The binding energy, bond length, projected density of states and differential charge density of graphene–metal interfaces are investigated using a first-principles method in which a single layer graphene is adsorbed on the low-index metal surfaces such as the (111), (110) and (100) surfaces. The bond length results show the graphene sheet has a different degree of buckling after graphene is adsorbed on the (110) and (100) surfaces of metals. The projected density of states and the differential charge density results confirm the adsorption of graphene on the Ni(111), Co(111), Ni(110), Co(110) and Cu(110) surfaces is chemisorption due to the strong orbital coupling effect and the obvious charge accumulation between the carbon and metal atoms, while the adsorption of graphene on the Cu(111) surface is physical adsorption owing to the absence of the orbital coupling effect and the charge accumulation between the carbon and Cu atoms. Interestingly, the adsorption of graphene on the (100) surface of Ni, Co and Cu is all physical and chemical mixed adsorption because there are the strong orbital coupling effect and the apparent charge accumulation between the carbon and metal atoms in some parts of these surfaces while there are almost no orbital coupling effects and charge accumulation between the carbon and metal atoms in other parts. Unlike (111) and (110) surfaces, we find graphene is both physically and chemically adsorbed on the (100) surface of metals. These unique properties of graphene make it a hot research topic in the field of materials science, and endow graphene-based composites with better properties.9 Graphene–metal composites are an important part of the research on graphene-based composites, mainly including graphene-loaded metal nanoparticle composites and graphene–reinforced metal matrix composites. Graphene-loaded metal nanoparticle composites utilize graphene as the carrier to load metal nanoparticles in order to enhance the activity and dispersion of nanoparticles, which are applied in a broad range of fields such as catalysis,10–12 sensors,13,14 spectroscopy15,16 and so on. Graphene–reinforced metal matrix composites incorporate graphene sheets into the metal matrix, which can greatly enhance mechanical properties of metal materials without affecting or even improving the thermal and electrical properties of materials.17–19 Obviously, the interactions between graphene and metals will play a crucial role in the properties of graphene-based composites. Therefore, it is essential to study the interactions between graphene and different metal surfaces. There have been numerous experimental and theoretical studies on graphene contacted to metals such as Ni, Co, Ru, Rh, Pd, Ir, Pt and Cu.20–37 Experimental studies about the growth of graphene on metal close-packed surface such as Ni(111), Cu(111) and Ru(0001) rank first.38–41 Secondly, experimental studies about the growth of graphene on other low-index metal surfaces such as Ni(100), Rh(100) and Pt(110) have also been reported.42–44 However, theoretical studies on the interfaces between graphene and metals mainly focus on the metal close-packed surface such as Ni(111), Co(111), Cu(111) and so on.28–37 In 2018, Mafra et al. not only investigated different growth mechanisms of graphene on Ni(100), (110) and (111) surface by optical microscopy, Raman spectroscopy and optical transmission but also provided an atomistic model of the processes involved to support the experimental results by density functional theory calculations.43 Theoretical studies on the adsorption of graphene on the (110) and (100) surfaces of other metals except Ni are rarely reported.Graphene, a two-dimensional single atomic layer structure which is composed of spThe (111), (110) and (100) surfaces are the most basic and important low-index metal surfaces. In particular, the close-packed structure of the (111) surface of Ni, Co and Cu has been commonly used to make graphene–metal contacts owing to their structural resemblance. The difference is the adsorption of graphene on the (111) surface of Ni and Co is chemisorption while the adsorption of graphene on the Cu(111) surface is physical adsorption. However, the lack of hexagonal symmetry of (110) and (100) surfaces results in less theoretical studies on graphene–metal contacts. Therefore, in this work, in order to explore the adsorption mechanism of graphene on metal surfaces, taking Ni, Co and Cu as examples, the interfaces between graphene and low-index metal surfaces such as (111), (110) and (100) surfaces are investigated by using first-principles calculations at the level of density functional theory (DFT). The results obtained by the present study are not only expected to explain the adsorption mechanism of graphene on the metal surfaces, but also to provide help for the research of graphene-based composites and carbon nanomaterials.ab initio simulation package (VASP).44,45 The local density approximation (LDA)46 was used to describe the exchange correlation effect because of the better performance of LDA compared with the generalized gradient approximation (GGA) in predicting binding behaviour for interfaces between carbon nanostructures and metals.26,47 The projector-augmented wave (PAW) was used to describe the electron–ion interactions.48,49 Metal surface is constructed in a supercell as a finite number of layers of metal plus a region of vacuum repeated periodically in the direction perpendicular to the layers. The supercell used to model the graphene–metal interface is constructed from a slab consisting of six layers of metal atoms, with a graphene layer adsorbed from the top side of the slab and a vacuum region of 15 Å. Considering that the metal substrate is usually much thicker than the upper layer film and it is usually the film that trends to match the lattice constant (LC) of the metal substrate in experiment,50,51 the lattice constant of metal unit cells is fixed to construct the interface supercell. Therefore, taking the metal Ni as an example, the 4 × 4 graphene unit cell is adjusted to the 4 × 4 unit cell of Ni(111) surface as shown in  graphene unit cell is adjusted to the  unit cell of Ni(110) surface as shown in  graphene unit cell is adjusted to the 2 × 7 unit cell of Ni(100) surface as shown in  graphene unit cell is adjusted to the 2 × 5 unit cell of Cu(100) surface in order to build a better matching model as shown in 52 The electronic self-convergence criterion is set to 1.0 × 10−5 eV and the forces on all the atoms are converged to within 0.01 eV Å−1 with respect to ionic relaxation.Density function theory (DFT) calculations based on plane-wave basis sets of 500 eV cut-off energy were performed with the Vienna deq), the binding energy (Eb) for graphene adsorbed on the (111), (110) and (100) surfaces of metals and the maximum buckling on the graphene layer studied in this paper are listed in 28,43 but the overall trend is basically the same. We believe the difference in results may be due to the following reasons. Firstly, the supercells we constructed are larger than those in the literature28,53 when graphene is adsorbed on the (111) surface of metals. Besides, the adsorption configuration of graphene on the (111) surface of metals is different from that in the literature,28 but this configuration has been confirmed by experiments.34 The binding energy in the paper was calculated by underlying formulaEgraphene, Emetal surface and Egraphene–metal interface represent the total energy of the bare slab, the isolated graphene, and the adsorption system, respectively. According to the definition, a positive Eb indicates the adsorption system should be stable. Buckling is defined as the coordinate difference of carbon atoms along the z direction.The average equilibrium interfacial distance (deq) and the binding energy (Eb) show the adsorption types of graphene on the (111) surface of metals can be divided into chemisorption and physical adsorption according to the literature.27 To be more specific, when deq is less than 2.3 Å and Eb is greater than 0.1 eV per C, the adsorption of graphene on the (111) surface of metals is chemisorption, while deq is greater than 3 Å and Eb is less than 0.04 eV per C, the adsorption of graphene on the (111) surface of metals is physical adsorption. Combining the above criterion of adsorption type and our calculation results, it can be found the adsorption of graphene on the (111) surface of Ni and Co is chemisorption, while the adsorption of graphene on Cu(111) surface is physical adsorption. However, for graphene adsorbed on the (110) surface of metals, the average equilibrium interfacial distances are less than 2.3 Å, the binding energies of the graphene–Ni(110) interface and the graphene–Co(110) interface are greater than 0.1 eV per C while the binding energy of the graphene–Cu(110) interface is less than 0.04 eV per C. Unlike graphene adsorbed on the (111) surface of metals, the graphene sheet shows a certain degree of buckling. Therefore, the adsorption type of graphene on the (110) surface of metals needs to be further investigated. In terms of graphene adsorbed on the (100) surface of Ni and Co, the average equilibrium interfacial distances are less than 2.3 Å and the binding energies are 0.175 and 0.162 eV per C, respectively. Notably, when graphene is adsorbed on Cu(100) surface, the average equilibrium interfacial distance is more than 2.3 Å but less than 3 Å, and the binding energy is still less than 0.04 eV per C. However, the adsorption type of graphene on the (100) surface of metals also needs to be further investigated because the graphene sheet has a greater degree of buckling after graphene is adsorbed on the (100) surface. In conclusion, it is unreasonable to analyse the adsorption types of graphene on the (110) and (100) surfaces of metals by combining the binding energy and the average equilibrium interfacial distance due to no consideration for the buckling on the graphene sheet. In order to determine the adsorption types of graphene on different surfaces of Ni, Co and Cu more accurately, the bond lengths (r) between carbon and metal atoms at the interface can be used as a new criterion since the adsorption types of graphene on the (111) surface of Ni, Co and Cu can be determined. And the bond length (r) analysis will be discussed in the following paragraphs.In our calculations, all graphene-metal interface models can be confirmed to be stable according to the definition of the binding energy. All the initial configurations are shown in r) of carbon and metal atoms have changed to achieve the lowest energy state after graphene is adsorbed on metal surfaces. Local configurations are selected as the research object in order to better observe and compare the relative positions and the bond lengths (r) between carbon and metal atoms. It should be noted that local configurations are taken from the red line frame areas in r) between carbon and metal atoms induced by the adsorption of graphene on the (111) surface of Ni, Co and Cu are shown in r) between carbon and metal atoms at the interface are about 2.2 Å, indicating carbon atoms can form covalent bonds with metal atoms, that's to say, the adsorption of graphene on Ni, Co and Cu surfaces is chemisorption, while the bond lengths (r) between carbon and metal atoms are larger than 3 Å, indicating carbon atoms don't form covalent bonds with metal atoms, that's to say, the adsorption of graphene on Ni, Co and Cu surfaces is physical adsorption.The initial configurations were constructed by matching graphene to metal surfaces as shown in r) of carbon and metal atoms induced by the adsorption of graphene on the (110) surface of metals. The maximum and minimum bond lengths (r) between carbon and Ni atoms are 2.357 Å and 2.009 Å, respectively. And the maximum and minimum bond lengths (r) between carbon and Co atoms are 2.398 Å and 2.039 Å, respectively. According to the new criterion mentioned above, it is known that the adsorption of graphene on the (110) surface of Ni and Co is chemisorption. However, for the graphene–Cu(110) interface, the minimum bond length (r) between carbon and Cu atoms is 2.218 Å, which is very close to 2.2 Å, while the maximum bond length (r) between carbon and Cu atoms is 2.770 Å, which is slightly larger than 2.2 Å, but less than 3 Å. In general, the adsorption of graphene on Cu(110) surface is also chemisorption, but the interaction between carbon and Cu atoms is slightly weaker than that between carbon and Ni (or Co) atoms.Unlike graphene adsorbed on the (111) surface of Ni, Co and Cu, the graphene sheet shows a certain of buckling after graphene is adsorbed on the (110) surface of metals from the side views as shown in r) of carbon and metal atoms after optimization. The bond lengths (r) of majority carbon and Ni atoms are less than 2.2 Å, and the bond lengths (r) of minority carbon and Ni atoms are larger than 3 Å. Similarly, the bond lengths (r) of majority carbon and Co atoms are about 2.2 Å, and the bond lengths (r) of minority carbon and Co atoms are larger than 3 Å. According to the new criterion mentioned above, it can be concluded that the adsorption of graphene on the (100) surface of Ni and Co is physical and chemical mixed adsorption. Unlike the graphene–Ni(100) interface and the graphene–Co(100) interface, the bond lengths (r) of minority carbon and Cu atoms are about 2.2 Å, and the bond lengths of some carbon and Cu atoms are close to 3 Å while the bond lengths (r) of other carbon and Cu atoms are larger than 3 Å, which indicates the interactions between carbon and Cu atoms are slightly weaker than those between carbon and Ni (or Co) atoms. That's to say, the adsorption of graphene on the Cu(100) surface is the coexistence of physical adsorption and weak chemisorption. In other words, the adsorption of graphene on the (100) surface of Ni, Co and Cu is all physical and chemical mixed adsorption.An interesting phenomenon is that the graphene sheet shows a large of buckling after graphene is adsorbed on the (100) surface of Ni, Co and Cu from the side views as shown in r) and the relative positions between the carbon and metal atoms, but also have chemical changes, such as the coupling effect between atomic orbitals and charge accumulation between atoms. Therefore, in order to further verify adsorption types of graphene on the metal surfaces, we calculated the projected density of states (PDOS) and the differential charge density in the following paragraphs, respectively.According to the geometric analysis above, the adsorption types of graphene on the metal surfaces are initially determined. Chemisorption process will not only have structural changes, such as the bond lengths (84s2) and Co atom (3d74s2) have open d-shell with two and three unpaired electrons, respectively, while Cu atom (3d104s1) has fully filled d-orbital and half-filled s-orbital, which means Cu atom has only one unpaired electron. Therefore, the interactions between graphene and Ni (or Co) are stronger. Further investigation of the binding mechanism for graphene–metal interfaces was carried out by analysing the projected density of states (PDOS). Notably, as is known to all, the electronic states of graphene become obviously spin-polarized after it is adsorbed on the different surfaces of Ni and Co. Here, the present study only gives the PDOS of spin-up states in order to simplify the analysis. The different interactions between graphene and the metal surfaces mainly arise from the different properties of metals. Ni atom  surface as shown in z orbital and the Ni-dz2 orbital. Still, the electron occupied states of the Ni-dz2 orbital increase significantly above the Fermi energy. Similarly, in the case of the graphene–Co(111) interface, the same conclusions can be drawn according to the projected density of states results in z orbital and the Ni-dz2 orbital as shown in z orbital and the Ni-dz2 orbital form covalent bonds. Above the Fermi energy, the electron occupied states of the Ni-dz2 orbital increase obviously. In addition, for carbon and Ni atoms near the configuration centre, a few overlapping peaks between the C-pz orbital and the Ni-dx2−y2 orbital in the energy range from −3 to 0 eV, which indicates the formation of covalent bonds between the C-pz orbital and the Ni-dx2−y2 orbital. Above the Fermi energy, the electron occupied states of the Ni-dx2−y2 orbital also increase apparently. Similar to the graphene–Ni(110) interface, the same conclusions can also be drawn for the graphene–Co(110) interface according to the projected density of states results in z orbital and the Cu-s orbital in the energy range from −5 to −4.5 eV, −3 to −2.5 eV, −2 to −1.5 eV and −0.5 to 0 eV as shown in z orbital and the Cu-s orbital. Above the Fermi energy, the electron occupied states of the Cu-s orbital increase. Moreover, some overlapping peaks between the C-pz orbital and the Cu-dz2 orbital in the energy range from −5.5 to −3.5 eV and −3 to −1.5 eV as shown in z orbital and the Cu-dz2 orbital form covalent bonds but the amount of overlapping peaks is less than that between the C-pz orbital and the Ni-dz2 (or Co-dz2) orbital, illustrating the interaction between the C-pz orbital and the Cu-dz2 orbital is weaker. Above the Fermi energy, the electron occupied states of the Cu-dz2 orbital also increase remarkably. For carbon and Cu atoms near the configuration centre, a few overlapping peaks are found between the C-pz orbital and the Cu-dx2−y2 orbital as shown in z orbital and the Cu-dx2−y2 orbital form covalent bonds. What's more, the electron occupied states of the Cu-dx2−y2 orbital also increase obviously above the Fermi energy.There exists the strong orbital coupling effect between the carbon and metal atoms after graphene is adsorbed on the Ni(111), Co(111), Ni(110), Co(110) and Cu(110) surfaces, that is to say, the adsorption of graphene on these metal surfaces is chemisorption. In more detail, for the graphene–Ni(111) interface, many overlapping peaks between the C-pz orbital but the projected densities of states of the Cu-s and Cu-dz2 orbitals remain almost unchanged and there are no overlapping peaks found between the C-pz orbital and the Cu-s and Cu-dz2 orbitals as shown in z orbital does not form covalent bonds with the Cu-s and Cu-dz2 orbitals. Still, the electron occupied states of the Cu-s and Cu-dz2 orbitals remain almost unchanged.However, there is no orbital coupling effect between the carbon and Cu atoms after graphene is adsorbed on the Cu(111) surface. Thus, the adsorption of graphene on the Cu(111) surface is only physical adsorption. More specifically, there are slight changes in the PDOS of the C-pz orbital and the Ni-dz2 orbital in the energy range from −5.5 to −1.5 eV, and −0.5 to 0 eV as shown in z orbital and the Ni-dz2 orbital form covalent bonds. Still, the electron occupied states of the Ni-dz2 orbital above the Fermi energy increase obviously. However, for carbon and Ni atoms near the configuration edge, there are no overlapping peaks found between the C-pz orbital and the Ni-dz2 orbital below the Fermi energy as shown in z orbital and the Ni-dz2 orbital. Besides, the electron occupied states of the Ni-dz2 orbital above the Fermi energy also remain almost unchanged. Similarly, as far as the graphene–Co(100) interface is concerned, the same conclusions can be drawn according to z orbital and the Cu-s orbital in the energy range from −5.5 to −5 eV and −2 to −1.5 eV as shown in z orbital and the Cu-s orbital form covalent bonds. Above the Fermi energy, the electron occupied states of the Cu-s orbital increase. What's more, the overlapping peaks between the C-pz orbital and the Cu-dz2 orbital mainly concentrate in the energy range from −4 to −1 eV as shown in z orbital and the Cu-dz2 orbital. Still, the electron occupied states of the Cu-dz2 orbital increase apparently above the Fermi energy. It's worth noting that the amount of overlapping peaks between the C-pz orbital and the Cu-dz2 orbital is less than that of the central carbon atoms adsorbed on the Ni(100) and Co(100) surfaces, which indicates the interaction between the C-pz orbital and the Cu-dz2 orbital is weaker. However, for carbon and Cu atoms near the configuration edge, there are no overlapping peaks found between the C-pz orbital and the Cu-s and Cu-dz2 orbitals as shown in z orbital does not form covalent bonds with the Cu-s and Cu-dz2 orbitals. Besides, the electron occupied states of the Cu-s and Cu-dz2 orbitals remain almost unchanged.Interestingly, there exists the strong orbital coupling effect between the carbon and metal atoms in some parts of the model while there is no orbital coupling effect between the carbon and metal atoms in other parts of the model after graphene is adsorbed on the (100) surface of Ni, Co and Cu. Therefore, the adsorption of graphene on the (100) surface of Ni, Co and Cu is all physical and chemical mixed adsorption. When it comes to the graphene–Ni(100) interface, for carbon and Ni atoms near the configuration centre, there are lots of overlapping peaks found between the C-p−3 e Å−3 and the saturation levels are from −0.01 to 0.01 e Å−3 for −4 e Å−3 and the saturation levels are from −0.001 to 0.001 e Å−3 for The differential charge density has been calculated to further confirm the adsorption types of graphene on the metal surfaces. The differential charge density plots induced by the adsorption of graphene on (111), (110) and (100) surfaces of metals are shown in Notably, there are few reports about the differential charge densities after graphene is adsorbed on the (110) and (100) surfaces of metals. For the graphene–Ni(110) interface as shown in An interesting phenomenon is that the graphene sheet shows a large of buckling after graphene is adsorbed on the (100) surface of Ni, Co and Cu, which makes the interactions between the carbon and metal atoms have some differences. In terms of the graphene–Ni(100) interface as shown in We presented a first-principles investigation of the binding energy, the bond length, the projected density of states and the differential charge density of the graphene–metal interfaces. The interfaces between graphene and low-index metal surfaces such as (111), (110) and (100) surfaces are mainly discussed in this paper. We find that the graphene sheet has a different degree of buckling after graphene is adsorbed on the (110) and (100) surfaces of Ni, Co and Cu. The projected density of states and the differential charge density results confirm the adsorption of graphene on the Ni(111), Co(111), Ni(110), Co(110) and Cu(110) surfaces is chemisorption due to the strong orbital coupling effect and the obvious charge accumulation between the carbon and metal atoms, while the adsorption of graphene on the Cu(111) surface is physical adsorption owing to the absence of the orbital coupling effect and the charge accumulation between the carbon and Cu atoms. Interestingly, the adsorption of graphene on the (100) surface of Ni, Co and Cu is all physical and chemical mixed adsorption because there are the strong orbital coupling effect and the apparent charge accumulation between the carbon and metal atoms in some parts of these surfaces while there are almost no orbital coupling effect and charge accumulation between the carbon and metal atoms in the other parts. The results obtained by the present study are not only expected to explain the adsorption mechanism of graphene on the metal surfaces, but also to provide help for the research of graphene-based composites and carbon nanomaterials.There are no conflicts to declare.


To compare cardio-metabolic, perceptual and neuromuscular responses to an aerobic interval training (AIT) running session, with active (AR) vs. passive recovery (PR).−1·min−1, ⁓ 35 min in 10 km) completed the University of Montréal Track Test (UMTT) and 2 AIT sessions on track in random order, which consisted of 4 × 2 min at 100% of the maximum aerobic speed (MAS), with 2 min of AR at 80% of the velocity associated to the second ventilatory threshold (vVT2), or no exercise . During sessions, oxygen consumption (V̇O2), heart rate (HR), blood lactate [La], rating of perceived exertion (RPE), and countermovement jump (CMJ) were continuously monitored.Eleven well-trained male distance runners  between sessions , although the PR exhibited a greater time spent at peak V̇O2 close to significance . However, the AR elicited a higher mean V̇O2 . The AR favored a lower [La] after sessions  and a higher RPE during sessions . Meanwhile, the CMJ was significantly potentiated during both sessions.There were no differences in time spent in the “red zone” (i.e. > 90% V̇OConsidering that PR elicited lower perceptual loading for a similar cardiorespiratory response, its use would be preferable, at least, for this type of AIT running sessions. Based on the intensity of bouts, HIIT can be performed taxing more the anaerobic  or the aerobic  metabolism (Buchheit and Laursen lim) at the velocity associated to V̇O2max or maximum aerobic speed (MAS) for reaching V̇O2max in AIT running sessions. Thus, prescription of HIIT sessions includes the manipulation of intensity and duration of bouts and recovery intervals for designing appropriate training workloads when looking for specific metabolic and neuromuscular adaptations in the short and the long term  is a method that consists of performing repeated bouts  above the anaerobic threshold, interspersed with pauses, thus allowing the accumulation of more time at a targeted intensity during a single training session   and AR can improve some metabolic and hormonal parameters.Pause duration is determined by the duration of the bout and its intensity, to allow a proper recovery for successfully performing the subsequent work interval, and it is based on the work-to-rest ratio or the return of some physiological parameters  to a set value  for assessing lower limbs neuromuscular function in endurance runners of different levels  for a similar external training load .Therefore, the aim of this investigation was to compare the use of AR vs. PR during a typical AIT running session  performed on a 400-m outdoor track on metabolic , neuromuscular  and perceptual  responses in well-trained endurance runners. Based on previous literature  volunteered for participation. The main characteristics of the participants are shown in Table Our investigation was a cross-sectional study performed along 5 testing sessions separated by a minimum of 48 h see Fig. .Fig. 1ExThe first session was devoted to explain the study procedures and to instruct the participants about experimental conditions, which implied to avoid the ingestion of food, alcohol, caffeine and/or tobacco during the 3 h before evaluations, and not to perform any high-intensity effort during the 24 h prior to each session. Participants were also instructed not to modify their nutrition patterns during the study.The second session consisted of a familiarization with testing procedures. After a standardized warm-up, participants performed 5 continuous CMJs on a force plate  and were also instructed about the Borg’s 6–20 RPE scale.max) calculated according to Tanaka et al.  but with a cyclist setting the running pace  was also recorded.The MAS was considered as the speed attained in the final completed stage, and calculated more precisely according to Kuipers et al. . The tot2 and HR data were automatically filtered with a custom-made software and subsequently averaged to 15-s intervals. The V̇O2max and HRmax were considered as the highest V̇O2 and HR attained in 2 successive 15-s periods, respectively. To confirm a maximal effort, at least 2 of the following criteria were observed in all participants: a) a plateau of V̇O2 despite increasing the running speed (change in V̇O2 ≤ 150 mL·min−1); b) maximum respiratory exchange ratio ≥ 1.1; c) HRmax ≥ 95% age-predicted maximum HR; d) maximum [La] ≥ 8 mmol·L−1; and e) RPE ≥ 17  at 105% of MAS. This verification procedure has been previously described . Participants ran on a 400-m outdoor track following a cyclist who set the running pace, and were instructed to run 2–3 m behind the cyclist and to maintain an even pace for homogenizing drafting between experimental conditions  were carried out in the fourth and fifth sessions under thermo-neutral environmental conditions for all participants (i.e. < 24 °C and < 80% of relative air humidity). The participants performed a standardized warm-up at the beginning of each session. The sessions consisted of 4 bouts of 2 min at 100% of MAS, with a work-to-rest ratio of 1:1. In one session, the recovery period between bouts was passive , whereas in the other session, the rest interval was active  of 5 jumps were recorded for further analysis. Kvert was calculated as the quotient of the change in ground reaction force and displacement of the center of mass . Participants did not attain their V̇O2max nor their HRmax during the experimental sessions, thus peak V̇O2, mean V̇O2, peak HR and mean HR were recorded. The time-to-reach 90% of V̇O2max (TTR90% V̇O2max) and peak V̇O2 (TTRpeak V̇O2), and the accumulated time at or over 90% of V̇O2max (TT90% V̇O2max) and at peak V̇O2  was performed with session and bout as factors. When a significant session × bout interaction was detected, a post hoc t test was carried out with Bonferroni’s adjustment. If normality was rejected, a non-parametric ANOVA type test , whereas for significant pairwise contrasts are presented as Hedge’s g (G) and matched-pairs rank-biserial correlation (r) for parametric and non-parametric comparisons, respectively. The statistical power for the interaction of the 2 × 4 repeated measures ANOVA with a sample size of 11, a correlation among repeated measures of 0.7 and a medium effect size (f = 0.30) is 0.83. Additionally, we calculated the sensitivity of the repeated measures ANOVA to detect this interaction for an alpha level of 0.05, a power of 0.80, a total sample of 11 subjects, and a correlation between repeated measurements of 0.7, obtaining that the test was sensitive to detect a medium effect size (f = 0.29). Main analyses were carried out using the statistical package SPSS version 20.0 , while non-parametric ANOVA type analysis and rank-biserial correlation were performed using the nparLD R and rcompanion software package for R , respectively. The level of statistical significance was set at 0.05.Data are reported as mean ± SD and ranges. The normality assumption for each parameter was verified with the Shapiro–Wilk test. For comparisons between sessions, a paired 2 demands, both in absolute and relative (% V̇O2max) values, total covered distance, time spent in the “red zone”, and time-to-reach the “red zone” during bouts in AR and PR sessions. Higher mean V̇O2 values  and mean V̇O2 relative to V̇O2max  were recorded during the session with AR, whereas higher peak V̇O2 values relative to V̇O2max were obtained during the PR session . Oxygen kinetics during bouts and recovery intervals from the same runner during both sessions is shown in Fig. Table 2 and mean V̇O2 expressed as a percentage of V̇O2max throughout the bouts are represented in Fig. Absolute mean V̇Op = 0.001; G = 0.853, 95% CI ) and peak HR . A significant effect of bout , session  and session × bout interaction  were found for mean HR throughout bouts. Post hoc comparisons detected higher values in PR in comparison with AR for bout 2 , bout 3  and bout 4 . Similarly, mean HR during recovery intervals was significantly higher during AR when compared to the PR session .Recorded HR values during running bouts were significantly higher during AR when compared to PR for mean HR  and session , with no session × bout interaction, was found for [La] recorded 3 min after finishing the last bout during the sessions, with higher values for PR when compared to AR session .A significant effect of bout (p = 0.199), mean jump height (p = 0.729), peak power (p = 0.245), and kvert (p = 0.289). A main effect of bout was only detected for mean jump height  and peak power .Table p = 0.002; pη2 = 0.560) and session , with no session × bout interaction, was revealed with AR showing higher RPE values when compared to PR session .Finally, descriptive and ANOVA results regarding RPE are presented in Fig. 2, mean HR and peak HR levels during running bouts; (2) the peak V̇O2 relative to V̇O2max during bouts was higher with PR; (3) the mean V̇O2 and HR values during recovery intervals were lower with PR; 3) the peak lactate concentration was globally lower with AR; (4) the jump capacity was potentiated, independently from recovery modes; (5) the perceived effort was higher with AR; 6) total covered distance was greater with AR.To the best of our knowledge, this is the first study simultaneously analyzing cardiorespiratory, metabolic, neuromuscular, and perceptual responses during an AIT running session with AR vs. PR intervals. The main findings of the current study are: (1) as expected, the AR elicited higher mean V̇O2 values in the session with AR is not surprising and agrees with previous literature. However, it should be noted that most previous studies used shorter supramaximal bouts  and not all of them were performed with runners. This is an important consideration as the training session selected, in terms of intensity and volume, could be considered more appropriate for the level of the recreational runners of our study . In this regard, O’Brien et al. (2 (3200 ± 661 mL/min) and more time spent in the “red zone” (4.47 ± 3.55 min) during the session than 1-min bouts  or continuous running (2909 ± 584 mL/min) of equivalent external load. On the other hand, Seiler and Sjursen  when performing 12 self-paced bouts of 2 min interspersed with 2-min self-paced recovery intervals compared to 1-min bouts in a sample of well-trained runners. The higher mean V̇O2 values attained during bouts (ranging from 81 to 84% V̇O2max in both conditions) could be explained by the differences in volume and intensity of our protocol in comparison to that used by Seiler and Sjursen  were similar to those obtained in our study (ranging from 95 to 98% VO2max in both conditions).The finding of greater mean V̇On et al.  demonstr Sjursen  reported Sjursen   during the verification phase. In this sense, we found non-significant differences between experimental sessions regarding TT90% V̇O2max, TTpeak V̇O2, TTR90% V̇O2max and TTRpeak V̇O2. However, and although these variables were quite similar for both conditions, we found longer TTpeak V̇O2 in the PR session with confidence interval of the effect size not including null effect . This phenomenon could be explained by a more pronounced increase in V̇O2 rate for the PR condition due to a greater V̇O2 amplitude , resulting in a steeper V̇O2 slope . However, this increment in total running distance should be cautiously interpreted, since it was performed at low intensities . In this sense, one must consider that total external training load  will be greater for AR when compared to PR sessions. However, targeted training intensities during work intervals were identical for both conditions. Thus, from a practical point of view, the distance accumulated during AIT sessions with AR should be considered in the computed training volume. From the current results, it can be suggested the use of PR when targeting for accumulating a greater volume of high-intensity work intervals, whereas AR could be recommended for maximizing physiological stress during AIT running sessions of moderate volume. This suggestion is based on the lower mean HR and V̇O2 values recorded during the PR intervals when compared to the active ones. Meanwhile, the correspondence between V̇O2 and HR responses during running bouts does confirm the validity of HR as a simple and valid monitoring tool to verify the purported physiological adaptations during HIIT sessions.Taking together, this idea supports the previous recommendations of Hill and Rowell  of using2. These results are in accordance with previous studies which also demonstrated a better lactate clearance during AIT running sessions when active recovering at velocities close to the anaerobic threshold  initially and perceived as “very hard”  by the end of the workout  and other AIT running sessions with different schemes and work-to-rest ratios.For the first time, we have concurrently analyzed the cardio-metabolic, neuromuscular and perceptual response of AIT running sessions completed on a 400-m outdoor track at 100% of MAS but differing in recovery mode. The practical applications from the current results for coaches, sport scientist and athletes are different regarding training objectives. Recreational runners as those of our study could benefit from AR during AIT running sessions when looking for a higher physiological stress. In contrast, PR may elicit a lower physiological stress for a similar external training load and, therefore, could be preferable for high-volume AIT running sessions. However, it is still to be solved if the same picture would be evident with a longer session with more running bouts. Further, longitudinal studies are guaranteed to better understand the adaptations in the long-term to these recovery modes during AIT running sessions.


This study demonstrates a novel and scalable method to synthesize multilayer graphene using CO2 from ambient air at 1 g/kWh electricity, potentially allowing for multilayer graphene production by the ton. The approach creates opportunities to synthesize multilayer graphene particles with defined properties through a careful control of the synthesis parameters for tailored applications.Graphene produced by different methods can present varying physicochemical properties and quality, resulting in a wide range of applications. The implementation of a novel method to synthesize graphene requires characterizations to determine the relevant physicochemical and functional properties for its tailored application. We present a novel method for multilayer graphene synthesis using atmospheric carbon dioxide with characterization. Synthesis begins with carbon dioxide sequestered from air by monoethanolamine dissolution and released into an enclosed vessel. Magnesium is ignited in the presence of the concentrated carbon dioxide, resulting in the formation of graphene flakes. These flakes are separated and enhanced by washing with hydrochloric acid and exfoliation by ammonium sulfate, which is then cycled through a tumble blender and filtrated. Raman spectroscopic characterization, FTIR spectroscopic characterization, XPS spectroscopic characterization, SEM imaging, and TEM imaging indicated that the graphene has fifteen layers with some remnant oxygen-possessing and nitrogen-possessing functional groups. The multilayer graphene flake possessed particle sizes ranging from 2 µm to 80 µm in diameter. BET analysis measured the surface area of the multilayer graphene particles as 330 m The pro11 cm−2,  displays11 cm−2, ,6,7,8,9 /mK [2/g  and expe2/g [2/g ,13.The exact effect of these properties relates to the structural defects and functionalization of the graphene sheet ,13, whic2. This process differs from other CO2-based graphene synthesis methods in that the CO2 used in this process is directly sequestered from ambient air rather than originating from treated or purified CO2 stored in tanks. This allows for the design of continuous flow systems that enable the method to be scalable for commercial applications under optimum economy. Furthermore, the electrolytic recombination is done with graphene flakes in ethanol suspension compared to prior works, which exfoliate graphite rods using electrolysis. This method offers opportunities to recycle all of the generated chemical waste back into the process. This saves processing costs and allows for environmentally friendly method of production.In this work, we describe a novel multilayer graphene synthesis process using COVariations in the production method can result in graphene predisposed to different structural defects and functionalization, which make it paramount to examine the properties of the multilayer graphene produced by this novel method.2 solution; (2) heating an aqueous monoethanolamine solution; and (3) collecting the released CO2 containing magnesium element for graphene production. The multilayer graphene product was characterized via Raman spectroscopy, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), Brunauer–Emmett–Teller analysis (BET), and transmission electron microscopy (TEM). These analyses were used to study the number of layers present, the functionalization, and the surface area properties of the multilayer graphene product.The novel method for synthesizing multilayer graphene sheets from carbon dioxide involves the ignition of magnesium and carbon dioxide sequestered from air, followed by refinement in an aqueous suspension of exfoliated graphene . The priThe novelty of this method is that it was designed as a scalable process to be readily applied to an industrial setting with no environmental waste rather than a laboratory setting with small-scale yields. The inventor of this method chose magnesium metal as opposed to other reducing metals such as sodium because the equipment available is more readily designed for higher combustion heats and is generally more stable than sodium. The inventor of this method also chose MEA to sequester carbon as opposed to other options—zeolites, metal–organic frameworks, mesoporous silicas, hydrotalcites, or activated carbons—because monoethanolamine (MEA) is easier to integrate into continuous flow systems. MEA also has the advantage of being continuously recycled, meaning that it is not wasted in the process. All other waste streams in the process are salts that can be dried or refined back to their original constituents and recycled into the proposed method using similar continuous flow systems. It should be noted that the goal of this research is to prove the efficacy of already patented technology, and not to dispute against other methods with hypothetical alternative chemicals.(1)Sequester of carbon dioxide gas from ambient air:2 solution (30%) is heated to ~35 °C to release the adsorbed carbon dioxide, which is then stored in a collection tank.The sequester of carbon dioxide gas from ambient air comprises several steps, as shown in (2)Synthesis of multilayer graphene sheets from carbon dioxide gas:The synthesis of multilayer graphene sheets from carbon dioxide gas comprises several steps, as shown in Magnesium chloride, water, and graphene flakes are formed by washing the graphene flakes and magnesium oxide with aqueous hydrochloric acid solution, as shown in the following reaction.The graphene flakes are then exfoliated in an ammonium sulfate solution (0.1 M with pH 6.5–7) and tumbled in a blender for several hours. Finally, the sheets are washed and dried.(3)Analytical characterization of the multilayer graphene material:−1 and a 20 × 40 N microscopic objective. The laser power had a variable range of 200 mW and readings, which were taken at approximately 175 mW. The wave numbers measured were 300 cm−1 to 4000 cm−1. Only the range relative to characterizing graphene is presented. The ATR-IR spectra of the multilayer graphene were measured with a FTIR spectrometer  with a diamond ATR attachment allowing a spectral resolution of 2 cm−1 in the range of 4000–600 cm−1. X-ray photoelectron spectroscopy  was performed. Wide-energy range survey spectra (0–1350 eV) were acquired for qualitative and quantitative analysis . An assessment of the chemical bonding of the identified elements was accomplished by collecting core-level spectra over a narrow energy range . SEM  was performed. BET  analysis was performed. For the initial gas desorption, the samples were heated to 200 °C at a heating rate of 5 °C/min over a period of 360 min. The absorbing gas was nitrogen . The absorption and desorption curves were obtained from the unit and the samples were cooled with liquid nitrogen. The porosity of the sample was calculated using non-local density functional theory with slit pores for nitrogen gas on carbon. Scanning transmission electron microscope analysis  was performed with a field emission gun (FEG) operating at 100 kV to demonstrate the number of layers of graphene.Raman spectroscopy  was performed with a 532 nm laser with a resolution of 8 cm−1 denotes the D peak; the peak at ~1571 ± 2 cm−1 denotes the G peak; and the peak at ~2674 ± 3 cm−1 denotes the 2D peak. The D peak was not analyzed beyond recognizing that its presence indicated that structural disorders were present in the multilayer graphene [−1 and at ~2635 cm−1). The presence of this sub-peak indicates that the multilayer graphene has more than ten layers [graphene ,17. Bothgraphene ,19,20,21graphene ,19,20,21n layers ,17, but n layers ,17.G/I2D) was found to be 1.28. Previous work has modeled intensity ratio as a function of the number of graphene layers using an exponential equation; as the number of layers approaches infinity, the limit of this equation is 1.33 [From  is 1.33 . Due to −1 is assigned to CO2. The broad peak around 3630 cm−1 is attributed to -OH stretching [−1, respectively [−1 were associated with C–O in carboxyl or hydroxyl groups, -C-O-C, and C-O groups [In retching . The -C-ectively . Bands aO groups . These rXPS was conducted to further confirm the chemical composition of the graphene. As shown in In 2/g. Since the presence of the oxygen functional groups were shown in the FTIR spectrum, a comparison to the measured surface areas of reduced multilayer graphene oxides in other studies [In  studies ,28,29,30Commercial viability analysis of the synthesis process: The greatest limiting factor in the process is the electrical requirement per material input. At 400 ppm of carbon dioxide in ambient air, it is estimated that approximately 64 cubic meters of air would need to be processed per gram of carbon. At an Ecophene facility, with a production capability of 4.5 kg per month, the current electrical requirements from sequestered carbon dioxide in ambient air to multilayer graphene powder require about 1 kwh per gram of multilayer graphene. This data is for equipment having a maximum output of up to 10 kg per month; thus, with larger equipment and more sophisticated autonomous throughput systems, the electrical cost per gram is expected to decrease significantly. The method used reduced labor costs since a less-skilled workforce is required for operation and the potential for automation labor costs can almost be eliminated. Finally, the current production system has a relatively high material loss of ~3%. With more sophisticated systems, this material loss can be significantly reduced. The combination of these factors means that multilayer graphene can be reliably produced at about 20–25% cheaper than the market value of $70/g.Environmental Implications: The novelty of the method used demonstrates a practical method of converting atmospheric carbon dioxide, the primary greenhouse gas responsible for anthropogenic climate change, into useful raw material with various benefits. Although it may not be enough to remove all of the excess carbon dioxide responsible for anthropogenic climate change, it demonstrates that atmospheric carbon dioxide mitigation can be achieved in a cost-effective and environmentally beneficial way. With further investigation, the production cost could be further reduced with quality improvement of the material.2/g, and the pore distribution indicated ~51% of the pores between 0.8 nm and 5 nm in diameter. This work demonstrates a novel and scalable synthesis method to produce multilayer graphene from CO2 at 20–25% lower cost/gram with various physiochemical features that can be potentially tailored for a wide range of applications. Additionally, this synthesis method was developed to have a net-positive impact on the environment. The recovery of CO2 from ambient air reduces greenhouse gases in the atmosphere, and this reduction contributes to curtailing climate change. Furthermore, the chemical waste generated by the process can be recovered and recycled; this lends itself to the sustainability of the method.Eleven Raman spectra of the multilayer graphene sample obtained from different points were presented, and a view of the 2D peak from one of the spectra after baseline removal was shown. Analysis of the data indicated that the multilayer graphene sample composed of more than ten layers, structurally disordered and functionalized. The TEM image of the multilayer graphene indicated a thickness of 15–16 layers. The FTIR spectra showed the presence of C-O-C, -C=O, C-O, and OH functional groups in the sample; the XPS spectra confirmed the presence of these functional groups as well as nitrogen-containing groups (pyridine and pyrrolic-N). These were introduced during their synthesis. The absorption-desorption isotherm of the multilayer graphene indicated a measured surface area of ~330 mMultilayer graphene used in this manuscript is based on the patented technology. Alvarez, L. “Apparatus, System and Method for Conversion of Atmospheric Carbon Dioxide to Graphene”. United States Patent Number: US 11,192,790 B2, 7 December 2021.


The Coulomb excitations of charge density oscillation are calculated for a double-layer heterostructure. Specifically, we consider two-dimensional (2D) layers of silicene and graphene on a substrate. From the obtained surface response function, we calculated the plasmon dispersion relations, which demonstrate how the Coulomb interaction renormalizes the plasmon frequencies. Most importantly, we have conducted a thorough investigation of how the decay rates of the plasmons in these heterostructures are affected by the Coulomb coupling between different types of two-dimensional materials whose separations could be varied. A novel effect of nullification of the silicene band gap is noticed when graphene is introduced into the system. To utilize these effects for experimental and industrial purposes, graphical results for the different parameters are presented. A huge number of researchers from various disciplines have been showing their interest in new materials, silicene especially, after the development of its fabrication process in 2012 . Their rBoth silicene and graphene were studied in parallel. The former has a buckled crystal geometry, whereas the latter has a honeycomb planar geometry. Due to this, differences arise between them. Ab initio calculations showed that the bandgap of silicene is electrically tunable ,5,6, whiSeveral investigations have been carried out on both graphene and silicene with respect to transport phenomena ,14,15,16Recently, Dong et al.  studied The plasmon mode is tunable by the thickness of the substrate and the variation of material behavior. We first determine the surface response function of the structure, the same technique used recently by Gumbs et al. ,53, whicWe have organized the rest of our paper as follows. In In this section, we analyze the plasmonic behavior of the heterostructure consisting of graphene and silicene together for which we employ the low-energy form of the Hamiltonian near the K point in the Brillouin zone. One significant difference between the Hamiltonian of graphene and silicene is that a small band gap, K and We now briefly describe the case pertaining to silicene whose Hamiltonian in the continuum limit is given by:leys, vF≈×105 m/s silicene , kx and e system  for intr100 meV) . The lasgiven by :(2)H^σξ=This gives the low-energy eigenvalues as:The low-energy model Hamiltonian for monolayer graphene is similar to that in Equation  with thegiven by :(4)H^=ℏvq is the wave vector and e is the electron charge. The polarization function is an important quantity in calculations of the transport, collective charge motion and charge screening properties of the material. In the one-loop approximation, the polarization function for gapped graphene is given by [Considerable work has been completed on the dynamical properties involving the use of the dielectric function  systems ,58,59 un systems ,61, the  systems  and the given by :(6)Π0, which is reflected in their energy dispersions though the presence or absence of a band gap. The two layers could also have different or equal doping levels (Fermi energies). By employing the boundary condition of continuity of the electrostatic potential and the discontinuity of the electric field across the interface separating two media, we solved for the various coefficients appearing in the potential. Consequently, the result for the surface response function d is the thickness of the substrate. This substrate thickness is in the order of the wavelength of light considered, for a visible light it could be of the order of a few hundred nanometers. For a thick substrate, the thickness could go up to micrometer in size, and accordingly, the plasmonic mode is modified. The plasmon dispersion equation is obtained from the solutions of Here, ading to:g=1Dquation =Equation .We now turn to a critical issue in this paper, which concerns the rate of damping of the plasmon modes by the single-particle excitations. If this rate of damping for a plasmon mode with frequency Therefore, setting the function in Equation  equal toWith these formal results, we now evaluate the plasma spectra for a double layer heterostructure. The expression shows the dependence of In our numerical calculations, energy is scaled in units of Going next to the case when we have a structure with two graphene layers together separated by various distances, a set of plots  and optical (higher frequencies), or as in-phase and out-of-phase . The numWe should also mention that the frequency of the optical plasmon branch depends on the distance between the layers. One can easily verify this by analyzing how far the branch moves from the main diagonal To extract more information about the plasmonic behavior, in A special effect of overcoming the single-particle excitation region of silicene by the single-particle excitation region of graphene is observed, which causes the shortening of the plasmon branches that used to be there for the silicene–silicene structure. As soon as the plasmon branch reaches the particle-hole mode region, the plasmon mode decays by replacing one silicene layer with a graphene layer in the silicene–silicene structure. The effect, due to the band gap in silicene, is just nullified. In other words, the plasmon modes in the regime, where they used to have plasmon modes before, now do not have them, because the plasmon mode decays into the particle-hole mode of graphene. Furthermore, the result of adding a substrate between the silicene and graphene layer is illustrated in panel (b) of The results in equation , which iThese new effects on the plasmon branches in this type of structure were not reported previously. Results of this type help develop electronic and quantum computing devices where knowledge of the plasmonic behavior of materials and their damping nature is very essential.In summary, we have investigated the key properties of the plasmonic mode and damping for different combinations of graphene and silicene layers. The effect of the addition of substrate in between the two layers is further analyzed. This resulted in the development of a novel technique of tuning the plasmon excitation mode associated with the two dimensional systems. In our system, a complete new plasmon branch emerges from the bulk plasmon frequency, this would be very helpful in engineering modern computing devices.Another discovery we have from this study is the disappearance of the lower plasmon branch and the suppression of the silicene band gap effect. Along with the study of interesting features in the plasmon modes, we have also developed an approach for calculating the decay rates for the plasmons due to Landau damping by the particle-hole modes.The principal goal of our investigation and the main results of our work are concerned with the understanding of plasmonic nature and analyzing their Landau damping rates in a multi-layer structure. In contrast to Ref. , which iAdditionally, our results infer that the number of plasmon branches emerging from the origin can be varied by choosing the number of the 2D layer. In brief, we can say that our study gives an important idea about the plasmonic behavior of a graphene–silicene-based heterostructure, which would be very helpful in carrying out further studies of other types of heterostructure, including a variety of low dimensional materials.


Group I introns are mobile genetic elements encoding self-splicing ribozymes. Group I introns in nuclear genes are restricted to ribosomal DNA of eukaryotic microorganisms. For example, the myxomycetes, which represent a distinct protist phylum with a unique life strategy, are rich in nucleolar group I introns. We analyzed and compared 75 group I introns at position 516 in the small subunit ribosomal DNA from diverse and distantly related myxomycete taxa. A consensus secondary structure revealed a conserved group IC1 ribozyme core, but with a surprising RNA sequence complexity in the peripheral regions. Five S516 group I introns possess a twintron organization, where a His-Cys homing endonuclease gene insertion was interrupted by a small spliceosomal intron. Eleven S516 introns contained direct repeat arrays with varying lengths of the repeated motif, a varying copy number, and different structural organizations. Phylogenetic analyses of S516 introns and the corresponding host genes revealed a complex inheritance pattern, with both vertical and horizontal transfers. Finally, we reconstructed the evolutionary history of S516 nucleolar group I introns from insertion of mobile-type introns at unoccupied cognate sites, through homing endonuclease gene degradation and loss, and finally to the complete loss of introns. We conclude that myxomycete S516 introns represent a family of genetic elements with surprisingly dynamic structures despite a common function in RNA self-splicing. E. coli rRNA gene numbering system [Group I introns are self-splicing and mobile elements sporadically distributed within genomes of bacteria, bacteriophages, chloroplasts, mitochondria, eukaryotic viruses, and the nuclei of eukaryotes ,2. Nucleg system .Group I introns catalyze their own splicing due to the intron-encoded ribozyme. The splicing mechanism is well described and involves two succeeding transesterification reactions initiated by an attack of an exogenous guanosine (exoG) cofactor ,13. The Nuclear group I introns may also carry additional genes and sequences. Most common are homing endonuclease genes (HEGs), which are found in approximately 5–10% of known nuclear group I introns and code for site-specific endonucleases involved in intron mobility ,20,21,22Mucilago crustacea that contained 34 copies of the intron internal guide sequence [Several examples of direct repeat (DR) arrays within nuclear group I introns have been reported ,11,32,33Naegleria species and in Allovahlkamfia and harbored complex insertions in the P6 segment corresponding to HEGs and lariat-capping ribozymes [In a previous study, we reported self-splicing and structural organization of nuclear S516 group I introns  and haveibozymes ,38,39.In the original S516 intron study [Didymium alpinum isolate Fr-K12, were retrieved from the NCBI database . Spores were germinated and approximately 108 amoeba cells were harvested from DS/2 agar plates, total DNA extracted, and rDNA sequenced as described previously [All rDNA sequences included in this work, except that of ® 2022.0.1 . Multiple sequence alignments were generated using MAFFT version 7.450 [® software program.SSU rDNA sequences (with introns removed) were assembled and aligned in the software program Geneious primeon 7.450 ,41 with on 7.450 ,43, exclon 7.450 ,8,11 usiThe tree-building methods of neighbor joining (NJ), maximum likelihood (ML), maximum parsimony (MP), and minimal evolution (ME), interpreted in MEGA X , were usD. alpinum (Fr-K12) identified a 534-bp group I intron  at position S516 in the nuclear SSU rRNA gene. An RNA secondary structure diagram is presented in Tetrahymena intron [Ribosomal DNA sequence analysis of the myxomycete a intron ,46,47, wD. alpinum Fr-K12) was provided in this study. To assess structural variations among the S516 introns, 143 nucleotide positions in the ribozyme core region common to all 75 introns were strictly aligned according to secondary structure features  tree  is in geL. columbinum isolates cluster together in the SSU rDNA analysis to a well-defined clade (blue box), the corresponding introns are found scattered on the tree, e.g., the L. columbinum (HQ687198) and L. columbinum (HQ687197) introns are distantly related to the other L. columbinum introns. (ii) SSU rDNA analysis strongly support that M. aggregatum and M. cribrariodes are two closely related taxa from the same genus (green box), whereas intron analysis of the core region indicates that the S516 introns are distantly related. This is further supported by structural comparisons , but their corresponding S516 introns suggest a distant relationship. In summary, our phylogenetic analyses suggest that myxomycete S516 introns share a complex evolutionary history, with several clear examples of both vertical and horizontal transfers.Most introns, however, showed a relationship that is not consistent with stable vertical inheritance. To better resolve the evolutionary relationship between S516 introns, we analyzed a smaller dataset consisting of 14 selected taxa , and froparisons , where PL. pseudomaculatum (JQ031985)  (T. varia (KM494993/4/5)  lacking a HEG insertion  , 190 amiY842033) , and 210993/4/5) . Furthernsertion . Interesnsertion A. A nuclnsertion B.Porphyra  [Allovahlkampfia (amoeba-flagellate) [Naegleria (amoeba-flagellate) [Ppo I from the myxomycete Physarum polycephalum [A hallmark of nuclear homing endonucleases is a His-Cys box motif consisting of two zinc coordinating structures (Zn-I and Zn-II) and two catalytic amino acid residues. d algae) , Allovahgellate) , and Naegellate) , as wellcephalum ,52.Elaeomyxa, Comatricha, Colloderma, Lamproderma, Licea, and Trichia), and all except two (Licea and Trichia) classified to the myxomycete order Stemonitales  harbors the largest motif (ca. 220 nt), which is located in P2 and repeated twice. (ii) C. nigricapillitia (AY643824) harbors the smallest motif (only 4 nt) in P2 and is repeated four times. (iii) C. pseudoalpina (DQ903673) harbors DRs in two different extension regions (P1 and P5). While the P1-DR motif is large in size (ca. 110 nt) and repeated four times, the P5-DR is composed of an approximately 60-nt motif and repeated twice. (iv) L. columbinum (HQ687204) also harbors DRs in two extension regions, but in P2 and P9. Two DR motifs are located in P2 (ca. 20 nt and ca. 40 nt), in 5 and 3 copies, respectively, and the DR motif in P9 is 28 nt in size and repeated twice. (v) E. cerifera (JQ031967) harbors three different DR motifs in P6 of 11 nt, 10 nt, and ca. 80 nt in sizes, repeated 4, 6, and 2 times, respectively. (vi) One each of two closely related T. varia introns contains  or lacks  a HEG. Intriguingly, the shorter variant contains a DR, including a HEG remnant sequence, at the proposed HEG deletion site (L. parasitica (JX481297) harbors a complex array in P2. Specifically, the intron folds into a typical group IC1 intron structure (Some isolates showed unique and characteristic DR features : (i) L. ion site . (vii) Ftructure A, and thtructure B. Seven tructure C.D. alpinum Fr-K12 intron. Extension sequences such as HEGs or DR arrays are all located in peripheral segments that do not interfere with the catalytic ribozyme core. HEGs located as insertions into segment P2 in five taxa are interrupted by small spliceosomal introns. Moreover, DR arrays were found in 11 taxa at six peripheral segments, and the L. parasitica intron was found to harbor a highly structured DR motif in 25 copies. Intron evolution analyses indicate a complex inheritance pattern that apparently includes both vertical and horizontal transfers.We report analyses of structural organization and molecular evolution of nucleolar group I intron at position S516 in myxomycetes. All 75 introns belong to the group IC1 subtype and fold at the RNA level into a highly conserved catalytic core, exemplified by the Porphyra red algae [Allovahlkampfia and Naegleria amoeba-flagellates [Naegleria homing endonucleases have been studied in more detail and found to recognize a 19 bp partially symmetrical sequence at the intron-less allele close to the S516 insertion site and to generate a pentanucleotide 3′ overhang at the DNA cleavage site [All HEGs in myxomycete S516 introns encode His-Cys homing endonucleases with a characteristic set of conserved amino acid residues involved in zinc coordination and catalysis. This His-Cys box was found to be highly conserved among S516 HEGs, also outside the myxomycete phylum. These include the ed algae  and the gellates ,39, whicage site ,53. The age site ,29,30,31age site .C. nigricapillitia to 23-nt motif in 25 copies in L. parasitica. A common feature to most arrays was non-identical sequence repeat motifs, which argues against slippage-like mechanisms during replication [Fuligo septica L1949 [M. crustacea S1389 [L. parasitica DR array may suggest a selective structural feature at the RNA level, but no function has currently been assigned.Extension sequences containing DR arrays were noted in six peripheral segments, including P2. The arrays varied from small insertions (4-nt motif in 4 copies) in lication ,55 as a lication ,9,11,33.ca L1949  and M. cea S1389 . The higLamproderma, Echinostelium, and Trichia, but also from Naegleria [Allovhalkampfia [Porphyra [Naegleria martinezi [Bangia fuscopurpurea [Acanthamoeba sp. Isolate [D. alpinum, as well as 93% of the myxomycete S516 introns. HEG deletion was further supported in one of the Trichia S516 introns and suggests a link between deletion of HEG and generation of DR. (4) The complete intron became lost, probably due to homologous recombination with an intron-less allele resulting in SSU rDNA lacking an S516 intron, as noted in the approximately 80% of myxomycetes assessed.The S516 group IC1 intron in myxomycetes and other eukaryotic microorganisms constitute a phylogenetic distinct family with a common origin . While iaegleria , Allovhalkampfia , and PorPorphyra . (2) To artinezi , Bangia purpurea , and an  Isolate . (3) TheThe myxomycete protists represent a unique model system for studying the evolutionary history of self-splicing introns due to an exceptionally high content of nucleolar group I introns. We analyzed 75 group I introns at position 516 in the SSU rDNA of myxomycetes representing five distantly related taxonomic orders. The result reveals a conserved group IC1 ribozyme core, but highly variable peripheral RNA domains containing direct repeat arrays and homing endonuclease genes in 20% of the taxa. All HEGs were interrupted by small spliceosomal introns, which probably facilitate the expression of protein-coding genes embedded in nuclear rDNA. Phylogenetic analysis identified a complex inheritance pattern that can be explained by repeatedly intron gain and loss during the evolution. The current study expands our understanding of the structural organization of group IC1 introns and their evolution.


Conventional psychiatric services are not always acceptable to indigenous communities and people.To present successful models of interactions of psychiatrists with indigenous patients and communities based upon our work with five communities in Maine.We reviewed the strategies that worked for community interaction from our project for supporting indigenous communities to implement medication-assisted treatment and we reviewed the literature to see what other strategies are reported successful.Psychiatrists working in these communities may need to share more personal details than to what they are usually accustomed to be accepted. They may need to acknowledge local culture and spirituality and work with traditional knowledge holders to create collaborative healing approaches. As part of this, a narrative approach appeared to work best in which the psychiatrist worked within the stories and beliefs of the community which required taking the time in dialogue to learn those stories and beliefs. Specifically, we address the challenges of flying into northern, rural, and remote communities, of academic physicians consulting to tribal-based opiate treatment programs, of modifying usual counseling techniques such as motivational interviewing to an indigenous population, and of the changes made in practice styles when taking into account the critiques made by indigenous people about medicine in general and psychiatry in particular.We propose that participatory action-based approaches can improve service delivery to indigenous people. Indigenous cultures share a collectivist mindset in which the needs of the group supersede the needs of individuals, a reliance upon stories, and commitment to a biopsychosocial and spiritual approach.


The trans-activation response DNA-binding protein of 43kDa (TDP-43) is involved in the pathogenesis of multiple brain disorders. As scientists are unraveling TDP-43 function and its impact on various diseases, we have begun to subcategorize them into TDP-43 proteinopathies. Furthermore, glial cell dysfunction contributes to various disorders, and TDP-43 is involved with glial cells via multiple pathways (direct or indirect) that aggravate the pathophysiology of such disorders. We are only now discovering and understanding the vast and diverse roles TDP-43 plays on neuronal cells and its effects on gliosis and neurodegenerative pathologies. It has multiple roles: mRNA maturation and splicing, transporting and maintaining mRNA stability, a component of stress granules and ubiquitination of dysfunctional or misfolded proteins, transcription of microtubule “Futsch” protein, and a role in maintaining synapse integrity and possibly more as we continue to research and uncover the labyrinth of the neuronal network. TDP-43 could also have a detrimental impact on glial cell activation and pathophysiology in diseases where TDP-43 is associated with its pathogenesis. We will review the pathophysiology of various neurological disorders that are associated with the alteration of the TDP-43 levels along with glial cell activation. Further, multiple diseases have glial cell participation in the pathogenesis, and the role of TDP-43 has not yet been investigated. We, therefore, explore those disorders in the context of both TDP-43 and glial cells involvement. This step will enhance the understanding of neurodegeneration where further research could prompt curative modalities with the advancement of technology. There are two important brain-related structures that have contributed to different pathological processes discovered in the last decade. Initially, the trans-activation response DNA-binding protein of 43kDa (TDP-43) had been discovered in 1995 as a suppressor protein for HIV genes, it’s critical for the regulation of the viral gene expression . VariousThe physiological functions of TDP-43 are complicated. Extensive research has been conducted in the last few decades to understand the main physiological processes that aid in identifying future pathological disorders. TDP-43 contributes to RNA transcription, translation, messenger ribonucleic acid (mRNA) transport, splicing, and mRNA stabilization, as well as the processing of long non-coding RNA and microRNA . FurtherGlial cells are non-neuronal cells that do not participate in impulse transmission. These cells have important functions to maintain the environment safe and suitable for the neurons by providing protection, supportive mechanisms, regulation of microcirculation, synaptic plasticity and pruning, memory, and maintaining synaptic transmission through electrolytes and neurotransmitter regulations . They arOligodendrocytes are essential cells for myelination, and astrocytes play an important role in this process as well . AstrocyEpendymal cells are lining the ventricular system of the brain, as well as the spinal cord canal that transmits the cerebrospinal fluid (CSF) . Their fMechanism of TDP-43 neurodegenerationTDP-43 has been found as a major proponent of multiple pathways Figure  includinIn the initial pathway the of ubiquitin-proteasome system (UPS), misfolded proteins and/or dysfunctional proteins are ubiquitinated as a tag and sent to the proteasome to be degraded . If thisThe next major pathway in which the health of TDP-43 is imperative for the proper function is chaperone-mediated autophagy in lysosomes Figure  16]. Th. Th16]. In the third mechanism that requires TDP-43 health, the autosome-proteasome pathway proteins are degraded keeping normal function ,17. The Fourthly, the stress granule formation occurs following an external stimulus in the cytoplasm. Stress granule formation is important to cell survival following stressors in the environment ,19. The Lastly, there is growing evidence to understand TDP-43 roles in mitochondrial homeostasis and the defect causing cellular stress . MitochoAll the above pathways can be linked to TDP-43 dysfunction and the subsequent pathway being rendered dysfunctional causing subsequent protein aggregation and accumulation Figure . The proGliosis in TDP-43 proteinopathies2+ and phospholipid exchange [TDP-43 plays a major role in cellular signaling that activates an immune response leading to the mediation of neurological destruction and degeneration Figure  22]. It. It22]. exchange . Cardiolexchange . The traexchange . Lysophoexchange . In a stexchange ,25. TherGlial cells with increased inclusions of TDP-43 have been shown to increase the inflammatory response . MicroglAnother glial cell that is involved in gliosis of TDP-43 proteinopathy is oligodendrocytes Figure . They arDiseases associated with TDP-43 accumulation and toxicityAlzheimer’s Disease (AD) AD is the leading cause of dementia and the main histopathological features are amyloid-beta (Aβ) and tau protein neurofibrillary triangles that lead to a variety of cognitive and neuropsychiatric symptoms ,33. The Parkinson’s Disease (PD) PD is a neurodegenerative condition that is characterized by the loss of dopaminergic neurons in the substantia nigra and extending the basal ganglia . It is aLimbic Predominant Age-Related TDP-43 Encephalopathy (LATE) LATE is a TDP-43 proteinopathy of the limbic brain that mimics Alzheimer's-type amnesia dementia in persons over 80 years of age which is what distinguishes it from AD and FTLD . It has Huntington’s Disease (HD) HD is an autosomal dominant disorder caused by a trinucleotide, nucleobase coding triplet cytosine (C), adenine (A), guanine (G) (CAG), repeat mutation of the Huntingtin gene that is responsible for encoding the Huntingtin protein (HTT) and the eventual dysfunction of the subcortical motor circuits . The mutProgressive Supranuclear Palsy (PSP) PSP is a parkinsonism syndrome that has similar presentations to Parkinson's disease but cannot be diagnosed as such. PSP is characterized by the degeneration of the midbrain-diencephalic junction . StudiesCorticobasal Degeneration (CBD) CBD is a rare condition characterized by worsening movement, memory loss, speech, and swallowing . This coNeurofibromatosis Type 1 (NF1) NF1 is a neurocutaneous congenital syndrome affecting organs of embryological ectoderm origin that includes the skin, eyes, and central nervous system . This maLewy Body Dementia (LBD) LBD is dementia that has histopathology of alpha-synuclein clumps called Lewy bodies (LB) . It is sEpilepsy and Other Pediatric Epilepsy Syndromes These are chronic neurological disorders that are defined as multiple unprovoked seizures. There is a wide variety of possible causes of epilepsy including genetic, structural, metabolic, immune, and infections. There has been a recent focus on genetic manifestations, possible links between TDP-43 and glial cell activation, and their role in the metabolism of neurotransmitters . In a reTrigeminal Neuralgia (TN) TN is a disorder of the trigeminal cranial nerve (CN V) that is characterized by intense, sharp, pain in an area of the face when one or more of the three branches, the ophthalmic, maxillary, and mandibular, are affected . In caseFragile X Fragile X is an X-linked dominant disease-causing mutation in the Fragile X mental retardation protein (FMRP) leading to neurological developmental delay, autistic-like behaviors, and focal seizures . Recent Attention Deficit Hyperactivity Disorder (ADHD) ADHDis a neurological dysfunction disorder in which individuals exhibit inattention, hyperactivity, and impulsivity . In a reSchizophrenia This is a highly heritable psychiatric disorder that features symptoms of psychosis (positive symptoms), blunting of normal affect (negative symptoms) and cognitive impairment . The etiDiseases associated with TDP-43 depletion and/or loss of functionAmyotrophic Lateral Sclerosis (ALS) ALS is a fatal neurodegenerative disorder. Oftentimes when referencing ALS, FTLD is additionally mentioned due to the discovery of genetics and TDP-43 linkage in 2006 . TDP-43 A mutation in TDP-43 leads to ALS and firmly establishes the causal role of TDP-43 for neurodegeneration . In bothFrontotemporal Lobe Dementia (FTLD)FTLD is a neurodegenerative disease in which patients typically present with behavioral and personality changes subsequently followed by memory loss. This neurodegenerative disease has been linked to TDP-43 functionality and lack thereof . In an eTherefore, in FTLD it is found that a low expression of TDP-43 affects the lysosomal function. Aggregation of TDP-43 in the cytoplasm causes an increase in work in the autophagosome-lysosome fusion . The lysAutism Spectrum Disorder (ASD) ASD is a neurodevelopmental disorder with a spectrum of characteristics. The disorder ranges from behavioral and communicative deficits. In a preliminary study, TDP-43 levels were observed in children with and without autism . Low levKrabbe’s Disease (KD) KD is a rare fatal neurodegenerative disease that due to the lack of galactosylceramidase there is extensive destruction to the myelin sheath surrounding the nerves in the brain . The mitNiemann-Pick (NPC) DiseaseNPC is a rare lysosomal storage disorder that specifically affects the body’s ability to metabolize fat within cells . Over tiTuberous Sclerosis Complex (TSC) TSC is a genetic disorder characterized by tumors or hamartoma formation in multiple organs . When thDiseases associated with no changes in the level of TDP-43There is an increasing amount of research and evidence supporting the significance of TDP-43 and its role in neuronal cells. It is important to outline the normal function of TDP-43 and how it contributes to neurological homeostasis and neuronal remodeling, or gliosis. In these diseases, there is a lack of evidence of TDP-43 involvement in the pathogenesis or progression of the illness. Even though data has not shown a change in levels or an association in toxicity of TDP-43, it is not implausible to believe that TDP-43 contributes to the activation of glial cells and neural cell destruction through one of its many mechanisms that are continuously being studied. Understanding the similar pathophysiology of gliosis and neuro destruction in TDP-43 proteinopathies and non-TDP-43 proteinopathies we can compare and contrast and hopefully provide a new direction in the future research of neurodegenerative diseases.Guillain-Barre Syndrome (GBS) GBS is an acute, post-infectious, inflammatory, and demyelinating polyneuropathy caused by cross-linking the body’s autoantibodies to its own axonal antigens . This coCreutzfeldt-Jakob Disease (CJD) CJD is the most common human neurodegenerative prion disease and it is caused by the sporadic, familial, or infectious conversion of normal prion protein (PrPC) to conformationally misfolded and altered prion protein scrapie (PrPSC) . Normal Neurosyphilis Tabes Dorsalis (NTD) NTD is a result of untreated syphilis and subsequently causes a slow degeneration of the dorsal root and dorsal columns . Years aHerpes Simplex Virus-1 (HSV-1) HSV-1 is a virus that commonly causes cold sores. The virus sits dormant in the dorsal root ganglia and occasionally reactivates under stress. HSV-1 occasionally spreads to the central nervous system causing viral encephalitis . In receKennedy Disease Kennedy disease, reclassified as a neuromuscular disease, is an X-linked mutation of misfolded androgen receptor (AR) polyglutamine (PolyQ) accumulation in the muscles and motor neurons in the spinal tract and dorsal root ganglions . Animal Diseases associated with no check of the level of TDP-43, but glial cells involvedThere are different mechanisms involved in multiple diseases illustrated below. Glial cells are involved either directly or indirectly in the pathogenesis of these disorders, while TDP-43 has not been investigated yet. With the advanced technologies, we were able to understand the exact pathophysiology of each disease, this also should enlighten the scientists to further investigate TDP-43 involvement given its function within the neurons. Since the glial cells contributed to the pathology of such disorders, TDP-43 already has clear communication with those cells within the neurons whether initiating activation or inactivating glial cells. We highly suggest extensive investigation of TDP-43 as a contributor to the following diseases.Aicardi Goutieres Syndrome (AGS) AGS is a genetic interferonopathy disorder that affects the brain, spinal cord, and immune system . This diWilson’s Disease (WD) and Menkes Disease (MD) . The glial cells, specifically astrocytes, are key regulators of extracellular ion hemostasis of redox-active metal iron and copper in the brain [WD and MD share similar pathophysiologyhe brain . These che brain . They hahe brain . Wilson'he brain . The glihe brain ,98. Gliahe brain ,98. The he brain ,98. An iNeuronal Ceroid Lipofuscinoses (NCLS) NCLS, also known as Batten disease, is an inherited neurodegenerative disease that affects children . TDP-43'Dandy-Walker Syndrome (DWS)DWS is a cerebellar malformation that is characterized by cerebellar hypoplasia, an enlarged posterior fossa, and dilated fourth ventricle . It is bThese individuals express phenotypes that cause craniosynostosis of coronal sutures, with variable learning disabilities . Even thZellweger Spectrum Disorders (ZSD) ZSD are a rare group of autosomal recessive disorders characterized by mutations in one of 13 peroxisomal biogenesis factors (PEX) genes . These dFriedreich’s Ataxia (FRDA) FRDA is a genetic neurodegenerative disorder that is commonly associated with cardiomyopathy . NeurodeSphingolipidoses: Farber's, Fabry’s, and Tay-Sachs Disease These diseases share similar pathophysiology. The plasma membrane is composed of many molecular components. One major component is the sphingolipids which form tightly packed membranes in myelin . They haTourette Syndrome (TS) TS is a neuropsychiatric disorder in which patients have a persistent tic, either motor and/or vocal . The patPseudotumor Cerebri (PC) PC is a neurological condition presenting with increased intracranial pressure. Most believe it's a disease of CSF disturbance and venous hypertension . HoweverCentral Pontine Myelinolysis (CPM) CPM is characterized by the non-inflammatory demyelination process of the basis pons . There aWernicke-Korsakoff (WK) Syndrome WK syndrome is a neurological structural disease that damages certain brain regions. Patients with WK syndrome have neuropathological changes in the medial thalamus, mammillary bodies, and cerebral cortex . The maiVon Hippel-Lindau (VHL) ProteinVHL protein, a tumor suppressor, is part of the cullin-2 (CUL2) ring complex that functions in the ubiquitin ligase of fragmented forms of TDP-43 . VHL subBarth Syndrome (BS) 2+ and phospholipid exchange [BS is an X-linked recessive disorder that has mutations in the tafazzin (TAZ) gene, which is responsible for cardiolipin remodeling from monolysocardiolipin, which has major effects on skeletal muscle and cardiac muscles . Cardiolexchange . The intexchange . With a Pompe’s Disease (PD) PD is a type of glycogen storage disease caused by the deficiency of 𝛼-glucosidase (GAA), which leads to a toxic accumulation of glycogen in the brain and heart . The accSturge Weber (SW) SW is a rare neurocutaneous disorder caused by a somatic mutation in the guanine nucleotide-binding protein G (GNAQ) gene . IndividMicroglia are extremely sensitive to their microenvironment and as innate immune cells of the CNS, and under normal conditions, they express complement receptor type 3 (CR3) as well as the major histocompatibility complex (MHC I) that are involved in the immune response ,132. AnyTDP-43 and glial cells are involved in various pathophysiology with different mechanisms elaborated above. The signaling cascades among both components contribute to multiple neurological disorders. Therefore, further investigations could expand on TDP-43’s function as a second messenger and its role that is involved in glial cell activation and maintenance of the neuroinflammatory cascade. This results in the rapid progression of TDP-43 proteinopathies. The toxic aggregation of TDP-43 in the cytosol has been associated with a majority of the proteinopathies that have been studied. Accumulation of TDP-43 has been observed in microglia, astrocytes, and oligodendrocytes/oligodendrocyte progenitor cells in these diseases. The elucidation of the mechanism of TDP-43 and glial cell activation behind the pathogenesis of neurodegenerative diseases is the first step in unveiling the accurate pathophysiology of different phenotypes of TDP-43 proteinopathies. In particular, this reveals the pleiotropy that is seen within each disease.


Here we reportan order-of-magnitude acceleration of the interfacial water dissociationreaction under visible-light illumination. This process is accompaniedby spatial separation of protons and hydroxide ions across one-atom-thickgraphene and enhanced by strong interfacial electric fields. The foundphotoeffect is attributed to the combination of graphene’sperfect selectivity with respect to protons, which prevents proton–hydroxiderecombination, and to proton transport acceleration by the Wien effect,which occurs in synchrony with the water dissociation reaction. Ourfindings provide fundamental insights into ion dynamics near atomicallythin proton-selective interfaces and suggest that strong interfacialfields can enhance and tune very fast ionic processes, which is ofrelevance for applications in photocatalysis and designing reconfigurablematerials.Recent experiments demonstrated that interfacial waterdissociation(H The proton currents were found to be exponentially acceleratedwith increasing E (that reached above 108 V m–1), a phenomenon known as the Wien effect.In particular, graphene’s perfect selectivity with respectto protons and its atomic thickness were crucial to observe the Wieneffect. These properties enable the intense interfacial E to separate protons from OH– ions across the atomicallythin barrier that prevents their recombination, thus yielding notableproton currents. The time scale of the involved separation processshould be extremely fast—as a first approximation, comparableto the time scale of proton transport and proton–OH– recombination in water, which is in the subpicosecond range.13 On the other hand, previous experiments showedthat proton transport through graphene electrodes is strongly enhancedunder illumination via a hot-electron-mediated mechanism, the so-calledphotoproton effect.14 Hot electrons ingraphene have a lifetime of ∼1 ps.16 If the proton-hydroxide ion separation across graphene is comparativelyfast, then in principle the photoproton effect should also acceleratethe transport of protons generated by interfacial water dissociation.In this work, we report such an acceleration.A unique combination of propertiesin graphene allows using it as a proton-permeable electrode. One-atom-thickgraphene exhibits high in-plane electric conductivity14 In brief, the crystals were suspendedover holes (10 μm in diameter) etched in silicon-nitride substrates.2 The resulting graphene film was electricallyconnected to allow for its use as an electrode . One side of the suspended graphene was decorated with Pt nanoparticlesdeposited via electron beam evaporation, which served to increasegraphene’s proton conductivity.2 The opposite side of the suspended graphene electrode faced a 1M KCl electrolyte with alkaline pH solution . Thehigh KCl concentration ensures that the electrolyte resistivity isnegligible, whereas the alkaline pH ensured that water is the onlysource of protons in the system. Hence, in this setup all proton currentsarise from the water dissociation reaction, as demonstrated previously.12 The inner side of the devices was also coatedwith an anion-exchange polymer (FAA FumaTech) which is an excellentOH– ion conductor.17 Thepolymer coating was not essential for the described experiments; however,it provided additional mechanical support for the membrane, improvingthe devices’ reliability (“Device fabrication”in Supporting Information). For electricalmeasurements, the devices were connected in an electrical circuitas shown in Supporting Information).Proton-permeablegraphene electrode devices were fabricated usingmonocrystalline graphene obtained by mechanical exfoliation, as reportedpreviously.lectrode S1. One s2O ⇆ H+ + OH–) withthesedevices was demonstrated in ref (+ + e– → H*@Pt) that flow into graphene through theelectrical circuit. These adsorbed protons eventually escape as hydrogenmolecules through the discontinuous Pt film.2 Notethat the μm-sized electrodes ensure that proton transfer throughgraphene dominates the resistivity in the circuit, with negligiblecontributions from the bulk electrolyte and counter electrode19 . On the other hand, the photoeffectin proton transport through graphene electrodes was demonstrated inref response of the devices with alkaline pH electrolytewas measured both in dark conditions and under solar-simulated illuminationof 100 mW cm–2 intensity (Oriel Sol3A light source).We found that the potential at zero current, φ, was negative,in agreement with the previous work12 . For small applied biases V around this potential, the I–V response was linear, which allowed extraction of the devices’proton conductivity, G = I/ΔV, where ΔV = V –φ. I–V response ofthe devices measured at pH 11 under illumination. Surprisingly, G increased by an order of magnitude with respect to thedark case. The inset of Figure S3). The absolute value of G in dark conditions changedwith pH, in agreement with the previous report.12 In all cases, we have observed a strong increase in G under illumination.The currentdensity vs voltage  dependence could be described by the empirical relation I ∝ P0.2, which is consistentwith the dependence found for the photoproton effect reported in ref . Besides graphene,this leaves only the silicon/silicon-nitride substrate as an alternativephotoabsorber. It is unlikely that the robust photoeffect we observedis due to silicon, since it is insulated from the electrical contactsby a thick 500 nm nitride layer . Moreover, we previously demonstrated that the photoeffect in thesedevices can be entirely suppressed if metals like Au or Ag were usedinstead of Pt nanoparticles,14 which wouldbe inconsistent with silicon as the photoabsorber. Nevertheless, wecharacterized the photoeffect using a 1310 nm light source. Such along wavelength cannot be absorbed by the ∼1.2 eV bandgap insilicon but is readily absorbed by graphene.20 We also studied these devices using an acidic pH polymer (Nafion)to study the role of this long wavelength on proton transport. To rule out anypossible artifact, we performed additional measurements.Neither the polymer support nor Pt nanoparticles could yield the photoresponsereported here S6. Besid12 of 108 V m–1, dissociateswater molecules into protons and hydroxide ions (“Wien effect”in Supporting Information). The same fielddrives protons through graphene and hydroxide ions into the electrolytebulk, separating the generated ion pairs across the proton-selectiveinterface that prevents their recombination. The transported protonthen adsorbs on the Pt nanoparticles on the opposite side of grapheneby acquiring an electron. The role of illumination can be understoodusing the following two observations. First, while the absolute valueof I depends on pH, the photoeffect always enhances I by a factor of ∼10 with respect to the dark case.This is the same enhancement reported in ref (I(P), reported here is the same as in ref (Supporting Information).Our results can be understood as follows. The intense electricfield at the graphene–water interface, which is of the orderd in ref  for devis in ref . These o2O ⇆ H+ + OH–) eventually leads to full electrolysis (H2O →H2 + 1/2O2), producing hydrogenand oxygen gas. The gas evolution rates are much slower than the dissociationstep21 . However, in our devicesthese reactions take place in the large Pt nanoparticle film (H2 evolution) and the Pt counter-electrode (O2 evolution).These catalytically active areas are several orders of magnitude largerin size than the graphene electrode and hence effectively behave asdrain reservoirs for the ions. Because of this, gas evolution reactionsare not a limiting factor in our devices,14 and therefore, we also expect to observe an acceleration of thesereactions under illumination. To confirm this, we measured rates ofH2 and O2 production directly, both in darkconditions and under illumination. For hydrogen measurements, thegraphene electrode faced a vacuum chamber connected to a mass spectrometer,whereas an oxygen-concentration sensor (Clark microelectrode) placedinside the electrolyte solution monitored oxygen production . For zero or positive voltagesapplied to graphene, no H2 could be detected by the spectrometer,in agreement with the previous work.14 For the negativepolarity, both H2 flux and electric current were detectedsimultaneously. 2 molecule was detected by the spectrometer.This charge-to-mass conservation is described by Faraday’slaw of electrolysis: ΦH2 = I/2F, with ΦH2 the hydrogen flux and F the Faraday constant. For O2 gas, the area-normalizedderivative of the oxygen concentration versus time, d(O2)/dt = ΦO, was also described byFaraday’s law, ΦO = I/4F  that was also consistent with Faraday’s lawof electrolysis. The found relations show that H2 and O2 molecules were generated in a 2:1 ratio with 100% Faradaicefficiency, which again shows that the measured currents in our devicesare due to water dissociation.Waterdissociation  and thelifetime of hot electrons in graphene . Wehave also shown that strong electric fields acting across atomicallythin and highly selective interfaces can enable ultrafast ion-chargeseparation. The fundamental insights gained here could be of interestfor development of photocatalysts, for which charge separation isa central consideration. Another emerging possibility is the use ofprotons to reversibly modify the electronic properties of materials.This has been explored in low power memory storage,22 plasmonic materials,23 and neuromorphichardware.24 The protonation dynamics inthese applications is important as it can control the response timein write/read or potentiation/depotentiation cycles.24 In addition, our work suggests that atomically thin interfaces cancontrol ion-charge separation dynamics at time scales comparable tothose in optoelectronics, which could open new opportunities in theseapplications.Our work reports a strong photoeffect in the interfacialwaterdissociation reaction using one-atom-thick graphene electrodes. Theobservation is attributed to acceleration of proton transport whichhappens in synchrony with the dissociation reaction. The findingsare consistent with both the fast rate of proton transport and proton–OH