In addition, electrical conductivity and joule heat were significantly improved after microwave post-processing, especially its electromagnetic shielding performance with a shielding coefficient of 53 dB able to be achieved. At the same time, the thermal conductivity is as low as 0.05 W m−1 K−1. The mechanism for the improvement of electromagnetic shielding performance is that (1) microwave reduction effectively enhances the conductivity of the graphene sheet overlapping network; (2) the gas generated by the instantaneous high temperature causes a large number of void structures between the graphene layers, and the irregular interlayer stacking structure makes the reflective surface more disordered, thereby prolonging the reflection path of electromagnetic waves among layers. In summary, this simple and environmentally friendly preparation strategy has good practical application prospects for graphene film products in flexible wearables, intelligent electronic devices, and electromagnetic wave protection.The preparation of freestanding graphene films by convenient and environmentally friendly preparation methods is still the focus of attention in various industrial fields. Here, we first select electrical conductivity, yield and defectivity as evaluation indicators and systematically explore the factors affecting the preparation of high-performance graphene by electrochemical exfoliation, then further post-process it under volume-limited conditions by microwave reduction. Finally, we obtained a self-supporting graphene film with an irregular interlayer structure but excellent performance. It is found that the electrolyte is ammonium sulfate, the concentration is 0.2 M, the voltage is 8 V, and the pH is 11, which were the optimal conditions for preparing low-oxidation graphene. The square resistance of the EG was 1.6 Ω sq The preparation of freestanding graphene films by convenient and environmentally friendly preparation methods is still the focus of attention in various industrial fields. At present, most electromagnetic radiation pollution from systems such as microwave communication, communication base stations, and high-voltage transmission lines is caused by human factors. Electromagnetic radiation not only causes a disturbance or even damage to the normal working of electronic equipment, but its harmful effects on human health are becoming increasingly prominent.2With the rise and commercialization of modern information technology, especially 5G technology, electromagnetic waves, as a medium for disseminating information, have brought convenience to people's production and life in sophisticated electronics, cell phones, and computers.3 The multi-layer reflective interface and electron transfer properties make the research on the construction, assembly and modification of graphene-based films a current research hotspot. The physicochemical properties of individual graphene nanosheets often directly affect the stability of their dispersion, the homogeneity of the assemblies, the integrity of the conductive network and the orderliness of the stacked structure.4–6 Graphene nanosheets are irregularly shaped, which is not conducive to the ordered stacking of film formation. Introducing block polymers, cross-linkers, and nanomaterials into the interlayer of graphene has achieved remarkable results in macroscopic graphene films. Although the dispersion of graphene can be significantly improved, the introduced impurity ions tend to degrade the electrical, thermal, and magnetic properties of graphene films.7–9 In addition, the traditional preparation methods, such as the redox method, mechanical exfoliation method, and liquid deposition method,10–12 have insurmountable problems such as being time-consuming, easy environmental pollution and performance defects caused by hazardous chemicals. The chemical vapour deposition method13 is a complex preparation process. Expensive equipment requires harsh environments such as high temperatures and high vacuum, which need to transfer 2D materials from the metal surface to the target. The manufacturing process is difficult to control and even introduces impurities or defects into 2D materials, resulting in decreased product performance and difficulty removing graphene from the substrate. Therefore, convenient graphene preparation conditions and tunable graphene products are essential for constructing graphene thin films.Graphene-based film materials have good prospects for practical applications in electronics, especially in the field of electromagnetic shielding, occupying an irreplaceable position due to their unique interlayer stacking structure, as well as their good electrical conductivity and ultra-lightness.14 That can be quickly industrially produced using known electrochemical cell design and engineering principles. Various graphite materials, such as graphite flakes, graphite rods, and high-oriented pyrolytic graphite (HOPG), can be used as the carbon source for the electrochemical preparation of graphene.15–17 There are still a tiny amount of oxygen-containing groups on the graphene prepared by electrochemical exfoliation, which usually weakens graphene's electrical conductivity, thermal conductivity, and electromagnetic shielding properties. Many factors affect graphene's electrochemical exfoliation . Zhang et al.18 improved the electrochemical exfoliation efficiency by deploying a method containing organic solvents and cations. Tetrabutylammonium cations in propylene carbonate can intercalate into graphite efficiently under reducing conditions. The product showed an ultra-low defect degree of 0.05 (ID/IG). Justin Raj et al.19 introduced ultrasonic equipment simultaneously as electrochemical exfoliation. The pulse (2/4) of 2 s sonication and 4 s rest time can be used in acidic, neutral and alkaline conditions. Both of them promote the electrochemical exfoliation process; Lei et al.20 explored the effect of high and low voltage on the oxidation degree of graphene, and they evidenced two different regimes during the synthesis by Raman and XPS analysis: slow kinetics of exfoliation at low voltage vs. high concentration of OH˙ radicals at high voltage. Recently, Vaiva Nagyte21 conducted a systematic study of the Raman spectrum of electrochemically exfoliated graphene, produced using different electrolytes and types of solvents in varying amounts. All in all, it is urgent and significant to explore the preparation scheme of graphene with the advantages of easy industrial production, economy, simplicity and environmental friendliness.Electrochemical exfoliation is a top-down graphene preparation method, which has the advantages of simple operation and environmental friendliness  and does not require volatile solvents or reducing agents that can form highly controllable flakes.Here, graphene was prepared by the electrochemical exfoliation method. The effects of electrolyte type, concentration, voltage and pH value on the properties of graphene prepared by electrochemical exfoliation were discussed in detail, with conductivity, yield and defect degree as evaluation indicators. The optimum conditions for the electrochemical exfoliation of graphene with double electrodes were obtained. At the same time, the self-supported graphene films were treated by microwave reduction under volume-limited conditions. The conductivity, thermal conductivity and electromagnetic shielding performance of graphene films before and after microwave reduction were compared and discussed.2.2.1.Graphite (99% C content), chemically pure, Tianjin SKF Co., Ltd.; ammonium sulfate, sulfuric acid, analytical grade, Tianjin Tianli Chemical Reagent Co., Ltd.; ammonium chloride, sodium sulfate, diammonium hydrogen phosphate, tripolyphosphoric acid sodium, analytically pure, Xi'an Chemical Reagent Factory; potassium sulfate, analytically pure, Tianjin Fuyu Fine Chemical Co., Ltd.; sodium hydroxide, analytically pure, Tianjin Hedong District Hongyan Reagent Factory; ultrapure water, self-made in the laboratory.2.2.The EG dispersion liquid was freeze-dried into powder and ultrasonically dispersed in 50 mL of deionised water. The EG dispersion liquid was filtered on a polytetrafluoroethylene membrane with a Buchner funnel, dried in an oven for 4 hours after manually peeling off the substrate, and taken out to obtain a self-supporting graphene film (EGF).2.3.The prepared EGF was laid flat on a 5 mm thick quartz plate, covered with another 5 mm thick plate and fixed. Then put them in the microwave oven, adjust the power to medium, and set the timer to one minute. Then it was taken out to obtain microwave-reduced graphene films (MWEGF). The schematic diagram of MWEGF preparation is shown in 2.4.2.4.1.θ = 5–40°, and a scan rate of 10° min−1. The sample's infrared (FT-IR) spectrum was obtained by a Fourier transform infrared spectrometer , and the test wavelength range was 4000–400 cm−1. X-ray photoelectron spectroscopy  was used to test the sample's composition. A single-frequency Al Kα (1486.6 eV) ray source was used with a power of 250 W. The pollution carbon peak at 284.8 eV is the calibration standard, and the background vacuum is greater than 10–7 Pa. The structural defects of EG were tested with a Renishaw inVia microscopic confocal laser Raman spectrometer . The incident light wavelength was 325 nm, and the test range was 500–3500 cm−1.The EG, EGF and MWEGF microstructures were observed by scanning electron microscopy  with an accelerating voltage of 20 kV. The layer structure of EG was observed by transmission electron microscope . The accelerating voltage is 200 kV, and the maximum magnification is 200 000 times. An atomic force microscope  was used to test its surface morphology and size in tapping mode. The X-ray diffraction (XRD) test of the sample was carried out using an X-ray diffractometer , using D/max 2200 PC Cu target Kα radiation, 22.4.2.m1 is the mass of the upper layer liquid; m2 is the mass of the lower layer precipitated.The stripped product was ultrasonic, dialysed, and centrifuged at 3000 rpm for 10 min to disperse and purify the unexfoliated particles. The upper-layer solution and the lower-layer precipitate were freeze-dried and weighed, respectively. Then the graphene yield is:2.4.3.Measured with a four-probe tester . The surface temperature was measured with a thermal imaging thermometer . A vector network analyser (Rohde & Schwarz) was used to test the electromagnetic shielding effectiveness of EGF and MWEGF in the frequency range of 8.2–12.4 GHz.3.3.1.4Cl, Na2SO4, (NH4)2SO4, K2SO4, (NH4)2HPO4, and Na5P3O10 were selected as electrolytes, and the electrolytes were screened under the conditions of electrolyte concentration 0.1 M, working voltage 10 V, pH 7, and exfoliate for 2 h.In general, there is a close relationship between its exfoliation quality and electrochemical exfoliation conditions. To this end, we explored the electrochemical preparation conditions in detail, taking the product's yield, conductivity, and defect results as the object of investigation. Firstly, NH−1) and G (1590 cm−1) peaks confirm that graphene has a varying thickness. The characteristic peak at the D (1350 cm−1) band implies defect and disordered carbon. As shown in 4)2SO4 as the electrolyte had an ID/IG value of 0.669, indicating that the degree of graphitisation of the product was relatively low and showed fewer defects. At this time, its conductivity was excellent, the square resistance was only 3.55 Ω sq,−1 and the yield was 47.9%. When (NH4)2SO4 was used as the electrolyte, the graphene yield was higher than other electrolytes, and its conductivity was also the best. It was because the interlayer spacing of graphite was 0.335 nm, while the sulfate ion size was about 0.46 nm, which was similar to the interlayer spacing of graphite. So that it was easier to intercalate into the graphite interlayer than other ions. According to the previous reports,22 the electrolysis and co-intercalation of sulfate ions lead to producing gases such as SO2, O2, and H2. Efficient intercalation and gas eruption facilitate the separation of graphene sheets from adjacent graphene layers. The radius of ammonium ions is more significant than that of sodium ions and potassium ions. Partial intercalation can also be performed at the cathode to promote the expansion of the graphite electrode. After the electrolysis of water, the H+ generated by the electrolysis of water is reduced at the cathode to generate hydrogen to further promote the graphite electrode's exfoliation. Therefore, choosing ammonium sulfate as the electrolyte for electrochemical exfoliation is more appropriate.Raman spectroscopy has been widely used to evaluate graphene defects. The ratio of the signal intensities at 2D (2700 cm4)2SO4 concentrations  on graphene's yield and conductivity were investigated under operating voltage conditions 10 V, pH 7, and stripping for 2 h. The results are shown in −1, as shown in 4)2SO4 was 0.2 M, the ID/IG of graphene was 0.548, and the degree of graphitization was low. Thus, the concentration of (NH4)2SO4 was chosen to be 0.2 M.Then, the effects of (NH4)2SO4 electrolyte solutions with different voltages  on the exfoliated graphene products under the conditions of electrolyte concentration of 0.2 M, pH 7, and stripping time of 2 h were further explored. The results are shown in ID/IG = 0.338 was observed in the prepared graphene. Therefore, 8 V was selected as the appropriate voltage with better yield and conductive. The yield was 60% at this timed was 60%, and the square resistance was 1.3 Ω sq−1.Secondly, the effects of (NH4)2SO4 electrolyte solutions with different pH values  on the exfoliated graphene products  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>C bond in the EG structure and the out-of-plane bending vibration absorption peak of –OH; the absorption peak at 1200 cm−1 corresponds to the stretching vibration of the epoxy group –C–O–C–. The characteristic peak at 1083 cm−1 is the stretching vibration of –C–OH. Theoretically, EG contains some –OH and –C–O–C– because EG may only be partially oxidized.22,23Above all, we explored in detail the microstructure and properties of the product samples of the conditions under optimal experimental conditions. 24 Generally speaking, a low degree of oxidation means that the damage to graphene conjugation was soft, so the integrity of the graphene structure can be guaranteed. C (284. V), C–OH (285.5 eV), CO (287.6 eV), and C(O)–O (290.1 eV). It further showed that the EG surface contained a small amount of hydroxyl and carboxyl groups. In addition, we compared the XRD patterns of multilayer graphene and initial graphite. It can be seen that when the 2θ is about 26.42°, the characteristic peak of the graphite (002) crystal plane was sharp, the degree of crystallinity was high, and the interlayer spacing was about 0.335 nm. Compared with the initial characteristic peak of graphite, the intensity of the characteristic peak of the (002) crystal plane of the multilayer graphene exfoliated by the electrochemical method was weakened, indicating that the graphite expanded and exfoliated, and the degree of crystallization was reduced. The peak width of the characteristic peak increased, indicating that the disorder of the graphite sheet increased. At the same time, compared with pristine graphite rods, the (002) peak position of the EG peak did not shift to a small angle, which means that the interlayer spacing remains unchanged, and the exfoliated graphene product may only contain a small number of functional groups.25Secondly, −1 caused by defects, a strong G peak at 1580 cm−1, and a 2D peak at 2708 cm−1 elevation. The value of ID/IG was only 0.057. This indicates a lower defect level in pristine graphite, as shown in 3 hybridisation of carbon during intercalation and ultrasonication, resulting in the attachment of oxygen-containing functional groups to the graphene edge, introducing a small amount of oxygen-containing functional groups.26–28 The ID/IG value was 0.261, which indicated that the graphene prepared from electrochemical exfoliation had a higher quality, which was much lower than that of thermally reduced or chemically reduced graphene oxide (ID/IG ≈ 1.1–1.5), which further illustrated that graphene process introduced only a small number of structural defects. The G peak was caused by the stretching vibration between carbon atoms of the sp2 structure, which reflects the crystallinity of the graphite. The intensity of the G peak in the figure was more significant, indicating that EG had a complete crystal structure. Compared with graphite rods, the 2D peak of electrochemically exfoliated graphene had a higher degree of symmetry, increased intensity, and a significant left shift in the peak position, confirming that the number of layers decreases when graphite rods are exfoliated into graphene, as shown in Furthermore, the Raman spectrum of pristine graphite presented three characteristic peaks: a very weak D peak at 1350 cm2 hybridised carbon atoms at graphite edges and grain boundaries and, at the same time made two adjacent carbon atoms be hydroxylated. Subsequently, the two hydroxyl groups can interact with each other to form an epoxy ring. Likewise, they can also dissociate to form two carbonyl groups. At this stage, water molecules and sulfate anions co-intercalate to promote the expansion of anode graphite; the partial reduction of sulfate ions and the autooxidation of water generate gas that strips the graphite disperses it into solution. During this reaction process, the electrolysis of water and the intercalation of ions are interactive and synergistically promote graphite exfoliation. In addition to the oxidation reaction of graphite, other reactions take place, including releasing CO2 and O2 through the response. The generation of these gases can exert additional forces on the graphitic layers, separating the weakly bonded graphitic layers from each other. At the same time, under the action of the electric field force, the ammonium ion and the hydroxyl group in the sodium hydroxide generate ammonia gas at the cathode, further promoting the graphite rod's expansion and peeling.17The mechanism for the electrochemical preparation of graphene was generally assumed to be the result of the synergistic effect of ion intercalation and gas exfoliation. The graphite rod in the electrolyte is applied with a voltage, causing the water molecules at the cathode to be consumed. The electrolysis of water usually produces hydrogen ions and hydroxyl radicals. It is worth noting that hydroxyl radicals act as strong nucleophiles in the electrolyte. During constant voltage electrolysis, cations and anions in the electrolyte will move to the cathode and anode, respectively. The edge positions and grain boundaries of graphite were eroded first so that the graphite edges became loose; hydroxyl radicals generated by electrolysis of water acted as strong nucleophiles and continued to attack the spTo further explore the specific process and microscopic mechanism of electrochemical oxidation exfoliation of graphene, the above mechanism hypothesis was verified by observing the morphology of graphite rods during the exfoliation process. A constant bias voltage was applied to the graphite electrode, and the morphology changes of the graphite rod after peeling off for 0–60 min were detected by SEM, as shown in The surface of the graphite rod was flat and had a specific lustre. In the longitudinal direction, it can be seen that the layers were closely combined, showing a sheet or plate structure, and the edges were not warped. When a voltage is applied, graphite's surface and edge morphology change drastically; the graphite rod begins to expand longitudinally. At the same time, the cracks in the graphite layer increase, increasing the interlayer distance. There are many pores inside, forming a loose and porous structure, which is conducive to the further exfoliation of graphene, and many wrinkles are formed on the surface, as shown in 29 In this experiment, we designed a set of quartz-based fixtures to ensure the integrity of the graphene film during reduction. Because we found that the resulting self-supporting graphene films were often broken or incomplete if there was no quartz cover to hold them in place, this was because the graphene film may impact the graphene stack due to uneven heating or the generation of a large amount of gas under microwave radiation. As shown in 30 Thereby changing the flat morphology of the EGF membrane to a raised foam shape with increased thickness. Moreover, the interlayer spacing inside the film will increase compared to before microwave reduction.Microwave reduction has attracted extensive attention in removing graphene due to its efficient and rapid heating method.3.3.θ was about 26.42°, the crystallisation degree of EGF and MWEGF decreased. Compared with EGF, the half-width of MWEGF was more comprehensive, and the disorder of graphite sheets was further enhanced. Since the full width at half maximum was inversely proportional to the grain size, the smaller the grain diameter, the larger the full width at half maximum. It is indicated that the grain size of MWEGF is smaller than EGF's. It can be seen from the figure that the overall structure of the graphene film had little change before and after microwave reduction. When 23.4.3.4.1.−1, and the conductivity was 9.09 S cm−1, which showed good electrical conductivity. Compared with EGF of the same quality, the conductivity and square resistance of MWEGF obtained after microwave reduction have been improved. When the mass of graphene reaches 70 mg, the square resistance is 0.92 Ω sq−1, and the highest conductivity can reach 22.12 S cm−1. EG was subjected to high temperatures reduction during the microwave reduction process, so a small amount of oxygen-containing functional groups carried by EG were sintered.31 The degree of oxidation of EG prepared was reduced by electrochemical exfoliation, and the electrical conductivity was improved.3.4.2.32 MWEGF is more suitable for thermal insulation because of its relatively low thermal conductivity and high joule electric heating performance.31,333.4.3.34,35 It affects the average regular of nearby electronic equipment and increases the risk of headaches, depression, immune deficiency and other diseases for relevant staff.36–38 Therefore, there is an urgent need for efficient EMI shielding materials to attenuate electromagnetic waves to protect the regular operation of electronic equipment and human health. Developing graphene-based high-performance EMI shielding materials has become a research hotspot in this context. M is negligible. The calculation formulas of SET, SEA and SER are as follows:In the formula: SET, SEA, SER, and SEM, respectively, represent the total electromagnetic shielding effectiveness, electromagnetic wave absorption loss, electromagnetic wave reflection loss and multiple reflection loss of electromagnetic waves; T and R represent the power coefficients of transmission and reflection, respectively.37,39Electronic equipment's operation will generate adverse electromagnetic interference (EMI) to the outside world.A) of EGF and MWEGF far exceeded the electromagnetic reflection ability (SER). The analysis showed MWEGF had better conductivity and larger internal layer spacing than EGF. When the electromagnetic wave passes through the MWEGF film, it is first consumed by the reflection part of the surface conductive network. Then when the electromagnetic wave enters the inside of the MWEGF, it will continuously undergo reflection loss and absorption consumption between the graphene sheets. It is better than EGF, with a relatively compact internal structure and relatively poor conductivity. In addition, the irregular interlayer structure of MWEGF increased the diversity of reflection direction, causing the reflection path to grow. The specific electromagnetic shielding mechanism of MWEGF is shown in It is the electromagnetic shielding effectiveness diagram of EGF and MWEGF with different masses in the 8.2–12.4 GHz frequency range. The attenuation performance of the shielding material is evaluated by SE, as shown in the 4.−1, and the yield was 65%, ID/IG = 0.261 meanwhile, the structural defects were minor. The results show that the C/O value of EG was 5.19, the oxidation degree of the sample was low, the defect degree was small, and the position where the intensity of the characteristic peak of (002) crystal plane weakens remains unchanged. In addition, the C/O value of EG by microwave reduction could be achieved at 6.2, indicating that the graphene prepared by this method had a relatively complete structure and had a good crystal and graphitised form. The analysis results of EGF and MWEGF electrical, thermal and electromagnetic shielding properties show that MWEGF has more electrical conductivity than EGF. Still, EGF has more vital controllable thermal conductivity, possibly due to EGF's tighter internal sheet structure and interlayer. The conductive network is more complete. In addition, due to the high conductivity and irregular and complex interlayer structure of EMWEGF, it shows excellent performance in electromagnetic shielding, with a shielding coefficient of 53 dB, and has good application prospects in electromagnetic pollution protection and stealth.This paper uses conductivity, yield and structure as evaluation factors for the first time to systematically discuss the effects of electrolyte type, concentration, voltage, and pH on the yield and conductivity of graphene prepared by electrochemical exfoliation. Without introducing any organic solvent and other auxiliary equipment, the best conditions for the preparation of graphene by double-electrode electrochemical exfoliation are as follows: the electrolyte is ammonium sulfate, the concentration is 0.2 M, the voltage is 8 V, and the pH is 11. The square resistance of the product sample was 1.6 Ω sqThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infra-red spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show that such fraction can be selected by tuning the Fermi energy of electrons in graphene with a bias, a phenomenon controlled by Pauli blocking of photo-excited electrons. These findings demonstrate a dependence between graphene’s electronic and proton transport properties and provide fundamental insights into molecularly thin electrode-electrolyte interfaces and their interaction with light. Recent experiments have shown that proton transport through graphene electrodes can be promoted by light, but the understanding of this phenomenon remains unclear. Here, the authors report the electrical tunability of this photo-effect, showing a connection between graphene electronic and proton transport properties. Recent experiments demonstrated that the transport takes place mostly around wrinkles and nanoscale ripples in the crystal lattice, in which strain and curvature reduce the energy barrier for proton permeation6. Besides graphene, which is a zero-gap semiconductor, monolayers of hexagonal boron nitride (hBN), a wide-gap insulator, were shown to be even more permeable than graphene; whereas molybdenum disulphide (MoS2), a heavily doped semiconductor, was found to be impermeable to protons4. These results suggested that there was no correlation between the crystal’s proton permeability and its electronic properties and cemented the notion that the Fermi energy of electrons in the material played no role in the proton transport. This notion became contested with experiments in which graphene’s in-plane electron conductivity7 was exploited to fabricate two-dimensional proton-permeable electrodes. In the devices, protons transfer through graphene and combine with electrons to form H2 molecules;10 a process that is accelerated using catalytic nanoparticles10 and takes place with 100% efficiency 10. Unexpectedly, these experiments revealed that solar-simulated illumination can enhance proton permeation through graphene electrodes by an order of magnitude8, a phenomenon that we called the photo-proton effect. However, despite these observations, there is still no understanding of the fundamental mechanism behind this photo-effect, nor on the dependence of proton transport through graphene on the Fermi energy of electrons. In this work, we report the unexpected suppression of the photo-proton effect with a small <1 V bias when the devices are measured under infra-red illumination. We show that this arises due to a shift in the Fermi energy of electrons in graphene under the applied bias, which prevents the absorption of low energy infra-red photons and suppresses light-driven proton transport through graphene. The results provide fundamental understanding of the interaction of photo-excited electrons and protons in molecularly thin electrode-electrolyte interfaces, which we rationalise using the Gerischer model12 of electrochemical interfaces.The defect-free basal plane of monolayer graphene is impermeable to all atoms8  and electrically connected with a proton-injecting electrode . The whole device was placed in a gas-tight optical chamber (IR grade sapphire widow) filled with 100% H2 gas at 100% relative humidity to ensure the high proton conductivity of Nafion. The chamber faced the light source and an optical chopper. The infra-red light source used was either a broadband Bentham IL1 halogen light with an electrically controlled monochromator or individual single frequency lasers. The suspended graphene film was electrically connected into the circuit shown in Fig. −1. We also measured devices under low intensity white light illumination using a Keithley 2636 sourcemeter as reported previously8. For reference, we measured similar devices in which the freestanding film was trilayer graphene, which absorbs light similarly to graphene15 but is impermeable to protons4.The devices studied in this work consisted of a graphene monolayer suspended over a micrometre-sized hole etched into silicon nitride substrates , as reported previously8 Fig. . One sid9. In brief, under an applied bias, protons from Nafion transfer through the basal plane of graphene5. The protons then combine with electrons flowing into graphene from the electrical circuit8 and form adsorbed hydrogen atoms on the Pd nanoparticles on the opposite side of the suspended graphene film  at least twice larger than the Fermi energy, EEF, can be absorbed16. Photons with lower energy are not absorbed because the states accessible to the photo-excited electron are occupied, a phenomenon known as Pauli blocking  voltage dopes graphene with electrons (holes) and shifts the Fermi energy, EF, with respect to the charge neutrality point (NP) according to the relation:7EF = ħvFn the charge carrier density, vF ≈ 1 6 m s−1 the Fermi velocity in graphene and ħ the reduced Planck constant7. Hence, applying a voltage bias raises EF and this will block the absorption.To rationalise these observations, we note that a necessary condition for the photoresponse is the absorption of photons by graphene, which requires exciting electrons from the valence to the conduction band Fig.  inset. Ting Fig.  inset16,EF in our graphene electrodes as a function of applied bias using Raman spectroscopy (Raman spectroscopy characterisation in Methods). Figure V-bias shifts the Fermi energy of the electrodes with respect to the NP. The shifts we observe, of a couple hundred meV (corresponding to high doping of 1012−1013 cm−2), are sufficient to block the absorption of photons in the near infra-red. For example, the suppression of the photoresponse with 1800 nm (≈0.69 eV) light in Fig. EF ≈ 0.34 eV. The Raman data show that this EF is indeed achieved in our devices for ≈0.55 V within our experimental scatter of about ±50 mV, in agreement with our photocurrent experiments in Fig. 19 and result in a finite doping of ~5 × 1011 cm−2 at the NP (which is around −0.18 V) evident in the Raman data19.To verify if Pauli blocking could be behind our observations, we determined EF in graphene for a fixed photon energy. However, in principle, the suppression should also be achieved for a fixed EF by decreasing the photon energy until the condition E = 2EF is satisfied  and, from the linear power dependence of the devices’ photoresponse, we extracted their photoresponsivity for each wavelength .The unexpected voltage-gated suppression of the photo-proton effect merits additional characterisation. In the experiments described above, photo-induced proton-electron transport was suppressed by raising V-bias. This leads to shorter cut-off wavelengths for larger V-bias, as per the criterion defined above (99% suppression). Figure y-axis), its corresponding photon energy E (right y-axis) and applied V-bias extracted from all our measurements, at both constant bias  = E(V)/2, which can be compared with the EF(V) relation found in the Raman data  Raman data from Fig. EF, which demonstrates that proton-electron transport in the devices depends on the Fermi energy in graphene.Figure ata Fig. . Figure 12, which considers the role of the band structure of the electrode in the reactivity of an electrochemical interface11 . The rate of transfer is then proportional to the integral of all the possible transfer events across all energy states. For the case of proton transport through graphene accompanied by an electron transfer (reduction process), the rate is:11kWo the Fermi distribution; Te the temperature of the electronic system; Wo22. According to the Fermi distribution, electronic states with energy of up to ~4kBTe above EF are filled (kB the Boltzmann constant), so raising Te increases the number of filled electronic states in graphene for a given EF. Since the hot electron distribution is effectively constant (>1 ps lifetime) for the duration of a proton transfer event , the electronic levels filled with hot electrons can interact with the solution states. This leads to a larger overlap between electronic and solution states, and hence to a faster reaction rate, k . The model predicts that for such Te the reaction rate at a given EF should increase by an order of magnitude with respect to the reaction in the dark (Te = 300 K), in agreement with our observations in Fig. 8. (Gerischer model in Methods). The model also predicts that such photoresponse should increase exponentially with bias, in agreement with our measurements in Fig. 8. Finally, the model naturally incorporates Pauli blocking of the photo-proton effect. If photon absorption is blocked, Te does not rise and the reaction rate does not increase under illumination either. Hence, this model is consistent with all our observations.The key insight from this model is the elucidation of the role of the Fermi distribution and the electronic temperature in our devices’ photoresponse. Illuminating graphene is known to create a long lived (>1 ps) hot electron distribution with high , k Fig. . To vali27. We propose that absorbed photons generate a hot electron distribution in graphene that increases the overlap in energy between electronic and solutions states, leading to a larger number of possible proton-electron transfer events and thus to larger interfacial reactivity, as predicted by the Gerischer model. In the wider context of ion transport phenomena, these results show that protons interact with the electronic system in graphene under a large range of Fermi energies, unlike, for example, metal electrodes in which the Fermi energy is effectively constant for the entire operational voltage window28. Our results also provide insights into molecularly thin electrode-electrolyte interfaces and their interaction with light30, revealing the prominent role of the electron Fermi distribution and electronic temperature. In terms of applications, graphene electrodes are a rare example of a system in which an external stimulus, in this case a voltage, can suppress light driven proton transport for a controllable fraction of the light spectrum. These results could enable the design of light-powered devices in emerging technologies, such as proton-based neuromorphic hardware35, by providing an additional gating mechanism that could enable switching individual elements of these systems or more complex logic operations.Our experiments reveal insights into proton-electron transport across one-atom-thick interfaces, which are increasingly explored due to their unique catalytic properties4. The substrate fabrication follows the recipe in previous reports4. In brief, silicon nitride wafers  were first patterned by photolithography and reactive ion etching (RIE) is then used to remove a 0.8 × 0.8 mm2 section from one of the SiNx layers. The wafer is placed in the 30 wt.% KOH solution to etch out Si, leaving a free-standing SiNx window (100 ×100 μm2). A circular hole  was patterned in the centre of the SiNx window by photolithography and etched by RIE. The suspended graphene membrane was electrically connected with an Au electrode fabricated using photolithography and electron-beam evaporation 8 to 109 Ω for the V-bias we used in this work), which allows measuring the photocurrent from the sample by measuring the voltage drop across this resistor. The sample was biased with a Keithley source metre (2614B) and the photocurrent was measured with a lock-in amplifier (Stanford Research Systems SR865A) using the frequency of the chopper as reference signal37.The chamber containing the sample was mounted on a stage with micro-manipulators. The window in the chamber faced a black tube with a small aperture to block stray light and the opposite end of this tube faced a light chopper (Thorlabs MC2000B). The light sources used were either a Bentham IL1 halogen broadband source or individual frequency lasers (Thorlabs NIR laser series). For measurements with the Bentham system, the light was directed through an electrically controlled single monochromator (Bentham TMc300), which allowed selecting a particular wavelength from 1800 nm to 2500 nm with a resolution of 0.2 nm. To remove higher-order wavelengths from the diffracted light, we used a 1550 nm long pass filter. For measurements with both individual lasers and the Bentham system, the sample was connected into the circuit shown in Supplementary Fig. 8. This instrument uses the light chopper’s frequency as input and filters out all signals that do not have this frequency, including the dark current. This allows us to measure the photocurrent directly. If we were to measure without the lock-in amplifier, we would observe that the dark current rises with bias, as in refs. 10. However, the low intensity light of <1 mW cm−2 used here would yield only a small rise in the total current, that would be difficult to characterise accurately. The lock in amplifier allows us to clearly characterise even this small photo-response.The use of the lock-in amplifier is an important difference of the measurement setup in this work compared to refs. 8.We performed two photocurrent measurement experiments with infra-red light. In the first one, we measured the photocurrent of the samples with variable voltage bias (constant illumination wavelength). In the second experiment, we measured the photocurrent at constant voltage bias (variable illumination wavelength). For this experiment, the wavelength is fixed (within 0.2 nm) for various values between 1800–2300 nm in the Bentham system. To account for variations in the intensity of the light filtered at different wavelengths, we characterised the power density for each wavelength  and for different light intensities (the intensity is controlled by the diaphragm in the system). Supplementary Fig.G-band of graphene is traced as a function of applied bias  reveals the Fermi energy of electrons in graphene and the charge carrier concentration (n) via the following relations38. For electrons, EF [meV] = 21 ΔωG + 75[cm−1], for holes, EF [meV] = −18 ΔωG − 83[cm−1]. Both fittings are consistent with our data within the experimental scatter. For both type of carriers, their density is given by n[cm−2] = (EF/11.65)2 x 1010. We fit the data with the formula EF = ħvF18 is given by C ≈ 3.6 μF cm−2, the gate capacitance and NP = -0.18 V, the neutrality point.For Raman measurements, the samples were placed in the gas-tight optical cell. The Raman spectra was measured using a WITec alpha300 R—Raman microscope with a 514 nm laser. In the experiments, the position of the 39, D(ε). On the other hand, states in solution are modelled by two density functions, Wo(ε) and WR(ε), corresponding to the two different chemical species on the surface of the electrode: the proton (Wo) and the adsorbed hydrogen atom (WR) in our case. Each of these functions is a Gaussian with mean energy equal to ε0 + λ for the reduction states, ε0−λ for the oxidation states, and standard deviation (2λkBT)1/2. In here, ε0 is the standard potential for the reaction, kBT the thermal energy in the solution and λ is the so-called reorganizational energy, which is the energy required for the reactants to undergo the physical transformation involved in the reaction (e.g. change of coordinates). To evaluate the model, we estimate ε0 and λ. For ε0 we take ε0 = 0 V vs SHE (standard hydrogen electrode) for the hydrogen evolution reaction. This potential corresponds to ε0abs ≈ 4.44 V in the so-called absolute scale11, in which the energy of electrons is referred against their energy in vacuum.The Gerischer model is evaluated as follows. On the electrode, the number of electronic states is given by the density of states function for grapheneε0 vs the NP (ε0NP), rather than vs vacuum . Hence, to illustrate the model, we use λ = 0.5 eV, as a representative value for this parameter. We also evaluated the model for several parameters and found that the qualitative insights are insensitive to this number, as long as λ is larger than the activation energy for the process.Since in our experiments we determine the position of the neutrality point (NP) experimentally, we refer kWo dE using the parameters described above. The rate is normalised against the reaction rate calculated for EF = 0 in dark conditions. We find that the rate increases exponentially with EF, both in dark conditions and under illumination, in agreement with our experimental observations. The model also predicts that for an electronic temperature of Te = 1000 K, the reaction rate should increase by over an order of magnitude, in agreement with our observations in Fig. 8. We note that the value of Te arises from a chain of complex processes involving photoexcitation, thermalisation and cooling20, which can be expected to be different in our devices due to the interaction of protons with the electron cloud and the presence of noble metal nanoparticles (e.g. Pd)42. Given these two uncertainties, we ran the model using Te = 1000 K, a value typically reported in the literature for graphene devices20. However, we also ran the model using lower Te = 500 K. This lower temperature does not change the qualitative findings of the model, requiring relatively minor adjustments to the parameters to yield similar results .Supplementary Fig. Supplementary InformationPeer Review File


General public, often called consumers, are increasingly seeking health information online. To be satisfactory, answers to health-related questions often have to go beyond informational needs. Automated approaches to consumer health question answering should be able to recognize the need for social and emotional support. Recently, large scale datasets have addressed the issue of medical question answering and highlighted the challenges associated with question classification from the standpoint of informational needs. However, there is a lack of annotated datasets for the non-informational needs. We introduce a new dataset for non-informational support needs, called CHQ-SocioEmo. The Dataset of Consumer Health Questions was collected from a community question answering forum and annotated with basic emotions and social support needs. This is the first publicly available resource for understanding non-informational support needs in consumer health-related questions online. We benchmark the corpus against multiple state-of-the-art classification models to demonstrate the dataset’s effectiveness. For example, when someone with a severe, life-threatening condition interacts with others who have experienced similar medical conditions, they feel more supported5. Although consumers may find the information they need about the disease, such as treatments, symptoms, and side effects on authoritative health-related websites, getting emotional support or social networking support has been shown to add value, but can currently be obtained mostly through online interactions with peers. Previous studies have shown that social support is associated with improved well-being and better health outcomes8. The advent of medical Question Answering (QA) Systems has been considered as a promising solution and an efficient approach for retrieving relevant and precise answers from several health-related information sources9. Automated medical QA may support clinical decision making providing necessary information that otherwise is hard to find. Several research efforts tackled the problem of medical QA and highlighted the challenges related to question understanding, answer retrieval, and answer generation from the perspective of informational needs12. To the best of our knowledge, no studies were previously dedicated to medical QA and social and emotional support needs.Health Consumers may turn to online resources to satisfy not only their informational needs, but also seek emotional or social support. The benefits of social and emotional support have been well documented in the literature13, we believe that questions containing social and emotional needs have unique characteristics that require analysis and evaluation in a dedicated study. These characteristics include (i) variety of emotional states , (ii) emotion causes that may differ from the topic of the question, (iii) different types of social support needs , and (iv) a need for different answers based on the social support needs sought.While such consumer health questions (CHQ) have been included in a variety of earlier studies as part of broader and more diverse QA tasksTo illustrate, consider the consumer question from Yahoo! Answers Q&A in Fig. 12. To date, only a handful of works have considered emotional and social support in different contexts. For example, Sharma et al.14 introduced a dataset of 10,000 online conversations in which the responses were annotated using an empathy framework to indicate whether the response post contained no communication, weak communication, or strong communication of empathy. Another dataset introduced by Hosseini and Caragea15 includes messages in online support groups annotated as seeking or expressing support. The dataset contains 5,007 sentences, each annotated with one of the three empathy labels: seeking-empathy, providing-empathy, or none. Sun et al.16 annotated 4,012 answers with a set of mental health support strategies based on psychological counseling theories. Another dataset created by Liu et al.17 is based on 1,053 statements from a dialog system labeled as help-seeker or supporter mode, based on helping skill theory. These previous studies have provided useful references for emotional and social support corpus development. However, the existing collections’ coverage was insufficient in terms of available annotated consumer health questions to train and build efficient systems to answer beyond informational needs.Due to the importance of annotated questions for medical QA research, several efforts have focused on this task and collected some relevant datasetsTo this end, we introduce CHQ-SocioEmo, a manually constructed consumer health questions dataset covering social and emotional support needs. CHQ-SocioEmo was collected from a community question answering forum and therefore it is a valuable resource for understanding non-informational support needs in consumer health-related questions online. The CHQ-SocioEmo dataset consists of (a) various aspects of questions annotated based on demographic information, question focus, emotional states and evidence statement, emotion causes, social support needs and (b) annotated answer based emotional support provided. In addition to releasing CHQ-SocioEmo, we include experiments using baseline and state-of-the-art classification approaches, focusing on identification of social support needs, in order to demonstrate the value of CHQ-SocioEmo and benchmark the dataset for future researchers. The flow of building the CHQ-SocioEmo dataset is shown in Fig. 18. The dataset is made available by Yahoo! Research Alliance Webscope program to the researchers upon providing consent for using data for non-commercial research purposes only. The Yahoo! Answers L6 dataset contains about 4.4 million anonymized questions across various topics along with the answers. Additionally, the dataset provides various question-specific meta-data information such as best answers, number of answers, question category, question-subcategory, and question language. Since the focus of this study is on consumer health, we restricted ourselves to the questions whose category is “Healthcare” and the language is “English”. To further ensure that the questions are from diverse health topics and are informative, we devised a multi-step filtering strategy. In the first step of filtration, we aim to identify the medical entities in the questions. Towards this, we use Stanza19 Biomedical and Clinical model trained on the NCBI-Disease corpus for identifying medical entities. Next, we selected only those question threads with at least one medical entity present in the question. With this process, we obtained 22, 257 question threads from Yahoo! Answers corpus. In the final step, we remove any low-content question threads. Specifically, we retained the questions having more than 400 characters, because longer questions tend to include a variety of needs and background information of health consumers. The final data includes 5,000 question threads.We utilized the popular community question answering, “Yahoo! Answers L6” datasetWe used our own annotation interface for all annotation stages. We deployed the interface as a Heroku application with PostgreSQL database. Each annotator received a secure account through which they could annotate and save their progress. We started with smaller batches of 20 questions, and gradually increased the batch size to 100 questions as the annotators became more familiar with the task. The first 20 questions  were the same among all annotators, so the annotators worked on the task in parallel. Their annotations were first validated on a trial batch, and they were given feedback to help them correct their mistakes. They were qualified for the main annotation rounds after demonstrating satisfactory performance on the trial batch. In addition, group meetings were conducted to discuss disagreements and document their resolution before the next batches were assigned.The following aspects of the questions were annotated:Demographic information includes the age and sex mentioned in consumer health questions.Question Focus is the named entity that denotes the central theme (topic) of the question. For example, infertility is the focus of the question in Fig. 20, annotators label a question with all emotions contained. The annotators were allowed to assign none, one or more emotions to a single consumer health question, for example, a question could be annotated as exhibiting sadness or a combination of sadness and fear. Below are the included emotional states along with their definitions.Sadness: Sadness is an emotional pain associated with, or characterized by, feelings of disadvantage, loss, despair, grief, helplessness, disappointment, and sorrow.Joy: A feeling of great pleasure and happiness.Fear: An unpleasant emotion caused by the belief that someone or something is dangerous, likely to cause pain, or a threat.Anger. It is an intense emotional state involving a strong uncomfortable and non-cooperative response to a perceived provocation, hurt or threat.Surprise. It is a brief mental and physiological state, a startle response experienced by animals and humans as the result of an unexpected event.Disgust. It is an emotional response of rejection or revulsion to something potentially contagious or something considered offensive, distasteful, or unpleasant.Trust. Firm belief in the reliability, truth, ability, or strength of someone or something. That does not include mistrust or trust issues.Anticipation. Anticipation is an emotion involving pleasure or anxiety in considering or awaiting an expected event.Denial. Denial is defined as refusing to accept or believe something.Confusion. A feeling that you do not understand something or cannot decide what to do. That includes lack of understanding or communication issues.Neutral. If no emotion is indicated.Given a predefined set of Plutchik-8 basic emotionsEmotion evidence is a part of the text that indicates the presence of an emotion in the health consumer question, so annotators highlight a span of text that indicates the emotion and cues to label the emotion.Emotion cause is a part of the text expressing the reason for the health consumer to feel the emotion given by the emotion evidence. That can be an event, person, or object that causes the emotion.Alongside, we distinguish between emotion evidence and emotion cause, and we ask annotators to label both accordingly.infertility. As can be seen in this example, the evidence and the causes are not always found within one sentence. The annotation interface, however, ties them together.For example, the sentence, “Do you think my outlook is a good one?”, shown in Fig. 21, social support exchanged in different settings can be classified as follows:Informational support Emotional support Esteem support Network support .Tangible support According to Cutrona and Suhr’s Social Support Behavior CodeExamples of the five social support needs are represented in Table The following aspect of the answers was annotated:Emotional support in the answer. For each answer, annotators had to read the answer and indicate if it is responding to the emotional/esteem/network/tangible support needs by following:Yes: if the answer is responding to the emotional, esteem, network, or tangible support needs. The answers were not judged on the completeness or quality with respect to the informational needs. The text span that cued the annotator to the positive response was annotated in the answer.No: if the answer is not responding to the emotional, esteem, network, or tangible support needs.Not applicable: if questions only seek informational support needs. Thus, no need for the non-informational aspects of the question to be answered.22 was conducted by 9 annotators. It captured three dimensions in state empathy of annotators including affective, cognitive, and associative empathy. According to the instrument, the affective empathy presents one’s personal affective reactions to others’ experiences or expressions of emotions. Cognitive empathy refers to adopting others’ perspectives by understanding their circumstances whereas associative empathy encompasses the sense of social bonding with another person. According to the results shown in Table The annotation task was completed by 10 annotators . As Table 23.To measure inter-annotator agreement (IAA), we sampled 129 questions from the whole collection annotated by three annotators and asked three additional different annotators to annotate the same questions. IAA is calculated using overall agreement. Table The dataset contains a total of 1,500 questions and answers pairs. The questions include 8.8 sentences per health questions, 156.33 words per question, on average, whereas the answers on average include 7.3 sentences per answer and 156.33 words per answer.Distribution of the social support needs is imbalanced with 995 questions seeking informational support, 624 questions seeking emotional support, 207 questions seeking esteem support, 444 questions seeking network support, and 15 questions seeking tangible support. Therefore, we group questions of CHQ-SocioEmo dataset into the three dominant support needs including informational needs, emotional needs, and social needs. Because question counts of tangible support needs are very few compared to other needs, we do not include them in the model. Emotional and esteem support needs were used interchangeably in the literature which are having similar definitions and characteristics. Thus, we group the two types of social support needs, emotional and esteem under the same label.UMLS concepts (and associated semantic types) were extracted from the annotated data using Python (3.10.2), MetaMapLite (3.6.2rc6), and the Python MetaMap wrapper. Concepts were filtered out based on semantic type – only concepts that had at least one relevant semantic type were preserved. We used all the semantic types in UMLS , the details are available in GitHub. No additional cleaning was done on the extracted concepts. R (4.0.2) and RStudio (2022.02.3 + 492) were used for the creation of visualizations.Figure Figure Figure Figure Figure 24. The dataset is saved in JSON format and is organized according to a health consumer question ID. Each question ID is associated with a nested JSON object. This nested object includes a list of annotated aspects of the questions and answers, which contains question focus, age, gender, fine-grained labels of emotions, emotion evidence, emotion cause, types of social support needs in questions and emotional support in answers. The details of each annotated aspect are provided in the README file. Table The Consumer Health Questions Dataset for Social and Emotional Needs (CHQ-SocioEmo) dataset is available through the Open Science Foundation (OSF) at 10.17605/OSF.IO/3DX2SNaïve Bayes. Naive Bayes classifier is a simple classifier that was most commonly used in the field of text classfication25.LSTM. Long Short-Term Memory network (LSTM)26 is a type of Recurrent Neural Networks (RNN) capable of capturing long-term dependencies. LSTM cell can be used in the sequence-to-sequence model to remember the previous words in the sequence. LSTM processes one word at a time, calculating the possible values for the next word in the sequence.BERT. The Bidirectional Encoder Representations from Transformers (BERT)27 which uses encoders in a transformer as a sub-structure to pre-train models for NLP tasks. BERT’s execution of these tasks is divided into two phases: pre-training for language comprehension and fine-tuning for a specific task. BERT was trained using 16GB datasets from Books Corpus28 and the English Wikipedia. BERT has the advantage of being able to handle contextual information extraction due to its bi-directional capability, so it trains faster than other models.RoBERTa. The Robustly Optimized BERT pre-training Approach (RoBERTa)29 is a BERT variant that aims to optimize BERT by tweaking various key parameters in the early form of BERT and training on more data. The model was trained using 160GB of uncompressed text from five English language data sources: the data sources for the BERT model, the CC-News data, the Stories dataset30 and the Open Web data.DistilBERT. Is a distilled version of BERT31, with comparable performance but fewer parameters. DistilBERT employs distillation, a compression technique in which a compact model is trained to mimic the behaviour of a larger model.We conducted a series of experiments using various classification approaches to benchmark the CHQ-SocioEmo dataset and demonstrate how it can be used to automatically identify non-informational or emotional support needs from questions. We used the pre-trained language models that have shown state-of-the-art performance on the various classification tasks.To model the social support needs in CHQ-SocioEmo, we train classifiers to assign one of 3 labels: informational needs, emotional needs, and social needs. We then perform a 60/20/20 split to build the train, validation, and test sets.32. Precision is the fraction of correct (relevant) questions among all extracted questions; and recall is the fraction of successfully extracted questions among all correct (relevant) questions. The harmonic mean of precision and recall is called F1 score. The weighted-F1 score is considered for class imbalance in our corpus which calculates the F1 score for each class independently and when it adds them together uses a weight that depends on the number of correct questions of each class32. The following are equations for the benchmarking metrics:We have evaluated the performance of the classifier using precision, recall and weighted-F1 scoreTP is the true positive count (the number of questions that are correctly extracted), FP is the false positive count (the number of questions that are incorrectly extracted), and FN is the false negative count (the number of correct questions that are not extracted).We present the performance of models in Table Detecting emotions and emotional needs in text is considered a complex task due to many reasons. One reason is that emotions are subjective and differ among people. Treating the same health consumer question, people may feel different emotions according to their own experience. All these reasons make it hard to detect the emotions, which may impact the evaluation and result in lower performance compared to other three-way classification tasks. The state-of-the-art results for emotion detection tasks range from 44.4% to 70.9%. Yet, the DistillBERT model achieves an average F1-score of 0.58 which is higher, compared to the state-of-the-art datasets such as the GoEmotions dataset. Goemotion achieves an average F1-score of 0.46.1, and can be accessed after signing the Yahoo agreements.We have detailed instructions on how to process the CHQ-SocioEmo dataset in the README file provided with the dataset. The data will support other NLP tasks of interest, such as emotion detection, emotion causes, emotion span detection, question focus, etc. We are unable to directly share the Yahoo original questions due to copyright issues, but instead we provide questions IDs. These questions, however, are publicly available here


Herein, weemployed two in vitro BBB models of increasing complexityto investigate the bionano interactions with graphene oxide (GO) andfew-layer graphene (FLG): a 2D murine Transwell model, followed bya 3D human multicellular assembloid, to mimic the complexity of the in vivo architecture and intercellular crosstalk. We developedspecific methodologies to assess the translocation of GO and FLG ina label-free fashion and a platform applicable to any nanomaterial.Overall, our results show good biocompatibility of the two GRMs, whichdid not impact the integrity and functionality of the barrier. Sufficientlydispersed subpopulations of GO and FLG were actively uptaken by endothelialcells; however, the translocation was identified as a rare event.Thanks to their biocompatibility and high cargo capability,graphene-basedmaterials (GRMs) might represent an ideal brain delivery system. Thecapability of GRMs to reach the brain has mainly been investigated  The BBB is an essentialregulatory layer at the neural interface with the brain vasculature,which acts as a selective barrier. The tight junctions forming betweenadjacent cells prevent molecules from moving paracellularly, forcingthem to take a transcellular route for their translocation.19 In the nanosize range, the engagement with the biological membranesallows for active transport mechanisms of internalization and transcytosisthat are compatible with the process of BBB translocation. Althoughthis phenomenon is often observed as a rare event,22 nanomaterialsoffer a plethora of opportunities that might allow boosting the BBBcrossing, such as surface chemistry engineering, downsizing, and hybridconstructs decorated with endogenous motifs.28The idea of exploiting nanomaterials to overcome the BBB hasattractedgrowing interest in the past decade.33In this context, colloidal graphene-based materials (GRMs),withtheir proven biocompatibility and excellent cargo capability, areconsidered very promising.38 Despite a certain consensus, some controversial results can be foundacross the literature, reporting BBB transient disruption or brainaccumulation.40 However, to date, detailed knowledgeof the molecular interactions between GRMs and BBB cells and architectureis missing.41Several reports so far have investigated the biodistributionofvarious colloidal GRMs injected systemically, suggesting that it isunlikely for GRMs to cross the BBB and accumulate in the brain.in vitro investigationof two GRM interactions with the BBB. To this aim, we employed twoGRMs with different surface chemistry and stability, both murine andhuman models of increasing complexity, and a portfolio of complementarylabel-free analytical techniques. The use of label-free strategiesallows the avoidance of fluorescent tag interference and leaching,which makes the results of the bionano interactions hard to interpret.43 The workflow developed in this paper is widely applicable to thestudy of the translocation of different micro- and nanomaterials andrepresents a valuable method to reduce the more expensive and ethicallyconcerning in vivo biodistribution studies.In this work, we performedan Figure S1.45 Reduced graphene oxide (RGO)was also employed for some initial investigations. RGO material isobtained from GO, reduced at high temperatures (800 °C), as describedelsewhere .46 The surface chemistry ofRGO should then be more similar to FLG, but it can still present oxygendefects on the surface. As shown in the Turbiscan analysis of Figure S3, the colloidal stability of RGO inthe biological environment over time was very poor compared to thatof FLG and GO.For this study, two main graphene-based materials (GRMs) were employed:few-layer graphene (FLG) and graphene oxide (GO). These materialspresent similar sizes and morphological features but different surfacechemistry, and their characterization is extensively described inour previous works and also reported in Methods in the SupportingInformation). Cells were incubated with 10 μg/mL of each GRMat different time points. No effects on cell viability, monolayerorganization, cell morphology, or polarization were observed after24 h of exposure, as reported in Figure S4.The first BBB model that we employed was a monolayerculture ofmurine brain endothelial cells (bEnd.3). We initially checked whetherGO and FLG had any detrimental effects on the barrier features, suchas cell viability, morphology, tight junction expression, and barrierfunctionality. For imaging purposes, bEnd.3 cells were cultured onglass coverslips, while functional tests were performed using Transwellmembranes  was alsomeasured upon exposure to the two GRMs, using a fluorescent probe(dextran 4 kDa FITC labeled (FD4); Papp results related to RGO are reported in Figure S7.For bEnd.3 cells cultured on Transwell membranes,the barrier propertieswere assessed by measuring the trans-endothelial electrical resistance(TEER). As shown in 50 For this reason, following the exposure of bEnd.3 cells to eitherFLG or GO, we explored the cell proteome by obtaining label-free high-resolutionLC-MS data on the cell lysates.Previous studies reported theinfluence of pristine graphene andGO on signaling pathways and their role in inducing changes in theexpression and regulation of genes and proteins in various mammaliancells.Supplementary File P1 andcan also be found in the PRIDE database (data set identifier PXD038297).We detected only minor changes in the bEnd.3 proteome following exposureto GO (134 proteins) and FLG (43 proteins), corresponding to about2.6% and 0.8% of the total observed bEnd.3 proteome, respectively.The volcano plots reported in Figure S8 show the proteins (red dots) that were significantly (p < 0.05) altered compared to the total quantified proteome (graydots) for GO and FLG exposure, respectively. The full sets of alteredproteins are reported in Supplementary Files P2 and P3. A subsequent gene enrichmentanalysis failed to highlight any cell process or function significantlyaltered by the exposure to GO or FLG.We quantified a total of 5153protein groups in all three groups, with a total protein abundance profile thatspans over roughly 4.5 logs. The full list of quantified proteinsis reported in Once the persistenceof the barrier functionality and the tightnessof the paracellular spaces under our GRM exposure conditions wereassessed, we then moved to investigate the capability of the two GRMsto cross the BBB through transcellular transport. The stability ofthe GRM dispersion plays a crucial role in the processes of internalizationand translocation.51 Additional representative TEM images are reportedin Figure S9.First, we evaluated the cellular uptake ofGO and FLG. 55 The instability of the RGO suspension in cell culture media  probably affected the material uptake.Due to the absence of uptake after 4 h of incubation , RGO was excluded from the followingexperiments.The presence of such vesicles containing the twoGRMs makes itpossible to measure the uptake in a label-free fashion by measuringthe side scattering (SSC) values by flow cytometry. These values area recognized proxy for the increased cellular granularity upon materialinternalization.Figure S11) and mechanical properties. Indeed, SSC is mainlyinfluenced by the augmented size of intracellular vesicles engulfingmaterials (augmented granularity of the cells), but the influenceof the intrinsic scattering of the internalized material is unclear.For both FLG and GO, the uptake kinetics were evaluatedfrom 2to 48 h, and the measured uptake was already significant after 2 h.For both materials, a plateau was reached after 24 h of incubationwith 10 μg/mL of material, as shown in Figure S3) and tothe different mechanical properties of the aggregates.From a qualitative point of view, by TEM observation, the FLG-treatedsample presented a remarkable number of holes in the cells, correspondingto some visible material accumulation. This might indicate that largeragglomerations of FLG are removed during the microtome slicing process(slice thickness is set as 70 nm). Such observations were less frequentin the case of GO-treated samples, possibly due to the lower dispersibilityof FLG over time . Cells were pretreated for 30min with the inhibitor and exposed to 10 μg/mL FLG and GO for2 h before the evaluation of the uptake by flow cytometry. The resultsfor both GO and FLG internalization pathways are reported in 60For asufficiently dispersed subpopulation of smaller flakes, theendolysosomal uptake pathway might be involved in the internalizationprocess, as for most nanomaterials. Therefore, we evaluated the GRMuptake in the presence of inhibitors of phagocytosis , micropinocytosis , and clathrin-mediated endocytosis .61 Although the quantitative study of the translocationof label-free GRMs is a challenging task, some qualitative observationscan be attempted. As schematically shown in The translocation of fluorescent nanomaterials across the BBB througha transcellular way has been observed.Z-stack images with the light reflection (LR) acquisitionmode at the confocal microscope and positioning in the nuclear planein order to detect flakes internalized in the intracellular space, we could spot some rare LR signals associated with thepresence of graphene materials across the membrane.GO and FLG can be visualized by acquiring three-dimensional ar space3B, to de–1) and G (1580 cm–1) bands with different relative intensities indicating the presenceof GO and FLG.Finally,we analyzed the basolateral fractions of the Transwell.The collected fractions were deposited on glass slides and observedat the optical microscope, where it was possible to spot a few darkagglomerates, as presented in representative insets in Method sectionin the Supporting Information).62We implemented a second, more realistic, humanBBB 3D model basedon human multicellular assembloids (hMCAs). hMCAs were prepared from2D cultures of primary human astrocytes (NHA), human pericytes (hBVP),and human brain endothelial cells (hCMEC/D3) and validated as previouslyreported  images of The assembloids were incubated with 10 μg/mLof either GOor FLG for 24 h. At the end of the incubation, about 50–90organoids per condition were collected, washed to remove the excessexternal GO and FLG, fixed, and sliced at the cryostat. The slicingprocedure allowed accessing the hMCA core for further confocal analysis. Methods in the Supporting Information, was developedin house and validated using prestained NHA and hBVP that allowedseparating clusters for the three cell populations, as shown in We decided to complement ourobservations by employing flow cytometryand TEM imaging, as done in the 2D murine model. To evaluate the uptakeof materials in the different layers of hMCA by SSC by flow cytometry,we dissociated the hMCAs after incubation with either GO or FLG andwashing steps, as illustrated in Figure S14). Theseagglomerations are localized in cells situated at the periphery ofthe slice that, according to the architectural organization of hMCA,correspond to the endothelial cell layer. No sign of GO and FLG inthe internal core was found by TEM analysis. Even in this case, itcan be noticed how FLG (and not GO) produced bigger/stiffer agglomerates,producing holes when encountering the blade during the microtome slicingprocedure.TEM analysis further confirmed these observations.Although themicrographs depicted in in vitro models of increasing complexity hasbeen thoroughly investigated. GO and FLG do not induce any obviousharm to the BBB cells in terms of viability, tight junction expression,barrier morphology, and functionality, adding an essential brick tothe safe use of graphene in neuroscience. However, despite their excellentcargo capability and ease of functionalization, our GRMs do not seemto be promising carriers for BBB translocation.The interaction of two different colloidal GRMs,GO and FLG, withBBB in In this work,we employed an array of complementary techniques,all label-free, to study GO and FLG behavior in 2D and 3D models ofBBB. By means of confocal microscopy, flow cytometry, and electronmicroscopy, we found that graphene is internalized by endothelialcells, depending on its dispersion state, in large vesicles, whichis compatible with the micropinocytosis uptake mechanism. However,the export and the cell-to-cell exchange of this material rarely occur,especially in more sophisticated models of primary human cells mimickingthe complexity of the 3D BBB architecture.in vivo investigations. This work, complementing the existing in vivo literature, can contribute to guiding the graphenecommunity to focus their efforts toward graphene use more orientedto regenerative medicine, prosthetics, and sensors, rather than purenanomedicine.66The workflow developedhere can be applied to any fluorescent orlabel-free nanomaterial and will ensure thorough screening of potentialnanocarriers to the brain, bypassing costs and ethical concerns of


Such graphene film also exhibits a superhigh electromagnetic interference shielding effectiveness of ∼90 dB at a thickness of 10 μm, outperforming all the synthetic materials of comparable thickness including MXene films. This work not only paves the way for the technological application of highly conductive graphene films but also provides a general strategy to efficiently improve the synthesis and properties of other carbon materials such as graphene fibers, carbon nanotube fibers, carbon fibers, polymer-derived graphite and highly oriented pyrolytic graphite.Fabricating highly crystalline macroscopic films with extraordinary electrical and thermal conductivities from graphene sheets is essential for applications in electronics, telecommunications and thermal management. High-temperature graphitization is the only method known to date for the crystallization of all types of carbon materials, where defects are gradually removed with increasing temperature. However, when using graphene materials as precursors, including graphene oxide, reduced graphene oxide and pristine graphene, even lengthy graphitization at 3000°C can only produce graphene films with small grain sizes and abundant structural disorders, which limit their conductivities. Here, we show that high-temperature defects substantially accelerate the grain growth and ordering of graphene films during graphitization, enabling ideal AB stacking as well as a 100-fold, 64-fold and 28-fold improvement in grain size, electrical conductivity and thermal conductivity, respectively, between 2000°C and 3000°C. This process is realized by nitrogen doping, which retards the lattice restoration of defective graphene, retaining abundant defects such as vacancies, dislocations and grain boundaries in graphene films at a high temperature. With this approach, a highly ordered crystalline graphene film similar to highly oriented pyrolytic graphite is fabricated, with electrical and thermal conductivities (∼2.0 × 10 The high-temperature defects induced by nitrogen doping significantly accelerate the grain growth and ordering of graphene films during graphitization, enabling highly-oriented-pyrolytic-graphite-like highly conductive films. Graphene is well known for its extraordinary in-plane electron and phonon transport on a honeycomb lattice . Transfe2O, CO and CO2 during the thermal annealing process. The resulting structure expansion prohibits grain growth and ordering of the graphene film during graphitization. As alternative precursors, graphene materials with less functional groups, such as reduced GO (rGO) [Graphene oxide (GO) ,21–23 isGO (rGO) , a mixtuGO (rGO) , pristinGO (rGO)  and evenGO (rGO) , have beGO (rGO) . NeverthGO (rGO) , which a4 S cm−1; ∼1.7 × 103 W m−1 K−1) of the resulting graphene films are approximately six and two times better, respectively, compared to those fabricated by the commonly used GO precursor. Such a graphene film also exhibits a superhigh EMI-shielding effectiveness (SE) of ∼90 dB at a thickness of 10 μm, outperforming all synthetic materials of comparable thickness, including MXene films.Here, we show that nitrogen doping can retard the restoration of defects in graphene films below 2000°C and therefore retain abundant vacancies, dislocations and GBs at the beginning of graphitization. Such high-temperature defects substantially accelerate the grain growth and ordering of graphene films during graphitization, producing a HOPG-like highly crystalline film with electrical and thermal conductivities approaching the limit of single-crystal graphite within 10 min of graphitization at 3000°C. From 2000°C to 3000°C, the grain size of graphene films increases 100-fold, along with well-ordered AB-stacked layers being formed, leading to a 64- and 28-fold increase in electrical and thermal conductivities, respectively. The electrical and thermal conductivities  and elemental analysis were used to monitor the evolution of carbon, oxygen and nitrogen species in the films during annealing Fig. . Notably2 graphene domains surrounded by oxidized sp3 regions that are decorated by epoxide and hydroxyl groups on their basal plane, and its edges are decorated with carbonxyles and carbonyls [2O, CO and CO2 to generate a great number of vacancies in the carbon lattice, corresponding to the increased intensity ratio of D peak to G peak (ID/IG) at 1000°C. However, the ID/IG significantly declines from 1000°C to 2000°C, indicating that the in-plane defects are well-repaired below 2000°C  for disordered turbostratic stacking, while AB stacking leads to an asymmetrical 2D peak composed of two subpeaks at ∼2680 cm−1 of (2D1) and ∼2720 cm−1 (2D2) [We then studied the structure evolution of N-rGO and GO films during annealing from 2000°C to 3000°C. The Raman 2D peak, as the second harmonic of D peak, is usually used for measuring the degree of stacking order. A symmetrical 2D peak appears at 2700 cm−1 (2D2) ,29. As sTherefore, we further characterized the in-plane and through-plane microstructures of GO and N-rGO films after 2000°C annealing by using scanning tunneling microscopy (STM) and HRTEM, respectively. For the N-rGO films, nanometer-STM images show many edges Fig. , which aLa). X-ray diffraction (XRD) has been previously used to evaluate the through-plane grain size (Lc) of graphene films and other carbon materials based on the Scherrer equation [Lc, such as experimental resolution, grain shape, grain size distribution, degree of stacking order, microstrain and other defects [Lc.Bright-field TEM (BF-TEM), annular dark-field scanning TEM (ADF-STEM), HRTEM and scanning electron microscopy-electron channel contrast (SEM-ECC) imaging were then used to record the evolution of the graphite grain in N-rGO films during the graphitization process above 2000°C Fig. . In SEM-equation ,13,22,34 defects . Thus, A defects . As a reLc   decreases from ∼85.1% to 29.4%, the AB-stacking ratio increases to 45.8%, and the electrical and thermal conductivities increase ∼26 and 17 times, respectively. More importantly, Lc and La further enlarge ∼5- and 14-fold, respectively, and Pdisorder further decreases by ∼4 times with ideal AB stacking being formed, as the temperature increases from 2500°C to 3000°C. Accordingly, the electrical and thermal conductivities are further increased 2.5- and 1.7-fold, respectively. In total, the grain size, electrical conductivity and thermal conductivity are increased 100-, 64- and 28-fold, respectively, during graphitization from 2000°C to 3000°C.We further quantified the evolution of ges Fig. . At the ata Fig. , performDT) Fig. , and meaDT) Fig. . NotablyLc is increased only ∼9-fold in total, along with a moderate decrease in Pdisorder from 84.0% to 28.7% and a subtle improvement in crystallinity   . All theIt is well accepted that AB stacking is the most thermodynamically stable structure of graphite, while stacking faults and rotational mismatch can induce significant interlayer strain energy, which results in the crystals having a high-energy metastable state . Previou−3. These structural features are significantly different from those of the GO-derived graphene films, which feature abundant wrinkles, kinks and voids , giving strong evidence of grain growth through interlayer migration and arrangement of carbon atoms, as discussed above.Using the high-temperature defect-enabled highly efficient graphitization approach, we fabricated large-area HOPG-like graphene films with N-rGO as precursor Fig.  and 15. nd voids . Althougnd voids . Moreovend voids . Meanwhind voids , and thend voids . Notably μm Fig. , respect μm Fig. . It is a2 structure  indicate predominant AB stacking with only ∼8.8% turbostratic-stacked regions  and single-crystal graphite (∼2.5 × 104 S cm−1 and ∼2.0 × 103 W m−1 K−1) [For graphene-based materials, heat conduction mainly depends on the phonon transport from lattice vibrations of the spne layer ,11. It hne layer ,11, degrm−1 K−1) .Emerging 5G devices can provide ultrafast data transmission rates, more reliable and ubiquitous communications and ultralow latency, allowing various innovative services such as smart cities, the Internet of Things, artificial intelligence and satellite services ,9. Howev3CNTx MXene film is the best known EMI shielding material with EMI SE values of ∼75, 83, 97 and 116 dB at a thickness of 10, 20, 30 and 40 μm [−1 K−1 [Tind 40 μm , respect [−1 K−1 ). We mea [−1 K−1 . Signifiin-situ experiments such as TEM observations, which is essential for precise control of the structure of graphene films.Our work provides a new strategy to substantially accelerate the graphitization of graphene films by using N-doping to retain high-temperature defects, leading to significant improvements in their crystallinity, ordering, electrical and thermal conductivities, and EMI shielding performances. These findings pave the way for the practical application of graphene films to meet the rapid advancement of electronics and telecommunications. In principle, other heteroatoms—which can substitute the carbon atoms in a graphene lattice, hinder the restoration of defects and then be removed at elevated temperatures—could also be used to realize high efficiency graphitization. More generally, graphitization is the only method, known to date, for the crystallization of other types of carbon materials , includinwad147_Supplemental_FileClick here for additional data file.