We find that Φ scales linearly with Raman G-peak wavenumber shift (slope = 22.2 mV/cm−1) for all layers and twist angles, which is consistent with doping-dependent changes to graphene’s Fermi energy in the ‘high’ doping limit. Our results here emphasize that layer orientation is equally important as layer thickness when designing multilayer two-dimensional systems where surface potential is considered.By combining optical imaging, Raman spectroscopy, kelvin probe force microscopy (KFPM), and photoemission electron microscopy (PEEM), we show that graphene’s layer orientation, as well as layer thickness, measurably changes the surface potential (Φ). Detailed mapping of variable-thickness, rotationally-faulted graphene films allows us to correlate Φ with specific morphological features. Using KPFM and PEEM we measure ΔΦ up to 39 mV for layers with different twist angles, while ΔΦ ranges from 36–129 mV for different layer thicknesses. The surface potential between different twist angles or layer thicknesses is measured at the KPFM instrument resolution of ≤ 200 nm. The PEEM measured work function of 4.4 eV for graphene is consistent with doping levels on the order of 10 As the field of two-dimensional (2D) crystals expands to include stacking layered materials, the relative orientation between layers becomes another important variable. In the simplest case, stacking two graphene layers to form twisted bilayer graphene (TBG) already leads to measureable differences in interlayer screening4, optical absorption6, chiral charge carriers7, and chemical reactivity8.Vetting graphene as a candidate for advanced electronics requires examination of both intrinsic and extrinsic influences on its material properties, as well as a nuanced characterization of how graphene responds in different heterogeneous configurations. It is now well documented that graphene’s atomically thin carbon backbone makes it susceptible to influences from its supporting substrate and to any over-layers or adsorbates on its surface10, a feature unique to atomically-thin systems. Increasing θ greater than ~20°, the layers are effectively decoupled and the electronic properties are indistinguishable from those in single-layer graphene11. Notably, graphene’s small density of states and close interlayer spacing leads to incomplete charge screening, which can sustain a charge imbalance (Δn) between TBG layers with a measured interlayer capacitance around 7 μF/cm2 12.As compared to AB-stacked Bernal bilayer graphene, the interlayer electronic coupling in TBG rapidly diminishes as the twist angle (θ) increases above only a few degrees. Once a twist is introduced, a moiré pattern forms from the overlapping lattices. Intriguingly, this moiré structure can itself induce a periodic potential that influences the electronic structureN)15, doping (n)17, and carrier type18 have been considered. The combination of extrinsic doping from graphene’s support substrate  paired with interlayer screening helps explain measured differences in Φ with N. Density functional calculations15 and experiments16 show that single layer and bilayer graphene’s work function are tied to its Fermi level (EF) shift with respect to the Dirac point, while interlayer screening only becomes relevant when more than two layers are present. Since the difference in work function between graphene and, for example, a KPFM tip defines the contact potential ), ΔΦ is also directly influenced by changes in EF (or n). More broadly, the connection between n and Φ has important implications for a variety of systems, from designing low contact barrier electrodes19 to changing surface wettability20. For example, by varying EF by 300 meV, graphene’s surface energy varies enough to change the water contact angle by as much as 13°20.To date, variations in graphene’s surface potential (Φ) versus layer thickness /Si substrates. We choose graphene formed on the ‘outside’ surface of the Cu-foil enclosures for analysis since multi-layer islands consistently form there23. The resulting graphene films range in thickness from 1-layer (1LG) to 6LG and have a random assortment of stacking sequences, with domain sizes on the order of tens of microns. We note that each additional graphene layer grows beneath the continuous first layer24, forming an inverse ‘step pyramid’ type structure, which is preserved during the transfer process.Graphene films were grown by chemical vapor deposition (CVD) on copper foil ‘enclosures’26 and optical imaging6, we map out layer thickness  and twist angle domains in the multilayer CVD graphene films  that correspond to TBG twist angles of θblue ≈ 11°, θred ≈ 13°, θyellow ≈ 15°6. Second, Raman mapping shows variations in the G peak enhancement, as well as the 2D peak full width at half maximum (FWHM), which differentiates between Bernal-stacked (θ = 0°) and turbostratic bilayers (θ > 0°)27. Figure −1, we have a good approximation of the location of the smallest twist angles and Bernal regions , a ‘large’ angle domain (θL > 16°), and a ‘small’ angle domain (θs ≈ 0°). Finally, Fig. 2O and O2, as well as the underlying SiO2 substrate, to hole dope graphene1, we assume these films are p-type doped.Using a combination of Raman spectroscopylms Fig. . In partons Fig. 12,27. Fi28 technique called PeakForce-KPFM . Rather than measuring surface topography and surface potential (Φ) in a one-pass technique, we used a two-pass technique. In the first pass, the surface topography, stiffness, and adhesion are measured in a non-resonant peak-force tapping approach. In the second pass, the surface potential is measured. Unlike conventional FM-KPFM measurements, the tip flies at a fixed user-defined distance above the sample surface (50 nm here), which determines the spatial resolution . By not having the tip touch the surface while measuring the surface potential, one avoids mechanical cross-talk caused by tip-sample interactions that shift the cantilever resonance behavior and affect the sideband detection used in FM-KPFM.From these films, we conduct ambient surface potential measurements using a variation of the Frequency-modulated Kelvin Probe Force Microscopy (FM-KPFM)e.g. ‘3θs’ = 3LG with a small twist angle (θ ≈ 0°); ‘2θ13’ = 2LG with θ = 13°; ‘2θL’ = 2LG with large twist angle (θ > 16°)). The image signal-to-noise ratio is sufficiently large that we can use either pixel histograms  or θs ~ 0° (black squares). For example, the relative potential difference between 1LG and 2LG (written as ΔΦ1−2) for θL is 91 mV, whereas ΔΦ1−2 for θs is 129 mV. Notably, other works have shown measured values for epitaxial or exfoliated graphenes at ΔΦ1–2 = 135 mV13, 120 mV16, 110 mV28, or 66 mV15, though the layer orientations were not measured in these reports. For comparison, in Fig. 15 of ΔΦ for Bernal stacked graphene layers (θ = 0°). We note that Φ is sensitive to both carrier concentration and band structure (discussed below). To further visualize the correlation between Φ and n, in Fig. N-2) for θL domains versus the relative difference for the G-peak position (ΔΓG) as referenced relative to TBG. This comparison reveals a qualitative relationship between the variables ΔΦ and ΔΓG.The relative surface potential difference (ΔΦ) between sequentially increasing layer number [N − (N + 1)] is shown in Fig. G), as seen in Fig. G are a result of electron-phonon coupling and changes in bond stiffness29. When the Fermi level is at the Dirac point (ED), the G-peak position is close to 1580 cm−2 and increases symmetrically for hole or electron doping29. In our sample geometry, the top most graphene layer is a continuous single-layer film and on the length scales considered here, uniformly exposed to ambient dopants . The additional buried layers are protected from the ambient and are instead directly influenced by the nominally spatially homogeneous  trapped charges in the underlying SiO2. Thus, lateral differences in n across the film should directly correlate to how multilayer graphene regions with θL or θs screen charges from their ‘top’ and ‘bottom’ surfaces.Variations in graphene’s Fermi energy, or charge carrier density, induce shifts in the Raman G peak position . For all layers measured here, we find large twist angle domains (θL > 16°) have higher doping concentrations compared to small twist angle domains  for single-layer graphene at ‘high’ carrier densities (n>~ ± 0.5 × 1012 cm−2) the G-peak energy increases linearly with EF (or n)30 and (ii) θL multilayers behave as an ensemble of independent single-layer graphene despite their N > 1 thicknesses. Notably, our Raman measurements probe all layers here and provide an average doping level for the multilayer stack. Given the linear change in G-peak position with increasing N and the fact that θL multilayers behave essentially as independent graphene layers, we surmise that the carrier concentration per unit area is distributed over the multilayer stack. A linear regression fit for θL data in Fig. m = −2.4 cm−1/layer. The increased interlayer coupling/screening for θs multilayers results in a lower average doping level across all N and is most likely a result from screening that is nonlinear to the field amplitude32, a result of the different band structures between θL and θs multilayers.From the Raman data shown in Fig. ins Fig. . This coEF, n and Φ. Using electrostatic gating to control n between approximately 1.5 × 1012cm−2 to −2.5 × 1012cm−2, Yu et al.16. Showed their graphene work function data could be fit using the relationship 15. To visualize how Φ varies with the morphological features of our films, in Fig. 15. From this plot several features are apparent: (i) the surface potential drop (ΔΦ) between layers with sequentially increasing N monotonically decreases; (ii) the rate of decrease for ΔΦ is larger for θs compared to θL; and (iii) the trends for both θs and θL are approximately linear, whereas DFT calculations shown a large initial drop followed by a slowly decreasing potential. We note that ΔΦ1–2 for both our measurements and DFT calculations are similar (within 20 mV), which is reasonable since both systems have approximately the same initial doping concentration (~5 × 1012cm−2).To connect our spatially varying doping concentration with PF-KPFM measurements, we briefly review the relationship between EF as described above16. In our experiments we cannot extrinsically tune n, but we do have a range of n due to the relatively homogeneous doping from ambient and substrate with varying N and θ. In addition, these samples are in the ‘high-doping’ limit where Φ trends approximately linearly for both single and multilayers. This linear correlation can been seen in Fig. L layers as compared to TBG (ΔΦN-2), as well as relative Raman G peak positions, ΔΓG (a function of n), between TBG versus layer number. On a linear scale, both ΔΦ and ΔΓG have a monotonically decreasing trend with similar shape, which qualitatively suggests a proportionality constant between them. This scaling is notable since the PF-KPFM measurements are uniquely sensitive to surface variations as compared to Raman spectroscopy, which equally probes all layers in the film.For intrinsic graphene (no doping) there is no difference in Φ between 1LG and 2LG, while at low finite doping Φ varies with G between all measured configurations of N and θ domains in our samples. The table in Fig. N and θ domains from a given PF-KPFM image. Plotting this data in Fig. EF is approximately linear with ΓG.To further assess the relationship between doping and surface potential, in Fig. −1. Using the proportionality constants between different variables  for single-layer graphene, we can approximate the doping levels required to change the surface potential in our films. For 1LG in the high-doping limit, the proportionality between ΓG versus EF equals −0.04 cm−1/meV 29, resulting in n = 1 × 1012 cm−2 carriers for EF−ED = 40.3 meV30. Taken together with our data, we approximate the relation between ΔΦ versus n at 35.8 mV per 1 × 1012 cm−2 carriers. Importantly, this comparison reveals that ΔΦ between different twist angles can have the same magnitude as that for ΔΦ between different layer thicknesses, which appears to be driven by how a specific morphological feature (such as N or θ) screens charge.Given our films are in the high doping limit, we apply a linear fit to all data in Fig. To independently confirm the surface potential variation as a function of graphene morphology, we conducted spectroscopic Photoemission Electron Microscopy (PEEM) analysis of multilayer graphene films. Figure 1–2 ≈ 80 meV and ΔΦ2–3 ≈ 70 meV, which agrees with the surface potential difference determined for θL using PF-KPFM  vary significantly from 4.2 eV33 to 5.1 eV34, with a commonly accepted range of 4.5–4.6 eV35. Given this relatively wide scatter of reported work function values, the value of 4.4 eV for 1LG measured here via photoemission is within a reasonable range for a carrier concentration of 1012cm−2 (estimated from ΓG).Since the work function of thin graphite films is mainly determined by variation of the Fermi energy with respect to the Dirac point energy as a function of doping−2) between the surface potential and G-peak Raman shift for regions of different thickness (N) and twist angle (θ). Using this correlation, we estimate the proportionality between graphene’s surface potential and doping concentration at 35.8 mV per 1 × 1012 cm−2 carriers. Furthermore, we find that the rate at which the surface potential decreases for increasing layer number is larger for ‘small’ twist angles (θs ≈ 0°) as compared to ‘large’ twist angles (θL > 16°), which is consistent with the stronger interlayer interaction for small twist angle samples. Finally, using PEEM we independently confirm the surface potential differences for different morphological features (N and θ) in multilayer CVD graphene. Together, these results reinforce the notion that layer orientation, or twist angle, is another critical variable to account for when designing 2D multilayer systems.In conclusion, we quantitatively assess the surface potential of twisted graphene layers as measured by PeakForce Kelvin Probe Force Microscopy (PF-KPFM) and Photoemission Electron Microscopy (PEEM). By combining optical microscopy, Raman spectroscopy and PF-KFPM measurements of the same graphene regions, we find a linear correlation  focused the laser (spot ≈0.4 μm) onto the sample and gathered Raman scattered light for detection. The Raman scattered photons were dispersed in a half-meter Acton Sp-2500 spectrometer and were detected using a Princeton Instruments CCD array . Optical images were acquired using a microscope with a Nikon DS-Ri2 high-definition color camera (16.25 megapixel).For multilayer graphene >2 L, we can say with confidence which regions have all layers with relative twist angles θ > 16° or θ = 0°. The label “θ > 16°” (or “θ = 0°”) here means that directly neighboring layers in the ML stack have twist angles at least >16° (or θ = 0°). We make these assignments using optical inspection (graphene contrast is quantized per layer) and raman analysis of the G and 2D peaks. The raman spectra and optical micrographs will be a convolution of the couplings between every layer in the ML stack. The stronger interlayer coupling for low twist angles (θ < 5°) readily shows up as broadening in the Raman 2D peak FWHM, while the optically resonant domains readily show up in the optical micrographs. As such, we can discern between ‘rotationally pure’ regions with the bounds of θ = 0°  or θ > 16° . Since we are analyzing a maximum of 5-layers or less in this work, convoluted mixtures of twist angles can be identified. In Fig. TM microscope using an Icon scan head. Measurements were taken in air while enclosed in the systems’ quiet box. While the KPFM data presented here was acquired from different regions of the same sample to reduce variability, we have confirmed that different graphene growths produce comparable results for ΔΦ between different twist angles and layer thicknesses.AFM measurements were performed on a Bruker Dimension Fastscan with ScanAsystQ of the cantilever’s resonance and the spring constant (k) of the cantilever can be separately chosen to optimize the surface potential measurement. TappingMode requires the cantilever to have a sufficiently high k to overcome capillary forces from water layers that are often present on sample surfaces. It also requires the Q to be not so large as to limit TappingMode bandwidth. PeakForce Tapping removes these limitations, allowing the use of cantilevers with a much smaller spring constant and larger Q, enabling room for probe optimization. The PFQNE-AU probes used in this work are twice as sensitive as the commonly used SCM-PIT probes. Probes with higher Q/k ratio can be designed to further improve PeakForce KPFM sensitivity36.KPFM Sensitivity- Because the tapping during the topography measurement pass is not done at the mechanical resonance frequency of the tip, the 36, “for FM-KPFM, when the tip is lifted 5 nm above the surface, half of the signal is gathered from up to 15 nm above the tip end, corresponding to a diameter of 12 nm. This suggests a possible resolution of 10 nm may be achieved with FM-KPFM. The contact potential difference (CPD) information collected is local to the area right underneath the tip affording credible accuracy. Lifting the tip higher to 50 nm above the surface [as used in this work], the spatial resolution decays to around 200 nm, which demonstrates the sharp dependence of spatial resolution on probe-sample distance.”Spatial resolution- As outlined in the instrument Application Notes37). The photoemission yield measurement itself did not yield sufficient statistics to bear a work function map of the same area due to the low photoemission intensity. We note that the sample showed no sign of charging because of the continuous coverage of graphene films across the sample38. In addition, the use of a deep ultraviolet light for PEEM measurement helped mitigate sample charging as demonstrated in PEEM of transition metal dichalcogenide semiconductors on SiO239.Photoemission spectra were acquired using a photon energy of 6.53 eV. A work function map with a relative energy scale was created by fitting the secondary electron cutoff of the photoemission spectra pixel-by-pixel for the entire imaged area. The relative energy scale was calibrated using the work function of 1LG, determined from photoemission yield measurements acquired by recording the photoemission intensity as a function of photon energy  and valence band edges in PES. The energy scale of Evac smearing due to residues, and hence the smearing of the relative work function, is on the order of 100 s of meV (~350 meV). By comparing optical microscopy images with PEEM images and performing spectroscopic PEEM measurements of the graphene samples studied here, we avoided areas with non-uniformities in optical or PEEM intensities. As a result, work function variations in graphene were resolved with PEEM on an energy scale (10s meV), similar to what was observed with as-grown MoS237. Graphene work function values (4.4 eV for 1 L graphene) measured here with PEEM are consistent with several prior works35.Surface contaminants, such as PMMA residues, typically show up as non-uniformities in the photoemission intensity and coincide with a smearing of the vacuum level (


Programmed death ligand-1 (PD-L1) is a critical regulator of T cell function contributing to peripheral immune tolerance. Although it has been shown that posttranscriptional regulatory mechanisms control PD-L1 expression in cancer, it remains unknown whether such regulatory loops operate also in non-transformed cells. Here we studied PD-L1 expression in human dermal lymphatic endothelial cells (HDLECs), which play key roles in immunity and cancer. Treatment of HDLECs with the pro-inflammatory cytokines IFN-γ and TNF-α synergistically up-regulated PD-L1 expression. IFN-γ and TNF-α also affected expression of several microRNAs (miRNAs) that have the potential to suppress PD-L1 expression. The most highly up-regulated miRNA following IFN-γ and TNF-α treatment in HDLECs was miR-155, which has a central role in the immune system and cancer. Induction of miR-155 was driven by TNF-α, the effect of which was significantly enhanced by IFN-γ. The PD-L1 3′-UTR contains two functional miR-155-binding sites. Endogenous miR-155 controlled the kinetics and maximal levels of PD-L1 induction upon IFN-γ and TNF-α treatments. We obtained similar findings in dermal fibroblasts, demonstrating that the IFN-γ/TNF-α/miR-155/PD-L1 pathway is not restricted to HDLECs. These results reveal miR-155 as a critical component of an inflammation-induced regulatory loop controlling PD-L1 expression in primary cells. HowevT cells ––11. Of n cells ––. These v cells ––. This is cells ––. miRNAs  cells ––. Studies cells –––18. In pcells ––––21. HoweHere we show that PD-L1 is expressed in primary human dermal LECs (HDLECs) and IFN-γ and TNF-α act synergistically to induce PD-L1 expression in these cells. Using this cellular model of inducible PD-L1 expression we distinguish a number of potential PD-L1-targeting miRNAs. We identify differentially regulated miRNAs upon IFN-γ and TNF-α stimulation of HDLECs and show that miR-155 is the most highly up-regulated miRNA. Furthermore, we show that there are two functional miR-155-binding sites on the 3′-UTR of PD-L1. Mutation of both of these binding sites results in de-repression of a reporter under control of the PD-L1 3′-UTR. Consistent with these findings, miR-155 overexpression or inhibition results in suppression or enhancement of PD-L1 protein expression, respectively. Similar effects can also be observed in primary human dermal fibroblasts (HDFs), indicating that the IFN-γ/TNF-α/miR-155/PD-L1 regulatory loop is not restricted to HDLECs. These results suggest that during physiological immune activation of HDLECs, IFN-γ and TNF-α synergize to induce PD-L1 expression and concurrently activate miRNA networks that suppress PD-L1 expression, presumably to avoid prolonged immune suppression. Overall, our study reveals how the HDLEC small RNA landscape responds to inflammation and provides new insight into posttranscriptional regulation of PD-L1 in human primary cells.A and B). IFN-γ is capable of activating both signal transducer and activator of transcription 1 and 3 (STAT1/3). Both STAT1 and STAT3 have been shown to contribute toward increased PD-L1 expression . PD-L1 is predicted to have up to four N-linked glycosylation sites. De-glycosylation treatment led to total disappearance of both bands and a new band appearing at 33 kDa, which is the expected molecular mass of unmodified PD-L1 . Consistently with induction of the JAK/STAT pathway we showed that PD-L1 mRNA levels were up-regulated in activated HDLECs. IFN-γ treatment resulted in a 10-fold induction of PD-L1 mRNA levels at 24 h post-treatment (C). The effect was significantly elevated by concurrent addition of TNF-α, although addition of TNF-α alone did not significantly affect PD-L1 mRNA levels, demonstrating that the effect of stimulating with both cytokines was synergistic. Similarly, increasing the concentration of IFN-γ stimulation led to up-regulation of PD-L1 mRNA, which was further augmented in combination with TNF-α . Expression of interleukin-1β (IL-1β) mRNA, a downstream target of TNF-α signaling through the NF-κB pathway, was up-regulated in a similar synergistic manner between IFN-γ and TNF-α . PD-L1 mRNA was measured at 8 h where it was strongly induced and remained at the same level at 24 h, consistent with the cumulative increase in PD-L1 protein levels . Although TNF-α stimulation alone induced a minor increase in PD-L1 mRNA levels, protein expression of PD-L1 did not change compared with untreated levels (D). However, addition of TNF-α to IFN-γ-treated cells enhanced surface PD-L1 expression (E), whereas having minimal effects on total PD-L1 protein levels in comparison to treatment with IFN-γ alone (D). This indicated that, in IFN-γ-treated HDLECs, TNF-α can affect PD-L1 localization and mRNA levels (C). The effects of IFN-γ and TNF-α on PD-L1 expression were also determined by immunofluorescence. PD-L1 was localized at the cell membrane and throughout the cytoplasm and its levels increased following stimulation with the cytokines (F). Taken together, these data indicated that, as in the case of macrovascular endothelial cells, PD-L1 is inducible at the transcriptional level in HDLECs responding to inflammatory stimuli.Human macrovascular endothelial cells become activated by pro-inflammatory cytokines IFN-γ and TNF-α and display increased PD-L1 expression , 22. Howpression , 24. In reatment C. The efd levels D. Howevepression E, wherea-γ alone D. This iA levels C. The efytokines F. Taken A). More specifically, 48 miRNAs were identified to be differentially regulated by IFN-γ and TNF-α (adjusted p < 0.1) (B). Levels of up-regulated and down-regulated miRNAs were further assessed by qRT-PCR (C). We found that IFN-γ and TNF-α resulted in up-regulation of miR-155–5p, miR-4485–3p, miR-218–5p, and miR-146a–5p and down-regulation of miR-582–5p, miR-582–3p, miR-93–5p, miR-217 and miR-125b–5p . Gene ontology analysis using the miRNA enrichment analysis and annotation tool .Having shown that PD-L1 is inducible in HDLECs responding to inflammatory stimuli, we reasoned that this was an appropriate cellular model for identifying posttranscriptional PD-L1 regulators during inflammatory responses of primary human cells. To this aim and as the small RNA transcriptome of IFN-γ- and TNF-α-treated HDLECs had not been determined, we analyzed small non-coding RNAs in HDLECs stimulated with or without IFN-γ and TNF-α for 24 h. Collected RNA were enriched for small RNAs and analyzed on an Illumina MiSeq. Sequencing detected small nuclear RNAs (snRNAs), small nucleolar RNAs (snoRNAs), and miRNAs A. More sp < 0.1) B. Levels qRT-PCR C. We fouA). 49 detected miRNAs in basal or inflamed LECs also had predicted binding sites for PD-L1. Among these miRNAs, miR-155–5p (referred to as miR-155) was highly abundant and strongly induced by IFN-γ and TNF-α . As other highly induced miRNAs were lowly expressed we focused on miR-155 as a potential posttranscriptional regulator of PD-L1 expression in inflamed LECs. We dissected how miR-155 responded to IFN-γ and TNF-α and found that TNF-α was the primary inducer . Although IFN-γ alone did not affect miR-155 levels in HDLECs, it significantly enhanced the effect of TNF-α on miR-155 expression. Stimulating cells with increasing concentrations of IFN-γ in conjunction with TNF-α further increased miR-155 expression . Up-regulation of miR-155 by IFN-γ and TNF-α was observed at 8 h and continued to rise, remaining at high levels after 48 h .We compared detected miRNAs from small RNA sequencing with miRNAs predicted to target the 3′-UTR of PD-L1 using TargetScan software  Fig. 3AAFig. 3A.A) that are conserved in human and mice. To determine direct regulation of PD-L1 by miR-155, luciferase reporter assays were performed with mutagenesis of miR-155-binding sites. Wild-type, single, or double mutated miR-155-binding sites were co-transfected with miR-155 mimics in HeLa cells (B). Mutating the first miR-155-binding site (Site 1) in PD-L1 3′-UTR led to a significant increase in luciferase reporter activity compared with wild-type 3′-UTR, and the effect was more profound after mutating both miR-155-binding sites (B). Constructs containing the PU.1 3′-UTR, a previously validated miR-155 target . Overexpression of miR-155 resulted in significant down-regulation of 24 h IFN-γ- and TNF-α-induced PD-L1 expression (C and D). STAT1 expression and phosphorylation of STAT1 were significantly increased . PD-L1 mRNA levels were consistently increased from overexpression of miR-155 (E).We found two potential miR-155-binding sites on the 3′-UTR of PD-L1 A that arLa cells B. Mutating sites B. Constr5 target , were uspression , C and D miR-155 E.A and B). Suppressor of cytokine signaling 1 (SOCS1), a published target of miR-155 (A), although there was no change upon overexpression of miR-155 (C). Expression of STAT1 was increased in IFN-γ- and TNF-α-stimulated cells and decreased in untreated cells but resulted overall in no change in phosphorylation of STAT1 relative to total STAT1 . There was no change in the fold-induction of PD-L1 mRNA after IFN-γ and TNF-α stimulation, compared with control . To determine the effect of miR-155 on PD-L1 expression over time, we introduced an earlier (8 h) and later (48 h) time point for IFN-γ and TNF-α stimulation . Expression of PD-L1 at all three time points was increased following inhibition of miR-155 compared with control. This demonstrated that lack of miR-155 could affect the onset and maximum levels of PD-L1 expression upon IFN-γ and TNF-α treatments. Inhibition of miR-155 also resulted in the increased expression of SOCS1 and STAT1 that were consistently reproducible at the 24-h time point, and also of STAT3. To determine whether miR-155 targeting of PD-L1 could occur in a different cell type, we tested our model in primary HDFs. PD-L1 was undetectable at basal levels in HDFs (A and B). However, we found PD-L1 to be inducible, along with IL-1β and miR-155 in similar synergistic activation following IFN-γ and TNF-α stimulation . In treated HDFs, miR-155 was up-regulated within 8 h of stimulation, reaching its peak levels by 24 h (D). Overexpression of miR-155 resulted in PD-L1 down-regulation in activated HDFs (E) without a statistically significant effect on PD-L1 mRNA (F). Conversely, inhibition of miR-155 led to an increase of PD-L1 expression (G). miR-155 inhibition did not result in a statistically significant effect on PD-L1 mRNA under these conditions (H). These results indicate that miR-155-mediated suppression of PD-L1 is not specific to HDLECs and could be observed in other dermal primary cells responding to inflammatory stimuli.Next, we tested whether endogenous miR-155 could suppress PD-L1 expression. Inhibition of miR-155 resulted in significant up-regulation of IFN-γ and TNF-α-induced PD-L1 expression , A and B miR-155 , 29 was  miR-155 A, althou miR-155 C. Expres in HDFs , A and B by 24 h D. Overexted HDFs E without-L1 mRNA F. Converpression G. miR-15nditions H. These We reveal that in addition to promoting PD-L1 expression TNF-α and IFN-γ concurrently lead to induction of PD-L1-targeting miRNAs during a physiological immune response . We iden19–e.g. components of the JAK/STAT pathway) or by miR-155 primarily blocking PD-L1 translation rather than causing PD-L1 mRNA degradation. miR-155 is involved in development and function of T, B, and myeloid cells  supplemented with vascular endothelial growth factor C (VEGF-C) (R&D Systems) . All expm), hsa-miR-155–5p hairpin inhibitor (50–100 nm) (GE Dharmacon) based on the mature hsa-miR-155–5p sequence (5′-UUAAUGCUAAUCGUGAUAGGGGU-3′) or siRNAs targeting PD-L1  using TransIT-siQuest transfection reagent (Mirus Bio). All experiments utilized respective negative controls (GE Dharmacon). 48 h posttransfection, cells were stimulated with IFN-γ and TNF-α for 24 h and harvested for experimental analysis.Cells were seeded in 6-well plates 1 day before transfection with miRIDIAN hsa-miR-155–5p mimic (25 nm: PD-L1 (F), 5′-CATCTTATTATGCCTTGGTGTAGCA-3′ and (R) 5′-GGATTACGTCTCCTCCAAATGTG-3′; IL-1β (F), 5′-AGGATGAC-TTGTTCTTTGAAGCTGA-3′ and (R), 5′-TGCCTGAAGCCCTTGCTG-3′; β-actin (F), 5′-CACCATTGGCAATGAGCGGTTC-3′ and (R), 5′-AGGTCTTTGCGGATGTCCACGT-3′. Commercially available primers (Applied Biosystems) were used to assess mature miRNA levels and the loading control U6 snRNA. Relative gene expression was calculated by the comparative TC method.Total RNA was isolated using the miRNeasy Kit (Qiagen). PD-L1 and IL-1β mRNA expression were quantified by qRT-PCR using SYBR Green Master Mix (Applied Biosystems). β-Actin was monitored as a housekeeping reference gene. The following primers were used at a final concentration of 300 nn) and any reads with >20% Ns (−max-n 0.2). Reads were quality trimmed with Sickle (version 1.330), with a cutoff of >Q20 (−q 20), and truncating at the position of the first N (−n). Reads were mapped with Bowtie (version 1.0.1) with a seed length of 15 (−l 15), a maximum total quality score at mismatched positions of 99999 (−e 99999), reporting all valid alignments per read or read pair (−a), and the best option to pick the best reported alignments. Reads were mapped separately for merged reads and a concatenated file of unmerged forward and reverse reads. Reads were counted using Subread featureCounts (version 1.5.0-p1), with a minimum fragment length of 5 (−d 5). Reads were counted against all features in the HsGRCh38 GFF file as well as against features from mirBASE release 21. Counts for the mapped merged reads were doubled and then added to the counts for the mapped unmerged reads. Duplicate features, i.e. those with identical numbers of mapped reads across all samples and identical lengths, were removed. RPKMs (reads per kilobase transcript per million mapped reads) were calculated and then log2-transformed and 75th percentile shifted. Reads mapping to protein coding or pseudogenes were presumed to correspond to degraded RNA and were excluded from descriptive analyses of data (A). For each feature across all of the samples the baseline was set to the median value . A two-tailed t test and FDR p value correction were used to assess statistical significance.RNA were isolated and enriched for small RNA using the PureLink miRNA isolation kit (Ambion). RNA integrity was assessed using the Agilent 2100 Bioanalyzer (Agilent Technologies). Sequencing libraries were generated using NEBNext Multiplex Small RNA Library Prep Set for Illumina (Set 1) (New England Biolabs) according to the manufacturer's instructions. Samples were sequenced using Illumina MiSeq . Sequencing reads were examined for quality and mapped against all annotated human mature and precursor miRNA sequences (miRBase version 21.0). Residual adapter sequences and indexes were removed with Cutadapt (version 1.8.3), in the paired-end mode, first trimming any low-quality ends with a cutoff of Q10 (−q 10), then removing flanking Ns  containing protease mixture inhibitors P8340, P5726, and P0044 (Sigma). Protein concentration was determined by bicinchoninic acid assay (BCA) (Thermo Scientific) according to the manufacturer's protocol, using BSA as standards. Protein samples were denatured and resolved on SDS-PAGE gels using a Bio-Rad PowerPac HC and transferred onto PVDF membranes (Millipore). Membranes were probed overnight at 4 °C (1:1000) for the following primary antibodies to PD-L1 (E1L3N), SOCS1 (A156), STAT1 (9172), P-STAT1 Tyr-701 (D4A7), STAT3 (9132), and P-STAT3 Tyr-705 (D3A7) all from Cell Signaling, and for 1 h at room temperature for GAPDH (6C5) and β-actin (ab6276), both from Abcam. Membranes were further incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies and visualized with ECL . Band intensity was quantified using ImageJ version 1.50e .Cells were lysed with ice-cold radioimmunoprecipitation assay (RIPA) buffer (5 mN-glycosidase F (PNGase F) was acquired from New England Biolabs (P0704). PNGase F was added to denatured protein lysates according to the manufacturer's protocol and subsequently analyzed by Western blot.Peptide:m) and PD-L1 or PU.1 3′-UTR constructs for 48 h using JetPrime reagent. Samples were assayed with the Dual Luciferase reporter assay system kit (Promega) for Firefly and Renilla luciferase activities and measured on a PerkinElmer Life Sciences Wallac Victor2 1420 multilabel counter.PD-L1 3′-UTR were amplified from HeLa and subcloned into the psiCheck2 vector using XhoI and PmeI enzymes. Mutations were introduced at the PD-L1 3′-UTR at the miR-155-binding site  using a Q5 site-directed mutagenesis kit (New England Biolabs) and confirmed by DNA sequencing. The PU.1 3′-UTR constructs were described previously . LuciferCells were incubated with anti-PD-L1  and visualized with Brilliant Violet 421 (BioLegend) on a BD LSR Fortessa (BD Biosciences) using FACS DIVA software. Final analysis was done using FlowJo version 10 (Tree Star).Cells were cultured in 35-mm glass-bottom dishes with a 14-mm microwell (MatTek). After 48 h, cells were stimulated with IFN-γ or in combination with TNF-α for 24 h. Cells were fixed in 4% paraformaldehyde and permeabilized with 0.5% Triton X-100. Samples were incubated overnight at 4 °C with anti-PD-L1 (5H1) followed by goat anti-mouse secondary Alexa Fluor 488 (Thermo Scientific) and DAPI was used to stain the nucleus. Images were acquired with Zeiss Zen software using a Zeiss LSM 880 on a ×40 oil immersion objective lens.Experimental results are presented as mean ± S.D. The specific statistical tests are mentioned in the figure legends. Statistical analysis and graphs were made using GraphPad Prism 6 (GraphPad Software).D. Y. performed and designed experiments and wrote the manuscript. K. M. S. performed experiments. M. C. C. contributed to experimental design and supervised research. T. V. S. contributed to experimental design, supervised research, and co-wrote the manuscript. D. L. conceived the project, designed experiments, supervised research, and wrote and edited the manuscript.


The c-ITO on the monolayered graphene support showed significant enhancement in flexibility compared with the ITO/PET film without graphene because the atomically controlled monolayered graphene acted as a mechanically robust support. The prepared flexible transparent c-ITO/graphene/PET electrode was applied as the anode in a bulk heterojunction polymer solar cell (PSC) to evaluate its performance, which was comparable with that of the commonly used c-ITO/glass electrode. These results represent important progress in the fabrication of flexible transparent electrodes for future optoelectronics applications.Flexible and crystallized indium–tin oxide (ITO) thin films were successfully obtained on plastic polyethylene terephthalate (PET) films with monolayered graphene as a platform. The highly crystalline ITO (c-ITO) was first fabricated on a rigid substrate of graphene on copper foil and it was subsequently transferred onto a PET substrate by a well-established technique. Despite the plasma damage during ITO deposition, the graphene layer effectively acted as a Cu-diffusion barrier. The c-ITO/graphene/PET electrode with the 60-nm-thick ITO exhibited a reasonable sheet resistance of ~45 Ω sq In the early stage of development of a transparent electrode, a transparent conducting oxide (TCO) is deposited on a rigid substrate like glass. So far, one of the most commonly used materials for TCO is indium–tin oxide (ITO), which exhibits low electrical resistivity and high transparency in the crystalline state. However, amorphous ITO (a-ITO) does not have such properties as those displayed by crystalline ITO (c-ITO). Hence, for application as a TCO, the as-sputtered a-ITO must be transformed to c-ITO by heat treatment at a temperature of at least 250 °C9.Transparent electrodes are used in various industries, and they are especially popular for application in optoelectronic devices such as flat panel displays, touch sensors, light-emitting diodes (LEDs), and solar cells11. However, the growth of c-ITO directly on PET is technologically restricted because of PET’s lack of thermal robustness to withstand the high-temperature thermal treatment required for ITO crystallization. Therefore, the preparation of ITO on a PET substrate must be carried out at temperatures below 200 °C, the point at which ITO begins to display poor electrical conductivity and transmittance13. An alternative strategy is to synthesize highly crystalline ITO on a rigid substrate at high temperature and then transfer it onto a flexible substrate; successful implementation of this strategy is yet to be reported.Polyethylene terephthalate (PET) is one of the most popular alternatives to rigid glass as a substrate material owing to the increasing demand for flexible, lightweight, and cost-effective transparent electrodes2-bonded carbon atoms, has been intensively researched as a material for flexible transparent electrodes because of its high optical transmittance, electrical mobility, and mechanical flexibility14. Although excellent mechanical properties have been reported for graphene16, its electrical resistivity is still higher than that of ITO17. Therefore, some transparent electrode materials such as ITO19 and GaN20 have been deposited on graphene transferred onto a PET film, which requires no heat treatment for the electrode fabrication. In the study reported here, we first used graphene on a Cu foil as a rigid substrate for synthesizing highly crystalline ITO. The prepared c-ITO was then transferred onto a flexible substrate. In our study, the graphene layer was utilized as an atomically thin two-dimensional support for obtaining a flexible c-ITO film on a PET substrate. In addition to exhibiting high optical transmittance and mechanical flexibility, the thermal stability of graphene renders it a diffusion barrier of Cu during heat treatment of a-ITO for crystallization. The prepared c-ITO/graphene/PET film was mechanically flexible, while the high optical transmittance and low sheet resistance remained unchanged.Graphene, a two-dimensional monolayer of sp22. The a-ITO films were deposited onto the graphene/Cu substrates at various thicknesses of 60, 80, 100, and 120 nm using a direct-current (DC) magnetron sputtering system. Following the a-ITO deposition, the a-ITO/graphene/Cu films were annealed at 250 °C to obtain the crystalline phase. Each graphene-supported c-ITO film was then moved onto a PET film by a well-established graphene-transfer technique24.The fabrication procedure for the flexible c-ITO-based films is outlined in Fig. 26. The c-ITO formation on the graphene/Cu layer was confirmed by the diffraction peaks at 30.3° and 35.2°, corresponding to the (222) and (400) planes, respectively, of cubic In2O3 (JCPDS card No. 71-2494), a component of the sputtering target for ITO deposition. As expected, no crystalline ITO peaks were observed in the XRD pattern of a-ITO/graphene/Cu. As shown in Fig. The crystal structure of each layer was analysed by X-ray diffraction (XRD) Fig. . The  on the graphene support were examined by high-resolution transmission electron microscopy (HRTEM) Fig. . The cro31. To examine the plasma damage of graphene during ITO sputtering, Raman spectra were obtained for as-grown graphene, graphene after a-ITO deposition, and graphene after crystallization of a-ITO on Cu foil. As shown in Fig. −1, respectively, for the as-grown graphene on Cu foil. The symmetric 2D band and minimal D band indicate that the graphene was well-grown, with a negligibly small portion of structural defects, thus qualifying the material for further processing as a flexible transparent electrode32. However, the 2D peak disappeared and the D peak appeared at 1350 cm−1 after a-ITO deposition, which were likely due to the plasma-induced damage in graphene. The ITO crystallization step did not have any effect on the Raman spectra of the a-ITO/graphene/Cu film, suggesting that the structural defects did not propagate and there was no recovery of the graphene. The graphene damage may have induced Cu diffusion into the ITO layer during heat treatment for ITO crystallization. It has been reported that Cu diffusion into the TCO layer results in a decrease in transmittance and conductivity34. Figure Graphene is known to incur damages as a result of plasma exposure during thin-film deposition−1, respectively. In addition, the transmittance of c-ITO/graphene/PET (91.3%) was only ~2% smaller than that of c-ITO/glass (93.3%) at a wavelength of 550 nm because of the transmittance and absorbance of visible light by the single-layered graphene35. Consequently, the plasma exposure for deposition of up to a 60-nm-thick ITO layer was not long enough to damage the graphene. Nevertheless, the low sheet resistance of 44.7 Ω sq−1 and high transmittance of 91.3% have been beyond the reach of other ITO/PET systems31.The electrical and optical properties of the c-ITO/graphene/PET system were evaluated, and the results are shown in Fig. R/R0  was measured as a function of the number of bending cycles (N); the results are shown in Fig. 2 bending cycles with the highest strain of 1.12% (8 mm bending radius), and thereafter, the resistances changed by less than 5% of their initial resistance. Although ΔR/R0 changed gradually with repeated bending, the film with a 60-nm-thick layer of c-ITO showed the smallest variations. As mentioned earlier, the graphene damage with increasing c-ITO thickness might have been responsible for the gradual increase in ΔR/R0 as the number of bending cycles increased. Because graphene has extremely high strength and stiffness36, it effectively acted as a mechanically robust support between the ITO film and PET substrate18. In addition, the interfacial C–O bonding between graphene and the oxygen atoms of ITO37 induced a strong attachment of the ITO layer to the graphene substrate and prevented fractures in the c-ITO. As a result, the graphene-supported 60-nm-thick c-ITO film had the best electromechanical stability against bending stress owing to the relatively low plasma damage to the graphene layer. Meanwhile, despite the slight increase in the c-ITO film thickness (from 60 to 120 nm), the gradual damage in graphene with increasing c-ITO thickness resulted in a steeper increase in ΔR/R0.The electromechanical durability was evaluated by applying repeated tensile strain to the electrodes composed of graphene-supported c-ITO films with c-ITO thicknesses of 60, 80, 100, and 120 nm. This was accomplished by bending the films to radii of curvature of 16, 12, and 8 mm, thus inducing tensile strains of 0.56, 0.75, and 1.12%, respectively, in the top c-ITO layer. Meanwhile, the normalized resistance change, ΔR/R0 for the first 104 bending cycles of the graphene-supported c-ITO film, the graphene-free c-ITO/PET film cracked after 102 bending cycles for all values of the bending radius. Furthermore, the resistance changes of the graphene-free a-ITO/PET increased remarkably after 102 bending cycles. From the above analysis, it is obvious that the graphene support effectively enhanced the electromechanical stability of the c-ITO film against the bending stress, which is attributed to the robust adhesion of the c-ITO layer on the graphene support.Figure J)–voltage (V) characteristics of the prepared PSCs are shown in Fig. Jsc), open-circuit voltage (Voc), and fill factor (FF), were also very similar. Such comparable performance of c-ITO/glass and c-ITO/graphene/PET as the transparent conducting electrode is advantageous for various flexible device applications because of the c-ITO/graphene/PET system’s superior flexibility and excellent bending stability.The graphene-supported 60-nm-thick c-ITO film was evaluated as a transparent electrode of a bulk heterojunction polymer solar cell (PSC), as illustrated in Fig. In summary, we demonstrated the successful fabrication of a flexible c-ITO electrode with the aid of single-layered graphene support on a PET substrate. The atomically thin graphene film acted as a mechanically robust support for enhanced flexibility, as well as a thermal diffusion barrier against Cu diffusion into the ITO layer. The c-ITO/graphene/PET electrode exhibited sheet resistance and transmittance that were highly comparable with those of the c-ITO/glass electrode; it also showed significantly enhanced bending stability compared to that of the ITO/PET electrode without a graphene support. The fabricated c-ITO/graphene/PET electrode was used in a bulk heterojunction PSC, and the resulting PSC showed device performance comparable to that of the PSC with the c-ITO/glass electrode. These results suggest that c-ITO/graphene/PET is a promising flexible transparent electrode material for a variety of next-generation flexible optoelectronic devices. Also, the electrode transferring technique suggested in this study could bring out a technical issue of transferring an already-prepared module from a copper surface to a flexible or transparent substrate. As a next step for this research, a whole electrical cell could be fabricated on a copper substrate, and then transferred to a transparent substrate by this electrode transferring technique.4 was supplied to the chamber at 30 sccm for 500 s while maintaining the temperature for graphene growth. After the graphene growth, the chamber was cooled to room temperature22.Single-layered graphene was grown on copper foil (99.8%) by RTCVD Fig. . The Cu-2O3–SnO2 (Sn concentration: 10 wt%) was used as the ceramic sputtering target for the ITO deposition. The deposition conditions were as follows: DC power, 500 W; Ar to O2 ratio, 30:0.5; working pressure, below 2.5 × 10−6 Torr. The film thickness was varied from 60 to 120 nm. The as-deposited a-ITO/graphene/Cu electrode was then annealed at 250 °C to form c-ITO/graphene/Cu . A 4-in disk of In/Cu Fig. .For the transfer of the graphene-supported c-ITO onto the PET substrate, the as-prepared c-ITO/graphene/Cu film was first attached to a piece of thermal release tape. Using a standard wet etching method, the bottom Cu foil was then etched with an aqueous 0.1 M ammonium persulfate solution. After the residual etchant was removed several times with de-ionized water, the remaining graphene-supported c-ITO (c-ITO/graphene) on the thermal release tape was placed on the PET film with the graphene side facing the PET surface. A set of rollers was used to apply pressure on the back side of the thermal release tape and laminate the c-ITO/graphene film on the PET film at a mild temperature of 120 °C. The c-ITO/graphene film was transferred to the PET film as the thermal release tape lost its adhesive force at the elevated temperature. An a-ITO/graphene/Cu film was also prepared using the same procedure, but without the annealing process.α radiation (λ = 1.54056 Å). The cross section and surface morphology of the graphene-supported ITO films were examined with a transmission electron microscope  equipped with an energy-dispersive X-ray spectrometer . The specimens for the cross-sectional TEM analysis were prepared with a focused ion beam. The TEM was operated at 80 kV, and the EDX signal was collected at around 4.0 nA with a convergence angle of 13.5 mrad. The structure of the graphene layer in the specimens was monitored by a Raman spectrometer  operated at 2.41 eV, with an excitation wavelength of 514 nm. The transmittance of the graphene-supported ITO films was measured with ultraviolet–visible–near-infrared (UV–vis–NIR) spectrophotometer . The sheet resistance was measured with a four-point probe . Using a bending tester , the electromechanical bending test was performed by measuring the change in sheet resistance as a function of the number of bending cycles with various bending radii.The crystal structure was identified by XRD  with Cu KSupplementary Information.


The influence of graphene and retinoic acid (RA) – a π-conjugated organic semiconductor – interface on their hybrid system is investigated. The physical properties of the interface are assessed via scanning probe microscopy, optical spectroscopy (photoluminescence and Raman) and ab initio calculations. The graphene/RA interaction induces the formation of a well-organized π-conjugated self-assembled monolayer (SAM) at the interface. Such structural organization leads to the high optical emission efficiency of the RA SAM, even at room temperature. Additionally, photo-assisted electrical force microscopy, photo-assisted scanning Kelvin probe microscopy and Raman spectroscopy indicate a RA-induced graphene doping and photo-charge generation. Finally, the optical excitation of the RA monolayer generates surface potential changes on the hybrid system. In summary, interface-induced organized structures atop 2D materials may have an important impact on both design and operation of π-conjugated nanomaterial-based hybrid systems. Organic semiconductors offer a wide range of possible applications, from thin-film transistors to sensors and solar cells –6. Theirx) on Si, graphene and graphite microplates were tested . Several attempts with mica and SiOx yielded amorphous 3D-like RA agglomerates only  which was estimated via Mulliken population analysis (Hirshfeld method) [In order to confirm the nature of RA rippled domains seen in  method) –21.trans-retinal species [1Bu+ and 1Ag-(ππ*) singlet excited manifolds states [Retinoic acid is a well-known dye molecule with potential applications in solar cells –24 and,  species , and wits states –27.Nevertheless, the most interesting feature is shown in Vtip < 6 V, creating a strong electric field at the tip apex. In order to analyze the electrical response of the RA/graphene hybrid, the following experimental procedure was employed: during image acquisition, the RA monolayer edge was kept perpendicular to the horizontal (fast scan) direction, while the slow scan  axis was disabled. In other words, the same region of the RA monolayer and graphite substrate  – a graphite microplate surface prior to any RA deposition – under dark and illuminated conditions , functionalized graphene (GfDark and ∆ωGfLight), and the RA monolayer (RADark and ∆ωRALight). Blue (brown) symbols in VTip < 3 V and their variation according region and illumination condition is shown in Figure S3 in Besides RA SAM optical response, interface-induced modulation of the electrical properties of the RA–graphene hybrid system were investigated in a series of photo-assisted electric force microscopy (EFM) and scanning Kelvin probe microscopy (SKPM) measurements. nditions . Figure In conventional EFM, cantilever oscillation frequency shift (∆ω) can be modeled by0 and k are the cantilever’s resonant frequency and spring constant, respectively, C´´(z) is the second derivative of the tip–sample capacitance C(z), Vtip is the applied bias, Φ is the tip–sample surface potential difference, and f´(z) is the first derivative of the electric force resulting from permanent polarization or free charges on the surface [where, ω surface . In a siAccording to Considering, initially, parameter α in EF – Evacuum, where EF is the Fermi energy and Evacuum is extracted from the electrostatic potential calculation in the vacuum region near the surface. In the case of electron transfer from graphene to RA molecules (p doping), the graphene Fermi energy moves below the Dirac point, leading to an increase on its work function φ [eΦ = φTip – φS, where φTip(φS) is the tip (sample) work function and e the elementary charge [Nevertheless, the most significant information in nction φ –36. Sincy charge , a p-typAnother important result from eΦ = φTip – φS [Initially, considering the pristine graphite microplate surface case (green line in Tip – φS –39. When+ + O2− → O2 (gas)), releasing electrons that, then, contribute toward an effective n-doping [The effect of illumination on the hybrid system is also portrayed in n-doping –40. The n-doping –40. Thusn-doping –45. An aFinally, the charge transfer within the graphene/RA hybrid has also been investigated via Raman scattering experiments. Monolayer graphene, instead of graphite microplate, was chosen for this analysis due to the sensitivity of Raman spectroscopy to chemical doping effects in graphene –50. Ther−1) reassures that the graphene piece is a single-layer flake [−1 to 1590 cm−1, and its full width at half-maximum of 18 cm−1 to 8 cm−1, after RA functionalization. That is, the G band frequency increases and its width decreases, indicating graphene doping [50−1 arising from C=C RA molecule bond [5013 cm−2, consistent with the value predicted from ab initio calculations.The single-Lorentzian shape of the 2D band  [0 = 70 kHz and a spring constant k = 0.4 N/m. During operation in peak force mode, they are oscillated at a frequency f = 2 kHz with a typical amplitude A = 2 nm [0 = 75 kHz and ω0 = 20 kHz; and a spring constant k = 2.8 N/m and k = 0.3 N/m, respectively. For tapping and EFM imaging, these probes are oscillated near their resonant frequency with amplitude A ≈ 20 nm. EFM images were acquired with a lift height z = 50 nm within the bias range −6 V < Vtip < 6 V applied to the probe. The photo-assisted EFM data in Figures 4c–e are plots of averaged frequency shift vs bias from multiple (≈20) measurements. The experimental deviation is very small . The SKPM imaging was performed in the amplitude mode (AM-SKPM) with an AC bias VAC = 2 V applied to the probe at the resonant frequency of the cantilever and a lift height z = 20 nm. Steady-state photoluminescence (PL) measurements of RA monolayer/graphene system were done at different temperatures using a liquid He immersion cryostat and temperature controller. The sample excitation was performed using a 355 nm line from a pulsed Nd:YAG laser and the PL detection was made by an Andor spectrometer.High-purity graphite flakes were obtained from Nacional de Grafite Ltd., Itapecerica – Brazil. Retinoic acid (RA) was purchased from Alfa Aesar and was used without further purification. The RA multilayer (bulk-like film) was produced by spread coating method –61. Thinpy (EFM) –66 and spy (EFM)  experimeA = 2 nm . The HQ:a = 23.82 Å. In this case, the molecules are considered isolated atop graphene. We also used a rectangular supercell with sides of 34.95 and 8.64 Å  has been taken into account in all Ef values using the counterpoise correction [First-principles calculations were based on density functional theory –69 as im64 Å see . In orderrection .File 1Additional Figures.


Graphene is a promising next-generation conducting material with the potential to replace traditional electrode materials in supercapacitors. Since energy storage in supercapacitors relies on the electrolyte-electrode interface, here we elucidate the interfacial subnanometer structure of a single component liquid composed solely of cations and anions – an ionic liquid- on electrified graphene. We study the effect of applied potential on the interaction between graphene and a silicon tip in an ionic liquid and describe it within the framework of the Derjaguin-Landau-Verwey-Overbeck (DLVO) theory. The energy is stored in an electrical double layer composed of an extended Stern layer, which consists of multiple ion layers over ~2 nanometers, beyond which a diffuse layer forms to compensate the applied potential on graphene. The electrical double layer significantly responds to the applied potential, and it shows the transition from overscreening to crowding of counterions at the interface at the highest applied potentials. It is proposed that surface charging occurs through the adsorption of the imidazolium cation to unbiased graphene (likely due to π-π interactions) and that the surface potential is better compensated when counterion crowding happens. This study scrutinizes the electrified graphene-ionic liquid interface, with implications not only in the field of energy storage, but also in lubrication. Made up of a honeycomb carbon lattice, it has been found to exhibit many unique properties including ballistic electron transport3, large in-plane elastic modulus4, and high thermal conductivity5. Graphene owes its superior electronic properties to its honeycomb lattice carbon network, in which 2s, 2px, and 2py orbitals hybridize such that each carbon atom is bonded to its three neighbors by strong “sigma” bonds. The remaining “π” orbital determines the low-energy electronic structure of graphene. These desirable properties make graphene of considerable interest for potential use in many applications, several of which rely on liquid-graphene interfacial properties, including its use as supercapacitor electrode8. Interfacial water consisting of monolayers and multilayers have been often observed between graphene films and hydrophilic substrates such as mica and sapphire10, and between graphene sheets11. A fundamental understanding of the interfacial liquid properties imposed by electrified graphene is, however, still lacking.Since its discovery in 200412; due to its ionic composition, they are subjected to significant electrostatic interactions. Because of their high charge density and wide electrochemical window, and the possibility to tune intermolecular forces and physicochemical properties, ILs are considered to be ideal electrolytes for energy storage13. ILs display more pronounced ordering than conventional electrolytes due to strong ion-ion interactions -especially of Coulombic, van der Waals and solvophobic origin-, and many form well-defined nanostructures in the bulk phase14, at solid surfaces15 and in confinement16. Experiments18 show that ILs near the solid surface commonly exhibit oscillatory density profiles, which reflect the layered arrangement of the IL ions at the buried liquid-solid interface. Besides out-of-plane order, in-plane order has been also demonstrated by atomic force microscopy and scanning tunneling microscopy.19 Several parameters have been found to influence the interfacial structure, such as the chemical composition of the surface20, the strength of ion-ion interactions, i.e. the IL molecular structure21, and the surface charge and potential23. Increasing surface potential leads to an increase in the strength of the ion-surface Coulombic interaction.24 Further, theoretical studies have shown that, when the electrode polarization increases, the interfacial structure of ILs undergoes a transition from overscreening the surface charge by a single monolayer of counterions to crowding of counterions across more than a single monolayer25.A single component electrolyte composed of ions –an ionic liquid– with a moderate polarizability has been chosen for this study. Ionic liquids (ILs) are organic molten salts with low melting point26. A long-range electrical double layer force with a decay length as large as 13 nm has been measured for several ILs on various substrates31. This finding is important since the interfacial capacitance is inversely proportional to the effective thickness of the electrical double layer where the charge is stored, and hence, it affects the stored energy in the supercapacitor. The proposed “aggregation” model26 assumes that ILs are dielectric solvents composed of a strongly correlated ionic network, where each charge is counterbalanced by the sum of the neighbours’ charge and only a small percentage of the ionic network is effectively dissociated. To reconcile the aggregation model with NMR diffusivity measurements, which fail to find evidence for long lived ion pairs32, the coordinated cation-anion network is proposed to be highly dynamic and transient. Although the temperature-dependence of the electrical double layer force further strengthens the argument in favor of a diffuse layer, the shape of the reported capacitance and ion conductivity in separate works and in different systems contradicts the assumption of low ion dissociation, and it is still a subject of debate26. Nevertheless, our results are consistent with the reported aggregation model.Over the past three years some evidence has accumulated demonstrating that long range surface forces on electrically charged surfaces immersed in ILs are of electrostatic origin and they respond to the characteristics of an electrical double layer force of a dilute electrolyte solution38. The results are contradictory with regard to the composition of interfacial IL layers, since some of them show a significant enrichment of imidazolium cations on uncharged graphene36, while others show a densification of the interfacial layer composed of ion pairs, although, admittedly, π-π interactions are missing in these simulations38. A thorough experimental study of the Stern and diffuse layers of ILs on electrified graphene has not been performed yet. In this work, we have scrutinized the electrical double layer of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (abbreviated as [EMIM][TFSI]) at the graphene plane, for single- and few-layer graphene by probing normal surface forces by atomic force microscopy under applied positive and negative potentials. Statistical analysis of the steps resolved in the force-separation curves and modeling of the surface forces provide molecular insight into the electrical double layer of [EMIM][TFSI].To date, a few simulations, scattering and spectroscopy works have investigated the IL-graphene interfaceA 90 nm thick silicon dioxide layer –that we refer as silica substrate– and a working electrode composed of a 9 nm thick gold layer thermally evaporated on the silica substrate were chosen as substrates for mechanically exfoliated graphene. The number of mechanically-exfoliated graphene sheets was determined by combining Raman microspectroscopy and atomic force microscopy (AFM) imaging of the topography. All graphene samples were first imaged in air and then in [EMIM][TFSI] to exclude changes of topography upon immersion in the IL. Figure After equilibration, normal force-separation curves were measured on edge-free areas of single-layer (SLG), bilayer (2LG), few-layer , and multi-layer (MLG) ( > 7) graphene supported on gold and silica at a constant approach speed of 10 nm/s. Figure 40, i.e. the layered arrangement of the molecules at the buried liquid-graphene interface. The FTT happens when the force required to overcome a maximum in the oscillatory force is reached. In terms of mechanics, if the second derivative of the effective surface interaction potential exceeds the spring constant of the cantilever, the tip will push through an IL layer, thereby leading to a step in the force-separation curve. On unbiased graphene, ~4–7 FTTs are resolved in each force-separation curve, i.e. more than on silica and gold supports (~3–4). While the atomically smooth graphene plane is expected to favor efficient ion packing at the interface compared to silica, the roughness of gold is also sub-nanometer (RMS ~0.3 nm as determined by AFM), and hence, only surface roughness cannot explain the enhanced IL-layering on graphene.Discontinuities in all force-separation curves appear at separations smaller than D ~ 2–3 nm superposed to an attractive force; the “red” regions within the clouds of data points with higher density represent these discontinuities in a bivariate histogram. The discontinuities, which are referred to as film-thickness-transitions (FTT), reflect the oscillatory density profile of liquids at interfacesSince the number of graphene sheets did not significantly influence the interaction between tip and supported graphene in the IL Figure , the inv21. This previous work also detected an attractive force but did not rationalize its origin. We propose that the electrical double layer (EDL) force is attractive for the dissimilar graphene-tip system and that the variation of the force with surface potential reflects the change of the EDL with applied potential. Further, the decrease in the attractive EDL force at the highest applied potentials(~ ± 0.7 V) is related to the onset of crowding, as discussed later.On graphene Fig. , the for28), or the Hamaker constant on gold is much smaller than on graphene as a result of the unique electronic properties of graphene; the discussion of the Hamaker constant in the next section does not support the latter, though. Nevertheless, the consistently lesser sensitivity of the measured force on gold to surface potentials compared to graphene  is expected to be larger than that of graphene, the higher pull-off force on graphene in the absence of an applied potential (OCP) might appear surprising. However, due to the presence of oscillatory entropic solvation forces, multiple adhesive minima are present in confined liquids that arrange in layers. Such adhesive minima depend on the number of confined layers, as already demonstrated for ILs. 42. Figure 43. Asymmetric electrowetting has been also measured for deep eutectic solvents composed of choline chloride in organic solvents like urea, ethylene glycol and glycerol on HOPG, and hence, it is not a unique feature of ILs44.The pull-off force remarkably decreases when the potential goes beyond a threshold , D is the surface separation (in m), ψG is the potential at the Outer Helmholtz Plane (OHP) on graphene (in V), −1), ε is the relative permittivity of the IL (unitless), and εo is the vacuum permittivity (in F/m). The expression for the EDL force is based on Hogg-Healy-Fuerstenau approximation45 and it assumes constant surface potential as boundary condition; neither constant surface charge nor mixed boundary conditions were found to agree with the experimental data. The second term in the EDL force always leads to an attractive force, whereas the first term can cause an attractive or a repulsive force depending on the sign of the diffuse potentials. Calculations were not carried out for DLVO forces between silica or gold supports and the tip due to the small value of the measured surface forces at D > 2 nm.To get more insight into the EDL of [EMIM][TFSI] on graphene, the measured surface forces were modeled according to the DLVO theory. The following expression gives the DLVO force for dissimilar surfaces as the sum of van der Waals and electric double layer forces47. The Lipkin theory48 was used to estimate the Hamaker constant of graphene and tip  in air with 15 s−1, and 15 s−1 46, which yields AG ~ 1.52·10−19 J and is close to reported experimental and theoretical values for HOPG (1.35·10−19 J in ref. Au ~ 1.91·10−19 J for gold (15 s−1). There is no agreement about the influence of the number of graphene sheets on the Hamaker constant yet50, but these results suggest the influence to be small. According to mixing rules, the IL is expected to reduce the Hamaker constant with respect to the values obtained in air39. Gebbie et al.28 argued that surface-adsorbed IL ions can further affect the Hamaker constant and used a value of ~0.9–2·10−20 J for mica-IL-gold systems. An accurate analytical estimation of the Hamaker constant for the AFM probe-IL-graphene system is not possible yet. Satisfactory fits to the force-separation curves with Eq. , as previously determined for [EMIM][TFSI] in the potential range + /− 0.5 V)27. The good fit of the DLVO theory to the measured surface forces under applied potential demonstrates that an EDL force can explain the change in the measured attractive interaction , the stronger attractive force leads to a more negative effective diffuse potential on graphene Fig. . A betteFigure extended Stern layer because it is composed of multiple layers– can be determined through statistically scrutiny of the film-thickness transitions detected in the force-separation curves. The size of a film-thickness transition is defined as 52. 2D histograms with the layer size (∆) and the layering force (F) were constructed to compare the composition of the four IL-layers closer to the hard wall on graphene, and silica and gold supports ; the second and third IL-layers are much larger than on the silica support , while the thickness of the following IL-layers decreases toward ∆ ~ 5 Å. The cartoon in Fig. extended Stern layer of [EMIM][TFSI] on graphene, consisting of a film with 4–7 IL-layers. The characteristic size of the IL-layer at the graphene plane (~3.3 Å) is consistent with a cation-enriched layer, in which the imidazolium ring is parallel to the graphene plane. A cation-enriched adlayer would yield a plane of net positive charge on unbiased graphene with a maximum overscreening of ~1.6 positive charges per nm2 , qualitatively consistent with the positive diffuse potential at OCP .The thickness of the IL-layers on silica-supported graphene significantly deviates from the values measured on the silica support Fig. : the IL-OCP Fig. . Figure 1 ~ 3.1 Å, ∆2 ~ 8 Å and ∆3 ~ 5 Å) were reported for [EMIM][TFSI] on HOPG . Since water molecules preferentially interact with the anion, they might be enriched in the second layer, where the highest expansion was observed on silica-supported graphene.We note that the extended Stern layers built up on gold- and silica-supported graphene are qualitatively similar Fig.  vs. 5B,Cst layer remains essentially unchanged at negative potentials, which is consistent with a cation-rich composition. The size of the second and third IL-layers responds to the applied negative potential through a smaller expansion, likely to result from the increase in near-surface cation population compared to OCP  that differs from the characteristic layer size distribution on silica and graphene surfaces. At positive potentials, the thickness of the 1st layer does not change, which would be consistent with an anion-enrichment at OCP and ∆U > 0. The decrease in size of the 1st layer to ∆1 ~ 3–3.5 Å at negative potentials clearly supports cation-enrichment and parallel orientation of the imidazolium ring relative to the surface (6), as observed for graphene. We note that previous work has shown the specific adsorption of 1-butyl-1-methylpyrrolidinium cations to gold at OCP and even at positive potentials56. However, the interaction between gold and [EMIM]+ is known to be weaker than between gold and 1-butyl-1-methylpyrrolidinium, and hence, this is unlikely to happen here58. The observed increase in the layering force required to push through the IL layer closest to the hard wall under applied potential compared to OCP supports the last resolved layer to be enriched in counterions. The force differs under negative (∆F ~ 0.75–1 nN) and positive (∆F ~ 0.44 nN) potentials, which indicates the different binding strength of the (positively and negatively charged) counterions, justified by the ion pair asymmetry59 and in agreement with other works28. Although no layers were resolved at loads above 2 nN, it cannot be totally excluded that IL remains confined between the AFM probe and the gold substrate at the maximum applied load. Such an effect could explain the smaller pull-off force on gold compared to graphene. Future studies, e.g. with our Surface Forces Apparatus, are needed to test this hypothesis on gold surfaces.The out-of-plane structure of [EMIM][TFSI] on gold is clearly different at all potentials. Figure 26, ion pairs are expected to populate the solid-liquid interface in the absence of surface charge and specific interactions, thereby eliminating overscreening and EDL forces, as it occurs on silica surfaces  are not able to fully screen the surface charge, which leads to a non-zero potential at the Outer Helmholtz Plane; to compensate this potential, a diffuse layer builds-up. Figure 31.The described force measurements provide insight into the EDL of [EMIM][TFSI] on graphene. While EDL forces have been previously measured between charged or biased surfaces in ILsces Fig. . HoweverAn increase in applied potential is reflected in an increasing onset of the EDL force while the decay length remains constant. An important observation is that the thickness of the IL layers decreases. This is likely because a lesser population of co-ions is present within the extended Stern layer. The trend of the EDL force is reversed at the highest potentials, at which the EDL force becomes less attractive, which suggests that the surface potential is better compensated by the counterions. We propose that this reversal coincides with the transition from overscreening to crowding. The phenomenon of crowding implies that the electric field is high enough to dissociate more effectively the ionic network, so that several layers of counterions populate the interface Fig. . Thus, c46 and in water47. The different interfacial structure of [EMIM][TFSI] on graphene compared to gold at the same potential must rely on specific surface IL-interactions. Image forces, i.e. the electrostatic force on the IL in the neighborhood of a conductor, are expected for both graphene and gold, and hence, they are not expected to be the main source for the observed differences, although image forces are expected to play an important role. First-principle density functional theory (DFT) calculations have shown strong donor-acceptor interactions between ions and graphene61 and molecular dynamics simulations suggest π-π interactions to be one of the main mechanisms for adsorption of proteins on graphene63. Such π-π interactions are also possible between the π-orbitals in graphene and in the imidazolium ring, and hence, they may be responsible for the enrichment of cations with planar orientation at the graphene interface. Considering that the extended Stern layer at negative potentials appears to be thicker than at positive potentials, it is likely that π- π interactions between graphene and the imidazolium ring of the IL provide more efficient packing of the cation than of the [TFSI]- ion. Similarly, specific interactions between gold and [EMIM][TFSI] could justify the better compensation of the surface potential on gold compared to graphene and consequently, the less pronounced EDL force at all potentials on gold, but this will be investigated in a separate work.The shielding effect of graphene in the IL is demonstrated through the remarkably different interfacial structure that is resolved on the selected supports, gold and silica. This is reasonable considering the reported shielding effect of graphene in air64, it has been demonstrated that the capacitance is dominated by the EDL in the IL if the graphene electrode is composed of more than four graphene sheets. In this case, the potential-dependent differential capacitance13 could be roughly estimated with the effective Debye length. Our results show that, for this particular IL, the effective thickness of the EDL on graphene is >1 nm and hence, larger than ideally expected for supercapacitors (<1 nm). Importantly, the measured change of the layer size distribution with potential shown in our force measurements supports that the compacity parameter (or packing efficiency) of [EMIM][TFSI] is not constant but it depends on the applied potential, which is not considered in the simplified EDL theory13. The high configurational and conformational entropy of the IL ions, and the ion dissociation as a function of the potential are important parameters to consider for the selection of IL electrolytes for energy storage on graphene electrodes. The observed instability in the force-separation curves  will help to clarify the type of interactions that are responsible for the observed interfacial structure and will contribute to guide the design of IL-based supercapacitors with graphene electrodes.66. No exfoliation of graphene has been observed in [EMIM][TFSI]67, which has been attributed to its lower surface tension (33 mN/m), which is also consistent with the stability of our system for at least 12 hours, which was the maximum duration of the experiment.[EMIM][TFSI]  was purchased with > 99% purity. Recent work has shown that for an IL to flow in between graphene sheets, the surface tension of the IL must be in the range 37–45 mN/m, i.e. closely match the surface energy of graphene2. The wafers were then thermally oxidized at 1100 °C for 22 minutes, which led to an oxide layer of ~90 nm that we refer to as silica support or surface. Prior to graphene transfer, the silica surfaces were rinsed with ethanol, dried, and treated in a UV-ozone cleaner for 40 minutes. The gold (Au) working electrode was prepared on the silica support. A chromium (Cr) layer with a thickness of 1 nm and a gold layer with a thickness of 9 nm were thermally evaporated on the silica support with an E-beam evaporator. The Au/Cr film was kept at ~10 nm to yield a semi-transparent film allowing for the fast identification of single- and few-layer graphene with an optical microscope. Prior to exfoliation, the gold electrodes were cleaned for 10 min in a UV-ozone cleaner, followed by thorough rinsing with milliQ water for 1 minute and ethanol for an additional minute. The gold electrodes were then dried with dry N2, cleaned by UV-ozone for additional 5 minutes, and rapidly immersed into an ethanol bath for one hour to reduce the gold surface. After reduction, the electrodes were removed from the ethanol bath, and dried with dry N2 prior to graphene exfoliation.Graphene was prepared by mechanical exfoliation using Kish graphite, Grade 200 . Silicon wafers were cleaned in a base piranha solution for 20 minutes at 85 °C, rinsed thoroughly with milliQ water, followed by ethanol rinsing, and dried with dry NRaman spectroscopy and atomic force microscope imaging of the topography were used to detect the number of graphene sheets on silica and gold supports. Raman microspectroscopy measurements were collected with a Nanophoton Raman 11  microscope using a 532 nm laser. Laser power was set to at least 1 mW, with exposures lasting at least 15 seconds per spot. The graphene was exposed to ambient laboratory air for ~3–4 hours during identification of suitable graphene samples for experiments, and during Raman spectroscopy. The samples were then stored in vacuum (−0.5 bar) until force measurements were performed, which happened within 24 h to minimize aging.68.The atomic force microscopy (AFM) studies were performed on a JPK Nanowizard Ultra  under ambient laboratory conditions . Prior to experiments, all AFM tips were cleaned via UV-Ozone for at least 40 minutes. Graphene images were acquired first in tapping mode in air with a backside gold coated tip  with a resonant frequency of ~300 kHz. The images were collected at scan rates between 1–2 Hz. Following imaging in air, the AFM tip was changed to a contact mode tip, and graphene samples and tip were immersed in vacuum-dry [EMIM][TFSI] and the IL was allowed to equilibrate for 40 minutes prior to force measurements. Images of the graphene samples immersed in the IL were typically collected in contact mode with sharp Si-tips  with a spring constant of ~0.5 N/m and a nominal tip radius < 12 nm, at an applied load of 5 nN and scan rates between 1–1.5 Hz. The spring constant was determined according to the thermal noise method3N4-tips. For the normalization of the force, the tip radius was measured by scanning electron microscopy after the experiment.Force measurements were performed on edge-free areas on single-layer (SLG), few-layer , and multi-layer (MLG) ( > 7) graphene supported on gold and silica, and the control measurements were carried out on silica and gold supports, all in [EMIM][TFSI], in an open cell. Force maps were collected at a constant approach speed of 10 nm/s and an applied normal load that did not exceed 10 nN within scan areas that were at least 500 nm by 500 nm, with at least 64 force isotherms collected per scan area. Although most of the experiments were performed with a Si-tip, some force measurements were conducted with Si2. The platinum counter (dia. = 0.5 mm) and reference electrodes (dia. 2 mm) were sonicated in dilute (1 M) HCl for 5 mins, followed by rinsing with milliQ water and ethanol, and dried with dry N2.The electrochemical AFM cell consists of a gold working electrode and platinum counter and reference electrodes. The volume of the electrochemical cell (~1.3 mL) was filled with the IL to ensure immersion of the counter and reference electrodes. The diameter of the gold working electrode is ~15.6 mm, resulting in a working electrode area of ~1.9 cmWater uptake cannot be excluded during the duration of the experiment, but after 12 h it did not exceed 0.45 wt% and 0.1 wt% in the experiments with silica- and gold-supported graphene, respectively, as obtained gravimetrically. The reason for the different water content is the different volume of the open AFM cell used in both experiments (1.3 mL for gold-supported graphene and 20 µL for silica-supported graphene) and the uptake rate.The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.Supplementary Material