A novel versatile method for graphite exfoliation and graphene production using magnetic water: preparation, characterization, and simulation studies

doi:10.21203/rs.3.rs-3947456/v1

There is an increasing demand for mass production of graphene through a simple, environmentally friendly, and cost-effective method. In this study, a novel versatile method was developed to prepare high-quality mono/bilayer graphene using magnetic water. Graphene nanosheets were synthesized through this novel method and then were characterized. Furthermore, the effect of magnetic water on the exfoliation of graphite was assessed by molecular dynamics (MD) simulation. Magnetic water was produced in the laboratory by circulating water between two strong magnets (7000 gausses) for 2 and 6 h. The durability of magnetic water was investigated using a Magnetometer-Based Diagnostic Test. Then, the generated magnetic water was added to graphite. By adding magnetic water, the graphite absorbed more energy, creating more space between the graphite layers by weakening and breaking the van der Waals bonds and forming high-quality graphene. Finally, the formation of mono/bilayer graphene was confirmed through XRD and AFM tests. According to the results, the use of magnetic water increased graphene yield to almost 67%, while simulation studies predicted the yield of 70%. In addition, MD outputs predicted that the number of departed graphene nanosheets reached 35 and 1252 carbon atoms were stabilized in these nanosheets. According to the results of this study, magnetic water can be applied effectively in the production of graphene nanosheets.

Magnetic water

Graphite

Exfoliation

Graphene

Molecular dynamics

Magnetic water is a type of water that has been exposed to a magnetic field to alter its properties. This process changes the structure of the water at a molecular level, resulting in water that is more easily absorbed by other structures [1–3]. One of the most commonly cited benefits of magnetic water is the high atomic interaction of this type of H₂O molecules with target samples [4, 5]. Magnetic water has also been explored for its potential applications in industrial processes. Some industries have investigated the use of magnetic water for cooling systems, with the belief that the altered structure of the water could improve heat transfer and reduce energy consumption [6, 7]. Additionally, there is interest in using magnetic water for a new atomic synthesis process and descaling purposes as it is thought to have the ability to prevent mineral buildup and improve the efficiency of industrial equipment [8].

As described above, magnetic water can be used to improve the efficiency of the synthesis process of various atomic structures (especially nanostructures). The appropriate structural stability for magnetic water molecules and carbon-based samples such as graphene nanosheets, was also reported in previous studies. Hu et al. [9] synthesized a magnetic water-soluble hyperbranched polyol functionalized graphene oxide matrix. They reported the good structural stability of the sample, which caused them to obtain a promising case for a high-efficiency water remediation process. Jia et al. [10] introduced graphene-water nanofluid solidified with a static magnetic field and then melted this sample in STP initial conditions. They reported that the external magnetic parameter (field) could improve graphene dispersion in the solidification process of nanofluids by limiting nanoparticles to displace towards the solidification regions. On the other hand, the synthesis of graphene-based nanostructures is important to improve the efficiency of various physical procedures, such as heat or mass transfer procedures [11–13]. There are several common techniques for synthesizing graphene, each with its advantages and limitations. The most common methods include mechanical exfoliation, chemical vapor deposition, epitaxial growth on silicon carbide, and reduction of graphene oxide [14–17]. Each method offers distinct advantages in terms of scalability, quality, and tunability, providing researchers and engineers with a diverse toolkit for harnessing the remarkable properties of graphene in various applications. Today, graphene synthesis techniques continue to evolve to meet the growing demand for high-quality graphene materials. According to our literature review, graphene nanosheet synthesis using magnetic water has not been reported in previous studies.

In the current research, therefore, we introduced an effective method for the synthesis procedure of graphene-based structures by creating magnetic water flow in the vicinity of the graphite matrix for the first time. It is expected that the appropriate atomic adsorption of magnetic water to carbon atoms inside the graphite matrix causes high inter-particle collisions and graphene nanosheets depart (synthesized) from the ideal graphite. To this aim, computer simulations and the molecular dynamics approach are used in current computational work [18–20]. Technically, Avogadro and Packmol software was used for modeling the atomic sample (the magnetic water-graphene system) and the LAMMPS computational package was implemented for MD simulations [21–25]. In our simulation, the kinetic, potential, and bonding energies with enthalpy and the number of departed graphene nanosheets were calculated for the physical analysis of the modeled atomistic procedure.

2.1 Computational method

2.1.1 Molecular dynamics simulation

The MD simulation is a powerful computational approach used to simulate the behavior of atoms and molecules in nanostructures [26]. This method is widely employed in the field of nanotechnology to understand the dynamic properties of materials at the atomic level. By utilizing MD simulations, researchers can gain valuable insights into the structural, mechanical, and thermal characteristics of nanostructures, which are crucial for the design and development of advanced nanomaterials and devices. Computationally, this method predicts the time evolution of the system using Newton’s laws and formalism as below [27],

$${F}_{i}=\sum _{i\ne j}{F}_{ij}=-grad {V}_{ij}= {m}_{i}\frac{{d}^{2}{r}_{i}}{{dt}^{2}}$$

1

here, the $F$parameter is the atomic net- force, ${m}_{i }$is the mass of atoms, ${r}_{i}$is the position of atoms, and $v$is the atom’s velocity. This formalism is evaluated via the velocity Verlet algorithm to integrate Newton's formalism [28–30],

$$r(t+\varDelta t)=r\left(t\right)+v\left(t\right)\varDelta t+\frac{1}{2}a\left(t\right){\varDelta t}^{2} \left(2\right)$$

$$v(t+\varDelta t)=v\left(t\right)+\frac{1}{2}\left[a\right(t)+a(t+\varDelta t\left)\right]\varDelta t \left(3\right)$$

In Equations (2) and (3), the $\alpha \left(t\right)$parameter is the atomic acceleration and $\varDelta t$is the atomic time step. In MD simulations, the interactions between atoms and molecules are modeled using force fields, which are mathematical expressions that describe the potential energy of the system as a function of atomic positions [31]. In our MD simulation the interactions between various particles are described with DREIDING and TERSOFF force fields [32, 33]. Our modeled samples in the initial step of MD simulations are depicted in Fig. 1, which was rendered with OVITO software [34]. Computationally, the DREIDING force field is used to describe the interaction between magnetic water and magnetic water-graphene interactions. In the DREIDING force field, $4\epsilon [{\left(\frac{\sigma }{{r}_{ij}}\right)}^{12}-{\left(\frac{\sigma }{{r}_{ij}}\right)}^{6})]$ and ${k}_{r}(r-{r}_{0})$ equations are implemented to describe non- bonds and simple- bond interactions between various particles [35, 36]. Furthermore, the ${k}_{\theta }(\theta -{\theta }_{0})$ relationship is implemented to describe angle- bonds inside samples. The TERSOFF force field also describes the atomic interactions between carbon atoms inside a pristine graphite sample. In TERSOFF formalism, possible energy for atoms arrangement is represented by a superposition of the interactions distance component. Theoretically, the common description of the TERSOFF force field is [33],

$$E=\frac{1}{2}\sum _{i}\sum _{i\ne j}{V}_{ij}$$

4

$${V}_{ij}={f}_{c}\left({r}_{ij}\right)\left[{f}_{R}\right({r}_{ij})+{b}_{ij}{f}_{A}({r}_{ij}\left)\right]$$

5

This formula's summations are over all neighbors $j$and $k$of atom $i$within a cutoff distance. In Eq. (5), ${f}_{R }$is computationally a two-body term (repulsive), ${f}_{A }$includes three-body (attraction) interactions, and ${f}_{c}$is a smooth cutoff function that decreases from 1 to 0 values. The constant values for the TERSOFF force field in our MD simulations are reported in Table 1.

Table 1

The TERSOFF potential parameters for graphite sample simulation in current MD research [33].
Interaction Type	R (Å)	D (Å)	A (eV)	B (eV)	λ₁ (1/ Å)	λ₂ (1/ Å)
C-C-C	1.95	0.15	1393.6	346.7	3.4879	2.2119

In the current research, we describe a computational approach to introduce the atomic interaction between magnetic water and a pristine graphite matrix to design an effective method for graphene nanosheet synthesis. For this purpose, our MD simulations are done in two main phases. Firstly, the modeled sample (see Fig. 1) is equilibrated at 300 K for 1 ns. In this step the kinetic and potential energy changes of the system as a function of simulation time are calculated using the NVT ensemble and the Nose-Hoover thermostat with a 0.01 fs value for the time step [37, 38]. After equilibrium phase detection, the NVT ensemble is converted to NVE one and the atomic interaction between various particles is estimated to detect the graphene nanosheets created inside the computational box. In this step, H₂O molecules are accelerated to collide with the target graphite sample. Our MD simulation settings in the current work are listed in Table 2.

Table 2

MD simulation settings in current computational research.
Simulation Parameter	Setting
MD Box Length	103×103×103 Å³
Number of Atoms	19038
Boundary Condition	Periodic Boundary Condition [41]
Initial Temperature	300 K
Time Step	0.01 fs
Computational Algorithm	NVT/NVE
Damping Ratio of Temperature	1 fs
Equilibrium Time	1 ns
Total Simulation Time	11 ns

2.2 Experimental method

2.2.1 Materials

Natural graphite flakes (carbon content > 99.5%) were purchased from Merck Co., Ltd. (Germany). Magnets with a power of 3500 gauss were purchased from Arad Co., Ltd. (Iran). Pump was purchased from Wego Co., Ltd. (China). Water tank was purchased from Tehran polymer Co., Ltd. (Iran). All the chemicals were of AR grade and used as received.

2.2.2 Preparation of magnetic water and graphene synthesis

The tank was filled with 15 L of urban water. The pump was turned on, and the water passed through the polyethylene pipe, on both sides of which two strong magnets (7000 gausses) were placed and recycled back to the tank. After 2 h, the tank’s outlet valve was closed, and the resulting magnetic water was removed. The above operation was repeated with 6 h of water circulation. To ensure the magnetization of water and assess how long the water can remain magnetic, the Raman test, laboratory tests (such as Ca. H, Mg. H, T.H, and pH), and Vibrating Sample Magnetometer (VSM) magnetic field durability tests were conducted. After ensuring the was magnetized, 5 g of graphite was poured into a balloon, 10 cc of produced magnetized water was added to the balloon, and the sample was taken to the laboratory for characterization.

3.1 Simulation results of magnetic water-graphite system

3.1.1 Equilibrium phase

In the first step, the equilibrium phase of the magnetic water-graphite system is simulated for 1 ns in the presence of an external magnetic field. For this purpose, the temperature of the system is set to 300 K. The graphical evolution of the system predicts the physical stability of them by MD time passing. This structural evolution is depicted in Fig. 2. To numerically analyze the equilibrium phase of the magnetic water-graphite system, changes in kinetic and potential energies are calculated as a function of the simulation time. As shown in Fig. 3, the kinetic energy of the designed sample is converged to a constant value after 1 ns. Physically, this atomic performance predicts the amplitude of atomic fluctuations decreased by simulation time passing. This structural procedure maintains the physical stability of the sample in the equilibrium procedure. Thus, the water-graphite system can be reproduced in experimental conditions. Furthermore, the structural stability of the system can be described by potential energy changes inside the computational box. This parameter is converged to 9.200 eV after 1 ns. This convergence indicates the mean attraction force created between various particles at 300 K. Finally, the mentioned attraction force causes the unity of the sample detected in the equilibrium phase simulations. Technically, these results show the appropriate MD simulations settings as reported in previous studies [39–42].

After the equilibrium phase detection, the radial distribution function (RDF) of the graphite sample is calculated to validate the process done in the current work. In MD simulations, the RDF is a parameter that describes the probability of finding an atom at a certain distance from a reference atom. It provides information about the spatial arrangement of atoms/molecules in a simulated system, helping to understand the structure and interactions within the system. The RDF output of the LAMMPS package for the equilibrated graphite matrix is depicted in Fig. 4. This numerical result is consistent with a previous structural report about a graphite sample [43]. Therefore, this structural consistency validates our computational method.

3.1.2 The Graphene Nanosheets Departing from Pristine Graphite

In the second phase of our MD simulations, H₂O molecules accelerated inside the computational box and atomic collision between them and the pristine graphite sample occurred effectively. By this atomic evolution, the graphene nanosheets departed from the target ideal graphite. Figure 5 depicts the time evolution of graphene nanosheets departing from the target structure. MD outputs indicate the graphene nanosheets with various sizes synthesized in this step. This procedure occurs with total energy changes inside the computational box. Figure 6 shows the total energy changes as a function of the simulation time. Numerically, the total energy of the system changes from 11.27 to 9.56 eV in the graphene departing from the graphite matrix process. These energy outputs predict that the graphene ratio in our results can be manipulated by the total energy of the systems changes with the amplitude of the external magnetic field variation. Besides, the total energy decreasing by the simulation time passing predicts the departed graphene nanosheets stabilized in defined initial conditions.

The bonding energy and enthalpy of the system were calculated to further analyze graphene nanosheets departing from the graphite process. The bonding energy in nanostructures refers to the energy required to break the bonds between atoms or molecules within the nanostructure. It represents the strength of the bonding forces holding the nanostructure together. Thus, this energy decreases by the simulation time passing predicts that the graphene nanosheets depart effectively from the graphite sample (see Fig. 7). Numerically, the bonding energy of the system changes from 0.58 to 0.42 eV by the simulation time variation from 0 to 10 ns. Furthermore, the enthalpy parameter includes the internal energy of the system and the amount of energy transferred as heat during a reaction. It is often used to analyze and predict the heat changes in atomic interactions. MD outputs for the enthalpy parameter are depicted in Fig. 8. From this result, we conclude that the number of released graphene nanosheets increases with the simulation time passing, and this evolution converges the enthalpy parameter to lesser values and decreases the intensity of graphene nanosheet production in the designed procedure. As listed in Table 3, the enthalpy of the total system converges to 7.93 eV after 10 ns.

Table 3

The numerical outputs of bonding energy, enthalpy, and total energy of designed graphene synthesis procedure in various MD time.
MD Time (ns)	Bonding Energy (eV)	Enthalpy (eV)	Total Energy (eV)
0	0.58	8.44	11.27
2	0.53	8.35	11.02
4	0.49	8.19	10.83
6	0.46	8.05	10.2
8	0.45	8.01	9.84
10	0.42	7.93	9.56

The final step of the current research reports the number of departed graphene nanosheets from the target graphite sample. This output changes as a function of the simulation time depicted in Fig. 9-a. From this output, we conclude that the designed mechanism in the current research, i.e., the magnetic water usage in graphene departing from the ideal graphite sample, operates effectively. Therefore, this designed mechanism should be supposed in actual applications for graphene nanosheet synthesis. Moreover, the number of carbon atoms in departed graphene samples increased to 1252 atoms, as shown in Fig. 9-b. This increase in the atoms number predicts the physical stability of the departed graphene nanosheets in the presence of H₂O molecules inside the computational box (Fig. 10).

3.2 Characterization of produced magnetic water

3.2.1 Raman

We measure successively the Raman spectra of scattering of magnetized and pure water by using a Raman spectrum instrument. The samples were examined on a model of $inVia Reflex,$ $Renishaw$ $\left(Australia\right)$ with a 532 nm laser source and 100x objective lens, which was used to identify the layer number and quality of the obtained samples.

The magnetized water is exposed to the magnetic field of 7000 gausses for 2 and 6 h. The experimental result in the range of 5-2000${cm}^{-1}$, is shown in Fig. 11. These figures exhibit that the frequency shift of some peaks and a new peak at 1320 ${cm}^{-1}$occur in the range of 5-2000 ${cm}^{-1}$, the strengths of all peaks are greatly increased. This result agrees with those of Pang X. F. et al [44]. This means that the magnetic field changes the properties of water. Therefore, the properties of magnetized water differ greatly from those of pure water [45].

3.2.2 Physical properties

Magnetic water affects the properties of water. Properties such as calcium hardness (Ca. H), magnesium hardness (Mg. H), total hardness (T. H), chlorine test (Cl⁻), total alkalinity, pH, electrical conductivity (EC), total dissolved solids (TDS), and turbidity.

Table 4 shows the results of magnetized and urban water and compares them with the reference. Examining the results obtained in this work shows that water has magnetic properties [46].

Table 4

Test results with 2 and 6 h magnetized water and its comparison with reference.
Settings	Urban water without magnetization	Magnetized water for 2 h (This work)	Magnetized water for 2 h [46]	Magnetized water for 6 h (This work)	Magnetized water for 6 h [46]
Ca. H$\left(ppm\right)$	150	117	116	104	104
Mg. H$\left(ppm\right)$	100	41	40	36	36
T.H$\left(ppm\right)$	250	158	156	140	140
Cl⁻$\left(ppm\right)$	52	45	45	40	40
P$\left(ppm\right)$	0	0	0	0	0
M$\left(ppm\right)$	160	141	140	157	156
M _Total (P + M)$\left(ppm\right)$	160	141	140	157	156
PH	7.68	8.11	8.09	8.37	8.36
E.C$\left(\frac{\mu s}{cm}\right)$	826	704	701	745	744
TDS$\left(\frac{mg}{L}\right)$	479	435	433	440	440
Turbidity ($NTU$)	0.54	0.50	0.52	0.51	0.51

3.2.3 VSM

Accomplish VSM measurements with materials that display magnetic hysteresis effects, for example paramagnetic, ferromagnetic, or ferrimagnetic materials, the initial magnetization and sample orientation must be controlled. All testing was performed at $25 ℃$using a Model$1660 DMS VSM \left(China\right).$

Figure 12 shows the duration of water magnetism after 2 and 6 h of water magnetization. With 2 h of magnetization, a magnetic water memory of 13 h, and with 6 h of magnetization, a magnetic water memory of 22 h was reported. According to Fig. 12, after 13 h, the amount of magnetic water was 240 gauss; after 22 h, it was 2050 gauss. By examining the VSM test, it was found that increasing the duration of magnetization in the device increases the intensity of the magnetic memory of water (the duration of maintaining the special properties of water after passing through a magnetic field is called the magnetic memory of water) [47, 48].

3.3 Characterization of synthesized graphene

3.3.1 XRD

The graphene obtained using the operating conditions mentioned was characterized through XRD spectroscopy [49]. The graphite and graphene dispersions were deposited individually onto glass slides and then dried under vacuum (${10}^{-3} mbar$) at room temperature. The samples were examined on a model of $D/max-2200/PC XRD \left(Japan\right)$. The analysis conditions were irradiated at ${10-70}^{0}$with a scan rate of ${5}^{0}/ min$. The patterns were recorded under the acceleration voltage of $45 kV$and a current of $20 mA$.

XRD spectrums of raw graphite and graphene samples synthesized using magnetic water are depicted in Fig. 13. The position of the main peaks of graphite and mono/bilayer graphene reported in the literature are also given for comparison in Table 5.

To further explain the meaning of the XRD test, it can be said that when X-rays are emitted from the XRD device onto a material, they can act like a fingerprint to identify a material. To this end, XRD analyses of graphite and graphene samples and a comparison between them were performed to further investigate the structural changes of graphite after using magnetic water [49, 50]. Figure 13-a shows the prototype of graphite and graphene. According to Figs. 13-a and b and comparing these two Figures, it was found that the primary graphite had very high purity. By comparing Figs. 13-c and d with Fig. 13-a, it was also found that the position of the XRD peak in the spectrum of graphene is similar to that of graphite. Still, the intensity of the peak in the XRD pattern is similar to that of graphene and is greatly reduced compared to graphite. This significant decrease is related to the decrease in the density of graphite layers. In other words, due to the fragile layers formed after the exfoliation process, the intensity of the (002) peak in the graphite decreased significantly, showing that the extraction of graphene using magnetic water (6 h) was successfully compared with magnetic water (2 h) and it was converted into mono layer graphene [50].

Table 5

Position of the main XRD peaks of graphite and graphene in the present study and the previous literature. Reproduced with permission [50]. Copyright 2021, Royal Society of Chemistry.
Material	2θ (˚) in the current study	2θ (˚) in the previous literature
Graphite	26.66	26.66
Monolayer graphene	26.48	26.48
Bilayer graphene	26.44	26.45

Figure 13. a) XRD patterns of initial graphite and graphene [50], XRD spectrum of (b) raw graphite, (c) bilayer graphene synthesized using magnetic water (2 h), and (d) monolayer graphene synthesized using magnetic water (6 h).

3.3.2 AFM

A promising method for determining the number of graphene layers is the investigation of AFM height profiles obtained for graphene samples. The samples were examined on a model of $VECCO Dimension 3100 \left(USA\right)$. Several microliters of graphene dispersion were deposited onto freshly cleaved and heated mica substrates. The mica surface was dried at 105 $℃$ to evaporate water. To characterize the layer number of graphene more accurately, AFM is used to analyze the thickness of graphene sheets. The theoretical thickness of a monolayer graphene is about 0.34 nm. So, the layer number can be calculated by measuring the thickness [51].

Figure 14 shows AFM images of graphene sheets. Figures 14-a and b show that the water magnetized for 2 h without/with ultrasound has thicknesses of 3.14 nm and 3.09 nm, respectively, which indicates the number of graphene layers is less than ten. Figures 14-c and d show that the water magnetized for 6 h without/with ultrasound has thicknesses of 0.675 nm and 0.672 nm, respectively, which shows the number of graphene layers is two and less than two layers. It was also observed that according to the operation of magnetizing water, performing ultrasonic operation on graphene and the number of its layers had a very small effect. However, it is reasonable to suggest that monolayer graphene sheets were formed because of the instrumental offset (caused by different interaction forces) and the surface wrinkle of the sample. To further confirm the yield of graphene sheets, AFM measurement was performed on randomly selected 100 samples. The percentage of graphene sheets obtained with water magnetized for 2 and 6 h and the histogram of the layer distribution is shown in Fig. 15. All results are consistent with our theoretical simulations.

As shown in Fig. 15-a, about 26$\%$ of the graphene sheets are less than four layers, among which about 6$\%$ are monolayers, 9$\%$ are bilayers, 11$\%$ are three layers, and 61$\%$ are multilayers. As shown in Fig. 15-b about 78$\%$ of the graphene sheets are less than four layers, among which about 44$\%$ are monolayers, 21$\%$ bilayers, 13 $\%$ three layers, and 9$\%$ multilayers.

In this work, magnetic water was used to depart graphene nanosheets from graphite matrix. The results of RAMAN spectroscopy, VSM and laboratory tests show that magnetic water can be successfully produced with the help of a fluid magnetizing device, and the produced water maintains its magnetic properties for a long time. XRD and AFM results confirmed that graphite absorbed more energy by injecting magnetized water for 6 h, weakening and breaking the van der Waals force, creating more space between graphite layers and turning it into mono/bilayer graphene. Also, this energy prevented the resulting graphene sheets from being placed on each other again at the end of the experiment. AFM results indicated that the production yield of mono/bilayer graphene was almost 67 $\%$. In the next step, MD approach with LAMMPS package was used for atomistic analysis of magnetic water-graphite system time evolution description. Technically, the DREIDING and TERSOFF force fields were used to describe atomic interactions inside computational box. MD simulations show that a large magnetic field applied to the H₂O molecules facilitates graphite delamination with stable separation, supporting the experimental observations. In addition, graphene production yield was predicted as 70%, which is quite close to the experimental results. The number of departed graphene nanosheets and their carbon atoms increased to 35 and 1252 by simulation time passing. According to the results of this study, the proposed method proved promising for mass production of high-quality graphene.

Acknowledgment

We gratefully acknowledge support from the High-Performance Computing Centre of Ferdowsi University of Mashhad.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by Ferdowsi University of Mashhad [grant numbers 59632, 2023].

Data availability statement

The data that support the findings of this study are available on request from the corresponding author.

Author contribution

Software: S. A. Saeedi and M. A. Fanaei; experimental: S. A. Saeedi and J. Sargolzaei; writing-original draft preparation: J. Sargolzaei and S. A. Saeedi; writing-review and editing: J. Sargolzaei and M. A. Fanaei; supervision: J. Sargolzaei; All authors have read and agreed to the published version of the manuscript.

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ResearchHighlights.docx

A novel versatile method for graphite exfoliation and graphene production using magnetic water: preparation, characterization, and simulation studies

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Abstract

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1. Introduction

2. Computational and experimental section