We investigated the nucleation and grain growth of graphene grown on Cu through radio frequency plasma-enhanced chemical vapor deposition (RF-PECVD) at different temperatures. A reasonable shielding method for the placement of copper was employed to achieve graphene by RF-PECVD. The nucleation and growth of graphene grains during PECVD were strongly temperature dependent. A high growth temperature facilitated the growth of polycrystalline graphene grains with a large size (~ 2 μm), whereas low temperature induced the formation of nanocrystalline grains. At a moderate temperature (790 to 850 °C), both nanocrystalline and micron-scale polycrystalline graphene grew simultaneously on Cu within 60 s with 50 W RF plasma power. As the growth time increased, the large graphene grains preferentially nucleated and grew rapidly, followed by the nucleation and growth of nanograins. There was competition between the growth of the two grain sizes. In addition, a model of graphene nucleation and grain growth during PECVD at different temperatures was established. In-depth research has been conducted on the basic preparation, performance optimization, and R&D applications of graphene10. The synthesis of high-quality graphene with excellent performance is a prerequisite for many applications and therefore a core technology for research. A variety technologies for graphene preparation have been developed to meet the needs of practical applications and in-depth research, including mechanical exfoliation1, epitaxial growth11, oxidation-reduction13, chemical vapor deposition (CVD)17, and so on. Due to its excellent controllability and low cost, CVD is one of the most effective methods for preparing high-quality graphene. CVD can be classified into thermal CVD and plasma-enhanced CVD (PECVD) depending on the mode of energy supplied for grain growth. Traditional thermal CVD involves heating a substrate to the cracking temperature of the carbon (C) source  and using dissolution-precipitation19 or adsorption14 of C on a metal substrate to achieve graphene. The high-temperature growth environment required for this method limits substrate preparation and deteriorates the graphene quality during the cooling process21. In addition, the long growth cycle of thermal CVD is not conducive to industrial production.Among the nanomaterials discovered to date, graphene is the thinnest, with the highest strength and electrical and thermal conductivities. These unique properties make graphene a very useful novel material24, copper (Cu)27, and cobalt28, dielectric substrates31, and other 2-dimensional materials32.PECVD offers the advantage of a lower preparation temperature than CVD. Plasma contains a large number of high-energy electrons. Collisions between electrons and gas-phase molecules promote the breakage and recombination of chemical bonds of reactant gas molecules to generate chemical species with high activities. High-energy electrons provide the activation energy required for the CVD process. The mode of energy supply for the reaction system in PECVD is different from that in CVD and enables the entire reaction to proceed at lower temperatures. Therefore, PECVD shows considerable potential for low-temperature graphene preparation. Researchers have achieved the low-temperature growth of graphene thin films by PECVD on transition metal substrates such as nickel33, which considerably limits applications in electronic devices. Previous studies have shown that factors such as the plasma energy35, C/H ratio37, and temperature39 play a significant role in graphene nucleation and grain growth during the PECVD process; among them, the effects of the growth temperature on nucleation and growth were reported to be crucial. Liu et al. revealed that changing the growth temperature induced a nanocrystalline-to-polycrystalline transition of graphene and that nucleation but no graphene grain growth occurred at a specific temperature and vice versa38. Recently, Yen et al. studied the kinetics of nucleation and growth during PECVD and found that the graphene nucleation density and grain size changed with the temperature25.More complex reactions occur during the PECVD process than those during thermal CVD. The plasma can promote the decomposition of hydrocarbon to generate a large number of free radicals and active species, which have extremely high densities and activities and rapidly react on the substrate surface, resulting in the fast nucleation of graphene and a slow growth rate. The final graphene film may have problems such as a small grain size, excessive edges, or the formation of amorphous carbon, which significantly deteriorate the electrical performance of graphene. The electron mobility of graphene prepared by PECVD is much lower than that of graphene films prepared by thermal CVDHowever, in previous studies, there was only one type of graphene nucleation and growth at a specified growth temperature, either nanocrystalline or micron-sized polycrystalline. In this study, a surprising finding that was both nanocrystalline and micron-sized polycrystalline graphene could grow simultaneously during RF-PECVD under certain temperature conditions. Consequently, we investigated the effect of the growth temperature on the nucleation and growth of these two kinds of graphene grains and verified the criticality of temperature for the appearance of nanocrystalline and micron-size polycrystalline graphene. The growth processes of the two graphene grains were observed during different growth times, and a model of graphene nucleation and grain growth at different temperatures during PECVD was established.3PO4:H2O = 2:1) for 5 min. The Cu foil was then rinsed with deionized water for 5 min and blown dry with nitrogen. Atomic force microscopy (AFM) was used to characterize the surface morphology and roughness of the Cu substrate after different pretreatments. Figure Alfa Cu foil  was used as the substrate for graphene growth. The Cu foil was cut to 2 cm × 2 cm and ultrasonically cleaned sequentially using hydrochloric acid (5 wt%), acetone, and isopropanol for 5 min to remove the oxide layer and organic impurities on the surface. The Cu foil was then dried with nitrogen. There have been extensive reports that the Cu foil surface roughness significantly affects the nucleation and growth of CVD-grown graphene. Cu foil with a low surface roughness and high flatness promotes the growth of large grains. Therefore, the Cu foil was pretreated by electrochemical polishing to obtain a flat surface on which to grow graphene by PECVD. The electrochemical polishing was performed at a bias of 1.9 V in a phosphoric acid electrolyte  was turned on, and etching was performed for 1 min. Immediately afterwards, 8 sccm CH4 (methane)/Ar (5% by volume) was introduced for graphene growth. Growth times of 10 s, 20 s, 30 s, 40 s, 60 s, and 90 s were used. When growth was completed, the CH4/Ar mixed gas, H2, plasma, and heating system were turned off. The quartz shield and Cu foil were quickly removed from the reactor. The temperature was reduced to room temperature in 500 sccm Ar. The vacuum system was turned off, and 500 sccm Ar was continuously passed through the system until the system pressure reached ambient pressure. Finally, the Ar gas supply was terminated, and the sample was removed from the apparatus. Figure Graphene was prepared in a radio frequency PECVD (RF-PECVD) apparatus, which was mainly composed of a gas delivery system, a plasma device, a heating system, and a vacuum system. A schematic of the apparatus is shown in Fig. 2/Si). First, PMMA was uniformly spin-coated on the surface of the graphene grown on Cu foil as a protective layer, followed by curing in a vacuum-drying oven at 140 °C for 30 min. The sample was then placed in an iron(III) chloride (FeCl3) solution (5% by mass). After the Cu foil was completely etched, the graphene/PMMA film was transferred to deionized water using a glass sheet, followed by rinsing 3 times to remove residual chemical impurity ions from the sample surface. SiO2/Si was used to pick up the sample. The surface PMMA was removed using acetone and isopropanol to produce graphene on SiO2/Si.The structure and properties of the prepared graphene were subsequently characterized. A polymethyl methacrylate (PMMA)-protected transfer method was used to transfer the graphene to silicon dioxide/silicone  and scanning electron microscopy (SEM). The SEM images were acquired by using an FEI Nova Nano450-SEM instrument at 10 kV. The layer numbers and defects of the graphene were identified by Raman spectroscopy (Horiba Evolution) with a 532-nm laser.Tapping-mode AFM (Oxford Cypher VRS AFM system) was performed to characterize the surface morphology of the Cu foil before and after the electrochemical polishing pretreatment and the morphology and thickness of the graphene on SiO26. In addition, high densities of H atoms and other free radicals cause excessive etching of graphene40. Therefore, we employed three different placement methods to grow graphene. The schematics of the three different substrate placement modes and the corresponding PECVD-grown graphene are shown in Fig. Plasma can effectively promote the decomposition of hydrocarbon precursor, and a mass of plasma-generated ions and radicals, such as Ar ions, cause drastic bombardment2/Si are shown in Fig. 2D/IG ratio of approximately 1.17 showed that there were few layers. The high-intensity D peak of the Raman spectrum in area B suggested there were a mass of edges and defects in area B, which were caused by the nanometer-sized grains of graphene. Figure The characteristics of graphene grown using the third placement method were measured. Optical microscopy and SEM images of the graphene transferred onto SiO4/H2 gas ratio of 0.04, growth pressure of 44 Pa, and growth time of 60 s. In Fig. The nucleation density and grain size of graphene grown on Cu by PECVD using the third placement method were studied at different temperatures. Figure We investigated the dynamics of the nucleation and growth of graphene grains of two sizes; the nucleation density and grain sizes of the large graphene grains (> 600 nm) and nanocrystalline graphene grains (< 600 nm) are plotted as a function of the growth temperature in Fig. 41. Besides, During the high-temperature annealing process, the surface roughness of copper was improved, and the impurities on the copper surface and inside were reduced, which also reduced nucleation and promoted graphene grain growth. When the temperature was very low, there was less catalytic effect of the copper surface, and the dehydrogenation of hydrocarbon depended entirely on the plasma. Due to the high binding energy at low temperature, the nucleation of the active carbon species on the copper surface or adhesion to the edge of the graphene nucleus was determined by the mobility of active radicals on the copper surface, which was reduced at lower temperature. The nucleation rate was limited by capture of carbon adatoms by supercritical nucleus42. There is a critical state in the middle temperature region. The copper substrate surface did not catalyze as strongly as they did at high temperatures, but it was stronger than that of at low temperatures. Carbon atoms are more likely to coalesce and nucleate preferentially at high-energy sites such as the rough surface of the copper substrate, defect sites  and impurities, as they did at high temperatures. Then, some of the subsequent carbon atoms coalesced at these nucleuses to make the grains grow because that subsequent carbon atoms were more likely to enrich at these places. As a result, there were enough carbon atoms to grow graphene for these nucleuses. On the other hand, the adsorption of carbon atoms also occurred elsewhere on the copper surface, but it was sporadic and random, so graphene growth at those sites were affected by the capture of carbon adatoms by supercritical nucleus, which was determined by the diffusion and migration of carbon atoms. The preference of nucleation was related to the energy difference at different sites on the surface of the copper substrate, which could be ignored at lower temperature due to the complete loss of copper catalysis.Generally, temperature has significant effects on the dehydrogenation of hydrocarbon precursors, the adsorption and diffusion of active carbon species on the copper substrate surface, and the surface roughness and cleanliness of copper. At high temperature, plasma and catalytic copper enhanced the supply of the active carbon species by promoting the dehydrogenation of hydrocarbon, which were effective to suppress the excess nucleation and to facilitate graphene growthThe energetics of the growth were investigated by measuring the activation energies. Figure 2/Si, a large number of nanograins smaller than 100 nm were found on the substrate, as shown in Fig. PECVD was carried out at 850 °C for different growth times  to further investigate the growth process of large graphene grains and nanocrystalline graphene grains over the moderate temperature zone. All other conditions remained unchanged. Figure Figure The growth process in the medium temperature region confirmed that the nucleation of large grains preceded the nucleation of small grains and grows at the same time. The nucleation and growth of large and small grains competed with each other for carbon atoms at a given carbon source flow rate. The plasma growth of graphene mainly includes four major processes: the dissociation of carbon sources, the transport of reactants to the substrate surface, the migration and nucleation growth of reactants on the substrate surface, and the desorption of the reaction byproducts on the substrate surface. Due to the greatly enhanced decomposition of the carbon source by the plasma, carbon supersaturation is very high, and the nucleation barrier is very low. The carbon clusters will spontaneously aggregate, and the growth barrier is determined by the deposition of carbon atoms and their diffusion rate on the metal surface. The surface roughness and chemical state of the copper foil greatly influence the deposition and diffusion of carbon atoms. Carbon atoms are more likely to coalesce and nucleate preferentially at high-energy sites such as the rough surface of the copper substrate, defect sites  and impurities. And the follow-up of carbon atoms shows two kinds of behavior. The carbon atoms adsorbed near the nucleus could make the crystal grow, while the carbon atoms adsorbed at other locations were restricted by diffusion and migration, and tended to the termination of the growth of the crystal nucleus, eventually leading to the two completely different graphene grains. This was because that the energy at different locations on the surface of the copper substrate in the medium temperature region played a dominant role in the nucleation and growth of graphene rather than that of at lower or higher temperature.The size distributions of the large grains and the nanograins are shown in Fig. The analysis above was used to develop a model to describe the nucleation and grain growth of graphene grown on a Cu substrate by PECVD at different temperatures. Figure Besides, the copper surface roughness and impurities are not well decreased, so it is easy to produce the growth of nanocrystalline graphene. At medium temperatures, the catalysis of copper substrate is improved to some extent, and the surface roughness of copper is reduced. So there will be carbon atoms preferentially nucleate at some high energy positions on the surface of the copper substrate, where the subsequent carbon atoms are easily attached, providing the raw material to fuel graphene growth. However, the carbon atoms adsorbed in other parts of the copper substrate nucleate and are difficult to grow up due to the influence of blocked diffusion and migration at low temperature. At this stage, the difference of energies on copper surface is an important and non-negligible factor that causes the difference of nucleation growth of graphene. At high temperatures, the catalysis of copper surface is stronger enough, the roughness of copper surface is reduced and the cleanliness is improved. According to the classic diffusion equation In summary, we surveyed the nucleation and grain growth of graphene grown on Cu during RF-PECVD. A reasonable shielding method for the placement of copper was employed and effectively reduced the damage to the graphene in the PECVD process, which could be beneficial for high-quality graphene growth. In addition, the graphene nucleation and grain size of graphene were significantly affected by the growth temperature. At low temperatures (670–760 °C), a mass of nanocrystalline grains was obtained. The nucleation density of nanocrystalline grains decreased and the grain size increased with increasing temperature at this stage. At moderate temperatures (790–850 °C), large grains and nanocrystalline graphene coexisted and grew simultaneously. In this case, as the growth time increased, the large graphene grains preferentially nucleated and grew rapidly, followed by the nucleation and growth of nanograins. At high temperatures (880 °C), there was no more nucleation and growth of nanocrystalline graphene, and grains with an average size of ~ 3 μm were generated. These results reveal the effects of temperature on nucleation and graphene growth during PECVD and provide guidance on the synthesis of high-quality graphene by PECVD.


Lack of directional bonding between two-dimensional crystals like graphene or monolayer transition metal dichalcogenides provides unusual freedom in the selection of components for vertical van der Waals heterostructures. However, even for identical layers, their stacking, in particular the relative angle between their crystallographic directions, modifies properties of the structure. We demonstrate that the interatomic coupling between two two-dimensional crystals can be determined from angle-resolved photoemission spectra of a trilayer structure with one aligned and one twisted interface. Each of the interfaces provides complementary information and together they enable self-consistent determination of the coupling. We parametrise interatomic coupling for carbon atoms by studying twisted trilayer graphene and show that the result can be applied to structures with different twists and number of layers. Our approach demonstrates how to extract fundamental information about interlayer coupling in a stack of two-dimensional crystals and can be applied to many other van der Waals interfaces. Here, the authors show that the interatomic coupling between two layers of a 2D crystal can be determined by studying the angle-resolved photoemission spectra of a trilayer structure with one aligned and one twisted interface, and obtain the inter-atomic coupling for carbon atoms in twisted trilayer graphene. In contrast to conventional heterostructures, in which chemical bonding at interfaces between two materials modifies their properties and requires lattice matching for stability, stacks of two-dimensional crystals are held together by weak forces without directional bonding. As a result, any two of these materials can be placed on top of each other, providing extraordinary design flexibility4. Moreover, subtle changes in atomic stacking, especially the angle between the crystallographic axes of two adjacent layers, can have big impact on the properties of the whole heterostructure, with examples including the observation of Hofstadter’s butterfly6 and interfacial polarons7 in graphene/hexagonal boron nitride heterostructures, interlayer excitons in transition metal dichalcogenide bilayers9, appearance of superconductivity in magic-angle twisted bilayer graphene11 and explicit twist-dependence of transport measurements in rotatable heterostructures14. Phenomena like these arise because the misalignment of two crystals changes the atomic registry at the interface and hence tunes the spatial modulation of interlayer interaction. Consequently, understanding the coupling between two two-dimensional materials at a microscopic level is crucial for efficient design of van der Waals heterostructures.Following the isolation of graphene (a layer of carbon atoms arranged in regular hexagons) in 200417, band replicas and minigaps due to scattering on moiré potential19, charge transfer and vertical shifting of bands21 as well as changes of the effective masses20. Variations in the interlayer coupling as a function of the twist angle, θ, were probed for example using photoluminescence, Raman and angle-resolved photoemission (ARPES) spectroscopies24. Here, we use the last of those methods to image directly the electronic bands in trilayer graphene with one perfect and one twisted interface. From our data, we extract the interatomic coupling, t, describing coupling between two carbon atoms separated by a vector r3D =  = . Such coupling functions, usually based on comparisons to ab initio calculations, can be used to determine electron hoppings in tight-binding26 and continuum28 models of corresponding van der Waals interfaces at any twist angle. We show that t determined purely by measurements on one of the structures accurately describes electronic dispersions obtained for stacks with different θ and number of layers, providing an experimentally verified set of parameters to model twistronic graphene. Our approach makes use of the fact that a trilayer structure is the thinnest stack that can contain both a perfect and twisted interface. The former, due to translational symmetry, can be straightforwardly described in the real space using t. At the same time, the impact of the moiré pattern formed at the latter can be captured in the reciprocal space by considering scattering by moiré reciprocal vectors on the momentum-dependent potential t  at K1. Close to each corner, the intensity reflects the low-energy band structures of unperturbed 2L and 1L. Because the bilayer flake is below the monolayer, signal from the former is attenuated due to the electron escape depth effect. In between the two spectra, coupling of the two crystals leads to anticrossings of the bands and opening of minigaps  in carbon materials.In Fig. In order to understand our data, we use a generic Hamiltonian for a van der Waals heterostructure comprised of three layers of the same two-dimensional crystali-th layer at a twist angle θi, with on-site energies of atomic sites in this layer, εi. Here, because only the relative twist between any two adjacent layers is important, we have θ1 = θ2 = 0 and θ3 = θ. Also, our choice of energy reference point is equivalent to ε3 = 0 and we introduce potential energy difference, 2u = ε1 − ε2, as well as average energy, Δ = (ε1 + ε2)/2, of layers 1 and 2 (the charge transfer between the copper foil and the graphene layers giving rise to u ≠ Δ ≠ 0 is discussed in more detail in ref. 29). For graphene, the intralayer blocks 31 for a triangular lattice with two inequivalent atomic sites, A and B, per unit cell and nearest neighbour coupling between them γ0 ≡ −t, where rAB is a vector connecting neighbouring A and B atoms with the carbon-carbon bond length ∣rAB∣ = 1.46 Å.In this Hamiltonian, the diagonal block, 32). As the bottom two layers are stacked according to the Bernal stacking, a real-space description of the interlayer interaction block t ≡ γ1, with interlayer distance c0 = 3.35 Å, due to atoms with neighbours directly above or below them, as shown in Fig. 33. In contrast, we describe the coupling between the twisted layers, i = 2, 3, in the reciprocal space based on electron tunnelling from a state with wave vector k in layer 2 to a state with wave vector 35, G and t so thatτ =  and θ  and t than structures with one type of interface only. For our graphene trilayer, we compute the miniband spectrum of t25,Vπ and Vσ represent the strength of the π and σ bonding36, respectively, and απ and ασ their decay with increasing interatomic distance.The uniqueness of a trilayer with one perfect and one twisted interface  the magnitudes of the gaps θ = 0, In fitting our numerical results to the experimental data in Fig. t and γ0, γ1, απ and ασ are summarised in Table 25. Importantly, parametrization of t does not depend on the twist angle and so should be applicable to other graphene stacks with twisted interfaces. It also does not depend on the doping level because, for the relevant range of electric fields, the electrostatic energies Δ and u do not modify the electron hoppings. At the same time, once these energies are determined for a particular stack, their influence on the band structure (shifting of the positions and magnitudes of anticrossings) is captured through the Hamiltonian t to different graphene stacks, we compare in Fig. K2-K1k-space cut for, in Fig. θ = 9∘ and, in Fig. θ = 19.1∘. Our model describes the bands of both of the structures well, despite changes in the twist angle, number of layers, potentials u and Δ  and the magnitudes of minigaps.The miniband spectrum resulting from our model is shown in red dashed lines in Fig. entclass1pt{minimat, further by modelling directly the ARPES intensity data  and simulated theoretically (bottom row), in Fig. θ = 9∘ and energies indicated with grey dashed lines in Fig. ε = 0, the two spots of high intensity indicate the positions of the valleys K1 and K2. For energies 0 < ε < −0.6 eV, the bilayer and monolayer dispersions are effectively uncoupled. The crescent-like intensity pattern in the vicinity of K1 reflects the pseudospin of n = 1 (evidence of Berry phase of π39) of electrons in monolayer graphene. In contrast, in bilayer graphene, the low-energy band hosts massive chiral fermions40 with pseudospin n = 2 so that the outer ring pattern in the vicinity of K2 displays two intensity maxima, feature best visible in panel (II). Because in our model all electron hoppings are generated naturally by t, agreement of our ARPES simulation with experimental data provides confirmation that our model and parametrization of the interatomic coupling t leads to the correct band structure. Finally, panels (III)-(V) in Fig. 15 and discussed also for twisted trilayer graphene29 . Overall, our simulated patterns correctly reflect the evolution of the minigap as a function of energy and wave vector as well as the measured photocurrent intensity.We assess the accuracy of our parametrization of the interatomic potential, t is applicable to a wide range of twist angles, including the magic-angle regime34 as well as the 30∘-twisted bilayer graphene quasicrystal42. To mention, it yields the k-space interlayer coupling at the graphene Brillouin zone corner K, 43 which require t decays more rapidly in the real space  than usually assumed. This might explain the discrepancy between theory and experimental ARPES intensities of Dirac cone replicas observed for the case of 30∘-twisted bilayer graphene in ref. 41.Our parametrization of t can be used in graphene structures with different number of layers as, similarly to the case of perfect graphite and other layered materials, coupling to the nearest layer dominates the interlayer couplings. The continuum approach has been applied extensively to model the graphene/graphene interface, including to predict the existence of the magic angle34. Hence, in Supplementary Figure θ ≈ 1.1∘, and show qualitative agreement with the recent experimental data45. The continuum model was also used successfully to interpret experimental observations in graphene on hexagonal boron nitride5 as well as homo- and heterobilayers of transition metal dichalcogenides47. Our approach allows for experimental parametrization of the interatomic coupling t for each of these interfaces as well as for others for which influence of neighbouring crystals can be approximated by considering the harmonics of the moiré potential52. To comment, previous studies suggest that adapting our model to stacks of transition metal dichalcogenides requires taking into account changes in the interlayer distance as a function of the twist angle20. Moreover, in contrast to graphene, for which the part of q pointing to the Brillouin zone corner, q ≈ K, for transition metal dichalcogenides more significant changes due to interlayer coupling occur in the vicinity of the Γ point. In multilayers of 2H semiconducting dichalcogenides MX2 , coupling of the degenerate states at the Γ point built of transition metal pz orbitals leads to their hybridisation and splitting which drives the direct-to-indirect band gap transition54. Using the form of t suggested in ref. 26 for chalcogen pz-to-pz hopping (which dominates the interlayer coupling) in transition metal disulfides and diselenides, we computed the corresponding cX−X ≈ 3 Å. Taking into account the fractional contribution of the pz orbitals to the top valence band states at Γ in a monolayer26, we obtain coupling between two such states in bilayer  ~0.4 eV. This, in turn, suggests band splitting of  ~0.8 eV, in qualitative agreement with observations55. This supports the idea that our model can accurately describe and parametrise interatomic coupling between materials other than graphene.As we have shown, the same interatomic coupling 11, structures containing both a twisted and a perfect interface like twisted trilayer graphene57, double bilayer graphene63 or double bilayer WSe264 recently attracted attention on its own due to observation of correlated electronic behaviour. Our approach provides one of the avenues to build an experimentally validated single-particle base to study such effects. It could be, in principle, also applied to stacks of different materials, as long as one of the interfaces is commensurate and can be described in the real space in a tight-binding-like fashion. Finally, apart from continuum models, the interatomic coupling t can also be used directly in large scale tight-binding calculations for commensurate twist angles67.Experimentally, our approach requires fabrication of trilayer (or thicker) stacks with one twisted and one perfect interface in order to benefit from the complementarity of the information obtained from self-consistent real- and momentum-space description of the interfaces. However, to note, building on the observations of superconductivity in magic-angle twisted bilayer graphene∘ for 30 minutes. The experiment was then performed at a base pressure of 10−10 mbar in ultrahigh vacuum and at the temperature of 110 K. We used photons with energy of 74 eV and estimate our energy and angular resolution as 50 meV and 0.5∘, respectively. For each sample, we determined the twist angle θ by measuring the distance between the Brillouin zone corners K2 and K1 which depends on the twist angle, The ARPES measurements were performed at the Spectromicroscopy beamline at the Elettra synchrotron . Before measurements, the samples were annealed at 350pz orbitals ϕ(r3D)31,k is electron wave vector, X = A, B is the sublattice, Rl are the lattice vectors of layer l and τX,l points to the site X in layer l within the unit cell selected by Rl. We include in the basis all states coupled to k through 38 for a detailed discussion of this approach for the case of graphene on hexagonal boron nitride). We determine the broadening of the ARPES signal as well as the decay constant for the intensity of Bernal bilayer signal by fitting to the experimental data.We write the Hamiltonian mentclass2pt{minimbitals ϕrD31,\docuSupplementary Information


This work presents the development of tin oxide nanofibers (NFs) and nanoribbons (NRs) sensors with graphene as a dopant for the detection of volatile organic compounds (VOCs) corresponding to different chronic diseases . This research aims to determine the ability of these sensors to differentiate between gas samples corresponding to healthy people and patients with a disease. The nanostructures were grown by electrospinning and deposited on silicon substrates with micro-heaters integrated. The morphology of NFs and NRs was characterized by Scanning Electron Microscopy (SEM). A gas line was assembled and programmed to measure a wide range of gases  at different concentrations simulating human breath conditions. Measurements were made in the presence and absence of humidity to evaluate its effect. The sensors were able to differentiate between the concentrations corresponding to a healthy person and a patient with one of the selected diseases. These were sensitive to biomarkers such as acetone and ethanol at low operating temperatures (with responses above 35%). Furthermore, CO and NO response was at high temperatures (above 5%). The sensors had a rapid response, with times of 50 s and recovery periods of about 10 min. For centuries, the use of aromas was employed to identify different diseases through the breath. Doctors could identify diseases such as diabetes or kidney failure using this method based on experience . SimilarThe air exhaled by a person contains many VOCs, whose concentrations can vary depending on various external factors such as age, weight, sex or lifestyle. Diseases are another parameter that can modify the composition of the breath, in particular, some respiratory and digestive diseases .Based on these ideas, electronic equipment capable of imitating olfactory organs of mammals began to be developed . All thiThere was great growth in the gas sensors area with the extension and discovery of new nanomaterials and improved manufacturing techniques. This allowed obtaining more selective sensors towards different compounds and sensitivity to lower concentrations. We investigate graphene-doped tin oxide sensors responses as components of a home-made electronic nose in this work. Sensors based on sensitive one-dimensional nanostructured metal oxide layers were demonstrated to have superior performance in comparison to thin-film ones. Besides, tin oxide remains an essential material in the manufacture of resistive sensors. The use of graphene as a dopant in this type of sensor improves its electrical properties and increases the chemical sensitivity to different compounds ,8.Nanostructures can be synthesized through different methods such as chemical vapor deposition, electro-deposition, thermal evaporation, rapid oxidation, electrospray or electro-spinning. The latter is a simple and economical method for the manufacture of nanostructures. The fibers manufacturing process begins with using a high molecular weight organic polymer, incorporating a metallic precursor. The process consists of applying an electric field to this solution. The solution formed by the organic polymer and the metallic precursor has a specific viscosity. The solution is projected onto the surface when the electric field effect is greater than the surface tension ,10,11.Improvements in electronic noses based on nanostructured materials will positively influence the challenges medicine faces today, enabling the development of economic and portable equipment. These devices open the door to better diagnosis and more effective control of various chronic diseases, such as asthma or diabetes  ,13,14. TStaphylococcus aureus, which affected more than 119,000 people in the USA in 2017, with a mortality rate of about 17% [On the other hand, pneumonia or respiratory infections can be a significant problem for patients with these chronic diseases. Due to this, they are more likely to contract them and suffer an exacerbation of chronic disease symptoms. One of the most common infections is bout 17% . Previoubout 17% .These pathologies cause an increase in the concentration of the corresponding compound in the patient breath, compared to a healthy person. Furthermore, this concentration increases with the worsening of the disease. Staphylococcus aureus, certain compounds such as alcohols and aldehydes can be observed. The concentration of these compounds increases exponentially for hours as the bacterial concentration in the culture increases. Of these, ethanol was selected, one of the gases where most variation is observed between 1 and 6 h. Moreover, if the sample contains This research aims to determine the capacity of these sensors to differentiate between gas samples (generated in the laboratory) corresponding to healthy people and patients with a disease. The final goal is to develop a multisensory system for this application.4·5H2O, 98%) precursor materials were supplied by Sigma-Aldrich . Distilled water as a solvent. Pristine graphene (PG) was used as a dopant prepared by the liquid phase exfoliation  and tin (IV) chloride pentahydrate (SnClous work ). The pre layers .4·5H2O and 4.1 mL of graphene solution were added, obtaining a final concentration of 100 ppm (graphene/Sn 0.01 wt.%). Finally, the solution was cooled to room temperature and stirred during the process to obtain a homogeneous mixture and avoiding leaving bubbles that could spoil the electro-spinning process [First, the aqueous PVA solution (11 wt.%) was prepared by dissolving it in distilled water and heating it to 90 °C while stirring it for 45 min. Then 1.2 g of SnCl process .2-graphene nanofibers and nanoribbons. The PVA/SnCl4·5H2O/PG precursor solution was loaded into a syringe pump connected to a metallic needle. A positive voltage of 19 kV was applied between the needle tip and metal collector at 6 cm of distance. The micromachined silicon substrate was placed on the collector and the precursor solution was directly electrospun onto the substrate at a flow rate of 2 µL/min for 20 min. All sensors were prepared under the same conditions. Electrospinning system details were described in a previously published paper [2-PG.An electrospinning process was used to synthesize SnOed paper . SubsequStaphylococcus aureus infection and diabetes, respectively. Both permeation tubes were home-developed and subsequently calibrated for use. The measurement setup shown in The permeation tube was placed in the oven of the OVG-4 vapor generator module  to generate ethanol or acetone concentration. The oven temperature was placed at the necessary value to achieve the desired concentration knowing the permeation rate, calculated by calibration. The oven flow rate was set at 100 mL/min, thus obtaining the maximum concentration required and then diluting with air afterward. It was necessary to ensure that the oven conditions remain constant throughout the measurement process.A humidity generator was also incorporated to prepare gas mixtures more similar to human breath. The exhaled air can contain between 90 and 95% relative humidity (RH). The experiments were carried out without humidity and at 50% RH to determine its influence on sensor response.A gas mixing unit , with four mass flowmeters, was used to control the gas mixture concentration. Flowmeter no. 1 controls the humidifier airflow, while flowmeter no. 2 controls the dry air. When a calibrated gas bottle is used, flowmeter no. 3 controls the CO or NO bottle flow.On the other hand, when permeation tubes are used, flowmeters no. 3 and 4 are utilized to keep a constant airflow through the oven. The sum of the flow of both flowmeters must always be the same to maintain the permeation conditions. The flowmeter no. 3 controls the airflow that is desired to add to the mixture. On the contrary, the rest of the air, controlled by flowmeter no. 4, is discarded. The gas mixture obtained was passed through the cell where the sensors are located. The sensors were connected to the programmable power supply  to supply the heaters. An electrometer  is used to measure the sensor resistance. The whole process and equipment were controlled through the pc, using software home-developed with LabVIEW.The National Microelectronics Centre  developed the micromachined silicon substrate used to deposit the nanostructures . This de2) was characterized by scanning electron-microscopy . SEM images . The spectrum ensures that the nanofibers contain O and Sn atoms. A carbon peak is due to the graphene loading, not detected in the pristine SnO2 NFs, as displayed in our previous work [ous work .2O3 NFs and NRs were also produced by this process [NFs and NRs are intertwined, forming non-uniform porous networks. The pore area of these networks varies from several microns to tenths of nanometers. Large pores with a high surface/volume ratio are favorable for gas detection facilitating gas penetration. Reports confirm that nanoribbons were obtained by electrospinning with PVA solutions at low concentrations (about 13%) and high Mw  ; In2O3 N process . Other w process ,28.Different concentrations of acetone, ethanol, NO and CO were utilized to determine the sensor response. This response is calculated using Equation (1) for reducing gases, where Ra and R correspond to the sensor resistance under exposure to the air and selected gas, respectively:Detections were carried out in the range of 25 to 300 °C to determine the temperature for maximum sensor response. Ethanol and acetone were selected as the most representative gases to show their responses. This is very similar in all sensors, with around 16% variations demonstrating that the deposition process is uniform. Therefore, only one sensor response will be provided to simplify the graphs. The sensor response to 4 ppm acetone and 2 ppm ethanol at the different operating temperatures is shown in At 300 °C, as shown in the experimental detection curves , detectiThe measurements with different concentrations of the selected gases were made at 300 °C, as a more significant response is obtained at this temperature. On the following response graphs, the green shade represents the concentrations corresponding to healthy people, while the red shade corresponds to the concentrations of people with the pathology under study in each case. For ethanol, this type of representation is not used as it shows the evolution of the infection in the culture over time.Detections were carried out in dry (0% RH) and wet (50% RH) air  to evaluThe percentage variations between the highest concentration in the healthy person and the lowest in the patient  with difStaphylococcus aureus infection. Finally, ethanol was measured at different concentrations as a biomarker of The sensors present different responses to the target gases in the employed temperature range. − [The gas detection mechanism on semiconductor metal oxide is generally described based on the “ionosorption model” ,30. When− ; the sim− ,33,34:InIt should be remarked that NO behaves as a reducing gas in the tested temperature range (25–300 °C). All the detection processes proved that the behavior and resistance of all sensors decreased in the presence of NO. Accordingly, a similar reaction to the reducing gases previously mentioned can be considered for NO (6):2 (oxidizing gas). However, detections were performed to confirm that NO does not oxidize in the test cell, which could be due to the optimal design of the gas line, facilitating immediate access to the gas.Nitrogen monoxide is unstable and oxidizes to form NO+, is ready for the reaction with lattice oxygen or adsorbed oxygen [In general, the detections in the wet atmosphere carried out in this work demonstrated that the sensor responses to VOCs (acetone and ethanol) decrease in the presence of water vapor. Water molecules can be adsorbed by physisorption (molecular water) and chemisorption (hydroxyl groups), although at temperatures above 200 °C, molecular water is no longer present on the surface. Adsorption of water vapor produces an increase in the electronic conductivity of tin oxide. This is due to the chemisorbed hydroxyl groups being bound to tin atoms and the proton, Hd oxygen ,35. The − and OH−). It was demonstrated that CO reacts with the OH− ions adsorbed on the surface of the semiconductors to form anions (HCOO2)− as intermediate species according to the reaction [Moreover, water molecules also act as a barrier. The VOCs detection scenario would be that water vapor inhibits oxygen adsorption on the tin oxide surface. However, in CO and NO detection, a response increase is observed: The higher response is due to two reactions that can take place simultaneously with the adsorbed species (Oreaction :CO (g) +2 NRs/NFs. Graphene NSs and SnO2 NRs/NFs form a heterojunction. SnO2 and graphene work functions are 4.55 and 4.60 eV, respectively [2 lies higher than the Fermi level of graphene.Finally, it should be noted that in this work, the presence of graphene improves the detection at low temperatures and increases the response to gases, possibly due to n–p heterojunction. In our previous work, undoped tin oxide nanostructures, also prepared by electrospinning, did not obtain a significant response to acetone below 300 °C . Interacectively ,38,39,402 to graphene, causing a depletion region on the SnO2 surface, resulting in increased base resistance. Specifically, at room temperature, the base resistance of SnO2 NRs/NFs is in the tens of KΩ range. The addition of 100 ppm of graphene results in a slight increase in initial resistance. This will form potential barriers at the heterojunctions that will be modulated by gas adsorption. This mechanism would add to the SnO2 intergrain barrier modulation and could explain the increase of sensor response. The morphology of the sensor layer with NFs and NRs forms porous networks facilitating gas penetration and improving sensor sensitivity.Consequently, to equilibrate the Fermi level, electrons flow from SnOThe above results confirm that graphene-doped tin oxide sensors can be used in an electronic nose for disease detection and control applications. The PG-doping effect seems to enhance the detection at low temperatures, compared to previous publications without PG, and increase the response at low gas concentrations. On the one hand, this will allow using sensors at different temperatures to differentiate between different gases and detect lower concentrations. Moreover, on the other hand, it will be possible to use sensors without heating resistances that will allow simplifying the substrate and making a more energy-efficient device. All this will contribute to the development of portable and low-cost equipment that could be used in health centers or by patients themselves at home. For all these reasons, we consider that this technology has a great potential to become a wearable technology, gadget or even to be integrated into smartphones or smartwatches.− groups can displace part of the adsorbed oxygen species, decreasing the sensor response. This is observed in the detection of ethanol and acetone. However, both interact with absorbed species (OH− and O−) in CO and NO detection, increasing the sensor response.The sensors have detected the gases selected as biomarkers  in the concentrations corresponding to healthy people and patients with different pathologies. The highest response was obtained at 300 °C, although the sensor also responded to lower temperatures, particularly at room temperature for acetone and ethanol. Different responses can be obtained with similar sensors, heating each of them to a different temperature to detect the biomarkers selected. This device can. Therefore, be used in a multi-sensorial system (electronic nose). It was also observed that humidity does not prevent adequate gas detection, but it does modify the sensor responses. The absorbed OHWe will consider using higher percentages of relative humidity to determine its effect on sensor response in future work. In this way, we will approximate the values found in the breath of a person. We will also use non-heated substrates to achieve a more energy-efficient device with longer battery life. Other metal oxides could be used as a sensitive layer and different dopants to achieve better selectivity and a broad spectrum of response when used in a sensor array in an electronic nose.


G3BP1/2ΔΔ cells. Collectively, our data suggest that SG and PB assembly may facilitate TDP-43 cytoplasmic localization and aggregation but are likely not essential for these events.Stress granules (SGs) are hypothesized to facilitate TAR DNA-binding protein 43 (TDP-43) cytoplasmic mislocalization and aggregation, which may underly amyotrophic lateral sclerosis pathology. However, much data for this hypothesis is indirect. Additionally, whether P-bodies  affect TDP-43 phenotypes is unclear. Here, we determine that induction of TDP-43 expression in yeast results in the accumulation of SG-like foci that in >90% of cases become the sites where TDP-43 cytoplasmic foci first appear. Later, TDP-43 foci associate less with SGs and more with PBs, though independent TDP-43 foci also accumulate. However, depleting or over-expressing yeast SG and PB proteins reveals no consistent trend between SG or PB assembly and TDP-43 foci formation, toxicity or protein abundance. In human cells, immunostaining endogenous TDP-43 with different TDP-43 antibodies reveals distinct localization and aggregation behaviors. Following acute arsenite stress, all phospho-TDP-43 foci colocalize with SGs. Finally, formation of TDP-43 cytoplasmic foci following low-dose chronic arsenite stress is impaired, but not completely blocked, in  Amyotrophic lateral sclerosis (ALS) or Lou Gehrig’s disease is a progressive neurodegenerative disease characterized by the death of upper and lower motor neurons, ultimately resulting in death, typically around 2–5 years after diagnosis. Approximately 90% and 10% of cases are sporadic and familial, respectively .TDP-43 is a nuclear RNA-binding protein that regulates a multitude of steps in the life of mRNAs from transcription to mRNA stability, as well as impacting miRNA biogenesis . NonetheStress granules (SGs), which are stress-induced assemblies of non-translating mRNA-protein complexes (mRNPs) ,9,10, haHowever, recent studies have suggested that the formation of cytoplasmic TDP-43 aggregates can occur either as an indirect consequence of SG assembly or be completely independent of SG assembly. For example, sequestration in SGs of HDAC6, which promotes autophagic turnover of protein aggregates , has beeIn this work, we utilized both yeast and human cell line models impaired in assembly of SGs, and/or related mRNP foci, termed P-bodies (PBs), to directly test the role of these mRNP granules in regulating TDP-43. We found that formation of cytoplasmic TDP-43 foci in yeast and human cell models shows a clear initial association with SGs, and at least in yeast later exhibits lower SG colocalization but increased localization with PBs. However, our yeast studies indicate no consistent relationship between the ability to form SGs or PBs and the aggregation, toxicity or abundance of TDP-43 protein. TDP-43 toxicity also does not strictly correlate with TDP-43 abundance or aggregation. In human cells, endogenous TDP-43 exhibits distinct localization phenotypes depending on the antibody utilized, which has implications for prior works in the field. Finally, cells deficient in SG assembly show impaired assembly of TDP-43 cytoplasmic foci during and following chronic stress. Together, our work is consistent with the notion that the ability to form SGs can facilitate TDP-43 cytoplasmic localization and aggregation under some circumstances but are not essential to this process.The strains used in this study are described in All plasmids utilized in this study are listed in GAL1-driven TDP-43 or empty vector plasmids were cultured overnight in 0.25% galactose and 1.75% sucrose. The overnight cultures were back diluted to 0.1 OD600nm in identical media, followed by growth at 30 °C to mid-log (~0.5 OD600nm), after which the cultures were adjusted to 0.2 OD600nm, serially diluted (1/5 dilutions), and spotted onto agar media containing either 2% glucose, 0.25% galactose/1.75% sucrose or 2% galactose. Higher levels of galactose induce stronger TDP-43 expression and thus toxicity [GAL1-driven TDP-43 plasmid/empty vector plasmid.To induce TDP-43 expression, strains with plasmids expressing toxicity . For theGAL1-driven TDP-43 and SG/PB marker were cultured overnight in 2% sucrose. The overnight cultures were back-diluted to 0.1 OD600nm in identical media, followed by growth at 30 °C to mid-log (~0.5 OD600nm), after which the media was switched to 2% galactose and live-cell microscopy was performed at indicated timepoints. Hoescht was added at a final concentration of 12 μg/mL to cultures 10 min prior to visualization to stain DNA. To induce TDP-43 expression , after which live-cell microscopy was performed. For To induce TDP-43 expression for sion for  onwards,Western blotting was carried out by standard protocols. Protein extracts were loaded onto SDS-polyacrylamide gels. Unless otherwise indicated, TDP-43 was detected by using Rabbit polyclonal anti-TDP-43  at a 1:10,000 dilution. GAPDH  was detected by using Mouse anti-GAPDH  at a 1:25,000 dilution. YFP was detected by using Rabbit anti-GFP  at a 1:10,000 dilution. Detection was carried out by using Li-Cor fluorescently labeled secondary antibodies and the LiCor Odyssey Imaging system . Secondary antibodies used were IRDye 800CW Goat anti-Rabbit IgG (H + L) and IRDye 800CW Goat anti-Mouse IgG (H + L)  to detect the primary antibodies mentioned above as appropriate.Oligonucleotides targeting TDP-43 were ordered from Integrated DNA Technologies . Oligonucleotides were annealed and cloned into pCas-Guide  according to manufacturer’s protocol. gRNA targeted the following sequence: GTTTGTGGGGCGCTGTACAG. Cloned pCas-guide was co-transfected with pDonor-D09  using Lipofectamine 2000  into U-2 OS cells. The following day, cells were treated with puromycin (1.5 μg/mL). After 48 h of selection, puromycin was removed. Single-cell clones were generated by limiting dilution.G3BP1/2ΔΔ cell lines were generated as previously described [U-2 OS cells were grown in 8-well chamber slides , fixed with 4% paraformaldehyde for 15 min, permeabilized with 0.1% Trion X-100 for 10 min and then blocked in 5% goat serum for 1 h. Cells were incubated with indicated primary antibodies at RT for 2 h. Cells were washed three times and then incubated with Alexa Fluor conjugated secondary antibody  for 1 h at room temperature. After three washes with PBS, cells were stained with DAPI  and imaged using a Deltavision Elite microscope  with a 20× objective. Antibodies used for immunofluorescence were α-TDP-43 , α-phospho(S409/S410)-TDP43 , α-G3BP , α-TIAR . escribed .GAL1 regulatable promoter, which behaves similarly to a previously described yeast TDP-43-YFP model [To assess the importance of SGs and PBs on initial TDP-43 aggregation events, we induced expression of TDP-43 in yeast and examined how TDP-43 foci formation over time relates to both structures. TDP-43 expression in yeast recapitulates aggregation and toxicity phenotypes associated with human cell models  and alloFP model ,35 in teFP model . Pab1-GFAt 2.5 h of induction, TDP-43-mRuby2 signal was not readily discernible above vacuolar auto-fluorescent background levels; some faint diffuse nuclear signal (white arrowheads) was observed in a fraction of cells, consistent with prior observations of nuclear TDP-43 accumulation under low expression conditions . NotablyIn summary, our data suggest that early in a TDP-43 induction timecourse (2.5 h), SGs are induced, which later serve as sites of initial TDP-43 foci appearance in the majority of cases; SG-independent perinuclear TDP-43 foci are also observed at 3 h, which is distinct from previously described intranuclear TDP-43 foci . Over tiGAL1-driven TDP-43-YFP from a single copy plasmid in previously described SG assembly mutants [As most TDP-43 foci initially appear within yeast SGs A, and th mutants ,38 and apbp1Δ strains slightly increased TDP-43 toxicity in our hands , has little effect on TDP-43 toxicity.We found that TDP-43 toxicity in previously identified SG assembly mutants was generally very similar to that in WT strains; findings ), whereastriking A. Additipub1Δ, pbp1Δ, eIF4G1Δ or eIF4G2Δ strains to form SGs and the propensity of TDP-43 to form cytoplasmic foci  that exhibit stronger blocks in PB assembly relative to the above tested SG mutants [While SGs have received much attention as putative sites of TDP-43 concentration, leading to aggregation and possibly enhanced toxicity, there has been less focus on whether PBs could play a similar role. Additionally, in yeast, PB assembly can stimulate SG assembly, and mutants exist , PBP1 (SG assembly protein), SCD6 (PB assembly protein), PAT1 (PB assembly protein), BRE5 (SG assembly protein) and UBP3 (SG assembly protein)  . While ntoxicity . As for -43 foci B,C, wherexamined D,E.PUB1 and SCD6 over-expression adhere to this. In contrast, PAT1 over-expression increases TDP-43 toxicity but strikingly reduces TDP-43 foci numbers/cell. Additionally, DED1 over-expression increases TDP-43 levels but does not result in significant changes to TDP-43 toxicity or foci formation. Even stronger DED1 over-expression via a GAL1-promoter plasmid, which does visibly increase TDP-43 foci size, still fails to exhibit significant toxicity effects ; however, contrary to other reported observations with this antibody in distinct cell lines [TDP-43Δ cells. In summary, endogenous TDP-43 indeed localizes to SGs, but the extent of colocalization observed depends strongly on the antibody used.To assist the TDP-43 community, we tested the specificity of these antibodies  via Western blotting of cells either harboring full length or an N-terminally truncated TDP-43-GFP species (and endogenous TDP-43)  and comp3Δ cells . Finallyll lines ,47, we oVarious models for how SGs may promote TDP-43 aggregation exist, predominantly based on human cell line and ALS patient tissue data. The first suggests that TDP-43 initially localizes in SGs, leading to formation of a persistent, non-dynamic TDP-43-containing SG aggregate; certain ALS histological studies and cell line studies with inducible SG assembly support this ,48. A seG3BP1/2ΔΔ cell lines, which are virtually devoid of microscopically visible SGs under arsenite stress (a stronger SG impairment than any yeast SG assembly mutants we earlier observed), and examined formation of TDP-43 cytoplasmic foci over both an acute high dose  and chronic low dose  arsenite stress timecourse, as well as after stress recovery.A simple test of the above models is to examine whether TDP-43 cytoplasmic aggregation is altered in cells unable to form cytoplasmic SGs. If SGs do facilitate TDP-43 aggregation, SG assembly mutants should exhibit fewer TDP-43 foci; if TDP-43 aggregation is SG-independent, no effect on TDP-43 aggregation in SG mutants would be expected. We utilized G3BP1/2ΔΔ cell lines following acute arsenite stress to determine if SG assembly and TDP-43 localization there may impact TDP-43 solubility. Notably, TDP-43 solubility clearly decreased more in WT cells than in G3BP1/2ΔΔ cells following arsenite stress, based on Sarkosyl detergent solubility [G3BP1/2ΔΔ cells  under acute arsenite stress conditions, but this does not result in persistence of TDP-43 foci thereafter once SGs have disassembled.During acute arsenite stress, only WT cells formed SGs as expected, into which TDP-43 readily colocalized; 94% colocalization at 1 h A. We alslubility , though ΔΔ cells B,C. ThisG3BP1/2ΔΔ cells, . Second, following 6 h of recovery, there was a higher number of TDP-43 foci present in WT cells  versus G3BP1/2ΔΔ cells , with again only occasional overlap with G3BP foci signal in WT cells. Third, in WT cells, we rarely observed microscopically visible SG formation with this concentration of arsenite, including at earlier timepoints. TDP-43 foci colocalized with SGs in only 1.9% of cases at the 16 h chronic stress timepoint; thus, a clear relationship between SG assembly and TDP-43 foci formation under this condition remains to be determined (see discussion). In summary, G3BP1/2ΔΔ cells are impaired, though not completely blocked, in TDP-43 foci formation under a chronic stress regime and following 6 h of recovery; this suggests a facilitating but non-essential role for mammalian SGs in TDP-43 aggregation under chronic stress.In contrast, during chronic arsenite stress, three key observations were made B. First,G3BP1/2ΔΔ cells, we observed no difference in TDP-43 levels compared to WT prior to stress. However, we did observe a modest 20% decrease in TDP-43 protein levels by 1 h of acute arsenite stress, which decreased a further 10% by 2 h of recovery . This preliminary data suggests that SG assembly may help maintain TDP-43 protein levels during and after acute stress.We next examined whether the ability to form SGs affects endogenous TDP-43 protein levels before, during or following recovery from an acute arsenite stress. In WT cells, no significant change in TDP-43 levels was observed over an hour of stress or after 1 or 2 h of stress recovery A,B. In GG3BP1/2ΔΔ cells again revealed a decrease in TDP-43 levels following stress, which was prevented by the presence of MG132, but not Bafilomycin A1. This preliminarily suggests that in G3BP1/2ΔΔ cells, the reduction in TDP-43 levels during and following recovery from an acute stress is related to increased proteasomal turnover of TDP-43. We cannot however rule out that other factors  may impinge on this result.To understand this result further and examine the possible contribution of protein turnover mechanisms, we re-examined endogenous TDP-43 protein levels before stress and after 1 h of stress and 2 h of recovery in the presence or absence of MG132  or Bafilomycin A1  . While WT cells showed no significant change in TDP-43 levels under any of the examined conditions, Our data, in yeast and human cells, suggest that >90% of cytoplasmic (non-nuclear-associated) TDP-43 foci first form in association with microscopically visible SGs. In yeast, inducing TDP-43 expression alone induces SGs, which appear shortly before visible TDP-43 foci appear . It is uTo our knowledge, the localization of TDP-43 in PBs has not previously been addressed, certainly during a time-course analysis. We do not know why in yeast TDP-43 initially localizes in SG-like foci and over time shows increasing localization to PBs. SGs and PBs interact physically and can exchange certain mRNP components ,51,52. PC9ORF72 repeat expansion mouse model of ALS [C9ORF72 repeat expansion mutations are the most common cause of familial ALS). Importantly, impairment of SG assembly via Ataxin-2 depletion and chemical inhibitors of eIF2α phosphorylation can suppress nucleocytoplasmic trafficking defects and C9ORF72 ALS models of neurodegeneration [Recently, cytoplasmic TDP-43 aggregates and SGs have been strongly linked to nucleocytoplasmic trafficking defects, which are now a pathology hallmark of interest in ALS. Specifically, forms of TDP-43 prone to aggregation or cytoplasmic accumulation interact and sequester nucleocytoplasmic machinery, leading to impairment of import and export processes and altered nuclear pore and lamina morphology ,54. SG al of ALS  , a key SG assembly factor in yeast [SCD6, a translation repressor protein that localizes within and promotes P-body assembly in human cells [SCD6 over-expression revealed the most striking increase in TDP-43 foci levels and size and a clear enhancement of TDP-43 toxicity  promote SG assembly [bre5Δ and ubp3Δ yeast strains [SCD6 over-expression .While TDP-43, by virtue of its IDR and RNA-binding activity, likely can accumulate in numerous RNP compartments rich in IDR-containing proteins , a key issue is the extent to which TDP-43 interactions, abundance, conformation and modification status drive distinct TDP-43 localization and aggregation behaviors. Recent work demonstrated that TDP-43 harbors poly(ADP-ribose) (PAR)-binding activity in domains that overlap its NLS, and this binding activity is critical to TDP-43 localization in mammalian cell and neuronal SGs , which aG3BP1/2ΔΔ) to SG assembly in mammalian cells completely impairs the formation of cytoplasmic TDP-43 foci under acute high arsenite stress  can facilitate TDP-43 cytoplasmic mislocalization and aggregation but are not essential for the process. Supporting this, TDP-43 cytoplasmic foci first form in the majority of cases with SGs —see alsoe stress  and redue stress . Notablye stress , though requency B. Taken


In this work, we have designed and simulated a graphene field effect transistor (GFET) with the purpose of developing a sensitive biosensor for methanethiol, a biomarker for bacterial infections. The surface of a graphene layer is functionalized by manipulation of its surface structure and is used as the channel of the GFET. Two methods, doping the crystal structure of graphene and decorating the surface by transition metals (TMs), are utilized to change the electrical properties of the graphene layers to make them suitable as a channel of the GFET. The techniques also change the surface chemistry of the graphene, enhancing its adsorption characteristics and making binding between graphene and biomarker possible. All the physical parameters are calculated for various variants of graphene in the absence and presence of the biomarker using counterpoise energy-corrected density functional theory (DFT). The device was modelled using COMSOL Multiphysics. Our studies show that the sensitivity of the device is affected by structural parameters of the device, the electrical properties of the graphene, and with adsorption of the biomarker. It was found that the devices made of graphene layers decorated with TM show higher sensitivities toward detecting the biomarker compared with those made by doped graphene layers. Graphtivities  a the prtivities ,5,6. To tivities ,9,10,11,tivities ,13, as ativities ,15, and tivities ,17 and btivities ,19. Usintivities ,22,23,24tivities ,28,29,30tivities ,32,33, ativities .2 molecules on the surface. Thereafter, researchers work extensively on graphene and its derivatives for sensory activities based on piezoelectric effects [Escherichia coli (E. coli) [Moreover, due to the high surface-to-volume ratio and the possibility of generating high adsorption site density , graphen effects ,38,39,40 effects ,42,43, s effects ,45,46, a effects ,23,47. G effects , monosod effects , EscheriE. coli) , ethanolE. coli) , glucoseE. coli) , hydrogeE. coli) , exosomeE. coli) , and nitE. coli) .In this report, we model, design, and analyse GFET biosensors. For this, graphene is transmuted into semiconducting material using two methods. The first approach is doping graphene with impurities such as boron (B), aluminium (Al), and gallium (Ga) as n-type and nitrogen (N) phosphorous (P) and arsenic (As) as p-type dopants. Decorating the graphene surface with a transition metal (TM) such as palladium (Pd) is the second technique that we use to manipulate the band gap structure of the graphene. Using these techniques not only allows for transferring of the semimetal graphene to a semiconducting material but also gives the capability to generate and control the concentration of adsorption sites on the surface of graphene layers to attach the biomolecules under investigation. The prepared graphene layers are then used to design GFET-based biosensors to detect biomarkers such as methanethiol.Helicobacter pylori bacteria (H. pylori) [Porphyromonas gingivalis  phylum Bacteroidetes [Methanethiol is volatile organo-sulphur material that is considered as a biomarker for the diseases caused by microorganisms like  pylori) , Porphyrroidetes ,58. To tDensity functional theory (DFT) accompanied by drift-diffusion formalism is used to calculate the physical properties of the semiconducting graphene such as band structure, mobility, and effective density of states. Adsorption energy is also calculated to analyse the surface phenomena on all variants of graphene with or without adsorption of methanethiol. The calculated parameters are used to design and simulate the GFET devices using COMSOL Multiphysics. The dependencies of I-V curves on the electronic properties of the graphene layer as well as the geometrical parameters of the device are considered to evaluate the device’s sensing performance.2/Si) substrate. The SiO2 is an insulating layer, serving as a dielectric with a dielectric constant (ɛr) of 3.99. For the sake of calculations, the boundary conditions at all terminals are considered ohmic.The semiconductor module of COMSOL Multiphysics was used to design and simulate a GFET biosensor. The geometrical configuration of the proposed device is illustrated in I-V measurements were used to determine the performance and characteristics of the device. These measurements were subjected to varying the dimensions of the graphene channel and its surface chemistry , the thickness of the dielectric layer, and the doping concentration of the Si substrate.The graphene layer serves as a channel in the above structure and must be in the semiconducting state. As it was a semimetal material in nature, we needed to manipulate its band structure to transfer it to a semiconductor. Among several methods to induce bandgap in the graphene band structure, we used the following two methods.In the first method, the graphene was doped with both donors and acceptors, making it compensated. Here, although graphene is doped with impurities, the material remains intrinsic since the concentration of the introduced n-type and p-type dopants will be the same.Most common dopants used in graphene are elements from group III for acceptors and from group V for donors (as carbon is in group IV). In this work, the semiconducting properties of graphene are studied for B-N, Al-P, and Ga-As doping.In the second method, the bandgap opening for graphene arises by adsorption of TMs to the graphene surface. The adsorption happens without introducing crystal defects in graphene lattice. Among TMs, we used Pd due to its high stability and catalytic activities ,62,63,642 into the graphene lattice, whereas the Al atom is one electron deficient and acts as a p-type impurity by incorporating one hole per nm2 to the lattice structure.In the proposed structure, the P atom with one extra electron than C atom acts as an n-type impurity by incorporating one electron per nmAfter geometry optimization, it was found that co-doping of graphene with Al-P atoms did not destroy the Clar’s structure but slightly deformed it, as shown in 2. It was found that the Ga-As pair has induced maximum bandgap as compared to other dopants.The same analyses were also performed for B-N and Ga-As dopants. Each dopant atom was linked with three C atoms and forms different bond lengths. The bond lengths along with the induced bandgap are summarized in z orbital of C atom (which is perpendicular to the plane of C atoms) and d orbital of Pd valence band. After optimization, bond length between the Pd and C is 5.44 Å, as depicted in 2. In semiconductor industries, an appropriate concentration of the dopant is usually considered to eliminate the effects of dopant–dopant interaction. In this work, we considered the 1 Pd atom per/ 1 nm2, by which there will be the least interaction between Pd atoms.TMs have high adsorption capabilities compared to other elements . In this3SH), and graphene is determined by their binding energy (EAD) [Characteristics of the interactions between the methanethiol, (CHgy (EAD) . Figure Compensated doped graphene shows a powerful association with the methanethiol through interaction between sulphur (S) and Al atoms. As illustrated in the AD+CP), which correct the errors arising due to overlapping of basis orbitals of the two interacting atoms [Contrary to what was observed for the case of compensated graphene, ng atoms .AD+CP in AD+CP corresponds to more efficient adsorption and consequently higher sensing functionalities toward methanethiol. Therefore, the comparison between the values shows that the graphenes doped with B-N and Ga-As do not have efficient adsorption energy towards the indicated biomarker. As a result, for further analyses, we only considered Al-P-doped graphene and Pd-decorated graphene with adsorption energies of −0.90 eV and −1.22 eV, respectively.The negative values of the Ec or Nv) represents the sum of quantum states disseminated on the entire band in the form of two Dirac delta function defined at the edge of the band [c (Nv) is a function of the carrier mass  and valence band maxima (VBM) converge towards the Fermi level, and they become massless at the Dirac point, which is the same as those of intrinsic graphene. After the adsorption of the biomarker, the bandgap increases, and consequently effective masses increase; as a result, Nc and Nv increase as tabulated in f). Since adsorption of methanethiol decreases Ef, it leads to increment in the work function of methanethiol adsorbed complexes. As is summarized in The effective density of states (Nthe band . Nc (Nv)r mhdos) . medos with relaxation time approximation (RTA) is used to calculate mobility (μ) in graphene structures. μ is directly proportional to the relaxation time of carrier (Ԏ) . AcoustiThe Pd decorated graphene shows n-type behaviour with a bandgap of 0.018 eV. As is illustrated in c and Nv also increase with adsorption. Biomarker adsorption also reduces the EF of the system as presented in F with Φ, Φ of Pd-decorated graphene changes from 4.01 to 4.77 eV after adsorption.Our calculations show that the longitudinal and transverse effective mass of carriers increases as the methanethiol molecule is adsorbed on the graphene. Consequently, N5 as it creates distortion in lattice. Pd atom acts as a linking agent between graphene and analyte and impedes graphene distortion. Therefore, adsorption of methanethiol increases mobility as summarized in Structural distortion increases the phonon scattering in the lattice, which adversely affects the mobility of the material. Decoration of Pd atom on the graphene decreases the mobility to 10COMSOL Multiphysics is used to investigate the DC characteristics of the proposed GFET devices. The software efficiently allows assigning physical properties of materials to model the device. The investigated semiconducting properties of the functionalized graphene in the presence and absence of the biomarker (as summarized in The Al-P doped GFET (AlP-GFET) and Pd decorated GFET (Pd-GFET) performances are characterized by considering the effect of geometrical and physical parameters of the devices.The impact of device parameters variation on the sensitivity of the sensor is discussed in the following sections.18 cm−3 is used as the substrate. While the source is grounded, the drain current (Id) is measured by sweeping the gate voltage (Vg) from 0 to 2 V at a drain voltage (Vd) of 10 mV. I-V characteristics of the devices are shown in n . According to the graphs, the Vn of 0.93 V and 1.09 V were observed for AlP-GFET and Pd-GFET, respectively.A GFET is a three-electrode device, composed of a graphene channel between two electrodes and a gate contact to modulate the electronic response of the channel. In this section, the electrical characteristics of the AlP-GFET and Pd-GFET devices in the absence of biomarkers are evaluated. For these analyses, the channel length  and channel width (W) of the device are considered 2 μm and 1 μm, respectively. A p-type Si with the doping concentration of 10d-Vg curve discussed in This peculiar behaviour of the I-V characteristics of the device is due to the ambipolar transport nature of graphene, which implies the coupled motion of holes and electrons. Therefore, the charge carrier concentration along the graphene channel gives more insight into the Ig is below the value of Vn of the device. At Vn, the concentration of both carriers is equal, and as Vg increases beyond Vn, a channel inversion is observed and the electrons will dominate the carrier concentrations.The density of the carriers for AlP-GFET and Pd-GFET devices versus the gate voltage are shown in d. Therefore, in d in the NDR region corresponds to the decreasing.The conductance of the channel is determined by the abundance of charge carriers, which is influenced by the applied gate voltage. The conductance, in return, determines the Id in the PDR region correspond to the increasing trend of the carrier electron concentration.The trend of carrier hole concentration and the positive slope of Id-Vg curve of AlP-GFET at different drain voltages. It is observed that with an increment of the drain voltage, the I-V curve shifts toward the higher current values. The Vn of 0.93 V remains nearly constant for all Vd values. Id-Vg characteristics of Pd-GFET shown in n is at the voltage of 1.09 V, which is higher than what is observed for AlP-GFET. Moreover, the lower current intensity of Pd-GFET is due to the lower carrier mobilities in this device compared to AlP-GFET, as summarized in d-Vg curves were calculated at Vd of 10 mV for the devices with different channel dimensions (W × L). n for both devices remains constant and is independent of the device geometry. This is one of the positive characteristics of the device that shows the sensing properties of the device will not be affected by the structural device dimensions. However, the device Id is a function of channel length and width, d follows the following equation [To give a more authenticated perception to the device study, Iequation .(1)Id=Wn as we change the doping type and its concentration of the substrate. The I-V characteristics in n moves toward higher voltages for p-type substrates, while it moves toward lower voltages for the n-type substrate case.We also investigated the characteristics of the device with respect to electrical properties of the silicon substrate for both variants of the device. The results show that they have a significant effect on the value of Vd-Vg for the AlP-GFET device, and n remains the same for both cases.To check the sensitivity of the device against biomarkers, the device DC characteristics are typically evaluated in the presence of a biomarker and compared with a reference test in the absence of biomarkers.2 (W × L) and a p-type substrate with doping concentration 1018 cm−3 is considered. Vg is swept from 0 to 2 V, while a constant Vd of 10 mV is applied on the drain. One biomolecule per nm2 was considered for the adsorption concentration of the biomarker on the graphene layer.For this study, a device with channel dimensions of 1 × 2 μmd-Vg characteristics of the AlP-GFET device, and d-Vg curves obtained for AlP-GFET show a clear shift in Vn from 0.93 V to 0.63 V after the adsorption of methanethiol by the channel surface, while for the Pd-GFET, it changed from 1.09 V to 0.42 V. The shift in Vn is attributed to the change of μ, bandgap, Nc or Nv, and Φ of the functionalized graphene once it is exposed to the methanethiol molecule. As summarized in n value. The observed shift in Vn for the Pd-GFET is larger than that of the AlP-GFET, which affirms the higher sensitivity to the biomarker for this device.Id of the device and vice versa.It is observed that the overall current intensity for AlP-GFET decreases after the adsorption of the biomarker. However, for the case of Pd-GFET, the intensity of the current slightly increases after biomarker adsorption. This behaviour of the device corresponds to the effect of adsorption on the carrier mobility of the graphene channel  and Porphyromonas gingivalis  phylum Bacteroidetes. Surface chemistry of the graphene layers is manipulated using two methods: (a) doping the graphene crystals and (b) decorating the surface of the graphene with TMs before using it as the channel of the GFET. The device was designed and characterized using COMSOL Multiphysics. The NDR characteristic of the graphene, which is due to its ambipolar behaviour, was observed using three-terminal measurements. The deep that appeared in the I-V characteristics of the device is used to study the sensitivity of the sensors. The results show that the device characteristic is only sensitive to the doping level of the silicon substrate; otherwise, it is independent of other physical parameters of the device. However, our investigations show that electrical properties of the functionalized graphene layers particularly in the absence and presence of the biomarkers are largely affected the characteristics of the sensor. The device is more sensitive to the adsorbed biomarker in the case of Pd-GFET compared to the devices developed using Al-P doping.In this work, we demonstrated the possibility of using a GFET biosensor for the detection of methanethiol biomarker, which is used to identify diseases caused by microorganisms such as


A fiber-optics tapered sensor that is covered by an electrospinning polyvinyl alcohol (PVA) nanofiber film, is demonstrated to measure humidity and temperature simultaneously. A section multi-mode fiber (MMF) was sandwiched between two leading-in and out single mode fibers (SMFs), which was further tapered down to 29 μm to promote the humidity sensitivity of the sensor. A thin layer of electrospinning PVA nanofiber film was uniformly coated on the MMF taper region by electrospinning technology. In order to promote the humidity sensitivity and mechanical strength of electrospinning nanofibers, the carbon nanotubes (CNTs) were mixed into PVA to formed PVA/CNTs composite nanofiber film. A Fiber Bragg Grating (FBG) was cascaded with the humidity sensing fiber to monitor the ambient temperature simultaneously. The addition of CNTs effectively eliminated the cracks on the electrospinning nanofiber and made it more uniform and smoother. As experimental results show, the humidity sensitivity of the sensor with PVA/CNTs film was 0.0484 dB/%RH, an improvement of 31.16% compared to that of the sensor with PVA film, for which sensitivity is 0.0369 dB/%RH. The nanofiber humidity-sensitive film constructed using electrospinning had a satisfactory humidity response, special 3D structure and extensive application prospect. Humidity monitoring is particularly important in the industrial, agricultural, medical, chemical, and construction fields ,2,3,4. TThe multi-mode interference-based optical fiber sensing structure is highly sensitive to the ambient refractive index change; hence, it is widely developed as a refractometer by probing the cladding mode perturbation ,7. BecauThe tapered optical fiber sensor has high sensitivity, compact structure, wide dynamic response range, and low cost. Therefore, there are many tapered sensors, such as refractive index sensors , biochemThe film-forming methods usually used are vacuum evaporation , ion spuCNTs have attracted great interest owing to their unique structure, mechanical properties, and electrical properties . And it In this work, an optical fiber sensor was designed for measuring temperature and humidity simultaneously, using tapered MMF cascaded FBG. Unlike traditional optical fiber coating methods, electrospinning is used to construct a humidity-sensitive nanofiber film quickly and simply. Experimental tests show that the produced electrospinning nanofiber film sensor is sensitive to temperature and humidity, and so electrospinning nanofiber film has good application prospects in future optical fiber sensors.A schematic diagram of the sensing structure is presented in The field strength of the light wave in the optical fiber is:The incident light field from SMF to MMF can be expressed as:Assuming that the input power of the SMF is From Equation (4), PVA gel solution preparation: 8 g PVA  was added to 100 mL deionized water. A magnetic stirrer was used to stir the solution for 6 h at 50 °C and 2000 r/min until all the PVA powder was completely dissolved. The preparation of PVA/CNTs composite solution: 0.4 g CNTs  were put into 100 mL deionized water, and then oscillated by an ultrasonic oscillator  for 1.5 h, resulting in uniform dispersion of the CNTs in water. Finally, 8 g PVA powder was added into the solution and stirred by a magnetic stirrer with 6 h at 50 °C and 2000 r/min until all the PVA powder was dissolved entirely and formed a uniform PVA/CNTs composite solution.The voltage, injection speed, type of needle tip, collector, collecting distance, and temperature in the electrospinning process will all affect the film-forming effect of the final nanofiber film.Under normal circumstances, a higher voltage results in a greater tip jet’s Coulomb force, and it is easier for the droplets to stretch and extend, resulting in a smaller fiber diameter. However, when the additional voltage is too large, the amount of charge will accumulate rapidly, and the jet will be ejected very fast, which will cause the Taylor cone to be small and unstable, and block the spinning process. As shown in The injection speed determines the supply amount of the available polymer solution. For each established voltage, a corresponding amount of injection is required to ensure the stability of the Taylor cone. Theoretically, when the injection volume increases, the solution volume extended by the needle tip increases, and the fiber diameter increases, as observed in The change in the concentration of the high molecular polymer solution is its viscosity. Changes in viscosity affect the process of electrospinning. It can be observed from The electrospinning machine model used in the experiment was DP30 (Yunfan Instrument). After many experiments, electrospinning was performed under a voltage of 18.5 kV, injection speed of 0.0015 mm/s, 18 G needle tip , collection distance of 14 cm, and temperature of 27 °C. Under these conditions, a better nanofiber film was obtained. A layer of uniform nanofiber film must be made in the tapered area of the optical fiber for humidity sensing. If the optical fiber is fixed on the collector for electrospinning, only the side close to the needle tip will have a nanofiber film, and the other side will have almost no nanofibers. This will affect the performance of the sensor. To solve this problem, we placed a stepper motor on the top of the electrospinning machine, and then fixed the optical fiber sensor on the stepper motor. The stepper motor drove the optical fiber sensor to rotate, and then the electrospinning fiber was able to form a layer of nanofiber film around the cone of the sensor. After the experiments, the speed of the stepper motor was set to 300r/min and the electrospinning time was set to 4 min. Under these conditions, a layer of satisfactory nanofiber film was obtained in the tapered area. The same method and settings were used to make optical fiber sensors based on PVA nanofiber film (as shown in Alaa proved through experiments that after adding CNTs to polyacrylonitrile (PAN), the ultimate elastic modulus and tensile strength of the composite electrospinning nanofibers increased by 84% and 38%, respectively . Dan proOnce the sensor was manufactured, its sensitivity responses to humidity and temperature were tested. The experimental setup consisted of a broadband light source , circulator, optical spectrum analyzer , and constant temperature and humidity chamber . A schematic diagram of the experimental setup is presented in The prepared sensor with the PVA nanofiber film was placed in a constant temperature and humidity chamber. In the process, the temperature and relative humidity of the chamber were set to 50 °C and 30%RH, respectively, and these conditions were maintained for 30 min to ensure a stable temperature and humidity ambience. The humidity range is from 30%RH to 90%RH, and the temperature was recorded at each 10%RH change. The output spectra for when the relative humidity slowly increased and decreased are presented in However, it can be observed from the SEM images of the PVA nanofibers that some of the PVA electrospinning nanofibers had some cracks (observed in After testing the sensor humidity response with the PVA nanofiber film, we further performed the same humidity response test of the sensor with the PVA/CNTs composite nanofiber film to study the effect of CNTs on the humidity sensing. The experimental results are presented in The experimental results indicate that after adding CNTs, the sensor sensitivity improved, and in addition, the mechanical strength of the electrospinning nanofiber on the sensor improved. These changes contributed to the sensor working more sensitively and stably.We implemented temperature experiments to verify whether the sensor could be used to measure temperature. The RH of the chamber was set at 55% RH and maintained for 30 min. The temperature increased from 30 °C to 80 °C, and the output spectra of OSA were recorded every 10 °C. Then, the spectra during the temperature decreasing process went from 80 °C to 30 °C. As observed in Ten days after the sensor test was completed, to demonstrate the performance repeatability and stability of the proposed sensor, we repeated the humidity response test three times at an interval of two days. The humidity response test results are presented in After obtaining the sensor’s humidity and temperature response features, we can get temperature and humidity information by tracing the wavelength and power of Bragg peak. The scanning speed of the spectrometer in high-resolution mode is relatively slow. In practical applications, the optical fiber demodulator with a scanning frequency of several kHz can be used to achieve high-speed real-time measurement.In summary, an optical fiber sensor that can measure temperature and humidity simultaneously using a tapered MMF cascaded with an FBG was designed. Electrospinning was introduced to as a replacement for the traditional method of coating a humidity-sensitive film on optical fiber sensors. When CNTs were added to PVA electrospinning nanofibers, the humidity sensitivity was improved. Moreover, the mechanical strength could be improved. The experimental results indicated that the humidity sensitivity of the designed sensor with PVA/CNTs composite nanofiber film is 0.0483 dB%/RH, which was 31.16% higher than that of the sensor with the PVA nanofiber film. The addition of CNTs effectively eliminated the cracks on the electrospinning nanofibers and made them more uniform and smoother. The temperature sensitivity of the sensor was obtained by monitoring the shift of the center wavelength of the FBG. This nanofiber humidity-sensitive film prepared by electrospinning showed a satisfactory humidity response with a special 3D nanostructure and extensive application prospects.