average concentrations size of three (Figure measurements S2). Different gave particle a value sizes of ranging151.8 ± 12.7 from nm 40 toand 400 mean nm wereconcentration observed. of The 1.02 average × 109 ± 6.48 size × of 10 three7 particles/g. measurements However, gave most a value particles of 151.8 had ±sizes12.7 between nm and ca. mean 30– 9 7 concentration200 nm, although of 1.02 the ×concentration10 ± 6.48 × of10 particlesparticles/g. around However, 300 nm mostwas also particles significant. had sizes The between number ca.of 30–200larger particles nm, although (> 350the nm) concentration was much lower. of particles A comparison around 300between nm was DLS also and significant. NTA reveals The that number DLS ofcould larger overestimate particles (>350 the particle nm) was sizes much of the lower. sample A. comparisonBoth techniques between provide DLS a andhydrodynamic NTA reveals radius that DLS(Rh) value could but overestimate larger particles the particle scatter sizesstronger of the and sample. are preferably Both techniques detected provideby DLS athan hydrodynamic the smaller radiusparticles (R sinceh) value the butscattering larger particlesintensity scattereffect depend strongers on and size are rather preferably than on detected the number by DLS of thanparticles the smallerwith similar particles diameter. since theDLS scattering is a fast, intensity simple effectand non-destructive depends on size technique, rather than but on it the presents number this of particlesinherent withfeature similar when diameter. analysing DLS samples is a fast, that simple presen andt some non-destructive polydispersity technique, [56]. In butthese it presentscases, it thisshows inherent distributions feature shifted when analysing to the largest samples particle that si presentzes. NTA, some on polydispersitythe other hand, [ 56distinguishes]. In these cases, with ita showsgreater distributions precision the shifted distribution to the largest of sizes particle (10–20 sizes.00 nm) NTA, because on the otherit is hand,based distinguisheson the tracking with of a greaterindividual precision particles the (Figure distribution S3) [27]. of sizes (10–2000 nm) because it is based on the tracking of individual particles (Figure S3) [27]. 1.4x107 1.2x107 1.0x107 8.0x106 6.0x106 4.0x106 Concentration (particle/ml) 2.0x106 0.0 0 200 400 600 800 1000 Particle size (nm) Figure 6. Nanoparticle tracking analysis (NTA (NTA)) size distribution curve of GNS.GNS. 3.7. Particle Size Distribution by AF4 3.7. Particle Size Distribution by AF4 Firstly, the influence of the membrane composition on retention properties and recovery from the Firstly, the influence of the membrane composition on retention properties and recovery from AF4 channel was studied. Polyvinylidene fluoride (PVDF), polyacrylonitrile (PAN) and regenerated the AF4 channel was studied. Polyvinylidene fluoride (PVDF), polyacrylonitrile (PAN) and cellulose (RC) were used. Figure7 shows the AF4 fractograms using different membranes and the regenerated cellulose (RC) were used. Figure 7 shows the AF4 fractograms using different frequently used 0.2% Novachem (Postnova Analytics) as carrier. Novachem is an aqueous surfactant membranes and the frequently used 0.2% Novachem (Postnova Analytics) as carrier. Novachem is mixture that stabilizes nanoparticles in solution. an aqueous surfactant mixture that stabilizes nanoparticles in solution. The recovery from AF4 runs was determined as follows: The recovery from AF4 runs was determined as follows: S RR( %%) = = · ·100100 (5) (5) S0 ◦ where SS andand S S0 0are are the the peak peak areas areas without without void void peak peak of theof the detector detector signal signal (UV, (UV,λ = 254 λ = nm/MALS 254 nm/MALS 90 ), obtained90°), obtained with and with without and without cross-flow, cross-flow, respectively. resp Theectively. MALS The detector MALS allows detector the direct allows measurement the direct ofmeasurement the radius of of gyration the radius in theof gyration 1–1000 nm in the particle 1–1000 size nm range particle [57]. size range [57]. The fractograms (90◦ light scattering detector) showed a low recovery using PAN and PVDF (less than 30%) due to the retention of graphene nanosheets in these membranes. It was easily visualized because they became black. This had to be due to the interaction of the graphene sheets with these Nanomaterials 2019, 9, 152 11 of 16 polymeric membranes. However, the fractogram exhibited a broad peak centred at around 33 min usingNanomaterials a RC 2018 with, 8 a, x recovery FOR PEERof REVIEW 30%, thus suggesting a weaker interaction with this membrane. 11 of 16 0.220 RC 10KDa 0.2% Novachem PAN 30KDa 0.2% Novachem PVDF 50KDa 0.2% Novachem 0.215 RC 10KDa Pure water 0.210 0.205 MALS detector, 90º (V) 90º detector, MALS 0.200 0.195 0 10203040 Time (min) Figure 7.7. Asymmetric flow flow field field flowflow fractionation (AF4) fractograms of GNS using regeneratedregenerated cellulose (RC), polyacrylonitrile (PAN) andand PolyvinylidenePolyvinylidene fluoridefluoride (PVDF) as membranesmembranes and Novachem and water as carriers. ToThe increase fractograms the recovery, (90° light pure scattering water was detector) essayed showed as carrier. a low Figure recovery7 shows using an AF4 PAN fractogram and PVDF of GNS(less usingthan 30%) a RC due membrane, to the retention which resulted of graphene in a recovery nanosheets of 95%. in Thesethese resultsmembranes. indicated It was that easily there wasvisualized no interaction because between they became the membrane black. This and had the to sample, be due and to the that interaction water was of the the appropriate graphene carriersheets towith separate these GNSpolymeric by AF4. membranes. However, the fractogram exhibited a broad peak centred at aroundThe 33 size min distribution using a RC with derived a recovery from the of 30%, MALS thus detector suggesting showed a weaker the presence interaction of with different this populationsmembrane. of particles (Figure8). The most satisfactory fitting was achieved with the random coil model.To increase This the model recovery, is usually pure chosen water was for thisessayed particle as carrier. range withFigure all 7 theshows different an AF4 angles fractogram of the MALSof GNS detector using a providingRC membrane, robustness which to resulted the method in a (Figurerecovery S4). of This95%. detectorThese results provides indicated the radius that ofthere gyration was no (R interactiong), which is between defined the as themembrane mass weighted and the averagesample, and distance that water from thewas core the ofappropriate a particle tocarrier each to mass separate element GNS in by the AF4. particle. Rg is more dependent on the structure of the particle than the valueThe of Rsizeh.R gdistributionincreases with derived increasing from thethe elutionMALS volume.detector Figureshowed8 shows the presence the size distributionof different (radiuspopulations of gyration of particles in nm) (Figure as a function 8). The ofmost the satisf differentialactory andfitting cumulative was achieved distribution with the of random the sample. coil Themodel. cumulative This model distribution is usually indicates chosen for the this fraction particle of a range sample with that all has the a massdifferent in a certainangles of range. the MALS Based ondetector this, it providing is possible robustness to determine to GNSthe method sample fractions(Figure S4). simply This by detector observing provides the height theof radius the step. of Thisgyration parameter (Rg), which is provided is defined by the as differential the mass weighted distribution, averag whiche distance is calculated from takingthe core the of differential a particle ofto theeach cumulative mass element distribution. in the particle. In this way,Rg is it more visually dependent provides on the the weight structure fraction of the of the particle sample than within the avalue certain of R massh. Rgrange, increases thus with giving increasing information the elution on the resolutionvolume. Figure of the 8 fractionation shows the size system distribution and the analysis.(radius of The gyration main in peak nm) of as the a function fractogram of the was diff centrederential at and around cumulative 360 ± 11 distribution nm. As can of be the observed, sample. thisThe techniquecumulative is abledistribution to discriminate indicates populations the fraction of particlesof a sample with that similar has sizes,a mass thus in allowinga certain a range. better characterizationBased on this, it is of possible the graphene to determine nanosheets. GNS sample fractions simply by observing the height of the step. MALSThis parameter detector coupledis provided to AF4 by canthe differential provide relevant distribution, information which about is calculated the mechanism taking the of aggregationdifferential of and the nanoparticle cumulative structure.distribution. This In information this way, it is visually included provides in the fractal the weight dimension fraction structural of the parametersample within (Df). a certain Df gives mass a detailed range, thus information giving information of the shape onof the the resolution materials, of thusthe fractionation allowing to understandsystem and the distributionanalysis. The of main particles peak in of aqueous the fractogram media. Awas sphere centred has at a Daroundf of 3, whereas360 ± 11 Dnm.f is As 2 for can a planarbe observed, structure this and technique 1 for a rigid is able rod [to58 ,discriminate59]. In the case populations of GNS, the of calculated particles valuewith wassimilar approximately sizes, thus 2allowing (1.85), which a better corresponded characterization to 2-D of objects the graphene with plain nanosheets. surface (Figure S5), thus confirming the regular layer structure observed by TEM. Nanomaterials 2019, 9, 152 12 of 16 Nanomaterials 2018, 8, x FOR PEER REVIEW 12 of 16 1.0 3.0x10-3 0.9 -3 0.8 2.5x10 0.7 2.0x10-3 Cumulative 0.6 0.5 1.5x10-3 0.4 Differential -3 1.0x10 0.3 0.2 5.0x10-4 0.1 0.0 0.0 0 200 400 600 800 Radius of gyration (nm) Figure 8. AF4AF4 size size distribution distribution of GNS with a RC membrane using water as carrier. MALSAlso, additional detector informationcoupled to onAF4 the can particle provide shape relevant can be obtainedinformation by calculating about the themechanism shape factor, of paggregation = Rg/Rh, whereand nanoparticle Rg is the average structure. radius This of gyrationinformation facilitated is included by AF4 in (360the nm)fractal and dimension Rh is the structuralZ-average parameter hydrodynamic (Df). D radiusf gives provideda detailed by information DLS (450 nm).of the Theshape theoretical of the materials, value of thus p for allowing a hard tosphere understand is 0.778 the and distribution for a stiff rod of partic of approximatelyles in aqueous 2 [media.60]. The A shape sphere factor has a increases Df of 3, whereas as the particle Df is 2 fordeviates a planar from structure an ideal and homogeneous 1 for a rigid spherical rod [58,59]. shape Into the a prolatecase of (pGNS, > 1) the or oblatecalculated (0.775 value < p was < 1) approximatelyellipsoid [61,62 ].2 The(1.85), shape which factor corresponded for GNS obtained to 2-D by objects exfoliation with ofplain micrographite surface (Figure (MG) S5), was thus 0.80, confirmingthus indicating the regular that the layer GNS structure particles observed have an oblate by TEM. ellipsoid shape. The ability of AF4 to separate and fractionateAlso, additional GNS particlesinformation can beon usedthe particle to minimize shape the can polydispersity be obtained ofby graphene calculating preparations the shape factor,and so p to = obtain Rg/Rh, morewhere accurate Rg is the data average on size radius and shapeof gyration of these facilitated materials by in AF4 future (360 investigations. nm) and Rh is the Z-averageIn summary, hydrodynamic AF4 and radius NTA give provided much richerby DLS information (450 nm). on The particle theoretical size than value DLS of whenp for dealinga hard withsphere a polydisperseis 0.778 and materialfor a stiff as rod graphene of approximately nanosheets. 2 AF4 [60]. can The be shape considered factor a increases promising as technique the particle for deviatesthe separation from an and ideal characterization homogeneous of aspherical variety ofshape graphene to a prolate structures, (p > including 1) or oblate not (0.775 only graphene < p < 1) ellipsoidnanosheets, [61,62]. as described The shape in factor this work, for GNS but alsoobtained graphene by exfoliation oxide, graphene of micrographite quantum (MG) dots andwas other0.80, thuscarbon indicating nanostructures. that the UnlikeGNS particles DLS and have NTA, an AF4 oblate is aellipsoid separation shape. technique The ability and can of AF4 be coupled to separate to a andgreat fractionate variety of detectors,GNS particles thus gatheringcan be used rich to information minimize the from polydispersity the sample. Itof separates graphene particles preparations in the andrange so from to obtain 1 nm more to 1–2 accurateµm, although data on other size field and flowshape fractionation of these materials techniques in future could investigations. expand this range up toIn particle summary, sizes higherAF4 and than NTA 100 µgivem. Interestingly,much richer the information existence ofon semipreparative particle size than channels DLS wouldwhen dealingallow the with separation a polydisperse and collection material of milligramas graphene quantities nanosheets. of these AF4 graphene can be considered structures. a In promising addition, techniqueNTA can provide for the theseparation concentration and characterization of GNS nanoparticles. of a variety Nevertheless, of graphene stability structures, concerns including of aqueous not onlydispersions graphene of largenanosheets, graphene as particles,described ain more this limitedwork, but range also of graphene particle sizeoxide, determination graphene quantum and the dotscurrent and limited other availabilitycarbon nanostructures. in many laboratories Unlike DLS are amongand NTA, the disadvantagesAF4 is a separation of NTA technique and AF4 and relative can beto DLS.coupled to a great variety of detectors, thus gathering rich information from the sample. It separates particles in the range from 1 nm to 1–2 µm, although other field flow fractionation 4. Conclusions techniques could expand this range up to particle sizes higher than 100 µm. Interestingly, the existenceThe ultrasound-assistedof semipreparative exfoliationchannels would of micrographite allow the (MG)separation to graphene and collection nanosheets of (GNS)milligram was quantitiesconfirmed of by these different graphene techniques, structures. such as In XRD, addition, TEM (sheetsNTA can size provide between the 200–500 concentration nm) and of Raman GNS nanoparticles.spectroscopy. TheNevertheless, particle size stabi distributionlity concerns of GNS of aqueous was firstly dispersion determineds of bylarge DLS graphene (ca. 450 nm),particles, which a providedmore limited the hydrodynamic range of particle radius size and determination polydispersity and of GNS. the Subsequently,current limited two availability different techniques, in many laboratoriesi.e., NTA and are AF4, among were the applied disadvantages here for theof NTA first timeand AF4 to graphene. relative to NTA DLS. provided an average size of ca. 150 nm and higher resolution than DLS as well as approximate concentrations. In addition, it proved4. Conclusions that DLS gave an average particle size whose intensity was biased towards the larger graphene particles.The ultrasound-assisted AF4 was able to separate exfoliation various of microgra populationsphite of(MG) GNS to withgraphene different nanosheets radius of(GNS) gyration was confirmed by different techniques, such as XRD, TEM (sheets size between 200–500 nm) and Raman spectroscopy. The particle size distribution of GNS was firstly determined by DLS (ca. 450 nm), Nanomaterials 2019, 9, 152 13 of 16 (centered at approx. 360 nm) and in addition it provided information concerning the structure and shape of the particles. Clearly, the application of NTA and AF4 besides DLS allows gathering much rich information on graphene particles. The above-mentioned advantages for NTA and AF4 reveal their usefulness for the determination of the actual polydispersity in graphene preparations, evaluation of their synthetic procedures and size determination and fractionation in aqueous media for studies related to biological applications, sensing and toxicity. Supplementary Materials: The following are available online at http://www.mdpi.com/2079-4991/9/2/152/s1, Figure S1: Calorimetric curve and linear fitting for the operational calibration of the ultrasonic equipment used for the GNS synthesis; Figure S2: NTA graph that represents GNS particle size and intensity; Figure S3: Nanoparticle tracking analysis images of GNS; Figure S4: Random Coil data fitting method; Figure S5: Analysis of the fractal factor dimension to identify the GNS particle shape where M is molecular weight and r is the radius of gyration. Author Contributions: Conceptualization, A.C. and F.J.R.-S.; investigation, J.A.-G., A.B. and R.O.; writing—original draft preparation, J.A.-G. and A.B.; writing—review and editing, A.C., D.E. and F.J.R.-S.; supervision, C.J.-S. and J.M. Funding: The authors wish to acknowledge the financial support from Ramon Areces Foundation, Spanish Ministry of Economy and Competitiveness (Project MAT2013-44463-R, MAT2017-87541-R), Spanish Ministry of Education, Culture and Sport for a FPU teaching and research fellowship (FPU17/03981), Andalusian Regional Government (FQM-346 and FQM-175 groups), Feder Funds, the support of Evelin Moldenhauer from Postnova Analytics GmbH and the technical staff from the Instituto Universitario de Investigación en Química Fina y Nanoquímica (IUIQFN). Conflicts of Interest: The authors declare no conflict of interest. References 1. Bhattacharjee, S. DLS and zeta potential—What they are and what they are not? J. Control. Release 2016, 235, 337–351. 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