The digital twin concept lays the foundation of the virtual vibrational analytics suggested in the current paper. The latter presents extended virtual experiments aimed at determining the specific features of the optical spectra of the studied molecules that provide reliable express analysis of the body spatial structure and chemical content. Reduced graphene oxide was selected as the virtual experiment goal. A set of nanosize necklaced graphene molecules, based on the same graphene domain but differing by the necklace contents, were selected as the relevant DTs. As shown, the Raman spectra signatures contained information concerning the spatial structure of the graphene domains, while the molecule necklaces were responsible for the IR spectra. Suggested sets of general frequency kits facilitate the detailed chemical analysis. Express analysis of a shungite carbon, composed of rGO basic structural units, revealed the high ability of the approach. This term refers to a very wide class of new molecular formations called necklaced graphene molecules (NGMs), presenting nanometer-sized graphene domains surrounded with heteroatom necklaces of various compositions. The number of corresponding rGO compositions is countless, differing both in the shape and size of the graphene domain and in the content of the heteroatomic necklace. The name ‘necklaced graphene molecules’ is common to all of this richness and better reflects its principle personality than rGO, which was only attributed to a chemically synthesized product.It is unlikely that there is at least one person today working in the field of materials science who would not know the widely advertised high-tech material called reduced graphene oxide (rGO). Its “discovery” and a base surge of popularity over the past 10–15 years have been facilitated by the special euphoria of a new direction in materials science-graphenics. Nevertheless, humanity, without realizing it, is familiar with the body from the first bonfire, from the first shovel of coal thrown into the furnace, from the first filler of wheel tires, from the first … and this listing can be continued indefinitely. The ash from a burnt fire, the deposits of natural coal, synthetic black carbon, and, finally, a laboratory product of the chemical reduction of oxidized nanoscale graphite—this is a short list of these unique materials, which are known as The graphene era revealed the wide demand for rGO for various applications, which immediately required the formulation and implementation of a reliable analysis of this material, which exists only in solid form. The structure and chemical composition, as a fundamental principle, and the chemical and physical properties as its consequences, became the basis for the development of appropriate analytics. The complexity of the analyzed object and the lack of standard structural and compositional features have inevitably led to the multi-method nature of the required analysis. The diffraction of X-rays and thermal neutron flux, as a source of information about the components of the structure of a solid; thermal gravimetric analysis, as the first cut of the atomic composition in gross as well as in the detection of the presence of hydrogen in the samples; chemical elemental analysis for the presence of carbon, hydrogen, nitrogen, and sulfur atoms; X-ray photoelectron spectroscopic (XPS) analysis for the presence of carbon, oxygen, and atoms of other heavy elements; and energy dispersive spectroscopic analysis of the distribution of these atoms in the mass of a solid all together allowed us to proceed to the stage of creating models of the atomic structure of the sample. Next comes the final analytic stage—verification and approval or rejection of the proposed models. At this stage, the main attention is given to spectral methods of investigation, the primary place among which is occupied by the vibrational spectroscopy of IR absorption and the combinational scattering of light. The latter was discovered independently by Mandelstam and Landsberg in the USSR  and Ramasp2 amorphous carbons [virtual vibrational analytics (VVA) applied to complicated carbon materials such as rGO. The VVA fundamentals and facilities are considered in the current paper. Digital twins (DTs) and a proper computational code constitute the VVA core. The former, as in the previous cases [sp2 amorphous carbon with experimental analytics [The recent development of virtual vibrational spectrometry (VVS) ,11,12,13nalytics ,5,6, onlgeneral frequency (GF) concept. The latter is a particular spectral signature of a selected individual covalent bond observed in the corresponding IR and Raman spectra [general frequency kits (GFKs), attributed to sets of similar covalent bonds. A particular feature of the study concerns a simultaneous consideration of both the density of vibrations and the IR spectra of the relevant DTs, which forms the grounds of the wished spectral marks. A successive result of such an approach is illustrated by the example of a VVA consideration of a shungite carbon.The analytic ability of the vibrational spectroscopy of multiatomic molecules, once presented as sets of covalent bonds, is traditionally based on the  spectra ,15. SuccThe rest of this paper is organized as follows. A general description of the VVS technique as well as the formation of DTs are given in VVS is a chain of successive steps leading to digitalized vibrational analytics according to a general scheme.Here, DTs are the molecular models under study, a virtual device is a carrier of the selected software, and the IT product covers a large set of computational results related to the DTs under different actions in light of the software explored. In the current study, the virtual device HF Specrodyn, implementing the software CLUSTER-Z1 , provide−1 if not pointed otherwise. The intensities are reported in arbitrary units, normalized per maximum values within each spectrum. Since the number of vibrational modes composing the spectra under consideration is too large, the excessive fine structure, statistically suppressed in practice, is covered by trendlines averaged over either 50 or 100 points of linear dispersion of 0.003 ÷ 0.010 cm−1 each. The procedure was applied to the plots of the density of vibrations and the Raman scattering spectra.Throughout the paper, the virtual spectra are presented by stick-bars convoluted with a Gaussian bandwidth of 10 cm66 (DT I) but surrounded with different necklaces. The first group involved compositions with necklaces outside the graphene domain, namely C66H22 (DT II), C66O22 (DT III), C66(COOH)20 (DT IV), and C66(OH)22 (DT V). The former were composed of densely packed monoatomic hydrogen, forming a complete framing of the domain with sp2C–H methines. The second concerned monoatomic oxygen, providing the domain framing with carbonyls sp2C=O. The next two DTs were related to necklaces consisting of individual carbonyls sp2C–COOH and hydroxyls sp2C–OH. All of the models corresponded to the maximal dense packing. These DTs were supplemented with a similar set of compositions whose necklaces consisted of only four units each, C66O4 (DT VI), C66(COOH)4 (DT VII), and C66(OH)4 (DT VIII), respectively. The second group of DTs resulted from the incorporation of oxygen atoms among the carbon edges of the domain, thus substituting the latter and forming necklaces as groups of esters, lactones, and other compositions, namely, C60O6 (DT IX), C56O10 (DT X), C70O6 (DT XI), C56O14 (DT XII), C62O8 (DT XIII), and C60O12 (DT XIV). Equilibrium structures of the species are presented in Unlike the usual attitude toward models for computational spectroscopy, the design of DTs was not subject to the requirement of achieving the best agreement with the experiment. The task of the DT concept is to identify the main including the so far hidden patterns that are characteristic of a given object. The achievement of this result is ensured by the wide variability of the model modifications. Following this trend, two groups of DTs simulating the rGO of different spatial structure and chemical contents were selected for the study. These were NGMs based on the only  graphene domain Csp2C–C bond pool of the graphene domains only. The second concerns the dependence of the spectra on structural factors such as the size and shape of the NGMs, on one hand, and the molecule packing, on the other. As it turned out, the IR spectra of the NGMs were practically insensitive to the geometrical factors, but readily responded to changes in the chemical compositions of the necklaces. Conversely, the Raman spectra were highly dependent on the former factor due to the extreme lability of the graphene domain bond structure [I) on the background of its density of vibrations (DOV). The domain was a flat sheet that was 1.2 × 1.1 nm2 in size. As shown by the DOV trendline, the vibration spectrum was clearly divided into two parts from 20 to 1100 cm−1 and from 1100 to 1800 cm−1, respectively. This two-part character of the vibration spectrum of NGMs also remained in the crystalline state [A comprehensive VVS analysis of IR absorption and the Raman scattering spectra of bare graphene domains has only recently been conducted. . In lightructure ,25, but ne state ,26,27.sp2C–C–C bending, benzenoid ring breathing, and sp2C–C–C puckering (1100–700 cm−1), in-plane and out-of-plane sp2C–C–C bending (700–400 cm−1) accompanied with low-frequency breathings of the graphene domain as a whole. In contrast, the region of 1100–1800 cm−1 was related to a large set of sp2C–C stretching. As seen in the figure, Raman scattering mainly involved the latter with a particular favor toward high-frequency ones. These modes also formed in the IR absorption spectrum of the domain [According to the fundamental consideration of the vibrational spectrum of the benzene molecule , the fire domain . Both spe domain . The sime domain .I with not only the presence of a complicated necklace, but with a larger size of its graphene domain , that is, 2.2 × 2.0 nm2. As seen in the figure, the DT Raman spectrum drastically changed, presenting the transformation of a broad multiband structure toward a single-band one. Such a transformation of the Raman spectra was also repeated for the DTs involving bare and hydrogenated  graphene domains and became more pronounced in the case of the  graphene ones [sp2C–H stretching.The Raman spectrum in ene ones . The matene ones ,31. In f crystal ,27, the sp2 amorphous carbon structures, the linear dimensions of the domains were smaller than Aside from the domain size, two more factors come into play. The first is due to the high tendency of graphene domains to stacking. Indeed, the single-layer graphene sheets observed in a number of experiments were only of crystalline structures, the micron linear dimensions of which far exceeded all of the known characteristic dimensional parameters of the graphene crystal quasiparticles, so that their behavior obeys the solid-state laws. Natural packing of the sheets unambiguously led to the sample graphitization. In contrast, in almost all of the 3spC–C bond of 1.53 Å, so that the unpaired electrons of carbon atoms in the domain basal planes of neighboring layers cannot be paired. However, as has been shown theoretically [3spC–C bond can be considered broken when the interatomic distance is greater than or equal to 2.5 Å. Later on, the existence of “long” single 3spC–C bonds was forced to be admitted experimentally [sp2 hybridization. At the same time, the vibrations of carbon atoms are not limited in space, which is supported by the occurrence of special out-of-plane phonons in a multilayer graphene crystal, the existence of which significantly changes the form of its Raman spectrum [3dynamic spC–C bonds between the domain layers, supported with the displacement of carbon atoms between the layers toward each other [sp2C–C stretching caused by the presence of oxygen atoms in the molecule carbon core [sp2 amorphous carbons into a sign marking the stack structure of the substance. In fact, the doublet mark of the sp2 amorphous carbons disappeared when their BSU stacks were completely destroyed [Indeed, the distance between adjacent layers in graphite-like structures is close to the van der Waals diameter of a carbon atom and constitutes 3.35–3.50 Å [etically , a singlmentally . Howeverspectrum ,35,36,37ch other . Furtherbon core . Additiobon core ,35,36,37estroyed . On the sp2 amorphics [sp2C–C bonds of their graphene domains. In the case of DTs related to the considered NGMs [sp2C–C stretching −1 because of the tight interconnection between sp2C–C stretching in the DOV shown in sp2C–C bond structure, the less As shown by a detailed analysis of the Raman spectra of an extended set of morphics , the forred NGMs ,13, the brations . This feonfirmed .sp2 amorphics composed of BSUs with predetermined size [As for  domains ,43. A st domains ,45. Howened size  did not Concluding the description of the main characteristics of the vibrational spectra of graphene domains, I–V against the background of their DOVs. The set was opened by the reference spectra related to the bare  graphene domain DT I. As seen in the figure, the DOV spectra of all of the derivatives strongly retained the common two-part structure, definitely separating the high-frequency stretching from compositions of the deformational modes. In all the spectra, this division occurred at 1100 cm−1. The main changes in the DOVs concern the stretching part. A detailed comparison of the DT DOVs with the reference one can be traced in We started from the general overlook of the virtual spectra of the NGMs forming the DTs of the first group. Presented in sp2C–C bonds of the pattern graphene domains, caused by the corresponding necklaces, on one hand, as well as the appearance of additional heteroatom covalent bonds, on the other. As for the first fact, it is important to note that even the necklace, consisting of only one hydrogen atom, disturbed the distribution of the sp2C–C covalent bonds of the domains quite significantly [sp2 amorphous carbons in practice [As seen in ficantly . Despitepractice .sp2C–H modes provided the spectrum shape. When the necklace included only oxygen atoms  graphene domain caused by the derivatization. As seen in the figure, the hydrogenation concerned all of the vibrational modes. In turn, the plot in II makes it possible to use the reference data in the table belonging to the benzene molecule. As seen in the table, the suggested GFK was well-coherent with the reference data and correlated well with experimental data related to the NGMs, for which the methine-unit content of the necklaces was firmly established [The plot in ablished ,24,46.3spC–H2, 3spC–CH2, and 3spC–CH3. The HF Spectrodyn allows for the reliable consideration of all of the cases, based on the  graphene domain DTs, as was, say, in the case of 3spC–CH3 [Obviously, in practice, hydrogeneous necklaces of NGMs are much richer and may involve a variety of hydrogen-containing groups such as sp3C–CH3 . In its sp3C–CH3 ,20 offerOxygen is the second most frequent element present in carbon materials. Its atoms combine willingly to carbon ones, forming a wide spectrum of organic functionalities from carboxylic acids to ketones and ethers. sp2 amorphous carbons, which were thoroughly spectroscopically studied [I–V is given in III–V were substantially emptied to four units in each case. The corresponding DTs VI, VII, and VIII are shown in −1, in general. At the same time, the observed similarity of the spectra allows us to suggest quite reliable GFKs with the above-mentioned accuracy.As described in  studied ,8,24. A To achieve this goal, we needed reliable reference data similar to those of the benzene molecule discussed in the connection of the GFKs listed in III–V were treated in the manner described previously for the necklaced graphene hydrides in the previous section. The The calculated data related to DTs III is composed of monoatomic oxygens, the addition of which fully inhibits the dangling bonds of the edge carbon atoms. The circumference composition is extremely similar to that of polycarbonyls , sp2C–C (1500–1600 cm−1), and sp2C=O stretching (1800–1900 cm−1). Accordingly, stretching dominated in the IR spectrum, among which the sp2C–O–C ones covered the largest frequency area, sp2C–C ones presented carbon atom vibrations stimulated by the presence of chemically added oxygens [sp2C=O ones were the characteristic signature of carbonyls.The necklace of graphene oxide DT yls  graphene domain, form the basis of the second group of DTs. Their equilibrium structures are presented in XI provided the simplest IR spectrum, revealing mainly two types of vibrational modes related to the sp2C–O–C and sp2C=O stretching. It should be noted that the latter were characterized by 200 cm−1 less frequency in comparison with that of the DTs of the first group. This mode feature was repeatedly observed when acid anhydride and lactone OCCUs were present in the molecules [XII or pure lactones, located at the zigzag (DT XIII) and armchair (DT XIV) edges. All of the discussed peculiarities are presented in Acid anhydrides of DT olecules ,22,47,48In the present work, we abandoned the desire for a virtual substantiation of the experimental spectrum of certain molecules and focused on revealing the characteristic spectral characteristics inherent in the chosen class of molecules. The digital twin concept assists in achieving this goal. The concept lays the foundation of the virtual representations of physical objects or processes along with the connections of data and information that tie the two together ,51,52. ITo illustrate the possibilities of VVA, in this work, practical graphenics was chosen as an area that occupies one of the central places in modern materials science. Methodical approaches and the levels of analysis of the obtained results were presented for an important high-tech material such as reduced graphene oxide, thus demonstrating that VVA can already today be attributed to modern analytical methods of a new type.sp2 amorphous carbons, the DTs used in this work were molecular models constructed by taking into account the entire body of knowledge acquired to date concerning these solids. The central place in the information obtained is occupied by a clear idea of the multilevel structure of these solids, which is based on nanosized quasi-molecular formations, or BSUs, which are graphene domains, necklaced with heteroatoms that terminate dangling bonds of the domains edge atoms. The choice of these BSUs as DTs and the possibility of a wide variation in the size and chemical composition of their necklaces is the first fact, which ensures the successful implementation of the VVA. The second element of success is the correct choice of a virtual device that allows for a large number of calculations to be performed at the modern level of the molecular theory of the object under study. In this case, BSUs are stable polyatomic radicals, or molecules with open shells, which determine the use of the UHF version of the HF Spectrodyn as an effective device. A comparative analysis of a large set of calculated data obtained was the completion of the digital cycle. As a result of extensive virtual experiments carried out using two dozen DTs, started in a previous work [Since rGO belongs to the class of real ous work  and comp1.The carbon atoms of the graphene domains of the BSUs and heteroatoms of their necklaces participate in the optical vibrational spectra in different ways: the vibrations of the former form the Raman spectra of the BSUs, while the IR spectra are assigned to the vibrations of the heteroatoms of the necklaces.2.sp2 amorphics of various origins. Being multiband in the case of individual BSUs, the Raman spectrum accepts a standard D–G doublet view when packing the BSUs into stacks. In this case, the width of the bands depends on the linear size of the BSUs themselves and the thickness of the stacks. It sharply decreases with an increase in these parameters as their size approaches or exceeds the critical value determined by the mean free path of the optical phonons The carbon-domain nature of the Raman spectra underlies their unique uniform appearance for a wide range of 3.sp2 amorphous carbon, accommodating numerous types of rGOs. For example, the typical Raman spectrum of shungite carbon shown in These conclusions make it possible to carry out an express analysis of the structure of any 4.sp2 carbons strongly depend on the chemical content of the necklaces of their BSUs [The IR spectra of amorphous eir BSUs . It has 5.−1 blue shift of the former, on average.The DTs considered in the work, which are close in size to empirical BSUs, consist of a hundred atoms, due to which eigenvectors of harmonic vibrations of the molecules involve many hundreds of components. This makes the attribution of the considered vibrational mode to individual atomic pairs, or particular chemical bonds, practically impossible. However, the empirical IR spectra of amorphics retain a certain similarity to the spectra of small molecules, which allows us to speak about the selection of atomic compositions in the realization process of the absorption spectrum. However, if in the case of small molecules such selection leads to the formation of an extensive pool of GFs corresponding to individual covalent bonds, in the present case, we can speak about GFKs, implying the excitation of a set of bonds. In the present work, by changing the composition of the necklaces of the considered DTs in a given way, we succeeded in revealing the GFKs that are related to the composition of the BSU necklaces of different rGOs. A comparison of calculated data with the reference ones revealed a ~250 cm6.sp2 amorphous carbon based on the shape of its IR absorption spectrum. Thus, the IR spectrum of a shungite carbon in sp2C–H groups and sp2C=O carbonyls. There were no hydroxyls in the necklace, while a final conclusion concerning the presence of carboxyl groups, although extremely improbable [As listed in probable , should The given express analysis of the Raman and IR absorption spectra of an rGO sample is only the beginning of the in-depth analysis and is given as an example. Nevertheless, they provide a reliable entry level of analysis, requiring further confirmation using all of the advanced methods of analytical chemistry and spectroscopy .


Moreover, the graphene–TPP photodetector has wavelength and angle selectivity, which can be applied in LiDAR detecting, sun sensors, laser beacon tracking, and navigational instruments in the future.Recently, two-dimensional materials have attracted attention owing to their special optical characteristics and miniaturization, with low thickness as well as extremely high responsivity. Additionally, Tamm plasmon polariton (TPP) resonance can be observed by combining a metal film and a one-dimensional (1D) photonic crystal (PC), where an electric field confinement is located at the metal–1D PC interface. In this study, a graphene layer combined with a TPP is proposed as a wavelength- and angle-selective photodetector. The graphene layer is located where the strong field confinement occurs, and the photocurrent response is significantly enhanced with increasing absorption by over four times (from 62.5 μA⋅W Light detection and ranging (LiDAR) is a widely used technology that emerged after the invention of the laser in the 1960s , artificTwo-dimensional (2D) material with atomic-scale thicknesses, such as transition-metal dichalcogenides (TMDCs), black phosphorus, and graphene, have been introduced in a variety of applications ,13,14, iThe PV , photothQ-factor) and strong field confinement located at the DBR-metal interface. Compared with SPPs, TPPs can be directly excited without any coupler or prism; likewise, the structure of TPPs is more easily fabricated by an evaporation system than that of SPPs because of its layer-by-layer structure. Moreover, TPP resonance can be adjusted by changing either the thickness of the dielectric layers of the DBR or the incident angle of the light source, which is a promising utilization for narrow band filters [Plasmonic resonance is a well-known plasmon state that includes SPPs. It creates strong localization of electric fields and has been extensively studied for various applications, including nanoantennas , metasur filters , thermal filters ,48, and  filters ,50.In this study, an idea was developed for a graphene photodetecting device employing the TP structure. As graphene was transferred onto the DBR, a metal film was fabricated on the graphene layer. The proposed graphene–TPP photodetector was devised and fashioned using gold electrodes to collect electrical signals. The graphene layer does not affect the TPP resonance thanks to the atomic layer thickness of graphene; however, the graphene locates the localized electric field formed by the TP structure. The structure converts incident light into TPPs that are collected and transferred into photocurrents by the graphene layer. The photocurrent generation mechanism of our device is related to the PV effect. In our proposed graphene–TPP photodetector, the photoresponse of graphene can be enhanced by the localized electric field, and the device facilitates angle and wavelength selectivity by means of the TP structure. Our device can be utilized as a miniaturized LiDAR detector for suitable applications, lowering the processing cost, and optimizing the processing yield.3)3 solution (33 wt.%) at room temperature (23–26 °C) for approximately 12 h. Subsequently, the stack was cleaned for 1 h with deionized (DI) water to wash off the residual etchant. After the floating stack became etchant-free, it was transferred to the target substrate, which was treated with UV-Ozone prior to the transfer for achieving better quality graphene. The UV-Ozone treatment enhanced the surface energy, which decreased the contact angle, resulting in a free adjustment of the stack on the substrate. Following the transfer process, the sample was left to dry in an oven at room temperature until complete dehydration was achieved. The sample was immersed in acetone to remove the photoresist and subsequently rinsed with isopropanol (IPA).Single-layer graphene grown on a Cu foil using the chemical vapor deposition technique was transferred using the wet chemical method. Initially, the graphene was covered with a thin layer of photoresist (PMMA-A4) by spin coating. The graphene/photoresist stack was removed after the Cu foil was etched away in a Fe(NOTwo graphene–TPP photodetecting devices were designed to prove that our device could work in both the near-infrared (NIR) and visible light regions. In 2, refractive index n = 1.475) layers is approximately 144 nm, and that of all the titanium dioxide  layers is about 95 nm, giving rise to the central wavelength of the DBR at 850 nm, which could be considered as an NIR-region sample.  of the TPP resonance. The TP structure and excited TPP resonance were designed using the finite-element method in COMSOL Multiphysics . In this model, a plane-wave light source of 700–1000 nm obliquely illuminates the designed TP structure, and it is transverse magnetic (TM) polarization. The different simulated TPP resonance peaks are as shown in Tamm Plasmonic structures have been extensively investigated; we can finely tune the wavelength of the target resonance by changing the incident angle or the thickness of the top dielectric layer of the DBR, and we can also change the different metal films  to achieve a higher quality factor (R = photocurrent intensity (IPC)/Light source power (Plight)), the red solid curve in −1 when the incident light power is 0.24 mW. Although both the peaks from the simulation and experiments happen at the same angle of 50, it can be noticed that there is still little deviation between the red and green curves because the simulated TPP (green curve) owns a better-quality factor in resonance than the measured TPP (red curve). Next, we removed the DBR layer to create a W/O TPP sample as a control group (for a detailed schematic of the control group, please see As we have already discussed the angle selectivity in −1 when the power of the 517 nm incident light is 0.32 mW. We also prepared a W/O TPP sample as a control group (for a detailed schematic of the control group, please see The contribution of this work is the simplification of the structure of the photodetector device by stacking layers to form the plasmonic structure. The results confirm that our Graphene–TPP photodetector can be universally applied to various optoelectronic materials. With the field confinement located at the metal–DBR interface, the TPP signal can be detected and converted into electrical signals.−1 at an incident angle of 50°, as the absorption increased from 0% to 60%; hence, it can be noted as an angle-selective device. On the other hand, the responsivity in Device B was enhanced from 60 mA/W to 271 μA⋅W−1 at the wavelength of the light source of 517 nm, as the absorption increased from 15% to 65%; therefore, it can be considered as a wavelength-selective device. Additionally, two devices working in the visible and NIR regions were demonstrated, indicating that the graphene–TPP device can work in both regions.In conclusion, a Graphene–TPP photodetector device was developed. By illuminating the TP structure, a strong localized field was generated by the structure and detected by graphene, which converted to the photocurrent response. Different photocurrent responsivities were observed at different incident angles and light source wavelengths. The responsivity of the photodetector can be affected by the absorption of the structure. In Device A, the responsivity could be enhanced from approximately 0 mA/W to 330 μA⋅W2 and MoS2, and the wavelength and angle selectivity can be applied to next-generation miniature LiDAR detecting, sun sensors, and laser beacon tracking and navigational instruments.To enhance responsivity, the graphene layer in the developed device can be replaced by materials such as WS


N-methyl-2-pyrrolidone (NMP) is recognized as the most efficientmethod for both the exfoliation and dispersion of graphene. Unfortunately,NMP is neither sustainable nor suitable for up-scaling productiondue to its adverse impact on the environment. Here, we show the realpotential of green solvents by revealing the independent contributionsof their exfoliation efficiency and graphene dispersibility to thegraphene yield. By experimentally separating these two factors, wedemonstrate that the exfoliation efficiency of a given solvent isindependent of its dispersibility. Our studies revealed that isopropanolcan be used to exfoliate graphite as efficiently as NMP. Our findingis corroborated by the matching ratio between the polar and dispersiveenergies of graphite and that of the solvent surface tension. Thisdirect evidence of exfoliation efficiency and dispersibility of solventspaves the way to developing a deeper understanding of the real potentialof sustainable graphene manufacturing at a large scale.Achieving a sustainableproduction of pristine high-quality grapheneand other layered materials at a low cost is one of the bottlenecksthat needs to be overcome for reaching 2D material applications ata large scale. Liquid phase exfoliation in conjunction with  Deconvolution of the overall grapheneyield of green solventsinto exfoliation efficiency and dispersibility. This deconvolutionreveals the high exfoliation efficiency of green solvents. Forsuch applications, graphene is generally produced by simple, scalable,and inexpensive liquid phase exfoliation (LPE) techniques wherebygraphite crystals are either shear-mixed (SM) or ultrasonically exfoliatedin a solvent. In LPE, there are three key factors that influence andgovern the graphene yield: the (i) graphite quality, the (ii) exfoliationefficiency, and the (iii) dispersibility of the solvent. The qualityof graphite, defined by the graphite size, crystallinity, and impurities,greatly affects its wettability.7 The higher the graphite quality,the lower its wettability, and if a solvent cannot wet the graphite,it cannot penetrate between the graphite layers to peel them off.Intuitively, this means that large, highly crystalline graphite flakesare more difficult to exfoliate than smaller, less crystalline, anddefect-containing graphite powders. The exfoliation efficiency isdefined by the ability of the solvent to “peel off”individual layers of graphene from the graphite crystal. In contrastto this, the graphene dispersibility is the ability of the solventto form uniform and stable graphene dispersions over a given time.Typically, 1-methyl-2-pyrrolidone (NMP) or dimethylformamide (DMF)is used as a solvent in LPE since both are ideal for exfoliating graphiteand producing stable dispersions of graphene.8 However, their toxicity and high boiling points, for example, 153and 202 °C for DMF and NMP, respectively, are an issue in thecontext of sustainable graphene manufacturing, and therefore, alternativeLPE solutions must be sought out.14 High-boiling-point solvents are difficult to remove and result inmajor loss of the material, degradation of the material quality, andthe generation of toxic waste.15 Therefore, major significantefforts have gone into finding suitable and sustainable solvent alternatives,so-called green solvents.16 Green solvents areeco-friendly solvents with low boiling points, for example, <100°C, and low toxicity.17 Although previouswork has shown that green solvents can indeed be used to produce grapheneby means of LPE, it has not progressed much further. To enhance thegraphene yield in green solvent LPE (GS-LPE), which currently is ca.50–75% lower than in DMF or NMP,19additives suchas surfactants and/or dispersants  have been intensively explored.23 Unfortunately, additives remainon the graphene and are difficult to remove after exfoliation, andtherefore, the as-produced graphene is no longer pristine, which canaffect its properties and negatively influence its performance.24 In the pursuit of improving the graphene yieldof the GS-LPE process, solvent exchange methods have also been investigated,whereby graphite was first “pre-treated” and/or exfoliatedin NMP or DMF, followed by re-dispersion of the as-produced graphenein a green solvent.27 While the graphene yield could indeed be increasedthrough the solvent exchange, toxic NMP and DMF solvents are stillrequired for the exfoliation. This will contribute in developing anunderstanding of the actual role that the solvent plays in the LPEmechanism and how it specifically contributes toward the exfoliationprocess. The current evaluation method of the graphene yield in greensolvents is hindered by the limited dispersibility of the as-producedgraphene in green solvents. The low amount of collected (and detected)graphene gives the false impression that green solvents are unsuitablefor the efficient production of graphene. This study paves the wayfor the development of a set of post-exfoliation procedures for theenhancement of the graphene yield in green solvents through the optimizationof their dispersibility. This route opens up new opportunities toexplore the real potential of green solvents, thought of as inefficientin the production of graphene via LPE.Grapheneis widely investigated as the next generation materialfor application in flexible electronics,S1.1), we employed shear mixing LPE  in conjunction with distinctively differentgraphite materials , and their surface areas of 13.15(G50) and 1.88 m2/g (G150) were measured by the Brunauer–Emmet–Teller(BET) N2 absorption isotherms. The experimental methodsused for the exfoliation and re-dispersion of the exfoliated grapheneare detailed in S1.2. The characterizationtechniques used for the graphite and graphene materials are detailedin S2. Following the work by Coleman etal., it is generally accepted that a higher graphene yield can beachieved if the surface tension or solubility parameters of a solventare similar to that of graphene.28 This rule-of-thumbis typically employed to select the solvents for the LPE of layeredmaterials.29 The surface energy of idealgraphene, that is, atomically perfect graphene, is 68 mJ/m2.30 This value changes for defective grapheneand may vary for graphite due to, for example, graphite morphology,lateral size, defect density, edge defects, d-spacing,additional functional groups, and so forth.31 Wedeliberately selected graphite starting materials with different degreesof defect in our study (S3). G50 graphiteis more defective than G150, with a higher D peak at (1350 cm–1 Raman shift), as analyzed through Raman spectroscopy. Herein, we employed SM-LPEin a range of green solvents  while keeping shearmixing parameters constant (S1.2.1). Asthe shear mixing product usually consists of well-separated/-dispersedgraphene and graphite aggregates composed of stacked graphene andpartially exfoliated graphite . We compared theabsorptivity values for GR150 and GR50 in both NMP and D.I. water. Absorptivity values, ε,for GR150 and GR50 in NMP are used for the concentration calculationbased on the Lambert–Beer law due to the high graphene dispersibilityof NMP. ε for GR150 and GR50 are 1178 and 1589 mL mg–1 m–1, respectively. In most cases, the grapheneyield or exfoliation efficiency is correlated with the initial weightof graphite used for LPE, and it is generally accepted that the graphitesource is represented by its mass,33 whilethe graphite surface area is neglected or not considered to be important.For example, Lund et al. claimed that the concentration of grapheneproduced using LPE is independent on the size of the graphite source.34 Here, we demonstrate that the nature of thestarting graphite material matters because the exfoliation efficiencyand dispersibility are greatly affected by the crystallinity  and the size of the graphite crystal. Both theconventional GS-LPE .To study the green solvent exfoliationefficiency and dispersibilityof graphene independently, we performed SM-LPE in a range of greensolvents and then removed the solvent and re-dispersed the subsequentpowder in NMP (with high dispersibility) for analysis only, referredto as the NMP re-dispersion (NMP-R) from hereon. Here, NMP merelyserves as a standard dispersing medium, that is, tool, to investigatethe exfoliation efficiency and dispersibility, independently. Withthis approach, it is possible to compare the actual yield of graphenein green solvents 1d. For tatersee S2. Absoratersee S2. Absoratersee S2. AbsorFigure S5a). Interestingly, the exfoliation efficienciesof both, IPA and EtOH, exceed that of NMP for GR150, whereas for GR50,the exfoliation efficiencies of IPA and EA are comparable to thatof NMP , in which G150 and G50 were firstshear-mixed in NMP. The graphene-containing suspension was then filteredand washed with EtOH in order to remove any NMP residues, dried, andre-dispersed in selected green solvents. This evaluation explicitlyshows that IPA has the best graphene dispersibility for a green solventfor GR150, followed by the EtOH/D.I. water, whereas for GR50, EtOH/D.I.water possesses better dispersibility than IPA  are shown in Figure S5c,d.In conventional GS-LPE, the poor graphene dispersibilityof thegreen solvents (besides NMP) results in a considerably lower grapheneconcentration in the supernatant after centrifugation than the actualamount of graphene produced 2a,a1; thS7). This resulted in the enhancement of GR50yield by 16 times when re-dispersed in IPA (from 0.0005 to 0.0077mg/mL) and 60 times (from 0.0005 to 0.0298 mg/mL) when re-dispersedin EtOH/D.I. water (S8.1), without the need of compressing it intopellets—required for a conventional contact angle approach.The properties  of the testliquids used for the contact angle measurement are shown in Table S1. The contact angle obtained are usedfor the Owens–Wendt–Rabel and Kaelble (OWRK) plot . The interfacial contact angle between all tested solvents andG150 and G50 is lower than 90° (p/σd)36 The polar component, S8). The analysis showsthe difference in σp/σd betweenG150 and G50 and the solvent [Δσ(p/d)] . Δσ(p/d) forNMP is lower than that for green solvents while maintaining a highexfoliation efficiency, regardless of its large surface tension differencewith G150 and G50 graphite. Similarly, IPA shows low Δσ(p/d),which explains its high exfoliation efficiency, close to that of NMP.On the contrary, Ace and D.I. water show high Δσ(p/d),which causes the low exfoliation efficiency.IPA has the highest dispersibility and exfoliation efficiencyforGR150, that is, it produces the highest graphene yield 3a. For GI. water 3c, implyRK) plot 3d for ththan 90° 3e, confithan 90° 3d, whichFigure S8). The evaluation of ID/ID′37 for all exfoliated graphene samples showed that the type of defectsis similar to that of NMP-R graphene, except for that of the EA-exfoliatedGR150 (ID/IG) asit is confirmed to be a more accurate way to determine the latticedisorder within graphene.39 The G peak fwhm ishigher for GR50 exfoliated in all investigated solvents; hence, GR50has a higher lattice disorder than GR150  nor the number of layers (2D peak). Atomicforce microscopy (AFM) examination was used to determine the thicknessof GR150 and G50 exfoliated in IPA. The exfoliated GR150 shows a veryhomogeneous leaf-like structure with a lateral size close to the micronscale and with the thickness ranging from 5 to 9 layers  the solvent exfoliationefficiency and (ii) the solvent’s ability to disperse the exfoliatedgraphene. We systematically evaluated a wide range of green solventsand their mixtures together with the state-of-the-art NMP solvent,which is known as the best for LPE, as a control. Specifically, westudied the potential of NMP-R that we developed in assessing andquantifying the exfoliation efficiency of green solvents and the GS-Rin assessing the graphene dispersibility of green solvents. From thestudy, the IPA solvent has a high exfoliation efficiency toward theexfoliation of GR150 graphene, which is comparable to that of NMP(despite its poor graphene dispersibility), and EtOH/D.I. water providesthe highest GR50 yield mainly because of its good graphene dispersibility.We also verified the superior exfoliation efficiency of IPA by experimentallystudying the surface energy and surface tension between graphite andthe solvent using the Washburn method. By re-dispersing the grapheneexfoliated in the solvent with a high exfoliation efficiency but poordispersibility into a solvent with a relatively high dispersibility,the graphene concentration can be improved up to 16 times. Our NMP-Rand GS-R approaches can be applied to LPE on any type of layered materialin order to evaluate the potential of green solvents for obtainingthe highest possible yield of the material.


N-methyl-pyrrolidone (NMP) are toxic and difficult to scale up. However,the search for alternative solvents is hindered by the intimidatingsize of the chemical space. Here, we present a computational pipelineinforming the identification of effective exfoliation agents. Classicalmolecular dynamics simulations provide statistical sampling of interactions,enabling the identification of key molecular descriptors for a successfulsolvent. The statistically representative configurations from thesesimulations, studied with quantum mechanical calculations, allow usto gain insights onto the chemophysical interactions at the surface–solventinterface. As an exemplar, through this pipeline we identify a potentialgraphene exfoliation agent 2-pyrrolidone and experimentally demonstrateit to be as effective as NMP. Our workflow can be generalized to any2D material and solvent system, enabling the screening of a wide rangeof compounds and solvents to identify safer and cheaper means of producingdispersions.The scalable production and dispersion of 2D materials,like graphene,is critical to enable their use in commercial applications. Whileliquid exfoliation is commonly used, solvents such as  Such techniques should alsobe applicable to other 2D nanomaterials with an even greater rangeof properties and thereby devices.Graphene has unique chemicaland physical properties, such as recordtensile strength and flexibility,6 Amongsolvent exfoliation techniques, high shear mixing and microfluidizationare the most commonly used for large-scale graphene production.9 Exfoliation is a result of mechanically driven tearing and peelingof incrementally smaller flakes away from a graphite crystal; thesolvent then stabilizes the freshly formed graphene flakes, preventingaggregation.11 However, graphene produced through solvent exfoliation is oftenof low quality, featuring inhomogeneity and imperfections.13 Unfortunately, the best solvents capable of minimizing the damageto graphene during production are also toxic. In particular, N-methyl-pyrrolidone (NMP), has been labeled as a substanceof very high concern by the European Chemicals Agency with restrictionson use, making it undesirable for larger-scale production (Table S1.3). The aim for scalable manufactureis, therefore, a solvent capable of producing graphene dispersionsof high quality while being safe to handle and exploit on a largescale.The demonstration of solventexfoliation in 2008 allowed the manufactureof graphene in kilogram batches.8 To account for the different interactions within the system , they derived Hansen solubility parametersfor graphene from the values of known effective solvents.14 When discussing Hansen parameters for predictions,it is important to consider the large data set that must be collectedfor any new 2D materials to calculate the material’s parametersbefore any predictions can be made (see Supporting Information Section 1.2 for the full discussion). These metricshave been used successfully to rationalize the performance of manycommon laboratory solvents,15 usually byexclusion of those with significantly lower  or higher surface tensions than graphene. Nevertheless, many othersolvents have comparable surface tensions yet are ineffective exfoliationagents.In the search for alternative solvents, different metricsand descriptorshave been used to predict graphene stabilization performance. Rationalizingthat a stable dispersion requires the graphene–solvent interfaceto be as close in energy as possible to the favorable solvent–solventinteractions, Hernandez et al. proposed that the surface tension ofa solvent should match that of graphite.Surface tension arises due to an imbalance of cohesiveforces atthe liquid–vapor interface .The interfacial tension, in contrast, describes heterogeneous interactions,such as between a solvent and a surface. Here, adhesive forces giverise to molecular structuring at the interface, thin-film formation,and wetting phenomena. Therefore, surface tension alone is insufficientto describe the heterogeneous physicochemical interactions, key tounderstanding the processes at the interface such as aggregation ofgraphene flakes in a solvent.Supporting Information Section 1.3 for a comparison of solventsused in previous studies).To this end, we use molecularsimulations to gain atomic-leveldetails on the structures, dynamics, and interactions at the interface.We develop a computational pipeline leveraging molecular dynamicssimulations for characterization of the interactions between solventmolecules and 2D materials. Representative molecular states are thenautomatically selected and interrogated at higher resolution via densityfunctional theory calculations. Applying this pipeline to the caseof graphene, we identify a correlation between the surface arrangementof common solvent molecules and their effectiveness at stabilizinggraphene dispersions. Using this methodology, and as an exemplar,we were able to predict and experimentally validate, 2-pyrrolidone,a solvent with equal liquid exfoliation performance to NMP, the bestperforming solvent currently in wide use , a commonly used solvent, very effective at exfoliation.16 We then included solvents with poor exfoliationcapabilities, specifically water, ethanol, and acetone.8 Finally, we selected two solvents that, havingsimilar physical properties to NMP, are used as substitutes in a laboratorysetting: N,N-dimethylformamide (DMF)and dimethyl sulfoxide (DMSO). DMF is already known to be an exfoliatingsolvent, albeit generally producing a lower graphene concentration.17 Conversely, DMSO is ineffective for exfoliation,19 despite having properties such as surface tension and Hansen solubilityparameters remarkably similar to those of NMP. All the solvents usedin this study and their physical properties, solubility parameters,and toxicity are summarized in Tables S1.1–S1.3, respectively.In orderto identify and quantify the specific solvent-surface interactionsthat stabilize exfoliated graphene layers and prevent aggregation,we use MD simulations to screen through a number of solvents withknown performance for graphene exfoliation. Our strategy is to compareand contrast interactions of a set of solvents known to exhibit differentexfoliation capabilities. First, we selected 2.3Table S3.1). This approach is a form of dimensionality reduction, allowingus to comprehensively describe the orientation of the solvent withrespect to the surface using only four values: elevation and azimuthof the vector and the plane, without strict dependency on the chosenreferential.21 Since graphene surfaces featurea 6-fold symmetry, azimuth values hold little additional information, allowing us to further reduceour descriptors into a two-dimensional plot of vector vs plane elevationsfor surface coating solvent molecules . From these statistical distributions, we observe thatthe known effective solvents share a similar pattern,  from amaterial and plotting a 3D bivariant histogram, statistically significantchanges to the material can be observed.22 A 3D histogram shows the occupancy of bins as a heat map, whilethe bins are simultaneously described by two metrics, in this casethe intensity ratios of Raman peaks: ID/IG is correlated with defects and inverselycorrelated to lateral size, while an increase in I2D/IG is usually caused byexfoliation.The statistical Raman analysis followedthe workflow introduced previously. In brief, by collecting many spectra, which remained stable beyond a month.CPN produced unstable dispersions that sedimentedwithin an hour,leaving a clear solvent 4c. This I2D/IG values indicates a statistically significantchange in the spectral data between the two samples. In this casethe increase in I2D/IG implies a decrease in the flake thickness that is mostimpactful for the PRL and NMP exfoliated graphene.23 Furthermore, the PRL histogram occupies a smaller areacaused by a decreased polydispersity of spectra obtained, indicatingmore uniform flakes22 (see Supporting Information Section 5.2 for a detaileddiscussion). The lower ID/IG is likely caused by larger flakes within the sample,and this is supported by the microscopy data of the few layer flakes.24DMF successfullyexfoliated graphene and produced a stable dispersion,indicating the presence of single and few-layer graphene. TEM wasused to image a large number of flakes, some examples shown in (Supporting Information Section 5.6), and fromthese distributions comparing the lateral sizes of NMP and PRL exfoliatedgraphene were produced . Although the density of states analysis highlightedslight differences between the partially occupied bands of effectiveand ineffective solvents; these differences were too small to be consideredstatistically significant. We note that graphene layers can distributecharges across the plane of their surface. Thus, even if some chargetransfer is present, its identification may not be possible withinthe level of statistical error.Previously,charge transfer between solvent molecules and the graphenesheet had been proposed to explain solvent stabilization of graphene.326 Our DFT study featured a number of extremelylarge systems, allowing us to minimize finite-size effects and undersamplingand, therefore, reduce the risk of false-positive conclusions.28 The lack of relevant changes in the electronic structure of grapheneand adsorbed solvent molecules within our calculations is of note,indicating that physisorption dominates chemisorption.The utilityof molecular modeling for the characterization andprediction of solvent–material interactions has been demonstratedon an example of solvent-mediated graphene exfoliation. We used MDsimulations to examine an array of solvents and to classify theirinteractions with the substrate, obtaining a distinctive molecularfingerprint associated with these solvents’ effectiveness.Interestingly, statistically inferred representative structures examinedvia planewave DFT showed no significant electronic structure changes,failing to confirm previously suggested charge-transfer mechanisms.Statisticalensembles from MD simulations were able to highlighta key interaction shared by all effective solvents tested–formationof a structured solvent layer at the interface with graphene, wherethe solvent’s π-system over part of the ring aligns parallelto the surface. The saturated section of the ring is, therefore, pushedaway from the surface and acts as a steric barrier. This preventsanother π-system from establishing close-contact with the surfaceand restacking. Solvents without π-electrons are ineffective,as they only weakly interact with the graphene, maintaining the flexibilityto reorient themselves and allowing for restacking. Planar conjugatedmolecules can also allow for the restacking of the graphene sheets,as they remain flat on the surface. This key interaction was sharedby all the effective solvents tested within this work, but it is possible,and indeed likely, that other adsorption modes exist from other solventmolecules within the vast possible chemical space.31 developed for colloid suspensions, to be better poised, as theyinclude forces between interfaces such as solid surfaces and liquidfilms. Our work has highlighted the importance of accounting for interfacialinteractions to describe the solvent-nanosheet stabilization mechanism.Furthermore, it should be highlighted that other combinations of 2Dmaterials and solvents should benefit from such an in silico approach as a part of assessment for nanomaterial processability.While previouslyHansen solubility parameters and surface tensionshave been used to guide the choice of new solvents, the predictivepower of the method is limited since it is based on solvent–solventmixing which ignores heterogeneous interactions at the interface.Our observations suggest that DLVO-based approaches,Overall, we demonstrated how our modeling pipeline was able toidentify key molecular interactions driving graphene stabilization,informing the identification of an effective solvent, 2-pyrrolidone,which was also experimentally validated. Our computational approachis of general applicability for the systems where physicochemicalinteractions of liquid or gas with a surface result in a macroscopicallyobservable phenomenon. In this context, we foresee utility of ourapproach for examining other 2D materials, such as MXenes, transitionmetal dichalcogenides, and layered double hydroxides.44.14.1.12 graphene or graphite surfaces,where graphite is formed by a stack of six graphene sheets. The materiallayer is placed at center of the simulation box of 10 nm, filled withsolvent molecules. See Supporting Information Section 2.2 for full details of the set up. All the simulationswere performed using CHARMM3632 force field,assigned with CGenFF.34 Parameters with a high assignmentpenalty score have been reassigned and thoroughly validated; see Supporting Information Section 2.1 for furtherdetails.MD simulationsfeatured 4.2 × 4.2 nm35 Each simulation was first energy-minimized usinga steepest descent algorithm with convergence criterion being themaximum force on any one atom to be less than 100 kJ mol–1 nm–1. Systems were then equilibrated for 5 nsin the isothermal–isobaric ensemble with a velocity-rescalethermostat set at 300 K, coupling constant set to 0.1 ps, and a semi-isotropicBerendsen barostat at 1 bar, coupling constant of 1 ps. The minimizationand equilibration simulations were run with real-space particle-mesh-Ewaldelectrostatics and a van der Waals cutoff of 1.2 nm. After equilibration,production runs of 20 ns were performed, using the same protocol exceptwith a longer cutoff of 1.4 nm.The simulations were performed with GROMACS 2018.DynDen(Supporting Information Section 2.3), and the last 10 ns of the trajectorywere used for further analysis. We then followed previously establishedanalysis protocols, obtaining linear partial density, layer undulations,and interlayer spacing .37 See Supporting Information Section 2 for the full details of preparation andvalidation systems for MD simulations.The simulations were assessedfor convergence using DynDen  versus its position on the z-axis . We then extracted the subset ofdescriptors belonging to surface coating, or adsorbed, molecules whichlay within 0.6 nm from the surface, as determined from the lineardensity profile . Using the k-means clustering algorithm, we aggregated molecules into12 clusters according to the surface interaction descriptors . We selected the molecules associatedwith the centroid of each cluster as representative of typical solventabsorption modes, their selection included the molecule itself, additionalsurrounding solvent molecules with any atom falling within 9 Åfrom the representative, solvent molecule, and surface patch underlyingit. For graphite, the selected patch included all six underlying layers,while for graphene, solvent molecules underneath the layer were alsoincluded. All systems occupied a simulation box of ∼2.3 ×3.1 × 3.4 nm3, which also allowed for vacuum in z-direction. Graphene systems featured between 500 and 700atoms, out of which 252 formed the graphene sheet. Graphite systemscontained 1510 atoms of material, with solvent molecules totallingto 1650 and 1800 atoms. The selected cluster IDs, as well as anglesof vector and plane elevation are given in Table S3.4. See Supporting Information Section 3 for full details of analysis of MD simulations.The coordinates of allsolvent atoms required by our orientation descriptors are extractedfrom simulations and saved into a file using a VMD Tcl script.4.239 The exchange-correlationinteractions were described within the generalized gradient approximationof Perdew, Burke, and Ernzerhof40 withthe semiempirical correction of Grimme for dispersion used in geometryoptimizations.41 Ultrasoft/PAW potentialswere used to describe the valence electron interactions with atomiccores. A supercell approach was used with periodic boundary conditionswith a vacuum region to simulate the surfaces. Brillouin zone samplingand plane-wave basis set cut-offs were set to converge total energydifferences to better than 0.01 eV/cell and SCF and eigenenergy convergencetolerance of 10–8 eV. An L-Broyden–Fletcher–Goldfarb–Shannominimization scheme was used for geometry optimization, which is consideredconverged when the following criteria are satisfied: electronic energytolerance of 1 × 10–6 eV, energy change 5 ×10–6 eV per atom, maximum displacement of 5 ×10–4 Å, and maximum force of 3 × 10–2 eV Å–1.Theelectronic structure calculations were performed using the CASTEPcode (v18).via Mulliken population analysis and Hirshfeld analysis.42 The valence electron density of states was calculated,and partially occupied bands shown on the structure. The data waspostprocessed with c2x. See Supporting Information Section 4 for full details of analysis of DFT simulations.After geometryoptimization, atomic charges of the models were calculated  with c2x and rend4.34.3.17 with a Silverson Ltd. L5M laboratory mixer witha 15.6 mm diameter rotor/stator with a gap size of 100 μm. Naturalflake 325-mesh graphite (50 mg mL–1) was added to100 mL of solvent and mixed at 6000 rpm (γ̇ = 49000 s–1) for 60 min. The resulting dispersion was centrifugedat 5000 rpm (3438 g) for 60 min to remove large unexfoliated flakes.Graphene wasexfoliated following the procedure outlined by Paton et al.4.3.24.3.2.1–1 Raman signalof silicon. Dispersions were filtered through a 0.45 μm PTFEfilter membrane to produce a smooth surface from which Raman spectrawere collected directly. Over a hundred points were collected fromeach sample, these spectra were fitted with a six-order polynomialbackground and Lorentzian line shapes using Python 3.4; further methoddetails published previously.22 Furtherdetailed information and a complete data set are given in Supporting Information Section 6.Raman spectrawere recorded with a Horiba LabRam Evolution using a 532 nm, 1 mWlaser and a 50× long working distance objective lens. The instrumentwas calibrated against the 520.7 cm4.3.2.225TEM images were acquired using a JEOL 2100F FEG TEM operating at80 kV. Samples were dispersed in ethanol solution then dropped ontoholey carbon on a 300-mesh copper grid. Flake lateral size measurementswere made following the National Physical Laboratory protocol, calculatinga mean of the longest length and perpendicular width value.4.3.2.3SEM images were collected with a Hitachi SU-70 FEG SEM. Samples weredispersed in ethanol and deposited on silicon wafers, and all imageswere collected uncoated.4.3.2.4AFM images were collected with an AIST-NT SPM SmartSPM-1000 operatingin noncontact mode with silicon tips; samples were washed in ethanolby repeated dispersion and centrifugation before being drop-cast ontosilicon for imaging.4.3.2.5UV–vis spectrawere collected with a Cary 5000 UV–vis–nIR using quartzcuvettes, path length 2 mm.4.3.2.6Photographs 4c were tSupporting Information Section S5 for full details of experimental preparation andcharacterization, including complete set of microscopy images.See 4.438 with carbon atoms in gray, oxygen atoms in red, nitrogen atoms inblue, sulfur atoms in yellow, and hydrogen atoms in white, unlessotherwise specified. All graphs reporting on simulation data, as wellas on statistics of Raman spectra were produced with Python 3.4 usingthe matplotlib package.44Simulation boxstructures were rendered with VMD v.1.9


In this paper, graphene/h-BN metamaterial was investigated as a new neutron radiation shielding (NRS) material by Monte Carlo N-Particle X version (MCNPX) Transport Code. The graphene/h-BN metamaterial are capable of both thermal and fast neutron moderator and neutron absorber process. The constituent phases in graphene/h-BN metamaterial are chosen to be hexagonal boron nitride (h-BN) and graphene. The introduced target was irradiated by an Am–Be neutron source with an energy spectrum of 100 keV to 15 MeV in a Monte Carlo simulation input file. The resulting current transmission rate (CTR) was investigated by the MCNPX code. Due to concrete’s widespread use as a radiation shielding material, the results of this design were also compared with concrete targets. The results show a significant increase in NRS compared to concrete. Therefore, metamaterial with constituent phase’s graphene/h-BN can be a suitable alternative to concrete for NRS. In recent years, the radiation shielding concept has been extended to exploit radiation-related technology properties, such as radiography and radiotherapy . NeutronPreparation of high-quality metamaterials can be accomplished through laser chemical vapour deposition. Because of its low porosity, high crystallinity, and high purity, the material deposited by this technique usually has mechanical properties and a thermal stability that are superior to other techniques . That isIn this article, the shielding properties of this particular type of metamaterial (graphene/h-BN) have been investigated by Monte Carlo N-Particle Transport Code (MCNPX) and the results compared with concrete as an indicator neutron shield. One of the index codes for evaluating the effects of radiation is the MCNPX code ,23,28,29The main aim of this research is the initial step to evaluate metamaterial as a neutron radiation shielding, and for this purpose, the results are compared with the most important neutron radiation shield, concrete, and if it performs better than concrete, it can be introduced as a neutron radiation shielding. It can provide a platform for more calculations and research in line with the use of metamaterials in the radiation shielding industry. By simulating a model, theorists can examine its properties and compare their predictions with the simulation results. The simulation is actually a virtual experiment that is performed to understand the response of the behavior system before a real one is conducted. However, it allows experimentalists to assess the validity of experimental results when a theory is highly complicated, while they do not have a precise method to solve it by theorizing. Since Monte Carlo simulations and modeling can be used in the science of particle transport at no cost, the calculations were performed through coding. As one of the most significant nuclear codes, the MCNPX code has been validated and verified by many researchers ,31,32, aA blank line is required to separate these three main cards. A cell card is required to describe the geometry. Each cell is made of different surfaces that are listed on the surface card. The data card contains all the necessary information for making the cells, including the material specifications (density and percentage of the elements in it), the specifications of the radiation source and how to extract the data. After writing the MCNPX code input file, this file is executed, and the desired results are recorded in an output file.3, which is initially completely filled with concrete and then defined with a metamaterial structure. There are two phases in the metamaterial state: hexagonal boron nitride and graphene. Hexagonal boron nitride (h-BN) and graphene both have similar hexagonal layer structural features, so that h-BN is referred to as white graphene.By defining the input file , the geometric structure of the target was introduced to the MCNPX code. This structure is a 30 × 30 × 30 cm3 cube is characterized by triply periodic Macrobody surface structures exhibiting a simple cubic lattice : The 30 × 30 × 30 cm lattice . Macrobo3 cube is characterized by structures of a periodic cubic lattice, each of them filled with rod columns : The 30 × 30 × 30 cmThe “Fill” and “Universe” orders can be used in conjunction with the “Lat” command to specify a lattice type  in the MCNPX cell cards. The required surfaces are defined on the surface card using the commands including Macrobody Rectangular Parallelepiped (RPP), Macrobody Right Hexagonal Prism (HEX or RHP), Macrobody Right Circular Cylinder (RCC), and sphere with centered at origin (So). A Macrobody has a specific definition, which is called from the code using the above symbols, allowing it to identify all types of Macrobodies .As part of the MCNPX code input file, materials are defined using the ZAID statement, which multiplies an atomic number by a 1000 and plus mass number (Z × 1000 + A) . It shouThe constituent phases in each metamaterial simulation are chosen to be graphene hexagonal boron nitride (h-BN) and graphene with their ZAID defined in the data card. The neutron source used in the simulation is Americium–Beryllium (Am–Be), which has an energy range from 100 keV to 15 MeV. In z-axis and y-axis and aligned with the direction of the incident beam. To consider all scenarios of hitting the target, the direction of the incident beam was considered along the z- and y-axes, since the target structure is different perpendicularly and parallelly to the sheets. For example, if the beam is irradiated in the direction of the z-axis in the GS1 structure, the incident beam will be perpendicular to the parallel sheets (xz surface), and if it is irradiated in the direction of the y-axis, it will hit the target parallel to the xy sheet. Therefore, both radiation directions were investigated in terms of NRS. Finally, the shielding percentage (SP%) is computed by varying the axis between 0 and 30 cm (cm) and calculating the CTR from an external surface.To obtain NRC in the MCNPX code, the current transmission rate (CTR) was calculated using F1 tally  and flux mesh tally. The mesh tally was defined in three dimensions and meshes were considered along the direction of the 3 sides containing concrete and metamaterial with the GS1 and the GS2 structure. The incident beam was irradiated towards the target in two directions of z- and y-axis, the results of which are reported in First, the CTR was evaluated for a cube target with 30 × 30 × 30 cmAccording to Significant effects of NRS per metamaterial can be observed compared to conventional concrete. As shown in As the incident beam can enter the target from two different radiation directions, the neutron leakage, which is the CTR, may be affected. This was checked using the The results of AX  A−1X reactions are performed at GS1 in thicknesses between zero and 3.4 cm, while neutrons are produced at GS2 in thicknesses up to 2.3 cm.Accordingly, the optimal geometric structure for the metamaterial with the two phases containing graphene/h-BN was investigated by examining GS1 and GS2. Concrete, the GS1 and GS2 structures in the initial thicknesses have an exponential growth of the CTR, which is due to the production of neutrons per  reaction . AX , which is a very impressive result and can be attributed to the boron element, which has a highly remarkable neutron absorption cross-section. Furthermore, the cross-sectional area of collision in energy ranges beyond 10−8 also has a significant growth. Therefore, the neutrons in the GS1 and GS2 structures first moderate the fast neutrons with a more acceptable scattering cross-section than concrete and then absorb thermal neutrons.To evaluate the reason for the improvement of NRS in GS1 and GS2 compared to concrete, the cross-section of each of them was calculated and charted in the energy ranges between 103.In 2020, Ying et al. , investiWhile polyethylene/h-BN shows slightly better results, the SP% is almost close to each other in both structures .One of the most important features of neutron shielding is thermal conductivity (TH). Shielding structures with more TH will therefore be considered advantageous. The value of TH for graphene/h-BN is in the range between 200 and 1000 W/mk , while tObtaining a material that performs well as a neutron shield and has high thermal conductivity is the most important application of shielding in cosmic rays. It may therefore be beneficial to introduce graphene/h-BN metamaterial into this research as a platform for wider studies.This paper introduces a new neutron radiation shield (NRS) using metamaterial with constituent phase’s hexagonal boron nitride (h-BN) and graphene. To evaluate this structure, the Am–Be neutron source was defined in the input file of the MCNPX code, and the current transmission rate (CTR) of the incident neutrons that enter the target was evaluated. The results of metamaterial were compared with the most famous neutron shield, concrete and polyethylene/hexagonal boron nitride. A maximum NRS of 96.43% and 96.77% was obtained at a thickness of 30 cm for the GS1Z and GS1Y, whereas the concrete led to a maximum NRS of 90.86% at a thickness of 30 cm, which is close to the shielding percentage (SP%) obtained from metamaterial at 20 cm thickness. On the other hand, graphene/h-BN has an extremely high thermal conductivity, making it a very significant advantage for NRS. Therefore, graphene/h-BN metamaterials can be a suitable combination to moderate the speed of fast neutrons and ultimately their absorption.


Due to the addition of graphene, the clad layer of specimen 2 was refined and a large number of hard phases, such as CrC and Cr23C6, were generated, which led to the increase in the hardness of the clad layer. When the content of graphene was further increased, the number of hard phases such as CrC and Cr23C6 produced in the cladding was relatively reduced due to the agglomeration of graphene, and the hardness of the cladding was reduced. As the impermeability of graphene reduces the diffusion of corrosive media to the substrate, the generation of hard-phase Al3Ni2 in the cladding layer makes the corrosion resistance of the cladding layer increase with the increase in graphene mass fraction. The result is that, when the content of graphene was 0.5%, the overall performance of the clad layer was the best, where its average hardness was increased by 40%, the average coefficient of friction was reduced by 12.7% and the wear rate was reduced by 60%.A Ni25—10% SiC—X% graphene  composite cladding layer was prepared on a 6063 aluminum alloy substrate using laser cladding in order to enhance the comprehensive performance of the aircraft refueling interface. The effect of the graphene content on the organization and properties of nickel-based silicon carbide composite cladding layers was investigated by laser melting. The macroscopic morphology, microstructure, hardness, elemental changes, corrosion and wear resistance of the cladding layer were studied by optical microscopy, scanning electron microscopy, a hardness tester, an X-ray diffractometer, an electrochemical workstation and an M-2000 frictional wear tester. The results indicated that the nickel-based clad layer without graphene incorporation had the worst forming, with a large number of pores and cracks in the cladding layer. Because graphene agglomerated easily, cracks were regenerated when the content of graphene was higher than 0.5%. The material phases of the cladding layer without graphene incorporation were mainly: Al The aviation pressure refueling connector is a key connection component for aircraft refueling and pumping by aircraft refueling trucks. Currently, the material of the aircraft pressure refueling connector and the aircraft refueling port docking area is mainly aluminum alloy. Aluminum alloys have properties such as a high specific stiffness and strength, easy processing and molding ,2,3. HowThe existing methods for improving the surface hardness and reducing the friction coefficient of aluminum alloys in aerospace pressure refueling joints are mainly micro-arc oxidation ,7,8,9, c60 + Y2O3 reinforced layer and optimized the process parameters by laser melting experiments. It was found that the combination of finite element numerical simulation to optimize the process parameters of laser melting and rare earth modulation modification could well improve the cracking of the laser-reinforced layer on the surface of aluminum alloy. Wu et al. [6Al4V surface using laser cladding technology. The average speed for all samples was investigated, with the microhardness at the coatings being lower than that of the substrate material. Riquelme et al. [Many researchers have carried out some applied basic research work for laser additive wear-resistant self-lubricating cladding layers and have applied them to parts in the aviation and aerospace industries. However, the development of laser additive wear-resistant self-lubricating cladding applicable to the aluminum alloy surface of aerospace pressure refueling joints is still at the stage of technology accumulation ,20. Li eu et al.  investigu et al.  made Ti e et al.  preparede et al.  preparede et al.  studied The use of laser cladding technology can improve many properties of aluminum alloys, but, at the same time, there are also some technical difficulties. First of all, because of the high thermal conductivity and low laser absorption properties of aluminum alloys, a higher laser power than other metal substrates needs to be used when melting the cladding layer. Secondly, most of the laser energy is reflected by the aluminum alloy surface during the laser cladding test, which is not conducive to the formation of the molten pool. Again, the coefficient of the thermal expansion of aluminum alloy is relatively high. During the cladding process, the thermal stress at the interface between the aluminum alloy substrate and the cladding layer is high and the bonding force is poor, which will cause the cladding layer to drop off in serious cases. The aluminum alloy contact surfaces of aviation pressure refueling joints require a certain degree of wear resistance. In view of the above technical difficulties, it is necessary to carry out in-depth research on the key technology of laser cladding coating on the aluminum alloy surface.2 and SiC powders. The ceramic properties of SiC and TiO2 improve the microhardness of the alloyed area and achieve a good defect-free surface alloying. Zhang et al. [Although scholars have prepared protective cladding layers on aluminum alloys using a laser, it is a challenge to adjust the corrosion resistance and wear resistance of the cladding layers when preparing them. Silicon carbide has properties such as chemical stability, a high thermal conductivity, a low coefficient of thermal expansion and good wear resistance . Kumar eg et al.  synthesig et al.  preparedg et al. . Torres g et al.  investigg et al. . Solving2, the diameter was 8 mm and the number was 100.A 6063 aluminum alloy was selected as the substrate material, the dimensions being 50 × 50 × 10 mm; the material composition is shown in Through a large number of preliminary experiments, the power of laser should be appropriate. This is because, if the laser power is too low, it will make it difficult for the coating material to fully melt and have good bonding strength with the substrate, and, if the laser power is too high, due to the low melting point of aluminum alloy, it will make the substrate over-melted, thus causing a large dilution rate; in addition, it will also cause the oxidation decomposition of graphene in the coating material. Therefore, the cladding layer was fabricated using a laser cladding system  with laser power of 2.7 KW, scanning speed of 0.015 m/s, spot diameter of 6 mm, lap rate of 50% and powder feeding rate of 6 g/min, and the cladding layer was prepared using laser on the aluminum alloy substrate. In addition, argon gas with a flow rate of 12 L/min was used to protect the melt pool from oxidation during the laser cladding process, and the powder was injected through a coaxial nozzle coaxially with the laser beam. The distance between the deposition nozzle and the substrate plate was 20 mm, and preparation of single-layer cladding layers used laser cladding. Laser cladding process was conducted using coaxial powder feeding method, and the laser cladding was performed as a single pass process.After the coaxial laser cladding experiments, metallographic specimens were cut along the vertical direction of the laser scanning direction using a wire cutter  and were polished with 60–2000 mesh SiC sandpaper in that order, and then the metallographic specimens were polished using an MP-2B grinding and polishing machine. Then, the metallographic specimens were etched with aqua regia etching solution for 1 to 3 s. After the experiments, the specimens were characterized by a scanning electron microscope  with its own energy spectrum, and the compositions of the additive areas were measured by an X-ray diffractometer , where the operating parameters of the XRD diffractometer were: Cu target, voltage 45 KV, current 200 mA, scanning angle 10–100° and scanning speed 8°/min. The specimen hardness was measured using the HVS-1000Z microhardness tester  with a load of 500 g and a loading time of 10 s from the surface layer of the cladding layer to the substrate. Finally, the diagonal values of the microscopic traces obtained after unloading were measured and the Vickers hardness values of the material were calculated by the Vickers hardness formula.2 of the cladding layer was reserved for electrochemical corrosion test, which was the electrode with Cu wire lead. The reference electrode was saturated glycerol, the auxiliary electrode was platinum sheet and the corrosion resistance of the specimen was characterized by Tafel curve.The corrosion resistance test of the clad surface in 3.5 wt% NaCl solution was conducted on CHI604E B16323 electrochemical workstation , and the test included two parts: potential polarization curve and electrochemical resistance. Electrochemical corrosion experiments cut the substrate and the additive layer size was 10 × 10 mm. Electrochemical corrosion specimens of the working surface, which was sandpaper-polished cladding layer, were polished and cleaned with anhydrous ethanol to remove the residual abrasive and impurities on the surface of the cladding layer, and then cleaned and blow-dried after the use of epoxy resin cold mount for sealing samples. A surface area of 1 cmThe friction and wear test was performed by cutting a specimen of 15 × 15 × 10 mm in length, width and height using wire-cutting machine. In order to have the same roughness of the sample surface, the friction and wear surface was polished with 60–2000 mesh SiC sandpaper in turn, and then the friction and wear test was performed by MPX-3G friction and wear tester . The experimental parameters are shown in The influence of the graphene content on the cladding-layer-forming quality is shown in The effect of the graphene content on the macroscopic morphology of the cladding layer is illustrated in 3Ni2 and Fe3Si, and hard phases, such as SiC, CrC, and Cr23C6. The Al3Ni2 phase diffraction peak was highest at 2θ = 44°, indicating that the Al3Ni2 phase grew selectively along this crystal plane, and the growth of the Al3Ni2 phase along other crystal planes was retarded. Meanwhile, it indicated that diffusion occurred in the melt pool during the cladding process. Due to the low density of aluminum elements, resulting in the aluminum substrate surface microfusion of Al elements into the melt pool inside, Cr and C at high temperatures have a strong tendency to combine, forming CrC, Cr23C6 and other hard phases. Combined with reference [3Ni2 are 4.20922 Å, 5.5361 Å, 5.4429 Å and 4.7266 Å, respectively. The average lattice constants of CrC are 4.3621 Å, 4.9116 Å, 4.7998 Å and 4.4001 Å, respectively. The average lattice constants of Fe3Si are 3.4975 Å, 3.8403 Å, 3.4991 Å and 3.6218 Å, respectively. The average lattice constants of Cr23C6 are 5.7541 Å, 6.8424 Å, 6.5846 Å and 5.8489 Å, respectively. The average lattice constants of SiC are 3.6560 Å, 3.9985 Å, 4.3590 Å and 4.2280 Å, respectively. By comparing the difference, it can be observed that the intensity of the diffraction peaks that was associated with Cr23C6 varies with the mass fraction of graphene in the fused layer at angles of 2θ = 23.68°, 38.06° and 48.71°. The intensity of the diffraction peak for Cr23C6 of specimen 1 without graphene addition was almost zero, and the highest intensity of the diffraction peak was observed for Cr23C6 of specimen 2. Similar trends were observed for the diffraction peaks related to CrC at angles of 2θ = 38.06°, 43.12°and 48.71°, indicating that specimen 2 generated the most CrC and Cr23C6. Compared to specimen 1, specimen 2 was added to a 0.5% mass fraction of graphene, and the elemental C content was increased in the melt pool; thus the contents of CrC and Cr23C6 were further increased. Compared to specimens 3 and 4, although the graphene mass fraction was further increased, too high a graphene mass was prone to agglomeration. The agglomerated graphene at high temperatures made it difficult to free the C element to combine with the Cr element in the molten pool; thereby, the contents of CrC and Cr23C6 were reduced. SiC and Fe3Si were detected, indicating that SiC was partially decomposed under the high-temperature irradiation of the laser, and Fe3Si was formed by Si and Fe. In the two specimens, there are Al3Ni2, CrC, Cr23C6, SiC and other substances that can enhance the corrosion resistance of the surface [eference , the ave surface .23C6, that are diffusely distributed. The clad layer is fully strengthened and thus less prone to cracking. This is because the thermal expansion rate of graphene is lower than that of metals, and the addition of graphene can effectively hinder the growth of metal crystals [3Ni2. With the increase in the graphene content, the microstructure consisting of Al3Ni2 in the cladding layer becomes coarse. This is due to the relatively high thermal conductivity of graphene, which can accelerate the solidification rate of the melt pool, thus making the temperature gradient of the whole pool larger. The contribution of graphene thermal conductivity to grain coarseness is greater than the contribution of its low expansion rate to grain fineness. Moreover, the increase in the graphene content caused a partial agglomeration of graphene, which made the contribution of graphene to grain refinement insufficient. The results of the face scan of specimen 3 in 23C6 generated in the cladding layer fewer, which leads to the weakening of the microstructure-strengthening effect of the cladding layer, and the cladding layer is prone to cracks. Concerning specimen 4, where the mass fraction of graphene is 1.5%, the long dendritic organization in the layer tended to be reduced compared to specimen 3. This is because, in the region of a higher C mass fraction, the nucleation rate of the condensation precipitation phase increases, and the long dendrite organization is relatively fine. crystals . In addicrystals ,42,43. Icrystals . Regardi0.5 to 902 HV0.5. The hardness of specimen 2 fluctuates from 501 HV0.5 to 1298 HV0.5. The maximum hardness value of 1298 HV0.5 occurs in the middle of the clad layer. The hardness of specimen 3 fluctuates from 428 HV0.5 to 782 HV0.5. The hardness of specimen 4 fluctuates from 592 HV0.5 to 884 HV0.5. Under the condition of SiC content, the hardness of the clad layer is related to the mass fraction of graphene added. When the addition of graphene is 0.5%, the cladding layer generates a large amount of Al3Ni2 intermetallic compounds and hard phases such as CrC, Cr23C6 and SiC. In addition, the combined effect of grain refinement and other factors resulted in the highest hardness of the clad layer of specimen 2, with a maximum value of 1298 HV, which is approximately 6.4 times that of the aluminum alloy base material. When the addition of graphene is 1%, the hardness of the clad layer starts to decrease, and the hardness value is smaller than that of the specimen without graphene addition. This is because the coarse-grained long strips of Al3Ni2 generated in the clad layer of specimen 3 contribute more to the reduction in hardness than the increase in hardness of the small amounts of CrC, Cr23C6, SiC, etc. generated in the cladding. Thus, specimen 3 exhibits a lower hardness than specimen 1. When the addition of graphene is 1.5%, the long stripes of Al3Ni2 produced in the clad layer start to become smaller than that of specimen 2. Therefore, the hardness of the clad layer is slightly higher than that of the clad layer, with a graphene mass fraction of 1%.3Ni2 in the cladding layer belongs to the corrosion resistance hard phase, which can improve the hardness and corrosion resistance of the cladding layer. Although the molding quality of the cladding layer of specimens 3 and 4 was worse than specimen 2, Al3Ni2 with corrosion resistance was generated, which improved the corrosion resistance of the cladding layer. As a result, the corrosion resistance of the cladding layer can be significantly enhanced by the addition of graphene.The coefficient of friction (COF) variation curves for the four cladding layers are displayed in 3Ni2 metal compound as the base phase [23C6 with a high hardness, are generated in the cladding layer. The hard phases can be used as wear-resistant pivot points to reduce the frictional wear of silicon carbide ceramic balls on the cladding layer [se phase . Due to ng layer . They cang layer . Therefo3Ni2 intermetallic compound reduces the microhardness of the alloy fused layer, which promotes wear damage. When the mass fraction of graphene is 1.5%, the wear surface of specimen 4 shows a large amount of plastic deformation and heavy tissue flaking. There were a large number of cracks as well as powdered debris on the wear surface; this is due to the large fluctuation in the friction coefficient and the presence of a large number of hard phases  in the fusion cladding layer, which increases its brittleness.(1)3Ni2, Fe3Si intermetallic compounds and SiC hard phase, and the phases of the cladding layer with graphene are mainly Al3Ni2, Fe3Si compounds and SiC, CrC and Cr23C6 hard phases. The addition of graphene reduces the crystallinity of the laser cladding layer and refines the cladding layer grains.The phases of the cladding layer without graphene are mainly Al(2)When the graphene content is greater than 0.5%, the grain refinement ability decreases. In addition, the presence of excess unmelted graphene weakens the absorption of laser energy in the clad layer, and the hardness and wear resistance of the clad layer are reduced.(3)When the graphene content was 0.5%, the number of cracks in the cladding layer was the least, and the hardness of the cladding layer was 6.4 times that of the substrate, with a 32.3% increase in hardness, a 27.2% decrease in friction coefficient and a 66.5% decrease in wear rate compared to the cladding layer without graphene addition.