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.


It has been found that the addition of only 1.2 wt% modified GO  increased the tensile strength, Young's modulus and storage modulus of EVA composites by 80%, 50% and 24%, respectively. These increments surpass many recent claims on relevant composites. Excellent molecular level dispersion was also observed from the fracture surface SEM images. Being amine-rich with high electron-donating capability and mechanically robust, the nanocomposite served as an outstanding tribopositive material, thereby generating 7.49 V and 4.06 μA output voltage and current, respectively, when employed in a triboelectric nanogenerator (TENG). The high electrical outputs led the device to light up 43 blue LEDs instantaneously upon hand pressing, demonstrating that the nanocomposite is indeed a promising candidate for harvesting green energy. Moreover, the nanogenerator displayed outstanding cyclic performance stability (even after 8000 cycles) and environmental durability.While the demand for lightweight high-strength nanocomposites is immense, their progress has been severely limited due to inferior filler dispersion and filler–matrix interface adhesion. This article reports a novel modification of graphene oxide (GO) encapsulated by the copolymer of polydopamine (PD) and polyethylenimine (PEI)  The fabrication of flexible high-performance EVA–graphene oxide nanocomposite triboelectric nanogenerators and the lighting of 43 blue LEDs. Graphene is regarded as the “magic bullet” for the composite world, owing to its remarkably high mechanical, electrical, thermal conductivity and gas and chemical barrier properties. Despite its huge merits and the large amount of published literature on graphene nanocomposites, scientists are still exploring the hidden potentials of this material in order to expand the scope of its application, because the improved properties achieved by graphene are still far lower than the theoretical predictions. Critical challenges that severely limit the continuous advancement of graphene for structural applications is its poor compatibility, non-uniform dispersion and weak interface adhesion with the polymer matrices due to the lack of adequate surface functionalities.1,8–10 Moreover, the strong interlayer van der Waals forces cause the graphene nanosheets to form irreversible agglomerates (or restack), making it extremely difficult to handle. Thus, the prevention of restacking should, therefore, be attained prior to incorporation in any system. Moreover, the level of enhancements has been found to depend significantly on the degree of dispersion, alignment and filler–matrix interface adhesion. Hence, to overcome the above drawbacks and enhance the chemical affinity towards polymer matrices and to successfully harness maximum reinforcement, the surface modification of graphene has become imperative.Among a variety of polymer nanocomposites, polymer–carbon nanomaterial composites, especially carbon nanotubes (CNTs) and graphene-based ones, are of the highest priority of current research interests as they deliver high electrical, thermal, mechanical and barrier properties to the composites at significantly low amounts.e.g., hydroxyl, epoxide, carbonyl and carboxylic acid groups)1,8–10 that can be used as an anchorage for further surface treatments depending on the needs. Here, ethylene vinyl acetate copolymer (EVA) was chosen as the matrix, since it has widespread applications in numerous areas including paints, adhesives, coatings, textiles, cables, automotive plastic fuel tanks, etc.11–14 The GO was modified with polyethylenimine (PEI) through the assistance of polydopamine (PD) coating via the Michael addition reaction, as demonstrated in Therefore, this article aims herein to design a novel surface modification process for graphene oxide (GO) in order to develop mechanically stronger polymer nanocomposites even at significantly low amounts of loading. GO was selected, as it is the most widely preferred derivative of graphene material, containing various oxygenated functional groups .14–17 The working mechanism of this device is based on the contact electrification effect, where energy conversion occurs via surface charge transfer resulting from periodic contact between two dissimilar tribopolar materials, a triboelectric positive and a triboelectric negative material.15–17 Interestingly, the nanocomposite-based TENG showed great performance to the triboelectric response, with an output voltage and current 4 and 4.2 times higher, respectively, than that of the pristine EVA device. Moreover, the EVA nanocomposite TENG showed highly stable performance against severe constant cyclic load and when exposed to ambient conditions for several weeks. Finally, the novelty of this research lies in the concept of the modification of GO, whereby the large reinforcement, excellent molecular-level dispersion and high triboelectric performance of the composite can be achieved concurrently at low filler loading.Besides the structural importance, we explored a new potential application of this composite material as a sustainable energy harvesting device, called a triboelectric nanogenerator (TENG). Recently, energy harvesting and conversion devices using lightweight materials have become an emerging trend in current science and technology, as they play an important role in building and driving self-powered nanodevices. To the best of our knowledge, this is the first article that introduced EVA/GO nanocomposites as a potential futuristic material for triboelectric energy harvesting application. Though graphene–polymer nanocomposites are a new attempt in TENG, Harnchana via several dehydrogenation steps, forming o-quinone units that can instantly cyclize to indole moieties and/or form C–C bonds. The Michael reaction takes place at the o-quinone moieties either at the carbonyl carbon atom or at the β-position of the inherent Michael system in an alkaline medium.18 This leads to the self-polymerization of dopamine and the simultaneous copolymerization with PEI. At the same time, the oxygenated groups on GO can form strong covalent and hydrogen bonds with the PD–PEI layer, making it very suitable in dispersing various solvents and polymer matrices when added.−1. Other characteristic peaks for the C PBM data was replaced with SVG by xgml2pxml:<glyph-data id="z.dbd" format="PBM" resolution="300" x-size="8" y-size="10" xml:space="preserve">00000000000000000000000000000000111111110000000011111111000000000000000000000000</glyph-data><svg xmlns="http://www.w3.org/2000/svg" version="1.0" width="13.200000pt" height="16.000000pt" viewBox="0 0 13.200000 16.000000" preserveAspectRatio="xMidYMid meet"><metadata>Created by potrace 1.16, written by Peter Selinger 2001-2019</metadata><g transform="translate scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O and CC bonds, C–OH stretching vibrations, epoxy (1224 cm−1) and C–O vibrations from alkoxy groups were seen at 1725, 1624, 1351, 1224 and 1039 cm−1, respectively.1,10 After modification with the mixture of PD–PEI, some noticeable spectral changes appeared in the measurement. The new absorption peaks at 2930 and 2831 cm−1 corresponded to the nonsymmetric and symmetric stretching vibrations of methylene, respectively, while the new peaks at 1649 and 1569 cm−1 represent the stretching vibrations of NHCO, 1453 cm−1 for the aromatic CC bond, and 1220 cm−1 for the C–N bands.2,19 It is important to note here that the amine groups in PEI (owing to highly branched structure) will also react with the carboxyl and epoxy groups of GO at the same time, resulting in the appearance of amide and C–N bonds in the respective spectrum. The peak at 3320 cm−1 can be ascribed to the N–H group of PEI. To further ascertain the attachment of PEI onto GO and to learn about the surface chemical compositions, XPS analysis was carried out. 20 This result clearly endorsed the successful attachment of PDA and PEI onto the GO surface. While the pristine GO sample had C and O contents of 69.8 and 30.2%, respectively, the PEI–rGO sample showed 80.5% C, 14% O and 5.5% N contents. However, for curiosity when we checked the XPS spectra for the PD–rGO sample, only 3.7% N content was found .FTIR analysis was performed first to verify the chemical changes in GO as a result of the modification process. −1, corresponding to the first-order scattering of the E2g phonon of sp2 C atoms and structural defects induced by the surface functional groups, respectively. It is well-known that the height of the D band implies the size of the inplane sp2 domains.1,3,8 Therefore, the increase of the D peak intensity indicates the formation of more defects in sp2 domains in the structure. As can be seen in ID/IG ratio of PD–PEI–rGO is higher (1.12) than that of pristine GO (0.84), indicating that surface modification had led to an increase in the number of disorders or defects in the graphene sheets.Next, Raman spectra were measured to understand the crystal structure, disorder and defects in the above GO specimens. As can be seen from 1 Following that, the decomposition, which brought about 20–22% more mass loss, was due to the thermal decomposition of the carbon skeleton. On the other hand, the modified GO showed much higher thermal stability, with only 5% weight loss at 240 °C and 28% total loss at 800 °C. The losses at above 240 °C can be attributed to the degradation of the polydopamine and PEI molecules. The TGA results also revealed that there is ∼15–16 wt% of PD–PEI in the modified graphene oxide (PD–PEI–rGO). The higher thermal stability clearly indicates that there are strong interactions between the GO and PD–PEI moieties, also endorsing the above FTIR spectrum that showed the formation of amide bonds between GO and PD–PEI due to the modification. The presence of such large amounts of PD–PEI in GO also suggests that this can be a good filler for polymer nanocomposites.In order to understand the effect of modification on the thermal behavior of the GO, TGA analysis of pristine GO and PD–PEI–rGO was conducted, and the corresponding results were compared in i.e., 0.4, 0.8 and 1.2 wt%) were added into the EVA matrix to fabricate various nanocomposites. E) was obtained after the addition of PD–PEI–rGO into EVA, and the values increased with increasing PD–PEI–rGO content. It was interesting to see that the addition of the same amount of modified GO (0.4 wt%) led to an increase in the T.S of the nanocomposite by 4.4-fold that of the pristine GO/EVA nanocomposite.To explore the potential of PD–PEI–rGO as a filler material in the area of polymer composites, they were blended with ethylene vinyl acetate copolymer (EVA) matrix to create the nanocomposites. The composites were fabricated by solution casting followed by a melt-blending process. The tensile and DMA test results of the composites will be discussed next, as they indicate the capability of the material for structural performance. Low amounts of PD–PEI–rGO  strong interfacial adhesion between the matrix and the modified graphene nanosheets (owing to strong hydrogen bonding between the carbonyl of EVA and the amine of the PEI), (ii) effective load transfer from the polymer matrix to the graphene nanosheets, and (iii) homogeneous dispersion of the graphene nanosheets throughout the polymer matrix. The higher mechanical strength can also be explained by the greater mechanical interlocking between the EVA polymer chains and modified graphene oxide nanosheets, which possess higher surface roughness. Interestingly, these values were found to be much higher than that of many earlier reports on EVA nanocomposites  is considerably lower than that of the nanocomposites. After the incorporation of GO, regardless of the type (unmodified or modified), the storage modulus of the nanocomposites increased significantly. While the storage modulus of neat EVA was found to be 1981 MPa, nanocomposites containing 0.4 wt% pristine GO displayed a storage modulus value of 2160 MPa, which was ∼9% higher than that of the neat EVA. Interestingly, when the same amount of modified graphene oxide was added , the storage modulus reached to up to 2320 MPa (17% higher), nearly double that of the pristine GO-containing nanocomposite. The gradual addition of PD–PEI–rGO  further increased the storage modulus to 2377 and 2457 MPa, which was ∼20% and 24% higher than the storage modulus of the neat EVA, respectively. Such large increments in the mechanical strengths of the EVA nanocomposites with the use of such a small amount of graphene oxide (1.2 wt%) clearly suggest the great potential of our functionalization process and that of modified GO. The tan δ maximum value, which corresponds to the Tg of the polymer, was also noted to increase with the addition of PD–PEI–rGO  are insulating in nature, the generated charges at each surface would, therefore, remain there , leading to no electric potential difference between the two electrodes. As soon as the compression force is released, a strong potential difference between the top and bottom electrodes was created due to the electrostatic induction effect or strong dipolar difference. As a consequence, the electrons began to flow from the negative to the positive potential through the external circuit, resulting in the experimentally observed positive electric output signal  on the screen. The electron transfer occurs until an electrostatic equilibrium is established. Upon further pressing the TENG, the electrostatic equilibrium was disrupted, and the backflow of electrons took place from the bottom electrode to the top electrode until a new equilibrium was reached. This resulted in the generation of the opposite current, thereby causing reversed electrical signals to be observed. This is considered as the second half of the triboelectric charge cycle.To understand the multifunctional role of the EVA nanocomposite, especially for energy harvesting application, triboelectric measurements were recorded. The construction of TENG is shown in Voc) and the short-circuit current (Isc) between the pristine GO/EVA nanocomposite and the PD–PEI–rGO/EVA nanocomposite-based TENGs, respectively. While the peak output voltage and current for pristine GO/EVA nanocomposites were about 1.89 V and 0.97 μA, respectively, the PD–PEI–rGO/EVA composite TENG showed electrical outputs of about 7.49 V and 4.06 μA. These values were ∼4 and ∼4.2 times higher than those of the output voltage (1.89 V) and current (0.97 μA) of pristine EVA, respectively. The higher electrical output for the PD–PEI–rGO/EVA nanocomposite TENG can be attributed to the higher surface polarity and electron-donating ability owing to the presence of the amine (from PEI) and OH groups (from DA) when rubbed with a fluoropolymer. Moreover, the embedded GO nanoplatelets in the composite can act as charge trapping sites, thereby promoting the relative dielectric property of the film, leading to an increase in the triboelectric output performance of the composite.14 To verify the feasibility of the above nanogenerator for practical uses, we connected 43 blue LEDs directly  to the output of the nanogenerator without any circuit. i.e., dancing or jumping.Next, the cyclic performance stability and time-dependent durability of the above TENG was tested, as it determines the quality and shelf-life of the device. From We reported a novel and effective approach for GO modification to produce mechanically strong EVA nanocomposites with multifunctional capability. The surface modification was carried out by a unique mussel-inspired polydopamine-assisted Michael addition reaction. This approach showed greater promise in terms of molecular level dispersion and the interface adhesion of graphene nanosheets within the EVA matrix owing to strong hydrogen bonding interactions. As a result, the achieved polymer nanocomposites showed radical improvements in the tensile strength (80%) and storage modulus (24%) even at only 1.2 wt% of graphene content, clearly demonstrated the robustness of the functionalization process. Besides the high reinforcing capability, the addition of modified GO (PD–PEI–rGO) turned the nanocomposite into an excellent triboelectric material owing to the amine-rich surfaces. As a result, the composite triboelectric nanogenerator showed outstanding electrical responses with an output voltage of 7.49 V and current 4.06 μA, thereby lighting up the 43 blue LEDs instantaneously. Such a high output voltage also implied that our device would be very effective for large-scale industrial applications. This also suggests that the performance of the device can be amplified further by increasing the graphene content as well as the degree of amine functionalization. Considering the above fascinating achievements, it can be concluded that our functionalization strategy was indeed a versatile platform for GO modification and can hopefully attract great attention from various sectors to develop other lightweight and strong composites for wider applications.Flaky graphite powders (300 mesh) were purchased from Huadong Graphite Factory . Dopamine, Trizma base and polyethylenimine  with an average molecular weight of 25 000 were purchased from Sigma Aldrich, South Korea. Ethylene vinyl acetate copolymer  was obtained from India. Polyvinylidene fluoride (PVDF) film was purchased from Starlab Scientific Co., Ltd, Korea.1 The as-synthesized GO was then thoroughly dispersed in 10 mM Tris (pH 8.5) buffer solution using a probe sonicator at 20 Hz frequency for 30 min. Next, an equal amount of dopamine (DA) and PEI (1 : 1) was added into the GO solution, and the mixture was magnetically stirred for 6 h at 50 °C. After that, the mixture was filtered by vacuum filtration and washed with large amounts of water and methanol repeatedly in order to remove any unattached DA and PEI. Then, the product was freeze-dried overnight and labelled as PD–PEI–rGO. The ‘r’ represents the partial reduction of graphene oxide.Firstly, GO was synthesized by a modified Hummers method from graphite flakes following our earlier report.Various PDA–PEI–rGO/EVA nanocomposites were prepared by solution casting followed by the melt blending process. Briefly, PD–PEI–rGO of 100, 200 and 300 mg were dispersed separately in 25 ml of toluene by ultrasonication at room temperature for 1 h. Concurrently, EVA (25 g in 100 ml) was dissolved in toluene separately. Next, the above PD–PEI–rGO dispersions were added separately into the EVA solution and mixed thoroughly with constant stirring at 100 °C for 8 h and then cast on a glass Petri dish. After complete drying in air followed by vacuum, the above three different nanocomposite films  were cut into small pieces and melt blended in a Haake mixture (MiniLab) at 145 °C to obtain the desired composites. Dicumyl peroxide  was used as a curing agent during the blending process. The extruded strips were then made into sheets (1–1.2 mm) by compression molding in a hot press at a temperature of 150 °C with a holding pressure of ∼10 MPa for 5 min. For comparative study, a GO/EVA nanocomposite was also fabricated under identical conditions.i.e., EVA nanocomposite and PVDF films, used to fabricate the device. The process of fabrication is as follows: a 1.7 cm × 1.7 cm × 1 mm piece of PD–PEI–rGO/EVA nanocomposite film was prepared. Then, the film was attached to the center of a strip of copper tape, which acted as the top electrode. The Cu tape was further attached to a PET film in order to protect the electrode from damage and as a hard supporting layer for easy handling of the devices. On the other hand, a PVDF film of the same size (but the thickness was 0.25 mm) was taken, and one side was coated with aluminum using a metal ion evaporator. This became another electrode for the device. The coated PVDF was similarly attached to a PET support. Then, the device was assembled by placing the two active surfaces face-to-face, separated by a 2 mm soft spacer and connected to the external circuit through copper wires. For comparison, a pristine EVA/PVDF TENG had also been fabricated keeping all parameters the same as earlier. It is important to note here that for the triboelectric experiment a nanocomposite of higher PD–PEI–rGO content  was used.All TENGs used in this study were vertical contact types. There were two active materials, −1 resolution. The surface elemental compositions of the above samples were determined by X-ray photoelectron spectroscopy (XPS) on a K-Alpha Thermo Scientific spectrometer with monochromatic Al Kα X-ray radiation. All XPS spectra were corrected according to the C 1s line at 284.8 eV. The Raman spectra of GO and PD–PEI–rGO were measured by an Alpha 300R WiTec confocal Raman microscope. The thermal stability of all specimens was tested using a TA Instruments TGA 2950 from 30 to 800 °C at a heating rate of 10 °C min−1 under nitrogen gas medium. The tensile tests of the EVA nanocomposites were performed at room temperature with a crosshead speed of 50 mm min−1. The storage modulus of the composites was measured by a dynamic mechanical analysis instrument (DMA Q800 TA) in the tension mode at a heating rate of 5 °C min−1. The surface morphology of the tensile-fractured samples was observed by field emission scanning electron microscopy  after coating with platinum. Triboelectric performance of the TENGs was measured as follows: the device was fixed onto a metal zig, and a 20 Hz square wave input was applied to the device from a shaker , which was controlled by a function generator (Keysight 33220A). The bottom electrode was pressed up by a shaker with 14 N force, while the top electrode was fixed onto a lab bench. The input force was measured by a force transducer (Brüel & Kjær 8230-001). The output voltage and current data were collected using a pulse analyzer (Brüel & Kjær 3560-B-030) and PC.The presence of surface functional groups of the pristine GO and modified GO powder were analyzed by Fourier transform infrared spectroscopy  spectra at a scan rate of 16 with 4 cmWe have no conflict of interest.NA-001-C9NA00142E-s001


However, conventional exfoliation fabrication methods and layer‐by‐layer transfer techniques have various limitations. The CVD synthesis of high‐quality large‐area graphene and hBN multilayer heterostructures is essential for the advancement of new physics. Herein, the authors propose an in situ CVD growth strategy for synthesizing wafer‐scale AAB‐stacked single‐crystal graphene/hBN/graphene trilayer van der Waals heterostructures. Single‐crystal CuNi(111) alloys are prepared on sapphire, followed by the pre‐dissolution of carbon atoms. Single‐crystal monolayer hBN is synthesized on a plasma‐cleaned CuNi(111) surface. Then, a single‐crystal monolayer graphene is epitaxially grown onto the hBN surface to form graphene/hBN bilayer heterostructures. A controlled decrease in the growth temperature allows the carbon atoms to precipitate out of the CuNi(111) alloy to form single‐crystal graphene at the interface between hBN and CuNi(111), thereby producing graphene/hBN/graphene trilayer van der Waals heterostructures. The stacking modes between as‐grown 2D layers are investigated through Raman spectroscopy and transmission electron microscopy. This study provides an in situ CVD approach to directly synthesize large‐scale single‐crystal low‐dimensional van der Waals heterostructures and facilitates their application in future 2D‐material‐based integrated circuits. An in situ CVD synthesis of high‐quality single‐crystal graphene/hBN/graphene trilayer van der Waals heterostructures is presented here. A single‐crystal CuNi(111) film is produced on sapphire and then subjected to carbon dissolution. Single‐crystal monolayer hBN and graphene are then synthesized. Carbon atoms diffuse to the hBN–CuNi(111) interface and form graphene. This study paves the way for future 2D‐material‐based large‐area integrated circuits. The van der Waals heterostructures consisting of graphene and hBN used in most studies were fabricated using mechanical exfoliation and layer‐by‐layer transfer techniques. The exfoliation of single or multilayer graphene and hBN from bulk materials preserve the high crystal quality and intrinsic physical properties of thin materials. However, disadvantages such as small sample size and interlayer chemical contamination limit their applications in scientific research and industrial applications. The chemical vapor deposition (CVD) synthetic technology has facilitated the production of high‐quality, large‐area, single‐crystal monolayer graphene and hBN. Many researchers have synthesized graphene and hBN heterostructures using the CVD method. Currently, graphene/hBN, hBN/graphene, and hBN/graphene/hBN have been grown on Cu substrates in situ via CVD. Although the graphene/hBN/graphene heterostructure is considered an ideal system to investigate thermoelectric transport in the cross‐plane direction and has demonstrated significant application in tunnel transistors, the in situ CVD growth of high‐quality graphene/hBN/graphene heterostructures has been rarely reported. Hence, there is an urgent need for a CVD growth method for fabricating large‐area single‐crystal graphene/hBN/graphene heterostructures to be used in both fundamental research and industrial applications.2D van der Waals heterostructures are currently regarded as promising materials owing to their special electronic structures.4, 5FigurexNi1‐x film. Raman spectroscopy and transmission electron microscopy (TEM) with selected area electron diffraction (SAED) were used to verify the crystal quality of the as‐grown graphene and hBN layers and to identify the stacking mode of the heterostructures. The proposed in situ CVD growth method can be extended to the synthesis of various multilayer graphene‐based van der Waals heterostructures.In this study, we synthesized wafer‐scale single‐crystal graphene/hBN/graphene multilayer van der Waals heterostructures with an AAB‐stacking mode via in situ CVD growth. First, to create an ideal substrate, we fabricated single‐crystal CuNi(111) films on a two‐inch sapphire wafer Figure1. Carb22.12O3(0001) wafer was treated with an acid mixture to remove scratches and residual stress by etching the surface, producing an atomically smooth surface consisting of a terrace‐and‐step structure. Then, 450‐nm‐thick Cu followed by 50‐nm‐thick Ni were deposited on the Al2O3(0001) substrate through e‐beam evaporation to form a Cu90Ni10 alloy on Al2O3. After annealing at 1050 °C for 2 h in the CVD system with flowing hydrogen (50 sccm) and argon (350 sccm)  substrate  film. Hence, the hydrogen‐argon plasma was used to remove the graphene islands, which created a clean surface of the CuNi(111) film. Subsequently, ammonia borane was heated to 80 °C and then introduced into the CVD growth chamber under Ar carrier gas flow, leading to the formation of single‐crystal hBN islands on the as‐fabricated CuNi(111)/sapphire substrate at 1050 °C  of 15.2 cm−1, indicating that as‐grown hBN is a high‐quality monolayer.By utilizing the specific solubility of carbon in the CuNi alloy,33 metC Figure . Some wh2.2Figure To decrease the influence on the pre‐grown hBN layer, we conducted the fast growth of top‐layered graphene to let the graphene film quickly cove the hBN surface as a protective layer. The SEM image showed a uniform surface with no apparent adlayers on the as‐grown graphene/hBN heterostructure  belonging to graphene, confirming the co‐existence of hBN and graphene  and the E2g (1361 cm−1) peak of hBN . The FWHM of the 2D peak of as‐grown graphene was ≈39 cm−1, indicating that the mismatch angle between graphene and hBN is <1°. Thus, from the Raman spectroscopy results, the stacking mode between the hBN layer and top‐layered graphene is regarded as AA stacking. The analysis of the electron diffraction patterns of the bilayer heterostructure allows to gain a deeper understanding of the relative orientation of the two films. Therefore, we separated the as‐fabricated graphene/hBN film from the CuNi(111)/Al2O3 substrate and transferred it onto a TEM grid to collect the SAED patterns. The SAED pattern in Figure  The SAED pattern corroborates with the Raman spectrum, indicating that as‐prepared graphene/hBN represented an AA stacking mode between layers.After growing the high‐quality hBN monolayer, we synthesized single‐crystal monolayer graphene directly onto the hBN/CuNi(111) surface to form the graphene/hBN heterostructures by re‐introducing methane into the CVD system at 1030 °C Figure3a. Thise Figure . A flat e Figure . Raman mr Figure . A typice Figure . The 2D N Figure , which i2.3 ≈1.3% between graphene and Ni(111); and ≈1.6% between graphene and hBN), under the interplay of the under‐layered single‐crystal CuNi(111) surface and upper‐layered single‐crystal hBN monolayer, the precipitated carbon atoms nucleated and epitaxially grew to form a single‐crystal monolayer graphene film at the interface, resulting in the formation of graphene/hBN/graphene trilayer van der Waals heterostructures  and 2D (2706 cm−1) signals assigned to graphene and the E2g signal associated with hBN  film gradually precipitated to the interface between CuNi(111) and hBN. To prevent the formation of BCN during the entire process, we optimized the hBN growth parameters to ensure that the pre‐grown hBN monolayer had fully covered the CuNi(111) surface. Considering the small lattice mismatches among graphene, CuNi(111), and hBN (3%–4% between graphene and Cu (111);45 ≈1. Figures . A smoot Figures . The typN Figure . The blu−1 was fitted by two Lorentzian peaks centered at ≈1352 cm−1 (D peak of graphene) and 1362 cm−1 (E2g peak of hBN) , and a higher component of carbons in the CuNi film can lead to the growth of more graphene layers at the interface, resulting in the formation of van der Waals heterostructures with multilayered graphene under the hBN film (Table The peak at ≈1359 cm) Figure . The inc  film on a sapphire wafer and subjected it to carbon dissolution to incorporate a specific concentration of carbon atoms into the CuNi(111) film. A high‐quality single‐crystal hBN monolayer was prepared on the surface of the CuNi(111) alloy after plasma cleaning. Following this, a monolayer graphene film was grown on top of hBN to form an AA‐stacked graphene/hBN heterostructure. Subsequently, a high‐quality single‐crystal graphene monolayer was formed at the interface between the hBN layer and CuNi(111) surface through a controlled decrease in the temperature of CVD growth, resulting in the formation of an AAB‐stacked graphene/hBN/graphene trilayer van der Waals heterostructure on the CuNi(111)/sapphire substrate. This study introduces a strategy for the contamination‐free in situ CVD synthesis of wafer‐scale single‐crystal graphene/hBN/graphene van der Waals heterostructures. The proposed method will provide a foundation for the development of more promising functionalized 2D materials for industrial applications.42O3(0001), 2 in., c‐plane, and double‐side polished from 11‐D Tech) was cleaned using hot acetone, isopropanol, and deionized water for 5 min. A mixed acid solution (H2SO4:H3PO4 = 3:1) was used to etch the surface at 320 °C for 30 min. The sapphire was then rinsed with deionized water and cleaned using oxygen plasma. Subsequently, Cu and Ni films were deposited on the Al2O3 (0001) wafer. The resulting CuNi/Al2O3 was loaded into the CVD system for annealing at 1050 °C under H2  and Ar  atmospheres at a pressure of 750 Torr for 2 h. After annealing, a single‐crystal CuNi (111) film was formed on the Al2O3(0001) wafer.The sapphire substrate  as a precursor, with H2 (15 sccm) and Ar (7 sccm) as the carrier gases. During the CVD growth process, the precursor was heated and maintained at 80 °C. After the growth of hBN, upper‐layered graphene was synthesized on the hBN surface in a CVD system at 1030 °C for 20 min, using a mixture of CH4  and H2 (20 sccm). After the growth of upper‐layered graphene, the chamber temperature was slowly decreased to 1000 °C over 30 min under CH4 (5 sccm) and H2 (10 sccm) gas flow. After the completion of the CVD growth process, the sample was removed from the furnace zone and quickly cooled under the same gas flow and pressure.hBN was synthesized on the CuNi(111) surface in a CVD system for 40 min at 1050 °C using ammonia borane  as a protective layer; an aqueous NaOH solution was used as the electrolyte. Upon applying a constant current with CuNi(111) as the cathode, H2 bubbles were formed at the interface between the CuNi(111) substrate and the PMMA/graphene/hBN/graphene film, leading to the detachment of the PMMA/graphene/hBN/graphene layers from the CuNi(111)/Al2O3 substrate. After rinsing with deionized water, the stacked layers were transferred to the target substrate. Eventually, PMMA was removed using hot acetone, rinsed with isopropanol, and dried in air.The as‐grown heterostructures were transferred onto a SiO2O3(0001) substrates. AFM  was used to determine the surface roughness and layer thickness. TEM images and SAED patterns were acquired using a transmission electron microscope  at an acceleration voltage of 200 kV.Raman spectra and maps were obtained by the confocal Raman spectroscopy  using 488 and 532 nm lasers. SEM  equipped with EBSD was used to characterize the surface morphologies of the CuNi alloy and the as‐grown 2D materials. XRD  patterns were obtained for the Cu(111) and CuNi(111) films on the AlThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


SSZ‐43 crystals are intergrowths of two polytypes: ≈90 % orthorhombic polytype A with ABAB stacking of the 12‐rings, and ≈10 % monoclinic polytype B with ABCABC stacking. Molecular modeling performed on the idealized Si‐SSZ‐43 structure along with empirical relationships for zeolite selectivity in boron‐ and aluminum‐containing synthesis gels were used in a combined approach to design new di‐quaternary ammonium organic structure‐directing agents (OSDAs). Experimental trials demonstrated that the new OSDAs produced SSZ‐43 over a broader range of compositions than previous mono‐quaternary OSDAs.The structure of zeolite SSZ‐43 was determined by 3D electron diffraction, synchrotron X‐ray powder diffraction, and high‐resolution transmission electron microscopy. The SSZ‐43 framework forms one‐dimensional, sinusoidal 12‐ring channels from 5 2 compositions.After two decades since its discovery, the structure of zeolite SSZ‐43 has been determined as a novel framework comprised of a primitive orthorhombic crystal system with monoclinic faulting that forms unique, 1D 12‐ring sinusoidal channels. A combination of molecular modeling and empirical relationships for zeolite selectivity was used to design two new di‐quaternary OSDAs and produce SSZ‐43 across a wide range of high SiO Standard Oil Synthetic Zeolite‐52), a small‐pore, cage‐containing, aluminosilicate zeolite with 8‐ring windows was discovered by Lee and Zones at Chevron in 2001,SFW by the Structure Commission of the International Zeolite Association) was determined in 2013.CHA topology, and signaled its potential use as an emissions abatement catalyst. Initially, commercial scale‐up of SSZ‐52 was hindered by the complexity of the original OSDA, but computational modeling efforts later identified alternative organo‐cation guest molecules to permit a more economical synthesis route.SFE) and SSZ‐31 (*STO). However, since its discovery over two decades ago, the structure of SSZ‐43 remained unsolved.Zeolites are widely used in catalytic, adsorption, and separation processes.6, 7 Tc‐axis in a sinusoidal manner, making this structure most unusual among other known 1D, large‐pore zeolites. Additionally, we report a new computationally guided synthesis route for SSZ‐43 that was developed by combining molecular modeling of the idealized SSZ‐43 framework structure with experimentally derived relationships in zeolite phase selectivity for boron‐ and aluminum‐containing synthesis gels. This approach was used to design two different di‐quaternary ammonium OSDAs, which were identified according to their stabilization energies in the idealized framework structure and further validated through laboratory experiments. Using the newly discovered OSDAs, both boron‐ and aluminum‐containing, high‐silica  SSZ‐43 zeolites could be synthesized in hydroxide (OH−) media.Developing new or modified medium‐ (10‐ring) and large‐pore (12‐ring) zeolites is often key to enabling significant advances in refining and petrochemistry because the confining void spaces and pore architectures of these frameworks are often well suited for interactions with small hydrocarbon molecules in fuels, lubricants, and petrochemicals. Thus, there is considerable interest in understanding the structural details of novel zeolites, such as SSZ‐43. However, as is often the case with synthetic zeolites, samples of SSZ‐43 are polycrystalline and prohibit structural solution by established single‐crystal X‐ray diffraction techniques. In addition, SSZ‐43 is a partially disordered material, making structural derivation challenging from powder X‐ray diffraction (PXRD) patterns alone. Fortunately, recent developments in three‐dimensional electron diffraction (3D ED) in combination with high‐resolution transmission electron microscopy (HRTEM)15, 166 cathode operating at 200 kV using Instamatic software.2 adsorption data for the calcined B‐SSZ‐43 sample (OSDA Molecule 3), are provided in Section 2 and Figures S1 and S2 of the Supporting Information. From 3D reciprocal space reconstructed from the cRED data using REDp software,a=12.51, b=29.03, c=17.30 Å. From the 2D slices, the reflection conditions can be deduced as the following: h0l: l=2n; 0kl: k=2n, which gives two possible space groups Pbc21 (No. 29) and Pbcm (No. 57). The highest centrosymmetric space group Pbcm was chosen for structure determination. Datasets from seven different crystals were merged to increase the data completeness and redundancy  by using SHELXTEdtool.Pbcm space group. The structure was further refined by SHELXLInitially, the average structure of SSZ‐43 was solved in the orthorhombic space group 461butterfly units connected via 4‐rings similar to *STO . The butterfly unit can be constructed using two mel [415262] composite building units (CBUs), one jbw [64], and two incomplete cages. As shown in Figure butterfly units along the a‐axis forms the SSZ‐43 5461 slab. The neighboring 5461 slabs are rotated by 180° around the a‐axis in the orthorhombic polytype A and shifted by 1/3a in the monoclinic polytype B, and further connected to form layers containing 12‐rings  or down (D) in a UDUUDUDUDDUD configuration. The layers are further connected to the next sheet with the same configuration via 6‐rings. Thus, one unit cell of SSZ‐43 contains two 6‐ring “honeycomb” blocks that are either shifted by ±1/2b relative to one another in the orthorhombic structure, or by ±c in the monoclinic structure as shown in Figure The framework structures of both polytype A and B of SSZ‐43 contain 14 unique T‐atoms  and can be assembled by using the 5c‐axis, which are arranged in an ABAB stacking sequence along the b‐axis . This disorder results in the appearance of sharp spots for reflections with h=3n and streaks for reflections with h≠3n.The orthorhombic SSZ‐43 framework hosts sinusoidal channels with 6.5×6.5 Å apertures along the n Figure b indicatλ=0.99995 Å) was used for further analysis. The orthorhombic unit cell parameters of a=12.324(2), b=28.435(1), c=16.898(1) Å as derived from profile fitting, were used to refine the structural model obtained from cRED data, with restraints applied to all Si−O distances (1.61 Å) and O−Si−O angles (109°). The refined atomic coordinates were then used to generate the base layer for DIFFaX simulationb‐axis for the original orthorhombic unit cell, the layer in parallel to the original ac plane was set as the base layer and the stacking vector was set as 1/2b. Then, 1/3a and 2/3a shifts were applied to generate the second and the third layers, respectively. To ensure that the desired layer stacking sequence was produced, the DIFFaX‐simulated PXRD patterns for the structurally ordered end‐members, i.e., orthorhombic polytype A (ABAB‐stacking) and monoclinic polytype B (ABCABC‐stacking), were verified by comparison to the calculated PXRD patterns from the refined ED structural models as shown in Figure θ=4.65° (d=12.32 Å) shifts to higher angles and merges with that of the (110) reflection at 2 θ=5.07° (d=11.31 Å) to form a broad peak at ≈5° when α≥0.2. Comparison of the synchrotron PXRD pattern for SSZ‐43 with the simulated data  within SSZ‐43 and the other zeolite structures considered in this study are not known. Additionally, we limited the modeling to van del Waals (vdW) interaction energies between OSDA molecules and the target zeolite framework without including other inorganic cations  or H2O molecules in the calculation. First, we determined the optimized vdW interaction energies between the six previously known OSDAs for SSZ‐43n=4 OSDA molecules per unit cell. The optimal OSDA loadings agreed with experimental results obtained by thermogravimetric analysis (TGA). As shown in Table −1 with the decahydroquinolinium‐derived organo‐cations (Molecules 4–6) being most favorable.After the structural models of the SSZ‐43 polytype A and B were derived, a molecular modeling study on OSDA‐zeolite interaction was performed to design new, energetically favorable OSDAs for this framework, and to computationally guide the experimental synthesis of borosilicate and aluminosilicate SSZ‐43 by using these identified molecules (Supporting Information Section 3). We note that pure SiOSTO, polymorph I), a one‐dimensional large‐pore zeolite, and SSZ‐35 (STF), a one‐dimensional medium‐pore zeolite with large internal cavities, are two zeolites that also crystallize from gel compositions and synthesis conditions similar to those used for SSZ‐43. From a structural standpoint, both SSZ‐43 and *STO contain the same mel [415262] composite building units, these units form the 5461butterfly units that are further connected to themselves to assemble the same building layers. The vdW interaction energies between OSDA Molecules 1–6  and SiO2/B2O3 (SBR) in Table inter‐zeolite comparisons of interaction energies for a given OSDA are not straightforward since the zeolite host framework density (FD) and the percentage of framework atoms available to participate in vdW interactions could vary between different zeolite frameworks.[STF) has the lowest FD (16.9 T×10−3 Å−3) among the three zeolites considered . Furthermore, SSZ‐35 (STF) is also the only example here where all framework atoms are exposed to the one‐dimensional channel to interact with the occluded OSDA molecules. Thus, as shown in Table 2 SSZ‐43 structure or *STO, then the modeling results in Table STO. However, neither of these structures could be produced experimentally with Molecule 8, because this OSDA is much more energetically favorable in STF so that SSZ‐35 could be formed under a broader range of synthesis conditions and gel compositions.As indicated by the modeling predictions and experimental results in Table −1 and prevents the crystallization of SSZ‐43 across a broad range of synthesis gel compositions. However, in the case of SSZ‐31, the ≈0.5 kJ (mole Si)−1 interaction energy increase between Molecules 5 and 7 is not significant enough to affect the product phase selectivity. These results demonstrate that both OSDA‐zeolite stabilization energies and synthesis gel chemistry must be considered simultaneously when designing new molecules or identifying conditions to steer selectivity toward a zeolite of interest while preventing the formation of more thermodynamically stable, undesired structures.Often a minor modification to the OSDA can significantly impact the vdW interaction energy between the guest molecule and framework host, resulting in phase selectivity changes for the crystalline products. For example, OSDA Molecules 5 and 7 , SSZ‐31 prefers to crystallize from high Si/heteroatom gels, while SSZ‐35 is generally favored at lower Si/heteroatom ratios. Thus, if OSDAs with more favorable vdW interaction energies in SSZ‐43 can be developed, then the experimental conditions to synthesize SSZ‐43 may be expanded to improve its selectivity across broader ranges of gel compositions and avoid formation of the competing *T>120 °C, autogenous pressures) during hydrothermal synthesis. Organo‐cations with two charge centers  were preferentially screened in an attempt to steer the crystallization products toward SSZ‐43 and away from *STO and STF. Since the periodicity of SSZ‐43 along the 12‐ring pore (c‐axis) is ≈16.9 Å for the orthorhombic polytype A, or approximately twice the length as monoclinic *STO  and STF , we hypothesized that longer chain di‐quaternary OSDAs could more effectively stabilize SSZ‐43 by providing a better match of size and shape between the guest molecule and host zeolite. For each simulation, the minimum vdW interaction energy between the di‐quaternary OSDA and the idealized all‐silica SSZ‐43 structure was calculated by using the molecular modeling procedure described in Section 3 of the Supporting Information, and then used to rank the OSDA candidates from most‐to‐least energetically favorable. Based on the combined modeling predictions and experimental results for Molecules 1–6 in Table −1  were excluded from the ranking. Next, the vdW interaction energies of these remaining di‐quaternary OSDA candidates in the all‐silica STF and *STO frameworks were computed. As previously discussed, the interaction energies for Molecules 1–12  and SSZ‐43 structures. So here we elected, as a starting point for the screening process, to exclude di‐quaternary OSDAs with ESTF<2×ESSZ‐43 and E*STO<ESSZ‐43 from consideration.To demonstrate this predictive capability for SSZ‐43, we initiated a search for new OSDAs by screening an internal library of existing quaternary ammonium compounds that have been used successfully to synthesize zeolites and remain stable under the harsh conditions −1, respectively, with optimal loadings of n=2 OSDAs per unit cell for both OSDA‐zeolite systems. The lowest energy configurations of Molecules A and B inside the one‐dimensional sinusoidal channels of SSZ‐43 as predicted by molecular modeling are shown in Figure Of the original ≈300 candidate OSDAs from the internal library, five di‐quaternary molecules were selected for experimental trials to synthesize B‐SSZ‐43 and Al‐SSZ‐43 according to the method described in Section 1.2 of the Supporting Information. Out of these five molecules, two OSDAs (denoted Molecule A and Molecule B) successfully produced pure SSZ‐4318H32N42+).SEM images along with the PXRD pattern of the as‐made Al‐SSZ‐43 sample synthesized from the new di‐quaternary OSDA Molecule A  indicate that the crystallites exhibit morphological and structural features similar to those in the B‐SSZ‐43 sample synthesized from the original mono‐quaternary OSDA Molecule 3 Figure a. TGA reSTO) and SSZ‐35 (STF) phases could not be avoided in either very high SAR (>300) or low SBR (<40) gels. For example, SSZ‐31 (*STO) crystallized in the presence of Molecule A from pure silica (SAR=∞) gel, but SSZ‐43 formed as Al(OH)3 was added to the synthesis gel (SAR<500). By contrast, SSZ‐43 was the dominant product in the borosilicate system with gel compositions of SBR>40, but at higher B concentrations (SBR ≈10–40) product selectivity shifted toward SSZ‐35 (STF). Similarly, Molecule B also produced B‐SSZ‐43, but required the use of seed crystals in the aluminosilicate gel to crystallize Al‐SSZ‐43 and eliminate the formation of ZSM‐12 (MTW) as a frequently observed by‐product. Interestingly, the interaction energy of Molecule 3, the original mono‐quaternary OSDA, was predicted to be ≈0.2 kJ (mole Si)−1 more favorable in SSZ‐43 than Molecule B  and physical  factors affect the kinetics of zeolite nucleation and growth. In such cases, empirical relationships for zeolite phase selectivity are useful supplements to computationally guided OSDA design.While Molecule A successfully produced SSZ‐43, formation of competing SSZ‐31  constructed from connecting 5*STO) and SSZ‐35 (STF). By using the idealized structural model of SSZ‐43, molecular modeling studies were performed to screen and identify thermodynamically favorable OSDA candidates based on the minimum vdW interaction energy between the guest molecule and host framework. Experimental trials showed that two predicted new di‐quaternary OSDAs could selectively produce SSZ‐43 across a broader range of compositions  than the previously known mono‐quaternary compounds. The strategy reported here demonstrates that consideration of both OSDA‐zeolite stabilization energies and gel chemistry are needed for rational design of new structure‐directing molecules to steer zeolite phase selectivity in systems that are known to produce multiple competing zeolite structures under similar synthesis conditions.An ongoing chemical challenge for synthesizing SSZ‐43 as an aluminosilicate in thermally stable high SAR compositions that are relevant for catalysis, adsorption, and separations is preventing the formation of competing phases, such as SSZ‐31  should be addressed to the authors.Supporting InformationClick here for additional data file.