The grafting density of CFG is controlled by the reaction time and very high levels of functionalization, up to the failing of the Tuinstra–Koenig (T–K) relation, while the functionalization layer remains at monolayer height. The grafting ink, effective for days at room temperature, can be used at ambient conditions and renders the patterning CFG by direct writing as easy as writing on paper. In combination with thermal sample treatment, reversible functionalization is possible by subsequent writing/erasing cycles.Covalent functionalization of graphene (CFG) has shown attractive advantages in tuning the electronic, mechanical, optical, and thermal properties of graphene. However, facile, large‐scale, controllable, and highly efficient CFG remains challenging and often involves highly reactive and volatile compounds, requiring complex control of the reaction conditions. Here, a diazonium‐based grafting ink consisting of only two components, i.e., an aryl diazonium salt and the solvent dimethyl sulfoxide (DMSO) is presented. The efficient functionalization is attributed to the combination of the solvation of the diazonium cations by DMSO and  A grafting ink displays unprecedented capability for the covalent functionalization of graphene, achieving a functionalized monolayer with ultrahigh grafting density. The writing is simple, efficient, and reversible, making the patterned covalent functionalization of graphene straightforward. Tailoring these basic properties is crucial for the application of graphene‐based materials in a wide range of applications. A promising approach therefore is the covalent modification of the sp2 hybridized graphene lattice. However, due to the chemical inertness of the delocalized π‐system of graphene, highly reactive species are required to achieve a covalent functionalization of graphene (CFG). Aryl radicals present such a reactive species, which has been extensively used for covalent modification of graphite and graphene. One of the approaches to generate aryl radicals is by the reduction of an aryl diazonium cation via electron transfer (ET) from graphene. To this end, several strategies to promote the ET between graphene and diazonium cations to realize the CFG have been developed.Graphene as a typical 2D material consists of spoperties.5, 6Figure  Although electrochemical grafting has been used extensively for the covalent functionalization of various surfaces, it is restricted to electrically conductive surfaces and the large‐scale surface functionalization remains challenging.Electrochemistry has been used to promote the ET and reduce the diazonium cations, whereby the graphitic substrate is used as the cathode in the electrochemical cell and thus injected with electrons Figure 1a.s Figure .Figure To further investigate the morphology of the grafted layer, the functionalized graphene was characterized by atomic force microscopy (AFM). Large‐scale AFM images show the formation of a uniform grafted layer on the functionalized graphene (80 mM NBD and 10 min) Figure . Interes2 was imaged by scanning tunneling microscopy (STM), which is known to show grafted molecules as protrusions. In Figure 2 confirm covalent functionalization, although the resolution is limited due to the intrinsic limitations of the sample, i.e., low electrical conductivity and high roughness. The large‐scale images are dominated by the topographic features of the substrate SiO2  for Chinese calligraphy (鲁汶 Chinese name of Leuven), on a 1 by 1 cm2 graphene sample (SLG/SiO2)  Figure  clearly 2.3 Additionally, DMSO has been shown to be a good solvent for stabilizing graphene in suspension. This is attributed to the formation of a stable DMSO solvation layer confined on the graphene lattice, in which the DMSO molecules in contact with the graphene lattice preferentially adopt either an oxygen‐down or oxygen‐up molecular orientation, thereby affecting the electronic state of graphene. Likewise, we demonstrated n‐doping of DMSO, measured under dry conditions after removal of excess solution, indicating the strong affinity of DMSO to graphene and the formation of an adsorption layer, in agreement with previous reports. Overall, DMSO has the capability to solvate the diazonium cation as well as to wet and dope graphene , which is known to be less reactive than graphene, the surface functionalization doesn't take place  and 3,5‐dichlorobenzenediazonium salt (DCBD), respectively, and drop‐casted the grafting ink onto SLG/SiO2. Drop‐casting the BBD grafting ink resulted in an I(D)/I(G) ratio of 2.9 after a functionalization time of 10 min and 3.6 after 15 min /I(G) ratio (1.6) after a functionalization time of 10 min with the DCBD grafting ink is lower compared to the other diazonium salts, but nevertheless shows successful covalent modification Figure . Further73 alt because of the extreme thin organic layer, and the limited sensitivity of EDS, signals are dominated by the underlying substrate (O and Si from SiO2/Si wafer)  measurements were carried out to visualize the functional surface and probe the element distributions. The SEM images , which was stored for different times, i.e., freshly prepared or stored at RT for 3 days or 14 days, respectively /I(G) ratio of ≈4.1. Even the 14 days old grafting ink still gives an I(D)/I(G) ratio of ≈1.2 , the composition of the grafting ink (80 × 10−3 m NBD in DMSO) was followed over time at RT /I(G) ratio at each temperature step  and functionalization time (10 min). Therefore, a SLG/SiO2 sample was repeatedly functionalized and subsequently de‐functionalized by annealing to 400 °C, whereby a Raman mapping of the sample was performed after each treatment /Si (1 × 1 cm2) (SLG/SiO2) were obtained from Graphenea and were used as received.4‐Nitrobenzenediazonium (NBD) tetrafluoroborate (98%) was purchased from TCI EUROPE. 4‐bromobenzenediazonium (BBD) tetrafluoroborate (96%), 3,5‐dichlorobenzenediazonium (DCBD) tetrafluoroborate, dimethyl sulfoxide (DMSO) (99.9%), and pyridine (99.8%)) were purchased from Sigma‐Aldrich. Ethanol (Spectroscopy purity) from EMD Millipore. Acetonitrile  from VWR CHEMICALS. All chemicals were used without further purification. High purity water  was used for all experiments. The pristine samples of in situ CVD‐grown single layer graphene on copper (diameter 1 cm) (SLG/Cu) and the transferred single layer graphene to SiO2 were first characterized by Raman spectroscopy before the doping experiment. Then the same graphene samples were used to check the doping effect of the candidate solvents. Typically, 100 µL pure solvent was drop‐casted onto pristine SLG/SiO2 for 10 min, and then the graphene sample was dried under argon flow. The dried samples were stored in a nitrogen gas atmosphere prior to further characterizations.Pristine samples of SLG/SiO2) were first analyzed for quality by Raman spectroscopy. NBD solutions were prepared by dissolving NBD in the 4 candidate solvents , and subsequently the effect of spontaneous CFG on SLG/SiO2 was tested for the 4 different NBD solutions. Typically, 100 µL NBD solution was drop‐casted onto the surface of SLG/SiO2 at room temperature (RT). After a given time, the CFG reaction was stopped by removing the droplet of NBD solution and rinsing the surface with the solvent used. The functionalized graphene was dried using argon flow. For DMSO, a series of CFG experiments were carried out probing concentration dependency, functionalization time dependency and reactivity of different diazonium cations (BBD and DCBD). In order to test the stability or lifetime of the grafting ink, the inks were stored at RT for different times, prior to using them for graphene functionalization. In addition, SLG/Cu was also used to repeat the CFG experiments. The dried samples were stored in a nitrogen gas atmosphere box prior to further characterizations.Pristine samples (SLG/SiO−2) using an objective . The Raman scattering signal was collected with the same objective and directed to a Raman spectrograph  equipped with a cooled charge‐coupled device (CCD) camera operating at −100 °C  through a dichroic mirror, pinhole and a long pass filter . The accumulation time for a spectrum was 1 s. Raman mapping was performed based on array scanning  resulting in 400 Raman spectra.Raman characterization was performed at room temperature using a Raman microscope . The 632.8 nm He‐Ne laser beam was directed and focused onto the surface of graphene . Raman mapping was performed based on array scanning . Pristine graphene was obtained upon heating to 400 °C. After cooling to room temperature, the sample was again exposed to the grafting ink leading again to CFG.Temperature‐dependent Raman measurements were performed in a Linkam stage HFS600, equipped with a liquid nitrogen controller for temperature control under a constant flow of nitrogen. A sample of functionalized SLG/SiO−1) with a resonance frequency around 100 kHz were used for the AFM imaging. OMCL‐AC240TS‐R3 probes (spring constant ≈2 N m−1) with a resonance frequency around 70 kHz were used in the contact mode for locally removing, i.e., nanoshaving, the functionalized layer. All STM experiments were performed at room temperature (21–23 °C) using a PicoLE (Keysight) machine operating in constant‐current mode. STM tips were prepared by mechanical cutting of Pt/Ir wire .AFM images were obtained using the Cypher ES (Asylum Research) system at 32 °C in tapping mode at the air/solid interface. OMCL‐AC160TS‐R3 probes (spring constant≈26 N mScanning electron microscopy/energy‐dispersive X‐ray spectroscopy (SEM‐EDS) measurements were obtained using a FEI Quanta FEG‐250 environmental SEM equipped with a spectrometer for EDS. The SEM images were recorded with operating voltage of 30 kV and the EDS mapping was recorded with operating voltage of 5 kV.α X‐ray source (120 W). Spectra were acquired using hybrid (magnetic/electrostatic) lens mode and slot aperture, with the analyzer operating in fixed analyzer transmission mode. Survey spectra were acquired with a pass energy of 160 eV, while high resolution spectra were acquired at 20 eV. Samples were electrically connected to the spectrometer using silver paint and measurements were made on three separate areas per sample. The binding energy scale was corrected to Ag 3d5/2 at 368.21 eV as measured on a clean silver foil on the same day as the sample analyses, using the same measurement conditions.X‐ray photoelectron spectroscopy (XPS) characterization was performed on a Kratos Axis Supra photoelectron spectrometer with a monochromated Al K1H‐NMR) spectroscopy was performed on a Bruker AMX 400 MHz NMR spectrometer. The solution of 80 × 10−3 m NBD in DMSO‐d6 was prepared and kept at room temperature. Chemical shifts (δ) are reported in parts per million (ppm) referenced to tetramethylsilane (1H). 1 mg of dimethylsulfone (10.6 µmol) was added to 0.5 mL of the stock solution and was used as standard to calculate the amount of product present in the solution. The spectra were analyzed with MestReNova software.Proton nuclear magnetic resonance (Mass spectrometry (MS) characterization was performed on a RADIAN ASAP MS (Waters) with a single quadrupole mass detector using atmospheric pressure chemical ionization. The spectra were analyzed with MassLynx MS software.3 covalent defects), D′ band , G band (intrinsic band to graphene), and 2D band (intrinsic band to graphene) were focused. The band position, intensity, and full width at half maximum (FWHM) of these bands were obtained. The intensity ratio of two different bands, such as I(D)/I(G), I(G)/I(2D) and I(D)/I(2D), were calculated t. Based on 400 values for every Raman map, further the statistical analysis regarding the band position, FWHM, and intensity ratio was done, obtaining the average value, error bar (the standard deviation), and histogram distribution.The AFM images, STM images, and the corresponding 3D representations were analyzed using Scanning Probe Imaging Processor (SPIP 6.3.5) software from Image Metrology ApS. The Raman result analysis is based on the Raman mapping . The D band (related to the presence of spThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Electronic structure calculationsdisclose that significant p-type doping occurs due to a combinationof sp3 bonds formed between C and O atoms at the interfaceand possible slightly off-stoichiometric defects of the aluminum oxidelayer. Furthermore, the sp3 hybridization at the AlOx/graphene interface leads to distinct magneticmoments of unsaturated bonds, which not only explicates the widelyobserved low spin-lifetimes in AlOx barriergraphene spintronic devices but also suggests possibilities for newhybrid resistive switching and spin valves.Adherence of metal oxides to graphene is of fundamentalsignificanceto graphene nanoelectronic and spintronic interfaces. Titanium oxideand aluminum oxide are two widely used tunnel barriers in such devices,which offer optimum interface resistance and distinct interface conditionsthat govern transport parameters and device performance. Here, wereveal a fundamental difference in how these metaloxides interface with graphene through electrical transport measurementsand Raman and photoelectron spectroscopies, combined with ab initioelectronic structure calculations of such interfaces. While both oxidelayers cause surface charge transfer induced p-type doping in graphene,in sharp contrast to TiO In particular, titaniumoxide and aluminum oxide have been widely used as tunnel barriers,primarily due to their efficacy and compatibility with device processingmethods. Although ultrathin metal oxide layers can be directly realizedusing atomic-layer deposition or sputtering techniques, these techniquescan lead to significant defects, impacting the overall structure andelectrical nature of graphene.7 Instead, Ti and Al aredeposited using electron beam evaporation in graphene spin devicesand are subsequently oxidized upon contact with air/O2.In graphene electronic devices, metal oxides are used as gate dielectrics,effective barriers for graphene tunnel junctions,8 and thin-film memristive devices9 for practical imitation of synaptic activities, where interfacecharge transfer and bonding can guide the resistive switching phenomena.10 For both planar and vertical graphene spintronicdevices,12 ultrathin layers (∼nm thickness)of the metal oxides serve as tunnel barriers offering optimum interfaceresistance to overcome the conductivity mismatch problem associatedwith electrical spin injection.14 However, obtainingfaithful pinhole-free coverage is challenging for both aluminum andtitanium oxides, prepared by e-beam metal evaporation and post-oxidation.In particular, compared to spin lifetimes up to ∼3.5 ns ingraphene spintronic devices using TiOx barriers,17 the AlOx-based deviceswidely show an order lower spin lifetime of ∼100 ps,20 which has been generally attributed to the presence of pinholes,consequent current crowding, and contact-induced spin relaxation.22 The one order lower performance of AlOx-based devices remains puzzling, despite the same fabrication processand similar thicknesses of oxides. Therefore, understanding the physicsgoverning graphene/metal-oxide interfaces is of fundamental significanceto graphene nanoelectronic and spintronic devices. While metals andmetal oxides on graphene introduce surface charge transfer p-typeor n-type doping arising from the difference in the work functionof the metal relative to graphene,24 the situation is non-trivial for tunnel barrier oxidessuch as ultrathin TiOx or AlOx on graphene. Considering expected charge transfereffects, the redistribution of electron density after oxidation ofmetals is unclear, even from a theoretical perspective. In additionto surface charge-transfer doping, in-plane and out-of-plane defect-relateddoping in graphene can greatly influence charge and spin relaxation.The possibilities of introducing long-range and short-range scatterers,defects due to ultrathin oxide layers on graphene, and their directinfluence on electrical properties of graphene and spin relaxationin tunnel transport through such barriers have never been explicit.This investigation aims to uncover, at an atomic level, the importantdifferences in the nature of defects between Al oxide and Ti oxideadhering to graphene for their influence on electrical and spintronicperformance.Graphene has evolved into an ideal mediumfor quantum and spintransport applications and a unique integration platform for complexheterostructures with other two-dimensional (2D) materials.x and AlOx adsorption on the electronic properties of fully covered graphene.To understand the electronic alterations due to oxides, we measuredelectrical properties on the same devices before and after the oxiderealization by metal deposition and oxidation. X-ray photoelectronspectroscopy (XPS) and Raman spectroscopy were used to determine thenature of doping and oxidation states of C, Al, and Ti in AlOx- and TiOx-coveredgraphene and their distinct interface behavior. The topography, probedby atomic force microscopy (AFM), shows characteristic features andcoverage unique to each kind of oxide. We correlate these resultswith electronic structure calculations to understand the intricateinterfacial properties and possible atomic and electronic configurationsthat lead to our experimental observations. Finally, we discuss howthe interface defects observed in this study illuminate the currentunderstanding of spin relaxation in the widely used tunnel barriersin graphene spintronics and lead to new implications for nanoelectronicand spintronic devices.In this work, we explore themodifications in graphene due to itsfull coverage with metal oxides through electrical transport measurements,spectroscopic techniques, atomic force microscopy, and theoreticalelectronic structure calculations. To faithfully explore the extrinsicdoping, defect effects, and their implications, we investigated theimpact of TiOSupporting Information).Next, electrical measurements were performed on the resulting devicesto obtain transport parameters of the pristine graphene channels.After these initial measurements, the devices were subjected to anadditional layer of metal oxide by electron beam evaporation and oxidationin open air. The critical part of the procedure is the Ti or Al (0.8nm) deposition on the same device and keeping the device working forrepeated measurements with the metal oxide layers on top of graphene.This allowed us to understand the modification due to doping and possibledefect creation in the same graphene stripes.R□) with varyinggate voltage (VG). To determine the contributionstemming from graphene and graphene covered with TiOx/AlOx, Dirac curves were measuredon the same devices before and after the deposition of the metals.As shown in VD), shifts towardthe positive gate voltage region. Such a shift means that these metaloxides cause a downward shift of the Fermi level in graphene, implyingp-type doping. It is worth noting that the VD shift (ΔVD) is significanteven with an ultrathin ∼1 nm layer, and the interface trapdensity of states for the acceptor is affected by both types of oxides,as evidenced by ΔVD. In VD , minimum conductivity(σ0), and mobility (μ), both oxide-overlaidgraphene samples show reasonably good values, and for most of thedevices, the changes are moderately small (similar to or ∼10%for most devices) from initial pristine graphene devices to graphene/oxidedevices. Strikingly, the sheet resistance at the CNP is similar forgraphene before and after metal oxide realization, indicating a minimumconductivity that remains reasonably intact  a lowtrap density in all samples, and the minor changes in electrical parametersafter the realization of top oxide layers can be linked to modificationsin long-range Coulomb scattering due to charged impurities25 and the short-range defect scattering,26 including possible sp3 defects. Consideringthat Al and Ti metals result in n-type doping in graphene,28 these observations suggest thatthe p-type doping of ∼1012 to 1013 cm–2 (for change in ΔVD of ∼ 50–100 V) is primarily due to the surface chargetransfer between the oxide layers and graphene for most devices. Thismeans that the oxide layer coverage achieved by electron beam evaporationand subsequent oxidation can be used to protect graphene without drasticallyaltering its properties. The charge transfer serves as a tool to tunethe carrier concentration faithfully. It is known that in-plane defectsin graphene can lead to n-type doping,29 which rules out such defects. However, in addition to charge-transferdoping, sp3 out-of-plane defects could also lead to p-typedoping30 and can cause spin-flip scatteringas well as spin precession relaxation in graphene. To further explorethe nature of such defects, we performed XPS measurements (see samplecharacterization details in the Supporting Information) on our samples.The initial characterizationof changes in the graphene propertieswas carried out by gate-dependent measurements of four-probe channelsheet-resistance , which signals strong evidence of sp3 defectscreated in the graphene lattice during the Al oxidation. Conversely,the transport parameters suggest that sp2 contributionshould maintain dominance even for Gr-AlOx, so significant quenching of the signal of sp2 contributioncan be due to the added surface oxide layers. Unlike Gr-AlOx samples, we observe a lower value of sp3/sp2 ≈ 1.6 for Gr-TiOx, suggesting a lower-level source of the sp3 signal. Here,in our analysis, subtracting the sp3 contributions of baregraphene from our oxide samples can reveal some sp3 contributionalso in Gr-metal oxide samples. However, since each sample has itsown background, for comparisons, we chose to look at the sp3/sp2 intensity ratios. Considering that high spin lifetimeswere achieved with TiOx tunnel barriers,the increased sp3 intensity does not necessarily mean ansp3 hybridization of the graphene lattice.34 In fact, with a large 100 μm X-ray probe diameter,a significant sp3 contribution can originate from the PMMAresist residues and related effects intrinsic to the CVD graphenetransfer process36 (similar to the sp3 background in pristine graphene). This, and the possible reductionin sp2 intensity due to oxide coverage, could increasethe observed intensity at the sp3 binding energy for Gr-TiOx. Additionally, it is worth noting that surfacecarbon species bonded to oxygen atoms can have binding energies equivalentto those of sp3-carbon,34 whichcould further add to the surplus intensity at the sp3-bindingenergy position for the Gr-TiOx sample.Thus, the XPS measurements with large-area sampling give qualitativeevidence of the presence of sp3 carbon in the graphenelattice covered with AlOx. On the otherhand, large-area sampling can be circumvented by micro-Raman characterization. –1, respectively, were obtained. The same peaks were also identifiedon the graphene samples with AlOx or TiOx layers, confirming the integrity of graphenesheets covered by oxide layers.In I2D/IG) isa parameter to determinethe quality and monolayer structure of graphene.40 Here, in pristine graphene and graphene with TiOx, I2D/IG ≥ 2 confirms the good quality of the CVD polycrystallinegraphene that we employed in this study.41 However, in the presence of AlOx, grapheneshows different behavior, with the value of I2D/IG significantly decreasingto 1.45, which suggests possible degradation of the sp2 structure of graphene. In addition, the G peak’s doping sensitivityhelps confirm the nature of doping. The location of the G peak forpristine graphene is 1590 cm–1. For graphene coatedwith AlOx, the peak shift was approximately3 cm–1 and for the case of TiOx, it was approximately 13 cm–1 compared withpristine graphene. A similar shift was also observed for the 2D peak.Such a Raman shift to the left in the oxide-layered graphene indicatesa p-type doping effect, which is in good agreement with our transportand XPS measurements. However, in the case of aluminum oxide-coveredgraphene, strikingly, we observed the emergence of the D peak (near1340 cm–1), which is a signature of Raman-activedefects in graphene, suggesting the introduction of appreciable sp3 carbon defects, a source of graphene modification by AlOx only. Although Raman spectroscopy in mostcases serves as a qualitative analysis, it is possible to quantifythe presence of defects in graphene. Using the model proposed in literature,42 we obtained the concentration of defects fora graphene sample with AlOx by extractingthe G to D intensity ratio from the spectrum and the excitation laserwavelength (see Raman spectroscopy details in the Supporting Information). From the estimation, we found a concentrationof defects for graphene with evaporated Al (0.8 nm) of ∼1.4× 1011 cm–2, which is nearly onedefect per 10,000 carbon atoms. As stated earlier, for a large shiftin VD of ∼ 50–100 V, a correspondingdoping of 1012 to 1013 cm–2 can be expected. Therefore, the significant doping is due to surfacecharge-transfer doping, while the sp3-related defect contributionsare up to 2 orders less, which is unique to the AlOx-interfaced graphene. Despite the defects, the electrical propertiesof graphene are relatively preserved in graphene/AlOx devices. In graphene spintronic devices, the sp3 defects are expected to contribute to spin relaxation, mainly whenthe electrical spin injection is carried out in graphene spintronicdevices, resulting in significantly shorter spin lifetimes. This hasbeen conventionally attributed to pinholes in the AlOx barrier. Density functional theory (DFT)-based electronicstructure calculations showed that the interaction between grapheneand metal oxides is weaker for Ti oxide than for Al oxide.43 The Ti-donated electron charge density is highlylocalized around the neighboring carbon atoms, and titanium does nottend to form clusters, which is excepted to lead to uniform coverage.44 To understand the surface morphology of theoxide coverage over graphene, we investigated the samples by AFM.We chose a 1 μm × 1 μm scan area to check the shapeof the grains on top of the graphene surface and the height profile.Expectedly, there is a deviation from the smooth morphology of pristinegraphene to graphene with the oxide layers. The common feature ofoxide-covered graphene is the presence of ridges and grooves. Thecomparison between the surfaces is shown in x, perceptible swings in the height profile are also observed in theGr-TiOx system. One can attribute theother large clusters to possible resist residue regions observed inpristine graphene that can act as nucleation sites. Both oxides showan area roughness of Rq ∼ 1 nm,suggesting that both Ti and Al deposited on graphene by e-beam evaporationand following oxidation of the metals do not necessarily lead to fullcoverage, and hence, current crowding can be a common problem forboth metal oxides. This leaves us with the additional sp3 defects unique to AlOx-layered graphene.Despite the XPS data indicating that Al and Ti are fully oxidized,we cannot assure perfect stoichiometric compositions leading to theobserved charge-transfer doping in graphene. In particular, previousDFT calculations established charge transfer from graphene to titanium.46 However, the charge transfer and sp3 defect interfacein graphene-Al oxide have not been addressed. To understand that onan atomic scale, we performed electronic structure calculations, shownin The ratio of the 2D peak to the G peak intensities. Each case leads to varyingresults of the electronic property of the composite. Here, we onlyhighlight three different interfaces where oxygen is in proximity to graphene and the total energy suggestsstable or metastable geometries. For all cases, the geometry was relaxedfollowing force minimization. For other geometries and details, seethe Supporting Information. x layers on grapheneusing the experimental oxide layer thickness value of ∼1 nm.Notably, calculations performed for the perfect stoichiometry (C8–Al12O18), with graphene interfacedwith aluminum atoms, did not yield any charge transfer and the Fermilevel remained intact (see the Supporting Information). However, when oxygen atoms are in proximity to graphene, a stronghybridization between the p-orbitals from oxygen and pz-orbitals from carbon atoms causes the Dirac coneto be strongly distorted and positioned above the Fermi level.Taking experimental conditions into account andusing DFT calculations,we performed an interface study of the AlO12O17) give rise to systematic Fermi-level shiftsof ∼1 eV and p-doping with oxygen atoms closer to the graphenelattice . Nevertheless, thepresented calculations show how sp3 bonds can induce significantband gap opening. The practical scenario for our samples preparedwith CVD graphene can combine these two features with every 10,000th location featuring a band structure as in 3-hybridized defect centers are a significantfeature of AlOx, which is expected tobuckle graphene locally. Such buckling is known to introduce spin–orbitcoupling47 and magnetic moments.48 Our calculations with both perfect stoichiometricand non-stoichiometric Al-oxide sp3-bonded systems leadto an effective magnetic moment situated on unsaturated bonds, withvalues ranging from 0.44 μB (off-stoichiometric)to 1 μB (high-density sp3-bonded lattice)per unit cell.Interestingly, calculations with a slight off-stoichiometry (Allattice 5awithou3 defects at the graphene/AlOx interface can have significant implications forgraphene spintronics, where spin currents are injected from a ferromagnetinto graphene through the ultrathin oxide barrier. Spin–orbitcoupling and local magnetic moments can dominate spin-flip and resonantscattering at graphene/AlOx interfaces.Specifically, the resonant scattering with magnetic impurities hasbeen considered responsible for observing low spin lifetimes of ∼100ps, widely observed in AlOx barrier graphenespintronic devices.49 With no magneticordering, the sparsely distributed sp3-based magnetic momentscan become an additional source of spin relaxation in AlOx barrier-based devices, other than the previouslyattributed pinholes in Al-oxide barrier-based studies in graphenespintronics. Furthermore, our calculations show that despite thesemagnetic moments being predominantly concentrated at non-saturatedbonds (as shown in 50 enhanced spin-scattering due to magnetic momentformation in graphene51 and reduced spinlifetimes due to colossal spin–orbit coupling52 have also been reported. Therefore, spin transport experimentswith aluminum oxide-covered graphene could provide further insightsinto such observations. At the same time, the sparse magnetic momentsat graphene/AlOx interfaces could be orderedin exotic heterostructures via proximity effects11 for enhanced proximity-induced magnetism in graphene53 and in a controlled manner for novel spin valves. For resistiveswitching devices, the sp3 bonds can act as carrier trapsfor synaptic junctions, and oxygen ions in the AlOx layer can be highly mobile in graphene and could form covalentbonds with the broken bonds of graphene for setting and resettingprocesses in memristive devices.10 Thus,magnetic defects with exchange-biased layers show potential for hybridmultilevel spin valve-resistive switching random access memory devices.In this investigation, we observed that non-invasivee-beam-evaporatedAl and Ti-based oxides with metals near full-oxidized states adherein subtle ways to graphene. While both oxides cause surface charge-transferdoping, the sp12 to 1013 cm–2 for both metal oxides, with reasonably preserved charge mobilityand sheet resistance. However, X-ray photoelectron spectroscopy suggestsan intricate nature of the doping, not just due to charge transferfrom C-atoms but also due to significant sp3 defects forAl-oxide. This is precisely confirmed by the emergence of the sp3 defect-active Raman D band for Al-oxide-layered graphene,in sharp contrast to Ti-oxide-layered graphene, where the band wasabsent. Our electronic structure calculations suggest that the observed100 ppm sp3 defects originate from O bonding with C andan out-of-plane buckling of carbon atoms. Such defects in Al-oxide-layeredgraphene can lead to a local magnetic moment in ∼0.5–1.0μB, primarily located on unsaturated bonds of O atoms.In the Ti-oxide case, this moment is absent, which offers an explanationfor the dramatic difference in spin lifetimes widely observed in deviceswith different oxide tunnel contacts. At the same time, these resultsprovide new implications for developing unique interfaces for hybridgraphene resistive switching and spintronic devices.In summary, we explored the subtle natureof ultrathin Al and Tioxides interfacing with graphene. With similar coverage observed byAFM, electrical measurements revealed surface charge transfer p-typedoping of ∼10


K and K’ points of the hexagonal Brillouin zone with topological winding numbers ±1. This Dirac cone description is nearly perfect within a ∼3 eV energy range—more than 100 times room temperature. Moreover, the chemistry of graphene sets its Fermi energy right at the Dirac points. A historic question, first posted by Linus Pauling, is whether the Dirac cone can be gapped as a result of the electron–electron interactions [Graphene is an amazing material that presents us with new challenges and opportunities, even after two decades of extensive study. The two linear energy bands of graphene cross at the ractions  because in situ manipulation via electric and magnetic fields [About a decade ago, two graphene architectures were theoretically shown to produce strongly interacting phases. One is an artificial architecture formed by overlaying two graphene layers with a small twist angle . The othc fields .N-layer system generalizes the monolayer's features: a pair of bands of approximately ±Np dispersions touch at the K and K’ points with the topological winding number ±N [For twisted bilayer graphene, the Dirac velocity drops to zero as the twist angle turns from 30° to ∼1°, dubbed the magic angle . A primeumber ±N . At charumber ±N ,7,8. At umber ±N ,10.π and the second moiré band is filled in a way such that every three moiré unit cells lack one electron [The magic occurs when two AB bilayer graphene, the duo duo, are twisted by 0.75° over These significant results  call forConflict of interest statement. None declared.


Surface plasmon polaritons (SPPs) on the graphene metasurfaces (GSPs) are crucial to develop a series of novel functional devices that can merge the well-established plasmonics and novel nanomaterials. Dispersion theory on GSPs is an important aspect, which can provide a basic understanding of propagating waves and further guidance for potential applications based on graphene metamaterials. In this paper, the dispersion theory and its modal characteristics of GSPs on double-layer graphene metasurfaces consisting of the same upper and lower graphene micro-ribbon arrays deposited on the dielectric medium are presented. In order to obtain its dispersion expressions of GSP mode on the structure, an analytical approach is provided by directly solving the Maxwell’s equations in each region and then applying periodical conductivity boundary onto the double interfaces. The obtained dispersion expressions show that GSPs split into two newly symmetric and antisymmetric modes compared to that on the single graphene metasurface. Further, the resultant dispersion relation and its propagating properties as a function of some important physical parameters, such as spacer, ribbon width, and substrate, are treated and investigated in the Terahertz band, signifying great potentials in constructing various novel graphene-based plasmonic devices, such as deeply sub-wavelength waveguides, lenses, sensors, emitters, etc. As one of the most important research fields in modern optics and nanophotonics, plasmonics has shown its strong vitality and lasting impact by taking advantage of the coupling between light and free carriers on the conducting and/or semi-conducting films ,2,3,4. TGraphene is a novel nanomaterial which is composed of an ultra-thin two-dimensional (2D) carbon atoms sheet within a honeycomb lattice. Its unique atomic arrangement results in a linearly carrier dispersion and ultra-high carrier mobility at room temperature ,8. TheseDespite this progress on the graphene metasurfaces with various types of topological structures ,41,42,43In this paper, the dispersion theory and its mode distributions on double-layer graphene metasurfaces with various physical parameters are presented, studied, and analyzed in THz band. The general dispersion theory is firstly provided by treating different field expressions in each region, along with the periodical boundary condition on double-layer graphene metasurfaces. Following these fully analytical expressions with different dispersion characteristics, its GSP dispersion diagrams and the mode distributions are studied with different physical parameters. Its potential applications based on double-layer graphene metasurfaces are also envisioned and discussed.ε has the same structural parameters of width d and period p. The bi-layer metasurfaces align with each other in both longitudinal and vertical directions and are separated by an air gap depth, as denoted by g. Its cross-section views of double-layer structure are schematically plotted in Distinct to previously double-layer graphene sheet with homogeneous boundary on the interface ,19,20,21σ(ω) is the frequency-dependent surface conductivity distribution of complete graphene sheet and m is the arbitrary integer. The surface conductivity of graphene has been widely applied [σ(ω) = intraσ + interσ. For intraband conductivity, it is given as:The key to obtaining its dispersion expressions on double-layer graphene metasurfaces is to apply the periodical surface conductivity to the different field expressions in each region, as indicated by I, II, and III in  applied ,41,42,43cμ| > > |kBT|:For interband conductivity, it can be approximated by the following under |f, chemical potential μc (or Fermi level), electron relaxation time τ (τ−1 is scatter rate), and temperature T. Some other constant parameters are electron charge e, reduced Planck’s value ħ, and Boltzmann constant kB. j is an imaginary unit. The intraband and interband conductivity can be simultaneously applied to graphene metasurface according to different operation frequency spectra. For some studies in the low frequency band, such as THz [The above surface conductivity of graphene is a function of radian frequency ω = 2πh as THz ,41,42,43x > g/2), its electric field along the z direction and magnetic fields along the y direction are as follows:In order to obtain its dispersion equations on double-layer graphene metasurfaces in x < −g/2) can also be obtained similarly, as below:Moreover, the field expressions in region III  denotes its propagation constant of the considered harmonic mode of n along the propagation direction. κ is the decay coefficient in the perpendicular direction, as calculated by 2κ = nβ2 − εk2, k = ω/c is the wave vector in free space, and c is light velocity.The fields inside the upper and lower dielectric medium are periodical by the Block’s harmonic waves along propagation direction z. g/2 < x < g/2), its electromagnetic fields obey the following expressions:nC and nD are the unknown index and ε0 is air permittivity. κ is the decay coefficient in the perpendicular direction. κ2 = nβ2 − k2. Other symbols are the same as those in Equations (4)–(7). sinh and cosh are hyperbolic sine and cosine functions, respectively. The similar derivation processes and obtained field expressions are also successfully applied to some other double-layer SPP structures, such as corrugated metallic waveguide [In the air gap region II, which is between upper- and lower-layer graphene metasurface , the following boundary conditions should be obeyed:Based on the above electromagnetic fields Equations (4)–(9), in region I, II, and III, the periodical surface conductivity and tangential electric field boundary conditions on the upper interface of x = −g/2 plane), there should be following expressions:Moreover, for the lower graphene metasurface between region III and II (Applying the electric field of Equations (4), (6) and (8) in region I, III, and II to the boundary conditions of (10) and (12), the following equations are obtained:Furthermore, taking the magnetic field of Equations (5), (7) and (9) in region I, III, and II to the boundary conditions of (11) and (13), we have the following equations:nA, nB, nC, and nD in Equations (14)–(17). The Equations (14) and (15) can be readily transferred into the following simple Equations (18) and (19), respectively. By integrating the periodical surface conductivity in Equations (16) and (17) in one period according to expression (1), the following Equations (20) and (21) concise equations also arise after some mathematic treatments:These four Equations (14)–(17) are the foundations of final GSP dispersion expression results. Obviously, the challenges are eliminating these four unknown indexes of g now become the well-known infinite surface conductivity of σ(ω) in Equations (20) and (21) with the help of our special calculations. Finally, the expressions of nA and nB in Equations (18) and (19) can be directly applied to Equations (20) and (21). Thus, the four unknown indexes are reduced to only nC and nD within two equations. If we solve these two equations by eliminating the two unknown nC and nD, the final GSP dispersion expression can be obtained directly in the proposed double-layer graphene metasurfaces system. For symmetric GSP mode, we have the following expression:It should be noted that the periodical surface conductivity of graphene in Equations (16) and (17) with σFor antisymmetric GSP mode, its analytical expression is:The symbols in the analytical dispersion expressions are the same as those in the above solved field expressions. The obtained concise dispersion equations with frequency-wave vector relation include some structural and material parameters and, thus, provide a simple yet useful tool to analyze the basic propagation properties of GSP mode on double-layer graphene metasurfaces in d = p, the results of (22) and (23) become the simple one, which has been discussed in [g as infinite in Equations (22) and (23), GSP mode on the upper- and lower-layer one will decouple with each other; thus, the two different modes become the unified single one with the same dispersion expression as shown in [Although the dispersion theory and its expressions on double-layer graphene structure without periodical patterns have long existed in the literature, such as ,19,20,21ussed in ,17,18. Aussed in ,47; thusshown in  and otheshown in ,61,62,63d = 0.5 μm, p = 1 μm, and g = 1 μm. Moreover, the graphene material parameters are also set as constant as: μc = 0.1 eV, τ = 0.5 ps, and T = 300 K. The upper and lower dielectric is silica with permittivity of ε = 3.92 in THz band [As a specific illustration of the GSP mode on double-layer graphene metasurfaces, the transcendental dispersion equations are solved and its curve lines with symmetric and antisymmetric mode are plotted in THz band ,50,51,52THz band . The oblCompared to GSP mode on the single graphene metasurface, GSP mode on double-layer structure splits into two newly symmetric and antisymmetric modes, which locate on the different regions of dispersion diagrams. Further, its phase velocity difference becomes larger in the middle of dispersion lines, as illustrated in the inset of ε = 1.0 (air) and ε = 3.92 (silica) in ε = 1.0 (air) and ε = 3.92 (silica), respectively. It is clarified that the field concentrations of symmetric and antisymmetric GSP modes with silica cladding are better than thosr of GSP mode with air cladding. The locations of upper and lower graphene metasurface are indicated by the dotted white lines. The superstrate and substrate medium are clearly marked in the structure. Finally, we examine the influence of structural parameters of graphene ribbon width d/p and the gap size g on the propagating GSP mode on double-layer structure. GSP dispersion diagrams and its propagation characteristic on double-layer graphene metasurfaces can be obtained and analyzed with arbitrary structural parameters based on the obtained analytic dispersion Equation of (22) and (23). In addition, the mode analysis and dispersion engineering lay the foundations for further applications based on the gradient index distributions, which rely on the structural parameter changes of double-layer graphene metasurface, such as graphene lenses, couplers, emitters, absorbers, and sensors. Here, we consider different dispersion modes with various dielectric mediums, spacer, and graphene ribbon widths on the structure. In this paper, the dispersion theory and its model properties of GSP mode on double-layer graphene metasurfaces are provided by solving the Maxwell’s equations combined with the periodical surface conductivity boundary conditions on the structure. Further, the analytical dispersion expression for symmetric and antisymmetric GSP modes is obtained and its detailed mode analysis with different structural dielectric and graphene ribbon parameters are presented in THz band. The dispersion theory on the bi-layer graphene metasurface provides a fast and powerful tool to understand and analyze its fundamental propagation characteristic of GSP mode on the complicated structured metasurfaces. The proposed dispersion theory on GSPs with double-layer graphene metasurfaces can be further verified by some numerical simulations and experimental measurements in the future. In addition, its presented dispersion characteristic is fundamental to design some novel THz devices on the bi-layer structure, such as couplers, meta-lenses, transmit-array, emitters, etc., in the future.


There are an estimated 460,000 Armenians in the United States, and more than half live in California. Armenian-Americans are generally represented within the ‘White’ or ‘Some Other Race’ race categories in population-based research studies. While Armenians have been included in studies focused on Middle-Eastern populations, there are no studies focused exclusively on Armenians due to a lack of standardized collection of Armenian ethnicity in the United States or an Armenian surname list. To fill this research gap, we sought to construct and evaluate an Armenian Surname List (ASL) for use as an identification tool in public health and epidemiological research studies focused on Armenian populations.Data sources for the ASL included the California Public Use Death Files (CPUDF) and the Middle Eastern Surname List (MESL). For evaluation of the ASL, the California Cancer Registry (CCR) database was queried for surnames with birthplace in Armenia and identified by the MESL.There are a total of 3,428 surnames in the ASL. Nearly half  of surnames in the ASL were not identified by the MESL. The ASL captured 310 additional Armenian surnames in the CCR than the MESL.The ASL is the first surname list for identifying Armenians in major databases for epidemiological research.The online version contains supplementary material available at 10.1186/s12874-023-01848-1. US Census race/ethnicity categories provide critical information allowing for health disparities to be recognized and addressed . These cUsing a common surname list is often employed to identify and study various ethnic groups –9. In paWhile the inclusion of Armenians in the Middle-Eastern studies is certainly an important step towards better representation of Armenians in research, studies specifically on Armenians are necessary to better understand health patterns among Armenians around the world –12. We sThe CPUDF is available through the Center for Health Statistics and Informatics (CHSI) branch of the California Department of Public Health (CDPH) and contains information about in-state California deaths . An annuThe MESL was created in 2007 and was extracted from a NUMIDENT extract file, a data source provided by the US Social Security Administration that began collecting place of birth in 1979 [The California Cancer Registry (CCR) is a comprehensive state-wide cancer surveillance program and meets SEER standards for quality and completeness of data . The CCRSoundex, which is a phonetic algorithm for indexing names based on sound rather than spelling [Soundex feature allowed for truncated Armenian last names in the MESL to be included in record comparisons. It also allowed flexibility in the matching process for surnames with special characters including spaces, hyphens, and capitalizations. For example, the surname ‘Ter-Minasyan’ was scored as a perfect match with ‘Ter Minasyan’.We used Match*Pro to link surnames in the CPUDF with Armenian surnames from the MESL. Match*Pro is a probabilistic linkage software developed by IMS  under contract with the National Cancer Institute (NCI). The Match*Pro configuration page includes blocking and matching methods, adjusting for blocking sensitivity, and manual review tools to filter categorized matches. Last Name was the comparator of choice and the blocking strategy selected was spelling . The SouAll linked records were manually reviewed using the Match*Pro Linkage Results interface. In this step, records were reviewed to sort matches at the surname level. Linkage results were manually separated into two categories of match or non-match described in Supplemental Table , a common Russian patronymic suffix  [anz’ and ‘Ter-Prakhourany’. Because many Armenians changed the suffix of their last names during the USSR period to follow Russian patronymic suffixes, we included Armenian last names with a common Russian suffix. All of the 1,332 unique Armenian surnames from the MESL that were not identified by the CPUDF/MESL Armenian surnames linkage nor by the birthplace in Armenia queries in the CPUDF were retained in the ASL.Surnames from the CPUDF that were born in Armenia, but did not link with existing Armenian surnames in the MESL (Step 1), were manually reviewed and surnames meeting the following two criteria were deleted from the list: 1) had a length of less than 5 characters or 2) did not have a common Armenian surname suffix ov, ova) , 19, andSince birthplace in Armenia is a reliable measure for Armenian ancestry , we compWe also sought evaluate the country of origin of surnames in the ASL compared to the CCR Birthplace in Armenia list because surnames with birthplace in Armenia are likely to have originated in Armenia and therefore represent Armenian ethnic identity , 20. We After manual review of linked surnames between the existing Armenian surnames in the MESL and the CPUDF, we selected 1,290 unique surnames to include in the ASL  unique surnames from this linkage that would not have been identified by an exact matching strategy.The Soundex blocking strategy allowed for truncated surnames in the MESL to match with full Armenian surnames in the CPUDF. For example, the surnames ‘Haroutunia’ and ‘Martirosya’ from the MESL matched with the surnames ‘HaroutuniaThere were an additional 2,018 unique surnames in the CPUDF with a birthplace of Armenia that were not identified by the Armenian surnames in the MESL  were also identified by the ASL  had Armenia ranked first as the most likely country of origin and 431 (12.6%) as the second-most likely country of origin from NamSor  of these surnames had a birthplace of Armenia in the CPUDF. Given the unique characteristics of Armenian surnames and the small percentage of surnames in the ASL with a -ov, -ova suffix, we do not expect a remarkable number of non-Armenian Russians to be identified by the ASL [During the process of creating the ASL, we considered historical and political events that may have impacted data collection and representation of countries of birth. Specifically, Armenia gained its independence from the Union of Soviet Socialist Republics (USSR) in 1991, raising the question of whether surnames of those born in Armenia during the USSR (1920–1991) had Armenia listed as their country of birth . Our anathe MESL . Out of  the ASL , 19.ian’ was identified with the same record where the last name followed a different naming convention of ‘Danielson’. A common limitation we faced is the lack of mother’s last name, which may have precluded the identification of children of Armenian mothers with an Armenian last name and fathers with non-Armenian last names.Another challenge in creating surnames lists is changing surnames due to marriage or to follow naming conventions of a new culture and society after immigration. To address this issue, we included all available father’s last names from the California death records for both males and females. For example, father’s last name of ‘DanielUsing full surnames, as we did when creating the ASL, is particularly advantageous in large database linkages for several reasons. In probabilistic linkages, full surnames will have a higher similarity score when they match a full versus truncated version of the surname. Also, deterministic linkages can be utilized with non-truncated surnames. Lastly, name-checking technologies, such as NamSor, will return more accurate rankings of surname country of origin with full surnames, as many naming conventions, including Armenian, rely on the suffix to identify ethnic origin. Due to the novelty of this surname list, we did not have a ‘gold standard’ or contact people to confirm their ethnic origin to validate the ASL. While previous researchers who have created surname lists, such as the Arab surname list, have used self-reported ethnicity from telephone surveys as a ‘gold standard’ when validating new surname lists , we did I , while 22% of surnames with birthplace in Armenia had surname suffixes of  and 77% had surname suffixes beginning with the letter Y . We attempted to address this within the ASL, as the surnames added to the ASL were not limited to birth in Armenia. A potential limitation of the ASL is that a small percentage of people born in Armenia may have a non-Armenian last name or may not have Armenian origin because we retained Armenian surnames from the MESL. Further research application of the ASL will clarify whether any enhancements to the ASL are warranted.Comparisons of the ASL with a list of MESL surnames from the CCR were suggestive that the ASL identifies a considerable percentage (34%) of Armenian surnames not identified by the MESL. This may relate to a few characteristics of the list of Armenian surnames extracted from the MESL. In addition, the Armenian surnames were extracted from NUMIDENT using a filter of birth in Armenia and may exclude surnames of people who were born in other countries and who had different surname conventions than those who were born in Armenia. For example, in the CPUDF and MESL Armenian surname linkage results, we observed that 83% of surnames with birthplace in Russia followed a surname convention of the suffix beginning with the letter Country of origin checks using NamSor for the ASL surnames and the CCR Birthplace in Armenia surnames retrieved similar results, with Armenia ranked as the most likely or second-most likely country of origin for more than three-fourths of surnames, suggesting that the ability of ASL to identify Armenian surnames is comparable to the ability of a list containing surnames identified solely by birthplace in Armenia. Because the two lists had only about 30% overlap between surnames, it may be worthwhile to consider the combination of the two lists to optimize the identification of Armenian surnames in large population-based databases.The use of the ASL can increase the representation of Armenians in public health research. For example, the ASL can be used to identify Armenians in population-based cancer registry databases and observe cancer patterns by demographic and clinical factors. This will result in a clearer representation and understanding of cancer patterns among racial/ethnic categories where Armenians are commonly included, such as Middle-Eastern and White. Such data can inform health education and awareness campaigns to increase access to preventive healthcare services, such as screening, in the Armenian population. The ASL allows for the identification and representation of Armenians in a myriad of research endeavors and lays the groundwork as a valuable resource for research studies in public health, epidemiology, and other fields concerning Armenian communities.Additional file 1: Supplemental Table 1. Manual Review Categorization Rules, Public Use Death Files 1905-2020 and Middle Eastern Surname List (MESL) Armenian Surname Probabilistic Linkage.


Metabolomic analysis of 630 metabolites covering 14 small molecule and 12 different lipid classes was carried out using flow injection analysis tandem mass spectrometry for lipids and liquid chromatography tandem mass spectrometry for small molecules. Levels were correlated with survival and disease severity. We identified 109 deregulated analytes in IPF compared to HV in cohort 1 and 112 deregulated analytes in cohort 2. Metabolites which were up-regulated in both cohorts were mainly triglycerides while the main class of down-regulated metabolites were phosphatidylcholines. Only a minority of de-regulated analytes were small molecules. Triglyceride subclasses were inversely correlated with baseline disease severity (GAP-score) and a clinical compound endpoint of lung function decline or death. No changes in the metabolic profiles were observed following treatment with pirfenidone. Nintedanib treatment induced up-regulation of triglycerides and phosphatidylcholines. Patients in whom an increase in these metabolites was observed showed a trend towards better survival using the 2-years composite endpoint . In conclusion, we report major changes in metabolites in two independent cohorts testing a large number of patients. Specific lipidic metabolite signatures may serve as biomarkers for disease progression or favorable treatment response to nintedanib.Idiopathic pulmonary fibrosis (IPF) is a progressive disease with significant mortality and morbidity. Approval of antifibrotic therapy has ameliorated disease progression, but therapy response is heterogeneous and to date, adequate biomarkers predicting therapy response are lacking. In recent years metabolomic technology has improved and is broadly applied in cancer research thus enabling its use in other fields. Recently both aberrant metabolic and lipidomic pathways have been described to influence profibrotic responses. We thus aimed to characterize the metabolomic and lipidomic changes between IPF and healthy volunteers (HV) and analyze metabolomic changes following treatment with nintedanib and pirfenidone. We collected serial serum samples from two IPF cohorts from Germany ( Idiopathic pulmonary fibrosis (IPF) is a fatal disease with a mean survival time of 3–5 years . Two medThe technique of mass spectrometry based metabolome profiling has significantly improved during the last decade with metabolome measurements becoming increasingly robust and reproducible . The tecRecently the involvement of aberrant metabolic and lipid pathways have been implicated to affect IPF pathophysiology. Altered metabolism of the amino acids glycine, glutamine and arginine and dysregulated glycolysis was shown to promote profibrotic phenotypes via TGF-ß dependent pathways . For lipIn the context of these recent findings, we got interested in the metabolome of IPF patients and whether treatment with approved antifibrotic medication is capable of reversing metabolic changes or predicting therapy response. In order to address these questions, we performed serial serum metabolomic assays in IPF patients and healthy volunteers as comparators and correlated disease progression and severity.For this study we retrospectively selected patients who had a confident diagnosis of IPF in accordance with the practice guidelines issued by the American Thoracic Society (ATS) and the European Respiratory Society (ERS)  and wereh 2006, Hannover, #2923–2015 and #2516–2014, 2 Nov 2015).The study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. All patients provided written informed consent, and collection of bio-samples was registered at the German Clinical Trials Register (DRKS00000017 and DRKS00000620). The respective institutional review boards approved of the bio-sampling  we estimated a significantly regulated proportion of metabolites at about 15%. Using the maximum number of targeted metabolites of the MetSizeR package , an falser group . Groups Serum samples were collected prior to initiation of antifibrotic therapy and at follow-up between 2 and 6 months after treatment start . Blood shttps://biocrates.com/mxp-quant-500-kit, accessed 14 Dec 2021) using 10 µl of the sample as previously described  with use of the MxP Quant 500 kit  as per manufacturer’s protocol  and compared via rank-sum-test. A two-tailed p-value of <0.05 was considered statistically significant.For patient characteristics, categorical data was expressed as number (percentage) and compared via ChiDeregulation of metabolites between HV and IPF patients (at baseline) and changes following antifibrotic therapy (post vs. pre) were calculated using the R limma package  with paiBaseline metabolite concentrations were correlated with baseline GAP index and annualized FVC decline during follow-up calculating the Pearson correlation coefficient. To analyze impact on outcome, a composite endpoint including death, FVC decline of ≥10% from baseline or DLCO decline of ≥15% was calculated. Baseline metabolite concentrations in IPF patients were dichotomized by median and hazard ratios (HR) for the composite endpoint were calculated via cox-regression modeling using the metabolite median and GAP index. Identified hierarchical clusters from deregulated analytes following antifibrotic therapy were also analyzed with respect to the composite endpoint using the same cox-regression model.In the first cohort from Germany, 122 patients with IPF and 16 healthy volunteers of similar age  were included in the study . Median p < 0.001) while the comorbidity profile was similar.In the second cohort from Spain, 21 patients with IPF were included . The majority was started on nintedanib (71%) and 29% on pirfenidone. Notably, the overall disease severity measured by GAP score/index was higher in the first cohort  were considered for further analysis, consisting of 12 lipid and 13 small molecule classes. In the second cohort, a total of 42 samples were measured with a total of 451 considered analytes . The dataset of cohort 1 and 2 is available online .In a first step, samples from IPF patients in the first cohort before initiation of antifibrotic therapy were compared to healthy volunteers. For small molecules, a total of 12 analytes were significantly down-regulated in IPF (defined as FDR <0.05) and 4 were up-regulated . For lipd-Glutamine and d-Glutamate metabolism  with significant overlap . NotablyWe calculated the Pearson correlation coefficients between the baseline GAP points  and found an FDR corrected significant correlation in 94 metabolites . NintetyOf note, no significant correlation between annualized decline of forced vital capacity was found for any of the analytes.We then dichotomized the baseline analyte concentration by the median of the IPF cohort 1 and fitted a cox-regression model for the median cut-off for each analyte adjusting for age and baseline FVC and gender. There were 16 significant analytes on cox-regression, again with the majority being lipids . Seven aFollowing antifibrotic therapy of median 8 (5–16) weeks, another set of serum samples were collected and remeasured. Interestingly, we did not observe any deregulated analytes following treatment with pirfenidone in both cohorts.Following treatment with nintedanib in the first IPF cohort, there were 38 up-regulated analytes and 1 down-regulated analyte, all of which were lipids   had a trend towards better survival, albeit missing statistical significance  .To account for compatibility, 30 samples from cohort 1 were re-measured alongside with cohort 2, with good correlation between the re-measured samples and a median ratio between analytes of 1.03 (IQR 0.9–1.18) .Recent data from the cancer field and pulmonary fibrosis suggest a major role of metabolomic changes in both disease pathogenesis and treatment. On this background we got interested in the metabolome of IPF patients and whether pirfenidone or nintedanib induce any metabolic changes. We comprehensively studied the metabolome and lipidome of two IPF cohorts comprising 143 patients and age-matched healthy volunteers.The serum metabolome of healthy volunteers differed considerably from IPF patients in both studied cohorts. One-hundred-nine of the 466 (23.4%) included analytes were differentially abundant in IPF in the first cohort. Compared to healthy volunteers we found 44 analytes downregulated and 65 analytes upregulated. Most impressively were the changes in the lipidome. Among the 44 downregulated metabolites in serum of IPF patients were 8 amino acids or amino acid related metabolites, 4 biogenic amines or hormones, but the majority of the significantly downregulated metabolites were lipids including 9 (20.5%) lysophosphatidylcholines, and 23 (52%) phosphatidylcholines. On the other hand, 65 metabolites were significantly upregulated and these were again mostly composed of lipids (94%) but with different subclasses. The majority of the up-regulated lipids were triglyceride (75%) and some were ceramides (8%), sphingomyelins or cholesteryl esters. A similar metabolome profile in IPF patients was also described by Yan et al., although the study cohort was substantially smaller and consisted only of 22 IPF patients . In addiChanges in metabolome are highly disease specific and were reported to serve as robust biomarkers . The finInterestingly also in other types of organ fibrosis an increase in triglycerides was noted such as chronic kidney disease and fibrotic liver diseases . In addiLysophosphatidylcholines and phosphatidylcholines were on the other hand down-regulated in serum of IPF patients. A major constituent of surfactant are phosphatidylcholines and it is thought that decrease of these lipoproteins in IPF and COPD is caused by decreased surfactant protein production by reduced numbers of alveolar epithelial type II cells . Interesl-glutamine highly upregulated (Log2 fold-change 105) in IPF. TGF-β, upregulated in fibrosis, was shown to induce glutaminolysis in lung fibroblasts and consecutively leads to increased collagen production . None of these metabolites were differentially expressed in the comparison of healthy volunteers and IPF.in-vitro experiments with a macrophage cell line indicated that SU1498, a TKI blocking VEGF-R signaling, induced upregulation of triglycerides and a decrease in glycerophosphocholine  treatment. Growing evidence indicates major changes in metabolome with imatinib, a TKI targeting platelet-derived growth factor (PDGF) receptors, used for treatment in chronic myeloid leukemia . Likewisocholine . These dOur study has significant limitations. Since we found metabolites that correlated with disease severity, the milder disease extent in the second cohort may partially explain incongruent findings between the IPF cohorts and may hamper comparability. Further, the overall milder disease in cohort 2 and smaller group size prevented us from running correlations with clinical features and analyte concentrations in this cohort. The analytes identified to correlate with both survival and baseline GAP score showed a rather low correlation, rendering their biological relevance subject to further studies. Metabolomic measurements are subject to a variety of confounders, including environmental factors . The cohIn conclusion, we report major changes in metabolites in two independent cohorts testing a large number of patients. Several metabolites are associated with poor outcome. In summary, specific lipidic metabolite signatures may serve as biomarkers for disease progression or favorable treatment response to nintedanib.


The Angstrom-scale space between graphene and its substrateprovidesan attractive playground for scientific exploration and can lead tobreakthrough applications. Here, we report the energetics and kineticsof hydrogen electrosorption on a graphene-covered Pt(111) electrodeusing electrochemical experiments, in situ spectroscopy, and densityfunctional theory calculations. The graphene overlayer influencesthe hydrogen adsorption on Pt(111) by shielding the ions from theinterface and weakening the Pt–H bond energy. Analysis of theproton permeation resistance with controlled graphene defect densityproves that the domain boundary defects and point defects are thepathways for proton permeation in the graphene layer, in agreementwith density functional theory (DFT) calculations of the lowest energyproton permeation pathways. Although graphene blocks the interactionof anions with the Pt(111) surfaces, anions do adsorb near the defects:the rate constant for hydrogen permeation is sensitively dependenton anion identity and concentration. In contrast, anionsare prohibited from binding to the Pt(111) surface. Our group hasrecently shown that sufficiently defective graphene on Pt(111) mayin fact improve the catalytic activity for hydrogen evolution.18A model system to investigate is the electroadsorptionof hydrogenin the Angstrom-scale space between the graphene layer and the Pt(111)electrode (denoted G-Pt(111)). On the one hand, the methodology forgrowing graphene over Pt has been optimized,EPt(111)–H). The lateral repulsion andthe Pt(111)–H surface bond energy are compared to the adsorptionof hydrogen on the unmodified Pt(111) electrode and to correspondingdensity functional theory (DFT) calculations. Next, the mechanismof proton permeation through graphene is investigated via in situRaman spectroscopy and impedance spectroscopy. The potential-dependentRaman spectra show no evidence of proton tunneling via graphene hydrogenation.From the impedance and Raman spectra of proton permeation as a functionof the graphene defect density, we conclude that proton permeationoccurs via defects. We will also show that although anions do notbind to the graphene-modified Pt(111) surface, they impact the kineticsof proton permeation, presumably by adsorbing at or near the defectsin the graphene overlayer.This paper aims to investigate the natureof a G-Pt(111)/electrolyteinterface and the fundamental aspects of the electroadsorbed hydrogenin the 2D space. First, by temperature-dependent electrochemical experiments,we evaluate the thermodynamic state functions, lateral interactionenergy, as well as the Pt(111)–H surface bond energy .Several noticeable features can be identified in the CV profile ofG-Pt(111). Compared to the bare Pt(111) electrode, the voltammetricregion attributed to the bisulfate adsorption/desorption (∼0.35to 0.50 V vs reversible hydrogen electrode (RHE)) and the sharp spikesof the anion adlayer order/disorder phase transition (∼0.45V) have disappeared. This is because graphene blocks the interactionof all ions and molecules to the Pt(111), except for hydrogen adsorption.23 From 25 In addition, the onset of hydrogen evolution on G-Pt(111) has shiftedto more negative potentials, close to 0.0 V18 (compared to ∼0.1 V for Pt(111)18). G-Pt(111) reaches the full H-monolayer in two ways. One, by shielding the solvent and the electrolyte, namely,water and ionic species, from the interface by the 3.7 Å gapbetween graphene and Pt(111).15 Second,graphene itself can weaken the Pt–H bond energy because thePt–H bond strength in G/Pt(111) electrode is slightly lowerthan the bond strength of Pt–H under UHV conditions .onolayer 1B before26 making its lattice slightly sparser and, thus, more permeable toprotons. Others have attributed the observed proton currents to atomic-scalelattice defects, including vacancies.27 Raman spectroscopy is sensitive to the hydrogenation of graphene;28 therefore, in situ Raman spectra of grapheneduring proton adsorption can shed light on graphene hydrogenation.In addition, impedance spectroscopy measurements allow us to trackthe rate of electrochemical adsorption of hydrogen onto the Pt(111)surface via permeation through graphene and how it depends on defectdensity.The mechanism of protonpermeation through graphene is still under debate. Geim et al. havesuggested that graphene can be partially hydrogenated during the measurements,2SO4 with thedifferent potentials probed by in situ Raman spectroscopy and EISindicated by different colors. 2SO4 in the 0.10–0.70 V range, respectively. 28 Therefore, graphene hydrogenation does not occurto a significant extent during hydrogen adsorption. As expected, theadmittance spectra in 31 showing thatunder those conditions, hydrogen adsorption/desorption is fast andreversible (at least too fast to be measured by EIS). Therefore, weconclude that the presence of graphene on Pt(111) not only changesthe energetics of hydrogen adsorption (Cdl) in series with the electrolyteresistance, while the adsorption of hydrogen to the Pt electrode canbe represented by the addition of an RC parallel circuit, with Rads being the adsorption/permeation resistanceand Cads the adsorption capacitance. Rads represents the resistance of proton permeationthrough graphene, as the electrosorption reaction itself of hydrogenonto the platinum surface is infinitely fast. Therefore, we use variationsin Rads with experimental conditions asa means to probe the permeation pathway.The cyclic voltammogram 2A indicasorption 1 but alssorption 2D of douRads) is studied as a function of defect density.The defect density is varied via defect generation and “defecthealing” or “defect blocking”. The “defectblocking” is performed by depositing gold in the defect siteby cycling between 0.0 and 0.6 V in the 0.1 M H2SO4 + 5 μM AuHCl4.32 The advantage of using gold to block the defect is that it has nointerfering electrochemical signal in the hydrogen electrosorptionregion. The defect generation is performed by graphene oxidation–reductioncycles between 0.0 and 1.20 V at 50 mV/s in 0.1 M H2SO4, as it is well known that oxidation–reduction cyclesgenerate point defects in the graphene surface.33To confirm the ideathat proton transport through Pt-supportedgraphene is mediated by defects, the permeation resistance  surface.n). It is evident that the resistance graduallydecreases upon cycling. In addition, we performed in situ atomic forcemicroscopy (AFM) analysis (Cdl of G-Pt(111) is much lower thanthat of clean Pt(111), which is also evident from the very low double-layercurrent of G-Pt(111). Finally, we deposited gold on defect-generatedgraphene , asshown in analysis 4C of G-P364 (no anion coadsorption), the hydrogen adsorption/desorptionregion appears between 0.06 and 0.4 V (vs RHE). In the presence ofanions , the voltammetric profiles are significantlydifferent because of the specific coadsorption of anions. The potentialat which the adsorption of each anion starts increases in the order:bromide (∼0.1 V vs RHE),38 chloride (∼0.25 V vs RHE),40 and (bi)sulfate(∼0.35 V vs RHE).4242–, Cl–, Br–) influence the proton permeation resistance. Thisis indirect evidence that the anion still adsorbs near the graphenedefect site and blocks the proton permeation. Interestingly, similarto Pt(111), the potential region in which the adsorption of anionsinfluences the proton permeation increases in the order: bromide (∼0.1V vs RHE), chloride (∼0.25 V vs RHE), and (bi)sulfate (∼0.35V vs RHE).In the case of Pt(111),anions often coadsorb specifically along with hydrogen.4 solutions withdifferent concentrations of added NaBr. 43 the PBE functionalwith DFT D3 dispersion corrections (PBE-D3) by Grimme et al.,44 and the optPBE-vdW functional.45 Allenergies are listed in Tables S1 and S2. The corresponding binding energies for *H as a function of coverageare visualized in To support theexperimental findings with computational evidence, DFT energies werecomputed for Pt(111) with and without a graphene overlayer and withvarious *H coverages, as detailed in the Table S2. For PBE-D3, *H binding is uniformlyweakened across different coverages by 6 ± 2 kJ/mol, while foroptPBE-vdW, there is a weakening of 7 kJ/mol at lower *H coverages,which trails off to ∼2 kJ/mol for *H coverages near 1 ML. Thelatter is within the error margin of PBE. For both PBE-D3 and optPBE-vdW,we observe a H–Pt bond weakening effect due to the presenceof graphene, in line with the experimentally observed weakening in Supporting Information, on the basis of a thorough comparison of PBE andPBE-D3. Besides, for all functionals, the coverage dependence is steeperfor the Pt(111) than for the G-Pt(111), showing the lateral interactionsbetween adsorbed hydrogen atoms are less repulsive in the presenceof a graphene overlayer. This is also in good agreement with experimentalobservations in VRHE, while the predicted onset potential using optPBE-vdW is 0.24 VRHE. Since graphene favorably binds to Pt(111)for PBE-D3 and optPBE-vdW, whereas the latter functional deviatesfrom experimental observations regarding *H adsorption, the PBE-D3functional is used in all subsequent calculations.In Table S3. Calculated diffusion barriersamount to 5 kJ/mol for *H on pristine Pt(111) and to 9 kJ/mol for*H at the interface between graphene and Pt(111). These barriers arenot significant and suggest that once adsorbed, *H can easily coverthe entire Pt(111) surface, even when covered by a graphene layer,in agreement with experimental observations.Subsequently,barriers were calculated for the diffusion of *Hon pristine Pt(111) and G-Pt(111). For this purpose, we assumed that*H jumps between fcc and hcp sites across bridge sites on both pristinePt(111) and graphene-covered Pt(111), the energies of which are listedin 47 with the latter arguing thattunneling is necessary for hydrogen transport.47 However, neither study fully describes H diffusion throughPt(111)-bound graphene,47 and therefore, we verifiedthese calculations for G-Pt(111). The energies of a hydrogen atommoving from vacuum through intact graphene onto Pt(111) are shownin Figure S4. The calculated barrier forthis process exceeds 190 kJ/mol, which means the process is unlikelyto occur under these conditions. Hydrogen permeation through graphenehydrogenation, in which hydrogen reacts to graphene first and is subsequentlytransported into the space between graphene and Pt(111), is not likelyeither, with a formation energy of no less than 123 kJ/mol for graphenefunctionalization on the vacuum interface. This corresponds to thenear-absence of proton transport for defect-free graphene, i.e., forlow numbers of oxidation–reduction cycles, as shown in 2 diffusion through graphene is likely accommodatedby atomic-scale defects.48 For atomic hydrogendiffusion, however, such as the reduction of solvated H+ from the solvent, the interaction of atomic-scale graphene defectswith the Pt(111) surface may affect the effective permeability of,and transport from, these vacancies. The smallest atomic-scale defectsin graphene include monovacancies and divacancies.Previous calculationsperformed by Tsetseris et al. and Mazzucaand Haut showed that atomic hydrogen cannot move classically throughdefect-free graphene,Table S5 and described in the Followingthe idea that graphene vacancies are necessary for hydrogenatom permeation from one side of the graphene layer to the Pt(111)surface, we computed the energies of formation for different hydrogen-passivatedmonovacancies and divacancies, as listed in VRHE, interacts stronglywith Pt(111), while its two C–H bonds occupy the gap left bythe vacancy. Hydrogen adsorption transport through, or hydrogen adsorptionunderneath this gap, is therefore unlikely. Both divacancies at leastpartially expose the underlying Pt(111) surface to the medium; hence,all adsorption sites for *H underneath these vacancies are taken intoaccount. Their binding energies are listed in Table S4, from which onset potentials can be derived for hydrogenationup to the specific number of passivating hydrogen atoms of a far andclose divacancy at 0.83 and 0.99 V, respectively. All onset potentialsare in the range of the oxidation–reduction cycles describedin the The most stable passivated monovacancy, with apassivation onsetpotential of 0.26 48 supports the hypothesis that hydrogen (atomicand molecular) permeates through point defects and corresponds tothe experimental observation that a graphene layer with a great numberof point defects will allow for significant permeation and reactionrates.The minimum thermodynamic barrier for *H transportthrough a fargraphene divacancy is 23 kJ/mol, while the equivalent value for aclose divacancy is 8 kJ/mol. The weak binding energies of *H underthe far graphene divacancy create an effective barrier for *H transport,more than doubling the expected Volmer reaction barrier on an unmodifiedPt(111). On the other hand, the binding energies under the upward-pointingC–H bonds allow for permeation of *H, with a barrier closeto the diffusion barrier on Pt(111). This low-barrier permeation processthrough divacancies, combined with the observations on molecular hydrogenpermeation through atomic-level vacancies by Young et al.,In this paper, we have studied the energeticsand kinetics of hydrogenelectrosorption on Pt(111) covered by a monolayer of graphene. Bothexperiment and theory show that hydrogen binds more weakly to Pt(111)in the presence of graphene. Density functional theory calculationswith various functionals show that this effect is due to Van der Waalsinteractions; presumably, the presence of hydrogen weakens the bindingof the graphene to Pt(111). In addition, the lateral interactionsbetween adsorbed H on Pt(111) become less repulsive in the presenceof graphene, as confirmed by both experiments and DFT calculations.Experiments with isolated defects generated by oxidation–reductioncycling and domain boundaries covered by gold clusters show that domainboundaries and defects are the sites where hydrogen permeates thegraphene layer. The rate constant for hydrogen adsorption followsdirectly the defect density, as confirmed by impedance spectroscopymeasurements. Although graphene blocks the interaction of anions withthe Pt(111) surfaces, anions do adsorb near the defects: the rateconstant for hydrogen permeation is sensitively dependent on anionidentity and concentration, with the more strongly adsorbing anion(bromide) having the largest effect. DFT calculations confirm thatintact graphene has a prohibitively high barrier for hydrogen permeation,that defects allow for a significantly lower barrier, and hydrogencan diffuse on the Pt(111) surface with low barriers, even in thepresence of graphene. The improved understanding of the effect ofgraphene overlayer of Pt, as obtained in this paper, will hopefullyimprove the design of tailor-made graphene-modified electrodes forspecific electrochemical applications.17 Theelectrochemical experiments were conducted in a Pyrex, two-compartmentelectrochemical cell. A platinum mesh was used as a counter electrode(CE) , and a reversible hydrogen electrode(RHE) was used as a reference electrode (RE). The glassware was precleanedaccording to a well-established procedure.51 The electrolytesolution was prepared from high-purity chemical (Merck-ultrapur grade)and ultrahigh-purity (UHP) water . All electrochemical experiments were conductedusing a Bio-Logic SP-300 potentiostat using proprietary software.Impedance spectra were measured with frequencies ranging from 10 kHzto 0.1 Hz and a peak-to-peak amplitude of 5 mV. The data were fittedto the equivalent electric circuit (EEC).31The experimentalwork was conducted using monocrystalline Pt(111) disc working electrodes(WE), and the graphene overlayer on Pt(111) was prepared using thechemical vapor deposition technique.53 Before assembly, the cell components werecleaned by sonication in high-purity ethanol and Millipore Milli-Qwater (resistivity 18.2 MΩ cm), respectively, and then blow-driedin Ar (g). Before each experiment, the counter electrode Pt foil  was flame-annealed and quenched with Milli-Q water beforeassembling into the in situ cell. An Ag/AgCl (3 M KCl) electrode (WPI)was used as the reference electrode, and the counter electrode wasa Pt wire. A potentiostat (μAutolab type III) was coupled withthe AFM/Raman spectroscopy to control the electrochemical conditionsduring the experiments.The in situ AFM andRaman experiments were carried out in an electrochemical cell madeof PEEK.53 The AFM (JPK Instruments) scan rate was 1 Hz, and all of the imageswere obtained using the tapping mode to minimize the damage to theelectrode. The tips used were purchased from Bruker . Images were taken eitherat 0.5 V after potential cycling or during cycling simultaneouslywith cyclic voltammetry (CV). The electrolyte was prepared from H2SO4 , which was neither thoroughlydegassed nor refreshed during the experiment. The immersion Ramanspectra were collected using a WITEC α 300 R-Confocal RamanImaging using immersion with a laser wavelength of 532 nm. The electrochemicalcell design for immersion Raman spectroscopy is based on the laboratorysetup described elsewhere.55 To minimize the potentialdamage from the laser heating effect, the laser power was controlledunder 1.1 mW. All measurements were performed under ambient conditionsat room temperature.The details of in situ AFM instrumentationand operation have been explained elsewhere.–6 mbar),and the images are collected at a beam setting of 10 kV and 0.40 nAusing an Everhart–Thornley detector.Graphene morphology was analyzed usingscanning electron microscopy (SEM)  andatomic force microscopy (AFM) (JPK Nanowizard 4). The SEM is operatedin high vacuum condition (<1 × 1056 and using the projectoraugmented-wave method.57 The fcc Pt(111)surface slabs were modeled usingfour layers of (3 × 3) Pt atoms. For calculating the net bindingenergy on pristine Pt(111), various (0–9 atom) coverages of*H in all possible symmetry-independent on-surface adsorption configurationswere added onto the top layer. Similarly, various 0, 1, 2, 7, 8, and9 *H atom coverages were placed on top of the Pt(111) slab and coveredby a commensurate 2√3 × 2√3 R30°graphene overlayer, as described in Section S.1 in the Supporting Information. All systems were relaxed to a maximumatomic force of 0.02 eV/Å, with a 450 eV plane-wave cutoff anda 6 × 6 × 1 γ-centered Monkhorst-Pack k-point grid.59 The free energies of adsorptionof *H were calculated with the computational hydrogen electrode modelusing the individual DFT energies and configurational entropies ofeach individual configuration58 and vibrationalcorrections, as described in the Supporting Information (Section S.1.2). Effect of solvation was not includedin the calculations.The DFT calculations were carriedout in VASP 5.4.4Barriers for *H diffusion were assessedby calculating the freeenergy profile between the lowest and second-lowest energy adsorptionsites. We also computed the energetics of proton permeation underneathpassivated graphene defects. First, either one carbon atom is removedfrom the graphene layer forming a monovacancy, or two atoms alongthe long or short edges of a graphene hexagon. Subsequently, the now-availablecarbon atoms adjacent to the vacancy are passivated with hydrogenatoms in various stoichiometries and configurations and relaxed. Finally,we added single hydrogen atoms in all unique adsorption sites underthe vacancies and obtained the resulting energies, through which thepermeation pathways and energetics can be determined.