Methamphetamine (meth) is an addictive psychostimulant and illicit use presents significant personal and socioeconomic harm. Behavioral studies support the involvement of the dorsal striatum in drug-seeking but stimulant induced dysfunction in this region is understudied. The dorsal striatum can be subdivided into the dorsomedial (DMS) and dorsolateral (DLS) striatum with the DMS implicated in goal-directed and DLS in habitual behaviors; both regions are primarily composed of GABAergic direct (dSPNs) and indirect pathway (iSPNs) spiny projection neurons. To examine the effect of repeated meth on SPNs, mice were administered meth (2 mg/kg) for ten consecutive days and intrinsic excitability, dendritic excitability, and spine density were examined. DMS iSPN intrinsic excitability was increased at 1 day but decreased at 21 days of abstinence. In contrast, DMS dSPN intrinsic excitability was unchanged at either timepoint. Dendritic excitability and spine densities were unaltered in DMS iSPNs and dSPNs at 1 and 21 days of abstinence. The effect of repeated meth on iSPN excitability was specific to the DMS; DLS iSPN intrinsic excitability, dendritic excitability, and spine density were unchanged at 1 and 21 days of abstinence. These findings point toward DMS iSPN dysfunction in meth use disorders with differential dysfunction dependent on abstinence duration. The primary pharmacological targets of meth are plasmalemmal reuptake proteins, particularly dopamine transporters, and vesicular monoamine transporter 2 (VMAT2)6. Binding of these transport proteins by meth results in elevated cytosolic and synaptic concentrations of dopamine ultimately resulting in euphorigenic and reinforcing effects. There has been a strong emphasis on understanding the effects of drugs of abuse on the nucleus accumbens and the role this brain region plays in substance use disorders; however, clinical and preclinical evidence indicates that the dorsal striatum is also an important region in need of further study. Imaging data in human subjects provide evidence that the dorsal striatum is involved in stimulant craving and that dopamine levels in this region may even correlate with craving severity11. Consistent with clinical evidence, dopamine receptor antagonism, inactivation, lesioning, and chemogenetic modulation of neuronal function within the dorsal striatum inhibits stimulant-seeking behavior in rodent models21.Methamphetamine (meth) is a potent psychostimulant and the number of individuals suffering from a meth use disorder, overdose deaths, and emergency department visits in the US has increased in recent years22. Additionally, the dorsal striatum can be subdivided into the dorsomedial (DMS) and dorsolateral (DLS) striatum, both of which are innervated by substantia nigra pars compacta (SNc) dopamine neurons. Electrical and optogenetic stimulation of the SNc is rewarding26 and the DMS in particular is associated with goal-directed behavior whereas the DLS is more heavily involved regulating habit and motor control30.Despite clinical and preclinical evidence implicating the dorsal striatum in substance use disorders the effects of stimulant administration, and in particular meth, on neuronal function in the dorsal striatum is unclear. The dorsal striatum is primarily composed of GABAergic spiny projection neurons (SPNs). These SPNs can be further subdivided into D1 dopamine receptor expressing direct pathway SPNs (dSPNs) which project to the substantia nigra pars reticulata and internal segment of the globus pallidus and D2 dopamine receptor expressing indirect pathway SPNs (iSPNs) which project to the external segment of the globus pallidusThe goal of the present study was to investigate the consequence of repeated meth administration on SPN function and anatomy in the dorsal striatum. Mice were administered meth (2 mg/kg) non-contingently for ten consecutive days and SPN intrinsic excitability, dendritic excitability, and spine density were examined after either 1 or 21 days of abstinence. Repeated non-contingent meth administration uniquely altered the intrinsic excitability of iSPNs in the DMS leaving DLS iSPNs unaffected. Additionally, the effect on DMS iSPN excitability was dependent on abstinence duration with an acute 1 day of abstinence producing an increase and protracted 21 days of abstinence a decrease in intrinsic excitability.34. Additionally, this dose is comparable to amounts self-administered by both rats and mice in short access self-administration paradigms41. Ex vivo brain slices entailing the DMS were prepared for electrophysiological study using whole-cell patch clamp techniques; iSPNs and dSPNs were identified based on green or red fluorescence, respectively. Patched neurons were subjected to successive sweeps of current injection up to 500 pA with 20 pA steps to generate current-spike response curves. Repeated non-contingent meth administration increased intrinsic excitability of DMS iSPNs resulting in more action potentials generated in response to depolarizing current injection compared to DMS iSPNs recorded from mice administered saline . This dose of meth was selected based on it being a behaviorally relevant dose capable of inducing motor sensitization and conditioned place preference in rodentsR) were recorded; active membrane properties including the action potential (AP) threshold, AP height and afterhyperpolarization (AHP) amplitude were calculated using the first action potential at rheobase. Meth-induced DMS iSPN hyperexcitability was associated with a decreased AHP amplitude with no detectable effect on AP threshold, AP height, RMP, or IR  and input resistance  and the anatomical dye Alexa 568 (50 µM) were included in the internal recording solution Fig. D. Back p42 Fig. D,E. Unli42 Fig. F,G; bAP R, and increased rheobase  in the home cage prior to sacrifice. In contrast to observations during acute abstinence, DMS iSPN intrinsic excitability was decreased after protracted abstinence resulting in fewer action potentials generated in response to 180–380 pA current injection compared to mice treated with saline  abstinence DMS iSPN intrinsic excitability was increased with an associated decrease in the AHP amplitude. In contrast to the current findings, repeated cocaine produces hypoexcitability in unidentified accumbal SPNs when measured at 3–4 days of abstinence56. Meth administration increases synaptic dopamine which inhibits iSPN activity via D2 receptor stimulation and would also favor LTD59; as a result, iSPN membrane excitability may compensate by increasing excitability in an attempt to restore firing rates. Consistent with this framework, our reported DMS iSPN hyperexcitability was associated with a decreased AHP amplitude; the AHP amplitude is regulated by calcium-activated potassium channels and accumbal homeostatic membrane plasticity was resultant from changes in SK-type calcium-activated potassium channels56.The observed hyperexcitability may be resultant from homeostatic membrane plasticity. Accumbal SPNs modify membrane excitability in response to shifts in excitatory synaptic input wherein increasing and antagonizing NMDA receptor activity produces a compensatory shift resulting in decreased and increased membrane excitability, respectively61. The observed DMS iSPN hypoexcitability was associated with a more depolarized AP threshold and hyperpolarized RMP but increased IR. While the change in the RMP and the change in IR broadly suggest changes in potassium channel expression and/or function, the effect on AP threshold points towards alterations in voltage-activated sodium channels. In the nucleus accumbens, repeated cocaine administration, which produces similar hypoexcitability (measured 3–4 days of abstinence), also causes a more depolarized AP threshold with reduced sodium currents and a hyperpolarized RMP 51. Additionally accumbal hypofunction is accompanied by decreased high voltage calcium channel potentials50. Taken together, current results and existing literature suggest multiple channels may contribute to the observed DMS iSPN hypoexcitability. These findings also suggest a dSPN biased DMS given that dSPN excitability was unchanged while iSPN excitability was reduced. The current report was not designed to investigate behavioral outputs; nonetheless, iSPN hypoexcitabillity without a concomitant change in dSPN function would render a dPSN biased DMS which may contribute to drug-seeking and/or consumption. Consistent with this, optogenetic stimulation of DMS dSPNs is reinforcing55 whereas D1 antagonism in the DMS decreases meth self-administration62 and meth-seeking12. D2 antagonism similarly attenuates meth-seeking behavior12 and infusion of the non-specific dopamine receptor antagonist 14. These combined studies suggest that addressing potential imbalance between iSPN and dSPN excitability may mitigate aberrant behaviors associated with stimulant abuse. Based on current findings, D2 antagonism in vivo would directly target meth-induced dysfunction by blocking dopaminergic inhibition of iSPNs, effectively disinhibiting them, whereas D1 antagonism would suppress dopaminergic drive of dSPNs, both of which would theoretically help to restore balance to a dSPN dominant DMS. It is important to re-emphasize that the current report is largely a characterization study. Mice were administered meth in the home cage with the goal of examining the effects of repeated non-contingent meth administration on striatal function. The above potential behavioral implications of the current findings are thus speculative but set a baseline to compare future investigations. Future studies employing self-administration models will be particularly valuable in determining whether (and if so how) contingency further shapes meth-induced striatal plasticity and implications for maladaptive seeking behaviors.In contrast to acute abstinence, protracted 21-day abstinence resulted in DMS iSPN hypoexcitability. This is consistent with findings in unidentified accumbens SPNs with cocaine, meth self-administration, and cocaine self-administration at 1–4 days abstinence as well as in meth sensitized rats at 17–25 days of abstinence47. In the current report we found no effect of repeated non-contingent meth administration on spine density in iSPNs or dSPNs suggesting that the number of axospinous synapses were unchanged. This is contrasted by a study showing decreased DMS and increased DLS spine density after chronic meth administration63. Similarly chronic amphetamine increased DLS spine density64. In both aforementioned studies, administration paradigms lasted for upwards of four weeks with an abstinence period of three months or longer. It is unclear whether spine dynamics in the dorsal striatum are resultant from overall lifetime intake of meth/amphetamine, duration of abstinence, or both. Additionally, despite no change in spine density, further study is needed to examine whether synaptic function is altered. For example, both alcohol and nicotine produce increases in DMS NR2B-NMDA currents that, for at least alcohol, contribute to consumption67.Spines on SPNs are the sites of glutamatergic axospinous synapses with most of these synapses forming corticostriatal circuits and a subset forming thalamostriatal circuits, particularly from centrolateral nucleusOverall, the presented studies point towards meth-induced dysfunction in the DMS with an emphasis on iSPNs. Moreover, changes in DMS iSPN excitability was dependent on the duration of abstinence. Further investigation is needed to elucidate the behavioral implications of our findings as it relates to substance abuse, maladaptive seeking behavior, and the potential role of contingency on plasticity differentiating DMS and DLS subregions.drd2 and Tdtomato under the drd1a receptor regulatory elements were bred in-house and maintained on a C57Bl/6 background. All experimental subjects were adult (> 8 weeks of age) male mice (n = 59 mice) that were hemizygous for transgenes. Experiments were conducted in male mice exclusively because meth-induced sex differences in rodents are reported at behavioral75, and molecular76 levels and because estradiol increases amphetamine-induced striatal dopamine release77. Future studies will be necessary to explore potential meth-induced sex differences in striatal dysfunction. Procedures were approved by the University of Minnesota Animal Care and Use Committee and in compliance with National Institutes of Health Guide for the Care and Use of Laboratory Animals and ARRIVE guidelines. Mice were group-housed on a 12-h light/dark cycle with food and water provided ad libitum; all injections and experiments were conducted during the light cycle. At approximately eight weeks of age experimental subjects were administered daily intraperitoneal (i.p.) injections in the home cage of either (+)-methamphetamine  or saline (10 ml/kg) for ten consecutive days. Subjects remined in the home cage for 1 or 21 days of abstinence prior to sacrifice.Mice expressing eGFP under the 2, 2.0 MgCl2, 26.0 NaHCO3, 1.0 NaH2PO4, and 16.66 glucose. Brains were removed and sagittal slices (275 µm thick) entailing the dorsomedial (DMS) or dorsolateral (DLS) striatum sectioned (Leica VT 1200S). Collected brain slices were transferred to a holding chamber containing normal aCSF  for > 30 min prior to experimentation. Carbogen (95% O2/5% CO2) was continuously bubbled throughout; aCSF solutions were pH ~ 7.4 and 310–320 mOsm.Mice were terminally anesthetized 1 or 21 days after the last saline or meth injection by 50 mg/kg ketamine/4.5 mg/kg xylazine (i.p.) and transcardially perfused with ice cold modified  artificial cerebrospinal fluid (aCSF) containing (in mM) 124.0 NaCl, 3.0 KCl, 1.0 CaCl. Patch pipettes were filled with internal recording solution containing (in mM) 135.0 KMeSO4, 5.0 KCl, 0.5 CaCl2, 10.0 HEPE-K, 2.0 ATP-Mg, 0.5 GTP-Na, 5.0 Phosphocreatine-Tris, 5.0 Phosphocreatine-Na, 0.1 Spermine, 0.05 Alexa 568, and 0.2 fluo-4; pH and osmolarity were adjusted to 7.25–7.30 and 270–280 mOsm, respectively. Whole-cell recordings were obtained in current clamp using a MultiClamp 700B amplifier (Axon Instruments) and PrairieView software (Bruker) consistent with prior studies44. Intrinsic excitability was examined in current clamp with successive 500 ms somatic current injections . The number of evoked action potentials, input resistance, and resting membrane potential were recorded; active membrane properties including rheobase , afterhyperpolarization amplitude, action potential threshold, and action potential height were also recorded. The afterhyperpolarization amplitude and action potential height were calculated as the voltage difference from the action potential threshold. Input resistance and the resting membrane potential are associated with potassium channels whereas the afterhyperpolarization amplitude is largely driven by calcium-activated potassium channel activity. The action potential threshold is linked to voltage-gated sodium channels whereas the action potential peak is the point in which sodium channels begin to inactivate and voltage-gated potassium channels open to repolarize the cell. Changes in these membrane properties therefore provide information that can guide future directions.Ex vivo brain slices were transferred to a recording chamber maintained at 32–34 degrees Celsius with continuous perfusion of carbogen-bubbled aCSF; iSPNs and dSPNs were identified based on eGFP or TdTomato expression, respectively, using an X-cite 110 LED (Excelitas Technologies) on a two-photon laser scanning microscope system (Bruker) consisting of a Nikon FN-1 microscope and Chameleon Ultra II two-photon laser (Coherent Inc.). Identified SPNs were patched under a Nikon 60X/1.00 W NA lens using thick-walled borosilicate glass pipettes (3–4.5 MΩ resistance) pulled on a P-1000 micropipette puller (Sutter Instruments)42. Line-scans (1.8 s duration) of dendritic shafts or spines were acquired in triplicate using a 10 µsec dwell time with 0.15 µm 42.Dendritic excitability was assessed by somatic current injection to evoke back-propagating action potentials (bAPs) and measuring the associated calcium signals via Fluo-4 fluorescence. Fluo-4 fluorescence was measured using 810 nm excitation by a two-photon laser  at proximal (30–60 µm from the soma) and distal (> 80 µm from the soma) dendrites and spinesz-series of proximal (30–80 µm from the soma) and distal dendritic (> 80 µm from the soma) segments were obtained using two-photon laser scanning microscopy (810 nm excitation) with 0.15 µm × 0.15 µm resolution, 0.3 µm z-steps, and 10 µs pixel dwell time44. Image J  was used to deconvolve z-stacks78 and semi-automated spine counting performed using Neurolucida 360 software . Spine densities for proximal and distal dendritic segments were averaged per neuron prior to statistical analysis comparing treatment effects.After electrophysiological recordings, post-hoc analysis; remaining datasets are presented as individual dot plots with a solid line depicting the mean and were analyzed using unpaired t-test or Mann–Whitney non-parametric test as appropriate . Tables present the mean t- or Mann–Whitney test as appropriate; Prism (GraphPad Software) was used for all statistical analyses. Current-spike response curves are presented as mean


Surface plasmons in graphene have mainly been affected by intrinsic optical phonons due to the vibrations of the carbon atoms and surface polar optical phonons (S-POPs) of the underlying dielectric surface. This plasmon hybridization dramatically changes the features of the plasmonic devices. However, a complete theoretical model for the graphene impedance to consider the optical phonons effects is yet remained to be developed. Here, we show how to derive a model for graphene impedance to include such impacts on graphene surface plasmons. Earlier models suffer from two limitations—i.e., the inability to show (i) the transformation of a single pure plasmonic mode into multiple hybrid plasmon–phonon excitations and (ii) the damping effect for energies beyond that of the intrinsic optical phonons due to the phonon emission. Our new model overcomes these two limitations. Then, we calculate the extinction spectra for a one-dimensional periodic array of graphene ribbons obtained through the impedance boundary condition method, addressing these obstacles. These spectra are directly related to graphene impedance, modeled using the dielectric function we developed in our earlier work. The extinction spectra show the presented model overcoming the limitations, firmly fitting the experimental data reported by others. Furthermore, we introduce our developed model for graphene to the CST Studio software to verify the accuracy of our extinction relation and impedance model. This study can be a step forward correctly predicting the behavior of graphene-based plasmonic devices. In particular, plasmon dispersion in graphene has been altered significantly by intrinsic and extrinsic optical phonons exposure11. Plasmons with energies higher than intrinsic optical phonons (≈ 0.2 eV) damp through inherent phonon emission into the intraband single-particle excitation region13. Furthermore, the extrinsic polar optical phonons of the surface  of the underlying polar-dielectric substrate significantly affect the dispersion of the surface plasmons of graphene. This interaction turns the primary plasmonic mode into several hybrid plasmon–phonon modes, depending on the number of S-POP excitation modes on the substrate surface, as we have demonstrated earlier5.Electron–phonon interaction is an inevitable source of scattering, strongly affecting carrier transport6. The existing resistance formulas for graphene proposed earlier15, obtained through semi-classical models, taking interband and intraband transitions into account and calculated electrical conductivity. Since these models neither include the impact of intrinsic phonons, nor that of extrinsic S-POPs, they suffer from two principal limitations. They can neither predict the plasmon damping phenomenon due to intrinsic optical phonon emission—i.e., demonstrated experimentally19, nor foresee the impacts of the extraneous S-POPs on the plasmon excitations for graphene loaded on polar dielectrics19. A substrate like SiC, hBN, or SiO2, with one or more (n) dominant vibrational S-POPs modes, splits a single graphene plasmonic mode into n + 1 hybrid plasmon–phonon modes. This effect is prevalent near the splitting energies, becoming negligible far from those values13. So long as the working frequency is near the phonon’s frequency, we should worry about the correctness of the impedance model in predicting the exact output extinction ratio. Notice, the semi-classical spatial dispersion model tolerable results for frequencies far from vibrational excitations in which the phonon effects are unimportant.Electron–phonon interactions enhance the graphene impedance, altering its extinction spectra—i.e., the amount of radiation lost by a sample as a function of frequency. In other words, electron scatterings result in loss of the energy and momentum of the carrier and hence, hinder the electronic response to an applied electric field due to the impedance enhancement. The scattering rate is directly associated with the number of optical phonons. Hence, to examine the impedance properly, the impact of the atomic vibrations must be considered, particularly at room temperature when the number of phonons is high enoughRPA}−1;19 (ii) The number of intrinsic optical phonons and extrinsic S-POPs. Our accurate and straightforward model includes these parameters. We also acquire an exact relation for evaluating extinction values, benefiting from the impedance boundary condition method, showing an excellent agreement between theory and experiment by utilizing the modeled impedance. Our new model indeed predicts the damping of hybrid modes for energies higher than that of the intrinsic optical phonons and the mode splitting caused by the extrinsic S-POPs. Moreover, we define our impedance model for graphene in CST Microwave Studio software and obtain the desired extinction values. One of the main limitations of the built-in graphene model in CST is that it is written based on the intraband and interband equations and does not include the effects of vibrational modes. However, we modify the model to the impacts of intrinsic and extrinsic phonons. The results show that the presented formulas work rightly, paving the way for accurate prediction of the experimental results.This work aims to overcome these discrepancies by introducing a new model for graphene impedance, taking the presence of intrinsic optical phonons and extrinsic S-POPs into account. In general, the impedance is directly related to two values: (i) The loss function, obtained by the imaginary part of the dielectric function, can be developed by random phase approximation (RPA)—i.e., Im{ε19. Here, we take in a 1D periodic array of infinitely long (in the y-direction) graphene ribbons of width wx and periodicity dx . Moreover, we obtain an extinction relation when a normal s-polarized  lightwave illuminates periodic plasmonic patterns, exciting surface plasmons on the graphene surface. A p-polarized light  cannot recognize the periodicity and hence does not excite surface plasmons19. We use the impedance boundary condition method to reach the desired extinction relation and apply the RPA dielectric function to introduce desired impedance.Different approaches are employed to excite plasmons in graphene, such as patterning into one or two-dimensional (1D or 2D) periodic arrays, like ribbons and discs, light scattering from structures adjacent to graphene, or coupling to a grating placed on top or below the graphene. The first approach is the most straightforward based on today’s technological progress. In this approach, by adjusting parameters like periodicity, width, or the spaces between nearby arrays, one can quickly obtain desired plasmonic peak frequency2 as a polar substrate with three dominant vibrating modes. Then, we compare the results of our theoretical model with the existing experimental results, showing perfect agreement among them. Moreover, we present the outcomes of software simulations to demonstrate our model’s correctness. The material introduced in CST software comes in Supplementary The organization of the rest of the paper is as follows. In the next section, after a brief introduction of Green’s function for an array of ribbons , we obtain the extinction ratio formula. Then, we model the graphene impedance in the presence of the optical phonons. Next, we present the numerical results, including extinction spectra of two periodic plasmonic arrays, one placed on a diamond-like-carbon (DLC) substrate—i.e., non-polar substrate—and the other on SiOwx and periodicity dx, placed on a nonpolar (polar) dielectric grown on an n++-Si together with the aluminum layer, acting as the ohmic contact to the gate material (the dielectric layer). As observed in the figure, by applying an appropriate external bias (VG) between the gate terminal and the aluminum contact on graphene, interconnecting the graphene ribbons, one can control the graphene chemical potential, μC. Letters m label the different orders of the transmitted and scattered waves in arbitrary directions depicted by red arrows.Figure 20,x′, z′) introduces y-expanded line source position, m is the scattered waves’ order, kxm(zm) is the wavenumbers along the x(z)-axis,Green’s function can represent the solution of Maxwell’s equations in 1D periodic structures, such as periodically arrayed graphene ribbons, considering a line source shifted by an appropriate phasekx(y) and k0 = 2π/λ represent the x(y)-component of the incident wavevector and the related wavenumber, with wavelength λ. Under a normal s-polarized illumination kx(y) = 0. So, according to 2(b), for kxm > k0, kzm becomes imaginary, degrading the Green’s function rapidly in the far-field region, z ≫ z′, making the reflected and transmitted lights invisible. For the sub-wavelength unit cell, the condition of kxm > k0 is valid only for m ≠ 0, meaning that only the zeroth-order scattered light can propagate20. Assume an array is positioned in an x–y plane at z′ = 0, ignore the terms m ≠ 0, and use the impedance boundary condition method20 to reach the extinction expression for the 1D array,η0 = 376.73 is the free space impedance and ZG,s(p) represents the impedance of a 1D periodic graphene array illuminated by an s(p)-polarized wave21RG is the graphene impedance that we will describe in the following sub-section.In (2a) and (2b), 1D and RG) are interrelated. So, to estimate the extinction coefficient accurately, we must genuinely predict the impedance magnitude. As we mentioned earlier, we have recently developed5 exact plasmon–phonon dispersion relations for graphene placed on polar substrates, using dielectric function expanded by RPA (See Supplementary RPA). Loss function, related to the Im{εRPA}−1, directly relates to the graphene impedance. The behavior of the loss function depends on the intrinsic optical phonons and extrinsic S-POPs5, which means the impedance also depends on the numbers of the inherent optical phonons and extraneous vibrational modes. So the impedance takes its value based on the type of the underlying dielectric substrate. In other words, the graphene impedance relation linearly depends on the total number of optical phonons obtained by the Bose–Einstein distribution22,Nphj and ћωphj stand for the number and energy of phonons of the j-th excited mode , ωphj is the related radian frequency, ћ is the reduced Planck’s constant, and kB and T are the Boltzmann constant and the ambient temperature, respectively. At low temperatures, the number of optical phonons is small enough not to participate in plasmon hybridization and damping. The phonon’s association starts to be significant as the temperature increases and, then, the impedance enhances due to the increased electron–phonon scattering. Therefore, the impedance directly links to the total number of phonons too. Hereafter, we work at room temperature, T = 300 K. Knowing all these, we introduce a new formula for the graphene impedance that is directly proportional to the loss factor and the total number of phonons,RPA follows (S9) and (S10) in Supplementary β (m−2) is a fit parameter, providing a perfect match between the experimental and theoretical extinction data. The value of the fit parameter strongly depends on the underlying dielectric type — i.e., whether it is nonpolar or polar, and the number of POPs oscillations for the polar material. For the fit to be practicable, we need some reliable experimental data to compare. Hence, we introduce the fit parameter (β) solely for DLC and SiO2, for which experimental data are available13. In other words, the model is a semiempirical one that applies to any nonpolar/polar dielectric material for which experimental data are available. To arrive at (6), we carefully examined all parameters that the impedance depends on, using experimental results reported earlier13, whereas previous studies solely considered the dependency of the impedance on either the number of phonons6 or the loss parameter13. Yet, other groups15 modeled the impedance using the Drude model, ignoring the phonons’ effect that is particularly crucial for operating near or above the phonon frequencies. Hence, to the best of our knowledge, (6) is the most accurate and straightforward equation describing the impedance that can be used to predict the behavior of the graphene-based plasmonic devices operating below the mid-infrared wavelength of ~ 6.2 μm.Based on (3) and (4), the extinction and impedance magnitudes (αwx ≤ 130 nm) and pitches dx = 2wx placed on a non-polar (DLC) substrate of relative permittivity εDLC = 5.7—i.e., similar structures used in an experimental study by13 —and calculated the extinction spectra, using (3) -(6) and (S9) with β = 5.29 × 1014 m−2, to have the best fit to the experimental data reported by13. The red dashes and blue cross signs (x) in Fig. 13 for graphene ribbons of the given widths and chemical potentials, μC = 0.3 eV. Then, introducing graphene as a material with impedance (6) in the CST Microwave Studio software, we calculate the reflection, R, and absorption, A, coefficients for the array of graphene ribbons on the dielectric, which results in the extinction spectrum through (A + R), as shown by the green dots in Fig. First, we considered arrays of graphene ribbons of widths  becomes narrower. Moreover, the corresponding spectral width becomes thicker, experiencing a blueshift. One may attribute these to the increase in the damping of surface plasmons. Various scattering mechanisms like electron scattering by background ionized impurities, optical phonons, the edge of the arrays, and electron–hole generation within the single-particle excitation region may dampen the plasmons, becoming less probable as wx increases. Background scattering highly depends on the fabrication process, and for a well-made graphene layer, the electron lifetime due to impurities takes the value of 85 fs13. The surface plasmons induced on a superstructure are affected by intrinsic phonons. They damp through emitting inherent phonons and enter the phonon emission (PE) continuum if their frequency becomes more significant than ωop 13. For ω < ωop, where the phonon emission is not considerable, the edge scattering, resulting in high-energy high-momentum intervalley phonon emission2, is the dominant effect among damping processes. So, plasmon peaks lessen as the width decreases—decreasing width equals heightening edge effects. In addition, plasmons fall within the interband single-particle excitation continuum and decay into electron–hole pairs at frequencies much higher than that of inherent optical phonons’. Our desired frequency range does not include electron–hole excitations.As shown in the figure, the extinction spectrum for each array, with given qpl ≈ π / (wx−w0), in which w0 ≈ 28 nm is the electrically inactive width of structured graphene13. The open circles and crosses ( ×), in Fig. qpl, obtained from (3) and the experimental data13, as shown in 2(a). The dashes represent the dispersion relation obtained for the similar graphene ribbons arrays on nonpolar substrates5,e is the elementary charge, ε0 is the free-space permittivity and εenv is the average dielectric constant of the upper and the lower media surrounding the graphene array, andq′ = 2πε0εenv(ℏωop)2/e2μC as the plasmons wavenumber at the frequency ω = ωop, vanishing at qpl ≪ q′ —i.e., γ(qpl ≪ q′) → 0. Figure In 1-D periodic arrays, the plasmons’ wavenumber μC causes a blueshift in peak frequency. So, we have considered an array of widths wx = 100 nm and calculated the extinction spectra while varying the chemical potential in the range of 0.3 eV ≤ μC ≤ 0.5 eV. Figure μC. As seen from this figure, one can conclude that the narrower the width of the ribbons, the larger the blueshift caused by an increment in μC. This figure gives us a piece of valuable information about how to choose a design parameter. Considering a CO2 laser of operating frequency ~ 28.5 THz (0.117 eV)19 as the light source, the best choice for wx of the graphene ribbons with chemical potential in the range of μC ~ 0.3–0.4 eV would be 80–100 nm.Another critical factor in determining the extinction peak frequency is the graphene’s chemical potential for a given array. According to (7a), entclass1pt{miniman + 1 coupled plasmon–phonon modes, where n is the number of the extrinsic vibrational frequencies5. Here, we consider two arrays of graphene ribbons of wx = 240 and 160 nm and μC = 0.6 and 0.45 eV, placed on SiO2 slabs — i.e., a polar dielectric with n = 3 and ħω1, 2, 3 = 100 meV (24.63 THz), 134 meV (32.68 THz), and 144.8 meV (35.32 THz), just the same as those used in two independent experimental studies19. The red and green dashes in Fig. 13 and magenta19, respectively), using the fit parameter β = 3.063 × 1012 m−2. The green and red dots in this figure depict the corresponding numerical results obtained by CST simulations, using Eq.  for this case is the total number of phonons provided for all vibrational frequencies.Electrons in graphene placed on polar substrates are exposed to both intrinsic and extrinsic phonons. Besides the effects of intrinsic phonons mentioned in the previous subsection, extrinsic phonons cause mode splitting around their vibrational frequencies and turn single plasmonic mode into m1 − m4, seen in this figure, denote the peaks of the four coupled plasmons-phonons modes for both arrays, with center frequencies ωm1 < ω1, ω1 < ωm2 < ω2, ω2 < ωm3 < ω3 and ω3 < ωm4. A notable feature shown in this figure is the damped peak of the third coupled-mode denoted by m3. The third mode starts to rise at a frequency greater than ω2. However, the proximity of the S-POPs frequencies ω2 and ω3 prevent the third hybrid mode, m3, peaks significantly. In other words, the mode m3 is too weak to be practically identified as an exciting hybrid mode. Here again, the closeness of the results from our theoretical model to the experimental results confirms the accuracy of the developed model. Nonetheless, the minor deviation between the fit with two different experimental results could be due to a slight dependence of the fit parameter on μ.CThe labels 13, varying the widths of the graphene ribbons in the range of 60 ≤ wx ≤ 240 nm and keeping the chemical potentials constant, μC = 0.6 eV. Then, we calculated the extinction spectra in the frequency range of 10–100 THz (0.041–0.41 eV)  as wx decreases, each resonance peak for a given array exhibits a blueshift that differs from one to another; (ii) unlike the other three modes, the blueshift exhibited by ωm3 is insignificant because of the closeness of ω2 and ω3, as mentioned earlier; (iii) the weight of the mode intensity transfers from m1 to m2 and then to m4, before the resonance peak for m4 reaches the onset of the PE continuum (ωm4 → ωop), beyond which it starts to damp through the emission inherent phonons (a similar phenomenon observed by5); (iv) the linewidth of m4 increases as ωm4 → ωop and beyond, due to the damping through intrinsic optical phonon emission.Next, we further compared the model with the experimental results ofeV) Fig. a and theqpl ∝ (wx−w0) −1. The open magenta circles and blue crosses represent the peak frequencies obtained from (3) and the experimental results of13, respectively. The four dashed curves show the dispersion curves obtained from (23) of5. Moreover, the red dots show the dispersion of the surface plasmons resonance (SPRs) on the graphene array ignoring the effects of the intrinsic and extrinsic optical phonons. A comparison of these data reveals the coupled modes peaks and SPR frequencies coincide far from splitting energies, where S-POPs have negligible effects, providing only electrons participate in the excitations. Hence, the hybridization of the plasmon–phonon prevails as the frequencies of hybrid modes and phonons are in proximity.Figure μC, on the center frequencies of the extinction peaks (ωm1-4), varying the ribbons' widths  to achieve the desired hybrid mode frequency. These plots also confirm the blueshift exhibited by each extinction peak as wx decreases, for a given chemical potential, varying from one mode to another. Moreover, a common feature observed for the resonant peaks m2, m3, and m4 is not true for m1, that the narrower the ribbons in the array, the larger the blueshift exhibited by the resonant peak as μC increases. Furthermore, a variation in the chemical potential has influenced ωm4 the most for the narrowest ribbons.Finally, we investigated the effects of the graphene chemical potential, see Fig. . The Hor4 in Fig. ωop. It is evident that for peaks’ frequencies higher than ωop, the resonance peak damps more rapidly due to the inherent phonon emission.By extracting full width at half maximum (FWHM) of the hybrid mode m2, dielectric and then calculated extinction spectra, which match with the experiment perfectly. Our results demonstrate that the S-POPs convert a single pure plasmonic mode into multiple hybrid plasmon–phonon resonances, which have never been shown theoretically. Moreover, our presented model predicts the damping caused by optical phonon emissions. Our article provided a new formula of extinction based on the impedance boundary condition method, which the experimental data and CST simulation confirm.Utilizing the dielectric function obtained by random phase approximation and the number of optical phonons, we have modeled the resistance of graphene placed on a non-polar, DLC, and polar, SiOSupplementary Information.


Stretchable sensors, as the important components of flexible electronic devices, have achieved progress in a variety of applications for monitoring physical or environmental conditions, such as sound, temperature, vibration, and pressure. However, it still remains a challenge to fabricate high performance stretchable humidity sensors. Herein, we present a novel stretchable humidity sensor, which was fabricated based on an ultrastretchable polyaniline composite fiber. Because of the composite fiber with a “twining spring” configuration  it maintains a stable electrical conductivity up to a strain of 200%. In addition, the conductivity of the composite fiber remains perfectly stable after 5000 cyclic stretching events of 200% strain. Incorporating the humidity sensitive properties of nanostructured polyaniline, the stretchable humidity sensor based on the composite fiber effectively maintains its humidity sensitivity at different elongations. In this work, a highly stretchable humidity sensor based on spandex covered yarns and nanostructured polyaniline was fabricated, and maintains its humidity sensitivity well at different elongations. With the rapid development of stretchable electronics, it has become increasingly urgent to develop a new generation of stretchable sensors.In recent years, stretchable electronics as an emerging and interesting research scope has motivated intensive efforts from materials scientists and engineers. This new class of electronics has opened up a wide variety of extraordinary application fields, including stretchable displays,8,9 gas sensor,10,11 bio-sensor,12,13 and strain/pressure sensor,14 Recently the importance of humidity sensing has been well understood and a great deal of research has focused on the development of humidity sensitive materials because humidity sensors have gained increasing applications in industrial processing and environmental control. It is verified that PANI is sensitive to humidity because its conductivity changes in the presence of water vapor due to the “proton effect”.15 Numerous studies also have reported16–21 humidity sensors, constructed based on PANI or its derivative materials. In general, chemically prepared PANI materials are usually powdery and have poor mechanical properties. To fabricate stretchable and flexible devices based on PANI material, the common approach is to prepare functional composites by incorporation of PANI into a rubbery polymer matrix through blending.22,23 However, simultaneously increasing stretchability and electronic conductivity is challenging because these properties are competitive, and the conductivity of those composites decreased significantly under strain tension. An alternative strategy is to use the stretchable materials as a fiber-core or substrate and cover them with PANI.14,24 In order to increase stretchability, a patterned poly(vinylidene fluoride) (PVDF) nanofibrous membrane was prepared via electrospinning and coated with PANI by in situ polymerization.14 Although the patterned nanofibrous membrane could be stretched up to 110%, the conductivity decreased significantly with the increase of deformation. As mentioned above, these stretchable materials based on PANI are more suitable to be considered for assembling strain/pressure sensors than humidity sensors because the conductivity of the material to fabricate a stretchable humidity sensor must remain stable when tensile deformation occurs. Recently, Lim et al. prepared different types of stretchable composite materials and discussed the resistance change depending on applied strain.24–26 They reported a stretchable humidity sensor based on a wrinkled polyaniline nanostructure. However, the performance of the sensor was not stable, particularly at low level humidity and a high elongation range above 30%.Polyaniline (PANI), as an environmentally stable conducting polymer, has been widely studied due to its unique properties, such as simple preparation and doping procedure, relatively high conductivity and low cost. To date, many sensors based on PANI material have been fabricated successfully for application in different fields, such as chemical sensor,in situ polymerization, serving as the conducting component. Since the unique spiral configuration of the SCY preserves extremely large prestrain, no actual elongation of the conducting component takes place when the composite fiber is stretched. It can be stretched up to 200% and maintains a stable conductivity at different elongation. The composite fiber also possesses superb cyclic performance without making any compromises on overall performance after 5000 stretching events of 200% strain and the conductivity changes only slightly due to the variation of ambient temperature from 20 to 40 °C. The stretchable humidity sensor based on the composite fiber was fabricated, featuring with good humidity-sensitivity, fast response, and good repeatability. In addition, the characteristics of the textiles allow them to be employed in the health, leisure and sports industries.Until now, it still remains a challenging task to develop a facile, cost-effective, and scalable way to prepare highly stretchable conductive materials, which are suitable for fabricating stretchable humidity sensors. In this study, we report the facile fabrication of highly stretchable composite conductive fibers based on spandex covered yarns (SCYs) and nanostructured PANI for the first time. The composite fiber comprises a selected SCY, serving as an elastic scaffold and nanostructured PANI, formed by 22.114,27 First, an aqueous solution of APS (used as an oxidant) was prepared by dissolving 9.1 g of APS in 100 mL of deionized water. Further, 3.72 g of aniline was dissolved in 100 mL of aqueous solution, which contains 5.08 g of SSA. Then, the APS solution was mixed dropwise to start the oxidation. In order to obtain the SCY–PANI fibers, the as-prepared SCYs were immersed in the blended solution, and the obtained mixture was kept steady for 12 h with the reaction temperature at about 4 °C. In the end, the SCYs turned from the original milky white colour to dark green, along with some dark green precipitate formed in the reaction vessel due to small amount of PANI prepared in the polymerization process. Then, the SCYs were taken out and washed with distilled water several times to remove any of the oxidant present till the filtered water became colourless. Finally, the prepared fibers were dried in a vacuum oven at 45 °C for 48 h.Some SCYs were taken directly from the SCY spindle  with an accelerating voltage of 15 kV. Humidity sensitive properties of the sensors were investigated by recording their electrical response to relative humidity. A schematic diagram of the humidity-sensing measurement system in our laboratory is displayed in 33.1As a type of cotton/spandex yarn, the SCY is inexpensive and widely used in the textile industry. Typically, the high-elastic polyurethane monofilament served as the core fiber and was tightly wrapped by a cotton yarn, which consists of a large amount of cotton fibers, such as a compressed spring . This tyR/R0)/S, where R0 is the initial resistance and ΔR is the variation of resistance after being stretched to a strain of S, was calculated for different strains. Clearly, the smaller the figure of merit, the higher the capability for the stretchable fiber to preserve its conductivity. Recently, another study reported an ultrastretchable composite fiber, which also used the SCY as the fiber core and covered with silver nanowires as the conducting component.28 The figures of merit for this case are 0.251 and 0.199 at strains of 100% and 200%, respectively. In our study, the figures of merit for the sensor 1# are 0.173, 0.152, 0.058, and 0.087 at strains of 50%, 100%, 150%, and 200%, respectively, indicating the superior stability of conductivity during the deformation.The key to realizing stretchable electronics is the simultaneous incorporation of excellent mechanical robustness and relatively stable electronic performance. In particular, for fabricating the stretchable humidity sensors, the material must maintain a stable electrical conductivity at different elongations. The effects of imposed severe deformation, such as stretching and bending, on the electrical conductivity of the sensors were investigated herein. In this investigation, three sensors were fabricated based on the SCY–PANI fiber segments, which were selected at random and marked as 1#, 2#, and 3#. A practical stretchable humidity sensor must possess stable performance. Because there was an acidic environment, the mechanical properties became poor during the process of producing SCY–PANI fibers. By adjusting the weights of SSA in the reaction process we can obtain SCY–PANI fibers that have relatively good mechanical properties. In our study, no significant changes in appearance and mechanical properties of the SCY–PANI fibers were observed after 5000 cyclic stretching events of 200% strain. We further undertook a cyclic stretching test of the sensor so as to evaluate the stability of the electrical property, which was a crucial factor from the viewpoint of practical applications. 3.229 Due to polymerization by strong oxidant (APS) and the un-bonded electron pair on the nitrogen atom, PANI has a chain with the protonated reduced (NH2+) and oxidized form (NH+). As evidenced by the NMR experiment, the proton transfer from or to the polymer takes place in the presence of water molecules.30 It is because of the existence of these protons, the electron transfer from NH2+ to the NH+ becomes easier. Thus, absorbed water plays an important role in the conductivity.31 Variation of voltammetry curves of as-prepared humidity sensor at the different relative humidity (% RH) are presented in It is reported that water increases the electrical conductivity of PANI through an increase in the interchain electron transfer and/or by increasing the mobility of dopant ions.Typical response transients of as-prepared humidity sensor obtained from SCY–PANI fiber during cycle tests are shown in 4In summary, we demonstrated the highly stretchable humidity sensor, which was fabricated based on a PANI composite fiber. The fabricated sensors stably maintained their good performance up to a strain of 200%, which benefited from the unique “twining spring” configuration of the composite fibers and the humidity sensitive properties of the PANI. In addition, the PANI composite fiber possesses a superb cyclic property and has the advantages of low cost, simple preparation, and scale production. We believe that the advantages of our fabrication strategy can be extended to environment and health monitors, sensory skins for robotics and many other applications of stretchable electronics.There are no conflicts to declare.


In hospitals, trained medical staff are often, in addition to performing complex procedures, spending valuable time on secondary tasks such as transporting samples and medical equipment; or even guiding patients and visitors around the premises. If these non-medical tasks were automated by deploying mobile service robots, more time can be focused on treating patients or allowing well-deserved rest for the potentially overworked healthcare professionals. Automating such tasks requires a human-aware robotic mobility system that can among other things navigate the hallways of the hospital; predictively avoid collisions with humans and other dynamic obstacles; coordinate task distribution and area coverage within a fleet of robots and other IoT devices; and interact with the staff, patients and visitors in an intuitive way. This work presents the results, lessons-learned and the source code of deploying a heterogeneous mobile robot fleet at the Tartu University Hospital, performing object transportation tasks in areas of intense crowd movement and narrow hallways. The primary use-case is defined as transporting time-critical samples from an intensive care unit to the hospital lab. Our work builds upon Robotics Middleware Framework (RMF), an open source, actively growing and highly capable fleet management platform which is yet to reach full maturity. Thus this paper demonstrates and validates the real-world deployment of RMF in an hospital setting and describes the integration efforts. In hospitals, trained medical staff are often spending valuable time on secondary tasks such as transporting medicine and laboratory samples . If thesAutomating transportation tasks requires autonomous human-aware robotic mobility system that can among other things navigate the hallways of the hospital ; predictWe present the results, lessons learned and the source code of deploying a heterogeneous mobile robot fleet for transporting time-critical samples from an intensive care unit to the laboratory at the Tartu University Hospital. These autonomous mobile robots navigate narrow hallways with intense crowd movement. Our developed system showcases the level of maturity for several technological capabilities and tools. Among them, the Robotics Middleware Framework (RMF) , an openThis work focuses on automating the delivery of objects across the premises of a hospital. The primary use-case is defined as transporting time-critical samples, e.g., blood samples, from an intensive care unit to the hospital lab. This section will first provide a detailed overview of the hospital environment and associated challenges, followed by the description of an openly available software framework for robotic fleet management, the RMF, used as a basis for our particular use case. All our application-specific source code, configuration files and setup instructions are openly available via GitHub  and retrieving (ingest) the samples from the robot and verifying via single-button GUI on the touchscreen mounted to the robot. Technically samples can be transported without incorporating RMF’s dispensing and ingesting mechanism, but doing so allows RMF to see if the robot is involved in a dispensing or ingesting sequence, i.e., unavailable./door_requests” topic).This section describes the procedure of deploying the RMF setup in a new environment, as well as how new heterogeneous robots can be appended to the existing RMF fleet. The following chapters only cover the fundamental steps for a concise overview. Please refer to our online materialsAnnotation: The floorplan is annotated in the Traffic Editor by adding walls, traffic lanes, chargers, locations, doors, etc. Additional items, such as furniture or people, are added as the annotated map can be to generate a simulated environment.1) Mapping: The physical environment is mapped with tools such as OpenSlam Gmapping (2) Gmapping  to generAlignment: The grid map is aligned with the floorplan inside the Traffic Editor. This is necessary for obtaining the coordinate transformation between the two map representations.3) Configuration: ROS2 launch files are configured to start-up RMF with the appropriate environment and coordinate transformation obtained from the previous step. Examples can be seen in our online materials at GitHub.4) RMF is designed for static environments having a fixed number of walls, doors, elevators. Thus a floorplan of the environment is the basis for setting RMF up, followed by:Mapping: ROS-based robots require a grid map for navigation. An existing map can be reused or a new one created. This map can be shared with all members of the fleet.1) FreeFleet preparation: Each robot is paired with a FreeFleet client application, which is normally installed on robot’s onboard computer. A FreeFleet server is also installed on the computer hosting RMF and normally one FreeFleet server instance is needed per homogeneous fleet.2) FreeFleet server configuration: The name of the fleet is configured in the server along with the DDS configuration.3) RMF fleet adapter configuration: RMF uses the characteristics of the robots within the fleet for traffic scheduling. These characteristic values are described in the RMF fleet adapter configuration file. Note that heterogeneous robots can technically be combined under single RMF fleet adapter and FreeFleet server, but RMF is then unaware of each robot’s individual technical characteristics, which can potentially lead to undefined behavior.4) FreeFleet client configuration: If the robots’s ROS Navigation topic and action names are different from default values, FreeFleet client is configured for the correct names. The client is set-up with identical DDS configurations and a fleet name as the server.5) As RMF is based on ROS, any mobile robot supporting ROS1 or ROS2 with a NavigationThe feasibility of this work was validated via a full scale deployment, where PAL Robotics TIAGo successfully transported blood samples from ICU to the lab . A videoUse time optimally—Test your system starting from simulation, then in a similar physical location and finally in the actual deployment area. This allows to maximize the valuable time spent on-site for testing and discovering new challenges, not debugging issues that could have been caught earlier.• Try to avoid reliance on public networks—While the hospital had a public Wi-Fi available, using a 4G network had fewer technical constraints . However, it was crucial to test for any signal coverage dead zones.• Get DDS right—ROS2 relies on DDS for communication. Make sure that your configuration is set up properly, e.g., supports multicast communication and all nodes have the same DDS configuration.• Double-check the navigation maps—Mapping large areas will likely result in skewed maps due to the cumulative uncertainty of state estimation. A more accurate map can be obtained by mapping the area in smaller sections and merging the sub-maps manually with an image processing software. Also maps should be carefully reviewed to remove any artifacts  that might result in undesired navigation behavior.• Stay out of the way—Make sure that the robot spends a minimal amount of time in the vicinity of the elevators and as close to the walls as it can, as the hospital’s traffic is very intense and time critical. Use a two single direction traffic lane layout wherever possible.• The successful deployment of this work is a result of thorough testing and validation, which has lead to accumulation of design and deployment related recommendations:Waiting out congestions—Narrow hallways get congested and in such situations it would be best for the robot to wait in a safe area until the congestion is cleared. However this would require a) a way to detect congestion and b) a method of informing RMF about the potential blockade. At the moment RMF does not support such behavior.• Emergency stopping—The medical staff must be able to halt the robot and get it out of the way. Thus there is a tradeoff between the bulkiness and the functionality of the robot. A well equipped mobile manipulator is functionally very capable but also potentially heavy.• Safe integration of legacy infrastructure—Most hospitals do not have programmatically controllable elevators and doors. While we created a temporary solution for opening the doors  for sample handover is a necessary addition to the manual dispensing and ingesting setup.• Utilizing an industrial mobile manipulator—As a continuation of the previous point, we are transitioning from TIAGo to a mobile manipulator based on the MiR100 mobile platform and UR5e manipulator  in a testing environment, we are yet to apply multiple delivery robots inside the Hospital, which would potentially increase the sample delivery throughput.• Covering more tasks—Due to the peculiar layout of the Tartu University Hospital, people tend to get lost in its premises. The medical staff has admitted that during critical periods, guiding people can take up too much of valuable time. Thus we are actively developing a robot for guiding people around the hospital.• This work demonstrated the feasibility of transporting objects with mobile robots, and utilizing the Robotics Middleware Framework as the core for coordinating robots and building’s infrastructure, such as doors. Our setup was validated in Tartu University Hospital, where PAL Robotics TIAGo transported blood samples from an active ICU to the lab through busy hallways. The ongoing and future work will focus on:


The characteristics of ionic and electronic currents flowing through the matrix with the superposition of cyclic potentials ± 100 mV were studied. The high stability of the composite was established during prolonged cycling (130 h) in an electric field with a frequency of 0.016 Hz. It was established that the composite films based on polyimide and graphene have good biocompatibility and are not toxic to fibroblast cells. It was shown that preliminary electrical stimulation increases the proliferative activity of human dermal fibroblasts in comparison with intact cells. It is revealed that an electric field with a strength E = 0.02–0.04 V/m applied to the polyimide films containing 0.5–3.0 wt.% of the graphene nanoparticles activates cellular processes .In this work, an electrically conductive composite based on thermoplastic polyimide and graphene was obtained and used as a bioelectrode for electrical stimulation of human dermal fibroblasts. The values of the electrical conductivity of the obtained composite films varied from 10 The human organism has an endogenous bioelectric system that constantly produces and receives natural electrochemical signals in various tissues, such as the nervous system, skin, muscles, heart, bones, etc. In recent decades, it has been demonstrated that exogenous electrostimulation can be used to modulate fundamental aspects of cell vital activity and behavior: adhesion, migration, proliferation, apoptosis, and differentiation. Vital functions and behavior of many types of cells can be effectively controlled by delivering electric signals through a conductive scaffold . The posTo understand the mechanism of the influence of electrostimulation at the cell level, it is first necessary to determine whether the electric field affects a cell directly or indirectly . The electric field can act upon a cell in one of the following ways. First, it can act inside the cell and affect the profiles of motion and concentration of charged cytoplasmic molecules. Second, it can change the transmembrane potential that has an influence on membrane reaction and activates ion transport through the plasmatic membrane . Third, the electric field can act along the plasmatic membrane and cause electrophoresis-assisted accumulation of surface molecules or modulate conformational states of membrane proteins, which affects the cell-substrate interaction and adhesion mechanisms .In addition to reactions of the cells that are traditionally considered electroactive , the influence of various electrostimulation protocols on keratinocytes, dermal fibroblasts , and adiAdvances in materials science, microelectronics, and tissue engineering facilitated the development of bioelectronic technologies, which involve the use of biocompatible polymer-based composite materials. Introducing fillers  into a polymer scaffold makes it possible to adjust the properties of the resulting nanocomposites, namely, to increase their mechanical strength and elasticity, modify surface properties, and vary the value and type of conductivity ,9,10,11.2O3, TiO2 ..52].The results of the study of the structure of composite films based on R-BAPB containing graphene particles by the SEM method are shown in It is shown that the initial film has a dense layered structure. The PI layers are oriented mainly in the plane of the film . IntroduThe composite films on the basis of aromatic PI and graphene should possess sufficient mechanical strength and deformation properties for application as bioelectrodes in cell technologies. The research demonstrated that the strength of the films containing 0.5–1.0 wt.% of graphene is equal to 75–85 MPa, and their tensile strain is equal to 35–45%. The films possessing these mechanical characteristics can be subjected to various technological manipulations both in air and in liquid media. An increase in graphene percentage is observed to lead to a decrease in strength and tensile strain, which is caused by the formation of a graphene percolation cluster.−15 S/m) and can be classed as a dielectric material, which agrees with the data reported in [orted in . An incrGraphene particles form a dimensionless conducting cluster; its conductivity is partially caused by the tunnel transition of electrons from one graphene particle to another. With increasing the graphene percentage in composites, electronic conductivity begins to prevail. The dependences of the electric conductivity of the PI/graphene composite films on the frequency of the electric field are shown in The study of the influence of the electric field on cell processes requires information about the value and type of the current flowing through the film placed into the measurement setup. The composite films were studied both in the dry state and in a physiological solution (0.9% aqueous solution of NaCl), i.e., under conditions approximated to the procedure of electrostimulation of the cells.When the content of graphene is equal to 3.0 wt.%, the conductivity of the composite film reaches 100 S/m, and the conductivity of the film containing 0.5 wt.% is equal to 0.1 S/m; i.e., this value decreases by more than three orders of magnitude. This value of conductivity is one order of magnitude lower than the conductivity of the physiological solution. For dry samples (red lines), all voltage-current relationships are linear -2,5-diphenyltetrazolium bromide) . OpticalAll tissues of a living organism exhibit some degree of electrosensitivity. Their normal functions depend on electric signals delivered to cell membranes and can be modulated via exogenous electrical stimulation. Adhesion, proliferation, and differentiation of cells of an organ or a tissue can be controlled by changing parameters of electric impulses . In the present work, human dermal fibroblasts were used in the investigation of the influence of the electric field on cell processes. The choice of the type of electric signal was based on the assumption that the use of an alternating current would help avoid the negative influence of prolonged action of a direct current  .2 to 1000 μA/cm2 constitute a critical factor in the launching and regulation of several important biological processes, including regeneration of damaged skin and soft tissues [Bioelectric currents with densities varying from 0.1 μA/cm tissues . Therefo tissues ; the autThe authors of ,58 estimThe CI values obtained for the cells stimulated on the composite film containing 0.5 wt.% of graphene at amperage ±0.4 μA and field strength 0.02 V/m at the time points corresponding to efficient adhesion and maximum proliferation are higher than the CI of the intact cells a. As shoThe CI values for the cells stimulated on the composite film containing 1 wt.% of graphene at amperage ±20 μA and field strength 0.4 V/m at the time points corresponding to efficient adhesion and maximum proliferation are virtually similar to those of the intact cells b. It wasThe CI values for the cells stimulated on the composite film containing 3 wt.% of graphene at amperage ±2500 μA and field strength 1 V/m at the time points of efficient adhesion and maximum proliferation are lower than the corresponding parameters of the intact cells c. When tThe CI value for the cells stimulated on the composite film containing 3 wt.% of graphene at amperage ±100 μA and field strength 0.04 V/m at the time point corresponding to efficient adhesion is lower than that for intact cells. However, at the time point corresponding to efficient proliferation, CI increases significantly and exceeds the value for intact cells c. As sho−15 to 102 S/m with increasing graphene content (from 0 to 5.0 wt.%).The conducting composite films on the basis of R-BAPB filled with graphene were prepared. The incorporation of graphene into a polyimide matrix had a significant influence on the structure, electrical conductivity, and mechanical properties of polyimide. The values of specific conductivity of the composite films increased from 10Analysis of the voltage-current relationships of the composite films obtained in the dry state and in the physiological solutions in the voltage range ±100 mV showed that in the sample containing 0.5 wt.% of graphene, ionic conductivity (caused by electrolyte ions) prevails. In the case of the film containing 3.0 wt.% of graphene, electronic conductivity is predominant; the current flows on the surface along the film.The results of the MTT test imply that the R-BAPB/graphene composite films are biocompatible and thus can be used as flat bioelectrodes in the studies of the influence of the electric field on the adhesion, proliferation activity, and differentiation of stem and somatic cells and as interfaces in medical devices.The studies of the dependence of the cell index (CI) on cultivation time demonstrated that the films containing 0.5 wt.% of graphene (which possess mostly ionic conductivity) can be efficient as electrodes in the investigation of the influence of the electric field on the adhesion and proliferation activity of the human dermal fibroblasts.It was demonstrated that an electric field with strength E = 0.02–0.04 V/m applied to the R-BAPB films containing 0.5–3.0 wt.% of the graphene nanoparticles activated cell processes . This result can be used to treat the skin.


Ionic Polymer Metal Composites (IPMCs) are in high demand owing to the ongoing advancements in technology for various applications. New fabrication techniques and a quick retort towards the applied load are the significant reasons for considering IPMCs in smart devices. Here, a Teflon fabric-reinforced Nafion (TFRN) membrane is used to create an IPMC. The materials employed as electrodes are silver and nanofillers. The basement membrane, Nafion 438 (N-438), is sandwiched between the electrodes using a chemical decomposition technique. Subsequently, the electromechanical properties (actuation) of the membrane are tested. The micro and molecular structure of the IPMC membrane coated with Silver (Ag), Ag-Carbon nanotubes (CNTs), and Ag-Graphene nanoparticles samples are examined with the help of SEM and X-ray diffraction (XRD). The membrane scratch test is carried out to evaluate the abrasion and wear resistance of the membrane. The lowest coefficient of friction is shown by N438 + Ag + Graphene (0.05), which increased by 300% when compared to a pure N438 membrane. The hydration and tip deflection test were also performed to understand the water uptake percentage. At 90 °C, the highest water uptake was observed for N438 + Ag + Graphene (0.05), which decreased by 60, 42, 23, 14 and 26% when compared to N438, N438 + Ag, N438 + Ag + CNT (0.01), N438 + Ag + CNT (0.05) and N438 + Ag + Graphene (0.01), respectively. A proportional relationship between hydration level and tip deflection is observed and the highest bending performance is observed for the N438 + Ag + Graphene (0.05) membrane. Ionic polymer metal composites (IPMCs) are categorized as Electro-active Polymers (EAP), which have an inbuilt tendency towards sensing and actuation . PerformIn recent decades, at various conditions and constraints, the nature of Nafion with respect to the ion exchange rate has been analyzed . Nafion 3O4 coated with SiO2 are observed with a weak band around 18° to 29° due to the development of amorphous silica encompassing Co3O4 [3O4 [4/H2O2). For CNT-Graphene, broad peaks are observed clearly at 25.7° [For pure Nafion, XRD peaks are observed at 19° and 40° , which ing Co3O4 . From th3O4 [3O4 . Uzundur3O4 [3O4  synthesiat 25.7° , whereasat 25.7° . Zhang eat 25.7°  investigat 25.7°  investigat 25.7°  investigat 25.7°  fabricatat 25.7°  identifiw/v ratio) and Ag-graphene (graphene with 0.01 and 0.05 w/v ratio) are novel contributions to the relevant field.Clearly, the literature indicates that no work was carried out on either coated (nano) or uncoated N438 (Teflon Fabric Reinforced Nafion (TFRN)) membranes. Nonetheless, the performance (as actuators and sensors) of the Nafion can be enhanced by the addition of nanoparticles over the Nafion membrane. In the current work, electromechanical actuation as well as determination of the morphological properties of the Nafion 438 membrane  monofilament reinforcement with dimensions of 300 × 300 × 0.320 mm3. This is also known as Teflon Fabric Reinforced Membrane (TFRN). Uniformity in expansion and less leakage are its notable features.The N438 membrane was acquired from the Power NafionSilver nitrate, which is less soluble in compounds with ether groups and more soluble in aqueous ammonia, was purchased from Fisher Scientific Co. in crystalline form, with more than 98% purity and with a melting point of greater than 200 °C.3. The length of the particle is approximately between 5 and 10 µm, whereas the outer diameter of the particle is 40 to 60 micrometers. To improve the properties of the CNT, chemical treatment was carried out, as reported by Sreekanth et al. [CNT powder was purchased from M/s Shenzhen Nanotech Port Co., Ltd., Shenzhen, China, with 95% purity, with a density of 2.16 g/cmh et al. .Graphene  was purchased from Platonic Nanotech with more than 98% purity and a thickness of 2 to 10 nm. It has a honeycomb lattice and multiple layers of carbon. Using JSM-IT500 InTouchScope™/Jeol Scanning Electron Microscopy , the surface morphology of the specimens was studied at various magnifications. The experiment was performed on a sample size of 5 mm × 10 mm at 30 kV with accelerating voltage.Using a JCM-6000 PLUS/Jeol , elemental characterization was carried out on all the samples (sample size −5 mm × 10 mm) with a 512 × 384-pixel resolution in the energy range of 0–20 keV and 15 kV.To further identify the chemical composition and structure of the prepared samples, an XRD analysis was performed using S-3700N—Hitachi (at 40 kV and 30 mA) . The scan range is 10.000 to 80.000, with a scan speed of 6.0000 (deg/min).The scratch test was performed on a DUCOM Scratch tester TR-101-IAS, which has a load of up to 200 N . The scratching speed was 10 mm/min with a loading speed of 2 and 3 N/min. Five readings were taken on each sample for higher accuracy and to develop a better understanding.wet—weight of the sample in wet state; Wdry—weight of the sample in dry state .Water uptake of the IPMC membranes  was carried out based on the equation below. Water uptake is defined as the ratio of the absorbed water to the mass of the sample in the dry state.The test is performed over the samples after soaking them for 1 h in a hot bath from 30 to 90 °C with a temperature interval of 15 °C.An SEM analysis was carried out for all the samples and the respective images are shown in 2O is observed due to the Ag coating. For N438 coated with Ag, the highest mass percentage of silver oxide is observed (91.87%). More cations are observed for N438 coated with Graphene and CNT, which shows more electrons than protons for a net positive charge. In contrast, for N438 coated with Ag, Aluminum was observed because of reactions with sulfur atoms [ur atoms . Table 2The scratch test was performed on all the samples at two different loads (2N and 3N). The water uptake of the N438, N438 + Ag, N438 + Ag + Graphene (0.01), N438 + Ag + Graphene (0.05), N438 + Ag + CNT (0.01), and N438 + Ag + CNT (0.05) samples is taken into consideration at different temperatures. The nanostructure of the composite membrane and the temperature play a crucial role in the water uptake of the composite membranes . The maiUnder the fixed free configuration of the membrane/sample, the tip force and tip deflection of the N438 + Ag, N438 + Ag + Graphene (0.01), N438 + Ag + Graphene (0.05), N438 + Ag + CNT (0.01) and N438 + Ag + CNT (0.05) samples are taken into consideration at room temperatures and four different input voltages.The highest scratch resistance and the lowest COF were observed in the N438 + Ag + Graphene (0.05) and N438 + Ag + CNT (0.05) membranes, which is because the fillers develop high bonding between the matrix and fiber.Graphene coating demonstrated the highest water uptake due to the presence of functional groups on its surface (hydrophilic), and because it stores water molecules effectively.Tip force and tip deflection were shown to be highest for Graphene (0.05), immediately followed by CNT (0.05) with a small difference, due to the presence of free electron mobility. This indicates that both composites can be used in the application of sensors and actuators.In the present work, TFRN membranes coated with Ag, Ag-CNT and Ag-Graphene at different ratios have been studied and the morphology of the membranes has been discussed. Additionally, their electro-mechanical behavior has also been analyzed. Based on the investigation of the membranes, the following conclusions were drawn and summarized:


Supercapacitors fabricated with the synthesized porous RGO (P-RGO) showed a high specific capacitance of 245 F g−1 at 0.1 A g−1, and a retention rate of about 96.9% after 12 000 cycle tests with respect to the initial specific capacitance with a scan rate of 10.0 A g−1. The production yield of this method was as high as 77.0%.In this paper, we introduce a combustion method which is rapid, low cost, mass-producing and environmentally friendly to produce nanoporous graphene. After loading a graphene oxide aerogel (GOA)/paper (GOP) on a preheated hot plate  under an ambient environment, in a few seconds, the GOA/GOP would self-combust and change into reduced graphene oxide (RGO) with nanopores mainly concentrated in the 0.4–2.0 nm range and a large specific surface area of 536 m The combustion process of GOA, and the specific surface area and pore size distribution of P-RGO are shown in the images. In addition, the self-aggregation would block the transmission of electrolyte ions, which would impede the progress of electrochemical process. To reduce the influence of the self-aggregation and fully take advantage of the intrinsic high SSA of graphene, researchers turn the attention to nanoporous graphene,14–17 which had porous structure, high SSA, and large enough pore volume (which benefits the transmission of electrolyte ions). During the past years, reactive ion etching methods18–20 have been used to make pores in the graphene sheets. These methods could produce porous graphene easily and were environment-friendly. However, the mass production of porous graphene is still a big challenge. Various methods based on the chemical etching21,22 and catalytic oxidation23–31 have been studied. With these methods nanopores as small as 0.6–5.0 nm were gained. However, it was not easy to remove the reagents introduced in the process of preparation. In addition, these ways were neither environment friendly, economical, nor mass-producing. Thermal expansion based methods,32–34 have also been used for mass production of nanoporous graphene. However, the methods needed high temperature, high vacuum, or special ambient condition.35,36 Also, these methods usually had lower production yield.However, in applications such as those involving supercapacitors, lithium ion batteries and so on, graphene sheets tend to self-aggregate irreversibly due to the strong π–π bonds and the van der Waals forces between graphene layers2 g−1 and the corresponding pore volume was 2.6 cm3 g−1. And the material was used to fabricate supercapacitor. The specific capacitance of the fabricated supercapacitor could reach as high as 245 F g−1 at 0.1 A g−1 specific current density. The retention rate of the supercapacitor was higher than 96.8% after 12 000 cycles with respect to the initial specific capacitance, which showed the electrochemical stability of the supercapacitor.In this paper, we introduce a combustion method which is rapid, low cost, mass-producing, environment friendly and no additional fuels were added in to produce nanoporous graphene from GO. The SSA of the obtained nanoporous graphene could reach as large as 536 m2.The whole process of producing P-RGO is described in the schematic diagram . In thisThe self-combustion process of GOA on the preheated hot plate (HT-300 °C) is shown in TEM images in MFA-140 was used to measure the specific surface area value by the Brunauer–Emmett–Teller (BET) method and the pore size distribution by the Barrett–Joyner–Halenda (BJH) method. The results are shown in As shown in −1 and 1410 cm−1 were hydroxyl groups (O–H), the peak at 1731 cm−1 was carbonyl groups  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O), the peak at 1625 could be ascribed to CC bonds, and the peaks at 1221 cm−1 and 1060 cm−1 were C–O bonds.35,37 As to the P-RGO samples (HT-300 °C and 200 °C), the peaks of O–H, C–O bonds were weakened, suggesting that GO had been reduced. Clearly, the O–H bond of 200-P-GO was nearly disappeared compared to that of 300-P-RGO, which could be explained by a stronger reduction under HT-200 °C treatment condition. From the spectroscopy of FTIR, it was known that the 300-P-RGO sample had a larger oxygen content compared to the 200-P-RGO sample, which might be explained by the fact that a larger SSA of 300-P-RGO sample would adsorb more O2/H2O onto the sheets and bond with the unstable and unsaturated atoms on the surface.The spectroscopy of FTIR has been studied to show whether the oxygenated functional groups were removed. As shown in −1/1335.68 cm−1, 1584.00 cm−1/1360.21 cm−1, and 1570.20 cm−1/1335.68 cm−1, respectively. D peak (1350.00 cm−1) was originated from a second-order process, relating to the structural defects or sp3 hybrid carbon atoms.38 The intensity ratio of D band to G band (ID/IG) of GO, 200-P-RGO, and 300-P-RGO samples are 0.969, 0.897, and 0.876 respectively. It suggested that the crystallization quality of the graphene became better through the combustion treatment. Under HT-200 °C condition, the explosion was more violent which produce more defects. This argument combined with the ID/IG data above explained that the 300-P-RGO sample had a better crystallization quality than the 200-P-RGO sample.C, C–O, and CO bonds.39 The spectrums of P-RGO (300 °C and 200 °C) have a more prominent peak of C–C/CC bond at 284.8 eV and relatively weaker peaks of C–O and CO bonds, suggesting the removal of most oxygenated groups of GO by the combustion treatment. The molar ratios of C atom to O atom were 2.03 (GO), 6.35 (300-P-RGO) and 8.35 (200-P-RGO) respectively. This result not only explained the reduction of GO but also provided further evidence that 200-P-RGO had a stronger reduction than 300-P-RGO. Due to the violent explosion at HT-200 °C, more pores with diameter larger than 2 nm were produced. Combined with the results of BJH measurements, the fact that 200-P-RGO had a smaller SSA than 300-P-RGO could be explained.The XPS were performed to analyse the degree of reduction of GO after the thermal treatment. O and epoxide groups) onto graphite sheets, but also generated lots of defects on the sheets. In the process of thermal treatment, when the GOA sample contacted the preheated hot plate, the position of the defect, oxygen-containing functional group and edge sites of GO sheets first got to the fire point because of the instability of the carbon atoms in these positions, and the sample started to burn with bright flame  thus creating defects in the form of etching holes within graphene basal plane, resulting in the reduction of GO. As shown in the FTIR spectra in O, –COOH, and the edge sites of GO is dominated by functional group –COOH. Abijit Ganguly et al.40 suggested, the activity of functional groups, from strong to weak, is: –COOH → CO → C–O → –OH with the increase of temperature. However, the order of the reactivity of the defect and the functional group is still unclear. Furthermore, these fast out-diffusion gasses brought about a large pressure stronger than the van der Waals forces between the carbon atom layers, which could exfoliate the physically densely stacked layers. At the same time, the gasses would strike around the defect sites, thus creating additional pores on the sheets. On the other hand, the high temperature produced by combustion also offer heat for the adjacent GO to burn until the whole aerogel burnout. Overall, the process of combustion not only got the GO reduced, but also generated nanopores on the sheets. Thus nanoporous graphene with relatively large SSA was obtained.The mechanism for producing P-RGO could be explained as follows. In the preparation process of GO, the intensive oxidation not only introduced a significant number of oxygenated functional groups /(ΔVm). At the scan rate 0.1 A g−1, 300-P-RGO based supercapacitor had an SC of 245 F g−1, and 200-P-RGO based supercapacitor had a SC of 229 F g−1. The SC data were shown in 42,43 indicating that the electrode of the supercapacitor prepared by P-RGO has less reversibility, and the shapes of charge curves suggest that the resistance of the electrodes is large and pseudocapacitive behavior may be exist. By comparison, the reversibility of the electrode prepared by 200-P-RGO is better than that prepared by 300-P-RGO, and in the case of no significant difference in specific capacitance between them, 200-P-RGO seems to be more advantageous in the supercapacitor application. Here, the obtained P-RGO was utilized in supercapacitors. And, the electrochemical characteristics of P-RGO based supercapacitors were investigated. As shown in CD graph  shows thAt last, it would be worth to mention the production yield of the P-RGO was more than 77.0% (through the whole process from the graphite powder to the P-RGO). Thus, this method might be applied to industrial production.3.3.1.49–51 from the natural graphite powder. Then, aqueous suspension of GO with concentration of 10 mg ml−1 was prepared.All the reagents used in the experiment were analytical grade. Graphene oxide (GO) was synthesized by a modified Hummers methodThe GO suspension was put into a sample box in the refrigerator, in which it was frozen. Then the sample was moved into the cold well of the freeze dryer which had been cooled down to −50 °C for drying. After several hours' freeze-drying, GOA was prepared, of which the color was brown. As to the GOP preparation, the suspension was uniformly coated onto the glass plates and dried at 55 °C in the constant temperature drying box. About 6 hours later, the dried GO layer was pealed from the glass plate, which looked like a paper and so is named GOP.3.2.Under the atmospheric environment, the obtained GOA/GOP was put onto the hot plate preheated to the temperature 300 °C (HT-300 °C). Immediately, a flame was observed from the contacting point between the GOA/GOP and the hot plate, and quickly spread to the whole GOA/GOP. After about 0.3 s, the flame disappeared, the black and fluffy P-RGO was obtained. The similar experiments at HT-200 °C, 400 °C, 500 °C were also carried out. It is noticed that violent explosion produced by the combustion could be observed when the experiment was carried out at HT-200 °C. However, nearly no explosion could be seen in the combustion at HT-300 °C, 400 °C, 500 °C.The obtained GO and P-RGO were characterized by field-emission scanning electron microscopy , field emission transmission electron microscopy , FT-IR spectroscopy (Nicolet 8700 FT-IR spectrometer), Raman microscopy (Horiba Jobin Yvon LabRAM HR-800), X-ray photoelectron spectroscopy (XPS) and MFA-140  method and the pore size distribution was calculated with the Barrett–Joyner–Halenda (BJH) method).3.3.2) was immersed into the slurry for absorbing P-RGO and afterword dried at 60 °C for about 24 h in the constant temperature drying oven. The P-RGO contained nickel foam served as an electrode of the supercapacitor. Each electrode contained about 4.5 mg active materials.Firstly, P-RGO, acetylene black and polyvinylidene fluoride (PVDF) with a mass ratio of 40 : 5 : 5 were mixed in the NMP, forming a slurry. Then, a nickel foam (1.0 × 0.5 cmvs. Ag/AgCl) with different scan rates  (for CV), and current densities  (for GCD). The equation for calculating the specific capacitance  was Cg = (It)/(ΔVm), where I (A) was the charge/discharge current, t (s) was the discharge time, ΔV was the potential range, and m (g) was the weight of the active materials contained in the electrode.A three-electrode system was used here for measuring the electrochemical properties: the P-RGO contained nickel foam (obtained at HT: 300 °C or 200 °C) worked as the working electrode, a platinum foil worked as the counter electrode, and an Ag/AgCl electrode worked as the reference electrode. The 6 M KOH aqueous solution was used as the electrolyte. CV and GCD tests were performed under the working potential ranging from −1.1 to 0 V .4.2 g−1. The P-RGO based supercapacitor exhibited a large specific capacitance 245 F g−1 at 0.1 A g−1 and a more than 96.8% retention rate after 12 000 cycles with respect to the initial specific capacitance at a scan rate 10 A g−1. Compared to other methods for producing porous graphene, our approach was more efficiency, rapid, environment friendly and low-cost, and could be implemented at relatively low HT-200 °C. Furthermore, this method had a high production yield of 77.0%, implying a possible industrial production. The P-RGO made by our method might have a significant potential in application to gas adsorption/storage, energy storage, dye adsorption and even could be used in compounding with other materials for getting new properties. This work shows the feasibility of the combustion method for producing nanoporous graphene, but the technique is not mature enough. There are still many problems need to be solved in producing the material in industrial production, also in applications.We presented a combustion method for producing nanoporous graphene from graphene oxide, and the application of the obtained material in supercapacitors. The obtained P-RGO samples had nanopores with diameter mainly ranging around 0.4–2.0 nm and SSA as large as 536 mThere are no conflicts to declare.RA-008-C7RA13568H-s001RA-008-C7RA13568H-s002RA-008-C7RA13568H-s003RA-008-C7RA13568H-s004