Generation of electric voltage in a conductor by applying a temperature gradient is a fundamental phenomenon called the Seebeck effect. This effect and its inverse is widely exploited in diverse applications ranging from thermoelectric power generators to temperature sensing. Recently, a possibility of thermoelectricity arising from the interplay of the non-local Cooper pair splitting and the elastic co-tunneling in the hybrid normal metal-superconductor-normal metal structures was predicted. Here, we report the observation of the non-local Seebeck effect in a graphene-based Cooper pair splitting device comprising two quantum dots connected to an aluminum superconductor and present a theoretical description of this phenomenon. The observed non-local Seebeck effect offers an efficient tool for producing entangled electrons. Thermoelectricity due to the interplay of the nonlocal Cooper pair splitting and the elastic co-tunneling in normal metal-superconductor-normal metal structure is predicted. Here, the authors observe the non-local Seebeck effect in a graphene-based Cooper pair splitting device. Thermoelectric effects in the superconducting systems22, in particular those dealing with non-local thermoelectric currents in superconductor–ferromagnet devices25 and in bulk non-magnetic hybrid NSN structures28 have attracted special attention. The connection between thermoelectric effects and the Cooper pair splitting (CPS)2, proposed in ref. 29, established a mechanism for the coherent non-local thermoelectric effect in hybrid superconducting systems. This connection was further studied and explicitly described for a ballistic NSN structure4. It was revealed analytically in ref. 4 that the electric transport in the NSN structures depends on the elastic co-tunneling (EC) process on par with the CPS. Contrary to intuitive expectations, together these two processes may enable the transfer of heat through the superconductor5. The EC and CPS probabilities can in turn be made energy dependent by placing quantum dots between each normal lead and the superconducting region2.Mesoscopic thermoelectric effects have been investigated in a variety of condensed matter systems that, besides fundamental normal metal–superconductor–normal metal (NSN) systemsHere we present the experimental observation of the non-local thermoelectric current generated by imposing thermal gradient across a quantum dot–superconductor–quantum dot (QD-S-QD) splitter. We find that both CPS and EC processes contribute to the non-local thermoelectric current and that their relative contributions can be tuned by the gate potentials. The ability to tune between the CPS and EC allows for testing of fundamental theoretical concepts relating entanglement and heat transport in the graphene CPS systems.E∣ < Δ, we find, see Supplementary Note τEC(E), and CPS, τCPS(E), probabilities are given by the expressionsτL(R)(E) is the transmission probability of the left (right) quantum dot renormalized by Coulomb interaction, which depends on the energy of an electron and on the side gate potentials applied to the dots Vsg,L(R) (τL(R)(E) is given by the sum of Lorentzian peaks or Fano resonances associated with discrete energy levels, see Supplementary Note τS is the effective transmission probability of the superconducting lead. The latter corresponds to the probability for an electron coming out of one dot so that, instead of escaping into the bulk of the superconducting electrode, it reaches the other dot. It becomes independent on the electron energy E if the dots are separated by a distance shorter than the superconducting coherence length. This condition is reasonably well fulfilled in our experiment. The non-local thermoelectric currents in the dots can, in turn, be expressed in terms of the EC and CPS contributions, TL(R).Let us consider an QD-S-QD device within the Landauer formalism. Taking that the non-local transport is primarily coherent and that the electron energies are smaller than the superconducting gap, ∣37, and particularly promising results have been obtained in carbon nanotube, graphene, and nanowire settings, where the splitting efficiencies approaching 90% have been observed. Our present device, depicted in Fig. Isw(T)38. The resistive heater comprises the graphene nanoribbon and two attached aluminum leads. The heater is distinctly apart and electrically isolated from the rest of the device, the heat to the Cooper pair splitter being transmitted through the substrate.Now, we turn to experimental realization of CPS and EC. Several material platforms have been employed in the experimentsT = TL − TR between the leads of the two-terminal device induces the thermoelectric current I = αGΔT, where G is the conductance of the device and α is the Seebeck coefficient39. For typical metals, such as aluminum or copper, the Seebeck coefficient is quite small, α ~ 3−7 μV/K. For graphene, α is inversely proportional to the square root of charge density, and it can reach much higher values close to the charge neutrality point41. In quantum dots with energy-dependent electron transmission probability42, and in superconductor–ferromagnet tunnel junctions25 large α up to a few kB/e ~ 100 μV/K can be achieved. In our experiment, we observe similar values of the Seebeck coefficient in graphene quantum dots. We operate the graphene heater at frequency f = 2.1 Hz and record thermoelectric currents through both quantum dots at the double frequency 2f (see “Methods”). Thermal gradient induced by the heater is measured by SGS thermometers, which were calibrated separately as discussed in Supplementary Note The temperature difference ΔIL(R), we subtract off its slowly varying average local background, 〈IL(R)〉 (see “Methods”):Vh = 5 mV. In Fig. gL(R) = hGL(R)/e2 is the dimensionless conductance of the left (right) quantum dot. We find that gL/dVsg,L]gR.The thermoelectric current induced by the heater in the left (right) quantum dot is given by the sum of dominating local  between the nth energy level of the dot  and, respectively, normal and superconducting leads; we also assume that the nth level is coupled to a dark energy level, having the energy tj,n. This results in the transmission probabilities of the dots 43, exhibit splitted peaks for tj,n ≠ 0. In our model, we ignore Coulomb interaction because the charging energies of the dots are relatively small, EjC, ≲ γj,n + Γj,n.Before proceeding to our main result, note that some conductance peaks are split into two closely located peaks see Fig. . The splVsg,R = −1.24 V. Although in order to reproduce this behavior we had to take hopping amplitude, tR, larger than required by the perfect fit to the conductance peak /2 in evaluating 44; the same theory was earlier employed in deriving the non-local contributions using Eq.  is inferred from the experimentally measured conductance gL, as explained in Supplementary Note Since, as noted, the non-local currents are relatively small, one can treat the measured currents foremost as local, entclass1pt{minimaIn the low temperature regime, the coherent model predicts very small current due to lack of quasiparticles, while the experimental thermoelectric current remains significant and exhibits additional sign changes in the vicinity of some of the conductance peaks. These features can originate from non-zero, thermally induced voltages across the dots. To capture these effects, we propose that electrons may undergo quick inelastic relaxation, see Supplementary Note 5 as the non-local thermoelectric effect is shown to develop from single peak to double peak structure when temperature is lowered5. The calculated double peak structure is similar to our local thermoelectric signal observed at low temperatures. However, the resonance energy dependence of the non-local signal with Coulomb blockade agrees poorly with the experimental results in Fig. Alternatively, the additional peak in the local thermoelectricity could originate from Coulomb blockadeThis work has demonstrated the use of thermal gradient as primus motor for generating entangled electrons in graphene Cooper pair splitter. As the quantum dots in the device can be tuned individually, we are able to tune the device operation between EC and CPS regimes, thereby accomplishing direct control of two streams of entangled electrons. This type of scheme is useful not only for enabling devices where electrical drive is neither possible nor desired but also as a platform for realizing quantum thermodynamical experiments.++ doped silicon wafer, coated by 280-nm-thick thermal silicon dioxide. The conducting substrate was employed as a backgate for coarse tuning of the graphene quantum dots, while fine tuning was performed by adjusting the side gates. Electron beam lithography (EBL) on PMMA resist was used to pattern a mask for plasma etching of the graphene structures. A second EBL step was carried out to expose the pattern for electrode structures, followed by deposition of Ti/Al  leads using an e-beam evaporator. Normal contacts to the graphene quantum dots were made using etched graphene nanoribbons with a small number of conductance channels at the operating point45.Our graphene films were manufactured using mechanical exfoliation of graphite  and placed on a highly p++ doping and the interfacial scattering at the Si/SiO2 interface reduce the phonon mean free path in the substrate to one micron range, which facilitates the use of the heat diffusion equation for estimating thermal gradients along the substrate near the graphene ribbon heater and the splitter. Heat transport analysis was done separately for each component involved in the operation of the CPS, as well as a COMSOL simulation, see Supplementary Note The strong p6 V/A, which provides a virtual ground of 20 Ω. The lead resistance including filters was approximately 100 Ω, which is much less than the quantum dot resistance ~h/e2, the quantum resistance. The galvanically separated heater was driven at f = 2.1 Hz, with an ac voltage amplitude ranging between 1 and 40 mV  were experimentally found to provide good thermometers over the relevant range of temperatures in our work.The local temperature was monitored using two SGS junctions. At low temperature, because of the proximity effect, graphene becomes superconducting, with a supercurrent exponentially proportional to temperature: T to infer the effective local temperature within the graphene sample. The SGS temperature under the voltage bias Vh in the graphene ribbon heater was obtained by direct comparison between L temperature and the heating voltage (Vh in Volts). For the SGSR thermometer, we obtained an estimate We have used the amplitude of the differential resistance peak entclass1pt{minimaIL(R), constituting the sum of local, IL(R) averaged over the gate voltage on the opposite dot; IL(R). On practice, however, the gate electrodes may be subject to cross-talk, which the described simple processing does not account for. For the most part, the cross-talk was eliminated by a small rotation of the data array. Bearing in mind the remaining residual cross-talk, we construct a slowly varying background Vsg,R. The non-local contribution is then obtained using the formulaVsg,L, Vsg,R} plane.The direct experimental measurement allows to obtain the total electric current through the left (right) dot, 46 for calculating the local thermoelectric current; Lorentzian resonance line shapes are employed for transport in the quantum dots48. For the non-local current, we employ a standard crossed Andreev reflection formalism51. In our incoherent theory, based on scattering matrix formalism52, we also include the influence of internal thermally generated current sources and their back-action effect owing to the environmental impedance caused by graphene ribbons. The inclusion of the back-action-induced voltage sources makes the incoherent calculation self-consistent. For details of the calculations, we refer to Supplementary Notes Our theoretical calculations are based on both coherent and incoherent modeling of transport. In coherent modeling, we employ the Landauer approach with Andreev reflectionSupplementary InformationPeer Review File


Background. Muscle synergy analysis is an approach to understand the neurophysiological mechanisms behind the hypothesized ability of the Central Nervous System (CNS) to reduce the dimensionality of muscle control. The muscle synergy approach is also used to evaluate motor recovery and the evolution of the patients’ motor performance both in single-session and longitudinal studies. Synergy-based assessments are subject to various sources of variability: natural trial-by-trial variability of performed movements, intrinsic characteristics of subjects that change over time , as well as experimental factors such as different electrode positioning. These sources of variability need to be quantified in order to resolve challenges for the application of muscle synergies in clinical environments. The objective of this study is to analyze the stability and similarity of extracted muscle synergies under the effect of factors that may induce variability, including inter- and intra-session variability within subjects and inter-subject variability differentiation. The analysis was performed using the comprehensive, publicly available hand grasp NinaPro Database, featuring surface electromyography (EMG) measures from two EMG electrode bracelets. Methods. Intra-session, inter-session, and inter-subject synergy stability was analyzed using the following measures: variance accounted for (VAF) and number of synergies (NoS) as measures of reconstruction stability quality and cosine similarity for comparison of spatial composition of extracted synergies. Moreover, an approach based on virtual electrode repositioning was applied to shed light on the influence of electrode position on inter-session synergy similarity. Results. Inter-session synergy similarity was significantly lower with respect to intra-session similarity, both considering coefficient of variation of VAF  and coefficient of variation of NoS  as well as synergy similarity . Virtual electrode repositioning revealed that a slightly different electrode position can lower similarity of synergies from the same session and can increase similarity between sessions. Finally, the similarity of inter-subject synergies has no significant difference from the similarity of inter-session synergies (both on average approximately 84–90% depending on selected VAF). Conclusion. Synergy similarity was lower in inter-session conditions with respect to intra-session. This finding should be considered when interpreting results from multi-session assessments. Lastly, electrode positioning might play an important role in the lower similarity of synergies over different sessions. The way in which the central nervous system (CNS) controls and coordinates many muscles in voluntary movements is a longstanding question . Muscle Referring to neurorehabilitation, several efforts were made in previous studies to characterize the patients’ EMG patterns with muscle synergies. It was shown that lower motor function (reduced Fugl–Meyer assessment scores) might be coupled with a reduction in the number of available synergies ,16. FurtIn this context, it was shown that several aspects related to the evaluation of motor recovery and the evolution of the patients’ motor performance may be quantified with muscle synergies, both in single-session and longitudinal studies. In fact, synergy-based assessments require extracting muscle synergies from data recorded in different experimental conditions and/or sessions and subsequently matching and comparing them for purposeful assessments. Thus, the results need to be interpreted considering the effect of intra-subject and inter-subject variability as well as intra-session and inter-session variability. Variability can be defined in this context as a set of similarity-based metrics to compare synergies across experimental conditions. Intra-session factors for variability include natural trial-by-trial variability of performed movements . On the These challenges have only been partially addressed in literature. The effect of some of these sources of variability on extracted muscle synergies was already emphasized in several studies on healthy people, when assessing upper-limb intra- and inter-subject synergy composition similarity ,21,22 orSeveral aspects related to the variability found in muscle synergies can be analyzed in more detail to provide an assessment preparatory to rehabilitation applications. More specifically, this study aims at quantifying the sources of variability of muscle synergy composition that are related to inter-subject variability as well as intra-subject variability separated into intra-session (different movement repetitions) and inter-session (different acquisition sessions). We decided to assess these features first on a dataset of healthy participants under the assumption that, in each session, the motor capabilities of the subjects recruited were the same. The analysis was performed using as a testing scenario the comprehensive, publicly available hand grasp NinaPro Database (dataset number 6), featuring surface EMG measures from two EMG electrode bracelets, placed at the forearm level ,29. At tBy analyzing robustness, stability and similarity of extracted muscle synergies under the effect of factors that may induce variability , this work contributes to the knowledge available regarding the clinical usability of muscle synergies. The presented results are application specific, since electrode repositioning is simulated and constrained to a bracelet configuration of electrodes that was used for the NinaPro database. Nevertheless, through this methodology, we give a preliminary assessment of the possible influence of electrode position on the stability of muscle synergies in hand grasps, possibly estimating the effects of electrode movement and subject variability.A graphical overview of the data analysis performed in the study is shown in The NinaPro database  is availThe set of hand grasps was chosen from the robotic and rehabilitation literature with the goal of covering several hand movements exploited in activities of daily living (ADL) ,35,36. TSurface EMG was recorded with 14 Delsys Trigno sEMG wireless electrodes as shown in EMG data were sampled at 2000 Hz. The recorded signals correspond to the entire movements. The subjects were asked to sit in front of a table with the forearm leaning on it. The grasp to be executed was shown in two videos and then a set of audio indications explained the tasks to be performed . A fixed image representing the grasp was shown on the screen of the laptop during the experiment. The number of repetitions was equally distributed among two different objects. Each repetition lasted for 4 s and was followed by 4 s of rest .The first step of data analysis was detecting the movement phases and aligning movement repetitions for each condition, grasp and subject considered. Moreover, data were preprocessed in several steps, with a preprocessing pipeline similar to the one employed in recent studies ,41. EMG For each condition  and subject, muscle synergies were extracted from concatenated EMG data of all exercises using nonnegative matrix factorization (NNMF) ,43.NNMF was repeated for a fixed number of extracted synergies ranging from 1 to the number of recorded EMG channels (14). Since NNMF is stochastic, analysis was repeated 50 times ,44 with In order to compare synergies from different conditions , we set up a brute force algorithm enabling to produce meaningful synergy matching after NNMF . The algWe classified several aspects of synergy stability and robustness, which we achieved by decomposing the NinaPro dataset as illustrated in Intra-session analysis focused on a comparison of synergies that were extracted from movement repetitions within the same session. Synergies were extracted from 6 randomly selected repetitions of movements out of the 12 available that were recorded in each session see . ExtractInter-session analysis focused on comparing metrics related to extracted synergies from different sessions. To achieve this result, all 12 repetitions of movements from the same session were concatenated and used to extract synergies of that session. The synergy sets of 5 sessions of each subject were compared see .The aim of this analysis was to assess the role of electrode positioning as a source of difference between inter-session and intra-session similarity of synergies. Placing electrodes in a slightly nonrepeatable way between sessions can happen in real scenarios and has been mentioned already as a possible reason for lower inter-session similarity and stability of synergies with respect to intra-session assessments .The NinaPro dataset 6 (Ninapro DB6) is a valuable resource to study the effect of electrode positioning on muscular hand synergies, and to our knowledge, no other publicly available datasets include the repetition of the same electromyography acquisition protocol in different sessions. The NinaPro DB6 contains recordings performed during 10 acquisition sessions with the EMG electrodes positioned in a bracelet configuration. The electrode configuration allows to simulate slight electrode displacements by artificially calculating values of EMG data from the recorded channels. The electrodes in each bracelet were equally spaced, and the bracelets were positioned according to anatomical landmarks. A first approximation to simulate the misplacement of the electrodes is to assume that each electrode in the same bracelet was rotated medially or laterally by the same distance. Thus, expected differences in rotation could be due to the possibility that the electrodes were misplaced by a few millimeters to the medial or lateral side according to the anatomical landmark. Again, a preliminary approximation to simulate the misplacement of the electrodes could be to assume that the misplacement can be approximated by linear interpolation of the EMG activity from adjacent electrodes. Similarly, in fact, each Delsys Trigno electrode detects sEMG at the skin surface by 4 silver bar contacts that are 5 mm large and positioned a few millimeters from each other. Obviously, this approach is a strong simplification of the electrode misplacement problem. The real change in the recorded muscle activity is likely nonlinear due to muscle physiology, as well each electrode is likely moved singularly further or closer to the anatomical landmark. Nevertheless, the simplification is justified by the limits of the acquisition setup itself , and it was sufficient for the aim of this analysis .Five simulated step sizes were tested  accordinDuring the recordings of Ninapro DB6, the equipment consisted of two electrode bracelets; both of them could, in theory, be moved for different step sizes or even in different directions. It follows that the number of possible movement combinations exponentially increases. Thus, at the present stage, we decided to limit our analyses to the more proximal bracelet including only the first 8 electrodes  and assume that all 8 electrodes were moved by an equal step size in the same direction.New artificial EMG data were created by linearly interpolating EMG recordings from two neighboring electrodes using the formula and schematics shown in The analysis was performed as follows: (1) From the original data, new artificial data were created by interpolating new channels for steps of −8 mm, −4 mm, 0 mm, 4 mm, and 8 mm. This simulation was performed for each participant and each session. (2) For each electrode displacement step, synergies were extracted with NNMF from all steps of all sessions of each participant. (3) Matching was performed between extracted synergies. Depending on the purpose of the analyses, synergies were matched according to specific criteria  as shown in First, we computed variance accounted for (VAF) curves depicting how VAF changes, when an increasing number of synergies was extracted with the NNMF algorithm for different sessions (inter-session) and different sub-selections of movements for the same sessions (intra-session). VAF values were used as a measure of the quality of reconstruction of the data. Furthermore, we analyzed the number of synergies (NoS), which was also employed as a measure of synergy stability . Since iIn order to quantify variability of VAF and NoS among sub-selections of movements or between sessions, the coefficient of variation (CoV) was used. It is a measure of the dispersion of data points around the mean. Subsequently, CoV was calculated for inter-session and intra-session VAF curves and NoS values. The inter-session dataset was created by computing the VAF (and NoS) values for each of the 5 sessions of each subject, whereas intra-session dataset was achieved by computing the VAF (and NoS) values for 5 movement sub-selections (containing 6 movement repetitions) inside the same session . To get representative intra-session CoV for each subject, 5 CoV from 5 sessions were averaged. In this way, our dataset was composed of 10 CoV for VAF values (one per subject) for each number of extracted synergies (1 to 14) and for each experimental condition (intra and inter) as well as 10 CoV for NoS values (one per subject) for each VAF value and for each experimental condition (intra and inter). In order to investigate the difference between the amount of variability intra-session compared to inter-session condition, the difference in the CoV values was assessed using two-way repeated measures ANOVA using condition type (inter and intra) and VAF (or NoS) as factors.Synergies in intra- and inter-session conditions were compared also according on their spatial composition.The inter-session synergy similarity assessed how similar is the spatial composition of synergies between different sessions in which an individual performed the same sets of movements. EMG data were extracted and filtered from each session individually, followed by the matching of synergies from 5 sessions. The most similar synergies between days, found with the “brute force” matching algorithm  was performed. Analysis was repeated for each session and each participant. Intra-session similarity of each subject was determined as the average of intra-session similarities of all 5 sessions for this subject. In this way, our intra-session dataset for spatial synergy similarity was composed of 10 average matching values (one per subject representing average of 5 sessions) for each VAF value. Since the aim of these analyses was to investigate the relationship between the amount of variability due to intra-session variability and inter-session variability, we tested our dataset to determine the difference in the average spatial synergy matching values between the two conditions (inter and intra) using condition and VAF as factors.Intra-session virtual electrode repositioning (IntraSessVER)The first step for our analysis was to investigate if a different synergy similarity is detected when slightly repositioning electrodes within the same session. This finding can confirm that electrode repositioning might influence synergy similarity and serves as motivation for the following steps of the analyses.To achieve this, we created a simulated dataset to compare muscle synergy similarity from different virtual electrode positions for the same session. We compared average similarities for all possible repositioning distances . This was repeated for all VAF values. Maximal similarity of synergies (MAX) between any two steps of rotations for each session (and subjects), average similarities (AVRG) between all step pairs, and minimal similarities (MIN) were calculated. MAX values represented, for each subject, the average (computed across 5 sessions) of maximum similarities detected between different electrode positions within each session. To achieve AVRG value similarity, values of all step pairs in each of the sessions were averaged (for each subject). Finally, MIN values represented the average (computed across 5 sessions) of minimum similarities for each subject detected for any combination of electrode positions within same session. In this way, our IntraSessVER dataset was composed of 10 AVRG, 10 MIN, and 10 MAX matching values (one for each subject representing an average of 5 sessions) for each VAF value.Inter-session virtual electrode repositioning (InterSessVER)Here, we aimed to assess if repositioning electrodes virtually between sessions can lead to higher similarity between sessions. If this condition was met, a part of the variability in the muscle synergy similarity that existed between sessions can be due to slightly different positions of electrodes. For each possible combination of two sessions, we created a simulated dataset computing the maximum muscle synergy similarity by calculating all combinations of steps for those two sessions. Maximum, minimum, and average similarities between different step pairs (25 combinations) and session pairs (10 combinations) were calculated for all the subjects. MAX values represented the highest similarity that each subject achieved between any two sessions having the option to also shift electrodes between sessions. MIN values reported the minimum value that each subject had between any two sessions. AVRG values were the average of MAX values found for each session pair, calculated for each subject. In this way, our InterSessVER dataset was composed of 10 ARVG, 10 MIN, and 10 MAX matching values (one for each subject) for each VAF value.Intra-session without electrode repositioning (IntraSessORIG)The intra-session dataset was created by computing the similarity of the synergies extracted from a different selection of movement repetitions but from the same session (no electrode repositioning). This was the same analysis as already described in Inter-session without electrode repositioning (InterSessORIG)The intersession dataset was created by computing the similarity of synergies between sessions. The dataset was analogous to the one described in Inter-subject (InterSUBJ)Finally, we considered a fifth condition that we labelled inter-subject . The following datasets were considered:Comp#1: to test whether significant differences existed between similarities of synergies extracted from the same sessions (IntraSessORIG) and synergies from different sessions (InterSessORIG) both without virtually repositioning of electrodes. This was analogous to the comparison in Comp#2: to test whether a significant difference exists in average values of similarities between intra-session (IntraSessORIG) and intra-session with different steps in virtual electrode repositioning (IntraSessVER). This allowed to show whether higher, lower, or comparable intra-session synergy similarity was achievable when electrodes are virtually repositioned.Comp#3: to test whether a significant difference exists between the average value of similarities of sessions with original positions (InterSessORIG) and sessions with the best electrode positioning combination (InterSessVER). This allows us to test whether on average it is possible to get higher inter-session similarity when allowing electrode displacement between sessions. In other words, is it possible that slight electrode repositioning between sessions is one of the factors influencing lower synergy similarity?Comp#4: to test whether a significant difference exists between maximal similarities that can be achieved for inter (InterSessVER) and intra-session (IntraSessVER) conditions while allowing electrode repositioning. This allows to test if, by moving electrodes between sessions, for any combination of sessions, it is possible to get similarity as high as with intra-session data.Comp#5: to test whether a significant difference exists between synergies of the same subject extracted in different sessions (InterSessORIG) when compared to synergies of other subjects (InterSUBJ). This investigation tests how well muscle synergies generalize between individuals with respect to the average inter-session similarity. The analysis was done in order to assess whether lower inter-session (with respect to intra-session) similarities impose serious concern for multi-session or longitudinal assessments. If inter-subject similarities were lower than inter-session ones, synergies contained subject specific information, but generalization of synergies between subjects may not be very high. On the other hand, if inter-subject similarities were on the same level (or higher) than inter-session, then the synergies generalize well between subjects but it is not possible to distinguish whether synergies are from the same subject but recorded during different sessions or from a completely different subject. This can be a serious point to consider for multi-session assessments.Given these 5 sub-datasets, the following comparisons were analyzed :For all the proposed objectives, the dataset was composed of 10 values for MAX, AVRG, and MIN value (one for each subject) for each VAF and condition. All the comparisons were repeated for 4 VAF levels: 80, 85, 90, and 95%.p-values were corrected if sphericity was not satisfied. All tests were performed in the statistical software R [Two-way repeated ANOVA measures were applied in the analyses. The used factors are the condition of the analysis  and VAF or NoS that were used as a criterion for extraction of muscle synergies. Mauchly’s test for sphericity was conducted, and ftware R  . The number of synergies also influenced stability (CoV) of VAF values  = 83.14, p < 0.001). The interaction between the type of comparison (inter vs. intra) and the number of synergies was also significant  = 48.28, p < 0.001).VAF and NoS vary between sessions and even for different movement repetition selections (not shown). In order to assess significance of this variation and to quantify the difference between inter- and intra-session variation, the coefficient of variation (CoV) was used. In p < 0.001). Similarly, VAF  = 13.71, p < 0.001) and interaction  = 10.8, p < 0.001) effects were also significant.Both from In p < 0.001). The VAF also has significant influence  = 7.34, p < 0.001) while interaction after sphericity correction is not significant  = 2.49, p = 0.12).In p < 0.001) after sphericity correction, as the distance is increased and stabilizes with bigger distances. There is also significant influence of VAF  = 37.74, p < 0.001) after sphericity correction and an interaction between VAF and distance  = 37.82, p < 0.001) after sphericity correction.In order to investigate why the inter-session similarity is significantly lower than intra-session similarity, a possible influence of electrode positioning was tested by simulating data from slightly different positions of the electrodes. Results are shown in The comparison of the similarity between different conditions and how they relate to each other is given as an example for a VAF value of 80%. For inter-session (InterSessORIG), average values (black) of synergy similarity between pairs of sessions were 0.841 ± 0.052, maximal values (red) of similarity between two sessions for different subjects were 0.942 ± 0.021, while minimal values (blue) were 0.722 ± 0.093. For intra-session (IntraSessORIG), these values were much higher, all above 0.9 . Average similarities of synergies between two people (InterSUBJ) were 0.837 ± 0.026. The highest similarity between two subjects was 0.940 ± 0.024. The lowest similarity between two subjects was 0.754 ± 0.018.When assessing changes in similarity, when electrodes were virtually moved within the same session (IntraSessVER), the highest similarity (for the given 5 steps) was 0.989 ± 0.003, while average values for different combinations of the steps were 0.824 ± 0.028 and minimal ones were 0.680 ± 0.052. When assessing whether similarity can be increased between sessions by comparing synergies from various positions (InterSessVER), the highest values obtained were 0.961 ± 0.020, average values were 0.912 ± 0.033, and minimal ones were 0.839 ± 0.063.p < 0.001) but without influence of VAF  = 0.94, p = 0.4 after sphericity correction) and significant interaction  = 7.96, p < 0.001).Comparing inter-session (InterSessORIG) and intra-session (IntraSessORIG) similarities without option to reposition electrodes (reported in p < 0.001). Also the VAF value  = 16.78, p < 0.001) and the interaction between type of comparison and VAF  = 36.79, p < 0.001 after sphericity correction) had a significant effect.A lower average similarity was found when electrodes were virtually moved (IntraSessVER) inside the same session with respect to the original inter-session similarity (IntraSessORIG) without moving electrodes. Similarity values for IntraSessORIG and IntraSessVER (reported in p < 0.001). While VAF also had a significant effect  = 4.89, p < 0.05 after sphericity correction), interaction was not significant  = 1.07, p = 0.36). This result suggests that it is possible that the lower similarity  was compared , Comp#3 milarity  Comp#1 tp < 0.001). Interaction had significant influence  = 6.55, p < 0.05 after sphericity correction), but VAF did not  = 0.91, p = 0.41).Even when optimally matching synergies between two sessions with virtual electrode repositioning (InterSessVER), it was not possible to achieve the similarity obtained in synergies computed from the same session after virtual electrode repositioning . VAF influenced the similarity significantly  = 8.37, p < 0.001), but there was no interaction between VAF and the type of analysis  = 0.23, p = 0.055).The last analysis proposed was to see how synergies from the same movements generalize between people (InterSUBJ). A comparison between the average subject-specific inter-session similarity  and the inter-subject similarity , Comp#5 An overview of previous studies revealed limited knowledge considering both inter-session and intra-session stability of synergies in healthy subjects. The novel contribution of this article is to clarify this difference using an appropriate dataset for both analyses. Intra-session stability of synergies is significantly higher than inter-session. There is a continuously decreasing trend of VAF CoV as the number of synergies increases, which stabilizes for a high number of synergies. A decreasing trend was observed as well by Taborri and colleagues  who studA significant difference between inter- and intra-session and a similar decreasing trend was detected also when considering stability of NoS that are needed to explain at least 80, 85, 90, and 95% of variance of original EMG data. Variation of VAF was higher for smaller NoS, and variation of NoS was higher for smaller VAF. This result suggests that, choosing a higher VAF as criteria for selection of the number of synergies, the number of synergies is expected to be relatively stable in both experimental conditions. Instead, increasing the VAF value and accepting a “high” decomposition order reduces the potential of the muscle synergy approach. Thus, according to our results, using the VAF threshold as a method to determine the number of synergies across several sessions (possibly for inter-session comparison) might be a trade-off between stability of synergies and parsimonious number of modules.The stability of VAF and NoS were highly informative but still could not provide details about the spatial synergy composition and the stability needed for multi-session assessments. Thus, the spatial synergy composition through sessions was compared using cosine similarity and matching.The synergy similarity between sessions had a broad range from 0.7 to 0.85 (cosine similarity) depending on the subject and VAF. Possible explanations for differences between subjects are that some subjects had higher movement repeatability because of redundancy (or abundancy) of the musculoskeletal system that allows to perform a movement using different muscle recruitment options as suggested by Latash and colleagues  or becauWe found that intra-session synergy similarity was higher than inter-session similarity. There are several possible reasons for finding significantly higher intra-session values compared to inter-session. First, the repeatability of EMG patterns can be higher inside the same session than between sessions. Since the subjects were instructed to perform exactly the same tasks during each session, this might happen because of natural variability of subjects or due to daily conditions, fatigue, or other factors related to each session. A second possible source of variability is slight electrode misplacement between sessions. Since even in the most accurate experimentation both factors can be found, it is challenging to control all the variables that may induce variability.When synergies from the same session but different combinations of movement repetitions were used and compared (assessing intra-session variability), average similarity  was around 0.962 ± 0.015. This value can be considered as the maximal similarity that we can expect between synergies from the same movement repeated several times. This is a very high similarity and such results have been reported previously ,31 but uIn the existing literature, studies analyzing inter-session or intra-session similarities were not performed on the same data and same muscles of interest. In all studies, it is claimed that good repeatability is found, both at the intra-session and inter-session levels. Kristiansen and colleagues  found veSince the assessment of variability in stability and similarity of synergies comparing intra-session and inter-session conditions revealed significant differences, we also provided a simulation of displacement of the proximal bracelet of electrodes to question whether repositioning might influence these features of muscle synergies.Comparing intra-session synergy similarity without electrode repositioning (IntraSessORIG) with electrode repositioning (IntraSessVER) allowed to detect a significant drop in average similarities when electrodes are repositioned (Comp#2). This leads to the conclusion that, if electrodes are displaced, we cannot expect that synergies can reach the similarity limit of 0.95 .Inter-session synergy similarity significantly increased with virtual electrode repositioning compared to inter-session similarity with the original positions of the electrodes (Comp#3). We found that similarity of synergies between two sessions can be increased if electrodes of one session were virtually repositioned with the goal to achieve higher similarities. This opens a possibility that the lower inter-session synergy similarity found when compared with intra-session (Comp#1) similarity was due to the fact that electrodes were not positioned in exactly the same way for all sessions. This is further clarified in Comp#4. Observing that the highest scores in InterSessVER were smaller than the highest scores in IntraSessVER, we conclude that electrode repositioning cannot account for all the differences that exist between sessions. Possibly, residual differences can be explained by variability induced by changing conditions between sessions  or because even more accurate simulations for electrode repositioning need to be used. For instance, while the simulated data accounted for linear, constant differences among the position of the electrodes, in reality, the variability of the positioning of the electrodes is most likely nonlinear and nonconstant also due to muscle activity and physiology.We consider this result to be of interest in muscle synergy analysis. We found that, in applications that involve distal upper-limb coordination, part of the inter-session variability can be attributed to effects that are probably not related to real physiological variability in motor coordination. While this effect can be relevant in this application that involves fine control compared to others targeting other body segments, the inter-session protocol-related variability should induce researchers to interpret results collected at different time stages with particular care. Only after considering the difference in synergies between sessions due to such protocol-related reasons, one can focus on quantifying other changes of interest, such as recovery in case of patients.Finally, after showing that the intra-session similarity is higher than inter-session similarity, we addressed whether synergy similarity can be distinguished when extracting synergies from the same person but in different sessions (inter-session) or extracting synergies from different people across sessions (inter-subject). We found the unexpected and very interesting result that there was no significant difference between the similarity of synergies from different people and the similarity of synergies from the same person, extracted in different sessions (Comp#5). This result can be interpreted under two perspectives: on one side, it confirms that synergies are meaningful and similar across subjects; on the other hand, while these results cannot be generalized to other scenarios and should be considered as specific of our application, they suggest caution for multi-session assessments and longitudinal analysis.These results also suggest that, across sessions, the subjects’ synergies may have a comparable variability with respect to other people ,25,50. TAll the mentioned results suggest that the synergy-based evaluation of a person within the same session should consider the natural variability that underlies human motor control, as previously shown by other authors . Even moIn this paper, we analyzed robustness, stability, and similarity of the extracted muscle synergies under the effect of factors that may induce variability, including inter-session measurements and natural intra-session variability. These analyses can help shed light on the applicability and challenges of applying muscle synergies in clinical environments as well as to more deeply understand their functioning.The main finding was that spatial similarity is significantly higher in intra-session conditions (synergies extracted from the same data acquisition) rather than in inter-session conditions (synergies extracted from the different data acquisitions). We also found that virtual electrode repositioning can significantly decrease the similarity of intra-session synergies, while it can also increase the similarity of synergies extracted in different sessions. Nevertheless, comparing the highest similarities achieved with virtual electrode repositioning for intra- and inter-sessions reveals that the electrode position does not fully explain the difference in similarity of inter-session compared to intra-session conditions. Future studies could explain if this is due to the strong simplification of the adopted modelling approach or to other experimental factors. Furthermore, the assessment of how well synergies generalize between healthy subjects while performing the same set of movements revealed no significant difference between the similarity of synergies from different subjects and the similarity of synergies from different sessions of the same subject. This point can have an impact on longitudinal studies where synergies can be used for the evaluation of neurological diseases at different time stages and for the assessment of treatment effects: if the changes we want to assess with the muscle synergy approach are smaller than this variability, then we will probably not be able to detect them. Lastly, the results are relative to the specific exercises and EMG channels recorded in the NinaPro hand grasp database 6 and cannot be extended to other movement tasks, electrode positions, and body segments. Nevertheless, they create a new understanding of the supporting evidence that muscle synergy analysis based on nonnegative matrix factorization is clinically and experimentally applicable with the limitations discussed in the paper. Further applications of our analysis need to be considered in longitudinal trials and clinical applications.


Both X-ray diffraction patterns and transmission electron microscopy images verified the dispersion morphology of OMMT in the copolymer matrix. Then, the effect of the introduction of OMMT layers on the copolymer properties was studied by comparing with pure copolymer AM/SSS/DOAAB (ADOS). The thermal degradation results demonstrated that the thermal stability of the ADOS/OMMT were better than pure copolymer ADOS. During the solution properties tests, ADOS/OMMT nanocomposite was superior to ADOS in viscosifying ability, temperature resistance, salt tolerance, shear resistance and viscoelasticity, which was because OMMT contributed to enhance the hydrophobic association structure formed between polymer molecules. Additionally, the ADOS/OMMT nanocomposite exhibited more excellent interfacial activity and crude oil emulsifiability in comparison to pure copolymer ADOS. These performances indicated ADOS/OMMT nanocomposite had good application prospects in tertiary recovery.In this research, a novel amphiphilic hydrophobically associative polymer nanocomposite (ADOS/OMMT) was prepared using acrylamide (AM), sodium 4-vinylbenzenesulfonate (SSS), N, N′-dimethyl octadeyl allyl ammonium bromide (DOAAB) and organo-modified montmorillonite (OMMT) through  Over Hydrophobic associating polymer is a kind of water-soluble polymer with a few hydrophobic groups in the hydrophilic main chain ,13. When+ and K+ ions between its layers. Therefore, in order to increase the compatibility of MMT platelets with hydrophobic polymer bulk, the original MMT needs to carry out organic pre-modification by cation exchange technology  dihydrochloride (AIBI) were produced by Shanghai Macklin Biochemical Co., Ltd. Octadecyl dimethyl tertiary amine were obtained from Shandong Xiya Chemical Industry Co., Ltd. Allyl bromide was bought from Aladdin Industrial Corporation (China). CTAB was obtained from Tianjin Guangfu Fine Chemical research institute. Na-MMT with a cationic exchange capacity of 1 mol 1 kg2.2.a.First, 1000 mmol N, N-dimethyl-octadecyl tertiary amine was dissolved in a three-mouth flask containing 300 ml of ethanol, and 150 mmol allyl bromide was added to the three-mouth flask for stirring. Then, the reaction was conducted under the protection of nitrogen at 60°C for 24 h. Third, the reaction mixture was distilled under reduced pressure to remove the ethanol thereby obtaining the crude product. Finally, the crude product needed to be recrystallized using acetone and ether and then put in the refrigerator for 48 h. The solvent in the product was filtered out to obtain the pure white powder product, which was put into the oven to dry for later use. The synthetic scheme is demonstrated in figure 12.3.− ion could be detected by solution of AgNO3. The finished samples were dried for one day in a drying oven at 70°C, dry samples were ground to powder (around 65 ∼ 75 µm) and put into self-sealing bags for later use. The process of organic modification of MMT is demonstrated in figure 1b.OMMT was obtained by cation exchange reaction, and the details are as follows. Firstly, 5 g pure natural Na-MMT powders was added into 100 ml of deionized water in a flat bottom three-mouth flask. Then, the mixture was stirred continuously for 1.5 h at 80°C in a water bath. At the same time, 1.2 CEC intercalation agent (CTAB) was dissolved in 40 ml of deionized water in a 150 ml beaker for later use. Finally, intercalation agent solution was slowly dripped into the swollen montmorillonite dispersion system above, and the dispersion system continued to react for 10 h at 80°C with stirring. After the intercalation reaction, the prepared suspension of OMMT was allowed to stand for 12 h in a separatory funnel. Then, the upper parts of samples were collected by filtering and lavation was carried out several times with deionized water until no Br2.4.In situ polymerization was used for synthesizing ADOS/OMMT nanocomposites. In a 150 ml beaker, 12 g AM, 0.42 g N′-dimethyl octadeyl allyl ammonium bromide (DOAAB), and 0.385 g SSS were dissolved in 40 ml deionization water in sequential order forming a uniform solution. After that the different quantities of prepared OMMT  were added into the above monomers solution slowly under high speed magnetic stirring and kept stirring for 2.5 h at 40°C. This was done to make sure that monomers adsorbed onto the MMT nanolayers adequately to synthesize composite material with better performance. An initiator AIBI (0.25 wt%) was added into the mixed suspension by injector, then, the mixture was stirred for another 30 min. The two steps were done under nitrogen protection. Subsequently, copolymerization was carried out for 6.5 h at 55°C. The resulting gel copolymer was cut into small pieces and washed in ethyl alcohol repeatedly, and dried them in a vacuum oven at 75°C. The scheme for the preparation of ADOS/OMMT nanocomposite is demonstrated in Pure copolymer (ADOS) was synthesized by almost the same process and condition. The only difference was that OMMT was not needed in the synthesis process.2.5.−1 was carried out for OMMT, Na-MMT, pure copolymer and nanocomposite by a FTS-3000 spectrophotometer (American Digilab) at room temperature. The 1H-NMR spectra of pure copolymer and surfactant monomer was measured by a Bruker ASCEND-400 NMR instrument, and deuterium oxide (D2O) was used as solvent. The interlayer spacing of the samples was characterized on a Bruker D8 Advance X-ray diffraction instrument  and calculated by Bragg's Law. During the testing, the system operated at a voltage of 40 KV and current 40 mA. Also the scanning speed was 1° min−1 from 1° to 10° with a step distance of 0.02°.FTIR spectrometric analysis in the spectral range of 4000–400 cm−1 under nitrogen flow rate of 140 cm3 min−1. Dispersion morphology of the OMMT layers in the nanocomposite was observed by TEM  at 200 kV. Meanwhile, the microscopic observation of pure copolymer matrix was obtained as blank control.The weight losses of the samples from room temperature to 700°C were recorded on a NETZSCH TGA (STA409PC) from Germany, and the samples were heated at the rate of 10°C min2.6.−1 flowing through the capillary tube of Ubbelohde viscometer (diluted) was measured with a stopwatch. Then the original sample solution was diluted by 1 mol l−1 NaCl aqueous solution several times and the flow time of sample solutions with different dilutions was obtained. Also the flow time of 1 mol l−1 NaCl aqueous solution was measured by the same method as above. Finally, the intrinsic viscosity of samples was calculated by the dilution extrapolation method and using the Mark-Houwink equation with experimental data  was the intrinsic viscosity (ml g−1).The intrinsic viscosity of copolymers and nanocomposites was obtained by the dilution extrapolation method at 30°C. First, the time of the sample solution with NaCl concentration of 1 mol ltal data :2.1ηr=tt2.7.−1 in the process of the measurements of salt resistance, temperature resistance and rheological properties.The correlation between the apparent viscosity and solution concentration, salinity and temperature was acquired by a Brookfield viscometer  and the test was carried out at the rotor speed of 20 r.p.m. The rheological behaviour of the copolymer was measured by a physical MCR 301 rotated rheometer (Austria). The shear resistance and viscoelasticity of the sample solution was tested under steady and oscillatory shear mode respectively. And all solutions of samples used for test were prepared with deionized water under room temperature conditions. The concentration of the sample solution was 6000 mg l2.8.The measurements of interfacial tension between crude oil and the copolymer solution and the nanocomposite solution were carried on a TX-500c spinning drop interface tensiometer . All sample solutions were tested for 35 min at the condition of 45°C, 6000 r.2.9.Equal volumes of crude oil and sample solution were measured, respectively, into a 50 ml centrifugal tube, then an electric mixer was used to stir the mixture at a speed of 5000 r for 10 min to turn the mixture into a uniform emulsion. The prepared emulsion was poured into a measuring cylinder with a plug, and then the total volume of emulsion was recorded. Afterwards, the volume of emulsion layer was recorded at regular intervals. The emulsification property of the sample solution was evaluated by the emulsification index, it could be calculated by the following formula ,5:2.4EI, OMMT (b), pure copolymer (c) and its nanocomposite (d) was gained and is presented in figure 3a, the small peak at 3626 cm−1 corresponded to the O─H stretching vibrations for SiO─H and AlO─H of silicate layers. The characteristic peak at 1624 cm−1 was attributed to H─O─H bending vibrations in the water molecules, which existed in the montmorillonite interlamellar  of the copolymer sample reflects the contribution of an individual copolymer molecule to the solution viscosity and it doesn't change with the concentration of sample solution  of ADOS, ADOS/1% OMMT and ADOS/2% OMMT nanocomposites were respectively 701.583 ml g−1, 825.25 ml g−1, 630.00 ml g−1 using dilution extrapolation.The intrinsic viscosity [solution ,50. As f3.7.−1, which was the critical micelle concentration (CMC) of the samples. Obviously, the apparent viscosity increased slowly as the polymer concentration increased before the turning point. This was because at low concentrations, the polymer macromolecules were mainly in the form of intramolecular association in the solution, which led to the curl of the molecular chain and the reduction of the hydrodynamic volume. After the turning point, intermolecular association played a dominant role, and supramolecular aggregates with network structure formed, leading to the sharp increase of apparent viscosity [In order to study the difference between the influence trend of the concentration of the nanocomposites solutions and the pure copolymer solution on the apparent viscosity, the apparent viscosity of the pure polymer solution and the nanocomposites solutions with different concentrations was tested at room temperature, as shown in iscosity . Howeveriscosity ,52. Howe3.8.−1 is shown in The influence of temperature from 25°C to 95°C on viscosity of ADOS solution and ADOS/OMMT solution for the concentrations of 6000 mg lIt can be seen from the 3.9.2Cl for both ADOS and ADOS/OMMT solutions was tested and recorded. The apparent viscosity of the sample solution as a function of different salt ions (NaCl and Ca2Cl) concentration is summarized in 2 concentrations, the apparent viscosities of the samples solutions decreased first, then increased, and then decreased. And similar phenomenon could be seen in previous literature [− and ─SO3H−) on the polymer backbone were shielded by salt ions (Na+ or Ca2+), leading to the reduction of electrostatic repulsion and the contraction of polymer chains. This resulted in the decline of the sample's apparent viscosities [+ and Ca2+ on the charge on the polymer chain. In addition, MMT platelets could promote and participate in formation of stronger intermolecular association networks [2 solutions exceeds 40%. Moreover, when the concentration of NaCl and CaCl2 solutions was about 290 000 mg l−1 and 330 000 mg l−1, respectively, the apparent viscosity of the samples reached the maximum value. Above all, both ADOS and ADOS/OMMT nanocomposites had excellent salt resistance, and the introduction of OMMT has a synergistic effect on the salt resistance of pure polymer.Salt ions are known to affect the apparent viscosity of polymer solutions. Therefore, the apparent viscosity in the presence of different concentrations of NaCl and Caterature . These ccosities ,56. At tcosities ,58. At hcosities . Howevernetworks . Also, a3.10.−1 to 1000 s−1, the apparent viscosity of the sample solution decreased gradually, showing the behaviour of shear thinning. However, under the same shearing rate, the shear degradation of ADOS/1% OMMT and ADOS/2% OMMT was lower as compared with that for ADOS. This was because the introduction of nano-OMMT enhanced the intermolecular hydrophobic association, which made the three-dimensional network structure more stable and less vulnerable to shear damage. Consequently, ADOS/OMMT nanocomposites had more excellent shear resistance performance than ADOS.Variation curves of ADOS and ADOS/OMMT solutions apparent viscosity versus shear rate are demonstrated in 3.11.fc) corresponding to the crossing point (Gc) was the characteristic relaxation time (tc) [tc of ADOS, ADOS/1% OMMT and ADOS/2% OMMT were 0.12, 2.7 and 13.7 s, respectively. Moreover, the longer tc was, the better the elastic efficiency. So, compared with ADOS, ADOS/OMMT had better elastic properties. These results could be interpreted as, the original intermolecular hydrophobic association was strengthened by electrostatic interaction and hydrogen bonding between molecular chains of matrix and exfoliated MMT layers, forming a more complex and stable physical network structure [The viscoelastic property of the polymer solution is of great significance to the displacement of oil trapped in pore dead angles. The viscoelasticity test results of ADOS and ADOS/OMMT solutions are reported in ime (tc) . Therefotructure .Figure 3.12.−1, respectively. Furthermore, the ADOS and ADOS/OMMT nanocomposite had a relatively good ability to decrease the interfacial tension between crude oil and water. Interestingly, ADOS/OMMT nanocomposites could contribute to more decrease than ADOS in the interfacial tension at the crude oil–water interface. These phenomena attributed to the fact that the hydrophilic and hydrophobic segments existing in copolymers had good orientation at the crude oil–water interface, which led to reduction of interfacial tension [Interfacial tension (IFT) of both ADOS and ADOS/OMMT nanocomposites at the oil–water interface have been tested. The relation curves between IFT of ADOS and ADOS/OMMT nanocomposite solution and their solution concentration at 45°C are demonstrated in  tension ,61. Addi tension ,62.Figu3.13.−1 or 5000 mg l−1, the emulsification index of ADOS/1% OMMT nanocomposites was greater than pure polymer and ADOS/2% OMMT nanocomposites throughout the test, that is, the emulsifying capacity of ADOS/1% OMMT nanocomposites was more superior than the other two samples. Moreover, it could be noticed that pure polymers had a better ability to stabilize emulsions in aqueous solutions than ADOS/2% OMMT nanocomposites. This was because the amphiphilic structure of the copolymer gave the copolymer the ability to emulsify crude oil. The hydrophobic groups of the copolymer could form network structure by intermolecular association, which could trap oil droplets into network structure thereby forming stable O/W emulsion with the interface membrane [The emulsifying capacity of the ADOS and ADOS/OMMT nanocomposites at room temperature was investigated by recording emulsification index against time. The results of emulsifying crude oil with these samples in aqueous solution are displayed in membrane . Additiomembrane . Neverth4.in situ polymerization. TEM and XRD analysis proved that OMMT was successfully dispersed in an ADOS copolymer matrix in the form of exfoliation and intercalated structure. The TGA results showed that the thermal stability of the ADOS/OMMT was better than pure ADOS. Meanwhile, the solution properties investigation indicated that ADOS/OMMT had higher apparent viscosity than pure ADOS. Besides, at the same condition, the temperature resistance, shear resistance and viscoelasticity of the ADOS/OMMT solution were enhanced relative to ADOS. Also, compared with pure ADOS, the copolymer ADOS with introduction of an appropriate amount of OMMT could demonstrate superior interfacial activity and crude oil emulsifiability. Therefore, ADOS/OMMT nanocomposites possess good application prospects in tertiary recovery and oil drilling.A amphoteric hydrophobically associative polyacrylamide/organic MMT nanocomposite (ADOS/OMMT) was prepared with


Polymer-composite materials have the characteristics of light weight, high load, corrosion resistance, heat resistance, and high oil resistance. In particular, graphene composite has better electrical conductivity and mechanical performance. However, the raw materials of graphene composite are processed into semi-finished products, directly affecting their performance and service life. The electromagnetic pulse compaction was initially studied to get the product Graphene/PEKK composite powder. Simultaneously, spark plasma sintering was used to get the bars to determine the electrical conductivity of Graphene/PEKK composite. On the basis of this result, conducting Graphene/PEKK composite powder can be processed by electromagnetic pulse compaction. Finite element numerical analysis was used to obtain process parameters during the electromagnetic pulse compaction. The results show that discharge voltage and discharge capacitance influence on the magnetic force, which is a main moulding factor affecting stress, strain and density distribution on the specimen during electromagnetic pulse compaction in a few microseconds. With the rapid development of automobile, aviation, aerospace, and rail transit, lightweight materials have become a relatively important topic as an effective measure to pursue global energy conservation and environmental protection ,2,3. PolPEEK composite is a lightweight material that can bear the main load-bearing structure of an aircraft. As a torsion box with a span of 12 m, carbon fibre with 6 m length and 28 mm thickness can be realized by fibre-reinforcement technology to strengthen the upper beam of a PEEK engine pylon ,8,9. AppIn some harsh service environments, polymer-composite materials can replace traditional metal materials. They are an important means to solve the problem of corrosion and light weight. If polymer composites have high strength and conductivity, then they can replace metal materials for use in harsh environments. Graphene is known to be the thinnest and strongest material that can be separated from graphite materials ,11,12. IThe conductive mechanism of conductive Graphene/PEEK polymer-composites is primarily through the formation of conductive passage . GraphenGraphene/PEKK composite materials are processed into semi-finished and finished products such as plates, bars, pipes, test parts, structural parts, and skin. To ensure the performance of Graphene/PEKK composite materials and to improve the quality of finished products, the moulding process is one of the most commonly used techniques. Graphene has been combined with the higher-performance thermoplastic PEKK to improve its electrical conductivity ,21. For In general, the moulding process can be divided into hot and cold moulding. Hot moulding can improve the quality of products primarily by adjusting the temperature, whereas cold moulding refers to finished and semi-finished products obtained from powder at room temperature, and cold moulding mainly depends on pressure and pressure holding time to obtain specimens with high density, and it is easy to control the moulding size. Thermoforming includes hot pressing, extrusion, injection moulding, calendering, secondary moulding, and casting moulding. With the rapid development of computer technology, 3D-printing technology has been gradually applied in various fields ,24,25. IThe use of 3D printing to form conductive Graphene/PEKK composite powder has certain problems. Firstly, the dispersion problem of graphene in the polymer matrix still needs to be solved to maximize its excellent mechanical properties and functionality . SecondlSome researchers have also used spark plasma sintering (SPS) to form specimens for polymer composite powder. SPS  is used 2 and PZT powders in an indirect way. After selecting the appropriate processing parameters, TiO2 and PZT ceramics with higher density and better electrical properties than those produced by traditional static compaction are generated [The powder-moulding process at room temperature is called cold moulding. Previous research showed an important cold-moulding method  named loenerated . Low-volB. Chelluri  describeFew studies have focused on the moulding of Graphene/PEKK composites, especially the moulding of self-prepared Graphene/PEKK composites . IdentifIn the present study, Graphene/PEKK composite powder was synthesized in the laboratory by way of in situ polymerization, and then it was called self-prepared Graphene/PEKK composite powder. Firstly, SPS was used to obtain a Graphene/PEKK composite compressed column with high electrical conductivity in order to determine the feasibility of electromagnetic pulse compaction conductive powder. Secondly, cold moulding-electromagnetic pulse compaction technology was primarily proposed to realize the moulding process of self-prepared Graphene/PEKK polymer powder at room temperature. In this paper, the finite element numerical analysis was used to determine process parameters during the electromagnetic pulse compaction moulding. The loose coupled FE analysis method with ANSYS and MSC.Marc was proposed, and it used ANSYS to obtain the magnetic force. Additionally, the magnetic-force distribution on different points was regarded as the boundary conditions of the MSC.Marc software. The FE numerical analysis method was initially used to determine the change law of process parameters during the cold moulding electromagnetic pulse compaction process and guided future theoretical and experimental research.Graphene used in this study was bought from Shenzhen Yuewang Energy Saving Technology Service Co. Ltd, Shenzhen, China. Terephthalyl chloride, diphenyl ether, aluminum trichloride (anhydrous), dimethylformamide, and dichloromethane were purchased from Sinopharmaceutical. The graphene was dispersed in dichloromethane, and then diphenyl ether, p-benzoyl chloride, N, N-dimethylformamide and anhydrous aluminum trichloride were added successively. After stirring evenly, the composite powder was obtained after cleaning, filtering, grinding and drying. According to the above technological process, Graphene/PEKK composite powder with 3.8% mass percentage of graphene was prepared. Among them, the molar ratio of diphenyl ether, terephthalyl chloride, N,N-dimethylformamide and aluminum trichloride is 1:1:2:6.Thermal properties including thermogravimentric analysis (TGA) and differential scanning calorimetry (DSC) of self-prepared Graphene/PEKK composite powder were characterized before moulding of conductive Graphene/PEKK composite materials. The TGA test  was conducted from 50 to 1000 °C at a ramp rate of 10/min. The DSC test  was carried out between 0 and 450 °C at a heating/cooling rate of 10 °C/min.gT) of this Graphene/PEKK composite may be defined as 125.5 °C. It should be noted that melting temperature and the corresponding viscosity of the polymer composite directly determines the difficulty and quality of flow forming process in engineering application. According to Graphene/PEKK composite powder samples were obtained by in situ polymerisation. Commercial graphene was satisfactory dispersed in high-performance thermoplastic PEKK polymer to improve its electrical properties. However, higher temperature moulding decreases the graphene performance, whereas lower temperature influences dispersion, tool life, and porosity. Thus, the suitable moulding temperature is a key factor influencing the quality of the electrode bar. The self-prepared Graphene/PEKK composite material is a thermoplastic composite material, which has the characteristics of light weight, high toughness, low energy consumption, corrosion resistance, good formability, and conductivity. In this research, SPS equipment  was usedSPS is a new powder-metallurgy sintering technology in which metals and other powders are placed in a mould made of graphite and other materials. The specific sintering power supply and pressing pressure are applied to the sintered powder by using upper and lower die-punched and electrified electrodes. High-performance materials are produced by discharge activation, thermoplastic deformation, and cooling. A previous article discussed how to process powder electrodes , as wellTo reduce the fitting time and evaluate the computation results, an effective experimental design method was needed. Several different factors and levels needed to be considered when optimizing the parameters during SPS moulding. The purpose of the optimisation of parameters during SPS moulding was to reach the maximum conductivity. Orthogonal design is a kind of design method that is primarily used to study multiple factors and multiple levels . The suiFive electrode bars were obtained based on the parameters in Graphene/PEKK composite with 3.8% graphene content had strong electrical conductivity by using the SPS moulding bar; The above research confirmed the electrical conductivity and matrix structure of self-prepared Graphene/PEKK composites and some shortcomings about SPS moulding technology. Compared with hot-press-moulding SPS moulding technology, it can save time as it needed only 30 min. Normally, the temperature can change the grain size. In particular, high temperature can produce toxic gases and influence the molecular structure, whereas low temperature sintering can affect the density of specimens. In other words, it influenced electrical conductivity and strength. At the same time, during SPS, the geometrical properties of the tool limited the specimen size.Moulding pressure directly affected the density, and at the same time increased the hardness and electrical conductivity by increasing the pressure; increasing the temperature can reduce the flow resistance and shear force between the material particles, as well as reduce the friction coefficient between particles to overcome mould cracks. Although increased temperature reduced the external force, it also reduced the mechanical properties of the material. Therefore, balancing the moulding pressure and moulding temperature was the key to mould polymer composites. On the basis of the above research, we have reason to believe that the product of conducting Graphene/PEKK composite can be obtained by electromagnetic pulse compaction. Accordingly, the following research is discussed.Electromagnetic pulse processing equipment is a new technology equipment which uses electromagnetic energy to process metal materials and is applicable in the field of special processing technology. It is especially suitable for processing non-ferrous materials, such as aluminium, magnesium, and copper. It can weld all kinds of homogeneous or heterogeneous metal materials with conductive properties, which cannot be achieved by traditional technology.Herein, electromagnetic moulding experiments were performed with a machine, and the technological parameters are given in The electromagnetic moulding powder pressing machine used is shown in Graphene composite materials have high electrical conductivity, and local welding can be achieved during the process of electromagnetic pulse compaction. The electromagnetic pulse compaction of Graphene/PEKK composite materials was primarily divided into four stages as shown in During the electromagnetic-moulding process, the energy-conversion process was more complicated, and the mutual coupling of complex energy fields realized powder moulding. Previous research focused on the electromagnetic moulding of metal powder, whereas self-prepared Graphene/PEKK composite material with high electrical conductivity was studied in the current work. Theoretically, the moulding mechanism of a polymer composite powder is similar to that of electromagnetically formed metal powder. This research firstly determined the process parameters of electromagnetically formed conductive Graphene/PEKK composite powder through FE simulation analysis; that provided basic guidance for future experiments. This research used a loosely coupled method with the ANSYS/Multiphysics module to establish the current excitation. The electromagnetic field model was used to study the influence of discharge current on the magnetic field and magnetic pressure with magnetic pressure as the boundary condition in the MSC.Marc software (2019), as shown in The discharge time of the electromagnetic pulse compaction was shorter than the compaction moulding time. The influence of the elastoplastic deformation of powder on the magnetic-field distribution and the magnetic force was ignored. The FE model was established by the loose coupling method . FirstlyIn fact, during the electromagnetic pulse compaction processing, the electromagnetic force and discharge current had a pulse signal, as shown in Electromagnetic pulse compaction can achieve the parameters of the macroscopic powder-compaction process through experimental methods, but it cannot accurately describe the powder-compaction process. This research used a loosely coupled method with the ANSYS/Multiphysics module to establish current excitation. The electromagnetic-field model was used to study the influence of discharge current on magnetic field and magnetic pressure. With magnetic pressure as the boundary condition, in MSC.MARC, the powder module and Shima–Oyane yield criterion were used to establish the powder-compaction model.Yield criterion: Shima–Oyane (1)F=1γ. With increased discharge energy, densification also increased as shown in In the current research, the magnetic-pressure distribution on the bar was obtained using ANSYS. Magnetic pressure was used as the boundary condition of electromagnetic moulding to realize FE numerical simulation analysis. In general, through the simulation analysis of the electromagnetic pulse compacted Graphene/PEKK composite powder, determining the change trend of the process parameters during moulding was possible, but there was a problem of stress distribution at each node in the simulation, especially in the electromagnetic distribution. In the decay stage after the maximum pressure, the positions of different nodes rose to different degrees. This finding showed that when the powder was sintered and the discharge was over, the elastoplastic properties of the material itself changed, and the impulse force acquired inertia, the phenomenon of falling after rising. Therefore, in future research, a constitutive model research should be conducted for self-prepared composite-material powder to further optimize the simulation boundary conditions and improve the simulation accuracy.On the basis of above research, the following conclusions were obtained.The spark plasma sintering technique was used to process the self-prepared Graphene/PEKK polymer composite specimens to get the electrical conductivity of Graphene/PEKK composite; the specimen with diameter 12 mm and height 11 mm was polished off 0.5 mm  in the axial direction, and the electrical conductivity was about 0.014S/cm. Thus, 3.8% of the content of graphene in the Graphene/PEKK composite can be regarded as the conducting graphene composite electrode.The moulding of self-prepared Graphene/PEKK polymer composite powder, discharge voltage, discharge capacitance, and material constitutive model of self-prepared Graphene/PEKK composite powder were important factors affecting the moulding quality. According to the inherent adjustable range of the experimental equipment, four fixed parameters of discharge voltage  and discharge capacitance  were selected.Simulation analysis using ANSYS and MSC.Marc was proposed, and it used ANSYS to obtain the magnetic force. Additionally, the magnetic-force distribution on different points was regarded as the boundary conditions of MSC.Marc software. It obtained 16 groups of simulation results regarding the discharge current and magnetic force. The different stresses, strains, and density distributions on the electrode bar were determined by simulation analysis. When the energy was the maximum, the stress, strain, and density also arrived at the maximum within a few microseconds.The self-prepared Graphene/PEKK composite powder will be modified and commercialized, so the material constitutive model must be reconstructed, and the existing constitutive model cannot accurately predict stress, strain and compaction density during the moulding process, especially considering the lack of accuracy in the law of stress changes. Subsequently, we will finish the electromagnetic pulse compaction experiment for self-prepared Graphene/PEKK composite powder based on the process parameters supported by finite element numerical analysis.NoOriginal WordsAbbreviation1Poly (ether-ketone-ketone)PEKK2Poly (ether-ether-ketone)PEEK3Spark Plasma SinteringSPS4Lead Zirconate TitanatePZT5Magnetic Pulsed CompactionMPC6Dynamic Magnetic ConsolidationDMC7Direct CurrentDC8Differential Scanning CalorimetryDSC9Scanning Electron MicroscopySEM10Finite ElementFE


The possibility of graphene synthesis (the bottom-up approach) in plasma and the effective control of the morphology and electrical properties of graphene-based layers were demonstrated. Graphene flakes were grown in a plasma jet generated by a direct current plasma torch with helium and argon as the plasma-forming gases. In the case of argon plasma, the synthesized graphene flakes were relatively thick (2–6 nm) and non-conductive. In helium plasma, for the first time, graphene with a predominance of monolayer flakes and high conductivity was grown in a significant amount using an industrial plasma torch. One-dimensional (1D) flow modeling shows that the helium plasma is a less charged environment providing the formation of thinner graphene flakes with low defect density. These flakes might be used for a water-based suspension of the graphene with PEDOT:PSS : polystyrene sulfonate) composite to create the structures employing the 2D printing technologies. Good structural quality, low layer resistance, and good mechanical strength combined with the ability to obtain a large amount of the graphene powder, and to control the parameters of the synthesized particles make this material promising for various applications and, above all, for sensors and other devices for flexible electronics and the Internet of things ecosystem. Graphene, due to its unique electronic characteristics ,2, is on2-carbon atoms) the material for the printed electronics should have, in addition to good electronic characteristics (high conductivity and carrier mobility), (a) proven and scalable technology for producing graphene flakes; (b) a low cost of starting materials and manufacturing of the graphene suspension and ink; (c) high physical and mechanical stability of the starting materials and devices under the operating conditions; (d) formation, after the solvent evaporation, of the entire printed layer with good adhesion and interaction between the particles. Compliance of most of these properties is conditioned by the production of thin (preferably monolayer) flakes. However, the graphite exfoliation does not, as a rule, satisfy this important requirement. The way out of this contradiction is in changing the approach: in the transition from graphite exfoliation to the synthesis of the graphene flakes.Unlike the ideal graphene  ,18,19. GThe authors of  show thaThe present work is aimed at searching for the conditions for efficient bottom-up synthesis of the graphene flakes utilizing the DC plasma torch as well as at investigation of the structural and the electrical properties of the conducting layers produced via the printing technologies. As a result, we show that the graphene powder with a predominance of monolayer flakes might be successfully applied in the 2D printing technologies and, as an example, in the production of the conductive layers for a wide spectrum of applications: various sensors and other devices of flexible electronics.3.To synthesize the graphene, we applied the plasma-chemical approach based on the use of a 40 kW DC plasma torch with the expanding channel of the output electrode and the vortex stabilization of the plasma jet. The design feature of the plasma torch (expanding channel of the output electrode) and the tangential input make it possible to obtain stable plasma jets within a wide range of parametric studies . A more To study morphology and the local properties with high spatial resolution, we employed electron microscopy and Raman spectroscopy. We used the Hitachi S5500 scanning electron microscope (Hitachi High-Technologies Corp (Microscopy), Japan) with in-lens technology (STEM mode) and a Nova NanoSem 650 raster electron microscope  with the standard processing technique (SEM mode). We recorded the Raman spectra at room temperature on a INTEGRA Spectra spectrometer  using λ = 532 nm exciting radiation. We applied X-ray element microanalysis (EDAX)  to identify the chemical elements and to determine their quantitative content as well as the dynamic light scattering (DLS) method)  to measure the nanoparticle size. The DLS method makes it also possible to determine the diffusion coefficient of the dispersed particles in the liquid using analysis of the correlation function of the scattered light-intensity fluctuations. Then, from the diffusion coefficient, we calculated the nanoparticle radii. We employed a Solver PRO NT-MDT  scanning microscope to obtain atomic force microscopy (AFM) images from the surface of the examined films and substrates and to evaluate the sample thicknesses. The measurements were carried out in contact and semi-contact modes. A X-ray photoelectron spectroscopy (XPS) measurements were carried out in an ultrahigh-vacuum chamber equipped with an X-ray source  and a hemispherical energy analyzer Phoibos .We printed the films on DMP-2831 Dimatix FUJIFILM jet printer . After printing a layer, the film was subjected to a drying procedure at 60 °C to exclude the possible mixing effects. Then we studied the layer resistance of the fabricated films using a four-probe JANDEL equipment and the HM21 Test Unit at room temperature . To measure the current-voltage (I-V) characteristics of the fabricated structures, we employed a high-precision Keithley picoampere-meter  at room temperature, with Ag alloy contacts.When studying the cyclic deformations, we performed simultaneous testing of the electrical parameters of the material or structures utilizing the home-made installations applying tensile and compressive loads to the tested films. The strain was estimated using the well-known equation ε = (d + t)/2r where d is the flexible substrate thickness (d = 100 mm), t is the film thickness, and r is the substrate bending radius. The film thickness t < 500 nm is negligible as compared to that of the substrate.The EDAX results for both types of sample see b show th2/g. For comparison, [2/g.The specific surface area for both types of flakes measured by the standard Brunauer–Emmett–Teller (BET) method was ~500 mparison,  presents2/Si substrate.To prepare the suspensions, we mixed 10 mg of the dry graphene flakes powder with 50 mL of the 0.7:0.3 ethyl alcohol-water solution, and added the surfactant . After sonication and centrifugation aimed at separation into individual flakes, we deposited the suspension on the silicon surface. −1), G (1585 cm−1) 2D (2700 cm−1). Note that the D-line structure for the C-Ar film attests to the fact that the synthesized flakes contain not one but several layers [D/IG > 1 for the C-Ar film indicates a significantly higher defect concentration than the C-He film where ID/IG < 1.l layers ,35. The The C-He film created by the drops turned out to be loose and crumbled. The C-Ar suspension made it possible to form denser and truly solid film. The thickness of the films was large, of the order of a micron. After drying, we measured the layer resistance of the films using the four-probe head. The values obtained were 1.3 MΩ/sq and 5.0–5.6 MΩ/sq for the C-Ar and the C-He suspensions, respectively. Our attempt to consolidate the film by a mechanical action did not lead to a change in the C-Ar film resistance and destroyed the C-He film. Thus, in the C-He film flakes do not form a unified material due to the relatively high concentration of surfactants on the surface of the fine flakes; that very fact was the reason for the high resistance. In contrast, the C-Ar film was formed as a singular layer and its high resistance is most likely related to the high resistance of the particles themselves.2 hybridization. Also the C1s spectra of the both graphene flakes includes peaks centered at about 286.4, 287, and 289 eV, corresponding to C–O, –C=O and –COO− groups, respectively [Crystal phase of the obtained materials were determined by XPS. XPS spectra for C-Ar and C-He samples are given in ectively ,37,38. TTo improve the conditions for the C-He film formation from the individual particles, we added to the above-described suspension a 1% PEDOT:PSS : polystyrene sulfonate composite) water solution, the total composition being 2:1 or 0.05 weight% in the film. This led to radical changes in the formed film quality. Here, for the C-He film, we obtained the layer resistance of 600–800 Ω/sq (for the film of submicron thickness) and 1.4–2.6 kΩ/sq for the thin (about 200 nm) film. For comparison, a thick PEDOT:PSS film (more than a micron) had the resistance of 3.6–4.2 kΩ/sq, and the thinner films (~200 nm) with the resistance of ~10 kΩ/sq. For the composite film with the C-Ar suspension, the resistance coincided with that of the PEDOT:PSS, that is, the contribution of the C-Ar particles was not noticeable.n = 3.1 × 1015 cm–2: it corresponds to the volume plane of ~7 × 1018 cm–3. For a thinner film, n = 3 × 1013 cm–2. The carrier mobility in the films turned to be relatively high: μ = 6–90 cm2/Vs. The carrier mobility values of ~90 cm2/Vs are usually obtained for the 1–2 monolayer thick graphene particle films [We performed the Hall measurements  for the C-He based composite film, its thickness being about 5 μm, the sheet concentration was le films .Numerical simulation of the plasma flow was performed using the quasi-one-dimensional approach when the two-dimensional system of equations was transformed into the one-dimensional system employing integration along with one of two coordinates under the given profiles of velocity and temperature . Plasma 2, C3, C3H, C2H2, and later at the temperature 3270 K the condensation of carbon into graphene/graphite (CGr) commences. Similar curves for the case of argon plasma are also given in 3, and Cgr). The condensation begins a little bit earlier at 3304 K. It means a longer sojourn of particles under high temperatures. As a result, temperature profiles along the jet axis and corresponding equilibrium plasma compositions were calculated. To print on the 2D printer, we prepared the ink from the C-He: PEDOT:PSS conductive composite suspension. We printed using the composite ink made of the C-He suspension kept for 8 months. Here, to obtain a homogeneous composite suspension, we only applied a brief ultrasound and centrifuge treatment. As a result, we printed the resistive structures on two types of substrate . The insert in It is an important fact that printing of the films and practically transparent layer using the C-He suspension without PEDOT:PSS (five printing layers) on the paper results in obtaining the conductive track, several nanometers thick, with the resistance of 470 GΩ/sq, without transition to the composite films.2/Si substrate. Note that the layers are porous and straight. In general, mechanical testing of such layers, both on the paper and on the PET (bends of the printed structures) demonstrates the formation of the unified layer. Deformations did not lead to the printed film destruction. A comparison of the resistances of the films obtained from the C-M particles with the C-He-based composite films  and some scattering in the resistance values (10–15%) at the repeated measurements.To obtain graphene or multigraphene within a short period, various plasma generators are engaged ,40,41,42The bottom-up synthesis method implies that the nanostructures are synthesized by stacking atoms onto each other: this gives rise to the crystal planes; and the crystal planes further stack onto each other resulting in the nanomaterial synthesis. Despite its short history (compared to the other techniques), the plasma-based technologies have already achieved successes for the synthesis of the carbon-based materials ,46,47. IAnalysis of electrical properties and the search for electronic applications are very poorly represented in the available literature. The exception is an electrochemical application in fuel cells , lithiumThe study of their structural flexibility shows both good adhesion to the composite film, to PET, and the stable layer properties under the bending up to 1.5 mm (tensile strain ~3%), thus providing the prospects of such a material and structures for flexible electronics. The flexibility of films created from C-M suspension was studied where changes in the resistance and some scattering in the resistance values under repeated measurements (within 30% for strain ~2%)  were deTo the best of our knowledge, this work paves the path to use of these kind graphene flakes in printed flexible sensors, logics, and other devices aimed at use in the continuously expanding Internet of Things ecosystem.We show that graphene flakes synthesized in helium plasma with the propane-butane mixture addition can be used to obtain a water-based graphene suspension or a composite suspension with PEDOT:PSS to create structures using the 2D printing technologies. The low thickness (from a monolayer to 2 nm) and the high conductivity of the layers obtained from such particles is one of the important and attractive parameters of such particles. For a bottom-up synthesis approach, the formation of a material with that low density of defects is not an easy task. On the contrary, the particles synthesized in argon plasma are thicker, more defective, and non-conductive.One-dimensional flow modeling shows that in the case of argon the environment encloses more radicals, electrons, and ions compared with helium. This is the precondition to increase the number of condensed cycles and side reactions, favoring the increase in size and thickness of flakes and defect density. In contrast, helium plasma leads to the creation of graphene flakes C-He with more promising application properties.Some test structures were fabricated from C-He suspension with the use of 2D printed technologies. The predominance of monolayer graphene flakes created in helium plasma provides the unique stability of the water-based graphene inks (at least 8 months). The composite graphene: PEDOT:PSS films have a smooth surface and a uniform structure. The layer resistance of the relatively thick composite layers obtained by droplets equals 600–800 Ω/sq for the submicron thickness film and to 1.4–2.6 kΩ/sq for a thin film (about 200 nm). The resistance of the ~80–500 nm thick layers created by the 2D printing on the PET was equal to 70–2000 Ω/sq: significantly lower than that of the graphene flakes created by graphite exfoliation. In general, good structural quality, low layer resistance, sufficiently high carrier mobility, and good mechanical strength combined with the possibility to obtain a large amount of the graphene powder, and the possibility to control the parameters of the synthesized particles, makes this material promising, above all, for resistive sensors. Our results contribute to the direct integration of the graphene structures into the 2D printing technology on flexible substrates for nanoelectronics, sensors, biomedical, and optoelectronic components and nanodevices.