Current electrolyticmaterials have limitation, and there is an urgent need to developnew materials showing especially high proton conductivity. Here, wereport the ultra-fast proton conduction in a novel metal–organicframework, MFM-808, which adopts an unprecedented topology and a uniquestructure consisting of two-dimensional layers of {Zr6}-clusters.By replacing the bridging formate with sulfate ligands within {Zr6}-layers, the modified MFM-808-SO4 exhibits anexceptional proton conductivity of 0.21 S·cm–1 at 85 °C and 99% relative humidity. Modeling by molecular dynamicsconfirms that proton transfer is promoted by an efficient two-dimensionalconducting network assembled by sulfate–{Zr6}-layers.MFM-808-SO4 also possesses excellent photocatalytic activityfor water splitting to produce H2, paving a new pathwayto achieve a renewable hydrogen-energy cycle.Proton-exchange membranefuel cells enable the portable utilizationof hydrogen (H In addition, H2 possessesa high gravimetric energy density of 141.8 × 106 kJ·kg–1, greater than most fuels such as gasoline (44 ×106 kJ·kg–1) at room temperature.2 Light-driven water splitting is the most sustainableand targeted approach to the production of H2 and is continuingto attract much interest as part of the roadmap to the Hydrogen Economy.3 A parallel challenge is the release of energythat is stored within H2 molecules, and proton exchangemembrane fuel cells (H2-PEMFCs) can convert this chemicalenergy to electricity with high efficiency.4 Within a PEMFC, the proton exchange membrane (PEM) is a crucialcomponent to enable high performance and efficiency for energy conversion.Nafion, a sulfonate tetrafluoroethylene-based polymer, has been usedfor decades as a commercial PEM. However, despite its excellent protonconductivity [0.05 S·cm–1 at 98% relative humidity(RH) and 25 °C],5 Nafion has inherentdrawbacks. The requirement of adequate hydration limits the operatingefficiency and temperature (<80 °C), and its amorphous structureseverely hinders the understanding of the mechanisms of proton-conductionand of associated structure–property relationships, thus restrictingthe design and development of improved PEM materials.6The achievement of global net zero targetsrelies on the replacementof fossil fuels with clean energy sources.8 To date, many crystalline MOFs with super-protonic conductivity(≥10–4 S·cm–1) havebeen reported,9 but examples of MOFs withultra-high super-protonic conductivities (≥0.1 S·cm–1) remain extremely rare.10 Our approach to the design of a MOF showing high proton conductivityis to incorporate sufficient protonic sources and sites, coupled toefficient proton-hopping pathways via accessiblehydrogen-bonding networks that enable protons to flow through thesystem rapidly. Currently, proton-conductive MOFs are based upon one-(1D) or three-dimensional (3D) networks, with the former dominatingthe field.12 MOFs with layered two-dimensional(2D) structures have also been studied for proton conduction. However,the 2D layers are assembled typically by metal nodes connected byextended and proton-insulating organic linkers, thus preventing protonsfrom transferring freely throughout the entire layer.13 Thus, proton conduction in layered MOFs has been enabledby the diffusion of guest molecules residing in the interlayer spaceto give a pseudo-2D proton-conducting network.14 Conventional 2D-structured materials, such asgraphene, graphene oxide, and boron nitride, show high proton conductivitiesin the range 10–3 to 10–1 S·cm–1, demonstrating the promise of 2D networks and topologiesfor rapid proton conduction.17Metal–organic framework (MOF) materials afforda versatileplatform for tuning both proton transport and catalysis.mfm topology with a unique layered structure comprising {Zr6}-clusters bridged by formate ligands. Upon a single-crystal-to-single-crystaltransformation, MFM-808 can be sulfated to yield MFM-808-SO4, where the formate bridges are fully replaced by sulfate ligands.The bridging sulfates within the layers of {Zr6} clustersserve as strong Brønsted acid centers, but also contribute toconstructing efficient hydrogen-bonding networks due to multiple hydrogendonor/acceptor sites. This ordered sulfate-{Zr6}-cluster-layeredstructure constitutes a 2D proton-conducting network, as revealedby molecular dynamics (MD) simulation, and exhibits an exceptionalproton conductivity of 0.21 S·cm–1 at 85 °Cand 99% RH, outperforming Nafion and most state-of-the-art MOFs.10 More interestingly, MFM-808-SO4 canalso function as an efficient photocatalyst to drive water splittingto produce H2 with an average rate for the hydrogen evolutionreaction (HER) of 670 μmol·g–1·h–1. Therefore, MFM-808-SO4 offers the potentialof combining cycles of proton transport and H2 productionwithin the same platform.Here, we report a novelZr-based MOF, MFM-808 , which shows an unprecedented 2, H4L , N,N′-dimethylformamide (DMF), and formic acid at 130 °Cfor 2 days (Scheme S2). Both single crystalsand microcrystalline powder can be isolated in pure phase , and the crystal structurewas determined by single crystal X-ray diffraction (SC-XRD). MFM-808,[Zr6O4(OH)6.5(H2O)2(DMF)(HCOO)5.5L], crystallizes in the monoclinic I2/a space group, with the linker (L4–) of low Ch2 symmetrybeing translated into the low symmetry of the resultant framework.18 The octahedral [Zr6O4(OH)4] cluster is formed via assembly of six Zr4+ ions with combinations of μ3-O and μ3-OH bridges. However, instead of forming one of the commonlyobserved 6-/8-/10-/12-fold connectivities, the [Zr6O4(OH)4] cluster in MFM-808 shows a rare five-foldconnectivity with each {Zr6} cluster connected to a neighboring{Zr6} cluster via bridging formate andto four different L4– ligands (2(5-c) binodal net with the new topology mfm (2}2{42·84·104}).20 The structure of MFM-808can also be viewed as two {Zr6} clusters bridged by formateligands to form pairs of {Zr6}2 moieties assembledinto a dense layer of {Zr6}2 pairs in the bc-plane . These layers arepillared further by L4– ligands, where each {Zr6} cluster is connected by four L4– ligandsalong the a-axis to afford a framework structureand creating porosity between layers (S9). Thepore size of MFM-808 measured crystallographically is 6–8 Å, consistent with that derivedfrom N2 sorption isotherms . Overall, the layered structure of MFM-808 is distinctto other reported Zr-based MOFs in which {Zr6} clustersare usually linked by extended organic ligands to afford 3D structureswith well-defined cages and pores.19MFM-808 was prepared by thehydrothermal reaction of a mixture of ZrOCl ligands 1B. This re phase S2–S6, anre phase S2–S6, an21 MFM-808can be activated under dynamic vacuum at 130 °C to give the desolvatedmaterial, which was reacted with chlorosulfonic acid in CH2Cl2  to give MFM-808-SO4. SC-XRD confirms MFM-808-SO4, [Zr6O4(OH)4(H2O)8.4(SO4)2.5L·(HSO4)3·(H2O)8.3], to have the sameframework topology as MFM-808 but with the bridging formates between{Zr6} clusters replaced by sulfates to afford {Zr6}–sulfate–{Zr6} bridges . Elemental analysis confirmsa sulfur content of 9.4% for MFM-808-SO4, in good agreementwith the crystallographic result (8.9%). Fourier transform infraredspectroscopy shows the presence of sulfate in MFM-808-SO4  with the symmetric and asymmetricstretching modes of sulfate observed between 1000 and 1200 cm–1.22 Thermogravimetric analysisshows an additional weight loss in the range of 500–700 °Cfor MFM-808-SO4 compared with MFM-808, corresponding tothe decomposition of sulfate . Solid-state magic angle spinning NMR spectra confirmedthe presence of protonated sulfate in MFM-808-SO4 , consistent with the analysis ofpotentiometric acid–base titration . The protonated sulfate species can act as effective sourcesof protons to benefit and enhance proton conduction in porous MOFs.24 N2 sorption isotherms reveal a notable decrease in theBrunauer–Emmett–Teller surface area on going from MFM-808(502 m2·g–1) to MFM-808-SO4 (47 m2·g–1), and the quasi-linearprofile of the isotherm of MFM-808-SO4 suggests that thepores in MFM-808-SO4 are occupied by additional sulfatespecies, with a 1:3 molar ratio of {Zr6} clusters to adsorbedsulfate species being observed .26 The hydrophilic sulfate groups in MFM-808-SO4 also lead to an improved ability to absorb water, thus facilitatingthe construction of hydrogen-bonding network and thereby enhancingfurther the proton conduction within the system .5Low connectivity often promotes flexibility inMOFs despite therigidity of organic ligands applied.4 was evaluated using alternatingcurrent (AC) impedance spectroscopy. MFM-808 showed a maximum valuefor σ of 1.74 × 10–5 S·cm–1 at 85 °C and 99% RH , which is comparable to many pristine MOFs.27 Significantly, an exceptional value for σ of 0.21S·cm–1  was observed forMFM-808-SO4 , an increase of >10,000 times compared with MFM-808, confirmingthe positive impact of sulfation of the {Zr6} cluster layers.To date, only a handful of MOFs have been reported to possess σ> 0.1 S·cm–1 (Table S2), andMFM-808-SO4 outperforms most of them as well as the benchmark,Nafion.10 Only one MOF, H2SO4@MIL-101-SO3H, shows a higher proton conductivity thanMFM-808-SO4.5 However, it ischallenging to visualize the proton-conducting pathway in this systemdue to the large cages (up to 4 nm) that are occupied by disorderedH2SO4 molecules, and its performance was limitedto below 70 °C. It is also worth noting that MFM-808-SO4 remains moderately proton-conductive at relatively low humidityat 25 °C . For example,MFM-808-SO4 exhibited a value for σ of 2.9 ×10–4 S·cm–1 at 60% RH, 25°C, thus maintaining a super-protonic level (>10–4 S·cm–1).28 Sucha good performance over a wide range of humidity is important forpractical applications.4The proton conductivity (σ)of MFM-808 and MFM-808-SOEa) for protontransfer was obtained to define the conduction mechanism in thesematerials. The value of Ea for MFM-808was calculated to be 0.46 eV , suggesting a vehicle mechanism (Ea > 0.4 eV) where protons are proposed to move via diffusion of protonated guest molecules that acted as proton carriers, e.g., water.6 In comparison,MFM-808-SO4 shows a value for Ea of 0.22 eV , which is notablylower than that for H2SO4@MIL-101-SO3H (0.39 eV).5 This indicates a Grötthussmechanism for MFM-808-SO4 involving proton conduction via hopping through a well-connected hydrogen-bonding network.14 Such a mode of conduction does not require carriermolecules and results in more rapid proton transfer in MFM-808-SO4 compared with MFM-808.31The activation energy, indicating the presence of strong Brønsted acidicsites that can act as abundant proton sources. The bridging sulfateand −OH/H2O species are adjacent to each other (O···O= ∼1.5–5 Å) within {Zr6}-layers  and form extensive hydrogen-bondingnetworks to afford efficient pathways for protons transport withinlayers (S25).Replacing coordinated formatesin MFM-808 with sulfates to give MFM-808-SO4 witha lower loading of sulfates  was prepared to give a material that is deficientin sulfate species. MFM-808-SO4-LL shows an excellent protonconductivity as high as 6.42 × 10–2 S·cm–1 at 85 °C and 99% RH, Ea = 0.18 eV . The detailed proton-conducting processes were analyzed by MD simulationswhich confirmed that protons from hydrosulfate/–OH/H2O centers were the only species that experienced diffusive movements(Supporting Film). The MD trajectories furthersuggested that such diffusive displacement of protons is confinedon and within the {Zr6} layer , contributing to further improvementin the proton conduction performance (up to 0.21 S·cm–1). This is consistent with the values for Ea obtained from impedance analysis, where MFM-808-SO4 shows a slightly higher value for Ea (0.22 eV) compared with MFM-808-SO4-LL (0.18 eV). Thisreflects the additional energy barrier originating from the requiredreorientation or translation of adsorbed sulfate species and watermolecules in the pores of MFM-808-SO4 during proton transfer.30 Nevertheless, such a barrier can be offset by the presence of abundantproton sources, which leads to an enhancement in the overall performance,as observed.31To gain further insights, a sample of MFM-808-SO6} layer 3C, leadi32 We found that MFM-808-SO4 can alsoact as a photocatalyst to produce H2via light-driven water splitting. In situ productionof H2 is one of the most appealing approaches for the developmentof PEM non-stationary fuel cells since it reduces the high costs andchallenges associated with the storage and transportation of externalH2. This approach also promotes the sustainable use ofnatural resources with zero emission at the point of use in a cycleof solar–chemical–electrical energy.36 Photocatalytic H2 evolutioncatalyzed over MFM-808-SO4 was stable under irradiationwith a total production of 16,080 μmol·g–1 at an average rate of 670 μmol·g–1·h–1 (Tables S4 and S5). Sulfation of MFM-808 to give MFM-808-SO4 triggers a desirable absorption in the visible light region due to a p−πconjugation between the lone-pair electrons of HSO4–/SO42– with aromatic phenyland/or naphthalene rings of the bridging ligands37 and also provides strong Brønsted acid sites to actas additional proton sources . As expected, MFM-808 showed a negligible H2 productivity. Moreover, MFM-808 + ClSO3H  exhibited much lower HER rates of 93.1 μmol·g–1·h–1 , Mott–Schottky analysis , luminescent quenching and time-resolvedphotoluminescence measurements , and by electrochemical experiments . The HOMO–LUMO band gap energycalculated from Tauc plots follows the order of MFM-808-SO4 (2.52 eV) < MFM-808 (3.31 eV)  was determined tobe +1.93 V for MFM-808-SO4 and +3.25 V for MFM-808, consistentwith the higher activity in photocatalytic HER for the sulfated samples.Hydrogen is an essential feed forPEMFCs to convert chemical energy into on-board electrical energy.·g–1·h–1 4A over 2t regionS30A due t regionS30A due t regionS30A due t regionS30A due mfm topology and unique{Zr6}-cluster-based layered structure have been achieved.Sulfation via single-crystal-to-single crystal transformationof MFM-808 yields MFM-808-SO4, which shows exceptionallyhigh proton conductivity of 0.21 S·cm–1 at85 °C and 99% RH with a novel 2D proton-conducting mechanism.MFM-808-SO4 can also act as a photocatalyst for water splittingto hydrogen, thus coupling its joint properties of excellent protonconduction with photocatalytic hydrogen production to unlock the developmentof a new platform of H2-PEMFCs with “solar-chemical-electric-energy-conversion”to promote the Hydrogen Economy.In summary, the synthesis and characterizationof MFM-808 showingan unprecedented


The injection of one, two, and three layers of 15 nm graphene leads to a change in the coefficient of thermal conductivity from 380 W/(m·K) down to 205.9, 179.1, and 163.6 W/(m·K), respectively. Decreasing the length of graphene layers leads to a decrease in the density of defects on which heat is dissipated. With one, two, and three layers of 8 nm graphene, the coefficient of thermal conductivity of the composite is equal to 272.6, 246.8, and 240.8 W/(m·K), appropriately. Meanwhile the introduction of an infinite graphene layer results in the growth of κ to 414.2–803.3 W/(m·K).This paper presents the results of molecular dynamic modeling, revealing that inserting confined graphene layers into copper crystal reduces the thermal conductivity of the whole composite, and the coefficient of thermal conductivity  The development of novel composites that exhibit improved mechanical properties by incorporating carbon structures and metal nanoparticles is of great importance. In recent decades, extensive research efforts have been focused on the integration of graphene with some of the most commonly used metals, such as aluminum, nickel, copper, titanium, and silver ,2,3,4.Among these metals, copper (Cu) has garnered significant attention, mainly due to its excellent thermal conductivity and cost-effectiveness . The stuFurthermore, the incorporation of graphene has been found to mitigate the thermal expansion coefficient in comparison to pure copper, a characteristic particularly advantageous for electronic applications ,8,9.An important result of this research is the suggestion of using copper–graphene composites as coatings ,11,12, tRecent research in the field of copper–graphene composites focuses on improving the stability of three-dimensional samples. The investigation actively explores the structure, strength, corrosion resistance, and tribological properties for potential applications across various industrial sectors ,17,18. HThe architecture of copper–graphene composites plays a crucial role in achieving a balance between increasing thermal conductivity through a new transport channel that covers a broad frequency range and dissipating heat at newly established interfaces. In many studies that explore how graphene enhances the thermal conductivity of metallic materials, the internal architecture of the composite is often overlooked. More specifically, the involvement of graphene in the transport process and the establishment of contact between graphene and the heat source are frequently neglected . The priThe simulation was carried out using a free package for classical molecular dynamics Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) , and The3, and the total number of atoms in the cells are around 67,000. Periodic boundary conditions were applied along all three directions. The Langevin thermostat was used to heat limited blocks of the crystal and calculate the thermal conductivity of the composite with the timestep of 0.2 fs. Thermal conductivity calculation time is equal to 1 ns. The temperatures of hot and cold blocks were 320 K and 280 K, respectively. The heat from the hot block to the cold block spread along the Z axis. The length of the blocks was equal to 1 nm. The calculation cell was a single crystal of fcc copper, with graphene layers introduced in the middle part. The linear dimensions of the calculated cells are approximately 4.7 × 4.7 × 36 nmκ is the coefficient of thermal conductivity, dQ is the energy flux, and dT/dZ is the temperature gradient .To calculate the thermal conductivity of Cu–graphene composite, the non-equilibrium method suggested by Ikeshoji and Hafskjold was used . The folN is the number of atoms, (Q1 − 2Q)/2 is the average total of input and output energy for two regions normalized by atoms, n is the number of steps, τ is the timestep, S is the XY box area, dT is the average temperature difference between two regions, and dZ is the distance between hot and cold blocks. The division by 2 should be taken into account, since energy flux goes in two directions due to periodic boundary conditions. Using these formulas, κ was calculated for all of the considered cases.In this formula, eD = −0.100 eV, eR = 2.220 Å, β = 1.700 1/Å for Cu–graphene interactions. The cutoff distance for Cu–graphene interactions was set at 6.5 Å. The choice of these parameters has previously been successfully validated in earlier research [One, two, or three layers of graphene with varying lengths were introduced into the simulation cell at specific positions. For the Cu–graphene system, it was essential to select potentials capable of accurately describing the covalent bonds within graphene, the interaction between Cu atoms and graphene, and the interactions among Cu atoms. We utilized the AIREBO potential  for grapresearch . Figure Z axis . This value coincides with the tabulated value of the thermal conductivity of copper. The size-dependent behavior of the coefficient of thermal conductivity can be attributed to what is known as ballistic conduction. Ballistic conduction pertains to the conduction of electrons in a material with minimal scattering, resulting in a notably high level of conductivity [ax + b has an error for a in the range of 4% and for b in the range of 20%.Firstly, it is important to note that the coefficient of thermal conductivity is influenced by the size of the simulation cell, as demonstrated by Formula (2). To determine the dependence, a curve of the coefficient of thermal conductivity values on the length of the simulation cell size uctivity . It shouZ axis is illustrated in Scenarios involving infinite layers of graphene were investigated, and, in line with previous cases, the thermal conductivity calculations were performed over an extended time frame of 1 ns. This extended time frame was chosen to enhance accuracy and gather statistical data. The temperature gradient along the This distribution of temperature across the simulation cell was presented to show the influence of applied simulation conditions such as the thermostat operation zone and the graphene positioning on the thermal conductivity properties of the composites.ZL was partitioned into 50 sections, and the temperature value was recorded at every time step. Following 1 ns of calculation time, the temperature was averaged. As previously stated, the coefficient of thermal conductivity (κ) for pure Cu crystal equaled 380 W/(m·K). Upon introducing one graphene layer, κ rose by 9%, reaching 414.2 W/(m·K). The coefficient of thermal conductivity of the composite with two layers of graphene is 654.6 W/(m·K). Once three layers of graphene had been inserted into the Cu crystal, its thermal conductivity increased by more than twice the amount when compared with pure Cu—resulting in a value of κ at 803.3 W/(m·K). As can be observed, an increase in the number of graphene layers within the composite resulted in a rise in the coefficient of thermal conductivity. This is due to the overlapping of the phonon spectrums of Cu and graphene. In [It is evident from the chart that the temperature aligns in all three scenarios with the temperature of pure Cu crystal. The simulation cell size hene. In , the autInterestingly, the coefficient of thermal conductivity for a single layer of graphene was determined to be 390 W/(m·K). However, when a monolayer of graphene was incorporated into copper, the composite exhibited higher thermal conductivity than the monolayer of graphene alone. In contrast, when two or three layers of graphene were added to copper, the resulting thermal conductivity of the composites was lower than that of the individual graphene layers. This is evidenced by the coefficient of thermal conductivity values of 729.3 W/(m·K) and 1128.3 W/(m·K) for two and three layers of graphene, respectively, as discussed in the previous section. Furthermore, when comparing the thermal conductivity of graphene and copper with identical geometric parameters, it was revealed that graphene had a coefficient of thermal conductivity of 4921.1 W/(m·K), nearly 13 times higher than that of pure copper crystal.Z axis. The temperature gradient in this scenario is illustrated in In the second case, the positioning of the graphene layers is oriented perpendicular to the κ) values for composites containing one, two, and three layers of graphene are 2.51, 2.18, and 1.53 W/(m·K), respectively. Graphene, aligned along the path of heat propagation, absorbs phonons at the interface and does not effectively conduct heat, instead releasing heat energy.The next step involved examining the scenarios that incorporated copper-capsulated graphene layers with lengths of 15 and 8 nm. As shown in κ = 163.6 W/(m·K). This behavior can be explained by the fact that the graphene–copper interfaces act as defects that dissipate heat when encountered. A study [As shown in  A study  delved iIn order to investigate the effect of the length of graphene layers, let us look at the behaviour of 8 nm graphene layers and compare it with the previous case. κ for the composites were expected to be similar. Indeed, the coefficient of thermal conductivity for the composite with one graphene layer was 272.6 W/(m·K), for the composite with two graphene layers, it was 246.8 W/(m·K), and for the crystal with three graphene layers, it measured 240.8 W/(m·K). As observed in the previous case with 15 nm graphene layers, thermal conductivity decreased with an increase in the number of graphene layers. The reason remained consistent—an increase in the number of graphene layers led to an increase in the number of defects. The influence of graphene layer length on composite thermal conductivity was apparent and could be explained in the same manner. κ) for Cu–graphene composites, and In Z axis. Conversely, a reduction in thermal conductivity is observed for other cases, particularly for copper-encapsulated graphene layers of 15 nm and 8 nm. Furthermore, it is important to note that all examined composites exhibit favorable thermal stability, with no significant alterations detected during the calculations.The coefficient of thermal conductivity of the composite increases only in the scenario where the graphene layers are infinite along the Z axis because this hinders heat conduction rather than facilitating it.When examining various cases with different composite configurations, it is crucial to understand how the coefficient of thermal conductivity varies with composite density. The composite density values were estimated using a mass-to-volume ratio approximation. The relationship between the heat transfer coefficient and composite density is depicted in Z axis, an increase in composite density leads to a decrease in the coefficient of thermal conductivity. This behavior can be explained as follows: when graphene is influenced by the Langevin thermostat, it heats up more rapidly than in other scenarios, resulting in an increase in the coefficient of thermal conductivity. Describing the dependence of the coefficient of thermal conductivity on composite density is challenging here, as computational cell dimensions and the operational zones of the Langevin thermostat have a significant impact on this process.As depicted in k′ is the thermal conductivity of the composite, ik is the thermal conductivity of the ith component, and iV is the volume fraction of ith component [Grk are presented in In addition to all of the above, the analytical approach for predicting the coefficient of thermal conductivity was tested for the all considered cases. The thermal conductivity of copper composites can be calculated using the following equation:omponent . The valk′ by substituting the values from Cuκ = 380 W/(m·K) into Equation (3), and these values are collected in Once again, only three of the configuration cases with the same thermal conductivity mechanism are discussed, excluding the case where graphene layers act as a barrier. It is worth noting that technical term abbreviations are explained upon first use. We can obtain the values of the coefficient of thermal conductivity κ.Upon comparing κ coefficient resulting from heat dissipation at boundaries, ultimately resulting in increased thermal conductivity. However, in scenarios where heating occurs only in a portion of the copper-bound sheet from the outset, the frequencies supported by this lattice realize the enhanced heat transfer capability of graphene, making the material less efficient. At the same time, the aforementioned heat dissipation effect at the boundaries leads to a reduction in κ compared to pure copper.In summary, there is no unified strategy or model currently available to comprehensively describe the thermal properties of metal–graphene composites, taking into account all their components and structural features. Nevertheless, the strong nonlinear interactions of graphene enhance the heat conduction efficiency in a system by introducing additional phonon modes. This effect is most pronounced in copper–diamond composites, where the high stiffness and oscillation frequencies of the carbon component lead to a significant increase in thermal conductivity . HoweverIn this work, the influence of the length and number of graphene layers on thermal conductivity of a copper–graphene composite was studied at room temperature within the use of a molecular dynamics method.The obtained results provide valuable insights into the engineering of graphene–metal composites. When analyzing composites with infinite graphene sheets, it becomes clear that efficiency initially increases when heat transfer occurs throughout the material. However, in cases where heating is confined to a portion of the copper-bounded sheet, efficiency decreases, influenced by heat dissipation at boundaries. This complexity underscores the challenges involved in comprehending the thermal characteristics of these composites.We believe that this study can contribute to a better understanding of the interaction between copper and graphene, as well as the development of copper–graphene composites with enhanced thermal conductivity properties. Future studies will focus on investigating the thermal conductivity of copper–graphene composites after undergoing severe plastic deformation, such as equal channel angular pressing or high-pressure torsion, which will allow for the assessment of a broader range of defect configurations contributing to the thermal properties of graphene.


Copper (Cu) is the electrical conductor of choice inmany categoriesof electrical wiring, with household and building installation beingthe major market of this metal. This work demonstrates the coatingof Cu wires—with diameters relevant for low-voltage (LV) applications—withgraphene. The chemical vapor deposition (CVD) coating process is rapid,safe, scalable, and industrially compatible. Graphene-coated Cu wiresdisplay good oxidation resistance and increased electrical conductivity(up to 1% immediately after coating and up to 3% after 24 months),allowing for wire diameter reduction and thus significant savingsin wire production costs. Combined spectroscopic and diffraction analysisindicates that the conductivity increase is due to a change in Cucrystallinity induced by the coating process conditions, while electricaltesting of aged wires shows that graphene plays a major role in maintainingimproved electrical performances over long periods of time. Finally,graphene coating of Cu wires using an ambient-pressure roll-to-roll(R2R) CVD reactor is demonstrated. This enables the in-line productionof graphene-coated metallic wires as required for industrial scale-up. However, copper wires easily oxidizewhen exposed to air even at room temperature, waning their electricalperformances with time in low-voltage (LV) applications and limitingtheir use in high-power electronic devices and integrated circuits.3 Therefore, nowadays, research efforts are devoted to develop effectiveprocesses and coatings to prevent oxidation and corrosion of Cu wires,thus preserving the electrical properties of the pristine metal overtime.5 Graphene represents an interesting candidatematerial for ultrathin coating of Cu wires, thanks to its extraordinarilyhigh electrical and thermal conductivity, flexibility, strength, andchemical inertness.9 Moreover, graphene’s tight structure is impermeable to gasesand liquids,11 exhibiting remarkable performanceas a protective barrier in comparison to other thin-film materials.12 A number of papers have discussed the potentialof graphene as a multifunctional coating for Cu, hindering oxidationand chemical etching15 while increasing electrical and thermal conductivity.17 Concerning Cu wires, it has been demonstrated that multilayer graphenecan be synthesized on cylindrical conductors by chemical vapor deposition(CVD),13 providing antioxidation protectionup to 350 °C and corrosion inhibition in ammonium persulfatesolution.19 Furthermore, graphene-coated (Gr-coated)Cu wires with diameter ≅ 0.1 mm displayed improved surfaceheat dissipation, electrical conductivity, and thermal stability upto 450 °C.19 However, to date, no work hasdemonstrated an industrially compatible approach for this process, i.e., performing graphene coating of cables complying withthe following requirements: (i) process gases below the lower explosivelimit (LEL), (ii) temperatures below 1000 °C, and (iii) ambientpressure. Addressing all of these points would pave the way to thein-line CVD Gr coating of metallic wires by an ambient-pressure roll-to-roll(R2R) CVD system and is the object of our work. Moreover, we addressthe coating of LV wires, which are expected to generate the highestrevenue in the copper wire and cable market in the 2021–2030timeframe.20The applicative realmof copper (Cu) is enormous: it is utilizedin indoor and outdoor constructions, tools, machinery, and portabledevices, both for civil and industrial uses. In particular, copperwires are commonly employed in industrial wiring and interconnectiontechnology,i.e., 1.37 and 1.74mm) can be effectively coated with graphene by a scalable and industriallycompatible process: at a temperature below 1000 °C, at ambientpressure, and with rapid growth in a nonexplosive atmosphere. TheGr-coated wires, characterized by electrical measurements and microscopicand spectroscopic techniques, display higher electrical conductivityand improved esthetics than uncoated wires, allowing for a significantsaving in the Cu market. Aging of Gr-coated wires is investigated,and in-depth studies to correlate the electrical performances andthe microstructural changes after the coating are provided. It isfound that the graphene growth process induces an improvement in thecrystallinity of Cu wires, which is responsible for the augmentedconductivity, and that graphene coating plays a major role in maintainingthis improved conductivity over time. Finally, the production of Gr-coatedCu wires with an open-end R2R pilot CVD system is demonstrated. Implementingin-line graphene coating of metallic wires in an industrial settingis required.Indeed, this work demonstratesthat wires with diameters technologicallyrelevant for LV applications  pristine Cu wires (reference); (ii) Gr-coated Cu wires: annealedat a high temperature  and then subjected to the graphene growth process;and (iii) only annealed Cu wires ).Industrial LVCu wires were provided by Baldassari Cavi, a manufacturer of Cu wiresoperating in the European market.22 . The coils were bound with thin, flexible copper wires(diameter 250 μm) to prevent them from unwrapping and thus touchingthe inner walls of the reactors during heating and cooling steps.Before the growth process, argon (Ar) gas was flushed to purge thereactor from air.To facilitate the industrial translation of theprocess, the wires were used as-received for all tests carried out. Copper wires 2.5 m in lengthwere taken from the bundle and arranged in a coil shape, in such away that the coil could fit inside a 4 in. BM Pro AIXTRON CVD reactorwhere wire treatment was performedFigure S2. Cu wires subjected only to thermalannealing were placed in the reactor and heated at 980 °C for10 min in a flow of Ar at 2000 sccm. In the case of Gr-coated samples,after the initial annealing of 10 min, 2 sccm of methane (CH4) were flushed for 5 s in hydrogen (H2) and Ar  at 980 °C to grow graphene. After eitherannealing or growth, the samples were cooled down in Ar flow. Processedcopper wires were taken out from the reactor once the temperaturereached 120 °C. The process conditions were transferred fromthe batch reactor to the R2R CVD system.The optimized process was carried out between900 and 1000 °Cunder an Ar pressure of 750–800 mbar. Details of the temperatureprofile and conditions employed in the CVD process are reported in 2.2–2. The numberof graphene layers was determined by analyzing the I2D/IG ratio, where I2D and IG are theintensities of the 2D and G peaks in the Raman spectrum, respectively.23Raman spectroscopywas performed to assess the coverage, quality, and number of graphenelayers. A Renishaw InVia system, equipped with a 473 nm blue laser,a 100× objective, and an 1800 l/mm grating, was used. Spatiallyresolved Raman maps were obtained with a 1 μm step while irradiatingthe samples with 22.3 mJ μmThe surface morphologies of the as-grownand aged wires were investigated by scanning electron microscopy , operating in Inlens Signal mode at 5 kV voltage and120 pA current. Additionally, atomic force microscopy (AFM) was performedwith a Bruker Dimension Icon in standard tapping mode. Optical microscopy(Zeiss Axioscope7 equipped with Axiocam 208 color) was employed torecord bright-filed micrographs and assess Cu oxidation.2 flow, employingthe same ratio of H2/Ar as in the growth process. XRD measurementswere carried out on a STOE Stadi P diffractometer equipped with CuKα1 radiation (λ = 1.5406 Å) and a Ge(111)Johansson monochromator from STOE & Cie. The samples (2–3cm long wire segments) were mounted on a goniometer head and opticallyaligned with the diffractometer’s center of rotation and keptunder spinning during the measurements. The diffracted intensitiesas a function of the scattering angle, 2θ, were acquired inthe range 84–127° by a MYTHEN2 1 K detector from Dectris.The profiles of the Cu(311), (222) and (400) peaks were analyzed individually,by fitting each of them with a pseudo-Voigt function. The dependenceof the peak full- width at half-maximum (FWHM) on the sample treatmentconditions was qualitatively evaluated for each of the three peakfamilies and for each of the two wire thicknesses. Due to the bulknature of the samples and the peculiar experimental geometry, theposition and the intensity of the peaks do not directly provide anycrystallographic information, but the variation of the normalizedFWHM with respect to the pristine material is indicative of the variationin the crystallite strain.24Forthe X-ray diffraction (XRD) experiments, short wires (2–3cm long segments) were processed with the same parameters describedin LR–1A–1, where R is the resistance of the cable, A is its cross-sectionalarea defined by design, and L is the distance betweenthe sensing probes (2 m for our measurements).Electricalresistivity measurements on the Cu samples were performedin the DC configuration using a Keithley 2450 source meter. In orderto minimize measurement errors, we performed all of the electricalmeasurements in a four-probe configuration. Such a setting reducesthe variation of the contact resistance between the probe and themeasurement clamp due to surface oxidation. Each set of samples weretested by putting the source probe at the end of the wires, whilethe sensing probes were put at exactly 2 m apart through a coupleof crocodile clips. The resistance was then measured by applying aconstant DC current of 10 mA and measuring the voltage drop betweenthe two sensing tips. Performing measurements in the DC configurationallows us to neglect the skin effect. All measurement were performedat room temperature.” Conductivity was calculated as follows:σ = i.e., Baldassari Cavi) ina commercial setup that allows measurements at controlled temperature,see Figure S3 of the Supporting Information.A 2.5 m long coiled copper wire was kept inside the water maintainedat 20 °C and firmly fixed at both ends so that there was no bendingor loops. A couple of wedge holders were used as electrical sensors,while the wire holder at the end of the line provided the source current,with the distance between them that could be precisely tuned. In thisway, it was possible to measure the resistivity of pristine and graphene-graftedwires avoiding any variation arising from the copper temperature orcontact resistance and reducing the uncertainty on the wire length.In addition, before the resistivity was measured, a small portionof the wire was cut and measured to check the possible changes indiameter before and after the process. For the electrical measurementsreported, the average electrical conductivity was obtained from measuringseven samples of each type. The oxidation experiments were conductedwithin a climate chamber (Espec SH-262 Benchtop Temperature and HumidityChamber) at temperatures between 40 and 90 °C, humidity levelsbetween 80 and 100%, and times between 20 s and 24 h.Also, additionalelectrical resistivity measurements were performedat industrial premises . Notably, anddifferent from what is reported in the literature until now, the optimizedprocess shown herein has a volume percentage of explosive gases, whichcomplies with LEL requirements. Indeed, H2 and CH4 used during the process were at 1 and 0.1% concentrations, respectively,and this is significantly below the LEL . This allows this processto operate in safe conditions, and this can be easily implementedin an industrial setting (see the SI).Optimized process temperature and pressure were 980 °C and 780mbar, respectively. Notably, no wire pretreatment was necessary, besidesreactor annealing, prior to graphene growth. This is also relevantas most of the work reported to date requires some form of chemicalpretreatment, thus introducing additional complexity and significantcost to the implementation of this graphene coating process at industrialpremises. Table S1 presents a comparisonbetween this work and those present in the literature with respectto sample chemical pretreatment, process temperature, and gas LEL.Preliminary studies were performed to identifythe process conditions to obtain graphene-coated Cu wires while satisfyingthe following requirements: (i) process gases below the LEL, (ii)temperatures below 1000 °C, and (iii) ambient pressure. A summaryof such preliminary investigations is reported in the Supporting Information(SI) (2), respectively. SEM micrographs of the Gr-coatedwires display instead a smoother wire surface decorated with particlesof ∼160 nm size. We verified that the presence of particlescould be avoided by introducing a wire pretreatment step, i.e., Cuelectropolishing25 . AFM micrographs reveal the presence of atomicterraces, typically observed after the growth of graphene with goodcrystallinity and thickness homogeneity.28 The RMS roughness values measuredfrom 1 μm2 micrographs for the 1.37 and 1.74 mm wiresare ∼3.9 and 4.6 nm, respectively.To study in detail the surface morphology, SEMand AFM characterizationsfor all the samples were performed. –1) and 2D bands (2720 cm–1) could be visualized.The average I2D/IG ratios over an area of 30 × 30 μm2 werefound to be ∼0.9 and ∼0.80 for 1.37 and 1.74 mm diameters,respectively /I(G) indicated that the average number of layers is 2–3.30 Furthermore, the as-grown samples exhibited a negligible D peak.The electrical conductivity of Gr-coated wiresmeasured at controlledtemperature with a commercial system at industrial premises is reportedin 3.2To assessthe performances of aged Cu wires, a complete characterization ofthe samples by means of optical microscopy, Raman spectroscopy, andelectrical measurements was carried out. The effect of aging on thechemical properties was investigated at different time points, from6 to 24 months after the CVD process.Figure S8 confirms a similar trend for both kindsof wires also at intermediate aging times. It is well known that Cuwires tend to become darker over time: this is usually thought asan indication of “poor quality” and causes significantsale returns, which negatively affects Cu wire manufacturers and retailers.Graphene coating offers a viable solution to this issue, providingan esthetic advantage.xO) range (between150 and 800 cm–1),36 on both the green and bright areas . It is to be noted that defectivegraphene (even 2/3 layer thick) is not effective in preserving Cuwires from oxidation and might even be counterproductive, owing togalvanic coupling, as previously reported in refs.35 The electrical properties of the wires at room temperature werealso investigated for different aging times by recording their resistanceat 10 mA. The relative improvement of the electrical conductivity,calculated with respect to the pristine Cu wires at the same agingstage, is reported in 33 Furthermore, the graphene coating was foundto be effective in preserving the wires from significant oxidationeven at high temperatures (up to 90 °C) and humidity levels (upto 100%) .Optical microscopy analysis might apparently contradictthe resistanceto oxidation of Gr-coated wires since oxidation spots (observed asgreen areas) can be found on both pristine and Gr-coated wires  and improvedconductivity at t = 0, it was found that the conductivityimprovement over time is lower than that measured for Gr-coated wires. With the aim of further investigatingqualitative microstructural differences in pristine, annealed, andGr-coated wires, XRD measurements were performed. The qualitativeassessment of the XRD peaks further clarifies the role of annealingand graphene growth steps in the conductivity of copper. The histogramsin Figure S13). The annealed wires display narrower FWHM compared tothe pristine Cu wires, and further FWHM reduction is observed uponGr growth. The FWHM is sensitive to the variation in microstructure and stress–strainaccumulation in the material.37 Duringthe annealing and recovery process, the improved atomic diffusionat high temperatures enables the release of the stored strain energyof the extruded wires. The decrease of XRD peak broadening is suggestiveof a decrease of crystallite strain, which can explain the enhancedconductivity of Cu after annealing. The growth step implies a remarkabledecrease in peak width regardless of the annealing time . This observation suggests that theconditions used for graphene coating relieve crystallite strain muchmore effectively than annealing in Ar does.From the analyses reported above,it appears that Gr-coated wires have the following advantages withrespect to pristine ones: (i) increased electrical conductivity attime zero and over time and (ii) oxidation protection. One can arguethat the increase in electrical conductivity could be induced by microstructuralchanges in the Cu wires due to processing conditions rather than fromthe presence of the thin layer of graphene itself. Indeed, on millimeter-sizedwires, it is quite unlikely that a thin layer of graphene could havesuch a remarkable effect on the electrical properties, although suchan explanation has been provided for thinner wires.pearance S11 and iiressee 3b and 4bpearance S11 and i2/CH4, the effect of hydrogen on the microstructureof copper was investigated, analyzing samples annealed in Ar and thenprocessed in H2 flow. The details of the samples and processconditions are reported in Table S2 ofthe SI. As demonstrated by the histograms reported in The aforementioned microstructural observations,as well as theincreased malleability and smoothness, confirm that the enhanced conductivityis due to a more radical and deep change in the bulk copper crystallinityoccurring during the growth treatment rather than to the presenceof graphene itself. Since the growth step employs a mixture of HFigure S14 and Table S2), which further confirm that high-temperature H2 treatment positively affects Cu crystallinity.38 In conclusion, we can identify the hydrogengas present in the CVD process during graphene growth as the mainplayer in the improvement of Cu crystallinity and the consequent enhancedelectrical properties; however, the structural, chemical, and electricalmeasurements performed for the different wires indicate that grapheneis necessary for maintaining enhanced electrical properties over time.Additional XRD measurements were performedfor different annealingand hydrogen treatment times wires. Specifically, the conductivity is 1% higher than that of pristinewires immediately after graphene coating and 3% higher after 24 months.Structural analyses performed via XRD indicate that the exposure tohigh temperatures and the presence of hydrogen during graphene growthcause an increase in Cu crystallinity, which is a reasonable explanationfor the observed increase in electrical conductivity. Combined electricaland chemical characterizations show that graphene efficiently actsas a barrier against oxidation , which is beneficial to preserve the augmented conductivityin time. The reported increase in electrical conductivity potentiallyallows for a reduction in wire diameter with consequent savings inwire production costs. Building on such promising premises, we demonstratethat the developed process can be adopted in a R2R CVD reactor forin-line coating of metallic wires, which builds a road towards therealistic translation of the graphene coating technology in industrialsettings. The extension of such coating technology also to flexibleCu cables and wires adopted in automotive and aerospace industriescould lead to a significant decrease in the overall amount of Cu weight,leading to lighter vehicles with a lower impact on the environment.


Analysis of 1028 gas samples taken over a 6-year period (2008–2013) reveals that dimethyl sulphide ((CH3)2S) is the major odour active compound present in the mine, being detected on 679 occasions throughout the mine, while hydrogen sulphide (H2S) and sulphur dioxide (SO2) were detected 5 and 26 times. Analysis of gas samples has shown that main DMS sources in the mine are coal extraction locations at longwall faces and development headings and that DMS is releasing during transport from main coal transport system. The dispersion simulations of odour sources in the mine have shown that the concentrations of DMS at median levels can represent relatively modest odour nuisance. While at peak levels, the concentration of DMS remained sufficiently high to create an odour problem both in the mine and on the surface. Overall, dispersion simulations have shown that ventilation regulation on its own is not sufficient as an odour abatement measure.Underground coal extraction at Coal Mine Velenje occasionally gives rise to odour complaints from local residents. This manuscript describes a robust quantification of odorous emissions of mine sources and a model-based analysis aimed to establish a better understanding of the sources, concentrations, dispersion, and possible control of odorous compounds during coal extraction process. Major odour sources during underground mining are released volatile sulphur compounds from coal seam that have characteristic malodours at extremely low concentrations at micrograms per cubic metre (μg/m It mines the largest Slovenian lignite deposit, which is one of the thickest known coal seams in the world. The seam is bowl shaped, 8.5 km in length, and 1.5–2.5 km wide with an average depth of 300 m (200–600-m deep) and extends almost under the entire Šaleška Valley  and sulphur dioxide (SO2) are less significant. The odour detection thresholds2 2.32 mg/m3, H2S 0.58 μg/m3, and DMS 7.75 μg/m3  and 20 μg/m3 (averaged over 1 hour). At selected sites, H2S concentrations did not exceed 20 μg/m3 in 1-h air samples and 5 μg/m3 in 5-h air samples. Maximal modelled 1-h H2S concentration of 10 × 10 km2 area was 1.91 μg/m3. While there were no exceedances of health hazard H2S concentrations, there were regular complains of unpleasant sensation of smell from nearby settlements. According to the data obtained from the Ministry of Environment in 2013, as much as 1323 air pollution complaints were recorded in Poland and 65.7% referred to odour.For the assessment of potential health hazard due to the H3).The literature research since 2011 point out that there are almost no published studies exist of DMS emissions from mining activities. Only published work referring DMS to mining activities is from oil sand mine operations in Fort McKay area in Alberta (Canada) and from those performed by CMV. In the air quality investigation of 30-km radius around Fort McKay of fife year monitoring period was performed due to the countless environmental complaints regarding oil sand mining activity in the area AER, . During 2, and DMS) from coal stockpiles . The DMS concentrations fell to less than 2.58 mg/m3 within a few days as it is only released from freshly loaded coal. The measured DMS concentration levels in the mine air, which was sampled once a week for 15 consecutive weeks in the return airway of a longwall face during coal production, ranged from 55.47 to 128.48 mg/m3. During a series of in situ coal desorption tests made in 1998 and 1999 , while H2S was < 1.42 mg/m3.The only published studies referring to DMS emissions from coal mining activities are those performed on coal from Velenje Coal Mine of gaseous sulphur emissions 2S2) can be from Kraft pulp mills  that were identified by both analysis used in the study (GCSCD and GC-MS). The maximum DMS value was 4.53 × 103 , and estimated odorous emissions of mine sources in order to establish a better understanding of the sources, dispersion, and ventilation based control options to reduce the presence of odour active compounds released during the coal extraction process.As the first step in this study, the long-term monthly monitoring data of gas concentrations in the mine atmosphere were analysed in order to determine the main odorants in the mine, their source, and to estimate emissions.4, CO2, DMS, H2S, SO2, O2, CO, H2, NO, NO2, and N2.Monthly chemical analysis of mine gases is carried out to control gas concentrations in mine air and includes the following gases: CH2 content of the mine gas is the difference between the sum of the monitored gases and from 100% . The concentration of CH4, CO2, DMS, and H2S was determined using gas chromatography. The test method PM 3.01 was used for CH4, CO2 (GC—FID), while the test method PM 3.02 was used to determine H2S and DMS (GC—FPD) . Oxygen and CO concentrations were determined using the PM 3.03 test method, while the remainder were determined using the PM 3.04 test method. All three methods were developed by Erico—since 2017 is named Eurofins Erico  and peak sources (97.5th percentile).Additionally, the odour activity values (OAV) were calculated considering characteristic concentrations and ODT , is numerically equal to the dilution factor necessary to reach the odour threshold that is the minimum concentration perceived by 50% of population. According to European standardisation, 1 OU/m3 is defined as the amount of odorant that, when evaporated into 1 m3 of gas air at standard conditions, causes a physiological response from a panel (detection threshold) equivalent to that of n-butanol (reference gas) evaporated into 1 m3 of neutral gas . The software allows 3D graphical representation, simulated paths and concentrations of smoke, dust, diesel particles or gas for planning of emergency situations, short and long-term planning of ventilation, and the simulation of gas and aerosol concentrations . In the model, fixed air flows were used for the upcast ventilation shafts (ventilation station stations), in the airways of the auxiliary ventilators and in the ventilation boreholes . The model does not consider natural ventilation and compressible flows, which only have a significant effect when simulating mines deeper than 500 m , cross-section, airway type, and total resistance. Other data included the average surface temperatures, both dry (10 °C) and wet (7 °C), together with temperature and atmospheric pressure (985 mBar). The network air density was calculated from the average monthly temperatures and pressures  from the ventilation stations were calculated by multiplying the modelled odour concentrations (OU/m3) and airflow rate (m3/s).Odour emission rates  is rarely detected. Levels of SO2 throughout the mine exceeded the limit of detection on only 26 occasions , while H2S was only detected 5 times (2.41–13.63 mg/m3).Over a 6-year period (2008/1–2013/12), 1028 point measurements were taken during mine operations. The monitoring sites were selected systematically so that the return airways of all production and development worksites and all main return airways were included. Under normal working conditions at the mine, H3 (levels above 129 mg/m3 were recorded as > 129 mg/m3). Out of all DMS detections, 116 times out from 163 measurements were detected on longwall faces, 262 times out of 398 measurements on development headings, and 30 times out of 72 measurements on main coal transport. The detection frequency shows that DMS is releasing during coal extraction process  and DMS detection at main coal transport shows that DMS is released by desorption processes as the coal is being transported from the mine, similar to desorption from the coal in the stockpiles  due to the very low DMS’s ODT even while the DMS concentrations are at trace levels. Even lower ODT concentration as at DMS, resulted the OAV value of HLongwall faces and development headings as odour sources are regarding ventilation and dispersion relatively simple if not considering the variability of production intensity and amount of DMS presence in the coal. While the main coal transport system of six successive conveyers of total length 2.6 km was ventilated with six intakes of fresh air at junctions and connection to the surface Fig.  and, six3 and average airflow rate 71.8 m3/s than is 6297 mg/s and is potentially the biggest DMS source versus longwall faces (4569 mg/s) and development headings (944 mg/s). The division of whole source in the model at leakages from L1 to L6 was 3.5%, 1.8%, 6.1%, 6.7%, 6.7%, and 9.7%. Locations of leakages are marked on Fig. For the main coal transport source in the model was considered that DMS is releasing at constant release rate from the constant mass flow of coal through the whole length. The source in the model was divided to each individual part of main coal transport airways accordingly to their lengths. Each individual part represented in the model as a partial source of DMS. The simulation results showed that 34.5% of main coal transport source was dispersed to the ventilation station Pesje and 65.5% was dispersed to the ventilation station Šoštanj which was detected with monthly measurements. Considering the whole main coal transport DMS emission rate at maximum concentration 87.7 mg/mThe odour model is based on DMS emissions. The model is considered inert since it assumes that all the sources of DMS do not decay over time.3) radicals and ozone (O3) and nitrogen dioxide (NO2)  and nitrate  times of DMS from the sources to the surface at operational air flowrate as of October 2021 showed that travelling times from longwall faces were between 556 and 750 s, from development headings were between 750 and 1836 s, and from main coal transport were between 521 and 1923 s. The longest travelling time 7409 s or 2.1 hours was from the main coal transport at simulation where the main fan blades at station Šoštanj was set on −10° (minimum air flowrate) and at station Pesje was set on +2°. The extreme travelling time is due to the changed airflow directions in some airways and dispersion through station Pesje instead of station Šoštanj as normal.Based on the cases described above and modelled travelling times, any decay mechanisms of DMS were not considered in the model. The identified odour sources were the longwall faces K.-130/B and K.-65/A, road building faces 4, 6, 7, 8, 11, and 13 and the main coal transport system. In the model, sources are represented as point sources for each source, except at main coal transport, where the whole source in the model represents 7 point sources at return airway of main coal transport and at 6 leakages . The monitoring locations from 1 to 50 and ventilation stations Šoštanj (VSS) and Pesje (VSP) in the model  and from Pesje with (at odour concentration of 6059 OU/m3 and an airflow rate of 153.3 m3/s) 928,558 OU.m3/s are likely to lead to odour complaints. If considered scenario with only one longwall face at peak levels, the emission rate would be 580.242 UO.m3/s. Figure In comparison, the odour emission modelling of newly planned ventilation shaft at the Illawarra coal mine, NSW, Australia  at CMV’s ventilation stations were conducted. The monitored odour concentration levels were similar as modelled levels. Four separate odour concentration measurements at ventilation stations (NLHEF, 3, and on 26 November 2007, three measurements (NIPH, 3.The odour concentration estimation of mine air is based on the DMS concentrations and its odour detection threshold. Simulation results show odour concentrations at ventilations stations between 672 and 7790 OU/ms NLHEF,  in 2016 ts NIPH,  showed oThere is almost no information concerning the fugitive emissions of DMS and odours in general from underground coal mining activities.In this paper, this was addressed by describing and quantifying a dispersion of odours gases released from sources of CMV by focusing on analysis of gases monthly measurements in the mine and simulations of characteristic emissions of odorous compounds with mine ventilation model constructed in Ventsim™.This research, based on the analysis of monthly gas measurements, confirmed DMS as a major potential odorant in the VCM released during coal extraction process and during the transport to the surface from identified and quantified mine odour sources: longwall faces, development headings, and main coal transportThe dispersion simulations of odour sources based on DMS concentrations in the mine show that median emissions represent relatively modest odour nuisance. While during peak emissions in the exit airways, odour is potentially high to be disturbing, and on the surface at the ventilation stations would be subject to odour complaints from the local residents. Simulating to additionally reduce odour levels with increasing air flowrate with the regulation of main fans showed that it is not an effective measure for mitigating odorous emissions, while measures by reducing coal production would impose severe economic penalties.Since DMS is not regularly monitored in mines and levels are significantly varying due to its content and distribution in the coal, releasing mechanisms, mine ventilation design, and varying production intensity during the coal extraction process, the future work will focus on real-time monitoring of DMS levels and study of its correlations to coal extraction process to better understand and more accurately estimate odorous emissions from specific work phases of coal extractions process.The DMS content in the seam is related to the petrographic heterogeneity of the coal; future research will involve investigating the coal desorption characteristics of DMS from coal.In addition, to effectively address the odour issue at the VCM, especially in relation to fugitive odour emissions at the surface and for the design of technical measures for odour control, monitoring, and dispersion modelling of odour sources on the surface are necessary from hereafter.However, underground coal mines are not widely recognised as an odour nuisance, and the development of technical abatement solutions to control odour from coalmining operations, especially given the large volume of ventilated air produced by the mine, will need more recognition of the problem and more support for its solving.


Dielectric measurements reveal that the environmental moisture has an obvious influence on the dielectric properties of the samples. The best humidity response was found in a sample with the doping level of x = 0.005. This sample was therefore selected as a model sample to further investigate its humidity properties. In doing so, nanosized particles of Hf0.995(In0.5Nb0.5)0.005O2 were fabricated via a hydrothermal method and the humidity sensing properties of this material were studied in the relative humidity range of 11–94% based on impedance sensor. Our results show that the material exhibits a large impedance change of nearly four orders of magnitude over the tested humidity range. It was argued that the humidity-sensing properties were related to the defects created by doping, which improves the adsorption capacity for water molecules.(In+Nb) co-doped HfO The ta0.5NbO3 ,7. The s2 has become a research hotspot in the microelectronics industry in recent years [2 are of vital importance. In addition, HfO2 is one of the few dioxides with both ferroelectric properties and a large band gap of 5.7 eV [2 system [2 [2 [2 ceramics. This motivates us to investigate the dielectric properties of (In+Nb) co-doped HfO2. In addition, the morphology and structure over a humidity sensing material also play an important role in its humidity performance. Compared with micro-sized bulk materials, materials with nano-sized structure can provide more active sites for adsorbing water molecules, thereby greatly improving humidity sensing properties. To our surprise, (In+Nb) co-doped HfO2 ceramics show excellent humidity properties instead of colossal dielectric behavior.As a promising high-k material, HfOnt years . It had nt years ,11,12,13nt years ,15,16. Ff 5.7 eV . Currentf 5.7 eV  and has 2 system ,21,22,232 system ,27,28,29ystem [2 , (In+Nb)x1-(In0.5Nb0.5)xO2  ceramics were successfully prepared via a solid-state reaction method. The sample of Hfx1-(In0.5Nb0.5)xO2 (x = 0.005) shows the largest response and a large impedance change of nearly four orders of magnitude. The humidity sensing properties can be attributed to the dual doping-induced defects, which act as active sites for water absorption. We, herein, firstly report the humidity properties and the dielectric properties of (In+Nb) co-doped HfO2 ceramics will be reported in an ensuing paper elsewhere.Herein, the (In+Nb) co-doped Hfx1-(In0.5Nb0.5)xO2  were prepared via a solid-state reaction method in order to find out which doping level leads to the best humidity sensing properties. HfO2 (≥99.99%), Nb2O5 (≥99.99%), and In2O3 (≥99.99%) were used as starting materials. These powders were weighed according to stoichiometric compositions and were thoroughly mixed via ball milling for 12 h. The mixtures were calcined at 1473 K for 10 h. Then, the mixtures were ball milled again. The resulting powders were pressed into pellets with an average thickness of 0.80 mm using polyvinyl alcohol (PVA) as a binder. Finally, these pellets were sintered at 1673 K for 6 h. To test the humidity properties, copper wires were glued on both sides of the sintered pellets as electrodes. The results shown in x = 0.005 shows the best humidity properties. Since the humidity properties strongly depend on sample surface, materials with large specific surface area (SSA) are more conducive to the humidity properties. The sample HINO-0.005 was, therefore, selected to be further fabricated using a hydrothermal method in order to increase its SSA values. The flow diagram is shown in 4 (99.9%), 0.0094 g InN3O9 (99.99%), and 0.0085 g NbCl5 (99%) were dissolved into a beaker containing 250 mL deionized water to form solution A. Secondly, 30 g NaOH was dissolved into another beaker containing 250 mL deionized water to form solution B. Next, 250 mL of solution A was added into solution B under magnetic stirring for 20 min. Thirdly, the mixed solution was transferred to a stainless-steel autoclave lined with polytetrafluoroethylene and heated at 393 K for 24 h. Finally, the obtained sample was repeatedly washed and centrifuged several times and dried in an oven at 323 K overnight.In this work, both solid phase and wet chemical methods were used to fabricate the samples. First, Hf2O3 substrate covered with Au interdigital electrodes. Finally, the two copper wires were glued on the Au interdigital electrode with silver paste and dried at 373 K for 16 min.The humidity sensor was fabricated via the aerosol deposition method using a spray gun  with a diameter of 0.2 mm. Firstly, the HINO-0.005 powder was mixed with 10 mL absolute ethanol solution and sonicated for several minutes to form uniform paste. Secondly, 10 mL of slurry was uniformly sprayed on Al2, Mg(NO3)2, NaCl, KCl, and KNO3 salt solutions, which yield relative humidity (RH) levels of 11, 33, 54, 75, 85, and 94%, respectively, at room temperature, as shown in The phase structure and microstructure of the samples were tested by X-ray diffraction  and scanning electron microscope  equipped with energy-dispersive spectroscopy (EDS), respectively. The humidity sensing properties were measured with a Hioki 3532-50 LCR HiTester  precision impedance analyzer with different frequencies. The amplitude of the AC signal is 100 mV. Different humidity environments were provided by supersaturated LiCl, MgCl0.5Nb0.5) concentration gradually increases from x = 0 to 0.1, first, the average grain size of the ceramics gradually decreases from 0.32 to 0.2 μm, then it gradually increases from 0.2 to 0.5 μm, indicating that the (In0.5Nb0.5) doping in the HfO2 matrix can effectively align grain growth. The average grain sizes were found to be 0.32, 0.20, 0.38, and 0.50 μm for HINO-0, 0.005, 0.05, and 0.1, respectively.7 Ω @11%RH to 2.955 × 105 Ω @94%RH found from the curve recorded with 100 Hz. Therefore, the sample was selected as a model sample. The hydrothermal method was used to prepare the sample in order to reduce its particle size to nanoscale. Before doing so, ferroelectric properties of this sample were examined as ferroelectric properties were frequently reported in slightly doped HfO2 film [The humidity properties of the ceramic samples were displayed in fO2 film ,35,36,37fO2 film ,40,41,42An XRD pattern of the HINO-0.005 sample prepared via the hydrothermal method is shown in 2 lattice, we performed elemental mapping of In, Nb, Hf, and O as shown in 2.To demonstrate that In and Nb elements are doped into the HfO2 exhibits obvious humidity sensitivity.The humidity sensing response is calculated using the following relation ,44:(1)S=des and Zads and hysteresis values of the HINO-0.005-based sensor in the range of 11–94%RH. The sensor shows small hysteresis value in various humidity environments.The hysteretic behavior of the sensor is evaluated in terms of impedance changes during adsorption and desorption processes. In all humidity environments, the sensor was kept for 5 min and then the changes in impedance were recorded; the results are shown in The repetitive behavior of the sensor is shown in It has been reported that the environmental conditions, such as experimental environment (isobaric measurement), actual environment (measurement in open atmosphere), and corrosive environment , have strong influence on the sensitivity of the sensor. Among them, in the experimental and actual environments, the environmental conditions have less influence on the sensor sensitivity with time. However, in corrosive environments, a greater degree of reduction in sensor sensitivity occurs over time . Based oSince the impedance spectrum can provide more information about the sensing mechanism of humidity sensor ,49, impe5+ as a donor can provide a lot of delocalized electrons, as described by the defect equation:The purpose of  co-doping is to construct electronically pinned defect dipoles in the metal oxide. Nb3+ as an acceptor will generate a lot of oxygen vacancies, providing a local anoxic environment to inhibit the delocalized electrons, resulting in a charge-balanced defect-dipole complex/cluster.Likewise, InDue to the high electrical properties of Hf atoms, discontinuous hydrogen bonds are formed after the water molecules are trapped by the Hf edges. At low humidity levels , the content of water molecules is very low and water molecules are adsorbed in the form of chemisorption and cannot move freely. A continuous water layer is not yet formed on the sensor surface, and the conduction of free protons from one position to another on the surface is difficult, easily leading to the generation of high impedances, as shown in Depending on the defect response, oxygen vacancies can also cause humidity sensing in the form:− group. The electrostatic field generated by the − groups. They can also act as an effective chemisorption centers and play a role in reducing the sensor impedance.When RH = 75%, from the complex impedance diagram, a significant decrease in impedance occurs and a smaller semicircle is formed, as shown in − groups, more and more water molecules are physically absorbed to form a continuous water layer [− groups to form H3O+ and, at the same time, H3O+ can also generate H+ and H2O.Due to the electrostatic effect of OHer layer . The for3O+, which greatly reduces the impedance of the sensor and improves the sensitivity of the sensor.This process promotes the transfer and hydration of H3O+ and protons. When H3O+ releases a proton to a neighboring water molecule, the latter accepts the proton and releases another proton at the same time, and so on repeatedly; charge transfer occurs, which is called Grotthuss chain reaction. It is considered to represent the conduction mechanism of liquid water. According to Grotthuss [With the further increase in humidity level, the relative humidity reaches above 85%, and the formation of multiple continuous layers of water due to physical adsorption makes the physical adsorption close to saturation. At this point, the decrease in sensor impedance is caused by the combined jump of Hrotthuss  and Casarotthuss :(7)H2O+H2 ceramics.The impedance plot shows a straight line at the end of the semicircle. This is due to the saturation of the physical adsorption and the Warburg impedance caused by the electroactive material on the electrode . Moreovex1-(In0.5Nb0.5)xO2  ceramics were prepared via the solid-state reaction method. The humidity-sensing properties of the samples were investigated over the humidity range of 11–94%RH. The sample with x = 0.005 was found to show the largest response, and was used as a model sample to further boost its sensing properties via the wet chemical method to reduce the particle size and enlarge the specific surface area of the sample. A large impedance change of nearly four orders of magnitude was achieved in the sensor based on nanosized HINO-0.005. The humidity sensing properties were attributed to the dual doping-induced defects that act as active sites for water absorption. The Grotthuss mechanism can be used to explain the humidity sensing properties of the (In+Nb) co-doped HfO2 ceramics.In conclusion, (In+Nb) co-doped, Hf


We investigated the possible adsorption of each of the main building blocks of spider silk: alanine, glycine, leucine, and proline. This knowledge could help develop new biocompatible materials and favors the creation of new biosensors. We used ab initio density functional theory methods to study the variations in the optical absorption, reflectivity, and band structure of a modified graphene surface interacting with these four molecules. Four modification cases were considered: graphene with vacancies at 5.55% and fluorine, nitrogen, or oxygen doping, also at 5.55%. We found that, among the cases considered, graphene with vacancies is the best candidate to develop optical biosensors to detect C=O amide and differentiate glycine and leucine from alanine and proline in the visible spectrum region. Finally, from the projected density of states, the main changes occur at deep energies. Thus, all modified graphene’s electronic energy band structure undergoes only tiny changes when interacting with amino acids. At present, developing biosensors to detect antibodies, nucleic acids, and peptides is of great interest to several fields, with potential health, industrial, and environmental applications. Several materials have been studied from silicon ,2 to difRecently, engineered biosensors have provided a high electron transfer between molecules and electrodes. The high electron mobility of graphene, combined with the relatively easy way of doping, makes it an excellent candidate for a molecule sensor. Another favorable feature of graphene is its transparency to the visible spectrum. The large number of states provided by a biomolecule considerably modifies this property, making it useful for optical sensors ,15.This work focuses on the interaction between graphene and four amino acids, known to be the main building blocks for spider silk : alanineInvestigating the individual interactions of graphene with the amino acids of spider silk could yield a successful blending of graphene and spider silk. It may be necessary to functionalize graphene with peptidic chains to achieve this goal. The new material obtained from this blending may result in a combination of the extraordinary mechanical properties of each material. Ab initio density functional methods provide an excellent tool for such an investigation.Next to each case in The left column in X = alanine, glycine, leucine, or proline and the modified graphene energy refers to the energy of either graphene with vacancies or the F-, O-, or N-doped graphene surfaces. The results are shown in We calculated the adsorption energies using the following equation:We calculated the recovery times from Equation (6) using the values for the adsorption energies shown in The adsorbed molecule should remain on the sensor’s surface for a significant enough time to consider the latter as a suitable detector. In this way, it is possible to measure some convenient properties of the material, searching for changes. However, considerable recovery times could rapidly lead to surface saturation, making the detector unsuitable.The cell size used showed Brillouin folding, placing the Dirac cone at the gamma point instead of the kappa point. However, as this was an effect of the symmetry and size of the unit cell, it left the results unchanged. In all cases, the presence of the amino acids generated a semi-flat band that could vary in a range from −0.9 eV to −2.7 eV, as seen in We obtained the projected density of states (PDOS) for all the calculated structures. We present the variations in the s and p states of graphene modified with and without amino acids. Also, we show the individual states of each amino acid. For all structures considered, the PDOS plots confirmed the metallic nature of the systems, shown as well in the band structure plots. As can be seen in For F-doped graphene , the chaThe main changes in the PDOS occurred at deeper energies, which modified the optical absorption shown in the next section. In this and the previous section, we only focused on showing the invariance of the electronic properties as the four amino acids interacted with the vacancies and various dopants. We will see that optical activity is the main form of detection and discrimination of amino acids.−2, suggesting that only Van der Waals interactions were relevant. We have not reported the Löwdin charge values in this work because of their low-range variance.The electron transfer (Löwdin charges) was low, with values around 10y-axis is expressed in eV. We used the fact that a wave with a wavenumber k = 8065.544 cm−1 would correspond with a photon with an energy of 1 eV.From the calculation of the dielectric tensor using Equations (2)–(5), we obtained the absorption and reflectivity for each structure. We considered the propagation of the electromagnetic wave perpendicular to the graphene plane. In −1 or 0.20953 eV [We obtained the principal infrared absorption peak for graphene with 5.55% vacancies extinguished upon interaction with any of the four amino acids studied, as shown in 20953 eV , so grapWhen doped with fluorine, only glycine left the IR absorption spectrum unchanged. In contrast, the other three amino acids showed a peak at 0.70 eV. This variation could already be detected because the higher energy resolution of the sensors could be around 0.0067 eV . With thFor the F-doped graphene case, glycine was the only amino acid that kept the absorption spectrum unchanged. The other three amino acids increased the activity in both orange (2.02 eV) and violet (3.15 eV), while cancelling the peak generated when doped with fluorine. The differences obtained would be enough to be detected, considering that current biosensors can detect differences of around 0.0067 eV . For theIn The effect of the four amino acids on the three doped-graphene cases considered was negligible for the main peaks. Glycine produced a peak at 8.5 eV in the four modified graphene cases. The four amino acids considered caused a small amount of UV absorption, with an energy of 6.5 eV.Reflectivity was calculated over a range from 0 to 30 eV and plotted up to 20 eV because from this energy, the reflectivity became zero in all cases. The other amino acids only produced an increase in the peaks at 12 and 14 eV, while the peak at 11 eV decreased. When graphene was doped with F, N, or O, the connectivity remained invariant when interacting with alanine or glycine. Only a small peak was seen for both cases at an energy of 8.30 eV.In this work, we performed ab initio DFT calculations to study the electrical and optical properties of modified graphene and its interactions with four amino acids , which can be considered to be the building blocks of spider silk. Four cases of graphene modifications were considered: graphene with vacancies at 5.55% and fluorine-, oxygen-, or nitrogen-doping of graphene at the same percentage. For all cases, we found that the electronic properties—the projected density of states, band structure, and Löwdin charges—overall remained unchanged while interacting with the four amino acids considered. Regarding the recovery time, F-doped graphene at 5.55% could be the most suitable proline detector among the cases considered.Graphene with vacancies could also be a suitable glycine sensor, even if it presents an adsorption energy 0.08 eV higher than the detection upper limit. A higher adsorption energy could saturate the sensor, while a lower energy would not be enough to detect the amino acid.On the other hand, there were interesting findings on the optical properties of the systems considered. We found that the case of graphene with vacancies presented the adsorption of amino acids, with proline having the highest adsorption energy (2.24 eV). A loss of the peak in the infrared spectrum (0.20 eV) when interacting with the four amino acids was also found. Thus, the vacancy percentage considered (5.55%) could be used to detect amide. For this case, we also found blue light absorption when interacting with glycine and leucine, differentiating them from alanine and proline.In addition, we obtained a cancellation of the three peaks of the reflectivity of the graphene with vacancies. This case showed an activity of 20% in the visible region when interacting with leucine, making it a possible optical sensor in the said region.Fluorine-doped graphene at 5.55% could also be used to differentiate between alanine and glycine by absorption in the orange range. We found that N- and O-doped graphene required a higher resolution to differentiate between amino acids, which could also imply a cost increment of a sensor based on those surfaces.The ab initio calculations performed in this work were obtained using the density functional theory (DFT) and the software suite Quantum ESPRESSO ver. 6.2.1 ,24. XCry−8 Ry. As the code used considers periodic boundary conditions, the supercell size was large enough to avoid spurious interactions. For the same reason, the cell parameter in the z-axis was set to 15 Å, meaning there was a 30 Å distance between each graphene layer. In this way, we could model a 2D surface in a vacuum.We also considered norm-conserving pseudopotentials with the Goedecker–Hartwigsen–Hutter–Teter method and the Van der Waals VdW–DFT correction ,29,30,31−3 Ry/Bohr. Self-consistent and non-self-consistent calculations were performed on the resultant structures to obtain their corresponding band structures, the density of states, and the PDOS.We first optimized the graphene surface for the four cases considered: addition of vacancies, and F-, N-, or O-doping. Then, the amino acids were included. We performed a geometric optimization to minimize the forces of the system below a threshold of 1.0 × 10iiε(ω)) was calculated from the band structure. Then, the Kramers–Kroning relation was used to calculate the real part of the dielectric tensor (Re iiε(ω)). Knowing the real and imaginary part of the dielectric tensor, the reflectivity (iiR(ω)) and optical absorption (iiA(ω)) were obtained via the following equations [In each case, the imaginary part of the dielectric tensor (Im quations :(2)Riiω=n is the refractive index and k is the extinction coefficient. Finally, considering Eyring’s theory of state transitions [In Equations (2)–(5), nsitions ,20, we cEads is the adsorption energy of each molecule within the surface and BK and h are Boltzmann’s and Plank’s constants, respectively. Finally, T is the temperature, set here to be 300 K. We did not perform molecular dynamics calculations in this work; the value of T = 300 K was exclusively used in Equation (6) to estimate the recovery time at room temperature.In this expression,


Due to the growing scarcity of spectrum resources in the low-frequency band, the requirement of beam-reconfigurable antennas in the millimeter wave band is urgent. In this paper, a W-band graphene-based metasurface working in a broad bandwidth is proposed with reflective amplitude coding. Here, graphene sheets play a dual role in radiating and regulating electromagnetic waves. By adjusting the Fermi levels of graphene, the reflective amplitude and phase of the metasurface can be modulated simultaneously, enabling multi-beam switching and beam deflection in far-field. The proposed metasurface achieves amplitude-phase modulation within a significantly wide bandwidth which covers 75–91.5 GHz and 99.3–115 GHz. By optimizing the coding patterns, the proposed graphene-based metasurfaces are able to not only realize 2-D beam steering, but also achieve beam switching from single beam to four beams at 87 GHz. The proposed design provides a novel solution for the flexible manipulation of millimeter waves, which can be applied to various fields such as vehicle radar, satellite communication, 6G wireless communication, and beyond. As the evolution of mobile communication technology has progressed from 1G to 5G, a multitude of wireless communication methods have emerged, encroaching upon scarce spectrum resources. In order to expand communication capacity, i.e., obtain wider bandwidth, future wireless networks will be compelled to venture into higher frequency bands, including millimeter wave and terahertz bands, which hold promise for the advancement of sixth-generation communication technologies (6G communication). Against this background, beam-reconfigurable antennas are increasingly being employed in personal communication devices, wireless local area networks, the Internet of Things, and 5G communication technologies. Traditional beam-reconfigurable antennas include phased array antennas , and beaGenerally, depending on whether controllable elements or materials are added, the metasurface can be divided into active and passive types . Once a Initially, graphene has gained significant popularity in the optical and terahertz frequency bands owing to outstanding optical characteristics and the pliable and manageable surface conductivity over an extensive range of high frequencies. Chiang et al. demonstrated a broadband terahertz amplitude regulator based on complementary stacking of multilayer metamaterials, which shows a bandwidth of 0.5 THz centered at 1.25 THz, corresponding to a relative bandwidth of 40% . A. FallIn this work, we propose an active and reflective graphene-based metasurface in the W-band. To achieve beam reconfigurability, the reflection amplitude and phase of each metasurface unit is modulated by varying the Fermi level of graphene. And the coding bandwidth rages cover 75–91.5 GHz and 99.3–115 GHz. Under the premise that the two coding units have a certain reflection phase difference, beam steering and multi-beam switching can be achieved at a fixed frequency through the elaborate arrangement of the amplitude coding pattern. In comparison to conventional phased-array antennas, the graphene metasurface has the advantages of simple structure and light weight.n is the carrier concentration in graphene, Graphene is a new type of high-performance material that was isolated from graphite in 2004 by Geim and Novoselov at the University of Manchester . It is tT = 300 K  is shown in Equation (2), where the Fermi velocity The relationship between the Fermi level and carrier concentration of graphene at room temperature The relationship between relaxation time and Fermi level is shown in Equation (3). When other conditions have been determined, the relaxation time The effect of temperature on graphene carrier mobility is small, and the effect of impurity scattering on graphene carrier mobility is relatively large. Therefore, the graphene carrier mobility can be improved by increasing the purity of graphene at room temperature.fE > q is the fundamental charge, T is the temperature, Kubo, a Japanese scientist, proposed that the Kubo formula  can be ag effect , when thTo summarize, the range of variation of graphene conductivity is limited by several factors, including Fermi level, carrier concentration, temperature, and operating frequency. Only by selecting the appropriate parameters can a large enough range of variation be achieved to ensure that the graphene surface switches between high and low impedance states. Based on Equation (5), the sheet impedance of graphene is inversely proportional to both carrier mobility and the Fermi level. Therefore, by applying a voltage to graphene, the concentration of carriers in graphene is controlled and the Fermi level of graphene will be changed. Eventually, the surface conductivity of graphene is manipulated. The adjustable Fermi level of graphene provides an idea for dynamic modulation of electromagnetic beams using graphene-based metasurfaces.In 2014, Professor Cui proposed the notion of digital coding metasurface . The metmn, −mn, and so on when expanding in different directions on both sides of the origin unit. The formula for far-field scattering is shown in Equation (8) according to the relevant conventional phased array antenna theory [mx, ny), respectively. Similarly, mx, −ny), respectively. The desired beam state is obtained when the coding units on the digital metasurface are arranged with reasonable planning.Inspired by , the unia theory  and genea theory .(8)E with a thickness of 0.05 mm and the relative permittivity was 2.5. The DC feed was loaded between the upper and lower layers of the graphene. In this design, graphene was modeled and analyzed as a thickness-free 2-D material. The upper graphene served as the positive stage for DC excitation, while the lower graphene acted as the negative stage. Consequently, two vias with radius r1 were inserted into the substrate, as shown in 2r of the hole should be greater than the radius r1 of the via. As shown in To confirm the relationship between the phase and amplitude of the coding unit, the frequency domain simulator of the CST Studio Suite software was used to simulate and analyze the graphene metasurface unit. For this study, all discussions and results correspond to normal direction incidence scenario. The Fermi level of both upper and lower layers of graphene were simultaneously regulated, tuning it from 0 eV to 1.8 eV in steps of 0.2 eV. Based on the data presented in However, an exception can be seen within the shaded area of In R should be in the range of 1.56–4.96 mm. The selection of a reasonable focal length plays a crucial role in the overall metasurface performance. The time domain simulator of the CST Studio Suite software was used to simulate and analyze the graphene metasurface. R = 2 mm is chosen as the final option. The metasurface dimension D = 12.5 mm, and the corresponding focal diameter ratio R/D = 0.16.As depicted in For convenience, we use “m” to denote the number of rows in the graphene metasurface unit “0” in the following simulation. The case where m = 0 corresponds to a situation that all rows are set to unit “1”; m = 1 means only row 1 is set to unit “0”; and m = 2 signifies that both rows 1 and 2 are in the “0” state and the rest in the “1” state, and so on. To verify the reconfigurable performance of this graphene-based reflective encoded metasurface beam, we encoded the metasurface according to Equation (8). The operating frequencies led to different far-field functions of the subarrays, which in turn led to differences in the directionality functions of the entire hypersurface at different frequencies. Due to the fact that each unit of the metasurface in this design had two states, there were a total of 225 encoding and array methods for the entire array. Combining As shown in In this work, a multifunctional metasurface with reflective amplitude-phase modulation is designed based on graphene. Graphene is commonly used in the terahertz band, and this work applies it to the W-band. The metasurface is composed of a 5 × 5 array consisting of only 25 units. By varying the Fermi level to encode the reflective amplitude and phase of the graphene metasurface, the metasurface has the capacity to execute beam steering and multi-beam switching concurrently. The graphene-based metasurface achieves beam reconstruction function over an exceptionally wideband from 75 to 91.5 GHz and 99.3 to 115 GHz. Compared to traditional phased array antennas, the graphene metasurface offers numerous advantages such as wide working bandwidth, simple structure, and lightweight design, making it an ideal candidate for vehicle-borne radar, satellite communication, and 6G wireless communication.