The Maugis-Dugdale theory was applied to convert the AFM measured adhesion force to adhesion energy, while taking into account surface roughness. The obtained adhesion energies were compared with those for mono-, bi-, and tri-layer graphene, as well as SiO2 substrates. The average adhesion energies for the MXenes are 0.90 ± 0.03 J m−2 and 0.40 ± 0.02 J m−2 for thicker Ti3C2Tx and thinner Ti2CTx, respectively, which is of the same order of magnitude as that between graphene and silica tip.Two-dimensional transition metal carbides (MXenes) have attracted a great interest of the research community as a relatively recently discovered large class of materials with unique electronic and optical properties. Understanding of adhesion between MXenes and various substrates is critically important for MXene device fabrication and performance. We report results of direct atomic force microscopy (AFM) measurements of adhesion of two MXenes  is important for potential MXene device fabrication and performance. Here, the authors show that adhesion of MXenes depends on their monolayer thickness and, in contrast to graphene, does not show number-of-monolayers dependency. These properties render MXenes prospective materials for supercapacitors4, Li-ion and beyond Li-ion batteries6, triboelectric generators7, photonic diodes and Q-switched lasers8, sensors10, composites12, etc. More than 20 different MXenes have been synthesized by selective A element extraction with fluorine-containing etchants from bulk ternary compounds known as MAX phases13. MXenes have a general formula Mn+1XnTx, where M represents an early transition metal , X is carbon or nitrogen, and n is an integer. T denotes the terminating functional groups  attached to MXene basal surfaces during synthesis16. Among experimentally available MXenes, Ti3C2Tx and Ti2CTx are some of the most widely investigated. MXenes are intrinsically hydrophilic and yet, they have demonstrated higher electrical conductivity than solution processed graphene17. In addition, their exceptional electrochemical properties show great promise for flexible electronics and planar devices18. There are studies on MXene dispersions in organic solvents for incorporation into polymers, inks, etc19. As researchers move closer to device fabrication, adhesion to different materials, as well as other mechanical properties of MXenes become of greater importance. There is a handful of published data on the mechanical behavior of MXenes. Theoretical calculations using molecular dynamics (MD) have predicted the Young’s modulus of 597 GPa for bare Ti2C and 502 GPa for bare Ti3C2 MXenes20, whereas a recent experimental AFM indentation study of a single suspended Ti3C2Tx MXene flake reported the value of 333 ± 30 GPa21. Although no other experimental data for Ti3C2Tx or Ti2CTx are available for comparison, the agreement between MD derived and experimental Young’s modulus is fairly good, taking into account the defective structure and surface terminations in real MXene samples that have not been captured in the simulations. MD modeling has also predicted a high bending rigidity of MXenes compared to single atomic layer 2D materials like graphene and hexagonal BN22, an important result for the development of sensing applications of 2D materials. However, to our knowledge, no theoretical or experimental studies of adhesive properties of MXenes have been reported to date.A large family of two-dimensional (2D) transition metal carbides and nitrides (MXenes) have emerged over the past few years as a class of materials with superior and highly tunable electronic and optical properties25. In recent years, the adhesive interactions of monolayer and a few layer 2D materials have been intensively investigated. One of the important questions is to understand how the properties, in particular adhesive strength, change when transitioning from bulk to 2D form of a material. Answering this fundamental question will require systematic studies of the property  while varying the thickness of a material without changing its atomic composition or type of bonding within the material. From this standpoint, the MXenes family represents another unique and still widely underutilized advantage, allowing to systematically change the thickness of the monolayer without changing the type of bonding or elemental composition of the material . Other 2D materials have fixed monolayer thickness and thus would not allow the systematic study of a property as a function of their monolayer thickness disentangled from other variables, such as elemental composition, chemical bonding, etc.Nanoindentation has been widely used to characterize adhesion of thin films3C2Tx, Ti2CTx), as well as the mono-layer, bi-layer, and tri-layer graphene interacting with the oxidized silicon tip. The force-displacement responses were evaluated and compared. The measured adhesion force was converted into the adhesion energy using the Maugis-Dugdale26 theory and taking surface roughness into consideration. The experimentally measured adhesion energy between Ti3C2Tx and SiO2 is 0.90 ± 0.03 J m−2, which is higher than that of Ti2CTx (0.40 ± 0.02 J m−2), thus the monolayer thickness was found to have a significant effect on the adhesion energy. However, in contrast to our experimental data for graphene, the number of MXene monolayers in a stacked MXene structure was found to have little impact on the adhesion energy.In this work, AFM was used to measure the adhesive properties of two MXenes  with different thicknesses were calculated and presented in Fig. 3C2Tx, 69–87 pm for Ti2CTx) and within 5% of the corresponding thickness  than those for Ti2CTx (0.53 µN). The “jump-off” (V to VI) observed for graphene, as well as MXene samples describes adhesion with a large interaction range, which may be a sign of the capillary force effect. Similar findings were reported in the nanoindentation experiments conducted on the surface of graphene27. The jump-off instability is worth mentioning at this conjunction as it might affect the accuracy of the measurements. However, this concern was eliminated by an accuracy analysis comparing the cantilever stiffness with the adhesion gradient during the experiment , graphene  and MXenes , all shown in Supplementary Fig. 29. The actual adhesion energy is:Rfilm is the RMS value for the sample surface, Z0 is the equilibrium separation of two surfaces. In our experiments, the equilibrium separation Z0 is defined as zero-force distance between the surface of SiO2 tip and the sample surface, which was estimated to be 0.3 nm30. All adhesion energies in this work were calculated according to Eq.  force using the Maugis–Dugdale theory2/SiO2 (0.40 ± 0.01 J m−2) is fairly close to the value obtained for piranha solution treated Si wafer by Na, et al. (0.33 ± 0.01 J m−2)30.We compare all measurements and plot the average adhesion for each type of interactions in Fig. 2 with mono-layer, bi-layer, and tri-layer graphene are 0.58 ± 0.02, 1.36 ± 0.02, and 1.33 ± 0.03 J m−2, respectively, indicating the number-of-monolayer dependence. This experimental dependence shows that adhesion energy of graphene with SiO2 initially increases when going from mono-layer to bi-layer graphene and then stays constant when the number of graphene monolayers in the stack is increased to three. Similarly, a small increase in normal pull-off force that was more pronounced when going from 1 to 2 stacked graphene layers and less pronounced for a larger number of layers, has been predicted by modeling31. However, this trend was “not observed in experiments possibly due to the experimental uncertainty”31. Another relevant paper on the number-of-layer effect on adhesion of graphene32 mentions the opposite trend (measured by blister method), which also ceases when the number of graphene layers exceeds 2. There are also studies mentioning no number-of-layer effect on the pull-off force of graphene33. This broad spectrum of literature results may indicate the challenges associated with experimental measurements, as well as the differences between the measurement techniques , and differences in graphene sample preparation 32. However, for the purposes of our study it is important that: (i) modeling predicts a slight increase in the adhesion with a number of graphene monolayers31, while it is not easy to explain the trend in opposite direction32; and (ii) both modeling and experiments (even those where oppositely directed trend was observed) converge on that the number-of-layer trend for graphene ceases when this number exceeds 2–3, i.e., when the distance between the top-most and the bottom-most graphene layers is ~0.7–1 nm.The adhesion energies of SiO−2) is close to the results of Jiang and Zhu (0.46 ± 0.02 J m−2)23 and Torres et al. (0.57 J m−2)34. The small differences between these results are possibly due to different methods of graphene synthesis or different measurement methods. Jiang and Zhu measured graphene sample prepared by mechanical exfoliation, while CVD graphene was used by Torres et al. Here, we use an AFM experiment similar to Jiang and Zhu23, while Torres et al.34 measured using the nanoparticles method. Due to differences in sample preparation approaches, as well as adhesion energy measurement techniques, the authors could not provide explicit or definite reasons for the slightly higher adhesion measured in this work as compared to different literature data.The average adhesion energy of the monolayer graphene measured in this work , and larger than that between SiO2 and monolayer graphene. At the same time, the average adhesion energy between SiO2 and 1-monolayer Ti2CTx is less than between SiO2 and monolayer graphene   data in Supplementary Fig. 2, we did not observe any number-of-monolayer (or sample thickness) dependency  surface was used to measure adhesive behavior of the samples. SEM images of the microsphere AFM tip are provided in Supplementary Fig. −1. The force-displacement responses for the approach and withdrawal stages were recorded and analyzed.AFM  was conducted under the ambient conditions as illustrated in Fig. oxide SiO surface 36. The capillary force is usually induced by water bridging the sample and tip surfaces38. We did check the effect of moisture by conducting AFM experiments with Ti3C2Tx while varying the relative humidity . This indicates that the drop in adhesion force for Ti3C2Tx after 48 h exposure to ambient air is due to chemical changes of the MXene, emphasizing the need to work with freshly prepared MXene samples, which was always properly taken care of in this study: all MXene samples were measured within no more than 12 h from their preparation and drying.The typical adhesive interaction of thin films involves the van der Waals, capillary, and electrostatic forces39.Large-area monolayer graphene was grown by chemical vapor deposition (CVD) on 2 × 10 cm copper foils . During this process, gas species were fed into the reactor flow over the 25 µm thick piece of copper foil, where hydrocarbon precursors decomposed to carbon radicals at the copper surface and then formed monolayer graphene40. The foil was then etched away in 0.2 mol L−1 FeCl3 and 0.2 mol L−1 (NH4)2S2O8 for 2 h41. The remaining graphene/PMMA was cleaned with deionized water, transferred onto freshly synthesized graphene on copper foil and heated at 50 °C in dry air to remove water. After another copper foil etching process, the graphene/graphene/PMMA sample was obtained. The tri-layer graphene was prepared by repeating this procedure. The graphene/PMMA, graphene/graphene/PMMA and graphene/graphene/graphene/PMMA samples were then transferred onto target Si (111)/SiO2 substrates and baked at 120 °C for 15 min. Prior to transfer, Si substrates were cleaned by 30 min bath sonication in acetone and hydrophilized in piranha solution (3 mL 30% H2O2 slowly added to 9 mL 98% H2SO4) for 24 h, followed by thorough rinsing with deionized water. Finally, PMMA was removed using acetone solution, yielding a sample of graphene on the Si/SiO2 substrate. The residue of polymer film was etched away at 400 °C in hydrogen27.To prepare the multilayer graphene, a copper foil with graphene on top was spin-coated with a layer of polymethyl methacrylate (PMMA) (3000 rpm for 30 s)3AlC2 was prepared by pressureless synthesis method42. The initial powders of titanium , aluminum , and graphite  were ball-milled in 3:1.1:1.88 molar ratio in a polyethylene jar for 12 h at 100 rpm. Afterwards, the mixture was sintered at 1550 oC for 2 h in Ar flow in an alumina boat using a tube furnace . For Ti2AlC synthesis, the initial powders of titanium carbide , titanium , and aluminum  were ball-milled in a molar ratio of 0.85:1.15:1.05. The mixture was then heated at 1400 oC for 4 h under Ar flow in an alumina boat. The resulting ceramics were manually crushed into powders using mortar and pestle.Ti3C2Tx MXene was synthesized by selective etching of Al from Ti3AlC243. The etching was done by slowly mixing 0.3 g of Ti3AlC2  to the etchant, prepared by dissolving 0.3 g LiF in 6 mL of 6 M HCl in a 50 mL plastic centrifuge tube. The mix was stirred for 24 h at room temperature, followed by repeated washing with deionized water and centrifugation until the pH of supernatant reached 5.5–6.0.Ti3C2Tx aqueous colloidal solution was obtained via 5 min hand-shaking followed by 1 h centrifugation at 3500 rpm. Ti3C2Tx thin films on Si were prepared from the concentrated Ti3C2Tx colloidal solutions via interfacial film deposition method8. In order to prepare MXene thin films, 50–300 µL of Ti3C2Tx colloidal solution was mixed in 50 mL DI water together with 3–6 mL toluene added during 15 min of vigorous stirring. The dispersion was then poured directly into a beaker filled with 400 mL DI water and with a few pieces of pre-cleaned Si wafers placed at the bottom. After ~20 min standing still, the Ti3C2Tx film was self-assembled at the interface between water and toluene, and then the pieces of Si wafers were slowly lifted up from the solution through the interface, catching the interfacial MXene film. Finally, the MXene coated Si wafers were dried for 12 h in Ar flow at room temperature to avoid oxidation. Ti2CTx colloidal solutions, as well as thin films were obtained using same methods, except the MAX phase in this case was Ti2AlC  and the MXene (Ti2CTx) film drying time was 4 h in Ar flow at room temperature.TiBy adjusting the concentration of MXene colloidal solution during sample preparation, MXene films with different thicknesses were deposited ranging between 1.4 to 26.9 nm. The adhesion measurements were carried out immediately after the films were dried.3C2Tx samples after initial drying (12 h in dry Ar flow) were placed into a closed chamber with P2O5, where RH was monitored with CECOMINOD046940 monitor (Hyelec). The samples were removed for adhesion measurements when RH reached 24%, 21%, 18%, 15%, 12%, 9%, and 6%  of 2D band is ~27 cm−149. The 2D/G ratio and FWHM for the bi-layer graphene are 1 and 52 cm−1, and for the tri-layer graphene, these values are 0.5 and 63 cm−150  with Cu K < α > radiation (The structures of Ti3C2Tx and Ti2CTx MXene thin films were performed using a KRATOS AXIS 165 X-Ray photoelectron spectrometer with a monochromatic Al X-Ray source.X-Ray photoelectron spectroscopy (XPS) measurements of Ti3C2Tx and Ti2CTx are at d-spacing values are 1.48 nm and 1.36 nm52, which are sums of the thickness of MXene monolayer and the interlayer spacing. Therefore, the number of MXene monolayers in different thin films can be calculated as the local AFM measured thickness of the films  peaks for Ti peaks foSupplementary InformationSource Data


This was [Stephen] Hawking’s central point in 1976 when he created something that came to be known as the information paradox. It was an extremely deep and important observation. It wasn’t important that Hawking didn’t get the right answer; he asked the right question. And this became a central debate that took twenty five years to resolvehttps://www.youtube.com/watch?v=2DIl3Hfh9tY, Minute: 13:40)Leonard Susskind , but the really exciting questions about our genome biology arose only afterwards.If an idea is truly unexpected, then we could not have arrived at it solely through existing questions; instead, we had to navigate through night science, moving from disparate observations to previously unknown questions. It is freeing and exhilarating to embrace this uncertainty, to fly right into the heart of the cloud, even if we may feel stupid and lost there. Night science, that realm where questions and ideas are born, appears so mysterious that it is often not described at all. But it is our premise that there are patterns to it, and this is what will occupy us in the following installments of this mini-series.


Since the advent of graphene, a variety of studies have been performed to elucidate its fundamental physics, or to explore its practical applications. Gate-tunable resistance is one of the most important properties of graphene and has been studied in 1–3 layer graphene in a number of efforts to control the band gap to obtain a large on-off ratio. On the other hand, the transport property of multilayer graphene with more than three layers is less well understood. Here we show a new aspect of multilayer graphene. We found that four-layer graphene shows intrinsic peak structures in the gate voltage dependence of its resistance at zero magnetic field. Measurement of quantum oscillations in magnetic field confirmed that the peaks originate from the specific band structure of graphene and appear at the carrier density for the bottoms of conduction bands and valence bands. The intrinsic peak structures should generally be observed in AB-stacked multilayer graphene. The present results would be significant for understanding the physics of graphene and making graphene FET devices. Controllability of resistance by using gate voltage is one of most significant properties of graphene for practical application in FET devices. It is known that transport property of graphene is highly influenced by the surface environment . Gate-voltage dependence of the resistance of such dirty graphene samples often shows multiple-peak structure, which possibly originate from local potential energy differences due to the surface contamination. Placing graphene on high-quality h-BN flakes or using encapsulation techniques drastically improve the electron mobility of graphene samples and enables one to measure intrinsic features of the transport property of graphene7. In high-mobility graphene, a large resistance peak appears at the charge neutrality point and resistance decreases monotonically with increasing carrier density7. This would be a natural property of graphene with a single band, such as mono- and bilayer graphene. Although AB-stacked trilayer graphene has a bilayer-like band and a monolayer-like band, the gate voltage dependence of its resistance would be similar to that of the single-band system because the density of states of the bilayer-like band is much larger than that of the monolayer-like band and is dominant7. On the other hand, AB-stacked multilayer graphene with larger number of layers does not necessarily show the above mentioned property because it has more than two bilayer-like bands. In this work, we studied AB-stacked tetralayer graphene, which is the simplest case of multilayer graphene with more than three layers. The band structure of AB-stacked tetralayer graphene is shown schematically in panel i of Fig. Graphene is a material with excellent physical properties—its electrical mobility, for example, much higher than that of organic semiconductors10, does not have a band gap. Bilayer graphene, where electron bands have massive dispersion relations12, does not have a band gap either. However, it was predicted that a perpendicular electric field forms an energy gap between the bottoms of conduction and valence bands14. The response of AB-stacked graphene’s electronic structure to perpendicular electric fields shows significant layer-number dependence. AB-stacked trilayer graphene, for example, has a bilayer-like band and monolayer-like band. Unlike bilayer graphene, it does not exhibit insulating behavior induced by applying a perpendicular electric field. Its electric resistance instead decreases15. Electronic band structure in AB-stacked tetralayer graphene in the presence of a perpendicular electric field is schematically described in panel ii in Fig. We employed a technique to modify electronic band structure by using perpendicular electric field. The method was originally proposed to create an energy gap in the graphene system. Monolayer graphene, where electrons behave like massless Dirac fermions with linear dispersion relationh-BN16, and onto the top of the stack was transferred a rather thick graphene flake serving as a top gate electrode. This stack of films was formed on a SiO2/Si substrate, where Si is conducting at low temperatures and served as a bottom gate. Encapsulation of graphene by high-quality h-BN flakes drastically increases the electric mobility of graphene. The high-quality and atomically flat surface of the h-BN flakes reduces scattering due to ionized impurity and surface roughness17. Mobility of the graphene which was calculated with μ = 1/nep, was more than 40,000 cm2/VS at the high carrier density regime.In order to detect electronic structure by using a transport experiment, the quality of the graphene should be sufficiently high. Moreover, top and bottom electrodes are required to apply a perpendicular electric field. This requirement was attained by using the AB-stacked tetralayer graphene device shown in Fig. Vbg dependence of resistivity for different top gate voltages Vtg measured at T = 4.2 K. In the trace with Vtg = 0V, a slightly complicated peak structures are discernible near the charge neutrality point. The peak structure showed significant variation as top gate voltages was varied. The most prominent variation is enhancement of the peak, which grows with increasing |Vtg| values and appeared roughly symmetric with respect to Vtg = 0V. The enhancement of the resistance by top gate voltage would be qualitatively understood by formation of a band gap by perpendicular electric fields, as in bilayer graphene14. However, the largest peak of Vbg-dependence of resistivity at Vtg = 0V reached to only approximately 250 ohms, and this value was smaller than that in the preceding study in AB-stacked tetralayer graphene that reported insulating behavior18. This indicates that energy gap in tetralayer graphene encapsulated with h-BN would be considerably small (see the Supplementary Information).Figure Vtg = 0V. As shown in the following discussion, the presence of these peaks is an intrinsic property of AB-stacked tetralayer graphene. In the case of dirty graphene, multiple peaks might be observed because inhomogeneity in the sample or surface contaminations can create locally different electrostatic potentials. However, our samples were encapsulated using a dry process, which ensures clean surfaces. The peaks are reproducibly observed in other samples with the same number of layers. Samples with larger numbers of layers also show different peak structures (see Supplementary Information).Beside the large peak structure there were small peaks as shown in Fig. ntg and nbg, which are induced by top and bottom gate voltage, and were calculated by using calibrated specific capacitance. It is clear that the observed peak in Fig. ntg and nbg, and appeared as resistance ridges. By applying both top and bottom gate voltage, total charge density −entot induced in graphene can be expressed by Ctg and Cbg are top and bottom gate capacitances, respectively. The white broken line a in the figure that passes through nbg = 0 and ntg = 0 is a resistance ridge that connects two large peaks appearing at ntg = ±0.8 × 1012. On this line, graphene is in a condition of charge neutrality and total carrier density estimated from Hall resistance vanishes. Here, carriers induced by the top gate voltage and bottom gate voltage are compensated, i.e., CtgVtg + CbgVbg = 0. The ratio of capacitances, Cbg/Ctg was calculated to be 0.078. Using calibrated specific bottom gate capacitance, Cbg = 108 aF/μm2, Ctg was calculated to be Ctg = 1385 aF/μm2. On the other hand, D⊥ = −e(nbg − ntg) = CtgVtg − CbgVbg is the difference in charge density induced by top and bottom gate voltages and is proportional to the electric flux density in graphene. D⊥ is proportional to the electric field perpendicular to the surface of graphene. At the charge neutrality point, ridge a appears. In addition, other resistance ridges b, c, and d showed different dependence on gate voltages. In particular ridges b and c are not parallel to the line of charge neutrality point (ridge a), and crossed at approximately ntg = ±0.8 × 1012 cm−2.In order to study the peak structure further, we measured resistivity as a function of the top and the bottom gate voltages Fig. . Gate vontot and electric flux density D⊥ as shown in Fig. D⊥ = 0, from which one could infer that the ridge structures originated from the intrinsic property of graphene. In particular, ridges b and c overlap at D⊥ = 0, forming a single peak. These ridges possibly originated from bottoms of a conduction band and a valence band of light-mass bilayer-like band. At D⊥ = 0, the conduction band and valence band of the light-mass bilayer-like band contact at their bottoms .In order to inspect the nature of the ridges, we replot it as a function of T = 4.2 K. The structure of Landau levels revealed the nature of the resistance ridges at zero magnetic field. Figure Rxx as a function of ntot and B. Here Vtg and Vbg were varied so that the condition D⊥ = 0 was satisfied. Figure 19. Next, we focus on zero-mode Landau levels that appear near the bottoms of bands, and energy gap appearing in the vicinity of charge neutrality points. Arrows β and γ, which grow vertically with increasing magnetic field, are zero-mode Landau levels of the light-mass and the heavy-mass bilayer-like band. These zero-mode Landau levels generally appear at the bottoms of bands in the Dirac fermions9. Analysis of filling factor ν of energy gaps associated with the Landau level crossing indicated that the zero-mode Landau levels have a degeneracy of eight, which is a hallmark of bilayer-like bands.Energy band structure can be directly probed by quantum oscillation measurement in magnetic fields at ntot with those of zero-mode Landau levels. Because zero-mode Landau level is formed near the bottoms of the bands, ntot at which the zero-mode Landau level appears would be a measure of ntot for the bottoms of the bands at zero magnetic field. For D⊥ = 0, the zero-mode Landau level β of light mass bilayer-like band appeared at approximately the same ntot as the crossing point of the ridges b and c in the lower panel in Fig. γ for heavy mass bilayer-like band appeared on ridge d in the vicinity of D⊥ = 0.Now we discuss the relationship between the fan diagram and the ridge structure at zero magnetic field. Ridge structures appear approximately the same values of D⊥ = -2.7 × 10−7 and +2.7 × 10−7 cm−2 sA, respectively. Values of D⊥ are indicated by arrows in lower panels. It is clear that zero-mode Landau level β in Fig. β1 and β2 with four-fold degeneracy. . The zero-mode Landau levels β1 and β2, appeared at approximately the same ntot of that for ridges b and c in zero magnetic field (yellow points). As for the heavy-mass bilayer-like band, splitting is not clearly observed in the fan diagram. However ridge structures similar to a and b are actually observed for heavy mass bilayer-like band in measurement of wider area using a different sample (see the Supplementary Information).A similar correspondence can be found in the case of non-vanishing vertical electric field. Figure B > 0.5 T, there was an energy gap at around ntot = 0 (indicated with arrow α). This indicates that carrier density is considerably small in zero magnetic field. The ridge d in Fig. D⊥| > ± 0.8 × 10−7 cm−2 sA.Ridge a, on the other hand, is not relevant to zero-mode Landau levels. As seen in Fig. ntot and D⊥. Upper panel in Fig. B = 3.3 T. The derivative of longitudinal resistance with respect to total carrier density ntot (dRxx/dntot) is shown to enhance visibility. The step-like structure indicated by β2 corresponds to zero-mode Landau level β2 in Fig. β2 split. Zero-mode Landau level β1 also split into two levels. By comparing with lower panel in Fig. β1 and β2 follow the ridge structure b and c. This clearly indicates that the ridges b and c originate from bottoms of split light-mass bilayer-like band. The step-like feature originates from crossing of zero-mode with other Landau levels with higher indices. For example, a step appearing at D⊥ ≈ −2 × 10−7 cm−2 sA and ntot ≈ 1.3 × 1012 cm−2 is a crossing with the Landau level labeled as δ. On the other hand, the zero-mode Landau level of the heavy-mass bilayer-like band, is not clearly seen in Fig. ntot = −0.4 × 1012 cm−2.The origin of the ridge structure was further checked by detailed measurements of Landau levels as a function of ntot dependences at fixed values of D⊥) at zero magnetic field reflected electronic band structure. Ridges, which appeared not at the charge neutrality point, are closely related to the bottoms of conduction and valence bands. Conductivity of the samples is contributed by the light-mass bilayer-like band and the heavy-mass bilayer-like band, which are naturally expected to have different mobilities. Therefore, in the frame of two-carrier model conductivity σ is expressed bynL and nH are carrier densities of the light-mass bilayer-like band and heavy-mass bilayer-like band, and μL and μH are their mobilities. Total carrier density is sum of nL and nH, i.e., ntot = nL + nH. The values of the mobility may be different because the band masses of the light-mass bilayer-like band and heavy-mass bilayer-like band should be different. In order to discuss resistance peak structure (or conductance dip structure), one needs to assume ntot dependence of nL or nH. If we assume a semi-metallic band structure consisting of parabolic bands and assume that μL and μH are constant values, ntot dependence of the conductance is simply given by a polygonal line whose vertices are located at ntot for the bottoms of the bands. This results in discontinuous dσ/dntot at the vertices and generally results in a single dip structure in the conductivity (or a single peak in the resistance). To explain resistance peaks at the bottoms of the bands, the mobility for each band would presumably be dependent on the carrier density. Mobility calculated by using μ = σ/entot generally varies with the carrier density. This phenomenon is widely seen in monolayer and bilayer graphene and results from nature of ionized impurity scattering and screening20. Moreover, mobilities would vary at the bottoms of the bands because the band mass would vary near the bottoms of the band owing to mixing of light-mass and heavy-mass bilayer-like bands which is shown in a band calculation considering full Slonczweski-Weiss-McClure (SWMcC) parameters21 (see the Supplementary Information).As seen in the above, the ridges in the carrier density dependence of resistance . Electronic states near the charge neutrality point in tetralayer graphene is expected to be complicated as compared to graphene with fewer number of layers, and would require further investigation.On the other hand, ridge structure, which was observed at the vicinity of charge neutrality point, would require a bit different explanation. The observed ridge at the charge neutrality point would be related to the report from ref.k = 0. Therefore, bottoms of conduction and valence bands contact at k = 0, and an energy gap does not open23. However if spatial inversion symmetry is broken by the potential due to a perpendicular electric field, an energy gap is allowed to open. This fact could be clearly observed by the crossing of ridges b and c at D⊥ = 0. Simple band calculation indicates that gap magnitude generally differs between light-mass and heavy-mass bilayer-like bands, as was observed in the experiment (see Supplementary Information).In case of even-layer graphene, spatial inversion symmetry and time reversal symmetry impose strict conditions on the energy state. A conduction band and a valence bands are degenerated at D⊥ = 0, are due to inequivalent quantum states for K and K’ points. Zero-mode Landau level splitting due to a perpendicular electric field is a result of breaking of spatial inversion symmetry. Moreover Landau level calculation based on effective mass approximation indicated that the splitting is due to the valley-splitting; quantum states for K and K’ points are no longer equivalent, and the zero-mode Landau levels show large valley splitting while those levels with larger indices show smaller valley-splitting, which is consistent with our observation.The broken spatial symmetry caused by the perpendicular electric field is also relevant to the valley splitting of the zero-mode Landau levels. At zero magnetic field, spatial inversion symmetry results in degenerate quantum states for K and K’ points in reciprocal lattice space. Quantum states at K and K’ points are also degenerated in magnetic fields. The eight-fold degenerated zero-mode Landau levels, which were observed in present experiment for 24 (see the Supplementary Information).In AB-stacked tetralayer graphene samples with a single gate electrode, the valley split zero-mode Landau levels with degeneracy of four or less are always observed rather than eight-fold degenerate Landau levels even though a perpendicular electric field is not intentionally applied by using top and bottom electrodes. This is because spatial inversion symmetry is broken owing to the electrostatic potential due to gate induced charges which screens gate electric fieldsVg dependence of resistance at zero magnetic field would be a general property of multilayer graphene with four or more layers. In six-layer graphene we found ridge structures similar to those in Fig. The multiple-peak structure in h-BN flakes and have top and bottom gate electrodes. We found that, at zero magnetic field, the top and bottom gate voltage dependence of resistance shows non-trivial ridge structures which stem from band structures. By analyzing Landau fan diagrams, positions of some ridge structures were verified to correspond to those of the zero-mode Landau levels of bilayer-like bands. They are eight-fold degenerated at zero perpendicular electric field while they split into two four-fold degenerated levels in presence of perpendicular electric field. Correspondingly, the ridge structures crossed at zero electric field. On the other hand resistance increased by applying perpendicular electric field at the charge neutrality point at zero magnetic field, however, strong insulating behavior was not observed. In AB-stacked six-layer graphene we also found similar ridge structures. The ridges that appear in the top and bottom gate voltage dependence would be a common feature of multilayer graphene with number of layers larger than three.We have studied transport property of AB-stacked tetralayer graphene samples which are encapsulated with h-BN flakes. The top gate was several-layer graphene that was deposited on top of the encapsulated graphene. Each sample was patterned into a Hall bar using standard electron beam lithography. Electric resistance was measured using the standard lock-in technique with a low-frequency excitation current whose frequency and amplitude were typically 10 Hz and 1 μA. Magnetic fields were applied by using a superconducting solenoid. Transport measurements were performed at temperature of 4.2 K.Graphene was prepared by mechanically exfoliating high-quality Kish graphite using adhesive tape. Graphene was encapsulated with high quality Supplementary Information


Electrochemical measurements confirmed the higher conductivity of DGP over graphene prepared by chemical method due to lack of structural defects. Its perfect structure facilitates the mobility of charge carriers that makes it preferable in optoelectronic applications.Graphene (G) is a newcomer material that holds promising properties for many applications. The production of high quality G with a good yield is a long-standing goal for many researchers. This work emphasizes synthesis of dispersed graphene nanoplatelets (DGP) through aqueous dispersion technique in surfactant/water solution with the aid of tip sonication. A chemical method was also used to prepare graphene oxide (GO) and reduced graphene oxide (RGO) for comparison. Elemental analysis revealed the C:O ratio to be 12:1 for DGP but much lower for other graphene structures. Optical characterization of DGP, GO and RGO with UV and Raman spectroscopy confirmed the ideal structure of DGP. Moreover, X-ray diffraction (XRD) revealed the amorphous structure of DGP. Transmission electron microscope (TEM) imaging showed that DGP was composed of a few flat layers, unlike the wrinkled and partially bent multilayered G. Topological study of the DGP surface with scanning electron microscope (SEM) depicted its rough surface with (r Modified glassy carbon electrode, Pt wire, and Ag/AgCl served as the working, auxiliary, and reference electrodes, respectively. Typically, 1 mg of solid material was dispersed in 1 mL double distilled water and then 10 µL of Nafion solution was added. The working electrode was prepared by adding a 10 µL droplet of the prepared solution on the surface of the glassy carbon electrode and left to dry under vacuum for 30 min. Then, it was installed in the electrochemical cell. The electrical conductivities of the obtained graphene platelets were calculated from cyclic voltammetry in terms of µF.s/V units according to the following steps:Scanning electron microscopy (SEM) measurements were obtained using a Zeiss SEM Ultra 60 field emission scanning electron microscope (FESEM), Königsallee 9-2137081 Göttingen (Germany). Elemental analysis was obtained from Vario El-Elementar, IRMS-North (Germany). The spectra of the prepared samples were collected at laser wavelength 532 nm and laser power 0.10 MW at 25 °C using Raman Spectroscopy, Bruker Optics, Rudolf-Plank-Str. 2776275 Ettlingen (Germany). AFM images were captured on Dimension 3100 . Samples for AFM imaging were prepared by spin coating ten layers of G colloidal suspension (0.5 wt % in dimethylforamide) on clean glass slides , Mainland (China). The sample powder was compressed well between two copper plates separated by a round hollow Teflon cylinder, and then connected to the electrical cell. The values were calculated from Equation (2):2NH2) was added to GO solution (1 wt. %) and heated in the domestic microwave (1000 W for 3 min) to perform the reduction process. Finally, the formed graphene flakes were separated and washed well then dried at 80 °C overnight.The production of reduced graphene nanosheets via Hummer method involved two subsequent steps, oxidation of graphite followed by reduction of graphene oxide. The typical procedure was to stir 15 g of graphite powder in solution of 7.5 g sodium nitrate dissolved in 230 mL of concentrated sulfuric acid, and the temperature was decreased to 0 °C. Then, 45 g of potassium permanganate was slowly added to the mixture and the temperature was allowed to rise to the ambient value. The mixture was left under vigorous stirring for 3 h. Once the reaction was completed, 700 mL of distilled water was added and the temperature was kept at 98 °C. After 20 min of stirring, 2100 mL of hot distilled water was added. Then, 150 mL of hydrogen peroxide was added slowly to the previous solution to avoid effervescence. Finally, the graphite oxide suspension was sonicated for 30 min and then filtered out. The produced GO solid was washed several times with hot distilled water until pH ~7. The resultant brown paste was then collected and dried overnight at 60 °C under vacuum. To prepare reduced graphene oxide, 100 µL of hydrazine hydrate  and D (1350 cm−1) −3/4 solution as an electrolyte. One can observe oxidation peak at 0.0 V and reduction peak at 0.13 V of the DGP. Other modified electrodes showed oxidation peak at 0.01 V and reduction peak at 0.14 V (nearly at the same position as DGP). However, a significant difference in the current values was noticed exhibiting the highest current in DGP. This may be attributed to the perfect structure of DGP with absent of defective sites that hinder the mobility of the charge carriers. As aforementioned, TEM images confirmed the presence of monolayers and multilayers graphene sheets which could improve the electrical conductivity. Hence, the mobility of the electrons along the nanosheets is facilitated and led to increasing in the current. Moreover, the physical interaction between DGP and SDS in the form van der Waal forces did not change the planer structure of the nanosheet. Otherwise, decay in the current would be observed as in the case of RGO and GO. Furthermore, oxidation followed by reduction with hydrazine hydrate usually generates structural defects in the form of carbonyl, ether among others. As discussed before, the reaction of hydrazine with epoxide groups yields nitrogen containing rings [Cyclic voltammetry (CV) was used to investigate the electrochemical properties of DGP compared with other graphene derivatives using drop casting technique onto a glassy carbon electrode. ng rings  that hinwt./wt. of DGP sample within the modified electrode. From the cyclic voltammetry, the values of electrical conductivity were 61, 144 and 48 µF·s/V for 1, 2 and 3 mg wt./wt., respectively. Thus, the optimum concentration that exhibited the highest electrical conductivity is 2 mg (To select the best electrode, the effect of concentration was studied correlated with electrical conductivity using 1, 2 and 3 mg  is 2 mg .As the production of the high quality G in good yield is the goal of many researchers, in this context, graphene nanosheets were prepared in aqueous medium using SDS as a surfactant. Characterization of the DGP obtained with elemental analysis and Raman spectroscopy confirmed the high carbon to oxygen ratio and no defects in the form of hydroxyl or carboxyl groups were detected. Successful removal of the surfactant via washing several times was confirmed by FTIR and UV spectra. TEM images revealed mono- and multilayers graphene Nano platelets obtained in aqueous dispersion. Topological investigations with AFM showed the surface roughness of the films deposited on glass substrate, which equals 35 nm. This rough surface is ideal for the solar cells’ electrodes because the incident rays would not suffer any dissipation, which in turn should increase the efficiency of the solar cell. Studying of electrochemical properties using CV revealed the high electrical conductivity of DGP electrode. The DGP surpasses the graphene prepared with the Hummer method in the morphological and the electrochemical properties that makes it preferable in optoelectronic applications. Moreover, the high quality nanosheets obtained can replace ITO as a highly conductive layer forming a glass electrode for photovoltaic.


At room temperature, thermal fluctuations of the graphene lattice induce a rapid magnetic switching between two states with a high and low magnetic moment, indicating that due to the instability of the atomic structure of the vacancy, the associated magnetic moment is thermodynamically unstable. Lowering the temperature can significantly reduce the rate of the switching process and enhance the resident time on the high magnetic state. It stabilizes in the high magnetic state at as low as 30 K. Analyzing the atomic trajectories and the instant electronic structures confirms that these two magnetic states in MD simulations correspond to the magnetic and nonmagnetic states reported in the literatures. Such fluctuations of local magnetic moments are associated with the vertical displacement of the carbon atoms with the unsaturated dangling bond. This study reveals the dynamical correlation between atomic movement and the magnetic switching, and a comprehensive picture of vacancy magnetism in graphene. It has implications in graphene based spintronic devices.The stability of magnetic states is essential for potential spintronic applications. Here we report on the thermal stability of magnetic states of monovacancy graphene using  This magnetic moment originates from the removal of a single carbon atom, which breaks three σ dangling bonds in the graphene plane and a π bond in the perpendicular direction. Two of the σ bonds are saturated due to the Jahn-Teller effect12. The remaining σ dangling bond and the vacancy π band around the Fermi level gives rise to a local magnetic moment of 2 µB. Because of the antiferromagnetic coupling between the vacancy states through the itinerant π bands, the magnetic moments are less than 2 µB, usually 1.0 ~ 1.7 μB depending on the vacancy concentration18.Vacancy induced magnetism in graphene has attracted great attention in recent years due to its potential applications in spintronics and the fundamental interests in magnetic manipulations at nanoscale. While the pristine graphene is nonmagnetic, vacancies are known to carry a magnetic moment and have been intensively investigated over the past few years19. This nonmagnetic state has almost degenerate energy with the magnetic one but differs slightly in the geometric structure. For example, P. O. Lehtinen et al. pointed out that the nonmagnetic state was 0.1 eV higher in energy than the magnetic state, and the displacement of the dangling bond was 0.46 Å out of the graphene plane19. This conclusion was also supported by B. R. K. Nanda and coauthors, who obtained a flat structure with the magnetic moment of 1.5 µB and a deformed structure with a magnetic moment of 0.06 µB. The two states differ in energy by about 50 meV20. In addition, a Kondo-like state was suggested by C. C. Lee et al. as the ground state21. The inconsistency in the ground state suggests that the spin polarization of monovacancy graphene might be thermodynamically unstable and thus casts doubt on its potential applications. So far, the thermal stability of defect graphene has not been investigated.Although there seems to be a consensus on a magnetic ground state for graphene with a single vacancy, early reports in the literatures were controversial regarding a possible nonmagnetic ground stateab initio molecular dynamics (AIMD) to study the thermodynamic stability of a single-atom vacancy in graphene and its correlation with magnetic properties at different temperatures. We found that magnetic states of monovacancy in graphene at room temperature is unstable, and it jumps between two states with a high and low magnetic moment. These magnetic switches are associated with the thermal fluctuations of the vertical coordinate (h) of the unsaturated carbon atoms close to the vacancy. At lowered temperatures such as 200 and 77 K, the rate of the magnetic switching can be substantially reduced and can be suppressed for a long time at 30 K, where a relatively stable ground state can be reached. Our study reveals the atomistic mechanism of thermal stability of monovacancy magnetism in graphene and has implications to graphene based spintronic devices.Here we perform B) and low (0.5 µB) magnetic moment. Analysis of the atomic trajectories indicates that this magnetic switching is directly correlated with the local geometry fluctuations of the carbon atoms close to the vacancy, although vibration of the whole lattice is observable at this temperature  between atom 1 and graphene plane leads to the magnetic switching directly  and the low magnetic state is a metastable state (Sm) with a higher energy. Only at a low temperature of 30 K, the magnetic switching in monovacancy graphene is suppressed state in the 4.5 ps simulations and the system is stabilized on the high magnetic ground. At the same time, the vibration of the carbon atoms is much damped, and the vertical displacement h stays smaller than 0.3 Å as shown in movie Lowering the temperature to 200 and 77 K, the thermal fluctuations are suppressed, yet the switching between two magnetic states still persists at a lower rate. As shown in Fig. Sg and Sm can be deduced from the statistical residence time on the two states and the Arrhenius law for the transition rate across a barrier. The residence times on the two states at different temperatures are tabulated in Table T1 and T2, the potential barrier (Eb) can be deduced by,kB is the Boltzmann Constant, t1 and t2 are the average residence time on the same state at temperature T1 and T2, respectively. Using the average residence time on the ground state t1 = 98 fs and t2 = 177 fs at T1 = 300 and T2 = 200 K, the energy barrier from Sg to Sm is found to be 30.5 meV. Similarly, the energy barrier for the reverse process from Sm to Sg, is 19.2 meV, with t′1 = 80 fs and t′2 = 116 fs on the metastable state at T1 = 300 and T2 = 200 K, respectively. From these two barriers, the energy difference between state 1 and 2 can be determined, which is 11.3 meV as schematically shown in the insert of Fig. The energy barrier between h at different heights while fully relaxing all other atomic coordinates in the 6 × 6 and the 8 × 8 graphene supercell. Figure h. Clearly, a jump of the magnetic moment occurs at h = 0.3 Å for both set of calculations. Although the value of the magnetic moments changes slightly with the supercell, it confirms that the transition between the high and low magnetic states is present and occurs at about h = 0.3 Å. This conclusion is consistent with the results of the AIMD simulations. In addition, the small difference of magnetic moments is due to the sizes of the two supercells, which is in agreement with the previous works18.To further reveal the correlation between the local structures and the magnetic switching, we have done a series of static calculations by suspending the vertical displacement 2v → C2 symmetry transformation in association with the vertical deformation around the vacancy defect. The C2v symmetry of the magnetic ground state implies that the wave functions of the σ and the π vacancy states are orthogonal in space and do not hybridize. The two states can thus attain parallel spins according Hund’s rule of maximum multiplicity of spin occupation for independent orbitals, giving rise to the high magnetic state. In practice, the unsaturated σ state contributes to 1 µB as shown in Fig. B due to the antiferromagnetic coupling between vacancies at finite concentration. When atoms near the vacancy are deformed out of the plane by either thermal fluctuation or shear distortion22, the σ and π vacancy bands are no longer orthogonal and become hybridized, which can be clearly seen in their energy dispersion as shown in Fig. The origin of the magnetic switching results from the inversion symmetry breaking in the monovacancy graphene, which undergoes a Cab initio MD study on the thermodynamic stability of a single-atom vacancy in graphene. At room temperature, the magnetic states of monovacancy graphene is thermally unstable. This instability originates from the inversion symmetry breaking associated with local atomic fluctuations perpendicular to the graphene plane. It is found that lowering temperature to 30 K can stabilize the system in the high magnetic state. This theoretical study provides dynamic insight into thermal stability of the magnetic states of monovacancy graphene. It also hints possible ways to control the graphene magnetism by symmetry conservation and thus has implications in spintronic applications.We present an ab initio MD calculations are performed using the Vienna ab initio Simulation Package (VASP)23 based on density functional theory. It employs the projector augmented-wave (PAW)25 pseudopotentials and the general gradient approximation (GGA)26 in Perdew-Burke-Ernzerholf form27 for exchange-correlation energy. Spin polarization is included in all calculations. An energy cutoff of 600 eV is used for wave function expansion. The periodic supercells contain a vacuum layer of ~ 20 Å and all atoms are allowed to relax until the forces on each atom are less than 0.01 eV/Å. In the ground state, the C-C bond length is obtained to be 1.424 Å for the pristine graphene and is in agreement with the experimental value of 1.42 Å. The 6 × 6 supercell of graphene is used in the MD simulations with a time step of 1 fs and 3 × 3 × 1 k-sampling. The geometrical structure, electronic and magnetic properties of the MD snapshots of the single vacancy in graphene are compared with static 6 × 6 and 8 × 8 supercells with a finer grid of k-point sampling to check and assure the convergence of the simulations.Our Supplementary InformationSupplementary Movie 1Supplementary Movie 2


With further engineering, the semiconductor-graphene-semiconductor transistor is expected to be one of the most promising devices for ultra-high frequency operation.Graphene-base transistors have been proposed for high-frequency applications because of the negligible base transit time induced by the atomic thickness of graphene. However, generally used tunnel emitters suffer from high emitter potential-barrier-height which limits the transistor performance towards terahertz operation. To overcome this issue, a graphene-base heterojunction transistor has been proposed theoretically where the graphene base is sandwiched by silicon layers. Here we demonstrate a vertical silicon-graphene-germanium transistor where a Schottky emitter constructed by single-crystal silicon and single-layer graphene is achieved. Such Schottky emitter shows a current of 692 A cm Graphene-base transistors were originally proposed for high-frequency applications, but the height of the emitter potential barrier limits the transistor performance towards the THz range. Here, the authors fabricate a vertical silicon-graphene-germanium transistor with a Schottky emitter enabling a transition from MHz to GHz operation. In an n-p-n BJT, a p-type base semiconductor is sandwiched by n-type emitter and collector semiconductors, forming an emitter junction between the emitter and the base, and a collector junction between the base and the collector. During operation, electrons are emitted from the emitter, diffuse through the base, and eventually are collected by the collectorfα, which is used to represent the upper frequency limit when a BJT is biased in the common base mode. fα is inversely proportional to the delay time, which includes the emitter charging time τe, the base transit time τb, and the collector delay time τc5. In the past decades, there has been a persistent demand for higher frequency operation for a BJT, leading to the inventions of new devices, such as heterojunction bipolar transistors and hot electron transistors. The heterojunction bipolar transistors have achieved great development toward the terahertz (THz) operation9, however, their fα is ultimately limited by τb. For the hot electron transistors, when an electron is emitted into the base, the energy difference between the electron and the Fermi energy level (or the bottom of conduction band) of the base is transformed into electron kinetic energy. This makes the electron hot with a high speed and leads to a small τb14. However, the demand of a thin base without pinholes and with a low base resistance usually causes difficulties in material selection and fabrication. Recently, to reduce τb, graphene has been proposed as a base material to form graphene-base transistors15. Because of the atomic thickness, the graphene base is almost transparent to electron transport leading to a negligible τb. At the same time, the remarkably high carrier mobility of graphene will benefit the base resistance compared with a thin bulk material17.For a BJT, a main figure of merit is the alpha cutoff frequency 23. As predicted by simulations, in order to realize THz operation, the emitter potential barrier which is between the emitter metal and the emitter-to-base tunneling layer should be <0.4 eV, which remains an engineering issue25. To solve this problem, pioneering theoretical study on graphene-base heterojunction transistors has been done with a device structure of silicon–graphene–silicon26. Theoretically, THz operation can be realized when the collector current is >106 A cm−2.So far, the proposed graphene-base transistors generally use a tunnel emitter, which emits an electron through an insulator−2 at 5 V, and has a capacitance of 41 nF cm−2. As a result, fα is expected to increase from ~1 MHz by using the previous tunnel emitters to >1 GHz by using the current Schottky emitter. With further engineering, the vertical semiconductor–graphene–semiconductor transistor is expected as one of the most promising devices for ultra-high-frequency operation in future 3D monolithic integration, because it combines the merits of the atomic thickness and high carrier mobility of graphene, and the high feasibility of a Schottky emitter.Here, we demonstrate a vertical silicon–graphene–germanium (Si–Gr–Ge) transistor. The Si–Gr Schottky emitter carries a current of 692 A cm33. Three materials are directly stacked, including an n-type top single-crystal Si membrane, a middle single-layer graphene, and an n-type bottom Ge substrate (see the Methods section). An optical image of a fabricated Si–Gr–Ge transistor is shown in Fig. Vbe applied to the emitter junction , electrons are emitted from the emitter, go through the emitter junction with a barrier height qϕ1, the graphene base, then the collector junction with a lower barrier height qϕ2, and eventually are collected by the collector.Figure 6 at ±5 V. Obvious rectifying behavior indicates the formation of a Schottky barrier. Note that the Ohmic contact between the Au electrode and top Si is formed ], where τe is a dominating factor  and the one using the Schottky emitter (up to 1.2 GHz).For the Si–Gr emitter, Ie is emitted from the Si–Gr emitter, and part of it /Ie and Ileak = Ic (Ve = 0). Figure Ie increases, Ic increases accordingly, indicating a successful collection of part of the emitted electrons  is used. This results in a much-increased electrical field at the collector junction  of the transistor is possible  and LOR7A  were used in sequence. The top Si layer was patterned into ~26 × 26 μm2 squares by reactive ion etching (RIE) with the following parameters: CF4: O2 = 25 sccm: 5 sccm, 13.3 Pa, RF power = 100 W, for 10 min. The height of the Si membrane was more than 800 nm as measured by an atomic force microscopy (AFM) , leaving the patterned top Si membranes onto the bottom Si substrate.A silicon-on-insulator (SOI) substrate with a 2-μm-thick top single-crystal Si layer (resistivity: ~4.5 Ω cm), and a 1-μm-thick buried SiO27, the PDMS was placed on the bottom Si substrate with the Si membrane, and peeled away quickly at a rate >10 cm s−1. To release the Si membrane27, the PDMS with the Si membrane was placed on the target substrate, and peeled away slowly at a rate <1 cm s−1.For transfer of the Si membrane, PDMS was used as a medium to transfer the top Si membrane onto the target substrate. The PDMS was first prepared by stirring a mixed solution of PDMS and its curing agent (10: 1 in weight) and baking at 65 °C for 6 h. To retrieve the Si membrane2 piece of Pt foil  was rinsed with DI water, acetone, and ethanol in sequence for 1 h each, loaded into a quartz holder inside the fused silica tube (inner diameter: 22 mm) of a tube furnace , and then annealed at 1000 °C for 10 min to remove residual carbon or organic substances under a hydrogen atmosphere. Growth was then initiated and maintained for 40 min under a mixture of CH4 (4.5 sccm) and H2 (500 sccm) at 1000 °C. Finally, the Pt foil was quickly pulled out of the high-temperature zone, and the CH4 flow was turned off when the furnace temperature was below 800 °C31.A 20 × 10 mm31.For bubbling transfer of the graphene film, a Pt substrate with the grown graphene was spin-coated with PMMA  at 2000 r.p.m. for 60 s, and then cured at 180 °C for 15 min. A constant current of 0.2 A was applied to separate the PMMA/graphene layer from the Pt foil in a 1 M NaOH aqueous solution. The PMMA/graphene films were then collected on the target substrates, and finally acetone was used to remove the PMMA at 50 °C2O3 insulator layer was deposited on top of an n-type Ge substrate  by atomic layer deposition (ALD) at 150 °C  and water). Au electrode was formed on the top of Al2O3. The bottom of the Ge substrate was scratched, and Au metallization was performed to form an Ohmic contact. The Al2O3 layer was patterned by photolithography and etching with dilute HF (5 wt%) for 3 min, leaving an ~60 × 60 μm2 window to the Ge substrate.A 30-nm-thick Al2 plasma etching .Single-layer graphene and Si membranes were fabricated and transferred to the Ge substrate one after the other. The graphene was patterned to ensure isolation of each device by photolithography and OThe fabricated devices were characterized using an optical microscope (Nikon LV100ND), an SEM (FEI XL30 SFEG using an accelerating voltage of 10 kV), and an AFM (Bruker Dimension Icon AFM). The electrical performance of the transistors was measured using a semiconductor analyzer (Agilent B1500A with a capacitance measurement unit B1500A-A20) and a probe station (Cascade Microtech Inc. 150-PK-PROMOTION) under ambient conditions, and a vacuum probe station (Lake Shore TTPX/TSM1D1001) under low-temperature conditions. About 10–30 working transistors were successfully fabricated and characterized for each wafer with a yield of 10–30% (Supplementary Fig. Supplementary InformationPeer Review File


We have previously described that the blockage of both matBDNF and proBDNF signaling reduces neuronal death after SE in vivo  are secretory proteins that bind to target receptors and influence many cellular functions, such as cell survival and cell death in neurons. The mammalian NT brain-derived neurotrophic factor (matBDNF) is the C-terminal mature form released by cleavage from the proBDNF precursor. The binding of matBDNF to the tyrosine kinase receptor B (TrkB) activates different signaling cascades and leads to neuron survival and plasticity, while the interaction of proBDNF with the p75 NT receptor (p75NTR)/sortilin receptor complex has been highly involved in apoptosis. Many studies have demonstrated that prolonged seizures such as  On the other hand, proBDNF can be secreted and it can mediate apoptosis through its interaction with a dual receptor system composed of p75NTR and the type I transmembrane protein sortilin  brain-derived neurotrophic factor (matBDNF) plays an important role in neuronal differentiation and survival. matBDNF is initially synthesized as proBDNF and is released as a mature form through cleavage by furin or metalloproteinases , which in turn results in cell death in several areas of the brain  and their receptors  were followed. The animal model protocol used for this research was approved by the IIByT Animal Care and Use Committee, Resolution #1/2015. Care was taken to minimize the number of animals used per experiment as well as their suffering.Adult male 2–22, in 35 mm plastic dishes coated with 0.1 mg/ml poly-L-lysine. The second day after plating, 10 μM Ara C was added to the culture to avoid growth of glial cells. Cultures were maintained 10–12 DIV at 37°C in a 95% air/5% CO2 atmosphere, and were fed twice a week with maintenance medium.Primary cultures of embryonic day18 (E18) rat hippocampal neurons were prepared as described by Kaech and Banker , with mi2 poly-D-lysine-coated flasks with growth medium containing DMEM + 10% FBS + 0.5% Penicillin/Streptomycin. The glial mixed culture was grown to confluence (7–10 DIV) and non-astrocyte cells were removed by shaking the bottles containing the culture in an orbital shaker at 37°C , pH 7.3. SE was induced during 3 h, after which, medium was changed to maintenance medium to stop the insult. matBDNF scavenger, TrkB-Fc  was added to the cell culture immediately after SE termination, as indicated in the results section. The concentration of TrkB-Fc was chosen based on previous reports . Implantation was performed at the following Paxinos and Watson  stereotaSE was induced by an intraperitoneal injection of 3 meq/kg lithium chloride and 12–16 h later was follow by an injection of 40 mg/kg pilocarpine hydrochloride . Two hours after the onset of SE, 10 mg/kg diazepam  was injected intraperitoneally to stop seizure activity. To determine the onset of SE, animals were closely monitored, and seizure activity was assessed based on the previously described correlation between electrophysiological measures and observed seizures  were infused according to Vaynman et al.  in serial histological sections as described in Unsain et al. , since the loss of NeuN labeling is explained by neuronal death  followed by 4% paraformaldehyde  in phosphate buffered saline (PBS) solution. After perfusion, brains were post-fixed in 4% PFA for 1 h, then cryoprotected in 30% sucrose at 4°C for 3 days before their sectioning. Neuronal degeneration after pilocarpine-induced SE in vivo was assessed by Fluoro-Jade B (FJB) staining  as previously reported . The degree of injury in the hippocampus of the ipsilateral hemisphere was quantitatively compared to the degree observed in the hippocampus of the contralateral (control) hemisphere within each section. In vivo, the percentage of FJB-positive neurons was calculated according to Unsain et al.  inverted microscope. In each brain section, square fields were analyzed in the hilus (neurons within the polymorphic layer of the dentate gyrus), and in the CA1 , rabbit polyclonal anti-BDNF , or rabbit polyclonal anti-proBDNF  were used as primary antibodies and anti-rabbit HRP conjugated was used as secondary antibody . Anti-proBDNF does not cross react with mature BDNF as determined by the manufacturer’s specifications and by our own analysis . After centrifugation, the pre-cleared supernatants were incubated with 2 μg anti-proBDNF antibody  or 2 μg TrkB-Fc at 4°C overnight. Then, 12 μl of Protein A/G PLUS-Agarose was added. Immunoprecipitates were washed three times with ice-cold modified RIPA buffer before elution in SDS sample buffer. Samples were analyzed by Western blot using rabbit anti-p75NTR primary antibody , rabbit anti-TrkB primary antibody , rabbit anti-BDNF  or rabbit anti-proBDNF . Membranes were incubated with a rabbit secondary antibody before incubation with the primary rabbit antibody, as IgG loading control.post hoc test. For quantification of NeuN-positive cells and FJB-positive cells, a Nested ANOVA test was used. p values < 0.05 were considered statistically significant.Quantitative data are presented as mean ± SEM. The relative protein level between groups was analyzed by One-way ANOVA or Two-way ANOVA followed by Tukey in vitro model of SE . Considering that an in vitro proBDNF/p75NTR interaction increase 6 h post-SE .Astrocytes regulate several neuronal functions and provide proBDNF clearing and recycling in order to release BDNF , sequestering of matBDNF induces an increase in post-SE neuronal death. This phenomenon could be explained due to an imbalance between matBDNF/TrkB signaling and proBDNF/p75NTR signaling.In summary, in both In vitro treatment of hippocampal neurons with 100 ng/ml proBDNF reduced neuronal survival by approximately 50%, shown by a decrease in the NeuN staining in neurons in p = 0.024), supporting the idea that TrkB signaling is necessary to prevent proBDNF-induced neuronal death.In order to confirm the role of proBDNF in SE-induced neuronal death, pure hippocampal neurons were incubated with exogenous proBDNF, matBDNF or both at the same time and the neuronal death after 24 h was determined. Although we do not rule out the possibility that these NT are released by neurons under basal conditions, several studies had demonstrated that there is no secretion of matBDNF or proBDNF unless they receive a depolarizing stimulus  increased in the hippocampal CA1 at a similar level in both hemispheres in animals infused with vehicle. No neuronal damage was induced by TrkB-Fc alone in control animals . On the contrary, a four-fold increase in neuronal death was shown in response to post-SE infusion of TrkB-Fc compared to the contralateral vehicle-infused hippocampus (t-test *p = 0.0130). The effect of the infusion of TrkB-Fc after SE on neuronal death did not extent to the hilus of the dentate gyrus since the number of degenerating neurons was similar in the hilus of both hippocampi . These results support the idea that the marked increase in matBDNF that occurs after SE results in TrkB-fl downregulation.Since sequestering extracellular matBDNF p = 0.0017), indicating that TrkB signaling is attenuated in the injured hippocampus.TrkB-fl is activated by phosphorylation after matBDNF binding. Then, the levels of phosphorylated TrkB (p-TrkB) were determined in the rat hippocampus after SE in control and TrkB-Fc infused animals. We found a 30% decrease in pTrkB levels, in both hemispheres after SE .in vivo together with an antibody that only recognizes proBDNF (anti-proBDNF) immediately after seizures. Twenty-four hours later, neuronal survival was analyzed in ipsilateral and contralateral hippocampi by Fluro-Jade B. We found that, not only the administration of anti-proBDNF abolished TrkB-Fc-induced neuronal death, but it also reduced the level of neuronal death triggered by SE (p < 0.0001), suggesting that proBDNF plays an important role in mediating neurodegeneration after SE.Considering these results, it was then determined whether proBDNF potentiates the SE-induced neuronal death in the absence of matBDNF. TrkB-Fc was infused in vitro and in vivo, that proBDNF signaling through p75NTR exacerbated the SE-induced neuronal death in absence of matBDNF/TrkB signaling.NT elicit a paradoxical effect on neurons, since they can induce either neuronal survival or death, depending on which receptor and signaling pathways are activated. Our previous work revealed an intricate regulation of matBDNF and proBDNF in excitotoxicity that also involved the downregulation of TrkB and the upregulation of p75NTR (Unsain et al., matBDNF is known to promote neuronal survival, differentiation, and synaptic plasticity, although in intact mature neurons the endogenous matBDNF is not needed for survival (Shulga et al., Neurons may also secrete proBDNF, the immature form of BDNF and our results, together with those from other groups, demonstrate that proBDNF levels increase under pathological conditions such as SE (Unsain et al., via TrkB-Fc to demonstrate the role of proBDNF in neurodegeneration. TrkB-Fc is a BDNF scavenger unable to enter the cells, thus it will solely sequester the extracellular matBDNF. The intracerebral infusion of TrkB-Fc had been previously used to inhibit the development of kindling and it was probed to inhibit TrkB activation (Binder et al., in vitro and in vivo, that the scavenging of matBDNF post-SE increases neuronal death. In addition, we demonstrated that overproduction of matBDNF after SE is the sole trigger of post-SE TrkB downregulation, since withdrawing this NT restores TrkB level in the hippocampus.We have previously shown that matBDNF and proBDNF facilitate neuronal death after SE (Unsain et al., It has been demonstrated that the constitutive release of matBDNF and proBDNF to the extracellular space is low in basal conditions (Goodman et al., ProNTs have been shown to contribute to neuronal death by signaling through p75NTR and sortilin receptors (Lee et al., in vitro caused a significant neuronal lost at 12 h post-SE (Danelon et al., in vitro, although the mechanisms involved in neuroprotection are still a matter of study. In relation to this result, it has been shown that proNGF and proBDNF expression (Volosin et al., via p75NTR during excitotoxic insults and, at the same time, they may release several trophic factors (Bergami et al., Astrocytes play an important role during normal development as well as during an injury (Liddelow and Barres, in vivo axotomy model in which neuronal death occurs after 1–3 days post-injury (Harrington et al., The SE severely damages the hippocampus causing neurodegeneration in several hippocampal subareas. The temporal sequence of neuronal death differs among them, and it is also affected by the model used to induce SE, even by the doses of pilocarpine used (Fujikawa, Contrarily to the effect observed in the CA1, further death in the hilus after the infusion of TrkB-Fc was not observed. The hippocampal hilus is more vulnerable to the SE than CA1 and, in fact, the neuronal death occurs immediately after SE (Fujikawa, in vivo model of SE, the hippocampus is severely damaged, and in CA1, neuronal death occurs 24 h after seizures. In this study, we proposed that the exacerbated release of matBDNF after the SE insult could be a neuronal survival mechanism, since the matBDNF signal may serve to counteract the pro-apoptotic signals triggered by proBDNF/p75NTR. Our data shows that when the matBDNF/TrkB signaling decreases as a result of a matBDNF scavenger’s activity, the proBDNF/p75NTR becomes the predominant—pro-apoptotic—active pathway.As described in Unsain et al.  in the iOur results strongly support the idea that the lack of balance in neurotrophic receptors under neurodegenerative conditions may determine the fate of neurons, and that, even in the presence of pro-NT, matBDNF/TrkB signaling plays a key role in neuronal survival.All authors were responsible for the design of the study. LM and VD performed the experiments and analyzed the data. LM conducted statistical data analysis. VD and AC performed cell culture. The manuscript was drafted by LM. All authors critically reviewed the content and approved the final version for publication. DM supervised the project and conceived the original idea.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The design and execution of measurement in quality improvement (QI) initiatives is often poor. Better guidance on “what good looks like” might help to mitigate some of the problems. We report a consensus-building process that sought to identify which features are important to include in QI measurement plans.We conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusion based on literature review and the study team’s experience; (2) a two-round modified Delphi exercise with a panel of experts to establish consensus on the importance of these features; and (3) a small in-person consensus group meeting to finalise the list of features.A list of 104 candidate questions was generated. A panel of 19 experts in the Delphi reviewed these questions and produced consensus on retaining 46 questions in the first round and on a further 22 in the second round. Thematic analysis of open text responses from the panellists suggested a number of areas of debate that were explicitly considered by the consensus group. The exercise yielded 74 questions (71% of 104) on which there was consensus in five categories of measurement relating to: design, data collection and management, analysis, action, and embedding.This study offers a consensus-based view on the features of a good measurement plan for a QI project in healthcare. The results may be of use to QI teams, funders and evaluators, but are likely to require further development and testing to ensure feasibility and usefulness. Given iroaches, , 5, the roaches, –8.Current practice in measurement for improvement compares unfavourably with clinical trials, where high-quality measurement is recognised as a priority and accordingly is expertly led, is well-resourced, and has clear protocols for data collection. By contrast, QI teams often  may seem to lack capability and capacity to plan and conduct appropriate measurement: , 9 they We propose that it is possible to mitigate some of the problems associated with measurement for improvement through meticulous and well-informed planning. The production of a written measurement plan is analogous to a research protocol: it allows QI teams to develop and communicate intentions and reach a shared understanding of how the impact of a QI initiative will be measured. This is critical, because the choices made at the planning stage (conscious or otherwise) have long-lasting implications. For example, if a team does not plan to establish baseline levels of variables, it risks not being able to evaluate the outcome of the initiative objectively.What a QI measurement plan should include, however, has not been systematically established: little research has focused on the standards that should apply to planning for measurement for improvement. The available resources are predominantly textbooks and guides developed by organisations that support or fund QI teams. Examples include Health Quality Ontario’s Measurement Plan Tool, a checklist focusing on the data collection process ; NHS ScoIn this article, we aim to address the void in guidance on planning measurement for improvement by reporting a consensus-building process to identify which features are important to include in a QI measurement plan. We do not seek to establish standards for measurement, but instead to identify the features that might benefit from standards being set, with the aim of supporting planning and review.Guided by a Steering Group , we conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusion on the basis of importance (September 2015–February 2016); (2) conduct of a modified Delphi exercise (March–May 2016); and (3) an in-person consensus group meeting to finalise the list of features (8 December 2016).We generated a list of possible candidate features that could be entered into the modified Delphi study. We drew on two sources to do this.First, we reviewed the existing literature on good (and bad) practice in measurement for improvement, including both peer-reviewed and grey literature. We started with articles recommended by members of the steering group, and then checked the reference list of these articles to identify other relevant articles. We read the articles and evaluation reports, identifying features that were mentioned either as good practice, or as mistakes or pitfalls. We added articles cited by the initial list, until this ceased to yield further candidate features. The final list of articles reviewed comprised 22 journal articles , 14–32 aSecond, we drew on the experience of the core study team  who have supported over 50 QI initiatives over 7 years as part of the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (CLAHRC), Northwest London programme. We drew in particular on knowledge and experience of the challenges that teams encounter in seeking to do measurement, and of the CLAHRC’s measurement planning process, which was developed to support QI teams .Consistent with the vision outlined by Berenholtz et al.  of produA modified Delphi technique , 49 was The inclusion criteria for the panel of experts invited to take part in the study were: experience of measurement planning for healthcare QI initiative(s) or specialist expertise and authority or influence in the science of improvement. Authors of this article and colleagues in the NIHR CLAHRC for Northwest London were excluded from this stage. Potential panellists were suggested by the steering group and core study team and were invited by email to take part in the study and asked to consent to participation. We asked these potential panellists to suggest others who they considered suitable to participate, who we then invited in addition, provided they met the inclusion criteria. We used Qualtrics survey software (version 1.5) to create and administer the questionnaires. We aimed to achieve a panel of 11–30 members, sample sizes in this range are typical for the Delphi method and have been shown to be effective and reliable , 50.Round 1 of our modified Delphi used a structured questionnaire comprising the candidate questions identified in stage 1. Panellists were shown each of the candidate questions alongside the explanatory text. They were then asked to vote to keep, remove, or modify the question, or to state that they had no opinion. We used categorical response options to ensure that panellists were clear about the consequences of their votes, to make interpretation clear, and to ensure that the results were actionable in terms of establishing a final list of questions at the end of the study.For each candidate question, panellists were given the option to provide free-text comments to support their decision, or to suggest changes to the question. We also asked panellists to give their opinion on the overall structure and completeness of the list of questions. We conducted a simple thematic analysis of free-text responses to these open-ended questions by manually searching, reviewing, defining, and naming themes .Consensus was set a priori at 75% agreement with any one of the available actions , consistent with previous Delphi studies reported in the literature . ResponsWe asked panellists to review the aggregated agreement percentages for each question as part of the round 2 questionnaire, alongside their previous individual ratings and a summary of the panel’s comments from round 1. We then asked them to reconsider their rating using the same categories as in round 1. At the end of round 2 of the Delphi study, the analysis and feedback process was repeated.Thus the output of the questionnaire stage was three sets of questions: a set to retain by consensus, a set to remove by consensus, and a set with no consensus to retain or to remove.review and resolve proposals for questions that did not reach consensus through the questionnaire rounds, drawing on panellists’ responses from stage 2address themes emerging from the Delphi panel’s free-text responses on the overall structure and completeness of the list of questions.To decide what to do with the set of questions with no consensus to keep or to remove, we held an in-person meeting of the core study team and the steering group, and we also invited panellists who had completed both rounds of the Delphi study. The aim of this meeting was to finalise the structure and content of the question list. The objectives were to:Based on the results of the Delphi study , the study team proposed to retain or remove each of the remaining questions. The consensus group discussed these proposals in light of the panel voting and comments from stage 2, and accepted or rejected them, allowing the study team to finalise the question list. Any questions that reached consensus in stage 2 were not discussed in stage 3 as panel consensus was considered final.We identified 104 candidate questions as potential features of measurement plans that would be relevant in reviewing strengths and weaknesses  questions. These questions were included in the final content and were not entered into round 2. The remaining 58 questions were amended based on the panel’s comments and suggestions and re-entered into round 2.At the end of round 2, the panel had reached consensus on 24 (41%), agreeing to keep 22 and remove two questions. Thus at the end of stage 2, 70 (67%) of the 104 candidate questions met the predefined 75% agreement level: 68 to keep and two to remove. The number of questions in each subcategory reaching the specified consensus level is shown in Table For the 34 questions with no consensus at the end of stage 2, the core study team proposed to remove 27 questions and keep seven questions based on the Delphi panel’s comments. During the stage 3 in-person consensus meeting, the group  agreed with removal of all 27 questions proposed as meriting removal, and with six of the seven proposals to keep questions – the seventh was deemed to be sufficiently covered by another question. Therefore in this stage six questions were kept and 28 removed.In response to comments from the Delphi panel, the consensus group also made minor revisions to the phrasing of the six questions that were kept. This resulted in the final list of 74 questions  shown in Additional file The consensus group also discussed the themes emerging from the Delphi panel’s free-text responses on the overall structure and completeness of the list of questions, which broadly concerned whether the questions should concern methodological validity or simply transparency; the number of questions; inclusion of general project-level questions; and whether the standards that apply to research measurement should also apply to QI.The Delphi panellists’ free-text responses highlighted some tensions about whether the measurement questions should seek solely to address the transparency of a plan  or should also seek to assess the quality of the approach to measurement. The consensus group concluded that at this stage in the development of the field, it would be difficult to add to the study’s original goal of identifying the important features of a measurement plan to seek additionally to specify the means by which quality of the methods would be assessed, especially given the complexity and context-specificity of this task. For example, decisions about which analytical methods are most appropriate for dealing with missing data depend on factors such as the extent and nature of the missing data, and the relation to other variables in the analysis. Furthermore, the decision as to which approach is optimal may involve knowledge of advanced statistical concepts that may not be readily accessible to clinical teams.The panel raised the issue of the number of questions, noting that while the questions were comprehensive in scope, there were a lot of them taken as a whole. Given that there were already 68 questions according to the pre-defined threshold for consensus, the consensus group was careful to keep only questions deemed essential from the remaining 34 questions under consideration at the consensus meeting.Some panellists commented that some questions could be seen as not specific to measurement, but instead as pertaining to general project issues – e.g. project management or governance. The group agreed to remove any questions not specific to measurement, except those that were essential for subsequent questions to make sense. Each of these more general questions had received some votes to keep, revealing the blurred boundary between measurement and other activities undertaken by QI teams.Some panellists commented that certain questions seemed more appropriate for ‘research’ rather than QI initiatives. The experts in the consensus group commented that while there are valid differences in methodology appropriate for answering different types of questions, the purpose of this study was to help bring to QI the rigor that research work benefits from. For example, in making inferences from a random sample to a fixed population versus understanding whether a change has occurred in a process over time, one would use different statistical methods. In both cases, having a clear definition of the measures used and an understanding of the quality of data against the definitions is important for the integrity of the conclusions drawn from subsequent analysis.This article presents a consensus-building study aimed at identifying the important features of measurement plans for healthcare QI projects. The result is a list of 74 questions that may support QI teams in identifying the features relevant to planning and reviewing transparency and completeness of measurement planning, along with explanations for each feature. It is one of the first formal studies of this area, synthesising the cumulative learning from literature on measurement and experience in the field with the expertise of 19 leaders in the field of measurement for improvement. The findings may be of value to QI teams  and to funders, designers, and evaluators of QI programmes, though they may require further development and evaluation.This study has a number of strengths and limitations. The initial literature search, which formed one source of candidate features for entry into stage 2 of the study, was not a systematic review. It is therefore possible that some potential candidate features present in the literature were missed, and that some candidate features used in the study are not evidenced in the literature. Use of the modified Delphi technique in Stage 2 offered a number of advantages, preserving the anonymity of panellists and allowing unrestricted expression of opinions, and thus helping to reduce the influence of dominant personalities and the effect of panellists’ status on results . It alloFurther research is also needed to understand the relative importance of the questions identified through this study, to allow prioritisation of resources in planning improvement, and to convert the long list of questions we have identified into a practically useful guide for QI teams. Such work might focus on systematic approaches to help teams develop measurement plans that are scientifically valid, practically feasible, and promote successful improvement. This may require, for example, presenting the study findings in a user-friendly format suitable for QI teams, perhaps through development of an interactive guidance and support tool to facilitate adoption of the findings of this study. Such a tool could also provide useful data on which areas of measurement planning are particularly challenging for QI teams, and therefore where systematic support might best be aimed. A prototype tool has been developed , and theExisting checklists and templates to support measurement planning are not comprehensive and none has been developed through a formal expert consensus technique. QI teams may use the results of our study proactively to highlight areas where they need to seek additional expertise, or to develop their plans further. Further work may be needed to refine and test the tool to ensure feasibility and usefulness, and to ensure that QI teams are appropriately supported in developing and reviewing measurement plans.Additional file 1: Appendix 1. Table of candidate questions for measurement plan review. Appendix 2. Consensus results: table of measurement plan review questions.