The timing of turn taking in conversation is extremely rapid given the cognitive demands on speakers to comprehend, plan and execute turns in real time. Findings from psycholinguistics predict that the timing of turn taking is influenced by demands on processing, such as word frequency or syntactic complexity. An alternative view comes from the field of conversation analysis, which predicts that the rules of turn-taking and sequence organization may dictate the variation in gap durations . In this paper, we estimate the role of these two different kinds of factors in determining the speed of turn-taking in conversation. We use the Switchboard corpus of English telephone conversation, already richly annotated for syntactic structure speech act sequences, and segmental alignment. To this we add further information including Floor Transfer Offset (the amount of time between the end of one turn and the beginning of the next), word frequency, concreteness, and surprisal values. We then apply a novel statistical framework (“random forests”) to show that these two dimensions are interwoven together with indexical properties of the speakers as explanatory factors determining the speed of response. We conclude that an explanation of the of the timing of turn taking will require insights from both processing and sequence organization. Imagine a species that squawks at conspecifics. If it only has one message type , messages will have low information value. If there is only one rule of use, namely “one at a time,” communication will exhibit turn-taking, but not much other sequential patterning. Marmoset communication perhaps come close to this  and long turn transitions without talk (“gaps”). The “floor transfer offset” (FTO) provides a way of measuring gaps and overlaps in one single continuous variable .There are some previous studies of the distribution of FTOs. For example, Strömbergsson et al.  find thaHere we list some measures relevant to either production, comprehension, or both, whose importance we can readily check in the data to hand. We consider a number of hypotheses about how these might play a role in response times, measured in FTO.By definition, longer turns can have longer periods of overlap with another turn. Moreover, longer utterances are likely to be more complex than shorter utterances, requiring more processing. However, a longer utterance also gives more time for a listener to begin planning her own turn. Therefore, the predictions for effect of the length of T1 on FTO values are not clear without taking other measures of the content of the turn into account. On the other hand, the prediction for T2 length may be clearer. Planning a long utterance should generally take longer than planning a short one, so the FTO is expected to increase as the length of T2 increases.Psycholinguistic research has shown that word frequency plays a crucial role in ease of processing, both in comprehension and production. In lexical decision experiments for example , frequent words are responded to more rapidly than infrequent words  contrast with words that refer to abstract entities . Concreteness ratings have been shown to correlate with lexical decision times, with concrete words being comprehended faster . Consequently, there may be an asymmetry in the predictions for the syntactic complexity of A's turn and B's turn. While T2 has no way of influencing the relationship between syntactic complexity and when T1 ends (apart from other-initiated repair), there is the option of “buffering” planning at the beginning of T2. Speakers often use turn-preserving placeholders, or hesitation markers, such as “uh” and “um” at the start of their turns to minimize the gap between turns. They may use this extra time to plan their response. This asymmetry in the options for T2 predicts that the syntactic complexity of T2 would only be correlated with the FTO when excluding initial parts of T2 that were simply turn-preserving placeholders.If the timing of turn taking is the primary “ecology” to which language has to adapt . As reported below and in the Supplementary Materials, many of the independent variables in the Switchboard data are correlated.One solution to this problem is to use the method of “random forests” Breiman, . This isFigure 2. This was generated with FTO as the dependent variable and four measures of sequence organization . For clarity, only the first three levels are shown.First, the concept of a decision tree is reviewed. A decision tree is a hierarchy of yes/no-questions that splits data into sub-sets. To illustrate this, consider the tree in n which represents the number of observations in that sub-set. The tree can be read like a solution to a game of “20 questions.” If you are asked to guess the value of an FTO, the decision tree aims to show you the optimal sequence of yes-no questions that will guide your guess. The tree can also be read like a set of rules that describe patterns in the data . For a given turn transition, if T1 is initiating, then we follow the right branch. The next “question” splits the data into T2s with responding actions  and those without. If T2 does include a responding action, we follow the branch to the left, and are asked whether T1 included laughter. If not, then we end up at a terminal category which we might label “adjacency pair,” summarized in a bar chart. This bar chart indicates that the mean FTO is around 200 ms, based on 1130 samples  have a mean FTO of around 300 ms. This fits with work showing that dispreferred responses tend to be delayed . This reflects the trend for males to speak faster than females. For both male and female speakers of T2, slower speech in T1 (higher T1 delta) leads to shorter FTOs. The rightmost leaf represents 314 cases of FTOs between two female speakers where T1 is speaking very slowly (high delta). In this case, the mean FTO is in overlap.The tree in Figure One problem with decision trees is that their structures are not robust. The structure is sensitive to the selection of predictor variables and the particular sample of data  than other turns. Therefore, the tree would split the data into FTOs with high and low frequency T1s. A prediction from the sequence organization account might be that negative responses have higher FTOs, so the tree would split the data into FTOs before positive and negative T2 responses.density function in R set to default parameters) was 169 ms. For comparison, in our Switchboard data, the median for polar questions followed by a response was 199 ms, and , though there was only weak evidence for multicollinearity (maximum variable inflation factor = 3.9). The number of variables also makes the number of possible interactions very high. These two factors make simple linear regression analyses more difficult to interpret, but random forests is a robust to these concerns. Here we report various results relating to the random forests analyses.Many of the predictor variables are correlated with each other . To give an impression of the fit of the model, a single tree was generated . The predicted FTOs correlated with the actual FTOs with r = 0.51, meaning that the model accounts for about 30% of the variation. Another way of assessing the fit is to use the model to predict values for each FTO. When categorizing FTOs into gaps and overlaps, the model correctly categorizes 70% of cases.A random forests model was run with 1000 trees and 3 variables in each tree . This result is difficult to compare with linear models, since random forests work very differently (random forests are based on decision trees which divide data into sub-sets and fit each sub-set separately). Still, the difference between the two suggests that overall trends are weak, but there are more dependable patterns for certain types of transition.Figure t = −0.21, p = 0.83; mean rank for processing measures = 17.8, mean rank for sequence organization measures = 16.1 t = 0.47, p = 0.64).The top five most important variables are whether T1 includes a responding action, T1 duration, T2 duration, T1 speech rate and T1 sex. Measures of processing and sequence organization were not rated differently overall . For duration, speech rate and tree height the importance of the variable for T1 is greater than for T2, suggesting more weight on comprehension and planning. However, the opposite pattern holds for concreteness, frequency, and surprisal measures.There was no large difference in the ranking of measures for T1 compared to measures for T2 . T1s spoken with rates in the fastest quartile lead to FTOs around 100 ms longer than those in the slowest quartile. The speech rate of T2 is ranked as much less important. There is no strong relationship between T2 rate and FTO.r = 0.65, t = 171, p < 0.00001). Notice that here, as with speech rate, the processing factors only have significance in a particular sequential context, demonstrating how the two parameters, sequence organization and processing costs, are interwoven.T1 syntactic tree height is relatively important (ranked 6th most important out of 30), as is the number of clauses for T1 and T2 (ranked 9th and 10th). As the T1 increases in syntactic complexity, the FTO increases. Turns in the simplest quartile lead to FTOs 64 ms shorter than turns in the most complex quartile. There is no strong linear relationship between T2 syntactic complexity and FTO. The relative importance of the number of clauses in T2 may be attributed to the correlation with turn duration . When combined with utterance duration, then, the concreteness of T2 becomes a proxy for distinguishing response tokens (simple to project and plan) from question answers (more difficult to project and plan). Indeed, in a decision tree constructed with only T2 concreteness and T2 duration, T2 concreteness is used in a branch of the tree with short T2 turns and, within these turns, higher concreteness leads to longer average FTOs (positive relationship).r = 0.13), with the correlation being stronger as the length of T1's turn increases . That is the timing of turn transition is more tightly timed when T2 is less concrete .T2 concreteness seems to be more related to the absolute FTO, that is to how close the beginning of T2 is to the end of T1, ignoring whether it's a gap or overlap. There is an overall positive correlation between absolute FTO and T2 concreteness . Whether T2 starts with a responding action, and whether T2 starts with an initiating action are also ranked as relatively important, and since they form the basis of sequence organization they are discussed together here. Figure The most important factor in the whole random forests analysis is whether T1's  dialog act includes a responding action . On average, FTOs are smaller when T1 includes a responding action  is 200.7 ms. This kind of sequence forms the basis of adjacency pairs (see Section 4.1), and agrees very well with results for polar questions from Stivers et al. .The mean FTO is longer when T1 responds and T2 initiates (284.8 ms), a floor transition involving turns which do not form an adjacency pair. For example, in the extract below, B asks a question , and A gives an answer . This is a well-formed adjacency pair. However, if we consider the answer as T1, the next turn T2 is a different question from B. These latter turns are not part of an adjacency pair, but belong to other sequences.Conversation 3254, 0:19   A: Uh, there were a few things different      than the old series, but on the, on      the whole, it was pretty similar.      And, a lot of fun.   B: Lots of little funny spots, huh?T1 A: Oh, yeah, yeah. (Responding)   FTO = + 614 msT2 B: Did they have Thing, and,      (Initiating)   A: Oh, yes, in fact, Thing has a big,      much bigger role than he does in the      series.Another possible case is that in which floor transfers occur between two initiating actions. In such cases, the mean FTO was the longest (298 ms). In our data, these often involve cases of other-initiated repair . The following example is a case of other initiated repair. B asks a question (initiating action), but A does not hear or understand, and initiates a repair sequence on the previous turn. B goes on to rephrase their question, and A resumes the main question-answer sequence:Conversation 3232, 2:13(A and B are discussing scholarships)   B: -- it paid most of my tuition, and,      um, a lot of the book costs and that      kind of thing, so.   A: Wow, that's great.   B: Yeah, I really,T1 A: Was it a Pell grant? / (Initiating)      FTO = +494 msT2 B: I'm sorry, what did you say?      (Initiating)   A: What kind of grant was it?   B: Well, it was called a B E O G,      a Basic Equal Opportunity GrantIn line with our results, Kendrick  finds thFinally, we see that the shortest average FTOs are when both T1 and T2 involve responding actions. In this case, the mean FTO is shorter (157 ms). Many of these sequences involve T1 being a backchannel. Looking closer, we also find that many are part of sequences of assessment. The example below involves a news delivery sequence    A: But, uh, they just go around to      each, uh, door and pick it up.   B: Wow, that's excellent.T1 A: Yeah. (Responding)   FTO = +137 msT2 B: That's good. (Responding)Similarly, in the next example, A responds to B's statement with an assessment in T1, and then B produces a second assessment in T2.Conversation 3526 2:44   B: Yeah it and when it comes on the      manufacturing floor it's about ten      bucksT1 A: I'll be darned (Responding)   FTO = +206T2 B: Yeah (Responding)   A: Huh well   B: Well i watched something on TV a      couple of months ago by uh General      ex uh Surgeon General Kooppost-hoc, we observed that, when T1 is a backchannel, the FTO is around 38 ms lower on average than otherwise. This could occur if backchannels are regularly overlapped because they are not treated as real turns at talk . There is no big difference in means according to whether T2 is a backchannel  and this is reflected in it being ranked as relatively unimportant in the random forests results.T1 including a backchannel is ranked 9th out of 30 in terms of importance. Looking at the effect of this variable Post-hoc tests revealed that FTOs are 55 ms longer on average when T2 includes a negative response . This is in line with a delay for dispreferred responses, but the size of the effect is very small , especially in comparison to the effect of T2 being a responding action vs. not.Whether T2 provides a positive response is ranked in the middle of the distribution of importance. The sex of the speakers is relatively important, with each male in the conversation adding around 70 ms on average to the FTO .The rest of the variables have weaker importance values, but some observations are worth making. Many processing variables are not highly ranked, especially measures of information and surprisal, but also frequency, which goes against the processing predictions.post-hoc t = 5.4, p < 0.00001). FTOs are shortest when there is invited laughter: when there is laugher in both T1 and T2, the average FTO is -142 ms (overlap), as predicted by the literature on laughter in conversation. However, the laugher variables are the lowest rated variable according to the random forests analysis. This could be due to the relatively small number of cases that include laughter (about 4% of cases).FTOs are on average lower for transitions involving laughter . The prediction from processing is that the processing variables would be ranked as more important in this case, since placeholders gives responders time to plan.As discussed in Section 7, the beginnings of some turns may be turn-preserving placeholders, hesitation markers such as “um” and “uh,” that speakers use to “buffer” their response. This could obscure the demands on processing. To explore this, the same model was run, but calculating the FTO as the time from the end of T1 to the first non-turn-preserving placeholder in T2. The full results are available in the Supplementary Materials. The importance estimates in this model were weakly correlated with the main model importance estimates reported in the section above , but may reflect differences in socio-cultural norms or simply individual differences.We began with the observation that communication systems are imaginable, the marmoset system a putative case, in which issues of cognitive load and sequence organization play little role in influencing temporal patterns of behavior. Human communication contrasts on both dimensions, because of the formidable choice of alternatives faced by a speaker and the consequent unpredictability faced by a responder on the one hand, and on the other because sequences of ordered turns map structure onto the sheer fact that T1 is followed by T2.By using a large coded corpus we have been able to track the importance of a set of different measures of each dimension. We conclude that the temporal patterns of dialogue cannot be accounted for by either cognitive or sequence organization factors alone. The two are interwoven with indexical factors in such a way that, for example, the sex of a speaker in a particular initiating sequence type creates an environment where cognitive load plays a particularly strong role in influencing the speed of response. This suggests that an explanation of the timing of turn taking will involve a combination of insights from both cognitive processing and sequential organization.The ways in which factors load only in specific ecological niches make standard regression techniques inapplicable. Here the method employed, random forests, comes into its own, allowing the factor loading to be discerned in specific ecological niche formed by indexical factors, processing factors and sequence factors, as illustrated in the tree in Figure This study has not exhausted the information in the Switchboard corpus. It would be possible to analyze further the different distinctions in dialog actions, such as the distinction between polar questions and content questions . There is also more indexical information such as age and dialect. Speakers were assigned topics of conversation and these may also have stimulated speakers to different degrees, which could affect average FTOs. There are also a range of phonetic information and semantic factors that could be explored. This study thus has distinct limitations. Extending the analysis to other corpora and other languages will however require large amounts of transcribed speech data, matched with processing information such as frequency and surprisal for many languages.All data collected from individuals were from sources where informed consent had been provided.http://tla.mpi.nl/tools/tla-tools/elan/.Source data is available to download online (see the various references in the main text). The analysis software is also available: pympi (Lubbers and Torreira, Extracted and prepared the data: FT; Calculated FTO: FT; analyzed the data: SR, FT; Wrote the manuscript: SR, FT, SL.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.


B along with high in-plane magneto-crystalline anisotropy energy (MAE) of 17 meV. Under the influence of electric field, spin crossover effect accompanied by a change in the MAE is observed. The ascribed change in spin-configuration is caused by the modification of exchange coupling between defect states and a change in the occupation of d-orbitals of the metal complex. Our predictions open a promising way towards controlling the magnetic properties in graphene based spintronic and non-volatile memory devices.Developing nanostructures with tunable magnetic states is crucial for designing novel data storage and quantum information devices. Using density functional theory, we investigate the thermodynamic stability and magnetic properties of tungsten adsorbed tri-vacancy fluorinated (TVF) graphene. We demonstrate a strong structure-property relationship and its response to external stimuli via defect engineering in graphene-based materials. Complex interplay between defect states and the chemisorbed atom results in a large magnetic moment of 7 μ Understanding mechanisms that control magnetism at the nanoscale is crucial for designing novel spintronic and data storage devices. However, understanding these mechanisms remains an open challenge in material science, with a tremendous impact on today’s information technology1234567891012131415sp2 hybridized in honeycomb geometry and exhibit a large surface area. The outer low-energy pz orbitals of C atoms can hybridize with the defect states modulating its electronic and magnetic properties2224252728293031333435Graphene – a single sheet of carbon atoms has unique mechanical, electronic, and optical properties171720d-bands of adatom394143et al. synthesized reduced graphene oxide (RGO) by chemical exfoliation method and obtained fluorinated RGO by annealing RGO with XeF2. The fluorinated graphene is found to be stable and magnetic in the presence of vacancies37In general, MAE is an interplay among spin-orbit coupling (SOC), ligand field and surrounding environment . Thus, one can control the MAE and other magnetic properties by tuning these parameters5in silico identification of promising defects/impurities with desired properties, and thereby investigating structure-property relationship.As defects and doping play an important role in functionalizing graphene484950515253In this work, we investigate the magnetic properties of W atom adsorbed on tri-vacancy fluorinated (TVF) graphene; a schematic picture is shown in 5556Prior to investigate the physicochemical properties of W chemisorbed TVF graphene, we first investigate the thermodynamic stability of TVF graphene. Although nanoporous grapheneF2 molecule and nF is the number of F atoms incorporated. The last term in T) and partial pressure 2, and can be determined via statistical thermodynamics or from thermochemical JANAF TablesIn ab-initio computations for fluorine doped graphene, the phase diagram showing the defect formation energetics as a function of F2 chemical potential (Δμ(F2)) is shown in T-2) for thermodynamically stable TVF graphene with three fluorine atoms lies between −2.45 to −1.85. In the inset of 2) of thermodynamically stable TVF graphene with three F atoms. To ensure the surface thermodynamic stability of the system under real-world synthesis conditions, , the dependence of F2 chemical potential (Δμ(F2)) in the gas phase is translated to the pressure scale at 1100 K.Using 3 molecule in vacuum and a nanoporous of six C vacancies in graphene. Thus, our calculations, as shown in the As depicted in ETVF are the total energies of TVF graphene with and without adsorbed W atom, respectively.where ab-initio MD simulations. In T = 290 K. We find an almost constant energy and a stable ferromagnetic state over the time at T = 290 K, which confirms that the system (W adsorbed TVF graphene) is dynamically stable. We also tested the ferromagnetic stability at room temperature (T = 300 K) for a few hundred steps and found the system to be stable at room temperature and showing FM properties.In order to investigate the total energy and spin moment of the system at a finite temperature, we performed 1, C2, and C3. A stable structure after the relaxation process is achieved as a consequence of the repulsion between F atoms and un-bonded carbon atoms that results in W atom getting bonded with one of the un-bnded carbon atoms and breaking the symmetry of the system. This results in lowering the energy of the system and a Jahn-Teller distortion in the system. The geometrical reconstruction of dangling bonds results in symmetry breaking that results in the total spin magnetic moment of the system to be 7 μB. The physical origin of high spin magnetic moment can be inferred from the high-spin configuration of 5d-series W  adatom on TVF graphene.As shown in d-TM atoms have filled 6s orbitals and partially filled, half filled or completely filled d-orbitals. The electronic configuration of W atom is 5d5↑, 6s1↑. Adsorption of W atom on TVF graphene leads to a rise in the energy of 6s orbitals, which is then minimized through the polarization of 6s orbitals by transferring the charge from 6s to the minority states of 5d-orbitals593). The other two dangling bonds remain unsaturated and induce a finite magnetic moment of 0.70 μB/dangling bond which is same as the magnetic moment of the dangling bonds in absence of the adatom. As W is bonded to one of the dangling bonds by hybridization only, most of the uncompensated charges need to be accommodated on W atom itself, which leads to a large moment of 3.70 μB per W atom. Note that this spin magnetic moment is greater than the magnetic moment of 2.29 μB previously found for W adatom on di-vacancy nitrogenized grapheneThe valence states of 52 couples antiferromagnetically with C1 in the neighboring ring due to change in the occupation of states of both the dangling bonds. This results in decrease in the magnetic moment of the system. Thus the magnetic moment of the hybrid system jumps from a high-spin value to a low-spin value as the electric field changes from 5 to 6 V/nm resulting in a spin crossover effect. As the high- and low-spin states describe the different magnetic states, switching between the two states with an e-field can be used to increase the efficiency and sensitivity of magnetic memory devices.To check the stability of the hybrid system at high electric fields, we calculate its cohesive energy in the absence and presence of e-field. The calculated cohesive energy per atom of W adsorbed TVF graphene at zero and 6V/nm e-fields are 7.66 and 7.67 eV, respectively. These cohesive energies confirm that the defect can withstand high electric fields. The change in spin magnetic moment of W adsorbed TVF graphene as a function of electric field is shown in sp2 orbitals, however a small fraction of this moment also comes from the spin polarized π-orbitals. The electric field shifts the lower edge of the minority states towards the Fermi level, which leads to a decreased magnetic moment contribution by dangling bonds and therefore reduction in the total moment of the system as can be seen in d-orbitals. This further decreases the total spin moment of the system. Thus, through electric field, one can control the alignment of spins on carbon atoms in the defect region. Although the electric field affects the magnetic moment of W, the effect is greater on dangling bonds where the coupling of dangling bonds changes from the ferromagnetic to antiferromagnetic.Quantum mechanically, magnetism of dangling bonds arises primarily from the un-bonded xz(Ex–Ez) = −7.95, ΔEyz(Ey–Ez) = −17.19 and ΔExy(Ex–Ey) = 9.25 meV. This suggests that the easy axis of magnetization lies in the plane of the graphene  and hard axis is perpendicular to the surface lying along the z-axis with an MAE of 17.19 meV. Energy differences between principal magnetization directions are plotted in y–Ez) until the applied e-field reaches 6 V/nm. Beyond the e-field of 6 V/nm, a gradual variation in MAE has been observed as shown in x–Ez = −7.20, Ey–Ez = −12.93 and Ex–Ey = 5.72 meV. Hence, despite the decrease in the energy differences, the easy and hard directions of magnetizations remain unchanged.Despite the large magnetism, the use of any given material in spintronic devices also depends upon its MAE as it decreases the thermal fluctuations in the magnetization of the system. The estimated energy differences for W adsorbed TVF graphene between different magnetization directions are: ΔEd-orbitals and change in the orbital moment can affect the values of MAE5xz (Lx–Lz), ΔLyz (Ly–Lz) and ΔLxy (Lx–Ly), in presence of SOC is plotted in yz (Ly–Lz) is negative beyond an e-field of 5 V/nm and increases gradually indicating an increase in the orbital moment along the z-direction, which would suggest an easy direction of magnetization to be along z-direction. However, since this difference is small (<0.1 μB), it is difficult to predict the direction of easy axis based only upon the difference in orbital momentxy (Lx–Ly) and ΔLxz (Lx–Lz) suggests a switching of MAE at higher electric field. Inclusion of SOC suppresses the magnitude of spin moment, however it has the same trend as the non-SOC case shown in Change in the occupation of To obtain a quantum mechanical picture of the origin of magnetism and MAE, in Lz and Ly (Lx) are the angular moment operators along the principal axes. As, where 〈dzx and dx2–y2 and the coupling between dz2 and dxz through Ly have dominant contribution to y-axis. Although application of electric field increases the coupling between  and  orbtials, we find a decrease in the MAE of the system at higher fields. This decrease is found to be due to the increase in the coupling interaction of  and  orbitals through Lzy- to x-axis is expected to be due to the coupling of dxy with dxz, coupling of dx2–y2 with dyz and the coupling of dz2 with dyz orbitals realized through Lx operator.The DOS in To check the robustness of presented results with respect to the change in exchange correlation potential, we also performed DFT calculations using PBE-sol pseudopotentials. We find that both PBE and PBE-sol yield similar results for structure and magnetism in the absence of SOC at all the fields. Upon inclusion of SOC, the computational cost of calculations increases, therefore we calculated the MAE and orbital moments just at the smaller fields and found that the results change by 2–3 meV, however the overall trend remains the same.In summary, we have investigated the magnetic properties of tungsten adsorbed on nanoporous TVF graphene and have demonstrated the influence of intrinsic defects on the stabilization of the adatom and inhibition of aggregation. Our computational results suggest that the proposed defect is thermo-dynamically and geometrically stable and can be fabricated with existing experimental techniques. Further, we predict that the magnetic properties of the hybrid system can be modified using e-field via the changes in the occupation of W adatom states. As a result of this modulation, we find a switching between high-spin and low-spin states after an e-field of 5 V/nm. Present study also confirms an easy plane anisotropy accompanied by spin crossover in tungsten adsorbed on TVF graphene, which is an important result for non-volatile memory and spintronic devices. Further, we expect to see a change in the direction of magnetization at higher fields or by substituting different adatoms. We believe that our results will stimulate experimental work on these kinds of hybrid systems to develop highly efficient data storage and spintronic devices based on graphene.Ab-Initio Simulation Package (VASP)63−7 eV and a Γ centered k-mesh of size 7 × 7 × 1 is used to sample the Brillouin zone of the systemDensity functional theory calculations are performed using frozen core projector augmented wave method as implemented in Vienna 3Dh symmetry. The other three C atoms in the ring remain non-bonded and are called as dangling bonds. The relaxation breaks the 3Dh symmetry of the system and the W atom shifts towards one of the carbon atoms, as depicted in As demonstrated in the ab-initio molecular dynamic (MD) simulations using Nose-Hoover heat bath schemeTo check the stability of W adsorbed TVF graphene system, we also performed finite temperature How to cite this article: Kumar, P. et al. Tunable magnetism in metal adsorbed fluorinated nanoporous graphene. Sci. Rep.6, 31841; doi: 10.1038/srep31841 (2016).


Graphene monolayers are known to display domains of anisotropic friction with twofold symmetry and anisotropy exceeding 200%. This anisotropy has been thought to originate from periodic nanoscale ripples in the graphene sheet, which enhance puckering around a sliding asperity to a degree determined by the sliding direction. Here we demonstrate that these frictional domains derive not from structural features in the graphene but from self-assembly of environmental adsorbates into a highly regular superlattice of stripes with period 4–6 nm. The stripes and resulting frictional domains appear on monolayer and multilayer graphene on a variety of substrates, as well as on exfoliated flakes of hexagonal boron nitride. We show that the stripe-superlattices can be reproducibly and reversibly manipulated with submicrometre precision using a scanning probe microscope, allowing us to create arbitrary arrangements of frictional domains within a single flake. Our results suggest a revised understanding of the anisotropic friction observed on graphene and bulk graphite in terms of adsorbates. Graphene can exhibit pronounced frictional anisotropy, which was thought to arise because of nanoscale ripples. Here, the authors provide evidence that this effect could instead be a result of adsorbates that self-assemble into a highly regular superlattice of stripes with a period of four to six nanometres. Nanometre-scale surface textures with long-range order often give rise to pronounced frictional anisotropy. These textures sometimes originate from crystal structures: periodic tetrahedral reversals in the antigorite lattice create nanoscale surface corrugations, which generate the anisotropic friction that governs certain seismic processes45From a technological standpoint, nanometre-scale systems with such multistability are appealing platforms for switches or memories. Bistable states in redox centresIn this study, we identify a friction-producing nanotexture that naturally forms on graphene exposed to laboratory air and exploit its multistability to hysteretically switch friction with submicrometre precision. Using high-resolution atomic force microscopy (AFM), we directly image a superlattice of nanoscale stripes on exfoliated graphene and we show that this striped nanotexture produces the anisotropic friction previously observed13141617To image friction, we measure the deflection (diving board motion) and torsion  of a scanned AFM cantilever in light contact with the sample. The deflection signal primarily contains topographic information, while the meaning of the torsion signal depends on scan direction. For lateral scanning  without change in stripe period and with minor change in magnitude of frictional anisotropy  often minimally affects the frictional domains, but scanning at high normal force (30 nN) reproducibly reorients the domains  and highly oriented pyrolitic graphite  and observed no differences in superlattice phenomena between samples produced using different graphite sources or tapes. For hBN exfoliation, we used bulk crystals provided by Kenji Watanabe and Takashi Taniguchi. We also prepared graphene flakes on other substrates  under ambient conditions (40–60% relative humidity) on bstrates , includi−1), to below 100 °C under the same flow of oxygen and argon.We prepared epitaxial graphene heterostructures on oxidized silicon substrates by mechanical exfoliation of hBN followed by graphene growth at 500 °C by a remote plasma-enhanced chemical vapour deposition process described previously−1. We warmed up the samples under various atmospheres including moderate vacuum, helium gas or nitrogen gas; in all of these cases (over ten different samples cycled in the dilution refrigerator or PPMS) we found stripes on every flake or heterostructure  that we checked.We found stripes to appear on our samples after thermal cycling to liquid nitrogen temperatures or below using a variety of methods. Most commonly, and specifically for the sample shown in The epitaxial heterostructure in Q of 400. See All images shown in −1. See −1, whereas for erasing we used scan rates ∼300 μm s−1.For measurements in contact mode, we used silicon probes (MikroMasch HQ:NSC19/Al BS-15) with a nominal tip radius of 8 nm and a typical resonant frequency of 65 kHz. We used a normal force setpoint of 1 nN for all friction and transverse force imaging scans shown, with scan rates ∼10 μm s2.When imaging friction or transverse force, we collected torsion data for both forward-moving and backward-moving scans. To eliminate offsets in the friction and transverse force signals for −11 mbar). Samples were not baked in UHV before experiments. The sample stage was cooled by a copper braid attached to a cold sink held at low temperature by continuous flow of liquid nitrogen; by this method, we achieved a base temperature of 110 K. We used the same sharp probes as for ambient AFM (MikroMasch Hi'Res-C15/Cr-Au). In UHV, the cantilever Q reached 5,000, which significantly restricted scan speed for tapping mode; we therefore used on-resonance frequency-modulation mode, imaging at a typical frequency shift of −30 Hz. For all images, we applied a DC tip-sample bias to nullify the contact potential difference.To study stripe formation with changing temperature , we usedSTM measurements  were cargwyddion.net). All error bars reflect the full width at half maximum of the peaks in the fast Fourier transform; for instance, 12.0±0.5 nm means that the full width at half maximum of the peak maps to 1 nm in real space. The lateral scale of the Park XE-100 was calibrated by measuring the moiré period of graphene/hBN heterostructures grown by van der Waals epitaxy, in which the graphene and hBN lattices are nearly perfectly aligned, and defining this period  to be 13.6 nm. This definition corresponds to the assumption made in ahBN=0.25 nm and agraphene=ahBN/1.018. The lateral scale of the Omicron variable-temperature AFM was calibrated to the lateral scale of the Park XE-100 by measuring the moiré pattern of the same sample in both systems.All values quoted for moiré period and angular orientation are extracted from the fast Fourier transform of the AFM images. AFM images of all heterostructures described in this study are corrected for thermal drift by performing an affine transformation to produce regular moiré hexagons .Supplementary Figures 1-7, Supplementary Notes 1-8 and Supplementary References.Patterning frictional domains on monolayer graphene.


The high ON-state current of 0.8 mA/μm is enabled by a narrow (~0.3 eV) extrinsic band gap, while the smallness of the leakage current is due to an all-electrical doping of the source and drain contacts which suppresses the band tailing and trap-assisted tunneling.In a continuous search for the energy-efficient electronic switches, a great attention is focused on tunnel field-effect transistors (TFETs) demonstrating an abrupt dependence of the source-drain current on the gate voltage. Among all TFETs, those based on one-dimensional (1D) semiconductors exhibit the steepest current switching due to the singular density of states near the band edges, though the current in 1D structures is pretty low. In this paper, we propose a TFET based on 2D graphene bilayer which demonstrates a record steep subthreshold slope enabled by van Hove singularities in the density of states near the edges of conduction and valence bands. Our simulations show the accessibility of 3.5 × 10 Tunnel FETs (TFETs) with interband tunneling are among the principal candidates to meet this demand1d-dimensional TFET channel, the DoS scales with energy E above the band edge as Ed−2)/2/2(10812151920It is intuitive that the abrupt variations of electron and hole densities of states (DoS) near the band edges further enhance the switching efficiency of TFETs2 substrates: the measurements of infrared absorption27583031In this paper, we theoretically demonstrate that graphene bilayer (GBL) represents an ideal platform for the low-voltage tunnel switches due to its peculiar ‘mexican hat’ band structure of GBL formed under transverse electric field22μm is accessible due to the low extrinsic band gap of GBL (~0.3 eV) and large DoS far above the band edges.The advantage of graphene bilayer TFETs over those based on 2d materials with parabolic bands in terms of switching steepness can be illustrated by n- and p-types.Although a number of GBL transistors have been proposed33342 layer playing the role of back gate oxide and substrate for graphene bilayer. Alternatively, the SiO2 layer can be replaced with hexagonal boron nitride (hBN) possessing a small (~1010 cm−2) density of residual charged impuritiesκ dielectric  covers the graphene channel, and the top metal gates are formed above. The side gates near the source and drain contacts induce large densities of holes and electrons, respectively, which also leads to the formation of an abrupt tunnel junction and energy barriers , we choose them to be The fabrication of the device structure in dE in the energy scale, the electrons available for tunneling in graphene bilayer occupy a ring in the momentum space  − fc(E) over the momentum space d2p = 2dp⊥dp||A rigorous expression for the tunnel current density involves an integral of the single-particle velocity gs gv = 4 is the spin-valley degeneracy factor in graphene, pmax(E) is the maximum transverse momentum of electron at a given energy E, pmax(E) = min{pc(E), pv(E)}, where pc(E) and pv(E) are the inverse functions to the electron dispersion in the conduction and valence bands. The limits of integration over energy are the conduction band edge in the channel, Ec, and the valence band edge in the source, Ev. The factor of two before the quasi-classical barrier transparency comes from the presence of two turning points with zero group velocity in the GBL dispersion at which an electron attempts to tunnel.Here, pmin  is the imaginary part of electron momentum evaluated at the midgap, and l is the length of the classically forbidden region (tunneling path length). The latter is given by p⊥ < pmin, and l = 2E(p⊥)/eF for p⊥ > pmin, where F is the electric field at the junction found from the solution of Poisson’s equation, and where Im J(VG)–characteristics of graphene bilayer TFET at different drain bias VD are shown in VG, in agreement with the simple density-of-states arguments and J(VG)-curve slightly increases due to the sensitivity of the tunnel barrier transparency to the junction field. The subthreshold slope at VG = Vth reaches (20 μV/dec)−1 and is limited by the small thermionic current μm and the gate leakage current μm. About 100 mV below the threshold, the ambipolar leakage at the drain tunnel junction becomes pronounced; this can be, however, minimized by placing the drain doping gate at large distance from the control gate.The calculated room-temperature p+ − n+ tunnel diode between source and channel. The emerging negative differential resistance is due to the dependence of the band edges in the channel on the amount of injected carriers: at high electron density, the bands in the channel are lifted upwards, which reduces the source-channel band overlap and switches the tunneling off.The drain characteristics of graphene bilayer TFET shown in VS required to switch the transistor between the ON- and OFF-states. Considering the current at VG = 0 V as the ON-state current (JON = 0.8 mA/μm in VD = 0.15 V), and the leakage current as the OFF-state current (JON/JOFF = 3.5 × 104), we have obtained VS = 150 mV. In a conventional MOSFET, the gate voltage swing VS ≥ 285 mV is required to achieve the same current switching ratio. The average subthreshold slope of our TFET over 4.5 decades of current is 33 (mV/dec)−1. With this characteristic, it outperforms all sub-thermal tunnel switches2/germanium junction with a similar value of the average subthrehold slope was demonstratedμA/μm leaves much to be desired.For low-power applications, the maximization of the highest subthreshold slope is not as important as minimization of the supply voltage I60–figure of merit−1. While the best I60 reported to date equals 6 nA/μm , while in the 2D structures based on III–V materials being narrow-gap in the bulk, the gap value increases significantly due to the quantum confinementThe unique characteristics of GBL TFET surpassing the existing TFETs are enabled by the three factors. First of all, it is the small extrinsic band gap . At 150 mV gate voltage above the threshold, the current density in graphene bilayer exceeds 15 times that in a parabolic-band material. The factor of two is due to the valley degeneracy absent in III-V’s, another factor of two is due to the tunneling at two turning points of the ‘Mexican hat’ dispersion, and the remainder of 3.5 is due to the finiteness of electron momentum at the edge of the ‘Mexican hat’.where The steep switching of the tunnel current by the gate voltage can be masked by the leakage to the gates, band-tail and trap-assisted tunneling192038ρ(E) in the presence of fluctuating potential by integrating the singular ‘bare’ DoS ρ0 over the probabilities of voltage fluctuations37The main reason for the band tailing comes from the fluctuations of electric potential produced by the random charged defects or dopantsV2〉 is the root-mean-square amplitude of the voltage fluctuations proportional to the impurity density ni. The calculated energy dependencies of the ‘smeared’ DoS are shown in ni = 4 × 1013 cm−2, the conduction and valence bands almost merge together, which would result in a poor OFF-state, nothing to say about high switching steepness. A slight peak in the DoS near the band bottom becomes noticeable already at impurity density of 5 × 1012 cm−2 which corresponds to the low-quality graphene on SiO2 substrates. In graphene samples on a high-quality SiO210 cm−2δε ≈ 20 meV. Already for relatively small gate voltages, VG − Vth > δε/e, these corrections are irrelevant and the linearity of the J(VG)–characteristic holds.where 〈κ materials, zirconium oxide (κ ≈ 25) looks as an optimal solution for the GBL TEFT due to the large band offset with respect to graphene (Ub = 2.9 eVmt ≈ 0.3m0ne(h) into the metal gate to be .where J(VG) curve in the proposed FET reaches the maximum of (20 μV/dec)−1, while only 150 mV gate voltage swing is required to change the current density from JON ≈ 1 mA/μm down to JOFF ≈ 2 × 10−5 mA/μm. As a matter of fact, the effects of singular DoS on the interband tunneling are possible just in the TFET structures with an all-electrical doping, where the effects of band tailing and trap-assisted tunneling are minimized.We have proposed and substantiated the operation of a graphene bilayer TFET exploiting the van Hove singularities in the density of states near the band edges. The presence of these singularities leads to the increased steepness of the gate characteristics and to the high ON-state current as well. The subthreshold slope of Such steep switching in the lateral TFETs based on 2d materials is possible if only the van Hove singularities are present both at the top of the valence and the bottom of the conduction band. This property is unique to the graphene bilayer and is absent in other 2d materials , where a ‘Mexican hat’ structure is formed in one of the bands due to the spin-orbit couplingp+ − n+ tunnel junctionsξn and ξp are the electron and hole Fermi energies in the n+ and p+-doped regions (see I(V)-curves. It is worth noting that a widely used phenomenological model of tunneling proposed by EsakiI(V)-curve. In such model, the current reaches its maximum at eV = ξn + ξp and then drops abruptly (I(V) curves are not observed in the experiments, which speaks in favor of our rigorous model of tunneling.At present, it is challenging to quantitatively compare the results our model to the experimental data, which are limited to the characteristics of graphene bilayer Esaki-type The modeling of GBL TFET is based on the self-consistent determination of carrier density and band structure under fixed gate voltagesThe effect of charged impurities present in the substrate on the singular density of states in graphene bilayer is evaluated with Kane’s quasi-classical model of band tailsThe gate leakage current is estimated with a quantum-mechanical model of graphene bilayer tunnel coupled to the continuum of delocalized states in the metal gate. The model is presented in How to cite this article: Alymov, G. et al. Abrupt current switching in graphene bilayer tunnel transistors enabled by van Hove singularities. Sci. Rep.6, 24654; doi: 10.1038/srep24654 (2016).


Drosophila development.Smaug, a protein repressing translation and inducing mRNA decay, directly controls an unexpectedly large number of maternal mRNAs driving early http://genomebiology.com/2014/15/1/R4See related research,  Drosophila protein Smaug. In this issue of Genome Biology, Chen et al. [Regulation of translation and mRNA stability is a key aspect of early metazoan development. One of the best studied factors involved in these processes is the n et al.  report tDuring the first few cell divisions in animal development, the embryo’s genome remains silent. Development relies entirely on maternal RNA, a reservoir of RNA, including mRNA, copied from the mother’s genome during oogenesis and deposited in the developing oocyte, and protein synthesis is regulated exclusively at the levels of mRNA translation, stability and localization. In a process termed maternal-to-zygotic transition (MZT), control of development is then transferred to the zygotic genome. MZT obviously depends upon activation of the zygotic genome, but destruction of a large fraction of maternal RNA is also required. One reason seems to be that re-expression of specific genes from the zygotic genome can be limited to certain cells or regions of the embryo and thus, together with localization or localized destruction of maternal mRNA, contributes to differentiation. MZT ends with the first morphological alterations that depend on zygotic transcription.Drosophila, the first 13 cycles of genome duplication and nuclear division are rapid and synchronous. As these nuclear divisions are not accompanied by cell divisions, a syncytium  results. With the beginning of the much slower 14th division cycle, approximately two and a half hours after fertilization, cell membranes form around the nuclei, which have arranged themselves as a monolayer at the periphery of the embryo. This transition from the syncytial to the cellular blastoderm marks the end of the MZT, while zygotic genome activation begins already around cell cycle 10. The maternal mRNA present before this stage represents about 55% of all protein-coding genes; that is, 6,000 or more transcripts [In the development of nscripts -4. Amongnscripts -4. At lenanos (nos) transcript, which encodes the protein directing the development of the posterior end of the embryo. The majority of the nos message is distributed uniformly throughout the embryo, remains translationally silent, and is degraded during the first 2.5 h of development. A small fraction of nos mRNA, however, which is localized in the germ plasm at the posterior end, escapes repression and destruction, providing the local source of Nanos protein that is essential for posterior patterning. Thus, degradation of maternal mRNA is not just mindless wholesale destruction, but a very finely tuned process that is interwoven with translational control and mRNA localization.One of the best-studied maternal mRNAs degraded through the maternal pathway is the nos mRNA is the protein Smaug, which binds the nos transcript through two Smaug recognition elements (SREs) residing in the 3’ UTR. In contrast to Bilbo Baggins’ eponymous adversary, Drosophila Smaug causes the destruction of the treasure it is sitting on, being responsible for both the translational repression and degradation of nos mRNA. Together with the piRNA machinery [smaug (smg) mutants [nos manifests itself later in development, the early phenotype of smg mutants indicates that there must be other important targets. The only other Smaug-regulated mRNA that has been studied in detail, Hsp83 RNA  [smg mutants.Among the regulators of achinery , Smaug rachinery ,8 and adachinery . Synthes mutants . As a dey Smaug) , is unliet al. [smg and wild-type control embryos and analyzed them by microarrays. The experiments resulted in a high-confidence set of 342 mRNAs that were more strongly polysome-associated in smg mutants, implying their Smaug-dependent repression in the wild-type. Using a statistical analysis, the authors extrapolated that as many as 3,000 transcripts, about one-half of the total number of mRNAs detectable in the early embryo, may be under translational control by Smaug. However, the two well-known Smaug targets, Hsp83 and nos, were not among them. This was not unexpected: Hsp83 RNA is destabilized but not repressed by Smaug, and nos mRNA has been reported (and was confirmed in this study) to be associated with polysomes, even though translation products are not detectable. This is an important caveat, showing that the presence of an mRNA in polysomal fractions does not exclude regulation by Smaug.So how many and what kind of mRNAs are part of Smaug’s treasure? Microarray analyses have shown that at least 20% of all maternal mRNAs are substrates of the maternal degradation pathway . Surpriset al.  examinedet al. identified transcripts of 339 genes that are bound by Smaug. By means of a recently developed computational method, they then scanned the Smaug-bound RNAs and the high-confidence set of 342 translationally repressed RNAs for the presence of potential SREs, stem-loop structures with the loop sequence CNGGN0-4. Both in the bound and in the regulated RNAs, SREs were predicted with a 10-fold higher probability than in non-bound and non-regulated RNAs, respectively. In addition, the selected RNAs contained variant SRE sequences with probabilities matching the binding specificity of Smaug determined in earlier biochemical experiments: high-affinity sites were more enriched than low-affinity sites. These results come as no surprise with regard to the Smaug-bound RNAs; they merely support the reliability of their identification. However, a similar degree of enrichment of the SREs in the translationally repressed RNAs suggests that a large fraction at least of the high-confidence RNAs are direct targets of Smaug. By analyzing data from one of their previous studies [et al. found high degrees of overlap: two-thirds of the Smaug-bound RNAs were also destabilized by the protein, and three-quarters of the binders were also translationally repressed. Similarly, the destabilized and repressed RNAs overlapped to a large extent.How many of the mRNAs regulated by Smaug are direct targets? Using immunoprecipitation of the protein followed by microarray analysis of associated RNA (RIP-chip), Chen et al. concluded that a large fraction of the regulated RNAs are in fact direct targets of Smaug that escaped detection by RIP-chip.What about those RNAs that are destabilized or repressed but were not identified as Smaug ligands? These could be regulated indirectly by Smaug or they could be false-negatives in the RIP-chip experiments. From a significant enrichment of SREs in these classes of RNAs, Chen smg mutants.As the number of Smaug-regulated mRNAs is large, they code for proteins involved in many aspects of biology. Messenger RNAs localized to the posterior pole were prominent among the Smaug targets, as were those encoding proteins involved in the regulation of DNA replication and transcription. More unexpectedly, the list of targets predicts regulatory effects of Smaug on protein folding and proteasome-dependent protein degradation, lipid droplets and even basic energy metabolism. With regard to metabolism, the majority of glycolytic enzymes were identified as potential Smaug targets, and enzyme assays confirmed a modest increase in hexokinase and phosphofructokinase activity in Drosophila embryo seem to be regulated directly by Smaug. Destruction of the protein during cell cycle 14 is presumably necessary to prevent degradation of zygotic transcripts, as many are derived from the same genes as maternal mRNAs. Since Smaug is necessary for zygotic genome activation, including, for example, the synthesis of microRNAs required for the zygotic pathway(s) of maternal mRNA decay, many additional RNAs are controlled indirectly by Smaug. The new data also suggest that Smaug targets are typically both destabilized and translationally repressed. The poly(A) tail is a potent stimulator of translation, so recruitment of the CCR4-NOT deadenylase by Smaug might be sufficient to cause both destabilization and repression. However, in the case of nos, translational repression goes beyond deadenylation [In summary, an unexpectedly large number of mRNAs in the early nylation . The mecMZT: Maternal-to-zygotic transition; RIP-chip: RNA-binding protein immunoprecipitation followed by microarray analysis; SRE: Smaug recognition element.The authors declare that they have no competing interests.


Dear Editor,PD-L1, also known as CD274, plays a vital role in tumor cell related immune escape. It can be expressed on the cell surface of many solid tumors , and tumor associated macrophages (TAM) are recruited by different pathways  and the mutant U5A cells (ifnar2-/-) that lack of type I interferon receptor subunit ifnar2, we found that IFN-α induced PD-L1 in 2fTGH cells, but failed to induce PD-L1 in U5A cells . These data suggested that the induction of PD-L1 by co-culture supernatant may be interferon receptor dependent. To test this hypothesis, anti-IFNAR1 antibody was added to the co-culture medium. We found that the neutralizing antibody reduced splenocyte-induced PD-L1 expression in B16F10 cells  in other normal tissues Supplementary material 2 (PDF 102 kb)Below is the link to the electronic supplementary material.


The flexible hybrid transparent electrode was prepared by a two-step process: graphene film was firstly grown on Cu foil by modified thermal chemical vapor deposition (CVD) and then transferred onto indium tin oxide (ITO) electrode on the polyethylene terephthalate (PET) substrate. The quality of the graphene is characterized by various analytic techniques, including the AFM, SEM, TEM, and Raman spectroscopy. The gradient flux was found to be beneficial to decrease defect. The thickness, morphology, light transmittance, and electromechanical properties of three conductive electrodes were investigated and compared. The outcomes show that the hybrid electrode could resist mechanical force and the results are better than original ITO electrode. It may be a potential trend to apply the graphene to other conducts in the flexible transparent conductive field. A new generation of flexible devices has been extensively studied for electronics, optoelectronics, and energy harvesting applications –4. The kRecently, graphene becomes a novel kind of two-dimensional (2D) carbon allotrope with a unique band structure, which shows outstanding thermal, mechanical, and electrical properties . BesidesHerein, the graphene/ITO flexible hybrid transparent electrode was prepared by a two-step process: graphene film was grown on Cu foil by modified CVD method and then transferred onto ITO electrode on polyethylene terephthalate (PET) substrate. The transmission electron microscope (TEM) image, atomic force microscopy (AFM) image, and the Raman spectra of graphene films were analyzed firstly. The morphology, light transmittance, and electromechanical properties of the hybrid electrode were investigated. It is found that the gradient flux of carbon source modifies the synthesis of graphene and reduces the defect of surface structure. Moreover, the graphene layer of hybrid electrode enhances the ITO layer with excellent mechanical characteristic, and hence the electromechanical properties are improved compared to the ITO electrode.2 (pressure ~ 150 mTorr) flows. After reaching 1024 °C, the sample was left in H2 for 15 min and then a gradient flux of methane (CH4) was added to the tube for another 15 min . After that, the furnace was turned off to cool down the chamber with both CH4 and H2 presence. The CH4 pump was turned off when the furnace temperature reached 700 °C. Then, the sample cooled down to room temperature in the presence of H2 continually. Meanwhile, another graphene films were prepared by the same process with constant methane flux at annealing process of 1024 °C.The graphene film was synthesized using the CVD method similar to procedures reported previously –23. AccoThe PET substrate with ITO films  were purchased from Zhuhai Kaivo Optoelectronic Technology Co., Ltd. The graphene film was transferred to ITO/PET film by means of reported reference -28. Brie+ laser excitation wavelength of 514.5 nm. The laser beam was focused onto the sample through an ×50 objective lens. The Raman spectra were collected in the frequency range of 1000 to 3000 cm−1 with an acquisition time of 10 s. The morphology of hybrid electrodes of graphene/ITO on PET substrate was analyzed by scanning electron microscope (CARL ZEISS-∑IGMA/VP) and eclipse inverted microscope (Nikon-TE2000U). TEM imaging was carried out by JEM-2100 (HR) with 200-kV acceleration voltage and LaB6 emitter. AFM imaging was conducted with tapping mode on Multimode 8 SPM system (Bruker Inc.) to test the morphology and thickness. The optical transmittance of the samples was investigated by using X-Rite spectrometer (Coloreye 7000A). The sheet resistance and other electrical data were measured by four-probe meter (KDY-1), Hall effect measurement system (Lakeshore 7704A), and LCR meter (Agilent U1731B). The mechanical force in the stretching test was conducted by an electromechanical universal testing machine .The graphene films were characterized by Raman spectroscopy  with an Ar−1 representing the D, G, and G′ modes of representative graphene vibration, respectively. The obvious G peak and sharp G′ peak indicate the formation of graphene. The IG′/IG ratio for two samples is greater than two , which confirms monolayer graphene film. Meanwhile, the G′ bands with the full width at half maximum around 30 cm−1 demonstrate the uniformity of monolayer graphene film [ID/IG ratio, comparing the black curve of 0.11. It means that the gradient flux of methane in the process of graphene growth is beneficial to decrease the defects and improve the quality of graphene.The Raman spectroscopy was used to demonstrate the composition of graphene film. Figure ene film . The weaene film , 19. TheFigure The transferred graphene over the ITO electrode on PET substrate was observed by scanning electron microscope (SEM) image and optical image, as shown in Fig. The sheet resistance of all samples was measured by four-probe meter and Hall effect measurement system. Other measured results were listed in Table To investigate the electromechanical properties of graphene/ITO hybrid electrode, bending and stretching tests were performed. Experiments were repeated three times for each group above. Figure R/R0 to evaluate the trend. Among them, the R0 stands for the original and flat sample resistance with dimension of 1 × 1 cm2 and △R refers to the resistance change compared to R0. Figure R/R0 of the samples as a function of the applied tensile strain. The resistance of samples rises up as tensile strain increases. Before the 5 % tensile strain, the value of the three electrode △R/R0 is nearly square. For clearly distinguishing the difference, the data was shown in a log scale in the inset image. After 10 % tensile strain, the brittle property of ITO is evident. Unlike the ITO electrode, the graphene electrode could resist up to 20 % strain with △R/R0 of ~3.28 compared with that of ~125.91 for ITO at the same strain. Likewise, the hybrid graphene/ITO electrode is well performed with △R/R0 of ~17.78. The result demonstrates the pronounced advantage of graphene in protecting ITO brittle failure to some extent. It could be possible to take use of graphene hybrid conductors in flexible transparent electrode.In real time while observing the electrical change under stretch and bending process, we made lap joints (in electrodes) on the edge of sheet samples. The connector of LCR meter then bit the joint while the mechanical force conducted on samples. We recorded the real-time resistance data and calculated the value of △A comparative experiment for resistance change trend measurements was also performed under stable bending process at different curvature. The bending radius was measured by the scale, which is shown in Fig. In summary, this work demonstrates a feasible two-step process method to employ the CVD graphene in fabricating the graphene/ITO flexible hybrid transparent electrode. With this method, as-fabricated graphene shows lower defect and improves the mechanical stability of single ITO electrode. Such hybrid electrode makes a significant advancement toward traditional transparent flexible film both in electrical and optical properties. The hybrid method meets the criteria of low cost, conductivity, and mechanical stability. The graphene/ITO hybrid film as a flexible transparent electrode has important implications for future devices.


Graphene has been considered as a promising material for opto-electronic devices, because of its tunable and wideband optical properties. In this work, we demonstrate electro-refractive phase modulation in graphene at wavelengths from 1530 to 1570 nm. By integrating a gated graphene layer in a silicon-waveguide based Mach-Zehnder interferometer, the key parameters of a phase modulator like change in effective refractive index, insertion loss and absorption change are extracted. These experimentally obtained values are well reproduced by simulations and design guidelines are provided to make graphene devices competitive to contemporary silicon based phase modulators for on-chip applications. The most widely used approach for realizing phase modulators in integrated Si photonic systems is based on p-n junctions (depletion or injection type) which provides high-speed performance enabling the generation of data rates up to 60 GBit/s4In modern optical high-speed communication systems, phase shift keying is the standard method for data modulation1Graphene, a two dimensional allotrope of carbon, is considered as a promising material for a wide range of photonic applications81011121314In this work, we report on the experimental demonstration of a broad-band electro-refractive phase modulator using graphene as active material. Key parameters of this device such as insertion loss, change in effective refractive index, and change in absorption are extracted from the experiments and simulations have been performed reproducing these values. The results are then compared to the state-of-the-art Si modulators using the typical figure of merits and an outline is given for realizing graphene modulators that can significantly outperform current Si based phase modulators.We use a stack of graphene-oxide-graphene embedded into one arm of a Si waveguide based Mach-Zehnder interferometer (MZI), where graphene is located in the evanescent field of the Si waveguide. The chemical potential of the graphene is changed electro-statically by biasing the two graphene layers with respect to each other. Therefore, the effective refractive index of one MZI arm is changed which causes a shift in the transfer function of the MZI.2O3 were deposited with atomic layer deposition (ALD) at 300 °C using O2 plasma and trimethylaluminium (TMA) as precursors. 2O3. A single layer of CVD grown graphene was transferred to the sample by the PMMA transfer method172O3 at 150 °C using water vapors and TMA as precursors, a second CVD grown single layer graphene, which acts as counter electrode, was transferred, contacted, and patterned using the same methods described for the first layer. In order to passivate the second graphene layer, another 40 nm of Al2O3 were deposited. Finally, vias were etched through the Al2O3 layers wet chemically to access the two nickel electrodes. An optical image of the final device is shown in 16172O3 on the sample (black spectrum), ii) after the first graphene layer was transferred, patterned, contacted, and covered by 90 nm Al2O3 (green spectrum) and iii) the final device (blue spectrum) with two graphene layers. These transmission spectra demonstrate clear interference pattern with a high extinction ratio of >15 dB for each mentioned step.All optical and electro-optical measurements were carried out in air at room temperature using a tunable continuous wave laser (1520–1620 nm) with 1 mW optical output power. To analyze the effect of each fabrication step on the transmission spectrum, the device was characterized at each stage of fabrication by measuring the transmitted optical power as a function of wavelength. 2O3 on top, the extinction ratio reduced from 22.5 dB to 17.5 dB  in between the two graphene layers. −4.where L, d and Δλ are the graphene length (200 μm), the spacing between minima (6.6 nm), and the wavelength shift with voltage V, respectively. 2/H2O redox couples at the graphene/dielectric interface23In an MZI, the change in absorbance Δα in one arm can be determined from the change in extinction ratio. As can be seen in 2O3 are taken from literature182-Si-HSQ-Al2O3-graphene-Al2O3 is considered with refractive indices of 1.44-3.48-1.38-1.64-ng-1.64, respectively  with TE mode propagating along the non-planar waveguide, which is an idealized situation of the stack used in the experiments. In the simulations, the complex optical conductivity of graphene (σ) is expressed as sum of intra-band and inter-band contributions which are determined using Kubo formalism given by27In addition to the experiments, simulations of the optical properties of the waveguide-graphene stack have been performed to get complementary information on the main optical parameters extracted in the experiments  and to explore the parameter space in terms of chemical potential and mobility. The simulations are based on the complex optical conductivity of graphene, which depends on the Fermi energy, the scattering rate and the temperature, and have been carried out using finite difference method in MATLABF) are taken as 300 K, and 0.9 × 106 ms−1, respectively10c, ξ, e, ω, ħ, kB and fd are the carrier scattering rate, chemical potential, energy, electron charge, radian frequency, reduced Planck’s constant, Boltzmann constant and the Fermi-Dirac distribution, respectively. In the simulations, Γ is varied from 5e11 to 1e14 s−1 in order to recognize its effect on the optical properties. These scattering rates correspond to charge carrier mobilities (μ) of 270 to 54000 cm2/Vs at μc = 0.3 eV /(ΓμC )), which are typically found in real devices. Since graphene was found to be p-doped for our device, the simulations have been discussed only for negative electro-chemical potentials here. However, the optical conductivity of graphene is symmetric for positive and negative electro-chemical potentials due to symmetric band structure in graphene1029where temperature (T), and Fermi velocity (vg (and hence refractive index ng) of graphene is related to its optical conductivity byThe dielectric constant εg = 0.33 nm is the thickness of graphene and ε0 is the permittivity of free space. Using finite difference method, values of neff and absorption have been calculated from eigen-solution of Maxwell equationwhere t2-Si-HSQ-Al2O3-graphene-Al2O3 stack. The eigen-solution of above Maxwell equation gives complex eigenvalues, with the real and imaginary parts representing neff and absorption, respectively. The simulated values of neff and absorption are plotted in c = 0 eV, independent on Γ and in good agreement to experimentally obtained value of 0.01 dB/μm. At μc < −0.4 eV a strong dependency of absorption on Γ is observed, as intra-band absorption becomes the dominating process there. In this regime, low Γ, corresponding to high carrier mobility, gives a lower absorption. In contrast to the absorption, neff shows only a dependency on Γ at the maximum value of neff around μc ~ 0.4 eV, and is effectively independent on Γ for higher and lower μc as is clear from where ∈ is dielectric permittivity tensor which takes into account refractive indices of SiOAfter the measured and simulated values of the graphene based phase modulator have been presented, a comparison with silicon based phase modulators can be given using different common figures of merit. We first start to discuss two important intrinsic figures of merit, which do not depend on the exact device layout, but only depend on the doping level and the scattering parameter in graphene, i.e. the insertion loss for a certain phase change and the ratio of change in refractive index to the change in absorption.c| > 0.5 eV, the absorption is significantly reduced due to Pauli-blocking of the inter-band contribution. The insertion loss of a scaled phase modulator, which can perform a phase shift of π, would be only 2 dB at μc = −0.6 eV and Γ= 1.25e13 s−1 (μ = 1080 cm2/Vs at μc = −0.6 eV). Here, lower Γ, i.e. higher carrier mobility, leads to an even lower insertion loss. This would be an improvement compared to Si MZI based phase modulators having an insertion loss of at least 4 dBFor the phase modulator realized in this work, the insertion loss caused by the intrinsic graphene absorption is 2 dB, while a phase shift of π/20 was achieved. This means that for a scaled device, which can perform a phase shift of π, the insertion loss would be ~40 dB, which is not acceptable for practical applications. These values are in good agreement to the simulations. In addition, the simulations suggest that at higher doping levels where |μ−1 (μc is varied from 0 to approximately −0.35 eV in our experiments). These scattering rates correspond to a carrier mobility of 500–1000 cm2/Vs at μc = −0.3 eV, a mobility typically measured in reference devices using the same fabrication process. The low Δn/Δα of 0.1 μm/dB means that for obtaining a phase shift of π, the light intensity is changed by 10 dB, which is unacceptable for most applications demanding constant light intensity. Again our simulations suggests that a significant improvement can be expected either for lower Γ or for higher doping levels where |μc|> 0.5 eV. Under these conditions, Δn/Δα can reach excellent values being larger than 1 μm/dB  are required. Such high doping levels are realizable with molecular doping3314In conclusion, an electro-refractive phase modulator, operating in the wavelength range of 1530-1570 nm, is realized experimentally using graphene as active material. Key parameters of the modulator such as absorption, Δn and Δα have been extracted from the experiment and reproduced with simulations. While the parameters obtained from experiments are far behind state-of-the-art Si based phase modulators, the simulations suggest that outstanding parameters for phase modulation can be achieved using graphene as active material. This requires first an enhanced interaction of the graphene with the waveguide mode and a stronger dielectric coupling between the two graphene layers in order to achieve competitive values of VHow to cite this article: Mohsin, M. et al. Experimental verification of electro-refractive phase modulation in graphene. Sci. Rep. 5, 10967; doi: 10.1038/srep10967 (2015).


The effects of substrate positions and graphene thicknesses on the morphological, structural, and optical properties were found to be very pronounced. By setting the substrate to be inclined at 90°, the growth of ZnO nanostructures, namely, nanoclusters and nanorods, on single-layer (SL) graphene was successfully realized at temperatures of 600°C and 800°C, respectively. For the growth on multilayer (ML) graphene at 600°C with an inclination angle of 90°, the grown structures show extremely thick and continuous cluster structures as compared to the growth with substrate’s inclination angle of 45°. Moreover, the base of nanorod structures grown at 800°C with an inclination angle of 90° also become thicker as compared to 45°, even though their densities and aspect ratios were almost unchanged. Photoluminescence (PL) spectra of the grown ZnO structures were composed of the UV emission (378–386 nm) and the visible emission (517–550 nm), and the intensity ratio of the former emission (IUV) to the latter emission (IVIS) changed, depending on the temperature. The structures grown at a low temperature of 600°C show the highest value of IUV/IVIS of 16.2, which is almost two times higher than the structures grown on SL graphene, indicating fewer structural defects. The possible growth mechanism was proposed and described which considered both the nucleation and oxidation processes. From the results obtained, it can be concluded that temperature below 800°C, substrate position inclined at 90° towards the gas flow, and ML graphene seems to be preferable parameters for the growth of ZnO structures by thermal evaporation because these factors can be used to overcome the problem of graphene’s oxidation that takes place during the growth.A seed/catalyst-free growth of ZnO on graphene by thermal evaporation of Zn in the presence of O Grap103 W/mK -18. Ther103 W/mK ,20. It iSince a decade ago, intensive researches have been focused on fabricating one-dimensional (1D) zinc oxide (ZnO) semiconducting nanostructures because it can provide a variety of important applications due to their unique morphologies, compositions, and chemical/physical properties ,22. For 2) gas [The most common method to grow ZnO on graphene is thermal evaporation due to its simplicity and high growth rates. Recently, we reported the seed/catalyst-free growth of ZnO on multilayer (ML) graphene by thermal evaporation of Zn in the presence of oxygen (O2) gas . The eff2) gas .2)/Si were used as the substrates . Figure 2. The growth was carried out by thermal evaporation technique in dual zone furnace as shown in Figure 2) gas (99.80%) were used as the sources. Prior to the growth process, the substrate was treated with organic cleaning of ethanol, acetone, and deionized (DI) water to remove any unwanted impurity on the substrate. Zn powder of approximately 0.6 g was spread evenly into a ceramic boat. The ceramic boat was placed in the zone 1 of furnace while the substrate was placed with inclination angles of 45° and 90° facing towards the flow of O2 gas in the zone 2 of furnace. The distance between source and substrate was fixed at 23 cm. This is a distance from center-to-center of two zones. Two independent temperatures were applied to the furnace system. Here, T1 denotes to the set temperature (ST) of the source while T2 denotes to the ST of the substrate. Firstly, the temperature of zone 2 was raised to T2  in argon (Ar) environment (Ar flow rate of 200 sccm). Then, the temperature of zone 1 was raised to T1 . The flow of Ar was stopped when the temperature of zone 1 reached 400°C . This was done in order to avoid the transfer of Zn particles to substrate prior to actual growth. The heating of Zn powder was continued until it reached 1,000°C. It was confirmed from several attempts that such high temperature of 1,000°C was needed for continuous and constant evaporation of Zn. After reaching 1,000°C, O2 (400 sccm) was introduced for 1 h of growth time. Finally, the furnace was turned off and the samples were cooled down to room temperature. It is noted here that the above procedures are identical with the procedures reported in ref. [Two kinds of graphene structures, i.e., single-layer (SL) graphene and ML graphene, grown by chemical vapor deposition (CVD) and transferred onto silicon dioxide  was calculated. Figure Figure 2 gas is introduced into the system. This oxidation process seems to be faster than the nucleation of Zn particles when the position of substrate is inclined to 45°. This can be proved where no nucleation of ZnO was obtained for the growth on 45°-inclined SL graphene, but the growth was successfully realized on 90°-inclined SL graphene. It is also speculated that 90°-inclined position seems to help in increasing the nucleation rates. As mentioned in the previous section, the nucleation of Zn on ML graphene is also promoted by the availability of graphene stacking structures which provide graphene edges as the additional nucleation sites [As reported in ref. , the nucon sites , the temon sites .Figure 6In conclusion, the effects of substrate position and graphene thickness on the morphological, structural, and optical properties were found to be very pronounced. Substrate position with an inclination angle of 90° seems to be one of the effective control parameters to increase the nucleation rates which were proven by the ability to grow ZnO nanostructures on SL graphene as well as the growth of thick and continuous ZnO cluster structures and thick base structures of ZnO nanorods on ML graphene. The structures grown at a low temperature of 600°C show fewer structural defects. The possible growth mechanism is proposed and described which considered both the nucleation and oxidation processes. Not only temperature but also substrate position and graphene thickness play significant role in determining the properties of the grown ZnO structures by thermal evaporation because these factors can be exploited to overcome the problem of graphene’s oxidation that takes place during the growth.