news

Thank you for visiting Nature.com.The browser version you are using has limited support for CSS.For the best experience, we recommend that you use an updated browser (or turn off compatibility mode in Internet Explorer).In the meantime, to ensure continued support, we will display the site without styles and JavaScript.
Graphene, an extraordinary two-dimensional carbon nanostructure, has attracted global attention due to its electronic, mechanical, and chemical properties; therefore, there is a need to find an economical method for large-scale production of graphene.In this study, the aim was to find out the optimal conditions for the exfoliation of few-layer graphene (FLG) in a water-ethanol green solution.We varied different parameters of the ultrasound probe, such as the amount of power and the duration of sonication, to investigate the effects on the number of graphene layers and graphene density in solution.In addition, an attempt was made to predict the sound pressure distribution by solving the wave equation for various output powers of the ultrasonic probe (soldering head) by numerical simulation.Simulations and experiments verify each other.It was concluded that modifying the output power under the same conditions would significantly change the sound pressure within the acoustic reactor.The sound pressure difference at 90% output power of our experiments is much higher than the other conditions.Experimental results using UV-Vis spectroscopy, SEM (Scanning Electron Microscopy), TEM (Transmission Electron Microscopy) images and Raman spectroscopy show that the minimum thickness and maximum exfoliation of these samples are obtained at 90% of the maximum effective output power.The sonicator is 264 W for 55 minutes.
Recently, graphene, as a single atomic layer of carbon, has attracted great research attention due to its unique nanostructure, mechanical, electrical, and novel thermal properties1,2,3,4,5.The earliest pioneering experiments were performed on micromechanically cut monolayers, but the micromechanical approach suffers from low yields and low yields.In order to utilize graphene for future industrial applications requiring large-scale and high-output processing methods6.At present, the reduction of graphene oxide is the preferred scalable method for the preparation of graphene.In this method, graphite is oxidized according to Hummers’ modified method, and then the graphite oxide is exfoliated in water to obtain an aqueous dispersion of graphene oxide (GO), and the oxidation can be further removed by thermal or chemical reduction7,8.However, reduction of graphene oxide still retains high defect density, which degrades their performance.
Most researchers have focused on direct solution-phase exfoliation of natural graphite flakes to overcome the limitations of graphene oxide.Several layers of graphene were synthesized by evaporating polystyrene at atmospheric pressure by chemical vapor deposition (APCVD) method 9, 10 .Graphene sheets can be extracted by sonication 11 or shear exfoliation 12 in aqueous surfactant solutions and some organic solvents.Several groups have shown that graphene can be prepared in N-methyl-2-pyrrolidone 13 (NMP) and dimethylformamide 14 (DMF) to produce graphene nanosheets.These solvents have surface tensions close to 40 mJ m-2 and are suitable for direct exfoliation of graphite into FLG15.However, these solvents have high boiling points, limiting their feasibility for practical use.Therefore, dispersion of graphene in low boiling point solvents can be used for many applications such as nanocomposites16 nanoplasmas17,18,19, smart coatings20 and high frequency devices21,22,23.Numerous reports describe the effect of sonication parameters on MoS2 nanoflakes and graphene produced in deionized water-ethanol24,25,26.A simple, low-cost, and energy-efficient sonication has been reported to exfoliate natural graphite flakes in ethanol in a short time.The research aimed to use a top-down approach to determine the exfoliation rates of various forms of graphite and its oxides, and to use UV-Vis spectroscopy to gain a deeper understanding of electronic transitions28,29.In another article, UV-Vis can be found.A fast and inexpensive method to measure the percentage of few-layer sheets in GO dispersions.
In this study, an attempt was made to predict the sound pressure distribution by solving the wave equation for different output powers of the ultrasonic probe.Simulations have been carried out using numerical models.Graphene was then prepared by the LPE (liquid phase exfoliation) method using an ultrasonic probe.We then investigated the various effects of output power, sonication duration at the same concentration, to find the optimal conditions for obtaining more graphene and thinner layers from the graphite powder.The simulations are then compared with the experimental results.
All chemicals used in this project were research grade and deionized (DI) water throughout the experiment.The liquid medium used was a green solution prepared from a mixture of 65% deionized water and 35% ethanol.The ultrasonic processor used a titanium probe (Tip) with a diameter of 22 mm (model FAPAN-1200UPS manufactured by FAPAN Co. Ltd. Iran), operating frequency 20 kHz, nominal power 1200 W (RMS power 300 W).
Experiments for all samples were performed by immersing 250 mg of graphite powder in 125 mL of water-ethanol in a 150 mL glass beaker.Our aim is to use “green solvents” to minimise the impact on the environment.As expected, water is the most environmentally friendly solvent31.But the surface tension of water is about 72 mJ m-2.The surface tension of the solvent for better exfoliation of graphene is in the range of 40-50 mJ m-2.The optimal surface tension to minimize the interfacial tension between graphene and the solvent is a mixture of water and a solvent with lower surface tension.Ethanol is a good choice because of its low boiling point and surface tension close to 22.1 mJ m-2.The 65/35 volume ratio of DI water/ethanol was calculated using the Connors-Wright equation, and the surface tension of the solution was 46 m J m-2 for the preparation of binary aqueous organic solutions 27 .Keep the beaker in an ice-water bath to reduce ethanol evaporation due to the increase in solution temperature during sonication.Also, adjust the sonicator to 50% pulse mode to prevent overheating.Therefore, the total effective sonication time for sample preparation was 55 minutes.Remove the thick flakes by centrifugation using a benchtop centrifuge: the first step is carried out at 3000 rpm for 30 min, then the top 3/4 of the dispersion is reserved for the next step, and the remaining liquid is discarded. After that, again at 3600 rpm Speed ​​for the second step for 15 minutes, and finally collect the top 3/4 of the supernatant for subsequent analysis.
In this section, an attempt is made to predict the sound pressure distribution by solving the wave equation for different output powers of the ultrasonic probe.Simulations have been carried out using numerical models.Computational fluid dynamics is a powerful tool that can be used to optimize the characteristics of acoustic reactors.This numerical study aims to provide detailed explanations and instructions to model acoustic reactors under different operating conditions.In the next section, the computational domain, physical model, and boundary conditions will be introduced.For such an arrangement, it is generally assumed that the highest local pressure value is reached near the probe.The intensity$$I_{us}(0)$$ value is the power delivered to the reactor through the transducer probe$$P_{us}$$ divided by the effective surface of the tip$$A = \π r^{2 }$$,
As the distance from the probe increases, the intensity decreases according to the area in which it is distributed in a cone.To calculate the intensity distribution, first calculate the ultrasonic pressure amplitude distribution $$p_{0} (r)$$.The acoustic flow effects in the ultrasonic processing unit were modeled using the nonlinear Helmholtz equations33,34.
Sound pressure can be obtained by solving the wave equation.If linear wave propagation is assumed and shear stress corrected for liquid and gas is ignored, the wave equation has the form:
An axisymmetric 2D section of an ultrasonic processing unit with an ultrasonic probe is used as modeling geometry.Figure 1a shows the ultrasonic processing unit with the probe, and Figure 1b shows the mesh used for the simulation.Water-ethanol is considered a fluid medium.
Sonicator and Vessel Simulation: (a) Schematic diagram of the sonication cell with sonotrode (ultrasonic probe diameter Dp, probe immersion depth d, sonication cell diameter D and liquid height H in the cell); (b) Mesh used for simulation Program.
The pressure at the probe tip is calculated by the equation $$p = \sqrt {2I\rho c}$$, the output power intensity of the probe, the density of the medium (ρ) and the corresponding speed of sound (c).The side walls of the cylinder are modeled as a sound hard boundary.Use a fine mesh with node lengths less than the ultrasonic wavelength in the area around the probe tip, and use progressively coarser mesh sizes in the rest of the model.
The area of ​​sound pressure distribution in the solution was quantified by estimating the area area within the sonication unit.The output power is determined to have an effect on determining the size of the resultant sound pressure distribution.The output power of the validation study is listed in Table 1.
It is predicted that this output power will be the most effective for the sound pressure distribution performance of ultrasonic liquid treatment within the parameters considered.For the sound pressure analysis, various output powers and maximum and minimum sound pressure and differential pressure were selected, i.e. $$\Delta p$$ ($$\Delta p = P^{ + } – P^{ – }$$) Simulations were performed and are presented in Table 2.
Output power is considered to be one of the key ultrasonic parameters that significantly affects the performance of acoustic reactors.Figure 2 shows the effect of ultrasonic output power on the performance of the acoustic reactor.Under the same conditions, output power changes will change the sound pressure range and wave interaction.We conclude that modifying the output power under the same conditions will significantly alter the maximum and minimum sound pressures within the acoustic reactor.For example, at 20% (~ 34 W) output power, the maximum pressure is 0.48 × 106 Pa and the minimum pressure is – 0.43 × 106 Pa.While at 90% output power (~ 264 W), the maximum pressure is 1.4 × 106 Pa and the minimum pressure is −1.3 × 106 Pa, which is supported by an early report32.The difference between maximum and minimum pressure ($$\Delta p$$) is highest at 90% power.The minimum and maximum pressures of the 22 mm sonotrode at different output powers are shown in Figure 3.
Effects of typical sonicator output power on the sound pressure distribution in the vessel: (a) 34 W, (b) 40 W, (c) 170 W, (d) 225 W, (e) 264 W, 2D, and (f) 264 W, 3D analysis.
Simulate the effect of power variation on maximum and minimum probe sound pressure in a cylindrical reactor (vessel).
In this section, the effects of different parameters of power variation and sonication time on the graphene exfoliation process are introduced and discussed.
Graphene dispersions were prepared by using a sonicator probe in a water-ethanol solution at various output powers of the sonicator, where 40%, 50%, 60%, 70%, 80%, and 90% were equivalent to 70 , 170, 197, 225, 245, and 264 watts (we thought power had little effect on spalling at 70-170 power, we dropped the test) at 55 minutes of optimal sonication time.From the experimental results prior to this study, it was observed that the optimal condition was to use a solution with a volume of 125 CC.By measuring its UV-Vis absorption spectrum and scanning electron microscopy, the effect of changing the output power of sonication was documented in detail.
Optical characterization of graphene sheets was performed with a Perkin-Elmer model lambda 25 spectrometer.Using UV-Vis spectrophotometer absorption spectroscopy, it is possible to estimate the approximate thickness of the layers or likewise the approximate number of layers.Figure 4 shows the UV-Vis absorption spectra of graphene samples at 40-90% of maximum power in the CW mode.For the sonicated sample at 40% output power, two distinct peaks at 223 nm and 266 nm indicate that the sample contains a mixture of graphene oxide (peak at 223 nm) and graphene (peak at 266 nm).While for 50-90% ultrasonic power, only one peak was observed with increasing absorption.Furthermore, from 50% to 80% ultrasonic power, the sample showed only one peak at 266 nm, while for 90% ultrasonic power, the sample showed one absorption peak at 270 nm.It is expected that the presence of additional oxygen between the graphite oxide layers makes it easier to exfoliate, resulting in more graphene-like flakes but reduced by oxygen.The UV-Vis absorption spectrum of graphene produced by the 90% power of the sonicator is shown in Figure 4.A prominent peak is found at ≈ 270 nm, corresponding to the π to π* transitions of graphene and graphite.Figure 5 shows the absorption at 270 nm, the relative intensity of the peaks increases as the output power increases from 40% to 90% power.For the sonicated samples at 90% power, a higher amount of small layer (1-3) graphene was observed by the increase in peak intensity compared to 40% power.As shown in Figure 5, the absorbance continued to increase with increasing power.
UV-Vis absorption spectra of exfoliated graphene in water-ethanol under different ultrasonic powers.
This result is also confirmed by SEM (ESEM Philips XL30) images, as shown in Figure 6.Furthermore, Figure 6 shows that at a power of 264 W, the size and mass of the flakes are improved compared to the previous samples.At 70 W, the flakes are smaller and relatively thick.At 264 W, the flakes were approximately twice the size of the samples spalled at 70 W, and the layers were thinner.
SEM micrographs of graphene flakes produced under the following conditions: (a) 70 W, (b) 264 W sonicator power (scale bar is 2 µm).
Through the simulation of sound pressure distribution, we found that under the same conditions, the change of output power will change the sound pressure range (Figure 2, 3).We conclude that modifying the output power for precise geometric parameters will significantly alter the maximum and minimum sound pressures in the liquid composition of the sonic reactor.As the output power of the sonicator was increased, it was observed that the increase in positive pressure in the liquid always equaled the negative pressure.The difference between the simulated maximum and minimum pressures ($$\Delta p$$) is increasing as the sonicator output power increases from 0.91 × 106 Pa to 2.7 × 106 Pa (Table 2).By overcoming the van der Waals bonds between the graphite layers, the increase in the pressure difference causes more graphene flakes to be exfoliated from the graphite powder.Furthermore, at 90% of the sonicator output, the absorption power shift to 270 nm (Fig. 5) shows that graphene exfoliates with few layers (1-3 layers), which is supported by earlier reports34.In lower power sonication, graphite multilayer flakes in solvent are produced.As the power of the sonicator was increased, the exfoliated material transformed into several layers of flakes.Simulations validate the experimental results, with a large increase in Δp by implementing a small number of layers at 90% power, approved by absorption at 270 nm.The above results of absorption spectroscopy were also approved by previous reports for few-layer (1-3 layers), multilayer (4-10 layers) and thick-layer (>10 layers) graphene.
The effect of the effective duration of sonication of graphene dispersions in water-ethanol solution at 264 W power was investigated to find the graphene sheets at different sonication times of 25, 35, 45, 55 and 65 min The range of production, the results are shown in Figure 7.It can be seen from Figure 8 that with the increase of the effective sonication time, the average absorbance gradually increased until 55 minutes, and then gradually decreased.An explanation for the observed results is that the extended exposure time provides more opportunities for flake delamination.However, for exposure times over 55 min, there may be a competition between the increasing factor and the tendency of the nanosheets to aggregate with each other.Therefore, it can be seen that after 55 minutes, the absorbance decreases.
UV-Vis absorption spectra of exfoliated graphene at 264 W power versus different sonication times.
The SEM micrograph shown in Figure 9 confirms the above results.It can be seen that the 55 min flakes in Fig. 9b are more prominent and thinner than the 25 min sonicated flakes in Fig. 9a.By increasing the effective sonication time from 25 minutes to 55 minutes, more exfoliation occurred.However, above 55 minutes, the quality of the flakes will decrease due to the agglomeration process.Simultaneous agglomeration and crushing were observed in the flakes in Figure 9c.
SEM micrographs of graphene flakes for different sonication times: (a) 25 min, (b) 55 min and (c) 65 min (scale bar is 5 µm).
All findings in this study indicate that our most refined graphene samples in these experiments were obtained at; power of 264 W, pulse duration of 50%, and irradiation duration of 55 minutes, which is “Best-case scenario” for producing graphene flakes.
The structural characterization of the graphene nanosheets was further examined by TEM (Zeiss EM10C, 100kv).Figure 10a shows that the suspension contains well exfoliated graphene sheets, including multiple layers (less than 10 layers) and some layers (1-3 layers), as well as larger sheets (Figure 10b).Figure 10a clearly shows partially exfoliated graphite flakes with some aggregation as well as multilayer graphene flakes that appear darker grey.Few-layer graphene sheets with large-scale thin planar graphene flakes are shown in Fig. 10b (also Fig. 9b).The results show that the exfoliated graphene sheets have few layers and no obvious structural defects, so the process can be successfully scaled up.
For added reassurance, Raman spectroscopic analysis was used.Figure 11 shows the Raman spectrum of the synthesized FLG.In the Raman spectrum of graphene, there are three distinct features, which are the D peak at ~1350 cm-1, the G peak at ~1586 cm-1, and the 2D peak at ~2655 cm-1.Therefore, the Raman spectrum of the sample shown in Figure 11 is consistent with the formation of few-layer graphene.The $${I}_{2D/{I}_{G}}$$ ratio of a sample can be calculated from the observed peaks.Based on the $${I}_{2D/{I}_{G}}$$ ratio from the sample Raman spectrum, it is calculated to be approximately 0.95–1.According to a previous report [10], the number of layers can be deduced from the ratio of peak intensities $${I}_{2D/{I}_{G}}$$ as well as the location and shape of these peaks.$${I}_{2D/{I}_{G}}$$ The ratio is about 2 to 3 For a single layer, the ratio is $${2>I}_{2D/{I}_{G} }>1$$ for bilayer graphene and the ratio $${I}_{2D/{I}_{G}}<1$$ for multilayer graphene.Therefore, it can be concluded that since the $${I}_{2D/{I}_{G}}$$ ratio is about 1, the number of graphene layers produced in this report is small.
We investigated the effect of key ultrasonic LPE parameters, namely power and duration of sonication, on the quality and yield of FLG flakes produced in deionized water-ethanol in a vessel containing 150 mL of water/ethanol-powder solution .In conclusion, the graphene produced by sonication is pure graphene and does not require reduction from GO or purification by washing chemicals.Aided by the sound pressure differential, the distribution of sound pressure events throughout the processing volume is a key factor in the production of higher quantities and high quality FLG flakes.Numerical simulations confirm the experimental results that increasing the sonicator radiation power increases the graphite-to-graphene conversion due to an increase in the pressure difference.Furthermore, for a sonicator power of 264 W, the absorption spectrum shifted from 266 nm to 270 nm, which indicated that the graphene exfoliated with few layers (1–3 layers).The UV-Vis technique has proven to be very effective in studying the number of exfoliated layers and detecting differences in conjugated polyenes that affect the π to π* plasma peaks.
Characterization by UV-Vis, SEM, TEM, and Raman spectroscopy showed that few-layer graphene with 55 min sonication time was the best choice for high-quality pure graphene exfoliated from graphite powder for this device.Graphene sonicated for 55 minutes had thinner and larger sheets compared to shorter or longer sonication times.Therefore, our analytical results suggest the optimal operating parameters of the sonicator with a probe diameter of 22 mm, a pulse mode of 50%, and 250 mg of graphite in a 125 ml aqueous ethanol solution and a 150 mL beaker to achieve almost 264 W at 264 W Layered graphene flakes with good yields were obtained under a power of 55 min and a sonication duration of 55 min.
Lee, C., Wei, XD, Kysar, JW & Hone, J. Measuring the elasticity and intrinsic strength of monolayer graphene.Science 321, 385–438.https://doi.org/10.1126/science.11​​57996 (2008).
Novoselov, KS et al.Electric field effects in atomically thin carbon films.Science 306, 666–669.https://doi.org/10.1126/science.11​​02896 (2004).
Ballantine, AA et al.Superior thermal conductivity of single-layer graphene.Nanolite.8, 902–907.https://doi.org/10.1021/nl0731872 (2008).
Geim, AK & Novoselov, The rise of the KS glyph.Nat.alma mater.6, 183–191.https://doi.org/10.1038/nmat1849 (2007).
Geim, AK Graphene: Status and Prospects.Science 324, 1530–1534.https://doi.org/10.1126/science.11​​58877 (2009).
Ruoff, R. Graphene: Calling all chemists.Nat.nanotechnology.3, 10-11.https://doi.org/10.1038/nnano.2007.432 (2008).
Stankovic, S. et al.Graphene-based composites.Nature 442, 282–286.https://doi.org/10.1038/nature.04969 (2006).
Stankovic, S. et al.By reducing exfoliated graphite oxide in the presence of sodium poly-4-styrene sulfonate, a stable aqueous dispersion of graphitic nanosheets is formed.J. Alma Mater.Chemical.16, pp. 155–158.https://doi.org/10.1039/B512799H (2006).
Ahmadi, S. & Afzalzadeh, R. Few-layer graphene grown from polystyrene as a solid carbon source using a simple APCVD method.physics.E low size.system.Nano-structure.16, 30021–30022.https://doi.org/10.1016/j.physe.2016.01.028 (2016).
Nguyen, VT et al.Synthesis of multilayer graphene films on copper tapes by atmospheric pressure chemical vapor deposition.Advanced.Nat.science.Vanosi.nanotechnology.4 (035012), 5. https://doi.org/10.1088/2043-6262/4/3/035012 (2013).
Vacacela Gomez, C. et al.Few layered graphene dispersions were prepared from hydrothermally expanded graphite.application.science.9, 2539. https://doi.org/10.3390/app9122539 (2019).
Tubon Usca, G. et al.Zeolite-assisted shear exfoliation of graphite into several layers of graphene.current.Computer Aided Drug Design.9, 377. https://doi.org/10.3390/cryst9080377 (2019).
Usca, GT, Hernandez-Ambato, J., Pace, C., Caputi, LS & Tavolaro, A. Liquid-phase exfoliated graphene self-assembled films: low-frequency noise and thermoelectric properties.application.surf.science.380, 268–273.https://doi.org/10.1016/j.apsusc.2016.115 (2016).
Dang, TT et al.Excellent dispersion of highly reduced graphene oxide in N,N-dimethylformamide.J. Colloid Interface Science.376, 91-96.https://doi.org/10.1016/j.jcis.2012.03.026 (2012).
Zhang, X. et al.Graphene was dispersed in ethanol using a simple solvent exchange method.Chemical.comminicate.46, 7539–7541.https://doi.org/10.1039/C0CC02688C (2010).
Young, RJ, Kinloch, IA, Gong, L. & Novoselov, KS Mechanics of graphene nanocomposites: a review.Compose music.science.technology.72, 1459–1476.https://doi.org/10.1016/j.compscitech.2012.05.005 (2012).

Post time: Jun-15-2022