L1 and L2, containing a fluorescent pyrene unit, and their Zn(II) complexes are proposed as fluorescent probes for the detection of PFOA in aqueous media. Binding studies carried out by means of fluorescence and NMR titrations highlight that protonated forms of the receptors can interact with the carboxylate group of PFOA, thanks to salt bridge formation with the ammonium groups of the aliphatic chain. This interaction induces a decrease in the fluorescence emission of pyrene at neutral and slightly acidic pH values. Similarly, emission quenching has also been observed upon coordination of PFOA by the Zn(II) complexes of the receptors. These results evidence that simple polyamine-based molecular receptors can be employed for the optical recognition of harmful pollutant molecules, such as PFOA, in aqueous media.The globally widespread perfluorooctanoic acid (PFOA) is a concerning environmental contaminant, with a possible toxic long-term effects on the environment and human health The development of sensible, rapid, and low-cost detection systems is a current change in modern environmental chemistry. In this context, two triamine-based chemosensors,  Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are two chemicals composed of a fully fluorinated carbon chain and a hydrophilic polar end group . They arThe strongest evidence of PFOA and PFOS toxicity is related to endocrine disorders, in particular dyslipidaemia. However, animal and epidemiological studies regarding communities exposed to contaminated drinking water and the general population established a positive association between PFOA levels and kidney and testicular cancer along with a statistically significant association between PFAS exposure and suppressed immune response ,16.−1) 3+ and [H2L1]2+ in the case of L1 and [H3L2]3+ in the case of L2 . The latter displays a higher sensing ability for PFOA with respect to L1 and L2 (LOD 26.4 nM), but does not discriminate between PFOA and PFOS. From this point of view, the ability of L1 and L2 to selectively bind PFOA over PFOS is a peculiar characteristic of these receptors in the panorama of molecular hosts for these pollutants. As a preliminary investigation of the effects of interfering agents on the emission of the PFOA complexes with L1 and L2, we analyzed the fluorescence response of L1 and L2 in the presence of PFOA (100 equivs.) and an excess (200 equivs.) of a few model compounds, which, for their anionic nature, can be considered suitable candidates as interfering agents. We choose 1,3,5-nitrophenol, benzenesulphonic acid, 4-nitro-benzoic acid, and simple metansulphonic acid, which are in anionic form at neutral pH value, and may represent good candidates as organic interfering pollutants. Fluorescence measurements reported in L1 and L2 adducts with PFOA. No changes in the emission properties and sensing abilities of L1 and L2 for PFOA are also found when environmentally relevant cations  or anions  are present in solution in excess with respect to PFOA  processes from the ammonium groups of L1 or L2 to the pyrene unit, inducing fluorescence emission quenching. To evaluate the influence of temperature in PFOA binding to the two chemosensors, the fluorescence titrations of L1 and L2 in the presence of increasing amounts of PFOA at pH 4 were also repeated at 288 K and 308 K , likely due to the formation of an insoluble adduct between this analyte and the two receptors, preventing the determination of the stability constants of the adducts formed.Potentiometric measurements confirmed that no interaction occur between the two receptors with PFOS. In the case of PFOA, precipitation is observed at an acidic pH value (below pH 7) in the condition of the potentiometric titrations . We partially solved this drawback by performing 1H NMR titrations at pH 7 and 4 in D2O/CD3OD 40:60 (v/v) mixture. However, L2 suffers low solubility even in this medium at pH 4, and therefore, the system L2-PFOA was analyzed only at pH 7. In the case of L1, the addition of increasing amounts of PFOA, up to 20 equivs., to a solution of the receptor induces a progressive upfield shift both at pH 7 and 4 . The addition of more than 20 equivs. of PFOA does not significantly affect the spectra. The signals of the 1AL and 2AL methylene groups , in keeping with a stronger host-guest interaction at this pH. In an attempt to clarify the role of the pyrene unit in PFOA binding, we also performed 19F titrations by adding increasing amounts of L1 or L2 to 10−2 solutions of PFOA. Unfortunately, in these conditions, precipitation at pH 4 prevents spectral analysis, while the spectra recorded at pH 7  mixture, shows negligible shift for both the aliphatic methylene groups and the pyrene protons, confirming the suggestion derived for fluorescence emission analysis. Similarly, the addition of PFOS to a solution of L1 at pH 7 and to the solution of L2 at pH 4 and 7 did not induce any relevant shifting of the signals of the receptors.Interestingly, L1 and L2 form stable 1:1 complexes with Zn(II) that can be isolated as solids from H2O/EtOH 1:1 solutions. Potentiometric titrations have been also used to determine the binding constant of the receptors toward the Zn(II) cation. The measurements have been carried out in an H2O/EtOH 50:50 (v/v) mixture in the presence of 0.8 equivs. of metal ions, and the explored pH range was 2.5–9 for L2 and 2.5–8.5 for L1 . The binding constants of both receptors are reported in As expected, both L1 and L2 are able to form Zn(II) complexes in neutral or slightly alkaline pH conditions. The higher formation constant of L1 (log K = 8.69) with respect to that of L2 (log K = 7.88) is in agreement with the lower ability of the dipropylentriamine chain in first-row transition metal coordination than diethylentriamine + is also found in solution, as often observed for Zn(II) complexes in which the coordination sphere of the metal is not saturated by ligand donor atoms. Similar species most likely exists also for L1, yet complex precipitation prevents a confident determination of such species. We decided to compare the emission of the Zn(II) with L1 and L2 at pH 8. At higher pH values, in fact, precipitation could prevent a correct analysis of the emission phenomena. At pH 8, the Zn(II) complexes of L1 and L2 are the most abundant species present in solution, although in the case of L2 a not trascurable amount of the receptors is also present in solution in its metal-free form. As discussed above, both receptors are poorly emissive at pH 8 (TRIS buffer) in water/ethanol solution (50:50 v/v). As often observed for Zn(II) complexes with fluorescent polyamine ligands, Zn(II) binding to both L1 and L2 results in the formation of emissive 1:1 complexes. When increasing amounts of Zn(II) is added to a solution of L1 at pH 8, the fluorescence emission linearly increases up to a 1 metal-to-ligand molar ratio (R), achieving a constant value for R > 2  up to an R value of ca 1, suggests the formation of complexes with 1:1 stoichiometry.A similar behavior is also observed in the case of L2 , althoug2O/EtOH (v/v) solution containing L2 and ZnCl2.6H2O in 1:1 molar ratio in the presence of an excess of NaClO4 (10 equivs.). In the asymmetric unit of [ZnL2Cl](ClO4) (compound 6) one [ZnL2(Cl)]+ cation and one ClO4− anion are present. The Zn(II) metal ion is bound by the three nitrogen atoms of the polyamine, while a chloride ligand completes the tetracoordinated environment (see 3) or larger macrocyclic derivatives unable to provide further donor atoms. In the present case, steric hindrance from the large pyrene pendant is likely to subtend to the adopted coordination geometry.Slow evaporation of an Hment see . The cooment see , are com…O24 3.199(1) Å), yet collinear to the Cl-Zn bond (Cl1-Zn1-O24 177.43(3)°): this long electrostatic interaction virtually completes a trigonal bipyramidal environment. The presence of outer sphere donor-acceptor interactions has been observed in Zn(II) polyamine complexes and generally happens along the expected direction for the addition of a further inner sphere ligand. For instance, prototypical square planar Zn(II) porphyrin complexes, when they interact with a fifth out-of-sphere oxygen donor, do so axially . Mononuclear examples of tetracoordinated Zn(II) centres bound to three nitrogen donors further showing out of sphere Zn…O contacts, as in our case, are rare, yet the FOJTAZ 2+ fluorescence emission decreases up to a [PFOA]/[ZnL1]2+ molar ratio of 1, to achieve an almost constant value for a [PFOA]/[ZnL1]2+ molar ratio greater than 1,4 suggesting the formation of 1:1 stoichiometry complexes. The quenching effect is only partial and can be ascribed to the weakening of the Zn-N bond upon PFOA binding, which can partially restore the PET effect from the amine groups to the fluorescent unit.The presence of a coordinated Zn(II) cation, which features an unsaturated coordination sphere can be exploited in the coordination of PFOA, through the interaction of the anionic substrate  with the metal center. The binding features of the Zn(II) complexes of L2, although, in this case, the minimum of the fluorescence intensity is reached with a higher amount of PFOA (15 equivs.). Apparent constants of 3.2 and 3.4 log units for the addition of PFOA to the Zn(II) complexes with L1 and L2, respectively, were calculated by data treatment with the Hypspec program, with detection limits (LODs) values 6.2 (L1)and 11.2 µM (L2). Both complexes show a binding ability lower than that found for the metal-free receptors at pH 4 and 7. However, as already observed for the polyammonium receptors, addition of PFOS to solutions of L1 or L2 at these pH values does not change the pyrene emission, indicating that, differently from PFOA, PFOS is not bound by the Zn(II) complexes. This result is in agreement with the known lower affinity for transition metal cations of the sulphonate group with respect to the carboxylate one.A similar result was also obtained for the Zn(II) complex of 1H NMR spectra of the Zn(II) complexes with L1 or L2 show a remarkable line broadening in D2O/CD3OD (40:60 v/v) preventing their interpretation. The addition of PFOA or PFOS does not affect the fluxional character of the spectra. Therefore, 1H NMR experiments cannot be used to infer a hypothesis on the observed lower binding ability of the Zn(II) complexes with respect to the metal-free triamine at neutral or slightly acidic pH values. We also performed FT-IR spectra on the solid-state ternary complexes ZnL1(PFOA)Cl and ZnL2(PFOA)Cl obtained by slow evaporation of H2O/EtOH 50:50 (v/v) solutions containing L1 or L2, ZnCl2.6H2O (1 equiv.) and PFOA (1 equiv.). The spectra show a slight, but not negligible (15 and 20 cm−1 for ZnL1(PFOA)Cl and ZnL2(PFOA)Cl, respectively) shift toward lower energy for the C=O stretching band, suggesting an interaction of the carboxylate group to the metal. Interestingly enough, the C-F stretching bands do not show significant shifts in the complex with respect to ‘free’ PFOA, suggesting that the perfluoroalkyl chain is not involved in complex stabilization. On the other hand, the crystal structure of the [ZnL2Cl]+ shows that Zn(II) complexation induces receptor stiffening which can prevent the interaction between pyrene and the perfluoroalkylchain of PFOA. Although the conclusion on structure in solution derived from X-ray structure can be misleading, we can tentatively suppose the carboxylate group replaces the chloride anion in the coordination sphere of the metal observed in the solid state structure shown in Unfortunately, the L1) and 1-(1-Methylpyrenyl)-1,5,9-triazanonane (L2) were prepared in accordance with the methods described in the literature 2+, and [ZnL2]2+ fluorescence spectra at pH 4 and 7 in H2O/EtOH 50:50 (v/v) were made, and the standard deviation of the blank measurements was calculated. The fluorescence intensity I0/I at 375 nm  in the presence of increasing amount of PFOA was plotted as a concentration of PFOA and gave a straight line, whose slope (K) was calculated. The detection limit was calculated by using the equation:The detection limit was determined from the fluorescence titrations data based on a reported method . Six mea2.6H2O (1 equiv.) and PFOA (1 equiv.) to a solution of the ligand L1 or L2 in an H2O/EtOH 50:50 (v/v) mixture. The pH of the solution was adjusted at pH 8 by the addition of a small amount of a 0.1M solution of NaOH in an H2O/EtOH 50:50 (v/v) mixture. Solid complexes were isolated by slow evaporation of the resulting solution. The spectra were recorded with an IRAffinity-1S Shimadzu instrument.FT-IR measurements were performed on freshly prepared complexes obtained by adding ZnClL1(PFOA)Cl, C29H20ClF15N3O2Zn: C 42.05, H 2.43, N 5.07. Found: C 41.23, H 3.57, N 6.34. Anal calcd. for ZnL2(PFOA)Cl, C31H24ClF15N3O2Zn: C 43.48, H 2.82, N 4.91. Found: C 44.76, H 3.54, N 4.21.Anal calcd. for Zn2F using all data (SHELXL-2018/3) [23H25N3)Cl]ClO4 (M = 543.73 g/mol): triclinic, space group P-1 (no. 1), a = 8.7070(2) Å, b = 11.4358(2) Å, c = 12.7837(3) Å, α = 77.662(1)°, β = 93.3735(9)°, γ = 68.582(1)°, V = 1157.50(4) Å3, Z = 2, T = 100 K, μ(CuKα) = 3.903 mm−1, Dcalc = 1.560 mg/cm3, 33,464 reflections measured (3.539° ≤ Θ ≤ 72.429°), 4558 unique (Rint = 0.0448) which were used in all calculations. The final R indices [I > 2σ] are 0.0281/0.0803, R indices  are 0.0305/0.0834 and the GoF is 0.884. CCDC 2237493 contains the supplementary crystallographic data for this paper. These data can be obtained free of charge via http://www.ccdc.cam.ac.uk/conts/retrieving.html .Single crystal X-ray diffraction data of 6 were collected on a Bruker Apex-II diffractometer equipped with a CCD detector . Data were collected with the APEX2 software,  The crys-2018/3) . All the-2018/3)  and mole-2018/3) . CrystalL1 and L2, that, at neutral or slightly acidic pH values, form protonated species. Despite their simple structures and their straightforward synthetic accessibility, they can form complexes with PFOA featuring stability higher than those formed by most of the previously reported receptors and, at the same time, selectivity for PFOA over PFOS. The ability of triamine to form complexes with Zn(II), a metal ion known for its ability to change/expand its coordination sphere in order to bind exogenous species represents an ‘added value’ of these molecular receptors. In fact, this metal ion can be exploited as an anchoring point for the carboxylate group of PFOA, a structural characteristic that leads to the formation of stable complexes between the Zn(II) complexes with L1 and L2 and PFOA and selectivity for the latter over PFOS. The Zn(II) complexes with PFOA, however, are less stable than that formed by the protonated species of the receptors, likely due to the rigidity of molecular architecture of the Zn(II) complexes with the present receptors, well outlined by the crystal structure of the [ZnL2Cl]+ cation. As a result, binding of the carboxylate of PFOA to Zn(II) can force the perfluoroalkyl chain to stay far from the pyrene unit, preventing the formation of stabilizing hydrophobic interactions with this aromatic moiety.These results point out that the straightforward coupling of a polar hydrophilic section is able to interact via charge-charge and H-bonding with the negatively charged perfluoroalkyl carboxylate groups, with a large aromatic unit, which can give hydrophobic interactions with the perfluorinated aliphatic chain may result in molecular receptors able to form stable complexes with PFOA, with great selectivity for this analyte over PFOS, whose sulphonate group shows a poor tendency to give H-bonding. This is the case of the triamine receptors L1 and L2 in the polyamine chain and/or in the fluorogenic moiety used, in order to develop a library of fluorescent probes. From this point of view, the assembly of arrays of chemosensors may be exploited to optimize the selectivity of the recognition process.Pyrene can be exploited not only to bind PFOA in cooperation with the polyamine aliphatic chain (when protonated or bound to Zn(II)), but also to signal the binding event through changes in its emission properties. Indeed, the binding of PFOA induces fluorescence quenching, more marked in the case of the metal-free receptors. Although the limit for PFOA detection is not particularly exceptional, PFOA is selectively detected over PFOS by both receptors, a peculiar characteristic in the panorama of molecular optical sensors for these analytes. Furthermore, the performance of the chemosensors in PFOA detection can be, in perspective, enhanced by their incorporation in nanostructured materials, in which energy transfer cooperative effects may occur between closely placed fluorescent probes. At the same time, the simple synthetic procedure used can be exploited to develop different chemosensors, differing from The above considerations outline that coupling a polyamine chain with a nearby fluorescent hydrophobic moiety may represent a novel approach for the development of new optical PFOA chemosensors, simultaneously displaying high stability of the adducts, fluorescence response and particular selectivity properties. Altogether, these characteristics make fluorescent polyamine-based receptors a promising tool for the binding and detection of this environmental contaminant.


Our objective was to assess their Kp clinical isolates were selected. Minimum inhibitory concentrations (MICs) were determined by broth microdilution in triplicate. Time-kill analyses were used to test CZA and MVB alone (1 and 4x MIC) and in combination with colistin , fosfomycin , gentamicin , meropenem , and tigecycline  against 1x108 cFu/mL. 24 hour log-kill was calculated as log cFu/mL decrease from time 0.15 KPC-ompK36 WT, IS5, or GD. 27% and 73% were KPC-3 and KPC-2, respectively. 100% were susceptible to CZA and MVB. None were resistant to COL. 3 were non-susceptible to GEN, which were all IS5 (Table 1).5 isolates each had Figure 1). Mean log-kills did not vary for CZA + COL, GEN, or TGC against ompK36 mutants vs WT; however, log-kills were significantly lower for CZA + FOS  or MEM  against ompK36 mutants compared to WT. Synergy rates were reduced from 100% against WT to 80%, 60%, and 40% against mutant isolates for CZA + COL, MEM, and FOS, respectively .In combination with CZA 1x MIC, each of COL, GEN, and MEM were bactericidal against all isolates; mean ± standard error (SE) log kills were -7.39 ± 0.3, -6.58 ± 0.93, and -5.81 ± 0.21, respectively . Mean ± SE log kills were significantly greater against porin mutants compared to WT for MVB + COL , FOS , or TGC . Rates of synergy were also higher against porin mutants vs WT for MVB + FOS or COL .MVB 1x MIC in combination with COL, FOS, GEN, and TGC were bactericidal 67, 27, 80, and 47% of the time, with corresponding log kills of -3.96 ± 1.1, -1.56 ± 0.83, -5.05 ± 0.82, and -2.53 ± 0.28, respectively  and MVB (meropenem-vaborbactam) at 1X MIC, stratified by ompk36 status: wild-type (WT) versus mutant (MUT). Bactericidal is defined as -3 log kill from time 0 at 24 hours and indicated by the dotted horizontal line. COL = colistin; FOS = fosfomycin; GEN = gentamicin; MEM = meropenem; MIC = minimum inhibitory concentration; TGC = tigecycline.Figure 2Proportion of bactericidal, synergistic, and antagonistic outcomes for ompK36 wild-type  versus mutant  KPC-Kp isolates tested against CZA (ceftazidime-avibactam) or MVB (meropenem-vaborbactam) at 1X MIC as single agents and in combination with colistin (COL), gentamicin (GEN), tigecycline (TGC), meropenem (MEM), or fosfomycin (FOS). Bactericidal activity was defined as -3 log kill from time 0 at 24 hours; synergy and antagonism were defined as -2 or +2 log kill at 24 hours compared to most active single agent, respectively.Porin mutations negatively impact CZA synergy with other antibiotics compared to WT, though 24-hour log kills for COL, FOS, GEN, and MEM remained below the bactericidal threshold. Conversely, porin mutations potentiate synergy between MVB and COL, FOS, or TGC.Ryan K. Shields, PharmD, MS, Allergan: Advisor/Consultant|Cidara: Advisor/Consultant|Entasis: Advisor/Consultant|GSK: Advisor/Consultant|Melinta: Advisor/Consultant|Melinta: Grant/Research Support|Menarini: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Roche: Grant/Research Support|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Utility: Advisor/Consultant|Venatorx: Advisor/Consultant|Venatorx: Grant/Research Support


The efficient conductivity of graphene-polymer systems is expressed supposing graphene, tunneling and interphase components. The volume shares and inherent resistances of the mentioned components are used to define the efficient conductivity. Besides, the percolation start and the share of graphene and interphase pieces in the nets are formulated by simple equations. Also, the resistances of tunneling and interphase parts are correlated to graphene conductivity and their specifications. Suitable arrangements among experimented data and model’s estimates as well as the proper trends between efficient conductivity and model’s parameters validate the correctness of the novel model. The calculations disclose that the efficient conductivity improves by low percolation level, dense interphase, short tunnel, large tunneling pieces and poor polymer tunnel resistivity. Furthermore, only the tunneling resistance can govern the electron transportation between nanosheets and efficient conductivity, while the big amounts of graphene and interphase conductivity cannot play a role in the efficient conductivity. The early studies on polymer graphene nanocomposites have focused on the preparation of products with small percolation start to achieve a big conductivity by a slight filler amount13. Generally, the percolation start is linked to the aspect ratio of graphene as the ratio of diameter to thickness15. So, the dimensions, dispersion quality and aggregation/agglomeration of graphene nanosheets manage the percolation start and thus, the nanocomposite’s conductivity (denoted as conductivity here). In addition, some novel parameters attributed to nanoscale including tunneling effect and interphase area can control the percolation start and conductivity.Graphene has a high stiffness and good electrical conductivity causing the stiff and conductive nanocomposites19. In fact, electrons can be easily transported via tunnels between nanoparticles. Therefore, the conductivity does not require the physical joining of nanoparticles. Figure 25. Figure 29. The interphase pieces can also connect to the nets, since they cover the nanoparticles31. This attractive subject have been studied for rigidity of nanocomposites33. Nevertheless, the impress of interphase on the conductivity was improperly studied.The tunneling mechanism mainly governs the conductivity35. They have assumed the roles of many terms for CNT such as amount, conductivity, waviness and aspect ratio in the conductivity. Also, some limited studies have exposed the significances of tunneling effect and interphase on the conductivity of CNT products, but their complex analysis limits their application in practice38. The theoretic works on the conductivity of graphene samples are also imperfect. The former authors commonly correlated the percolation start to aspect ratio and estimated the conductivity by old models such as power-law41. However, the interphase pieces and tunneling largely affect the percolation start and conductivity of polymer graphene nanocomposites. Obviously, disregarding of these main terms in the nanocomposites cannot lead to proper prediction of their behavior. Therefore, development of new models for calculation of conductivity considering these terms are valuable.Some novel models were suggested for conductivity of CNT-based nanocomposites42, a model for conductivity of graphene systems was proposed by interphase depth, filler network, network efficiency and tunneling properties. In the present work, the efficient conductivity of graphene-filled products is expressed assuming the volume shares and resistances of graphene, tunneling and interphase parts. Also, the percolation start and the shares of graphene and interphase pieces in the nets are stated by simple equations. The percolation start and the dimensions of graphene, tunneling and interphase parts express the volume shares of these parts in the nets. Additionally, the resistance of interphase piece is correlated to filler conductivity and interphase deepness. The innovative model is justified by the tried data of some examples. In addition, the impresses of factors on the efficient conductivity are explained and discussed.In our previous work43 as:The actual resistance of polymer graphene nanocomposites was expressedThe polymer nanocomposites include the filler, tunneling and interphase pieces, which affect the efficient conductivity. Figure i” and “λ” are interphase deepness and tunneling length, correspondingly.The latter equation can consider the size, resistance and volume share of each component in nanocomposites as:Since only the shares of filler, tunneling and interphase pieces in the nets can affect the actual resistance, the latter equation is expressed as:The efficient conductivity can be suggested by inverse “All parameters should be determinate to calculate the efficient conductivity.15 by:The percolation start in polymer graphite nanocomposites was statedSince D >  > λ, this equation is simplified to:The latter equation can be developed assuming tunneling and interphase pieces as:So, the percolation start can be estimated by filler size, interphase deepness and tunneling length.44 is given by:The interphase pieces also promote the efficiency of nanofillers in nanocomposites. The total volume portion of interphase in polymer graphene nanocompositesSince the interphase pieces can add to filler nets, the actual volume share of nanofiller consists of both graphene and interphase shares as:45 can be calculated by:Also, the percentages of nanosheets contributing to the conductive netsSupposing the contribution of interphase pieces to the conductive nets by “}φp” Eq. , “f” is So, the volume share of networked graphene is calculated by:form Eq. , which sFurthermore, the volume share of interphase pieces in the nets is given by:When “f” Eq.  and “\do}φi” Eq.  are exchm” is top interphase deepness in graphene nanocomposites. “tm” is 40 nm in the present study. This equation recommends the interphase conductivity by interphase deepness and filler conductivity.Also, it can be suggested that the interfacial attachments manipulate the interphase conductivity in nanocomposites. The interphase deepness commonly represents the extent of interfacial attachments. Consequently, the interphase conductivity is related to interphase deepness as:Moreover, the inherent resistances of graphene and interphase parts can be expressed by:Equations  and 18)18) deterNow, the volume share and inherent resistance of tunneling pieces are defined.43.It was found that the graphene nanosheets are overlapped in nanocomposites and the tunneling conductivity occurs by overlapped nanosheets Fig. 43.The total volume share of tunnels around interphase part in nanocomposites can be given like Eq.  by:19\doBut, only the tunnels in the nets are operative on the efficient conductivity. So, the share of tunnels in the nets is assumed as:g) and the polymer tunnel resistivity (Rp) as:The tunneling pieces in nanocomposites contain polymer layer and graphene nanosheets. As a result, the tunneling resistance considers the inherent resistance of graphene nanosheets in tunneling zones (Rg” and “Rp” can be suggested43 by:2).“RAssuming Eqs. –23, the f”   (PET) (48 and styrene acrylonitrile (SAN)  are calculated as , ,  and  nm for PI, PS, PET and SAN nanocomposites, correspondingly. These levels demonstrate the formation of large interphase and big tunnels in the examples. So, it can be concluded that both interphase deepness and tunneling length control the percolation start and efficient conductivity. These calculations are applied in the novel model to guess the efficient conductivity.The novel model is used to calculate the efficient conductivity in several examples from published articles. Several graphene examples including polyimide (PI)  are obtained as 200, 240), ,  and 300, 1000)  for PI, PS, PET and SAN graphene examples, correspondingly. The highest “d” and the lowest “ρ” are shown in PS/graphene nanocomposite, which cause the minimum level of inherent resistance of tunnels , the estimates of the novel model are acceptable. By these signs, the novel model fittingly displays the variations of efficient conductivity at numerous ranges of “t”. The maximum efficient conductivity of 0.14 S/m is shown at f = 0.6 and Rt = 0.02 Ω, whereas the efficient conductivity decreases to 0 at f < 0.3 and Rt > 0.07 Ω. These outputs designate that the efficient conductivity improves by the high shares of nanosheets and interphase in the nets as well as poor resistance of tunneling pieces. Furthermore, it is understood that the poor share of networked structures and high tunneling resistance meaningfully worsen the efficient conductivity.Figure 58. The large nets provide the efficient transference of electrons, but the small nets weaken the electron moving. Thus, it is rational to get a better efficient conductivity by higher “f”. Moreover, the tunneling resistance oppositely governs the efficient conductivity, because its high level restricts the conductivity of tunneling pieces and the charge transpiration. It is also concluded that only the high resistance of tunneling pieces affects the efficient conductivity, because the negligible levels of graphene and interphase resistances cannot control the electron moving. In fact, great tunneling resistance weakens the charge flow, but graphene and interphase components cannot produce actual resistance in the system. Therefore, the tunneling resistance regulates the efficient conductivity, as proposed by the novel model.The size and compactness of nets expectedly manage the efficient conductivity, for the reason that the conductive nets containing nanosheets and interphase pieces control the extent of electron shifting in nanocompositesThe efficient conductivity was expressed by graphene, tunneling and interphase parts. Also, the volume shares of these components in the nets and their inherent resistances were defined by simple equations. The novel model reveals good predictability compared to tested conductivity of examples. Similarly, the parametric examinations properly justify the stimuli of all factors on the efficient conductivity. These indications approve the correctness of the novel model. The predictions reveal that high filler amount, low percolation level, thin and big nanosheets, dense interphase, short tunnels, wide tunneling area and low tunnel resistivity grow the efficient conductivity. However, graphene and interphase components cannot resist against the electron transportation, while the tunneling resistance governs the electron current. Accordingly, only tunneling resistance affects the efficient conductivity. Among the studied factors, the size of tunnels and tunnel resistivity mainly affect the efficient conductivity. The efficient conductivity can grow to 0.7 S/m at


Furthermore, an equivalent circuit model of the CPW used in the measurements was constructed and simulations were performed, which showed good agreement with the measured results. The results validated the transmission properties of the graphene and the contact impedance at the interface between electrodes and the graphene in CPW circuits, which are necessary parameters for designing antennas using graphene. In addition, by comparing the transmission loss of three types of graphene, the parameters for improving the transmission characteristics were clarified.Graphene has been investigated as a transparent conductive film for use in a variety of devices, and in recent years it has shown promise for use in millimeter-wave devices as 5G technology. In this study, we applied single-layer (SL), triple-layer (3L), and P-type doped 3L graphene to coplanar waveguide (CPW) transmission lines and obtained transmission characteristics (S In particular, transparent conductive materials are attracting attention because they can be installed in a variety of locations without compromising their appearance. For example, indium tin oxide4, indium zinc tin oxide5, and meshed Cu formed on a substrate6 are commonly used, however, these materials have drawbacks such as trade-offs between electrical resistance and optical transparency8. Since our previous report, we have been focusing on chemical vapor deposition (CVD) grown graphene10. In general, graphene has excellent optical transparency and can be transferred onto various shapes and types of substrates due to its robustness and flexibility. If graphene can be implemented as a transparent 5G antenna, it can be embedded in transparent objects that require high optical transparency, such as building windows, car windshields, and mobile phones. However, graphene has higher carrier mobility but lower carrier concentration than metals, resulting in higher electrical resistance. This poses a challenge for its application in millimeter-wave devices. Recently, graphene has been extensively studied as an alternative material to metals, and various studies have been conducted to achieve low resistance while maintaining transparency using methods such as multilayering12 and carrier doping14. There have been reports investigating the electrical properties of graphene itself and its application to millimeter-wave devices. Pan et al. fabricated the slot antennas using ink containing graphene and evaluated their radiation characteristics up to 18 GHz15. Sa'don et al. reported printed array antennas with graphene and their radiation characteristics and beamforming capability at 15 GHz16. Hong et al. compared the electromagnetic interference (EMI) shielding performance of graphene with different qualities by changing the CVD process parameters17. On the other hand, there are limited reports evaluating the characteristics of devices using various types of graphene with different electrical properties in the frequency bands used for 5G technology (24.5 to 27.5 GHz and 37.0 to 43.5 GHz). Zhang et al. have evaluated transmission properties up to 40 GHz by applying graphene to a coplanar waveguide (CPW) with different structures with single layer graphene18. Similarly, Moon et al. evaluated the transmission properties of graphene from 0.5–110 GHz with different number of layers19. Grande et al. evaluated microwave ring resonators with multilayering and SOCl2 doping up to 10 GHz20. While device applications of graphene in the terahertz band23 have attracted much attention, there is insufficient research targeting the millimeter-wave region for 5G applications, which we aim to cover in our study.In recent years, various conductive materials have been considered for applications of millimeter-wave device as fifth generation (5G) technology21) from 1 to 50 GHz. Three types of graphene were fabricated: single-layer (SL), three-layer (3L), and P-type carrier doped 3L graphene with TFSA (Bis (trifluoromethanesulfonyl) amide) as the dopant, and their S21 were measured. Furthermore, the electrical properties of graphene in the CPW were clarified by simulating the S21 using the constructed equivalent circuit model of the CPW and comparing it with the measured S21 of the CPW. The results clarified the behavior of three types of graphene in millimeter-wave devices such as its transmission characteristics and contact characteristics at the interfaces between graphene and electrodes, which are necessary parameter for designing antennas using graphene.In this report, we systematically evaluate the effects of graphene multilayering and carrier doping on transmission characteristics  is required to evaluate optical transmittance evaluation, three types of graphene (10 × 10 mm2) were transferred to a quartz substrate and evaluated optical properties before forming the device. Furthermore, carrier doping was performed on 3L graphene before device fabrication, and the optical transmittance of P-type doped 3L graphene was evaluated. Note that the optical transmittance of the quartz substrate was subtracted for reference to discuss the optical properties of graphene only. As shown in Fig. 24. Being able to improve electrical conductivity while maintaining optical transparency is a unique feature of graphene.The optical transmittances in the visible region of the SL, 3L, and P-type doped graphene are shown in Fig. -1 and 2D peaks at 2680–2700 cm-1, which are characteristic of graphene, were observed as shown in Fig. -1, which may be due to the defects induced during the transferring, stacking and fabricating the CPW processes. Significant damage was not observed with the optical microscope observation in Fig. 2D/IG) correlate with the stacking structure of a multilayer graphene. The obtained I2D/IG of the 3L graphene was 1.5, which is as high as that of SL graphene (I2D/IG = 1.5). As shown in Fig. 2D) from fitting the 2D peak with the Lawrence function indicates that 3L graphene (FWHM2D:35.2) is close to SL graphene (FWHM2D:35.1). These suggested 3L graphene had a turbostratic stacking structure, which is characteristic of multilayer graphene obtained from a layer-by-layer process using polycrystalline graphene grown on polycrystalline Cu foils25. In general, the G peak of graphene originates from the in-plane motion of carbon atoms and shifts toward higher energies with higher carrier density27. In Fig. -1, which supported P-type doping with TFSA.The Raman spectra of the three types of graphene are shown in Fig. 21 of graphene  with guaranteed measurement range from DC to 50 GHz, a probe station , and a vector network analyzer  as shown in Fig. 21 measurement, the CPW was connected to two ports of the vector network analyzer and input impedance of 50 Ω was extracted. After calibrating shorts, opens, loads, and throughs, the S21 was measured.CPWs were used to evaluate the Sene Fig. a. A CPW 30. The contact impedance between graphene and Au in the CPW transmission line was treated as a parallel circuit of contact resistance Rcontact and contact capacitance Ccontact. To prevent delamination of the Au electrodes in the probe measurement, the probe was contacted about 200 µm inside from both ends of the transmission line. For the frequency from 1 to 50 GHz, the areas between the probe contact position and the edge of the transmission line could act as an open stub, so the distance between the probe contacted area and the end of the transmission line was incorporated into the equivalent circuit as a transmission line with a characteristic impedance of 50 Ω  depending on the mobility, Fermi level, and Fermi velocity32. The characteristic exponential relaxation time of τ = 2 picoseconds corresponds to ω/2π = 5.0 × 1011 (500 GHz), which means that the resistor–capacitor (RC) network can be considered constant at least up to 500 GHz34. Furthermore, the skin effect of the conductor is also frequency dependent. The thickness of the skin effect from typical CVD graphene conductivity (1.0 × 106 S/m) is 2.3–16 μm35 from 1 to 50 GHz as calculated using the following equation,36. In parallel with Rgraphene, the parasitic capacitance generation between Au electrodes across graphene channel can also be accounted for, but it was not included in the equivalent circuit model because the electrode thickness (500 nm) is thin and the distance between electrodes across graphene channels (30 μm) in Fig. The graphene channel in the transmission line was expressed only in terms of frequency-independent impedance as Rcontact and Rgraphene of the equivalent circuit model  improved compared to that of SL graphene (1200 cm2/Vs). This suggests that graphene is less likely to be affected by carrier scattering effects from the quartz substrate due to multilayering37. The sheet resistance of graphene (Rsheet) was 758 Ω, 405 Ω, and 125 Ω for SL, 3L, and P-type doped 3L graphene, respectively. The carrier mobility (1090 cm2/Vs) of P-type doped 3L graphene decreased with TFSA doping, while the sheet resistance decreased with high carrier density (4.6 × 1013 cm-2). A comparison of the carrier mobility of SL graphene (4.6 × 1012 cm-2) and 3L graphene (6.8 × 1012 cm-2) shows that carrier doping is effective in lowering resistivity. Rgraphene in the transmission line was determined from Rsheet, taking into account the shape of the signal line of the CPW  and L is the width of the graphene channel in the transmission line  versus SL (42 Ω) and 3L graphene (78 Ω).To determine hod Fig. a. Such phod Fig. b are shoRcontact between graphene and Au electrode, the transfer length method (TLM) was utilized as shown in Fig. RTLM between Au and the graphene40. The value of Rcontact was determined from the contact width between graphene and Au electrode  that contributed to the contact between the Au electrode and graphene. St between the graphene and Au electrodes in the CPW circuit can be expressed asTo obtain W is the width of the CPW signal line (400 μm). P-type doped 3L graphene exhibited an increase in St with P-type doping (5.3 × 10–5 cm2) as shown in Table Rcontact value.Where Ccontact can be treated as a series circuit of the quantum capacitance of graphene (Cq) and the geometrical capacitance (Cg) between Au and graphene.Cq and Cg can be obtained as follows43,EF is the Fermi energy, 8 cm/s), ħ is the reduced Planck's constant, and St' is the effective contact area between graphene and Au in the AC circuit. ε is the dielectric constant, and d corresponds to the distance between the electrode and graphene. Here, in the DC circuit, the effective contact area between graphene and Au (St) can be obtained from the TLM measurement. However, St' in the high-frequency band is difficult to determine because the current distributions in the CPW differ from that in DC measurements due to the current crowding and its frequency dependence. Therefore, Ccontact was treated as a fitting parameter in the analysis of S21, in which the measured S21 is compared to the simulations.21. The simulations were performed using a 3D planar high-frequency electromagnetic software (Sonnet Lite 18.53), and after fitting Ccontact  resulting from the increase in carrier density . This is because the contact area between the Au electrode and graphene in our study . Thus, these results indicated that the large contact area between the Au and graphene enabled the Ccontact to be the dominant factor in the contact impedance.The Au and graphene contacts of the CPW used in this study ware represented by a parallel circuit of udy Fig. a is larg21 of the CPW using the graphene at 1 –50 GHz and comparing them with the constructed equivalent circuit model of the CPW. To our knowledge, our study is the first compare the S21 of various graphene materials with different electrical properties while maintaining transparency. From this comparison, we found that the graphene channel in the CPW can be expressed only in terms of resistance. In addition, multilayering and carrier doping are effective in reducing transmission loss of the graphene, and the contact impedance can be reduced by increasing the contact area between Au and graphene. These are important findings for the design of transparent 5G antenna devices using graphene.Our research clarified the transmission characteristics of graphene for the 5G frequency by experimentally measuring the SIt is evident that graphene will continue to be studied to lower resistivity, increase mobility, and enable processes for larger area, toward a variety of device applications. Our study is one step in that direction, and it has provided valuable insights not only for designing transparent 5G antennas with graphene but also for the design of other devices such as microwave ring resonators, absorber, photodetectors, and terahertz devices using the graphene.21 from 1 to 50 GHz. We also measured the optical and electrical characteristics of the three types of graphene, built equivalent circuit models, and calculated. The agreement between the simulated S21 and measured S21 supports the validity of the constructed equivalent circuit model, in addition, the contact impedance value and the transmission loss of graphene channel were clarified. The comparison of the S21 of the three types of graphene shows that carrier doping and multilayering of graphene are effective in reducing transmission loss while maintaining the transparency of graphene in the operated 5G frequency. The results provide design guidelines for the introduction of graphene as a transparent conductive material in 5G antennas to replace existing materials such as meshed Cu, metal nanowires, and ITO films. Increasing the contact area between Au and graphene was also found to be effective in reducing contact impedance. In designing 5G antennas, it is important to connect the device to the power feed with minimal losses, and our experimental results show that a large contact area between the graphene and electrode is an important consideration as it reduces contact losses.We have fabricated CPWs using three types of graphene and measured the SOur findings provide insights into the design of millimeter-wave devices using graphene and, furthermore, provide the basis for the application of graphene as a radiating element of transparent 5G antennas.Figure 2 (20 sccm) atmosphere for cleaning. Graphene was grown by low-pressure CVD on the Cu foil using H2 and CH4 gas. The CVD growth proceeded for 30 min under H2 (20 sccm) and CH4 (2 sccm) flows at 1000 °C. For transfer processes, PMMA  in an ethyl lactate solution (4 wt%) was spin-coated onto graphene as a supporting layer and cured at 180 °C for 1 min.To grow graphene as a uniform monolayer, Cu foil was selected as a catalyst substrate. Before graphene growth, the Cu foil was annealed at 1000 °C for 30 min in H2:30 sccm, power: 20 W, time: 60 s) was performed on the opposite side of the Cu foil from the side where the PMMA film was formed to remove the unwanted graphene. Then the PMMA coated SL graphene sheet was obtained by etching the Cu foil. To form SL graphene on a substrate, the PMMA-coated SL graphene sheet (size: 10 × 10 mm2) was transferred onto a quartz substrate , and the PMMA was removed by immersing it in an acetone for 12 h. The 3L graphene samples were obtained by a layer-by-layer process in which a PMMA-coated SL graphene sheet was repeatedly transferred to another graphene grown on a Cu foil sample. The rest of the process was the same as that for fabricating SL graphene: etching Cu, transferring to the quartz substrate, and removing PMMA to obtain the 3L graphene on the quartz sample.The PMMA was wiped off with acetone during spin-coating because it also spread around to the back side of Cu foil. In the CVD process, graphene grew on both sides of the Cu foil, causing subsequent Cu etching failure. Therefore, oxygen plasma treatment  to completely remove the resist and unwanted graphene residue . The second process is the formation of the graphene channel. Resist coating, UV exposure using a mask for channel formation, immersion in the developing solution, dipping in the Au etchant, followed by immersion in the developing solution again, and oxygen plasma treatment were performed as in the first process. Through these processes, various devices could be fabricated with graphene.Electrode patterning for each device formation was performed in two steps. The first process is to remove unwanted Au and graphene, and the second step is to remove Au on the graphene channel area. For the first process, a photo resist  was spin-coated onto the Au and cured at 90 °C for 1.5 min. After UV exposure, the samples were immersed in a developing solution ) to remove the resist from areas other than the electrode patterns. The samples were then immersed in Au etchant  for 40 s to form the electrode pattern. Finally, the resist on the electrode pattern was removed using a remover , followed by oxygen plasma treatment  in 1-butanol solution (50 mM) onto 3L graphene, allowing it to soak for 1 min at room temperature in air atmosphere, and then spin coating itSupplementary Figures.


Buckled graphene has potential applications in energy harvest, storage, conversion, and hydrogen storage. The investigation and quantification analysis of the random porosity in buckled graphene not only contributes to the performance reliability evaluation, but it also provides important references for artificial functionalization. This paper proposes a stochastic finite element model to quantify the randomly distributed porosities in pristine graphene. The Monte Carlo stochastic sampling process is combined with finite element computation to simulate the mechanical property of buckled graphene. Different boundary conditions are considered, and the corresponding results are compared. The impacts of random porosities on the buckling patterns are recorded and analyzed. Based on the large sampling space provided by the stochastic finite element model, the discrepancies caused by the number of random porosities are discussed. The possibility of strengthening effects in critical buckling stress is tracked in the large sampling space. The distinguishable interval ranges of probability density distribution for the relative variation of the critical buckling stress prove the promising potential of artificial control by the atomic vacancy amounts. In addition, the approximated Gaussian density distribution of critical buckling stress demonstrates the stochastic sampling efficiency by the Monte Carlo method and the artificial controllability of porous graphene. The results of this work provide new ideas for understanding the random porosities in buckled graphene and provide a basis for artificial functionalization through porosity controlling. Buckling is one of the most common phenomena in low-dimensional nanomaterials. Generally, buckling induces delamination , instabiThe causes of bucking in graphene vary . BendingFor the porosities or the local atomic vacancy defects in graphene, the conventional and analytical deterministic models have a shortcoming in the random distribution quantification and computational cost . As mentCompared with molecular dynamics, the finite element model of graphene has competitive merits in computational costs of buckling analysis, especially for the tremendous stochastic sampling procedures . MoreoveIn this paper, a stochastic finite element model is proposed for the efficient quantification and propagation of the random porosities in buckled graphene. The main contents include the graphene geometrical characterization, method description, and result discussion. The buckling patterns of porous graphene are provided and compared under different boundary conditions. Based on the huge sampling space provided by the stochastic finite element model, the discrepancies caused by the numbers of random porosities are discussed. The work provides an important reference for the exploration of buckled graphene in energy harvest, hydrogen storage, and artificial functionalization.The carbon atoms in graphene are combined with the solid covalent bonds to form the periodic honeycomb lattice, which results in extraordinary material and mechanical properties. In order to describe the special periodic microstructure, the beam element is used to simplify the carbon covalent bonds in the finite element model. The corresponding material and geometrical parameters are settled according to the specific values reported in the literature ,31.P), aN) is a deterministic value. The number of the vacancy defect atoms P and aN.In addition, the percentage of random porosities  is settled as in nditions , the in-In addition, the boundary condition (B3) in the third case is more complicated than that in B1 and B2. As presented in Furthermore, the implementation program and numerical computation are performed by the integration of Matlab (Version 2020a) and ANSYS (Version 14.5) commercial software. The corresponding parameter definition, parameter value assignment, and Monte Carlo stochastic sampling are completed under the Matlab programming environment. ANSYS parameter design language (APDL) is used to create the finite element model for porous graphene and perform mechanical computation for elastic buckling. The flowchart of the stochastic finite element model by the combination of Monte Carlo stochastic sampling with the finite element computation is shown in In The critical buckling stress is the key factor in controlling the elastic recycling process efficiently . The eigIn order to compare the impacts of boundary conditions, the buckling patterns of both the porous graphene and the pristine graphene under different boundary conditions are presented in Under the third and fourth boundary conditions, the effects of random porosities in the buckling patterns are more apparent than those under the above-mentioned two boundary conditions. In The buckling patterns provide the deformation shape of porous graphene under compressive loads. For the hydrogen storage and energy harvest by the porous graphene, besides the buckling patterns, the critical buckling stress is the key factor to operate and control the process. The critical buckling stress is the compressive load at which the structure suddenly buckles or loses stability. Therefore, the critical buckling stress calculation for porous graphene needs further exploration. On the other hand, the randomly distributed porosities inevitably exist in the graphene sheets and nanoribbons with the current research and manufacturing technologies. The discrepancies caused by the numbers of random porosities are also essential to be analyzed and discussed.In order to further analyze the effects of random porosities in buckled graphene, the randomly distributed porosities in graphene are propagated by the repeated Monte Carlo stochastic sampling procedure. Different percentages of random porosities and boundary conditions are performed in the stochastic finite element model. The percentages of random porosities propagated in graphene are 0.2, 0.5, 1, 3 and 5%, respectively, and they are represented by P1, P2, P3, P4, and P5.In general, the atomic vacancies lead to the reduction of critical buckling stress compared with that for the pristine graphene under all four boundary conditions, since the mean of the relative value is less than one as in x and y axes are dimensionless units. The x-axis is relevant to the percent of atomic vacancy defects; the y axis corresponds to the relative value between the results of porous graphene and pristine graphene. In Furthermore, the fluctuation levels of the critical buckling stress caused by the location randomness of atomic vacancy defects are also computed by comparison with the pristine graphene. In According to the computational results of the stochastic finite element model, the specific situations caused by the location distribution of atomic vacancies are also tracked. As presented in In order to more precisely analyze the random porosities in the buckled graphene, the probability density distribution of the bucking critical stress under different boundary conditions is computed and presented in The differences in the probability density distribution of the relative variation for critical buckling stress are also presented in In addition, the shapes of the probability density distribution in The buckling patterns and critical stress of porous graphene are sensitive to boundary conditions.The randomly distributed atomic vacancy defects in porous graphene destroy the regularity and symmetry of buckling patterns.The possibility of strengthening effects in critical buckling stress is tracked under the first, third, and fourth boundary conditions.The distinguishable interval ranges of probability density distribution for the relative variation of the critical buckling stress prove the promising potential of artificial control by the atomic vacancy amounts.It is a potentially feasible method to improve the hydrogen storage and release performance by the adaptation and change in the boundary condition of the porous graphene.The approximated Gaussian density distribution of critical buckling stress demonstrates the stochastic sampling efficiency by the Monte Carlo method and the artificial controllability of porous graphene.The results of this work provide new ideas for understanding the random porosities in buckled graphene and provide a basis for energy harvest, hydrogen storage, and artificial functionalization.This paper proposes an efficient numerical model for the random porosity quantification and propagation in pristine graphene. Based on the huge sampling space of the stochastic finite element model, the following points can be concluded:


Curcuma longa L. Modification of the graphene’s surface with these compounds also increased the thermal and chemical stability of PVC/graphene nanocomposites.A large amount of graphene-related research is its use as a filler for polymer composites, including thin nanocomposite films. However, its use is limited by the need for large-scale methods to obtain high–quality filler, as well as its poor dispersion in the polymer matrix. This work presents polymer thin-film composites based on poly(vinyl chloride) (PVC) and graphene, whose surfaces were modified by curcuminoids. TGA, UV–vis, Raman spectroscopy, XPS, TEM, and SEM methods have confirmed the effectiveness of the graphene modification due to π–π interactions. The dispersion of graphene in the PVC solution was investigated by the turbidimetric method. SEM, AFM, and Raman spectroscopy methods evaluated the thin-film composite’s structure. The research showed significant improvements in terms of graphene’s dispersion (in solutions and PVC composites) following the application of curcuminoids. The best results were obtained for materials modified with compounds obtained from the extraction of the rhizome of  Research concerning the application of graphene materials is carried out in many areas, such as medicine, chemistry, materials engineering, energetics, and electronics. A large area of graphene–related research regards its use as a filler for polymer nanocomposites ,2,3,4,5.g) [An interesting and still relatively unexplored group of polymer nanocomposites with graphene are poly(vinyl chloride)–based materials (PVC/GN). Analysis of the literature has shown that in these materials with relatively well-dispersed graphene, regardless of the method of preparation , result in an increase in tensile strength and modulus of elasticity ,14,15,16g) ,24, loweg) ,26. HoweThe agglomerative behavior of graphene is due to strong π–π interactions and van der Waals forces ,28,29,30The π–π interactions refer to non–covalent interactions  between the π bonds of aromatic rings. However, this is a misleading description, because the direct sandwich overlap is electrostatically repulsive. Instead, we are dealing with staggered stacking  or π–teeing (perpendicular T–shaped), which makes the described interactions electrostatically attractive. The displacement occurs due to the superposition of carbon atoms with partially negative charges over hydrogen atoms with partially positive charges. Similarly, T–type perpendicular overlap is electrostatically attractive because here, too, there is an overlap of different charges ,33,46.A promising method of graphene modification using π–π stacking is the modification of its surface with curcuminoids. The interaction between the aromatic rings of curcumin and the GN surface was used to obtain graphene by reducing graphene oxide, through ultrasonic exfoliation of graphite ,34,47. HCurcuma longa L. (CE) obtained by extraction of the powdered rhizome of the plant, which was presented in our earlier work [Therefore, the present work aimed to modify surface graphene with curcuminoids and to investigate the potential of this modification to improve graphene dispersion in poly(vinyl chloride)/graphene nanocomposites obtained by the solvent-casting method. In this work, we used a commercially available mixture of three types of curcumin (CU)  and an extract of ier work . In addiCurcuma longa L. extract, and GN–CU and GN–CE colloidal suspensions. The analysis showed that the maximum absorption for graphene was observed at 272 nm, corresponding to π–π* transitions of C=C bonds [Curcuma extract, the described transitions were observed at 233 nm and 422 nm, respectively. The shift of the absorption maximum (233 nm) toward the ultraviolet spectrum is due to the presence of the other CE components. A maximum wavelength of 233 nm is characteristic of ar–turmerone [Before the morphology studies were conducted, the UV-vis studies were performed, in order to determine if the GN was successfully modified with curcuminoids. =C bonds ,54. Two =C bonds . In the urmerone ,57. Two urmerone . In addiurmerone ,55,59.2 hybridization was expected. Unfortunately, it was impossible to match sp2 in any way, so an additional sp3 hybridization peak was used. This fact may be due to the partial defecting of the graphene used and its partial oxidation  [Next, X–ray photoelectron spectroscopy (XPS) was used to characterize graphene surfaces’ functionalization accurately. xidized) ,47,60.2 and C sp3 peaks at 0.8 eV, especially for the starting sample, agrees very well with literature data on peak distances of thin carbon films, which are, respectively, 0.7 eV for graphene oxide and reduced graphene oxide [2 peak around 284.5 eV is also characteristic of this type of material [The distance between the C spne oxide , 0.8 eV ne oxide ,63, and ne oxide ,65,66. Fmaterial  and genematerial ,61,67.2 [The rest of the smaller carbon peaks , Table 12 . Conside2 ,70,71. T2 ,72.Curcuma longa L was stable up to about 175 °C, and its degradation occurred between 175 °C and about 450 °C  can be seen in the SEM images B,C 83,8,883,84. −1), which indicates the residual compression stress in the material. The RBS parameter (Raman Band Separtion) is relatively high and equals 287 (GN–CE) to 293 (GN–CU), whereas non modified filler has a value of ~291. This confirms the different mechanisms of carbon structure modification by both curcuminoids.The following step was the evaluation of the structure of graphene materials using Raman spectroscopy, an effective method for studying carbon materials . Recorde−1 for GN to 1600 cm−1 for graphene modified with curcumin and Curcuma longa L. extract, further confirming the better foliation of the material after surface functionalization with curcuminoids. Bands typical for disordered carbons are not visible .In paper , it was As we pointed out in our earlier work , in nanoThe analysis shows that the destabilization and stratification of graphene dispersion occur due to re-agglomeration and sedimentation of the filler ,89. The The Turbiscan Stability Index (TSI) (a specific Turbiscan parameter) was determined to compare the destabilization kinetics of the prepared systems, in particular, the differences between the CU and CE effect. TSI is an efficient method of comparing several systems, where the higher its value is, the less stable the system is ,92. OtheThe structure of nanocomposite polymer thin films obtained by solvent casting was studied using Raman spectroscopy and atomic force microscopy. In addition, the morphologies of the obtained materials were also observed on a macro- and micrometer scale, using images from digital photography and SEM. As mentioned in the introduction, the problem with graphene aggregation occurs in materials containing about 0.5 wt.% filler or more, so the structure evaluation was carried out for materials with 1 wt.% GN.−1 to C–Cl in the trans configuration of the polymer [−1 to C–Cl stretching [−1 to C–C stretching [−1 to C–H symmetrical stretching in CH2 group [−1 to C–H asymmetrical stretching in CH2 group [−1. It was attributed to the C–O bonds of curcuminoids [−1 , being the lowest in GN–CE and the highest in GN–CU. This can be explained by the layer-stacking enhancement in the matrix’s presence. Thus, the best filler dispersion was observed in GN–CU. Contrarily, the D-bands have been shifted towards higher Rs . The D (first–order peak) moves towards lower frequencies in the case of tensile stress and towards higher ones in the presence of compressive stress, as observed in nanocomposites. Additionally, the ID to IG ratio decreases, especially in the case of the GN–CU, indicating better structural ordering. However, the sheer increase in the intensity of the PVC-derived band (2916 cm−1) in the materials after its functionalization may indicate better dispersion of these materials and deposition inside the polymer matrix [Regarding the Raman spectra of the nanocomposites , D– and  polymer , bands aretching ,94, a baretching , a band H2 group  and a baH2 group ,93. In auminoids . The stuAFM also investigated the surface structure of the obtained nanocomposites in contact with a surface . AFM allows for the direct evaluation of the dispersion of graphene in the PVC matrix and the determination of roughness ,96. FiguThe image of the surface topography of the nanocomposites shows some corrugation of the samples due to the evaporation of solvent during the formation of the polymer film . AFM PVCThe observations made earlier were confirmed by analyzing the homogeneity of the polymer films on a macroscopic scale. The presented digital images of nanocomposites containing 1 wt.% GN, GN–CU, and GN–CE The same observations were confirmed by SEM imaging on the surface of the PVC/1%GN cryogenic breakthrough /graphene nanocomposites. Materials containing 0.01, 0.1, 0.5, and 1 wt% GN were produced.Observations of the structure demonstrated the best improvement in the dispersion of graphene in materials modified by Thermal properties were determined by the thermogravimetric method and the Congo Red test, with which the thermal stability time was measured. The results obtained are summarized in Thermal degradation of PVC and PVC/GN nanocomposites takes place in two stages related to the decomposition of the polymer. The first step occurs at 200 °C to 375 °C, and is related to the dehydrochlorination of PVC and the formation of conjugated polyene structures. The second step in the range from 375 °C to 600 °C corresponds to thermal cracking of the carbonaceous, conjugated polyene sequences and the formation of residual chars ,23.Due to the presence of residual THF in PVC, the nanocomposite films’ thermal stability was evaluated based on the differential thermogravimetry (DTG) ,19. DTG The max. DTG II analysis  showed nA commonly used method for assessing the thermal stability of PVC materials is the Congo Red test. The results presented in At the same time, it should be emphasized that discrepancies in the results of thermal stability measured by two methods are not unusual, due to the conditions under which the tests were conducted. Thermal stability by the Congo Red method is determined at a constant temperature that is close to the upper temperature range of PVC processing. In the TGA method, the sample is heated under a nitrogen atmosphere at a specified heating rate, over a wide temperature range, usually up to about 900 °C.An improvement of the mechanical properties of PVC/GN nanocomposites depends on the homogeneous dispersion of graphene in the polymer matrix and the structure of the filler. The lack of defects on the GN surface results in its high integrity and good mechanical properties, which directly determines the improvement of the mechanical properties of nanocomposites ,99,100. 14 Ω, and significant change occurs when the GN concentration in the composites is 0.5% and 1%. The lowest resistivity, which equals 1.4 × 107 Ω, is characteristic of the PVC/1%GN sample, which makes it possible to conclude that it is an antistatic material [14 Ω) was shown by the sample PVC/1%GN–CE.material ,101. Nan5 Ωm. Such a large change in resistivity (for PVC was 1.7 × 1014 Ωm) indicates that the dispersion of the GN was sufficient to create conduction paths. The PVC/GN–CE composites, as in the case of surface resistivity, did not show large changes in volume resistivity as the filler content in the matrix increased.The volume resistivity of PVC/GN composites also decreases with the increase in graphene concentration in the matrix. The materials containing 1% of GN were characterized by the lowest resistivity, and equaled 9.8 × 10References ,101 presThe numerous applications of poly(vinyl chloride) are due to its resistance to solvents ,102,103.dS is swelling degree, %,ES is equilibrium swelling, upper asymptote, %,Mt is time in which the swelling occurs with a maximum rate, s,t is time of exposure to the swelling agent, s,p is comparison parameter, 1 s−1.It was found that all the obtained materials undergo limited swelling, while the dependence of swelling degree on the exposure time to the swelling agent has a shape of a sigmoid function. Therefore, Equation (1) was used to approximate the swelling curves ,22.(1)SR2 are summarized in The parameters of the equation and the coefficient of determination M) also increases, which further confirms the correlation between acetone resistance of the materials and filler surface modifications. In materials with unmodified GN, a decrease in tM values was observed with an increase in its content in the PVC matrix.PVC/GN nanocomposites were found to have a lower equilibrium swelling ratio compared to unmodified PVC; the lowest SE value observed for PVC/1%GN, i.e., 43.5%, shows an improvement of about 5% in terms of the chemical resistance on the polymer matrix. Materials obtained with the addition of extract-modified graphene were characterized by a lower value of SE compared to corresponding materials with unmodified graphene. This effect was attributed to the better dispersion of the filler in the polymer matrix, as evidenced by significantly lower SE values for materials with 0.5 and 1% GN–CE. They were 32.1 and 27.3%, respectively, which represents a reduction in the equilibrium degree of swelling relative to PVC of 14.1%, in the case of PVC/0.5%GN–CE, and of 20.9%, in PVC/1%GN–CE. In addition, it should be noted that the agglomeration of the filler in the polymer matrix can lead to lower resistance to solvents in the form of acetone, which was observed in PVC/0.5%GN, where the SE was 1.3% higher relative to PVC. As the GN–CE content of the nanocomposites increases, the time in which the swelling occurs with a maximum rate  solution using unmodified suspensive poly(vinyl chloride) Neralit 601 , with a K number of 59–61, a bulk density of 0.56–0.63 g cm−3, a specific density of 1.39 g cm−3, and 97% purity. As a solvent for PVC and an environment used for graphene modification, tetrahydrofuran (THF)  was used. Curcumin from Curcuma longa L. turmeric powder  and Curcuma longa L. rhizome extract (made in-house [Graphene–based nanopowder with a flake thickness of 1.6 nm (maximum of 3 atomic monolayers), a flake length of 10 µm, and a specific surface area of 400 ÷ 800 min-house ) was use3 solutions of CU and CE in THF with a concentration of 2.25 mg cm−3 were prepared by ultrasound  using a SONOPULS rod-shaped probe homogenizer from Bandelin. Graphene was then introduced into the solution, which was prepared so that the dispersion concentration was 1.5 mg cm−3. Next, GN was sonicated under the same conditions as curcuminoids for 2 h. It was then stirred with a magnetic stirrer for 15 h at 200 rpm. After this time, the material was centrifuged 4 times at 12,000 rpm for 4 min and washed after each step with methanol, in order to remove the undeposited modifier. After centrifugation, the graphene was dried at 45 °C for 65 h to evaporate residual solvents.In order to functionalize the graphene’s surface with curcuminoids in the first step, 100 cmIn the first step, poly(vinyl chloride) was dissolved in THF at 25 °C for about 48 h, yielding a solution of 3 wt%. Then, the dry graphene was added to the solution and dispersed using ultrasound  at 50 °C for 2 weeks, in order to remove the THF residue from the polymer films. All samples were coded to take into account the graphene content and the presence of CE, e.g., a sample containing GN at a concentration of 0.01 wt.% was coded as PVC/1%GN, whereas a sample containing the same graphene modified by −3 and dispersions of GN, GN–CU, and GN–CE with a concentration of 0.03 mg cm−3 were prepared. The study was conducted in the 210–800 nm range. The experimental results were normalized in the range 0–1 using the OriginLab software.Absorption studies were conducted using a UV-vis/NIR spectrometer (Perkin Elmer Lambda 1050+) in a quartz cuvette. For this purpose, solutions of CU, CE in methanol with a concentration of 0.008 mg cmX–ray photoelectron spectroscopy: a PHI 5000 VersaProbe  spectrometer was used to conduct XPS measurements under the following conditions: monochromatic Al Kα radiation (hν = 1486.6 eV), an X-ray source operating at 25 W, 15 kV, 100 µm spot, pass energy of 23.5 eV, energy step of 0.1 eV. Obtained XPS spectra were analyzed with CasaXPS software, using the set of the sensitivity factors native for the hardware. Shirley background and Gaussian–Lorentzian peak shape were used for deconvolution of all spectra.−1 in an open ceramic crucible, under a nitrogen atmosphere, at 30 to 700 °C for fillers and at 30 to 900 °C for nanocomposites. In addition, static thermal stability tests were determined for the nanocomposite materials using the Congo Red test. The test was carried out at 200 °C, measuring the thermal stability time, i.e., the time during which the sample shows no signs of degradation in the form of hydrogen chloride release and color change of the indicator paper.The thermal stability of the fillers and nanocomposites was assessed by the thermogravimetric method using a TG 209 F3 Tarsus apparatus (Netzsch). The heating rate was about 10 °C minRaman spectra were collected with a Raman DXR microscope  using two laser lines, 532 nm and 780 nm, where the shorter wavelength was used for polymer composites, and fillers were studied using the longer wavelength line. The specimens were measured with 50 repetitions of 50 s each (20 in successive control measurements). The aperture was 50 µm, the lenses were 10 and 50 mm, and the laser beam power was 0.1 mW for 780 nm and 1 mW for 532 nm. Each sample was measured at least dozens of times (from 80 to >300) at different locations, and the final signal was obtained as an average and statistically representative one. The morphology of the samples was studied using scanning electron microscopy (SEM), and a Zeiss Crossbeam 350 microscope; in the case of polymer nanocomposites, cryogenic breakthroughs with a sputtered gold layer were observed. As a second technique, a Zeiss Libra 120 Plus transmission electron microscope (TEM)  operating at 120 kV was used, where the aqueous suspension was placed on a copper grid coated with a formvar polymer layer. Finally, the sample was left in the air (under a fume hood) to dry.Stability testing of the obtained graphene dispersions in PVC solution was carried out by multiple light scattering using the Turbiscan Lab apparatus , where suspensions of GN, GN–CU and GN–CE in 3% PVC solution in THF were placed in glass cylindrical test tubes, with a working height of 54 mm. The samples were then placed in a Turbiscan Lab instrument and scanned with light at approximately 880 nm. Scanning was carried out every 1 h for 24 h at room temperature (23 °C). The Turbiscan Stability Index (TSI) was determined from the results.−1.Filler dispersion in the matrix was also determined using an atomic force microscope Nanosurf  in contact mode with the PPP–XYCONTR probe , where the radius of the aluminum-coated blade was 7 nm, while the line angle was 20 degrees. 2D and 3D images were taken within a 50 × 50 µm area. To determine the surface topography of the area, 500 lines were measured , and the number of measurement points per line was 5000. The scanning speed of the sample was 5 µm s−1.A study of tensile properties was carried out using an in-house-built tensile tester, with the parameters presented in our earlier work . The tesThe electrical properties of nanocomposites were determined by measuring system consisting of a 6517A electrometer and a 8009 measuring chamber . The surface and volume resistivity were measured. The tests were carried out on film samples with a diameter of 70 mm in air, at a temperature of 23 °C and humidity of 50%, and at a voltage of 10 V.dS) was determined (see Equation (2)), depending on the immersion time in the swelling agent. The changes in the samples’ diameters were set on the basis of photos using the NIS Elements 4.0 software. The frequency picture-taking depended on the exposure time to the swelling agent. The measurement temperature was 20 °C and the initial diameter of the samples h0 = 10 mm.h is sample diameter after time t (mm),h0 is initial sample diameter (mm).The resistance of the obtained materials to swelling in acetone was tested in accordance with the method proposed in our earlier study . The chaIn order to analyse the obtained results, Origin 8.6 Pro software with implemented statistical analysis modules was used. ANOVA with Tukey’s post–hoc test was used to compare the significance of the difference for the mean values of the obtained results. The normal distribution was confirmed by the Shapiro–Wilk test, and the homogeneity of variance by the Levene’s test. All analyses were performed assuming a significance level below 0.05.Curcuma longa L.Graphene is one of the most promising nanofillers of nanocomposites, improving their performance. However, its uniform distribution in the polymer matrix is challenging. Several studies refer the need to reduce the agglomeration of GN and its derivatives during nanocomposite fabrication, in order to achieve improved properties ,106,107.Observations of the modified materials’ morphology showed better CE dispersion on the graphene’s surface. Spectroscopic studies have shown that modification occurs via a π–π stacking mechanism. TGA analysis revealed a higher amount of deposited curcumin on GN flakes i.e., 11.4 wt.%, while for the extract it was 6.9 wt.%. In addition, it is worth noting that the modified materials have a high thermal stability of about 340 °C. The analysis of the stability of GN, GN–CU, and GN–CE dispersions, as well as observations of the polymer films structure obtained after solvent evaporation from the dispersions, showed a significant improvement in the homogeneity of the nanocomposites after modification by curcuminoids. At the same time, extract-modified graphene showed better dispersion improvement in PVC. That indicates that not only the amount of modifier deposited on the graphene surface, but also its size and dispersion important in improving PVC/GN homogeneity. The analysis of the properties of nanocomposites with GN-CE has shown a better thermal and chemical stability of these materials. On the other hand, based on the results of the Congo Red test, it was stated that the proposed nanocomposites will require thermal stabilization at the processing stage by traditional methods, which is a well-known phenomenon in the field of the PVC technology.Summarizing, the proposed naturally derived compounds in the form of CE can be an alternative to previously proposed modifications of graphene for use in PVC and other polymer composites. In addition, the high thermal stability of the proposed modification, as well as the relatively low cost and possibility of obtaining the modifier on a large scale, provide opportunities for the technological use of CE in the future production of graphene polymer nanocomposites, through traditional processing methods at high temperatures.