Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence (AI)-based language processing model using deep learning to create human-like text dialogue. It has been a popular source of information covering vast number of topics including medicine. Patient education in head and neck cancer (HNC) is crucial to enhance the understanding of patients about their medical condition, diagnosis, and treatment options. Therefore, this study aims to examine the accuracy and reliability of ChatGPT in answering questions regarding HNC.154 head and neck cancer-related questions were compiled from sources including professional societies, institutions, patient support groups, and social media. These questions were categorized into topics like basic knowledge, diagnosis, treatment, recovery, operative risks, complications, follow-up, and cancer prevention. ChatGPT was queried with each question, and two experienced head and neck surgeons assessed each response independently for accuracy and reproducibility. Responses were rated on a scale: (1) comprehensive/correct, (2) incomplete/partially correct, (3) a mix of accurate and inaccurate/misleading, and (4) completely inaccurate/irrelevant. Discrepancies in grading were resolved by a third reviewer. Reproducibility was evaluated by repeating questions and analyzing grading consistency.ChatGPT yielded “comprehensive/correct” responses to 133/154 (86.4%) of the questions whereas, rates of “incomplete/partially correct” and “mixed with accurate and inaccurate data/misleading” responses were 11% and 2.6%, respectively. There were no “completely inaccurate/irrelevant” responses. According to category, the model provided “comprehensive/correct” answers to 80.6% of questions regarding “basic knowledge”, 92.6% related to “diagnosis”, 88.9% related to “treatment”, 80% related to “recovery – operative risks – complications – follow-up”, 100% related to “cancer prevention” and 92.9% related to “other”. There was not any significant difference between the categories regarding the grades of ChatGPT responses (p=0.88). The rate of reproducibility was 94.1% (145 of 154 questions).ChatGPT generated substantially accurate and reproducible information to diverse medical queries related to HNC. Despite its limitations, it can be a useful source of information for both patients and medical professionals. With further developments in the model, ChatGPT can also play a crucial role in clinical decision support to provide the clinicians with up-to-date information. The Chat Generative Pre-trained Transformer (ChatGPT) is a recent AI model, designed to generate human-like conversational dialogue in response to textual input by predicting answers from a vast database of publicly undisclosed resources including websites, books, and articles up to 2021 . It is fHead and neck cancer (HNC) ranks as the seventh most common form of malignancy globally, with an annual incidence of approximately 660,000 new cases , 12. Ala2Institutional review board approval was not sought for this prospective study due to the absence of patient-level data. Authors have no affiliation or involvement with OpenAI Inc., the developer of ChatGPT.2.1The data set of questions was compiled from queries frequently posted by professional institutions and societies such as the American Head & Neck Society (AHNS), National Cancer Institute, and the Medline Plus Medical Encyclopedia. In the interest of inclusivity and patient representation, questions sourced from patient support groups and social media posts were incorporated. These questions underwent a rigorous screening process by three authors to evaluate their eligibility for inclusion in the study. The selected questions pertained specifically to HNC. Exclusion criteria were implemented to disqualify questions with similar meanings, questions that were subjective or could vary between patients , vague inquiries , and non-medical questions related to the condition   basic knowledge, (2) diagnosis, (3) treatment, (4) recovery, operative risks, complications and follow-up (5) cancer prevention, and (6) other. Grammatical adjustments were made to certain questions to ensure clarity and precision.The selection was predominantly patient-oriented, seeking to evaluate the AI model’s ability to provide information to potential patient inquiries . Additionally, we included questions featuring technical medical terminology to simulate scenarios that patients might encounter during their medical journey . Complex questions were also included to assess the model’s capacity to assist medical professionals .2.2In this study, we used ChatGPT Plus , an advanced subscription-based version of ChatGPT that was released in November 2022. The questions were submitted on June 13, 2023. Each question was entered independently using the “New Chat” function. In alignment with previous studies, each question was entered twice to assess the reproducibility of ChatGPT’s responses , 10. Cha2.3Two experienced head and neck surgeons, currently active in academic practice, independently reviewed and graded the responses to questions for accuracy and reproducibility. The reviewers evaluated the accuracy of responses according to the following scale2.3.1Data is accurate and comprehensive; a head and neck surgeon would add no further information if asked by a patient.2.3.2The provided data is correct; however, additional pertinent information could be provided if asked by a patient.2.3.3Contains accurate and inaccurate data, potentially misleading.2.3.4The data provided is completely inaccurate or irrelevant.Reproducibility was assessed based on the consistency of the two responses to each individual question. If the responses were similar, only the first response from ChatGPT was graded. In cases where the responses differed, both were independently graded by the reviewers. If the grades differed, the responses were deemed non-reproducible. Any discrepancies in the accuracy and reproducibility of responses between the two reviewers were independently reviewed and resolved by a third reviewer, a highly experienced academic head and neck surgeon, who was blinded to the initial reviews. Reproducibility was evaluated for each category of questions and compared between categories.2.4The proportions of each grade among the responses were calculated and reported as percentages. Categorical variables were examined using the χ2 test and Fisher’s exact test. The kappa statistic was used to measure inter-rater agreement, revealing a substantial agreement between Reviewers 1 and 2 . All analyses were performed using IBM SPSS v.25.0 (IBM Corp.).3A total of 154 inquiries pertaining to HNC were directed to ChatGPT. The model provided “comprehensive/correct” responses to 133 out of 154 (86.4%) questions. Meanwhile, the rates of “incomplete/partially correct” and “mixed with accurate and inaccurate data/misleading” responses were noted to be 11% and 2.6%, respectively. It is significant to note that there were no instances of “completely inaccurate/irrelevant” responses.Questions were categorized as follows: basic knowledge , diagnosis , treatment , recovery - operative risks – complications – follow-up , cancer prevention  and other .Overall, the reproducibility rate of the model was 94.1% (145 questions). Reproducibility was 100% for the categories of basic knowledge, cancer prevention, and other. However, this rate decreased to 88.9% for diagnosis, 88.9% for treatment, and 92.5% for recovery – operative risks – complications – follow-up categories  to the same queries . The finOur findings indicate that the majority of responses from ChatGPT were accurate, with 86.4% of receiving a “comprehensive/correct” rating on our grading scale. Importantly, none of the responses were classified as “completely inaccurate/irrelevant”. Furthermore, the model demonstrated high reproducibility across all topics, and performed commendably without any significant differences between them. Our study may provide an early evidence base demonstrating the immense potential of this innovative platform in the field of AI-driven medical information, specifically concerning HNC. With additional validation, ChatGPT or similar tools could serve as invaluable resources for rapid medical information retrieval in high-speed clinical settings, thereby enhancing efficiency and aiding clinicians in their complex decision-making processes. However, we are only in the early stages of the era of AI-provided medical services, and it is currently not advisable to rely solely on the existing version of ChatGPT as the only source of medical information. With the advent of newer versions that are appropriately trained by medical experts using the most current medical literature, accurate medical information could be rapidly disseminated to both patients and medical professionals.To the best of our knowledge, this is the first study investigating the application of ChatGPT in the field of HNC as of July 2023. The questions incorporated in our study were sourced from reputable institutions and societies, as well as patient support groups. The assessment of accuracy and reproducibility was conducted by independent evaluators. However, it is necessary to acknowledge the limitations inherent in both the ChatGPT model and our study. Pertaining to ChatGPT, the current version’s knowledge cutoff is up to September 2021. Omission of data from the past two years could potentially impact the precision of the responses. Furthermore, the reliability of ChatGPT is fundamentally contingent upon the quality of the training data. Hence, given the undisclosed sources of the model, it remains questionable whether the training was based on the most reliable and accurate medical literature. Thirdly, the latest version of ChatGPT, which exhibits superior performance compared to the publicly available version, is accessible only via paid subscription, potentially constraining the public’s access to more accurate knowledge.In relation to our study, we utilized a grading method similar to those employed in previous studies , 10. How5ChatGPT has proven to generate markedly accurate and reproducible responses to a wide range of medical inquiries pertaining to HNC. Despite its inherent limitations, it may serve as a beneficial source of information for both patients and healthcare professionals. As the model undergoes further refinement, ChatGPT could potentially assume a vital role in clinical decision support, equipping clinicians with current information. It is imperative that future research efforts strive to delineate the risks and benefits of employing this AI model in the context of HNC, as well as in diverse medical domains.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.OK: Conceptualization, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing. AP: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. NS: Project administration, Supervision, Validation, Visualization, Writing – review & editing. SH: Investigation, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing.


Interestingly, the non-equidistant and nonlinear properties of LLs of graphene in the presence of a magnetic field which make it a promising material for various optoelectronic applications arises from its linear energy dispersion relation4. It is well-known that the zero-gap Dirac cones in the linear energy spectrum of graphene give rise to observation of the unconventional quantum Hall conductivity in the presence of a magnetic bias applied normally to its surface5.Under a normally applied magnetic field, unlike conventional 2D electron gas (2DEG) systems, the Landau levels (LLs) in 2D Dirac materials are not equally spaced and vary non-linearly with the field modulations. This could significantly affect the absorption properties of 2DEG systems with Dirac spectrum. Graphene, a 2D material composed of carbon atoms arranged in a honeycomb pattern, has attracted huge attention due to its exceptional electronic and optical properties10, the primary phenomenon is the absorption of incoming electromagnetic waves through materials and converting them to electrical current. The absorption of materials could be considered due to the electronic excitations in near-infrared and visible, phonons’ local vibrational modes in mid-infrared, and collective modes in terahertz regime11. However, the absorption of electromagnetic waves in a atomically 2D materials is generally insufficient for real-world applications. Therefore, developing innovative methods to enhance the absorption of them is an essential step toward improving its optical absorption properties.Now, the absorption of light is being studied to understand how electromagnetic waves can be harvested to stimulate electrons in materials. For instance, in optical sensors and solar cells16 to trap waves in an optical cavity and excitation surface plasmonic resonances19. Now, since these approaches are highly dependent on the structure, absorption is typically limited to a narrow electromagnetic spectrum. As a result, additional techniques are needed to achieve perfect absorption in a more straightforward and tunable manner. Here, coherent perfect absorption (CPA) is a promising concept to address these challenges. The underlying principle behind CPA is making standing waves by interfering with two beams with tuned frequency to trap electromagnetic energy onto the absorber and surpassing the scattering matrix. Therefore, the perfect absorption could be accessible by tuning the phase modulation of two incident beams21. Graphene, as a one-atom-thick 2D material, in the visible and near-IR zone under normal incidence could absorb only From a theoretical standpoint, the maximum absorption of a 2D material is 22. Fan et al., calculated the CPA frequency required to maintain perfect absorption. They considered monolayer graphene and illuminated it with two coherent beams. By finding the appropriate values for |r| and |t| to suppress the scattering matrix, they obtained a CPA frequency of 1.735 THz for doped monolayer graphene  in the mid-infrared and terahertz ranges. Rao et al., showed 80% modulation of light through the CPA concept. They employed unstructured multilayer graphene as an absorber in their setup and employed a continuous wave laser source  situation. To be more, specific, applying a magnetic field to the surface of graphene can introduce nonlinear Landau energy levels in its linear spectrum. This leads to a Hall term in the tensor of its magneto-optical conductivity which could significantly alter CPA conditions in QHE regime. In this work, for the first time, we propose that introducing a magnetic bias field into the unstructured monolayer graphene results in a magneto-tunable CPA at both sub-tesla and high field levels for RHC and LHC polarizations in THz regime. Our results could pave the way for magnetically tunable perfect absorber devices and ultrafast graphene-based quantum magnetometers.Up to now, the coherent absorption in graphene can be tuned substantially by varying the gate-controlled Fermi energy level which control the optical transitions of graphene. Optical conductivity of graphene is also a function of the illuminating frequency and the electron relaxation time. Some efforts have been made to change the Fermi level of graphene through chemical doping or applying voltagez-direction by two circularly-polarized coherent counter-propagating beams, 28. Both longitudinal and Hall conductivity terms could be obtained by the use of the Kubo formula:3:Our model is schematically proposed in Fig. In order to investigate the effect of magnetic field on magneto-CPA properties of graphene, we first calculate the transmission and reflection intensities for two sets of magnetostatic bias fields. As it is shown in Figs. Considering LHC polarized modes, as shown in Fig. entclass1pt{minimaentclass1pt{minimaentclass1pt{minimaentclass1pt{minimaFor the magnetic bias below The absorption of two LHC polarized coherent electromagnetic beams is shown in Fig. Now, we turn our attention to the low field limit for highly doped graphene. As illustrated in Fig. In conclusion, we prove that monolayer graphene could exhibit THz CPA in the QHE regime for circularly polarized radiations. Also, tunable property of quasi-CPA frequency corresponding to right- and left-handed modes by the intensity of the applied magnetic field was simulated. Moreover, at CPA frequencies, the two circularly polarizations revealed different phase modulations for an applied magnetic field intensity. It was demonstrated that two or even more CPA frequencies with different properties could be emerged for left-handed modes. Interestingly, it was shown that increasing the magnetic field bias for right-handed (left-handed) polaized beam red-shift (blu-shift) the CPA frequency. We also examined CPA properties at subtesla magnetic fields and found that the CPA frequency could be modulated ranging from about 1.4 to 2 THz. It was then revealed that our results at low magnetic field could recover earlier CPA conditions reported for graphene in the absence of an applied magnetostatic bias. The physics behind our results could be much more clear by analyzing Supplementary Figures.


We show thatwhile the ionic type and concentration alter the initial doping stateof graphene, they have no measurable influence over the rate of thedoping of graphene with applied voltage in the high ionic strengthlimit of 3–15 M. Crucially, unlike for conventional dielectricgates, a large proportion of the applied voltage contributes to theFermi level shift of graphene in concentrated electrolytes. We providea practical overview of the doping efficiency for different gatingsystems.Electrostatic gating using electrolytes is a powerfulapproachfor controlling the electronic properties of atomically thin two-dimensionalmaterials such as graphene. However, the role of the ionic type, size,and concentration and the resulting gating efficiency is unclear dueto the complex interplay of electrochemical processes and charge doping.Understanding these relationships facilitates the successful designof electrolyte gates and supercapacitors. To that end, we employ  EF). Since the first measurementof the electric field effect in graphene using a dielectric back gate,1 various electrostatic gating approaches havebeen used to study unique electronic properties of graphene.4 During nearly two decades of research, it has become apparent thatgating using ionic electrolytes, including organic/aqueous solutions,ionic liquids, and solid polymer electrolytes, is among the most efficientways to induce large densities of charge carriers in graphene.7 However, few systematic overviews exist of how various gate systemsdiffer in their efficiency to induce electrostatic doping in graphene,particularly in the case of aqueous electrolytes.The linear dispersion relationshipbetween the energy and momentum of the charge carriers centered aroundthe Dirac point makes graphene a zero-gap semiconductor with a lineardependence of the density of electronic states (DOS) on the Fermilevel , and adiabatic contributionsof the changes in the lattice equilibrium parameter and coupling ofphonons to higher energy transitions.16 For carrierdensities corresponding to |EF| > 98meV,the G mode stiffens almost symmetrically for both electron and holedoping. For carrier densities close to the Dirac point, the contributionof the phonon anomaly to the G mode frequency is mostly smeared outat room temperature, and only small changes can be observed.9 However, the strong electron–phonon coupling at small |EF| also causes phonons to decay into electron–holepairs, giving rise to a shorter lifetimes and thus larger full widthsat half-maximum (fwhm). For Fermi energies away from the phonon anomaly,the phonon decay is blocked according to the Pauli exclusion principle,17 and the G mode fwhm sharply decreases.For high doping levels, the intensity of the G mode sharply increasesdue to the partial blocking of the destructively interfering electronictransitions.18 The behavior of the 2D mode is also governed by the electron–phononcoupling and lattice expansion/contraction upon doping; however, thecontribution of the former is smaller and the resulting 2D mode frequencyshifts are markedly more asymmetric for electron/hole doping. The2D mode is further influenced by the doping-dependent electron-electronscattering rate, which causes the intensity decrease and fwhm broadeningupon carrier density increase.19 Furthermore,Raman spectroscopy also provides information about the structuraldefects, mechanical strain, and functionalization of graphene.20The explanation of the dependence of the Raman spectra ondopingis not trivial and comprises the strong nonadiabatic coupling of phononsto electronic transitions across the gapless bands of graphene nearthe Dirac point, where |21 which uniquely affects the operation of thegate, as we will describe in detail later. Since the solid-state dielectricshave capacitances several orders of magnitude smaller (∼10–9–10–8 F cm–2) than those of the ionic electrolytes (∼10–6–10–5 F cm–2), substantiallylarger voltages are required to achieve the same carrier densitiesusing the former (∼10–100 V) than the latter (∼0.1–1V).6 However, it is difficult to accuratelydetermine the gate capacitance, and therefore resulting doping effect,of an electrolyte gate due to uncertainty in the relative permittivityand Debye screening length. Moreover, the interpretation of the behaviorof ions at the interface is a complex issue involving multiple effects.The type of electrolyte, ionic strength, and charge scattering haveall been shown to affect the carrier density in graphene.25 Furthermore, concentrated electrolytes exhibit anomalous behavior,which leads to a breakdown of the classical decay relationship betweenthe Debye screening length and ionic concentration.27 However, as we show here, the complexity of the interaction betweenthe ionic species and graphene in terms of the resulting carrier densityis in fact greatly reduced in highly concentrated aqueous electrolytes,when an external voltage is forced through the system.The operating principle of electrostaticgating involves the creationof a capacitor between graphene and the gate electrode. The totalcharge built up in this capacitor, which determines the extent ofelectrostatic doping in graphene, is proportional to its capacitance.Furthermore, the low DOS of graphene gives rise to quantum capacitance,In thiswork, we study the electrostatic gating of graphene andits efficiency using various aqueous electrolyte solutions of differentconcentrations. We investigate the shift rate in the Raman G modeof graphene, which is directly proportional to its Fermi level andtherefore to the extent of doping, with the applied gate voltage.Our results show that the extent of charge doping of graphene is nearlyidentical for a range of highly concentrated electrolytes irrespectiveof their ionic strengths. Furthermore, we provide a general overviewof the gating efficiency dependence on the gate capacitance and appliedvoltage in different gate media.in situ Raman spectroelectrochemistryof electrolyte-gated monolayer graphene in a microdroplet electrochemicalcell, as shown schematically in 4, Zn(ClO4)2, AlCl3, Al(ClO4)3, and Al(NO3)3. Monolayergraphene prepared by chemical vapor deposition was transferred ontoa 300 nm SiO2/Si substrate and characterized by opticalmicroscopy and Raman spectroscopy with 1.96 eV laser excitation . The main Raman modes ofgraphene were observed: G at ∼1587 cm–1 and2D at ∼2653 cm–1. A microdroplet of electrolyte,10–20 μm in diameter, using a potential in the rangeof −0.6 to 1.2 V vs Ag/AgCl, was formed with the help of amicrocapillary (see Supporting Information for further details). One of the main advantages of the microdropletmeasurements is the small current passed through the electrode, whichreduces the undesirable contribution of uncompensated resistance tothe applied voltage.We perform G, in cm–1) as a function of the applied electrode potential (μ). Theelectrostatic interactions between the electrolyte ions and grapheneincrease the density of electrons or holes in graphene, dependingon the applied potential. The increased density of either of the carriertypes leads to the stiffening of the G mode of graphene from its minimumdoping value (ωCNP) at the charge neutrality point(CNP) where the carrier density is zero .8 We then subtract the CNP potential  fromμ to define the gate voltage, Vg = −(μ – μCNP), and plot theshift of the G mode frequency from its minimum at the CNP (ΔωG = ωG – ωCNP) asa function of Vg.For each electrolyte type and concentration, wemeasured the spatialfrequency of the Raman G mode  was calculated to be 23.0 ± 0.8 cm–1 V–1 considering all the hole dopingdata in Vg from 0.2 to1.4 V. The very narrow confidence limit implies that the ionic typeand concentration have a negligible effect on the extent of the electrostaticgating of graphene in concentrated aqueous electrolytes.dΔωG/dVg values fordifferent electrolyte solutions in I = 1/2∑i = 1ncizi2, where ci and zi are the concentration and charge of theion i, respectively). These striking observationssuggest that, for a given Vg, the electrolytegating establishes electrical double layers with similar electrostaticdoping efficiencies, irrespective of the type, concentration, andcharge of the electrolyte ions. We also found the electrostatic gatingusing concentrated electrolytes to be reversible. G for the forward  and reverse gating using 6 M LiCl and 2.4M Al(ClO4)3. The change in ωG with potential exhibits only a negligible hysteresis during thehole doping.Thisbecomes even more apparent when comparing the G minimum on the applied potential axis clearlyvaries, as seen in Supporting Figures S2 and S3. There are severallikely origins of these shifts. First, the potential of the Ag/AgClreference electrode used here depends on the chloride concentration,which is largely unknown in nonchloride electrolytes, and the appliedpotential will therefore vary by 59 mV for each 10-fold change inchloride concentration.28 Second, specificinteractions of different types of ions at the graphene surface willdetermine the initial doping state before the application of potentialas reported earlier.24 Third, charged impurities ortrapped transfer residues change graphene’s surface potentialand facilitate Coulombic scattering of carriers in graphene,30 which are, in turn, screenedby the surrounding media, including electrolytes.32While the effect of the gate voltage on dopingis independent ofthe type and concentration of the electrolyte, the absolute positionof the ω4)3 aqueous electrolyte. Wealready discussed the upshift of the G mode frequency with the holedoping, which is shown to increase by 39.3 cm–1 from0.0 to 1.6 V in Vg. Specifically, the G mode intensityincreases upon hole doping  and the outgoing photon energy (Eex – ℏΩG). The term ℏΩG, where ℏ is the reduced Planck constant and ΩG is the angularfrequency of the G mode, represents the energy of the scattered phonon.18 This G mode intensity maximum therefore corresponds to 2|EF| = Eex – ℏΩG/2 = 1.861 eV and |EF| = 0.930 eV, where ℏΩG/2 = 98 meV for our minimum ofΩG . The increase of the G band intensity at 2|EF| = Eex – ℏΩG/2 is caused by blocking electronictransitions due to filling (emptying) states in the conduction band, thereby canceling part of the destructively interfering Ramanpathways.18 Although we do not reach a clear maximumin Vg of 1.6 V, which we therefore tentatively assignas corresponding to EF of −0.930eV. We also note that the exact value of the EF, at which the G band intensity reaches the maximum, willbe slightly more negative than the value simply determined from 2|EF| = Eex – ℏΩG/2 due to electron-hole asymmetryof the band structure in the K-M direction.18Supporting Information. The fwhm of the G mode decreases with an increase in both electronand hole density in graphene for small gate voltages, as shown in Supporting Figure S4, which is consistent withprevious studies.17 The correlation between the 2D and G mode frequencies and the dependenciesof the 2D mode fwhm and the 2D/G mode intensity ratio on potentialare shown in Supporting Figures S4 and S5.We also recorded other parameters as a functionof gating, whichare reported in the EF with respect to the Diracpoint 33 The gating process can be described by the following relationship:21e is the elementarycharge. EF of graphene depends on itscharge carrier density  and Fermi velocity vF as follows:34q = ne) and gate capacitance (Cg):8Let us now discuss the mechanism of the electrostatic dopingbythe electrolyte gate. Before applying the gate voltage, the ions arerandomly distributed in the solution as shown schematically in Cg is equivalent withthe electricaldouble-layer capacitance (CEDL) for anelectrolyte gate. The high concentration of ions in concentrated electrolytesresults in efficient charge screening, which compresses the EDL toa typical width of ca. 1 nm corresponding to the Debye length (λD).27 This createsan efficient gate capacitor capable of inducing sizable charge carrierdensities in graphene with only moderate voltages, as discussed earlier.The resulting CEDL of this capacitor,normalized per unit area, is inversely proportional to λD and can be approximated as0 is the vacuum permittivityand ϵr is the relative permittivity of the electrolytesolution.CQ), arising from the low DOS and, subsequently, inefficientcharge screening in graphene. CQ is aspecial case of the space charge capacitance for a two-dimensionalelectron gas system.21 For EF (relative to the Dirac point), which is substantiallylarger than the thermal energy kT, quantum capacitancecan be approximated as follows:35In order to understand the electrostatic doping ofgraphene, onealso has to consider the quantum capacitance  who used a first-principles approachto determine the derivative of charge with respect to potential. Thelinear fit of the latter data (excluding a nonlinear region within100 mV of the Dirac point) yields a slope nearly 2 times larger thanthat calculated from vF in 29 (purple) showa significant deviation from both calculations around the Dirac pointbut convergence toward the Zhan et al. data at the highest potentials.While most reports agree that G on EF, which reflects the strength of the electron-phononcoupling in graphene9 and allows for adetermination of the Fermi level of graphene using Raman spectroscopy. G dependences on the Fermi level of graphenereported by Froehlicher and Berciaud (yellow),9 Das et al. (red),8 Chen et al. (blue),11 and our data (green) based on the estimate of EF = 0.930 eV at the maximum ΔωG = 39.3 cm–1 (and EF = 0.0 eV at ΔωG = 0.0 cm–1) for 2.4 M Al(ClO4)3 electrolyte. Note thatDas et al.8 reported a ΔωG – EF dependence with twolinear segments of differing slopes. The discrepancies in the determinationof the ΔωG dependence on EF in EF from Vg according to 9 employed a dual-gate setup and the known dielectriccapacitance to determine CEDL, while Daset al.8 used r and λD to accomplish the same. Importantly, allof these reports (including ours) neglect the dependence of CEDL on Vg, whichwill inevitably dictate the exact nature of these relationships. Inreality, CEDL is known to depend nonmonotonouslyon potential in different electrolytes and at different surfaces,with a several-fold difference between the lows and highs.38From a practical perspective, it is particularlyuseful to evaluatethe dependence of ΔωVg is split among compensating for the initial doping of graphene EF), and charging of the interface(ϕ). A clear distinction between EF and ϕ as depending on quantum capacitance and gate capacitance,respectively, was made previously.9 However, bothof the terms, in fact, depend on the quantum capacitance of graphene,which is evident by combining EF0 for simplicity):A naïve wayto understand CEDL in a concentrated electrolyte,the system behaves as if the gate electrode was positioned withina Debye length of the graphene surface.Nonetheless, due to the inverse dependencein the second term in CQ fundamentally limits the abilityto access high doping, even forthe most efficient gating approaches. This is illustrated by our analysisusing EF on Vg for several electrolytes with differing CEDL. The electrolyte gate with one of the lowest CEDL ,8 quickly deviates from the ideal1:1 linear proportionality between EF and Vg (black dotted line), as Vg increases. The most optimistic case of an electrolytewith one of the highest CEDL measuredexperimentally 38 follows the 1:1 line more closely but also deviatesfrom it at high gate voltages. Our estimate of EF from the G mode intensity maximum using CEDL =12.6 μF cm–2, which is similar to commonlymeasured values in highly concentrated aqueous electrolytes39 and results in a EF-Vg response between the two previousextremes. In contrast to the electrolyte gates, the Fermi level ofgraphene for a typical 100 nm SiO2 dielectric gate witha gate capacitance of 35 nF cm–2 depends very weaklyon the gate voltage (gray dashed curve).The quadratic dependenceof the second term in Vg = 1.0 V,the gating efficiency drops below 70% for our work (12.6 μFcm–2) and below 40% for Das et al. (2.2 μFcm–2).8 For comparison,the gating efficiency of a 100 nm SiO2 dielectric layer(35 nF cm–2) drops as low as 6% at Vg = 1.0 V (17% at Vg = 0.1V), contrasting the hypothetical 1 mF cm–2 capacitorwith gating efficiency larger than 99% up to Vg = 1.0 V. Insights from 14 cm–2 (correspondingto |EF| > 1.3 eV) remains mostly elusive,despite the progress in electrolyte gating approaches made in thepast decade.Expressing the performanceof the electrolyte gate as the gatingefficiency dependence on gate voltage is even more instructive, asshown in 40 Contrary to the predictionby classical models, the resulting reduction in charge screening paradoxicallyleads to an increase of the Debye length with increasing ionic concentration,which ultimately decreases the effective CEDL according to 42 Importantly, the independence of the gating efficiencyon the electrolyte type and concentration suggests that the effectscaused by variations in CEDL are smallerthan the measurement errors.Furthermore, the rise of the charge screening efficiencyin highlyconcentrated electrolytes is severely limited by the ionic interactionarising from the steric effects such as charge overscreening, ioncrowding, and ion pairing.in situ Raman spectroelectrochemistry.The application of potential difference (gate voltage) through theelectrolyte gate leads to electrostatic doping of graphene, whichlowers or raises its Fermi level and manifests itself by changes inthe position, shape, and intensity of the G and 2D Raman modes ofgraphene. Our results offer two critical insights into electrostaticgating using electrolytes. First, the rate of the G mode frequencychange with the gate voltage (corrected for the Dirac point position)is the same, regardless of the electrolyte type, concentration, andionic strength. This suggests that electrostatic doping is independentof the electrolyte properties, at least in the high ionic strengthlimit. Second, our analysis demonstrates that while electrolyte gatingis the most effective approach to alter the Fermi level of grapheneand induce high charge carrier density, it is not without limits.Even for electrolytes with highly efficient charge screening, thequantum capacitance fundamentally limits the maximum possible shiftof the Fermi level with applied gate voltage. We demonstrate by comparisonof different gating systems that this gating efficiency depends stronglyon the gate capacitance and gate voltage, dropping as low as 70% forcommon electrolytes and applied voltages. Our findings have criticalimplications for electrolyte gating not only of graphene but alsoother materials with low DOS. Specifically, large ionic strengthscan facilitate high charge doping regimes, through which exotic featuresof the electronic band structure, such as van Hove singularities,can be probed.43 Additionally, electrochemistrystudies of low DOS materials, from which conclusions are drawn usingthe relative position of the applied potential and electronic bandstructure of the material, should be thoughtfully reconsidered.In conclusion, electrostatic gatingof monolayer graphene usinghighly concentrated aqueous electrolytes of varying ionic strengthwas interrogated using


Light irradiation increases the amount of radicals and rate of antibiotic removal.Wastewater contaminated with antibiotics is a major environmental challenge. The oxidation process is one of the most common and effective ways to remove these pollutants. The use of metal-free, green, and inexpensive catalysts can be a good alternative to metal-containing photocatalysts in environmental applications. We developed here the green synthesis of bio-graphenes by using natural precursors . The use of these precursors can act as templates to create 3D doped graphene structures with special morphology. Also, this method is a simple method for in situ synthesis of doped graphenes. The elements present in the natural biopolymers (N) and other elements in the natural composition  are easily placed in the graphene structure and improve the catalytic activity due to the structural defects, surface charges, increased electron transfers, and high absorption. The results have shown that the hollow cubic Chitosan-derived graphene has shown the best performance due to the doping of N, S, and P. The Boswellia-derived graphene shows the highest surface area but a lower catalytic performance, which indicates the more effective role of doping in the catalytic activity. In this mechanism, O Using other metal-free catalysts, graphenes, or doping these compounds with other non-metal elements can be an effective and cheap way to improve the catalytic properties of these compounds. The combination of g-C3N4 with SiC and siligraphene (g-SiC) has created effective photocatalysts in the removal of dyes and antibiotics [The high recombination rate of photogenerated electron-hole and wide band-gap is the disadvantage of these catalysts. To overcome it, these catalysts are modified with metal or metal oxides to improve their catalytic activities. These metals are expensive, and also, the leaching of these metal ions might cause secondary pollution. Thus, it is challenging to find low-cost and high-effective co-catalysts to modify the efficiency of metal-free catalysts such as g-Cibiotics ,35,36. Although carbon nanostructures such as graphene are often used as adsorbents to remove pollutants, these carbon compounds are used to increase the surface area of other photocatalysts to subsequently increase the absorption and improve the catalytic properties . Also, tIn this study, doped bio-graphenes as the metal-free green catalysts were in situ synthesized using natural precursors. The use of natural resources can be a way to produce cheap, safe, and environmentally friendly compounds with a porous structure and special morphology. In this study, the effect of natural precursors on morphology, surface area, doping, and band levels was evaluated here. The doped structures were then tested for degradation of antibiotics via an advanced oxidation mechanism, and different structural parameters were investigated. In this research, only saturated oxygen in water (air bubbling) was used, and no oxidants were added to the system. However, the effect of oxygen and light has also been investigated in accelerating the degradation process in the removal of antibiotics.Carbon-based materials which are synthesized from natural materials (biochars or bio-graphenes) are of particular importance due to the easy, cheap, and green synthesis method. The use of natural precursors can act as a template and create a structure with special porosity and morphology. Here we have chosen natural gums as precursors. These natural polymers can create a unique polymeric network to produce the 3D graphene structures. The porosity and morphology of these graphenic structures are directly dependent on the natural precursors.−1. Also, the broad bands at about 3300–3600 cm−1 were related to stretching vibrations of O-H and N-H bonds, and the absorption bands at about 2925 and 2895 cm−1 indicate the symmetric and asymmetric C-H vibrations. In the X-BG, C-BG, and T-BG samples, which show the N-doping, the C-N absorption bands appeared at 1425 cm−1, and the presence of P and S dopants in the C-BG sample was observed at 895 cm−1 and 1080 cm−1, indicating the S-C and P-O bonds in this doped graphene.−1, respectively. The first-order G band is the primary mode which represents the sp2 planar configuration of carbon and the second-order D band is the disorder band which represents a ring mode of carbon adjacent to a defect. So, the intensity of the D band was increased by increasing the defects in the graphene structure. The doping of heteroatoms increased the degree of disorder and the intensity ratio of D to G bands (ID/IG) was increased. As shown in D/IG ratio is related to the C-BG graphene which was derived from Chitosan. It indicates the higher defects in the C-BG graphene structure due to the doping of N, P, and S. The lowest ID/IG ratio is related to the B-BG which shows the graphene structure with no element doping.Xanthomonas campestris bacteria. The EDX results show the N-doped graphene structure for the compound, which is caused by the presence of nitrogen compounds in the original natural composition. Na, K, Ca, and Mg elements have been removed in the acid washing step, which themselves are effective in creating porosity in the structure. x-C) at 168.9 eV and 170.6 eV, respectively. The amount of P and S obtained was 0.3 and 1.4, respectively.To confirm the placement of N, P, and S in the graphene structures, XPS analysis was conducted . In all 2 adsorption/desorption isotherms and pore size distribution curves, the highest surface area with different pore distribution was observed in the B-BG sample. This observed increase in surface area with different pores is dependent on its initial precursor, creating a porous structure with special morphology. After B-BG, the largest surface area is related to the C-BG sample, which has the highest amount of dopants. The structure of the primary polymer precursor and the presence of various dopants in the final graphene structure have created a hollow cubic structure and increased surface area in this compound. As shown in Since the amount of adsorption is related to the porosity of the substrate, the porosities of synthesized bio-graphenes are discussed in Next, the role of doped porous graphene structures obtained from natural sources in the catalytic removal of antibiotics will be investigated.In order to investigate the catalytic properties of synthesized bio-graphene, the removal of antibiotics from wastewater was investigated. Tetracycline (TCL), ciprofloxacin (CIP), and amoxicillin (AMX) were tested as the model antibiotics and the removal efficiency of the synthesized catalysts was evaluated in the presence of air. The effect of oxygen and light on accelerating the process was also investigated.zpc (pH of zero point charge) and can adsorb the positive molecules. At a pH lower than pHzpc, the surface of the catalyst is positive and can adsorb the negative molecules. The pHzpc of C-BG is calculated as 6.7, which is higher than the surface pH (6.4), so it can adsorb the negative molecules. As shown in 2TC+ was observed at pH < 3.3, zwitterionic species of H2TC0 was formed at pH 3.3–7.7, and anion species of HTC−/TC2− was observed at pH > 7.7 [TCL has several ionizable functional groups such as tricarbonyl amide, dimethylammonium, and phenol diketone. The cation species of HpH > 7.7 ,48.zpc of 6.7 and is positive in this pH, and zwitterionic H2TC0 is the main species of TCL, therefore, TCL can adsorb onto the surface of the catalyst via the interaction between the negatively charged tricarbonyl amide groups of TCL and the positive centers  in the surface of the catalyst. Thus, the best catalytic result of the C-BG catalyst is obtained at a pH of 5–7, which is lower than pHzpc (6.7). When the pH decreases to a pH lower than 4, the TCL removal reduces due to the repulsion between the cationic species of TCL and the positively charged catalyst (pH < pHzpc). By increasing the pH to more than the pHzpc of the catalyst, the electrostatic repulsion between the negatively charged catalyst and anionic TCL decreases the removal efficiency  of tetracycline adsorption/degradation was related to the pseudo-second-order kinetic model, so the antibiotic degradation process followed this model. 2 and light, and the radicals participating in the reaction were identified. 2 gas instead of air, the rate of reaction and yield of TCL removal increases, which shows that oxygen is involved in the reaction mechanism. To investigate the catalytic removal mechanism, the reaction was also performed in the presence of O2, the formation of oxygenated radicals was observed (•OH) radical is the dominant active species, while in the presence of O2, the role of the •O2− radical increases. By irradiating light to the system, the rate of reaction and the yield of TCL removal increases  and amoxicillin (AMX) were also investigated d. The reThe FT-IR of the fresh C-BG catalyst and its used ones at different conditions are shown in Natural precursors were used for the synthesis of bio-graphenes. Xanthan, Chitosan, Boswellia, and Tragacanth gums were purchased from a local shop with 70–80% purity and used after washing with water to remove the dust. Tetracycline (TCL), ciprofloxacin (CIP), and amoxicillin (AMX) were selected as the model antibiotics to test the removal efficiency of synthesized bio-graphenes.2 adsorption/desorption isotherms and the pore size distributions were recorded by a Belsorp mini instrument . Photocatalytic tests were measured by a Perkin-Elmer, Lambda-35 UV-Vis spectrometer .Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX) was used for surface analysis by a TESCAN, VEGA3 microscope, Czech Republic. FT-IR spectra were taken from a Bruker, Vector spectrometer, Germany. Raman spectra were obtained from Bruker , Senterra micro-Raman, Stuttgart, Germany. ESCALAB 250Xi Thermo Scientific system  was used for XPS analysis by using a spectrometer with MgKα = 1253.6 eV. N2 atmosphere. The obtained bio-graphenes were washed with diluted HCl to remove the metals . The bio-graphenes were obtained from Xanthan, Chitosan, Boswellia, and Tragacanth gums named X-BG, C-BG, T-BG, and B-BG, respectively.5 g of each natural precursor  was dissolved in 50 mL water at 50 °C. The solution was stirred until clear gel was obtained. The solutions were filtered to remove the impurities. Then, the obtained gels were dried at 80 °C for 12 h, and the resulting powders were transferred to a crucible and heated at 750 °C with the rate of 5°/min for 1 h at N2 = 0.9996), and the unknown concentration was measured according to the absorbance at 327 nm. The TCL removal % was determined using the following equation:0 and Ct are the initial and equilibrium TCL concentrations, respectively.To investigate the performance of synthesized bio-graphenes in the catalytic removal of antibiotics, a certain amount of doped graphenes was added to 10 mL of tetracycline (TCL) solution with different concentrations . The system was saturated with oxygen by air bubbling during stirring. To optimize the photocatalytic reaction, different amounts of graphene catalyst  were tested for degradation of TCL at a pH of 2–12. First, all of the samples were stirred for 10 min to reach the equilibrium and then, the removal of TCL was measured in the presence of dissolved oxygen. After every 10 min, TCL concentration was measured by UV-Vis spectroscopy at 357 nm using a calibration curve. The calibration curve of TCL standard solutions displays the concentration of TCL dependence of absorbance at 357 nm (maximum adsorption wavelength of TCL). First, the stock solution of TCL was prepared in 50 ppm concentration. Then, 5 series of standard solutions were prepared from this stock solution by means of dilution to 25, 12.5, 6.25, 3.125, and 1.562 ppm. Then, the calibration curve was plotted  as the scavenger of hydroxyl radical (•OH), 1,4-benzoquinone (BQ) as the scavenger of superoxide radical anions (•O2−), and ammonium oxalate (AO) as the hole (h+) scavenger.In order to investigate the role of oxygen and light, the above process was repeated in the presence of OIn order to check the ability of the mentioned catalysts to remove all kinds of antibiotics, catalytic tests were also performed for two other antibiotics (ciprofloxacin (CIP), and amoxicillin (AMX)).A schematic illustration of the synthesis procedure and their catalytic properties is displayed in 2 dissolved in water absorbs onto the positively charged C adjacent to N dopants to produce the oxygenated radicals, which enables the degradation of antibiotic molecules. Light irradiation increases the amounts of radicals and the rate of antibiotic removal. Oxygen also can accelerate the degradation process via increasing the oxygenated radicals. The quenching tests and continues recovery of doped graphene also confirm the degradation of antibiotics via oxidation process. In this study, bio-graphenes as metal-free, green, and inexpensive catalysts were synthesized with different morphology and porosity via a green method, using natural precursors . These natural polymers act as templates and create special networks that form the 3D graphene structure with special morphology. In this method, the elements present in the natural biopolymers (N) or in the natural composition  are easily placed in the graphene structure and doped graphenes are synthesized. Doping can improve the catalytic activity due to the structural defects, surface charges, increased electron transfers, and high absorption. The results show that the best catalytic performance is related to the hollow cubic Chitosan-derived graphene, which is due to the doping of N, S, and P to the graphene structure. The Boswellia-derived graphene shows the lowest catalytic properties with the highest surface area, indicating the more effective role of doping in the catalytic activity. In this mechanism, O


Evidence is accumulating for the crucial role of a solid’s free electrons in the dynamics of solid–liquid interfaces. Liquids induce electronic polarization and drive electric currents as they flow; electronic excitations, in turn, participate in hydrodynamic friction. Yet, the underlying solid–liquid interactions have been lacking a direct experimental probe. Here we study the energy transfer across liquid–graphene interfaces using ultrafast spectroscopy. The graphene electrons are heated up quasi-instantaneously by a visible excitation pulse, and the time evolution of the electronic temperature is then monitored with a terahertz pulse. We observe that water accelerates the cooling of the graphene electrons, whereas other polar liquids leave the cooling dynamics largely unaffected. A quantum theory of solid–liquid heat transfer accounts for the water-specific cooling enhancement through a resonance between the graphene surface plasmon mode and the so-called hydrons—water charge fluctuations—particularly the water libration modes, which allows for efficient energy transfer. Our results provide direct experimental evidence of a solid–liquid interaction mediated by collective modes and support the theoretically proposed mechanism for quantum friction. They further reveal a particularly large thermal boundary conductance for the water–graphene interface and suggest strategies for enhancing the thermal conductivity in graphene-based nanostructures. Ultrafast spectroscopy experiments demonstrate that graphene electrons can transfer energy directly to liquid water with no mediation from the crystal lattice as their collective plasmon oscillation excites water’s molecular charge fluctuations. Graphene’s distinctive dynamic properties on picosecond time scales have found several applications in, for example, ultrafast photodetectors, modulators and receivers5. The terahertz frequency range acquires particular importance at room temperature T, where it corresponds to the typical frequency of thermal fluctuations: kBT/ℏ ≈ 6 THz, where kB is Boltzmann’s constant and ℏ is Planck’s constant. One may therefore expect non-trivial couplings between the graphene electrons and the thermal fluctuations of their environment. These couplings have been intensively studied in the case of a solid environment: for instance, non-adiabatic effects have been shown to arise in the graphene electron–phonon interaction6, and plasmon–phonon coupling between graphene and a polar substrate has been demonstrated9. More recently, it has been theoretically proposed that similar effects are at play when graphene has a liquid environment: then, the interaction between the liquid’s charge fluctuations—dubbed hydrons—and graphene’s electronic excitations tunes the hydrodynamic friction at the carbon surface11. This ‘quantum friction’ mechanism holds the potential for entirely new strategies for controlling liquid flows on the nanometre scale13; it is therefore of interest to experimentally probe the underlying electron–hydron interaction.Free electrons in graphene exhibit rather unique dynamics in the terahertz frequency range, including a highly nonlinear response to photoexcitation by terahertz pulses19. In high-quality graphene, it has been used to identify the interaction of hot carriers with optical phonons18 and with substrate phonons as the main electron cooling mechanisms20; it has also identified the role of Coulomb interactions in the interlayer thermal conductivity of graphene stacks16. Here, we measure the electron relaxation time in the presence of different polar liquids to probe the electron–hydron interaction, which we find to be comparable to the electron–optical phonon interaction only when the liquid is water. A complete theoretical analysis shows that this specificity of water is explained by the strong coupling of its terahertz (libration) modes to the graphene surface plasmon, with the electron–electron interactions in graphene playing a crucial role.In this article, we probe solid–liquid interactions by measuring energy transfer at the solid–liquid interface Fig. . Specifi21. Even if an optical excitation of the solid’s electrons is used to create the temperature difference, the electrons are typically assumed to thermalize with phonons on a very short time scale, so that the solid’s phonons ultimately mediate the energy transfer to the liquid’s vibrational modes23. However, if the electrons were to transfer energy to the liquid faster than to the phonons, the interfacial thermal conductivity would contain a non-negligible contribution from near-field radiative heat transfer25  exhibits a relaxation that can be approximated by an exponential function: ΔT(t) = T(t) − T0 = ΔT0et/τ−. This allows us to extract the cooling times τ for the different liquids and different initial electronic temperatures (determined by the excitation laser fluence), displayed in Fig. 18. Now, for all initial temperatures, we consistently observe the same dependence of the cooling time on the sample’s liquid environment. In the presence of water (H2O) and heavy water (D2O), the graphene electrons cool faster than they do intrinsically, in an inert nitrogen atmosphere. Conversely, methanol and ethanol have almost no effect on the electron cooling time. Interestingly, we observe an isotope effect in the electron cooling process: there is a difference in the cooling times in the presence of H2O and D2O that greatly exceeds experimental uncertainties.Regardless of the medium that the graphene is in contact with, the electronic temperature We are thus led to hypothesize, as anticipated above, that the liquid provides the electrons with a supplementary cooling pathway, which, in the case of water, has an efficiency comparable to the intrinsic cooling pathway via phonons. We then interpret the faster cooling as a signature of ‘quantum’ electron–liquid energy transfer. We assess the pertinence of this hypothesis by developing a complete theory of quantum energy transfer at the solid–liquid interface.10, we represent the liquid’s charge density as a free fluctuating field with prescribed correlation functions. This naturally leads to a Fourier-space description of the solid–liquid interface in terms of its collective modes, rather than the usual molecular-scale interactions. Within this description, the quantum solid–liquid energy transfer amounts to electron relaxation upon coupling to a bosonic bath, a problem that has been extensively studied in condensed matter systems34. Interestingly, in the case of graphene, many of these studies are carried out within a single-particle Boltzmann formalism, which may incorporate multiple screening effects only in an ad hoc fashion35. These effects turn out to be crucial for the solid–liquid system under consideration: we have therefore developed an ab initio theory of solid–liquid heat transfer based on the non-equilibrium Keldysh formalism36, which has only very recently been considered for problems of interfacial heat transfer37. Our computation, detailed in Supplementary Information, section 10. The theoretical framework can formally apply to fully non-equilibrium situations and take interactions into account to arbitrary order. However, to obtain a closed-form result, assume that the liquid and the solid internally equilibrated at temperatures Tl and Te, respectively. Furthermore, we take electron–electron and electron–liquid Coulomb interactions into account at the random phase approximation (RPA) level. With these assumptions, we obtain the electron–liquid energy transfer rate asnB = 1/(eℏω/T − 1) is the Bose distribution and the ge,l are surface response functions of the solid and the liquid, respectively. These are analogues of the dielectric function for semi-infinite media, the precise definition of which is given in Supplementary Information, section εl(ω) is the liquid’s bulk dielectric function. For two-dimensional graphene, we show in Supplementary Information, section χ is graphene’s charge susceptibility.To tackle the interaction between a classical liquid and an electronic system whose behaviour is intrinsically quantum, we describe the liquid in a formally quantum way. Following ref. 39; our non-equilibrium framework, however, is better suited to the solid–liquid system under consideration. We note that equation  is the graphene electronic heat capacity at temperature Te. We focus in the following on the liquid contribution to the electron cooling rate, defined as τ requires the surface response functions of graphene and of the various liquids. We compute the graphene surface response function according to equation  and contains the signature of any potential strong coupling effects. We find that these effects are indeed important: removing the denominator in equation (μ = 180 meV. We observe that the graphene plasmon now splits into two modes, which are both a mixture of the the bare plasmon and water librations. These are in fact analogous to the coupled plasmon–phonon modes that have been predicted7 and measured9 for graphene on a polar substrate. It can be seen in the inset of Fig. Furthermore, detailed examination of our theoretical result reveals that the efficiency of the electron–water cooling is enhanced by the formation of a strongly coupled plasmon–hydron mode. Indeed, the result in equation  involvesequation  (that isequation . To gainequation 5\documen23, or with electronic degrees of freedom in the Born–Oppenheimer approximation44, here we demonstrate experimentally that the dynamics of the water–graphene interface need to be considered at the level of collective modes in the terahertz frequency range. In particular, our semiquantitative theoretical analysis attributes the observed cooling dynamics to the strong coupling between the graphene plasmon and water libration modes.We have carried out ultrafast measurements of electron relaxation in graphene, revealing signatures of direct energy transfer between the graphene electrons and the surrounding liquid. These results speak to the importance of electronic degrees of freedom in the dynamics of solid–liquid interfaces, particularly interfaces between water and carbon-based materials. Despite conventional theories and simulations that describe the interface in terms of atomic-scale Lennard–Jones potentials10. The near-quantitative agreement between the experiment and theory obtained for energy transfer suggests that a similar agreement should be achieved for momentum transfer. The water–graphene quantum friction force is small if the graphene electrons are at rest, but becomes important if they are driven at a high velocity by a phonon wind or an applied voltage12. The quantum-friction-based driving of water flows by graphene electronic currents appears as a promising avenue in light of our findings. The electric circuit configuration would furthermore allow for noise thermometry46 to be used as a supplementary probe of the electron relaxation mechanisms.The experimental observation of such a collective mode interaction supports the proposed mechanism for quantum friction at the water–carbon interface, which is precisely based on momentum transfer between collective modes47. Indeed, the electronic contribution to the graphene–water thermal boundary conductance is as high as λ = 0.25 MW m−2 K−1, exceeding the value obtained with the other investigated liquids by at least a factor of 2. This even exceeds the thermal boundary conductance obtained for the graphene–hBN interface, at which particularly fast ‘super-Planckian’ energy transfer was observed35. Our investigation thus suggests that the density of modes in the terahertz frequency range is a key determinant for the thermal conductivity of graphene-containing composite materials.Our results provide yet another example of the water–carbon interface outperforming other solid–liquid systemsAny methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41565-023-01421-3.Supplementary InformationSupplementary Figs. 1–7, experimental methods and theoretical methods.


The shape and structure of prepared micro-sensors were studied using scanning electron microscopy (SEM). The structural and compositional changes in the irradiated area were characterized using micro-Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), Rutherford back-scattering spectroscopy (RBS), energy-dispersive X-ray spectroscopy (EDS), and elastic recoil detection analysis (ERDA) spectroscopy. The sensing performance was tested at a relative humidity (RH) ranging from 5% to 60%, where the electrical conductivity of PI varied by three orders of magnitude, and the electrical capacitance of GO varied in the order of pico-farads. In addition, the PI sensor has proven long-term sensing stability in air. We demonstrated a novel method of ion micro-beam writing to prepare flexible micro-sensors that function over a wide range of humidity and have good sensitivity and great potential for widespread applications.In this study, novel flexible micro-scale humidity sensors were directly fabricated in graphene oxide (GO) and polyimide (PI) using ion beam writing without any further modifications, and then successfully tested in an atmospheric chamber. Two low fluences (3.75 × 10 Humidity is an important environmental characteristic that affects physical, chemical, and biological processes; therefore, the control of humidity, which causes material corrosion, is essential for almost all human health, activities, and comfort . To achiOrganic solids, such as graphene oxide (GO) or polymers, are excellent candidates for the fabrication of chemo-resistive sensors, due to their detection ability at room temperature, excellent sensitivity, mechanical stability, short reaction time, low cost, commercial availability, easy processing, and flexibility ,5,7,8. T2/sp3 ratio of carbon hybridization, sensory/catalytic properties, and dielectric properties). In addition, ion irradiation has several advantages, such as the absence of chemical agents, the absence of unwanted oxides formation, less formation of residual impurities, and relatively simple and cost-effective mass production [13 cm−2, the threshold for the overlapping of individual ion tracks is overcome, and the π-bonded carbon clusters increase in number, aggregate, and create a network of conjugated carbon bonds [13 cm−2, the nucleation and growth of nano-sized carbon-enriched clusters are expected until a quasi-continuous carbon-embedded layer is formed [Although there are several methods, such as inkjet printing, laser writing, or metal sputtering, for the fabrication of in-plane organic humidity micro-sensors, ion-beam writing has not yet been used ,19,20. Ioduction ,22. Condoduction . When thon bonds ,24. Thuss formed . The oris formed .3+ ion micro-scale beam to induce the carbonization/deoxygenation/dehydrogenation and locally increase electrical conductivity. The ion fluences of 3.75 × 1014 cm−2 (1800 nC/mm2) and 5.625 × 1014 cm−2 (2700 nC/mm2) were used, for which a significant increase in electrical conductivity was previously reported for GO, PI, and PMMA [In this study, we focus on carbon ion beam writing for the maskless fabrication of micro-meter electrode systems to insulate organic matrices for use in humidity sensors. Graphene oxide (GO), polyethylene–terephthalate (PET), polyimide (PI), and poly(methyl methacrylate) (PMMA) foils were irradiated using a focused 5 MeV Cand PMMA ,27,28. T−2) was determined by weighing the accurately cut portion of the GO film. The 50 μm-thick foils of PMMA (density (ρ) = 1.19 g·cm−3, glass transition temperature (Tg) = 105 °C, melting temperature (Tm) = 160 °C, surface resistance (σe) = 1014 Ohm/sq), PI—Kapton , and PET—Mylar  were supplied by Goodfellow, Ltd., Huntingdon, UK [GO was prepared using a permanganate oxidation method (modified Hummers’ method) and subsequently separated using a centrifuge, as described in . A GO figdon, UK ,31.3+ with a 250 pA current. The carbon beam spot on the foil surface was focused to 4 × 15 µm2. The ion fluences were 3.75 × 1014 cm−2 (1800 nC/mm2) and 5.625 × 1014 cm−2 (2700 nC/mm2). The microscopic structure was prepared as an image of 900 × 900 pixels2  as reference samples provided for the investigation by using RBS, ERDA, and XPS analyses, where appropriately broader modified sample area is required. The current of ions during irradiation was maintained at 10–15 nA·cm−2, significantly less than the current of ions used in microbeam writing (250 pA.60 µm−2–4.2 × 102 µA·cm−2). The higher current could not be reached during broad beam irradiation using a Tandetron accelerator.Ion-beam lithography was performed in an Oxford Microbeams micro-beam chamber utilizing 5 MeV CThe compositional changes in the connection to carbon ion irradiation were studied using Rutherford backscattering spectrometry (RBS) and Elastic recoil detection analysis (ERDA). The RBS/ERDA spectra were measured using a He beam of energy at 2.0 MeV. An Ultra-Ortec PIPS detector registered the back-scattered ions in Cornell geometry with a scattering angle of 170°. The input angle of the initial ERDA beam was 75°, and the scattering angle was 30°. The recoiled particles were registered by a Canberra PIPS detector equipped with a 12 µm Mylar foil. The current of the He ions used in the RBS and ERDA analyses was ~5 nA. Several RBS spectra were measured at random locations in the beam to reduce the effect of sample degradation. The resulting spectrum is a sum of incremental spectra. The concentration of the elements was analyzed using SIMNRA software .−1. To minimize damage to the sample, no more than 5% of the overall laser power was used. For the measurement, the samples were cast on a silicon wafer from a suspension of isopropanol (1 mg·mL−1).Raman spectroscopy was measured using an inVia Raman microscope . The spectrometer operates using a backscattering geometry with a CCD detector and a 50 mW Nd-YAG 532 nm laser with a 50× magnification objective. The calibration of Raman spectrometer was performed with a silicon sample that provided a peak position at 520 cmScanning electron microscopy (SEM) images of the GO, PMMA, PI, and PET micro-structures were obtained using a field emission electron source . The sample was adhered to a carbon conductive strip for SEM measurement.2 that were analyzed. The X-ray source was monochromatized to 1486.7 eV, and each measurement was performed with a step of 0.05 eV. CasaXPS, ver. 2.3.24 software was used for spectral evaluations.The X-ray photoelectron spectroscopy (XPS) was performed using the ESCAProbeP from Omicron Nanotechnology Ltd. , with exposed area dimensions of 2 × 3 mmTo examine the effect of humidity on the electrical properties of prepared structures directly associated with the ability to sense humidity, the modified foils were placed in an environmental chamber in which relative humidity (% RH) was controlled (RH range 5–60%) by mixing dry and wet air and monitored using a BME 280 pressure/humidity/temperature sensor . The change in electrical capacitance with varying humidity levels was determined by the measurement of the frequency dependence of the high-pass filter output voltage with a constant current of 0.5 mA, see 14 cm−2, the C/O and C/H ratios in GO growth change from 3.6 to 4.4 and from 7.6 to 8.9, respectively. Additionally, only low GO carbonization occurs, and carbon concentration in GO increases by about 3 at. %. The C/O and C/H ratios increase from 4.4 to 6.8 and from 2.2 to 2.7, respectively, in PI. The irradiation with 5 MeV carbon ions with predominant electronic stopping leads to the weak bond scission in GO and PI and the release of low-mass gaseous fragments, followed by GO and PI reduction and carbonization [14 cm−2 in PET from 36.3 to 25.4 at. % and in PMMA from 43 to 18 at. %. The increase in O concentration in PET and PMMA after ion irradiation may be caused by the post-irradiation oxidation of the damaged layer. Oxygen from the surrounding atmosphere is diffused into the open structures of polymers and captured in the defects [The element composition of non-modified and irradiated samples was determined using ion-beam spectroscopic methods (RBS and ERDA) with 2 MeV He ions. The available information depth of RBS with a He ion beam energy of 2 MeV in polymers and GO is approximately 1 µm, and it is approximately 0.5 µm for ERDA. The RBS and ERDA spectra from pristine and irradiated samples are shown in nization . A highe defects . Additio defects .−2 in our case), which causes local heating in the vicinity of the ion impact [12 cm−2, leads to the removal of pendant side chains in PMMA, and the creation of short chains with interrupted bonds and cross-linking. The shrinkage of the irradiated PMMA structure leads to surface cracking and swelling [The changes in PET, GO, PI, and PMMA morphology caused by carbon ion irradiation, acquired by SEM, are shown in n impact ,39,40. Mswelling ,42. The Energy-dispersive spectroscopy (EDS), simultaneously measured with SEM provides a qualitative insight into differences in the elemental composition of irradiated and nonirradiated parts see . An EDS −1 appear, whose intensity increases with increasing ion fluence. These two peaks correspond to the D and G broad bands of the disordered graphitic structure. The G band is connected to the E2g Brillouin zone-center phonon density of states in the sp2-bonded graphite-like carbon; the D band is caused by defects in the momentum conversation and is ascribed to the point defects and effects on the edges [2 structure growth are caused in the PI structure, leading to an increase in PI conductivity.Raman spectroscopy provides a detailed analysis of structural changes caused by carbon beam irradiation see . The prihe edges ,44. The −1), C-C stretching (987 cm−1), C-H2 bending (1455 cm−1), C=C stretching vibration (1590 cm−1), C=O stretching (1730 cm−1), and C-H symmetric stretching (2800–3100 cm−1) [−1), C-C breathing (857 cm−1), CH2 wag (1381 cm−1), benzene rings (1613 cm−1), and C=O vibration (1727 cm−1) [The Raman spectra of non-irradiated PET and PMMA show several peaks originating from PET and PMMA monomer structures see b,d. The bending 15 cm−1, C27 cm−1) . After i2 carbon pairs, and the intensity of this signal represents the degree of the GO lattice arrangement [−1 [−1 peak increase after carbon irradiation are more pronounced with increased ion fluence. The decrease in the D peak represents the reduction in the epoxide and hydroxyl parts of GO and the decline in multipeaks between 2400 and 3200 cm−2 is shown in the growth of sp2 domains [−1 growth is caused by the formation of non-six-carbon rings [The most prominent peaks are the D and G peaks in all Raman spectra of GO a. The G angement . The D mangement . The nexment [−1 . The D-p domains ,50, whicon rings . It is e14 cm−2) are presented in X-ray photoelectron spectroscopy (XPS) describes the changes in surface chemistry, which at first, directly interacts with the environment surrounding the analyzed sample and significantly influences the final electric and sensory properties. The deconvolution of high-resolution C1s peak for non-modified samples as well as for samples irradiated with the highest ion fluence  is plotted in 14 cm−2 is affected by a decrease in sheet resistivity from the humidity value of 40%. On the contrary, the sheet resistivity of the PI microstructure prepared with a 5.625 × 1014 cm−2 fluence decreases almost linearly from the lowest to the highest humidity by more than three orders of magnitude. The PI microstructure prepared using the highest ion fluence exhibits an excellent sensoric performance, similar to GO. The electrical sheet resistance of PI microstructure prepared with the highest C fluence decreases almost linearly with the increasing relative humidity. 14 cm−2 fluence again after 60 days, when the samples were kept in a room atmosphere in ambient light. It can be seen, in The humidity sensing performance of prepared structures was evaluated under various levels of relative humidity (RH) ranging from 5 to 60% in the atmospheric chamber by measurement of the electric sheet resistance of PI, PET, PMMA, and GO, as well as electric capacity changes in GO see . It shouIn this study, we used the 5 MeV carbon ion-beam writing for the preparation of capacitor-like microstructures with dimensions below 1 mm in GO, PI, PET, and PMMA, and these prepared microstructures were tested for their humidity-sensing properties. In all cases, the carbon ions lost energy and caused damage via electronic stopping, leading to the scission of weak bonds, the release of low-mass gaseous fragments, and the creation of new free bonds. In our cases, the phenyl and benzene rings were breaking, the O and H were released from irradiated areas, while carbonization increased and new six/non-six carbon rings were formed. GO and PI have a better radiation resistance compared to PET and PMMA due to higher aromaticity, and a carbon ion-beam causes less damage in GO and PI compared to PET and PMMA . In PI a2. Sensoric performance was tested in an atmospheric chamber with a relative humidity (RH) varying from 5 to 60% and by measuring the change in electrical sheet resistivity and capacity depending on relative humidity. In general, we demonstrated the great potential of carbonion micro-lithography for preparing humidity sensors in GO and PI substrates, which are able to operate over a broad humidity range with very good sensitivity, and have high potential in the implementation of practical humidity sensors.We reported the fabrication of novel resistive and capacitive types of humidity sensors based on a capacitor-like microstructure prepared by 5 MeV carbon micro-beam writing in GO and PI substrates. The prepared structures are a system of 10 µm-wide electrodes with a mutual mean distance of 20 µm; the total dimension of the structures is 900 × 900 µm


The stacking state of atomic layers critically determines the physical properties of twisted van der Waals materials. Unfortunately, precise characterization of the stacked interfaces remains a great challenge as they are buried internally. With conductive atomic force microscopy, we show that the moiré superlattice structure formed at the embedded interfaces of small-angle twisted multilayer graphene (tMLG) can noticeably regulate surface conductivity even when the twisted interfaces are 10 atomic layers beneath the surface. Assisted by molecular dynamics (MD) simulations, a theoretical model is proposed to correlate surface conductivity with the sequential stacking state of the graphene layers of tMLG. The theoretical model is then employed to extract the complex structure of a tMLG sample with crystalline defects. Probing and visualizing the internal stacking structures of twisted layered materials is essential for understanding their unique physical properties, and our work offers a powerful tool for this via simple surface conductivity mapping. Embedded structures in layered materials can be seen through by taking a map of surface conductivity in a way similar to X-ray imaging. Vertically stacking two-dimensional (2D) materials to introduce strong interlayer coupling is a powerful approach for regulating their physical properties . In partPreviously, it has been shown that the surface electrical conductivity measured by conductive atomic force microscopy (c-AFM) was very sensitive to the stacking states of graphene when the topmost layer was twisted and became reconstructed . In thisA schematic diagram of the electrical conductivity measurements of tMLG devices is shown in Fig. Figure h-BN heterostructures [Since directly tracking the detailed reconstruction state of different layers embedded inside the samples by experiment is extremely challenging, to better understand the atomic structures of tMLG, we conducted MD simulations of tMLG devices containing top AB-stacked graphene slabs with thicknesses varying from 1 to 10 layers deposited on an AB-stacked thick graphite substrate  calculations have shown that the surface conductivity of the twisted monolayer/multilayer graphene is largely determined by the top three layers, and the effect of adding more AB-stacked bottom layers is limited [iR  in our model represents the equivalent resistance of each unit cell of three neighboring graphene layers, as shown in Fig. iR in series, we could estimate the effective spreading resistance for a tMLG structure with N graphene layers to beBased on the atomic structures revealed in MD simulations, we proposed a theoretical model, the SSR model, to quantify the influence of the stacking state of tMLG on its surface conductivity. It is known that the measured current signal in c-AFM is determined by the local spreading resistance of the sample, which is closely associated with the resistivity in a nanoscale volume within the topmost graphene layer in tMLG, as schematically shown in Fig. ne layer . To capt limited . TherefoiR, i.e. 0.75 and 0.5, are factors to account for the repeated calculation , and the decaying factor α.Although the MD calculations suggest that the in-plane rotation angle within the domains of individual graphene layers gradually decays Fig. , the devMLG Fig. , one canα = 0.6754 and β = 0.5633. The magnitude of the decay factor α signifies that nearly 90% of the effective spreading resistance is determined by the top five layers of the tMLG. The fitted conductivity ratio of ABA unit to ABC unit (1/β = 1.78) is consistent with previous DFT calculation results [R1 and R2, both are RABA, while they are both RABC in L domain. Therefore, the contrast in the equivalent spreading resistance between the H domain and L domain in 2 L/graphite is greater than any other tMLG samples, including the twisted 1 L/graphite sample. Successful prediction of this unique phenomenon also suggests the validity of the SSR model. Since the proposed theoretical model is based on analysis of the internal structures with nearly perfectly stacked interfaces, it is mainly suitable for systems with small twist angles with obvious atomic reconstruction . By fitting the experimental results with the SSR model, considering the local stacking registry, we got γ = 1.4581, α = 0.8054  ,41, and Since the surface conductivity of tMLG is sensitive to the internal interface stacking states, if there exist crystalline defects that can affect the interlayer stacking, these defects may manifest themselves as disturbances to the surface conductivity. Figure In conclusion, we found that atomic reconstruction can occur spontaneously for small-angle tMLG structures even when the twisted interface is embedded deep inside. Reconstruction of the embedded twisted interface can induce in-plane deformation to the nearby graphene layers with a decaying magnitude as the adjacent graphene layers always try to stay in registry. Our c-AFM experimental results show that the surface conductivity is sensitive to the sequential stacking state of the internal graphene layers of the tMLG sample up to a depth of ∼10 graphene layers. The correlation between the surface conductivity and the internal stacking structure can be quantitatively described by a theoretical model, which has been proven to be applicable even for tMLG samples with crystalline defects. Our findings provide guidance for tuning the electrical properties of 2D materials by using twisted interfaces, and also enable the visualization and determination of internal stacking structures of tMLG based on simple surface conductivity measurements.2/Si substrate in ambient conditions by scotch tape. Second, the multilayer graphene was lifted by a small piece of polydimethylsiloxane (PDMS) with the help of a drop of ultra-pure water. Then the multilayer graphene was stacked on a thick graphite flake with a small twist angle 2/Si substrate to facilitate Raman spectrum measurement . A constant voltage bias was applied between the sample and the probe. The typical spring constant and resonance frequency of the conductive probe coated with Ti/Ir  are 2.8 N/m and 75 kHz, respectively. To exclude the possibility of an extra moiré pattern in top multilayer graphene created during the transfer process, we also carried out c-AFM measurements on suspended graphene near the graphite edge without the bottom graphite substrate . In our inimized . The RamWe built the large rectangular supercells of twisted multilayer graphene/AB-stacked graphite systems, which are periodic in the lateral directions. Here, a 10-layer AB-stacked graphene slab was used to simulate the graphite substrate and a certain number (1∼10) of AB-stacked graphene layers were placed on the graphite substrate with a twist angle of 0.3° to simulate the twisted multilayer structure. An additional twisted trilayer ABC-stacked graphene/AB-stacked graphite model was built to explore the effect of dislocation observed in experiments. The intralayer interaction within the graphene layers was computed via the second-generation reactive empirical bond order (REBO) potential . The intnwad175_Supplemental_FilesClick here for additional data file.


Twisted bilayer graphene provides an ideal solid-statemodel toexplore correlated material properties and opportunities for a varietyof optoelectronic applications, but reliable, fast characterizationof the twist angle remains a challenge. Here we introduce spectroscopicellipsometric contrast microscopy (SECM) as a tool for mapping twistangle disorder in optically resonant twisted bilayer graphene. Weoptimize the ellipsometric angles to enhance the image contrast basedon measured and calculated reflection coefficients of incident light.The optical resonances associated with van Hove singularities correlatewell to Raman and angle-resolved photoelectron emission spectroscopy,confirming the accuracy of SECM. The results highlight the advantagesof SECM, which proves to be a fast, nondestructive method for characterizationof twisted bilayer graphene over large areas, unlocking process, material,and device screening and cross-correlative measurement potential forbilayer and multilayer materials. This results in novel properties suchas topological transport,1 enhanced photocurrent,2 and correlated insulating phases4 at particular twist angles. Higher energy interlayer interactionscan be observed such as the formation of van Hove singularities (vHs)9 in the electronic density of states (DOS) due to the superpositionof bands from each of the two graphene layers. Optical resonancesassociated with transitions resonant with vHs occur with a twist angle-dependentenergy separation continuously tunable from infrared (IR) to ultraviolet.9 This enhanced absorption has been demonstratedto be beneficial to the performance of wavelength-selective photodetectors,11 motivating the development ofoptically resonant twisted bilayer graphene for optoelectronic devices.The band structure and thuselectronic properties of twisted bilayer graphene can be tuned bythe relative orientation or twist angle θ13 by stacking graphene monolayers16 or by folding them usingatomic force microscope (AFM) tips.17 Anycontamination between layers during processing reduces the interlayercoupling which may destroy angle-dependent phenomena.5 Atomically clean interlayer interfaces can be found inas-grown chemical vapor deposition (CVD)19 bilayer graphene.20 Significant efforthas been made to tailor CVD growth parameters to selectively obtainbilayer graphene,21 which is typicallyhindered by screening of carbon precursors from the growth catalystby the primary graphene monolayer. A further challenge, specific todirect growth of twisted bilayer graphene,12 is avoiding formation of the energetically favorable AB stackedand 30° rotated configurations which often make up the majorityof CVD grown bilayer and multilayer graphene.22Twisted bilayer graphene can be created directly during growth,23 and reflection,26 photoemission,29 photoluminescence,30 and Raman32 spectroscopies, which are often correlated with higher resolutionelectron microscopy25 or scanning probe microscopy.36 Many of these techniques rely on specific substrate properties,such as transparent6 or contrast-enhancing,37 which may be incompatible with characterization during particularstages of manufacturing.38 Spectroscopicimaging ellipsometry has emerged as a tool to determine the opticalconstants of graphene39 and other two-dimensionalmaterials40 and provide thickness informationwith single-atomic layer precision42 with a lateralresolution down to ∼1 μm on a wide range of substrates,including as-grown directly on metal catalyst foils.43 Spectroscopic ellipsometry measures the change in polarizedlight upon reflection at a sample to determine the wavelength-, λ,dependent complex dielectric function (or refractive index n(λ) and extinction parameter k(λ)values) which provides insight into fundamental light–matterinteractions crucial for understanding a range of optical phenomena.44 To extract the full complex dielectric functionor layer thicknesses of a given sample the ratio of perpendicular p and orthogonal s components of the reflectedlight represented by ρ = Rp/Rs = tan(ψ)eiΔ, where ψis the amplitude ratio and Δ is the phase difference, is measuredas a function of λ, angle of incidence (AOI), and polarizer(P), analyzer (A), and compensator (C) angles, and fitted to an opticalmodel.44Identifying bilayer graphene with a particular twist angleis challenging,particularly substrate-agnostic, fast, large-area mapping. Angle-dependentcharacterization of twisted bilayer graphene has been demonstratedthrough optical absorption46 and only images the intensity of reflected light,significantly improving characterization throughput.43 Building on this technique, here we perform spectral ECM(SECM) of the chemical vapor deposition (CVD) grown monolayer, bilayer,and multilayer graphene transferred onto Si/SiO2. We demonstratethat, in addition to layer-number sensitivity and high material contrast,SECM provides wavelength-dependent contrast of optically resonantbilayer and multilayer regions allowing us to extract a map of thetwist angle variation. The range of twist angles detectable is setby the spectral range of the image sensor. We validate the techniqueby correlating SECM data with Raman mapping and angle-resolved photoelectronemission spectroscopy (ARPES).Alternatively, ellipsometersettings  can be optimizedfor material and thickness contrast and fixed during imaging. Thistechnique, often termed ellipsometric contrast microscopy (ECM), hasbeen used across a variety of fields2 transferred graphenefilm showed colored regions in optical microscopy which typicallyappear as approximately radial sections in one or more “petals”within the bilayer graphene “flowers”. The region shownin 9 as schematically shown in VHS), as labeledin 2/graphenemodel described in the Methods section (see Supporting Information). To account for the presence of vHs, a Gaussianresonance term was added to the graphene model when fitting to thedata extracted from BLVHS. The thickness of graphene tGr was found to be 0.57 ±0.1 nm for monolayer and 0.75 ± 0.1 nm for bilayer, as detailedin Table S1 (see Supporting Information). Despite these values deviating from the expected monolayer thicknessof 0.335 nm,48 these values fall within thereported thickness deviations for copper foil-transferred grapheneas measured with AFM51 and ellipsometry,52 likely dueto polymer contamination or chemical interactions between grapheneand the substrate.53 It can be seen in both 2/graphene layer stack, i.e., without an additionalGaussian term, where the only free parameter was tGr. We see that under resonant illuminationthe extracted values of tGr for the region BLVHS, fitted using the simple graphenemodel, deviates from the adjacent bilayer regions, showing a higherapparent thickness.To extract layer thickness for the graphene flakewe perform imagingellipsometry using a rotating compensator ellipsometry (RCE) methodto measure ψ and Δ as a function of λ. We used theimaging RCE mode from 400 to 650 nm over 10 nm intervals, where aspatial map of Δ and ψ is measured for each wavelengthinterval, yielding 25 maps for both Δ and ψ. P and A wereboth fixed at 45°, with AOI at 50°. Examples of Δand ψ maps at λ = 440 nm are shown in 2 for ECM, we evaluate the choiceof ellipsometer parameters, as shown in 43I(ML) and I(BL) are the average pixelintensity values of the monolayer background and the BL or BLVHS, respectively. We theoretically model this by calculatingthe reflection coefficient Rp (Table S1), where Rp = 1 correspondsto 100% reflected intensity. For the resonant bilayer region, themeasured image contrast follows the theoretically expected contrast To find the maximum contrast between monolayergraphene and resonantbilayer graphene on Si/SiOcient Rp 2bas a fRp and Rs reflection coefficients as a functionof wavelength for monolayer (ML), bilayer (BL), and resonant bilayer(BLVHS) regions as labeled in Rp and Rs coefficientswere calculated using the layer-stack model parameters described abovewith AOI = 40°, with an additional Gaussian resonance centeredat the corresponding wavelength of 440 nm applied to resonant bilayerregion data. There is deviation noticeable in the reflection coefficientfor the resonant bilayer region as compared to monolayer and bilayerregions. This results in a predicted enhancement of the contrast onresonance for BLVHS. We perform SECM on the bilayer grapheneregions shown in Supporting Information). The spatial distributionof the resonant wavelength within the bilayer regions is shown in vF = 1 × 106 m s–1, ℏ the reduced Planck’s constant, and a = 2.46 Å the graphene lattice constant.shown in  to detershown in 4a, inset–1 and ∼2700 cm–1, respectively, and theirshapes and positions, as well as intensity ratios that vary with thenumber of graphene layers and twist angle.55 The spectra correlate well with spectra from –1 for small twist angles to 30 cm–1 for larger twist angles, as also shown in 5 for bilayer graphene with twist angle close to 12° (x (y) error bars in To validate our methodology, we correlate the twistangles determinedfrom SECM with Raman spectra. The individual Raman spectra for differenttwist angle bilayer regions, compared to a reference monolayer region,are shown in e to 12° 4e. This 12 orat wrinkles or folds within bilayer graphene films, which are one-dimensionaldefects that form as a result of mismatch in thermal expansion coefficientsof graphene and the substrate.58 To investigate the origins oftwist angle domains, we perform AFM and IR scanning near-field microscopy(SNOM) on a region showing changes in stacking between resonant bilayerregions, and which showed lines of dark contrast in the optical microscopyindicating the presence of folded graphene (The twist angle variation in bilayer graphene is oftenattributedto formation during graphene growthgraphene 1a.59 as shown in the map of the second harmonic amplitude(s2) (ude(s2) 5c, indic6150 This specializedARPES setup is capable of probing the band structure with a spatialresolution of down to 10 μm, which allows spatial mapping ofthe twist angle.62We performed ARPES experiments to quantify theelectronic bandstructure of twisted bilayer graphene. This experiment is especiallyhelpful to identify the energy position of the vHs in the valenceband and thus to corroborate the resonant energies obtained from ellipsometryfor various twist angles. To determine the energy–momentumdispersive band structure around the vHs of different bilayer grapheneregions, we use time-of-flight momentum microscopy.E – EF = −0.9± 0.1 and −1.4 ± 0.1 eV, respectively. Having identifiedthe energetic position of the vHs and measured that the bilayergraphene samples are minimally doped, we can determine the energydifference between the vHs of the valence and the conduction bandto 1.8 ± 0.2 eV and 2.8 ± 0.2 eV, respectively. These energiesmatch the optical experiments shown in To evaluate the energy–momentum dispersive bandstructureand, in particular, the energy position of the vHs of the valenceband in more detail, we apply the second derivative along theenergy axis to the energy-momentum maps 5e,g. Thit ∼ 30° to ∼2°, respectively.The SECM findings agree well with ARPES and Raman characterization.While Raman measurements typically require a contrast-enhancing substrate,like the 90 nm SiO2-on-Si substrates as used in this work,ellipsometry is substrate agnostic, which means it is applicable toa wider range of materials, and could also be used to screen differentstages of the manufacturing process. For example, high contrast isobserved between monolayer and bilayer graphene—imaged as-grownon Cu or after transfer onto Si—regardless of substrate . This capability enables wafer-scalemapping and fast identification of bilayers even on substrates withoutcontrast enhancement. The origin of some regions of twist-angle disorderis attributed to graphene folds as confirmed by AFM and SNOM, whereasother regions show twist angle variations away from any obvious folds.This indicates that a combination of processes during growth and postgrowth are responsible for the twist angledisorder. The presence of optical resonances is confirmed with ARPESby analyzing the band structure at regions with different resonantwavelengths. This technique could be applicable to other materialsystems,42 including transition metal dichalcogneides63 and twisted heterostuctures.64 With the advent of spectroscopic microellipsometry extensionsfor conventional optical microscopes, SECM has become even more affordableand accessible.65 This work confirms thatSECM is a powerful, fast, and nondestructive tool for material characterization,which unlocks the potential of material properties for a variety ofresearch applications.In this work we perform SECM and correlatedcharacterization tostudy the angle dependence of optically resonant twisted bilayer graphene.We compare the SECM results to full wavelength-dependent Δ andψ maps obtained through imaging RCE to confirm the thicknessof the bilayer regions. The ellipsometer wavelength range allows usto find twist angles between 9° and 17° and provides a typicaltwist angle accuracy of <1°. The range of twist angles couldbe expanded by using a spectroscopic imaging ellipsometer with anextended wavelength range such as commercial systems capable of measuringwavelengths of 190 to 2700 nm which would correspond to θ