This paper investigated the effect of electrode materials on the performance of quartz crystal microbalance (QCM) sensors by means of theoretical calculation, experiment, and finite element analysis methods. First, we calculated the particle displacement amplitude and thus obtained the mass sensitivity function distribution of QCMs with gold, silver and aluminum electrodes, and found that the QCM with the gold electrode has the highest mass sensitivity at the center of the electrode. Then, we tested the humidity-sensing performance of QCMs with gold, silver, and aluminum electrodes using graphene oxide (GO) as the sensitive material, and found that the QCM with the gold electrode has higher humidity sensitivity. Finally, we used the finite element analysis software COMSOL Multiphysics to simulate the specific electrode material parameters that affect the sensitivity of the QCMs. The simulation results show that the density and Young’s modulus of the electrode material parameters mainly affect the sensitivity. The results of this paper are instructive for optimizing QCM sensor performance and improving the capability of QCM quantitative analysis. The quartz crystal microbalance (QCM), consisting of a vibrating quartz thin wafer sandwiched between two metal excitation electrodes, is a surface-sensitive analytical tool and a highly sensitive surface interface process analysis tool with nanogram-level sensitivity that can reflect in situ and in real time the mass changes on the surface of quartz wafers ,2,3. QCMIt is noteworthy that researchers nowadays mainly focus on application-oriented studies of QCM, such as the vacuum film thickness monitor ; Noi et ribution . Based oribution ,15,16,17The main electrode materials commonly used in QCM are gold, silver and aluminum, as shown in In this paper, we first analyzed the particle displacement amplitude of QCMs with different electrode materials (densities) to compare their sensitivity. Then, QCM humidity sensors with different electrode materials were fabricated using graphene oxide (GO) as a sensitive material and their performances were compared. Finally, to further clarify exactly which material parameter affects the sensitivity of the QCM, simulation experiments were conducted using the finite element analysis software COMSOL Multiphysics.N is determined by the material constants of quartz crystal. E, U . c is the acoustic wave velocity in quartz crystal. According to previous works, the mass sensitivity of QCM exhibits a Gaussian distribution, which can be calculated by the following formula ,18,19,(equation .(3)r2∂2−3, respectively. Bringing these values into the above equations, we obtained the normalized mass sensitivity functions of the QCMs with gold, silver, and aluminum electrodes, as shown in The thickness and diameter of the wafer and electrodes used were 166 μm and 100 nm and 8.7 and 4 mm, respectively. The densities of gold, silver, and aluminum are 19.32, 10.5 and 2.7 g·cm2, Mg(NO3)2, NaCl, KCl, and K2SO4 solutions at We investigated the effect of different electrode materials on the performance of QCM sensors using a humidity-sensing experiment. In general, a QCM humidity sensor mainly consists of a sensitive material and a QCM transducer . Graphens method . A simplThe frequencies of QCM sensors before and after attaching GO films were recorded in The sensitivity is defined as the ratio of the frequency shift of the QCM sensor to the change in relative humidity, and the sensitivity of QCMs with different electrode materials in the relative humidity range of 11.3–97.3% is shown in Au-QCM > RAg-QCM > RAl-QCM during the adsorption or desorption of water molecules, which shows that all sensors have good stability in the full humidity range. Moreover, the stability of Al-QCM in the high humidity range is slightly higher than that of Ag-QCM and Au-QCM. The response/recovery time of a QCM humidity sensor is defined as the time it takes for the humidity sensor to reach 90% of the total frequency change. As shown in Humidity hysteresis is defined as the ratio of the maximum frequency difference between the desorption and adsorption of water molecules to the frequency shift in the full humidity range. As shown in −3), silver (10.5 g·cm−3), and aluminum (2.7 g·cm−3). As shown in −3. As shown in The finite element analysis (FEM) method has been applied in many scientific computing fields due to its high calculation accuracy and wide application range . In thisIn this paper, we firstly calculated the particle displacement amplitude and thus obtained the mass sensitivity function distribution of QCMs with gold, silver and aluminum electrodes Then, GO was used as the sensitive material to test the humidity-sensing performance of QCMs with gold, silver, and aluminum electrode, and it was found that QCM with gold electrode material has higher sensitivity. Finally, we used the finite element analysis software COMSOL Multiphysics to simulate the specific electrode material parameters that affect the sensitivity of QCM. The simulation results show that the density and Young’s modulus of the electrode material mainly affect the sensitivity. The results have guiding significance for optimizing the performance of QCM-based sensors.


The development of armour systems with higher ballistic resistance and light weight has gained considerable attention as an increasing number of countries are recognising the need to build up advanced self-defence system to deter potential military conflicts and threats. Graphene is a two dimensional one-atom thick nanomaterial which possesses excellent tensile strength (130 GPa) and specific penetration energy (10 times higher than steel). It is also lightweight, tough and stiff and is expected to replace the current aramid fibre-based polymer composites. Currently, insights derived from the study of the nacre  are finding applications on the development of artificial nacre structures using graphene-based materials that can achieve high toughness and energy dissipation. The aim of this review is to discuss the potential of graphene-based nanomaterials with regard to the penetration energy, toughness and ballistic limit for personal body armour applications. This review addresses the cutting-edge research in the ballistic performance of graphene-based materials through theoretical, experimentation as well as simulations. The influence of fabrication techniques and interfacial interactions of graphene-based bioinspired polymer composites for ballistic application are also discussed. This review also covers the artificial nacre which is shown to exhibit superior mechanical and toughness behaviours. Ballistic impact produces shock waves which may induce severe trauma injuries to the soldiers. Aramid fibre-based soft and hard armours can absorb the impact energy of a projectile efficiently . The curWetzel et al. found that graphene could improve the ballistic resistance of the body armour with light weight  . MoreoveThis review will focus on the cutting-edge research on the ballistic performance of graphene-based materials through theoretical, experimentation as well as numerical simulations. In addition, the effect of fabrication techniques and interfacial interactions of graphene-based nacre-inspired polymer composites for ballistic application have been discussed in detail.7/s. It has been observed that MLG possesses higher specific penetration energy (10 times higher than Steel at 600 m/s). This is mainly attributed to formation of cone waves and rapid propagation in the radial direction in the graphene layers. The penetration process is illustrated in i) impacts the strike face area (As) of multilayer graphene (MLG). An elastic wave propagates radially at CII followed by a conic deformation with radial speed Vc (Stage ii). Three to six cracks are initiated at the centre of As and propagates in radially outward direction resulting in the formation of the same number of petals (Stage iii). Moreover, the transferred momentum to MLG induces creasing and folding of each triangular-shaped petal while the elastic extension of the membrane is rapidly relaxed along the radial direction (Stage iv). Moreover, MLG dissipates the kinetic energy away from the impact zone. It has been suggested that the crack propagation in the polymeric composites can be prevented by incorporating multilayer graphene. Moreover, bio-inspired fabrication techniques enhance the toughness [Currently, graphene-based materials are replacing the existing aramid fibre-based body armour. Multilayer graphene (MLG) is an exceptional anisotropic material due to its layered arrangement composed of two-dimensional carbon lattices. Lee et al.  tested toughness .Kichul et al. have simulated the ballistic testing using silica and nickel projectiles over the graphene at supersonic initial velocity . They haZhaoxu et al. simulated the impact testing over a graphene plate using molecular dynamic simulation. It has been found that cylindrical projectiles penetrate the graphene plate at a lower velocity compared to spherical projectiles. Spalling like failure was observed in which the bottom section undergoes a wave superposition induced failure. Moreover, they have proposed a relationship to analyse the resisting pressure of graphitic plate during ballistic impact .Wetzel et al. theoretically predicted the ballistic properties of graphene. An interesting behaviour of graphene is that it is a planar 2D isotropic material with a capability to assemble in a perfect manner . This extraordinary behaviour has encouraged engineers to fabricate the composite structures like nacre. Nacre is natural armour system used by the seashell to protect themselves from the external environment and it gives a physical protection . NaturalWenjie et al. took inspiration from the natural nacre structure and they have proposed a molecular scale design with multilayer graphene/PMMA (poly methyl methacrylate) composites. They have performed a coarse-grained molecular dynamic to evaluate the interfacial failure mechanisms through pull-out simulations. From the simulation results they have concluded that the toughness and energy dissipation is significantly affected by the pull out at the graphene/PMMA interface and the yielding at the graphene layers. Beyond the critical point the yielding mode of failure turned into pull out failure. This modelling technique provides a platform to design the graphene-based polymer composites with optimum mechanical properties and toughness .Liu et al. carried out a coarse grained molecular dynamic simulation to study the mechanical and energy absorption of multilayer graphene/polyethylene composites under spall loading condition. The energy absorption capability of the model increases with an increase of overlapping distance of graphene layers. Polymer matrix act as a protective shield to graphene during impact. From Masta et al.  studied Dikin et al. fabricated a graphene oxide paper using flow directed assembly of graphene oxide nano sheets. Interlocking feature of graphene oxide nano sheets provides an excellent macroscopic stiffness and flexibility. The strength and modulus of the graphene oxide paper is 133 MPa and 38 GPa respectively .Putz et al. fabricated a layer by layer homogeneous and highly ordered graphene oxide/polyvinyl alcohol composites with 50% graphene oxide content through vacuum assisted self-assembly technique. Compared to pure polymer nacre like nano composites film exhibited higher modulus . Tan et Naturally available nacre had an extraordinary strength and toughness due to its hierarchical arrangement of micro and nanostructures. This structure inspired the researchers to make high performance artificial composites using the same nacre design model. 2O3 act as a brick and GO/PVA act as a mortar. The authors reported that even though artificial nacre composite structure possesses excellent strength, it exhibited moderate toughness. When the polymers are confined in between the graphene oxide nano platelets the structure will have superior properties, but it will lose its flexibility and ductile nature. Moreover, alumina microplatelets enhance the strength of the structure and it holds the ability of polymer matrix to deform and promotes the crack deflection. Artificial nacre structure showed an extraordinary strength and toughness (143 ± 13 MPa and 9.2 ± 2.7 MJ/m3), compared to natural nacre structures (80−135 MPa and 1.8 MJ/m3) [Wang et al. developed artificial nacre through layer by layer technique. In this artificial nacre Al8 MJ/m3) .Bertolazzi et al. developed an artificial nacre using MoS2/rGO/TPU. The breaking tensile strength and modulus of MoS2 is extremely higher (23 GPa and 270 GPa) for one monolayer and it has 2D nano sheet structure. This artificial nacre has been made through vacuum-assisted filtration self-assembly method. From the results it is understood that the tensile strength is 1.7 times greater than the natural nacre whereas the toughness is 3.8 times higher than the real nacre .Gong et al.  developeNacre exhibits excellent mechanical toughness due to the hierarchical micro/nano structure and better interfacial interactions ,44. ThisDecher et al. proposed the layer-by-layer fabrication technique for multilayer films based on electrostatic attraction mechanism. This could be achieved by alternative deposition of polyelectrolytes with opposite charges ,52.The pCompared to layer-by-layer fabrication technique, evaporation-based fabrication technique is a very simple procedure to produce bio-inspired nanocomposites. The nano sheets in the solution could form a perfectly aligned low energy structure after evaporation of solvent. Cui et al. fabricated the bio inspired graphene oxide/dopolyamine (DA) nanocomposites through evaporation technique as shown in Filtration is also a simple and efficient method to fabricate bio-inspired nanocomposites ,56. The Generally, sea water contains impurities, dust particles, micro-organisms etc. However, in ice the impurities were expelled into the interstices of the ice ,58. BaseHydrogel casting is a techno economical approach to produce bio-inspired composites. This technique is widely used to fabricate graphene-based bio-inspired polymer nanocomposites ,62. Due This technique has attracted the researchers because of its enormous advantages than other approaches. The cost of fabrication of artificial nacre through this approach is cheaper. Further it is the fastest fabrication technique among the artificial nacre fabrication techniques. Precise control of the hierarchical structure could be achieved using this approach. However, currently, researchers are using this technique for preparing thin bio-inspired polymer nano composites with a well laminated hierarchical structure . The eleGraphene aerogel is one of the emerging 3D graphene material which is used to fabricate polymer composites. Wang et al.  developeThe dispersed graphene oxide and hydroiodic acid were mixed in a magnetic stirrer for several minutes. The final mixture was then kept in an autoclave for 24 h at 120°. The mixture (GH) was cooled at room temperature and cleaned using distilled water to remove the impurities completely. The obtained GH was kept at −30° (for 12 h) and freeze-dried at −80° (for 48 h) in a freeze drier to produce graphene aerogel. Eventually the graphene aerogel/epoxy matrix composites were prepared through vacuum assisted infiltration method. They have concluded that graphene aerogel drastically improves the mechanical strength, energy dissipation and fracture toughness of epoxy composites. Moreover, graphene aerogel enhances the crack propagation resistance of the GA/epoxy composites .The material response to mechanical loads and the energy absorption characteristics of the bio-inspired nanocomposites not only rely on the inherent characteristics of the constituents but also depends on the sequence of assembling building blocks and the interfacial adhesion . Even thThe interfacial interaction is inevitable for achieving superior properties of the bio inspired polymer composites. Non-covalent bonding between the building blocks of artificial nacre can enhance the mechanical properties and energy absorption while the covalent bonds could improve the strength, toughness, strain resistance and fatigue strength of the structure. In the following section, different types of non-covalent bonding will be discussed in detail.Hydrogen bonding is quite common at the intermolecular or intra-molecular level . Even th2+ and Ca2+ at less than 1 wt.%. They found that the metal ion greatly enhances the mechanical performance of GO film by forming ionic bond with the GO nano sheets in the proximityAdditionally, they found that the GO-Mg2+ possess higher mechanical performance than GO-Ca2+ because of lower ionic radius of Mg2+ than Ca2+ [Addition of a small quantity of the metal ion into the biomaterial enhances the mechanical properties by forming ionic bonds with protein structure of the biomaterial. Abundantly available oxygen functional groups in the graphene oxide (GO) nanosheets are favourable to improve the coordination with metal ions. Park et al. prepared the GO-based films with Mghan Ca2+ .3 respectively [Strong π–π interaction in the graphene nano sheets improves the stability of the structure. Zhang et al. found that addition of less than 1 wt.% PAPBx with GO nano sheets produces hydrogel which enhances the π-π interaction with GO nano sheets as confirmed from the spectra pattern in the adsorption and fluorescence spectra analysis . The tenectively .Even though the non-covalent bonding could improve the mechanical properties drastically, it is inactive in salt solutions . CovalenLinear molecule in the polymer can form a strong covalent bonding network with the GO nano sheets leading to a nanocomposite film with superior mechanical properties. Among the various linear molecules, borate and GA were commonly employed to improve the mechanical properties of GO films. Both the tensile strength and storage modulus increased by 25% and 266% with the addition of 0.94 wt.% of borate in the GO film . Gao et Multiple functional groups in the branched polymer compared to linear molecule helps in increased crosslinking between the polymer and GO such that significant rise in the mechanical properties can be achieved. The commonly available branched polymer to prepare artificial nacre is hyper branched polyglycerol (HPG). GO-HPG nanocomposite had the tensile strength of 642 MPa which is higher than pure GO film (555 MPa) . It mustThermosetting polymers like epoxy have reactive functional groups that can be grafted on the surface of the building blocks of an artificial nacre and crosslinked with adjacent blocks to form a 3D network structure. Ming et al. fabricated the graphene foam (GF)/epoxy nano composites . GF obtaThus, it is clear that mechanical properties of the bio inspired nano composite structures can be augmented with the use of polymers which can form the covalent bonding mechanisms as discussed above. However, precise control of the interfacial interaction to achieve optimum performance under various mechanical loads is still a challenging task.3 respectively. This could be achieved via cross linking of graphene nano sheets through π-π interactions by using a pyrene group conjugate molecule on both ends.Shahzadi et al.  have fabUniform dispersion of nano filler into the matrix were achieved using techniques such as surface grafting and coupling reaction, polymer wrapping and surfactant adsorption . SurfaceDue to increase in demand for flexible, light weight and robust body armour it is essential to find an alternative for the current aramid fibre-based protection system. Graphene is one of the strongest enormous energy absorbers, lightweight, tough and stiffest material which can replace the current aramid fibre-based material. Further the extraordinary self-aligning behaviour of graphene encouraged the material scientist to fabricate the composite structures like nacre. This behaviour could overcome the drawbacks of conventional fabrication technique. The most common problem while fabricating the nanocomposites is the non-uniform dispersion of nano particles in the matrix. Uniform dispersion could be achieved through surface grafting and coupling reaction, polymer wrapping and surfactant adsorption. Nacre inspired graphene-based system required carefully arranged hierarchical multi-layered structures to achieve excellent stiffness, strength, toughness, energy absorption, impact resistance and light weight, which has to be considered while designing high performance armour system . Overall


Graphene deposition was conducted at low pressures (35 Torr) with a mixture of methane/hydrogen and a substrate temperature of 970 °C followed by spontaneous cooling to room temperature. A thin copper-strip was deposited in the middle of the SiO2/Si substrate as catalytic material. Raman spectroscopy mapping and atomic force microscopy measurements indicate the growth of few-layers of graphene over the entire SiO2/Si substrate, far beyond the thin copper-strip, while X-ray photoelectron spectroscopy and energy-dispersive X-ray spectroscopy showed negligible amounts of copper next to the initially deposited strip. The scale of the graphene nanocrystal was estimated by Raman spectroscopy and scanning electron microscopy.We report the first direct synthesis of graphene on SiO This table summarizes these methodologies under two classifications: Catalyst-free and metal catalyzed direct growth CVD, where both regular and plasma enhanced CVD (PECVD) are used [Since graphene was first obtained by microexfoliation of graphite in 2004  it has bd others . To dateare used .2 at low temperatures (400 °C) by using the electron cyclotron resonance CVD (ECR-CVD) method [In the first methodology , the majority of the graphene growth experiments on non-metallic substrates are conducted at high temperatures (1060–1100 °C) over a long deposition time . Liu et ) method .2/Si wafers as a catalyst, which was subsequently delaminated using adhesive tape, leaving behind the graphene layer on the substrate [2/Si substrate to synthesize graphene using a CVD tube furnace [3 solution [2/Si) to promote graphene growth [2/Si [In the metal-catalyzed direct growth method, many experiments have used a sacrificial metal layer to stimulate graphene growth. McNerny et al. deposited a nickel layer on SiOubstrate . They obubstrate . Dong et furnace . They cosolution . Similare growth . They foe growth . Kato etth [2/Si . They deth [2/Si .2/Si substrates by HFCVD. This technique allows the deposition of graphene over the entire substrate by using the metal-catalyzed method in a limited manner. A thin copper-strip was deposited on the middle of the SiO2/Si substrate allowing the methane dehydrogenation and the carbon absorption to occur and leaving the rest of the surface free of metal. Structural, morphological, and compositional analyses were made on the graphene grown on the SiO2/Si in areas on top of and next to the copper strip. This research targets SiO2/Si substrates due to their ubiquity in graphene applications, such as photodetectors, gas sensors, solar energy, and others [This paper reports a novel method suitable for industrial scale-up production to directly grow high-quality graphene on SiOd others . In addid others .2/Si wafers with a top oxide layer of 285 nm and a thickness of 500 ± 25 µm manufactured by Graphene Supermarket . These wafers were cut into 2 × 2 cm pieces and cleaned with: deionized water, trichlorethylene, acetone (histology grade), and isopropanol (histology grade); the last three reagents were obtained from Fisher Scientific . A mixture of sulfuric acid (H2SO4 purity range of 95–98%) and hydrogen peroxide (H2O2 solution at 30% w/w in H2O), both provided by Sigma Aldrich , was prepared for a further cleaning of the substrate. A thin copper-strip (3 mm width) was deposited in the middle of the SiO2/Si substrate by sputtering  with a deposition time of 1 minute  was used for the graphene deposition. The reactor consists of a heated substrate holder that is positioned below three heated filaments of rhenium. The gases enter the chamber from the top with a shower-like turbulent flow, (cf. 2/Si substrates (4 cm2) with the thin copper-strip (0.3 cm × 2.0 cm) were submitted to the graphene synthesis procedure at different growth parameters. The substrate was placed in the HFCVD as shown in A commercial HFCVD instrument  and hydrogen (10–50 sccm) for 30 to 120 min. Finally, the samples were cooled by spontaneous convection to room temperature. As a control study, SiO−1 with a spot size of 0.7 μm. In addition, Raman mappings were taken over an area of 150 × 100 μm2 and a step size of 2 μm; the collecting time for each point in the Raman mappings was 20 s. A morphological study of the synthesized graphene was done using a scanning electron microscope, SEM  at different magnifications  and an atomic force microscope, AFM  in tapping mode over an area of 3 × 3 µm. Compositional analyses of the graphene samples were done by energy-dispersive X-ray spectroscopy, EDS (JEOL JSM 6480LV) and X-ray photoelectron spectroscopy, XPS  over an energy range of 0 to 1200 eV.The structural characterization of graphene was conducted by Raman spectroscopy  equipped with an excitation laser operating at 532 nm. The spectra were collected over a frequency range of 1100 to 3100 cm2/Si substrate.A structural (Raman), morphological (SEM and AFM) and compositional (EDS and XPS) analysis was done on the synthesized graphene, both on top of and next to the copper- strip deposited in the SiO2 carbon atoms, the 2D peak appears in response to a two-phonon vibrational process and the D peak is activated by the edges or defects in graphene [2/Si substrate. For the control samples without a copper strip, these graphene peaks were not observed, indicating that the copper metal is necessary for the growth of graphene under our experimental conditions. 2/Si substrate, respectively. The red and green spectra show two different signals next to the copper strip  yields an estimate of the graphene grain size [D/G values, 0.45 ± 0.07 and 0.87 ± 0.03, were found on top of the metal strip. Although, we had a significant observed D peak, the average of the full width at half maximum (FWHM) of the D, G and 2D peaks indicates good quality crystallites [−1, 25 ± 1 cm−1, and 56 ± 3 cm−1, respectively and in areas next to the copper strip were: 38 ± 2 cm−1, 29 ± 1 cm−1 and 52 ± 2 cm−1.The average intensity ratio between the D and G peaks  measured by SEM (vide infra):To calculate the crystal size from the Raman data, we employ the Cancado equation (Equation (1)) , where LD represents the inter-defect distance, EL is the excitation energy and the defect concentration corresponds to 1/D in areas next to and on top of copper strip were 18 nm and 10 nm, respectively. We also estimate the defect concentration for both areas, next to and on top of copper strip with values of 3 × 10−3/nm 2 and 7 × 10−3/nm 2, respectively. These results confirm that some point defects are present in the nanocrystals and contribute to the ID/IG ratio intensity. In addition, we corroborate that higher concentration of defective crystals are present on top of the copper strip versus next to this metal film:The difference in the particle size estimates is likely due to the multiple phonon dispersion produced by defects inside of the graphene crystallites ,43. Thesto 1/LD2 . Our resThe G and 2D peaks characteristically correspond to the signal for graphitic materials , where t2/Si substrate and to estimate the number of graphene layers through the intensity ratio of the 2D/G peaks [2. In Raman mapping cf.  was done/G peaks ,39. In Fks 2. In ,32,35. Hks 2. In .From the SEM images, it was possible to estimate the size of the graphene crystals from the scale bar to ca.100 nm. By measuring many crystals, we obtained an average size of 120 nm and a range of 100 to 140 nm for particles next to the copper strip, and smaller particles  on top of the copper-strip. At lower magnification (5000×), no copper particles were observed next to the copper film.2/Si substrate for both next to  were observed on top of the copper-strip (3/2: 706.7–710.9 eV), Co (Co 2p3/2: 778.1–780.2 eV) and Ni (Ni 2p3/2: 852.5–854.4 eV) were not observed on areas next to and on top of the copper-strip. The absence of other metals demonstrates that the graphene growth was either catalyst free or catalyzed by copper [XPS measurements were taken both next to and on top of the copper-strip. er-strip f, as exper-strip c. Signaly copper . ; however, defects in the crystal due to phonon scattering may lead to an error in this estimate. These defects inside of the graphene nanocrystal were corroborated by the calculation of the inter-distance defect (Equation (2)).The structural (Raman), morphological (SEM and AFM) and compositional (EDS and XPS) characteristics of the graphene on SiOThe real size was confirmed through the images taken by the SEM technique where the particle size was in a range of 35 to 140 nm with an average of 120 nm (next to the copper-strip). The growth mechanism most likely begins with dehydrogenation of methane by the hot filament . In the 2/Si by HFCVD, avoiding a complex graphene transfer process. In this method, a thin copper-strip of 0.3 cm × 2.0 cm was deposited in the middle of a 4 cm2 substrate, leaving most of the substrate surface free of this metal. The structural analysis was done by Raman spectra to verify the graphene growth characteristics. SEM and AFM images allowed us to determine the graphene’s topography on the SiO2/Si substrate. Additionally, copper residues were observed on top of the copper-strip areas, but these were not present in areas next to the metal. A compositional study was made through EDS and XPS measurements, indicating the presence of carbon in all samples and the virtual absence of copper in areas next to the metal-strip. This work demonstrates that the thin copper-strip deposited on the middle of the SiO2/Si enables the graphene growth over all the substrate. By eliminating the need for a mechanical transfer step in the device fabrication process, this accomplishment opens up the possibility of integrating graphene with currently available silicon device technologies. Further research, needed to continuously improve the quality of the graphene deposition, is ongoing in our laboratories. One approach is the reduction of the nucleation density [This study demonstrates, for the first time, a method to deposit polycrystalline graphene directly onto SiO density ,54,55,562/Si by HFCVD, using the metal catalyzed method in a limited manner. The crystal size, structure, and inter-defect distance of the nanocrystalline graphene were estimated by SEM, AFM, and Raman measurements, respectively. EDS and XPS analyses confirmed the presence of graphene on SiO2/Si with negligible amount of copper in the area next to the copper strip. Our study allows the possibility of growing graphene directly on dielectrics without a transfer process and the opportunity to produce it on an industrial scale.This work presents an approach to directly grow graphene on SiO


Moreover, ID/IG increased from 0.87 to 0.92, indicating that the defect density decreased because of desorbing oxygen functional groups after ageing. When the temperature exceeded 60°C, CO2 produced by decomposing graphene oxide was detected. The thermal decomposition changed after ageing. The decomposition peak temperature decreased from 216°C to 195°C. The CO2 amount produced remained almost unchanged; however, the amount of CO, SO2 and H2O decreased. After ageing, the apparent activation energy of graphene oxide decreased from 150 to 134 kJ mol−1.After long-term ageing, the structure of graphene oxide prepared by the modified Hummers method changed. Because of the desorption of oxygen-containing functional groups, the C/O ratio of graphene oxide increased from 1.96 to 2.76. However, the average interlayer distance decreased from 0.660 to 0.567 nm. The content of -CH- and -CH Currently, researchers believe that oxygen-containing groups of graphene oxide are primarily the hydroxyl, carboxyl and epoxy groups . Further2 g−1) [Graphene oxide is a high-energy, thermally unstable material prone to the disproportionation reaction even under mild heating conditions; it emits a considerable amount of heat during the thermal decomposition process . Because2 g−1) , which a2 g−1) ,7. FurthIn recent years, there have been many studies using graphene oxide to prepare energetic materials and composite energetic materials –12. Usuaet al. examined the swelling phenomenon of graphene oxide films prepared using the Hummers method after ageing in air, water and different alcohols [et al. reported that ageing does not significantly affect the decomposition enthalpy of graphene oxide, but slightly reduces the initial decomposition temperature [et al. [et al. [Many studies have been conducted on the ageing properties of graphene oxide. Iakunkov alcohols . Furtherperature . Holt et [et al.  examined [et al.  examined [et al.  used firAlthough long-term ageing is a tedious method, it can better approximate the actual use of graphene oxide. However, studies on the effects of long-term ageing on the structure and thermal decomposition of graphene oxide have not been reported.. 2. 2.1Natural flake graphite, potassium permanganate, concentrated sulfuric acid, phosphoric acid, 5% hydrochloric acid and barium chloride were used.. 2.2The preparation of graphene oxide can be roughly divided into the following three processes: intercalation, oxidation and exfoliation. Common preparation methods of graphene oxide are the Brodie method, Staudenmaier method, Hoffman method, Tour method and Hummers method . Because2SO4 and 12 ml of H3PO4 were mixed and placed in a water bath at 25°C. Then, 5 g of flake graphite was added to the mixture and stirred for 30 min. Subsequently, 30 g of KMnO4 was added slowly to the mixture and stirring continued for 12 h until the solution turned dark green. Then, 18 ml of H2O2 was slowly added to the mixture to remove excess KMnO4, and the solution was stirred for 30 min until it cooled. After the mixture was suction filtered, a large amount of deionized water and HCl were added for washing. The suction filtration and washing step were repeated several times until the sulfate ions could not be detected after adding BaCl2. Then, the filter cake was added to 250 ml of deionized water under ultrasonic stirring for 4 h. During the ultrasonic dispersion process, biological ice packs are required to be continuously replaced to avoid excessive temperature. The beaker was taken out and freeze-dried for 24 h to obtain graphene oxide.First, 108 ml of concentrated H. 2.3The graphene oxide prepared above was stored in a constant temperature and humidity box for 2 years and then removed for characterization. The humidity box was purchased from MS SHIMEI Electric . The temperature of the constant temperature and humidity box was set to 25°C, and the humidity was maintained in the range of 20–70%.In this study, GO refers to newly prepared graphene oxide, while GO-a refers to graphene oxide aged for 2 years.. 2.4λ = 1.5438 Å). Samples were scanned from 5° to 60° (2θ) with a step size of 0.02° and scanning speed of 5° min−1. The Fourier transform infrared (FTIR) spectrum was obtained using a Bruker TENSOR II FTIR spectrometer . The samples were prepared by the KBr tablet method, and the mass ratio of graphene oxide to KBr was 1 : 100. The defect density of graphene oxide was characterized using a HORIBA Jobin Yvon LabRAM HR Evolution laser confocal Raman spectrometer with a laser wavelength of 532 nm and a 50× objective lens. The layer thickness of graphene oxide was characterized using a Bruker NanoManVS type atomic force microscope (AFM). The graphene oxide aqueous solution with a concentration of 0.01 mg ml−1 was ultrasonically dispersed for 20 min, and then dropped on a mica sheet and dried at room temperature. The probe was then operated in tapping mode. Elemental analysis was performed on an X-ray photoelectron spectrometer (XPS) with an Al Ka anode . The components of the gaseous products were detected by STA 449F3 thermal analysis combined with an infrared and mass spectroscopy system  at a heating rate of 20°C min−1 from 50°C to 900°C in Ar. The flow rate of argon was 50 ml min−1. The infrared spectrum scanning range was from 4000 to 650 cm–1, and the gas pool temperature was 200°C. The heat of decomposition of graphene oxide was measured by a Netzsch STA 449 TG–DSC synchronous thermal analyser where the carrier gas was N2 with a flow rate of 50 ml min−1. The heating range was from room temperature to 320°C, and the heating rate was 5, 10, 15 and 20°C min−1.X-ray diffraction (XRD) was performed on a Rigaku Ultima IV X-ray diffractometer operated at 44 kV and 44 mA using copper X-ray radiation  plane close to 9.68°, while GO-a had a diffraction peak of the (002) plane close to 11.02°. This result indicates that the adsorbed water and part of the oxygen-containing groups desorbed during the ageing process, which reduced the layer spacing. After ageing, the full width at half maximum (FWHM) of the diffraction peak of the (002) plane of graphene oxide increased from 0.53527° to 0.91882°. The Debye–Scherrer formula was used to calculate the lattice size of graphene oxide. After ageing, the lattice size of graphene oxide decreased from 14.48 to 7.11 nm. Furthermore, GO had weak diffraction peaks close to 19.70° and 42.20°, corresponding to the (002) crystal planes of oxygen partly desorbed graphene oxide and the (100) crystal planes of graphite, respectively [As shown in figure 1ectively . The difa shows the FWHM of peaks close to 20°. After ageing, the lattice size of partly reduced graphene oxide decreased from 12.16 to 1.47 nm. The increase in peak intensity close to 21.04° shows that additional oxygen-containing groups desorbed from GO-a. Graphene oxide heated at 200°C had a strong peak at approximately 20° [Figure 1tely 20° . After ately 20° .aL is the average grain size perpendicular to the crystal plane, λ is the X-ray wavelength, β is the FWHM of the diffraction peak and θ is the diffraction angle.The Debye–Scherer formula  is listed is the interplanar spacing, θ is the incident angle, n is the diffraction order and λ is the X-ray wavelength.The Bragg equation  is as beb shows the mid-infrared spectrum of graphene oxide. For the as-prepared graphene oxide, the infrared absorption peaks close to 3423 and 1400 cm–1 are the stretching and bending vibration peaks of OH, respectively [–1 are attributed to the stretching vibration peaks of the carbonyl group (C=O), the aromatic ring skeleton vibration peak, and the stretching vibration peaks of the epoxy and C–O bonds, respectively [–1 correspond to the C–H stretching vibration of the CH2 group [–1 corresponds to the antisymmetric stretching vibration of CH3 [3 and CH2 in the infrared spectrum of GO-a are not obvious. This result shows that CH3 and CH2 were degraded during the ageing process. In the infrared spectrum of GO-a, the absorption peaks at 3393, 1393, 1725, 1586, 1224 and 1053 cm–1 correspond to the stretching vibration mode of OH, the bending vibration mode of OH, the stretching vibration mode of the carbonyl group (C=O), the stretching vibration mode of aromatic C=C bonds, the stretching vibration mode of epoxy and the C–O bond, respectively. These results show that the type of oxygen-containing functional groups in graphene oxide did not change after ageing. Because of the desorption of surface water, the infrared vibration peak caused by OH bending vibration and aromatic C=C bonds close to 1622 cm–1 was red-shifted to 1585 cm–1.Figure 1ectively . The infectively . The infH2 group ,28,29, an of CH3 . Comparec shows the Raman spectrum of graphene oxide. The D band (1349 cm–1) of graphene oxide is the respiration mode of A1g symmetric k-point phonons, originating in the graphite region with a small domain size, which is believed to reflect the local defects and disorder of the crystal lattice, particularly the defects and disorder at the edges of the graphite sheet. The G band (1597 cm–1) is usually attributed to the first-order E2g phonon plane vibration of sp2 hybridized carbon atoms, which corresponds to the plane stretching of the graphite lattice [ID/IG ratio, the greater the defect density of graphene oxide; however, as per studies by Cancado et al. [et al. [ID/IG value of graphene oxide increased from 0.87 to 0.92. When the average defect distance LD is less than 4 nm, materials with additional defects have a smaller value of ID/IG. During the ageing progress, the formation of CO2 created vacancy defects on the basal plane of graphene oxide; however, the reduction in the number of oxygen-containing functional groups was considerably greater than the formation of vacancy defects, which makes the average defect distance (LD) of GO-a; i.e. the defect density decreased.Figure 1 lattice . Many reo et al.  and Lucc [et al. , this via,c shows the morphology of GO and GO-a, respectively. Graphene oxide had an irregular flake structure; after ageing, the size of graphene oxide decreased. The research results of Acik et al. demonstrated that the epoxy groups on graphene relax carbon bonds when they are arranged during the oxidation process. Ether groups are generated when the epoxy groups decompose, leading to the unzipping of graphene oxide [Figure 2b,d shows the thickness curves of GO and GO-a, respectively. Previous studies reported that the thickness of single-layer graphene oxide ranges from 0.5 to 1.2 nm. Therefore, the average thickness of GO (1.320 nm) and GO-a (1.134 nm) in figure 2b,d may belong to two-layer graphene oxide; i.e. the thickness of single-layer GO was 0.660 nm, which decreased to 0.567 nm of GO-a after ageing. The decrease in sheet thickness can be attributed to the desorption of oxygen functional groups.Figure 2α anode. The corrected binding energy of C 1s was 284.6 eV. Figure 3a shows the survey XPS spectra of graphene oxide. The intensity of the O 1s peak of GO-a was significantly lower than that of GO. After ageing, the C/O ratio of graphene oxide increased from 1.96 to 2.67; the results revealed that graphene oxide lost part of its oxygen-containing groups at 25°C and humidity of not greater than 70%. These results correspond to the XRD test.The surface elements of graphene oxide were characterized by a ULVAC PHI Quantera II XPS with an Al Kb shows a magnified view of the box in figure 3a. The peaks close to 231 and 168 eV are attributed to the 2s and 2p peaks of sulfur, respectively. Figure 3c,d present the C 1s and O 1s spectra of graphene oxide after deconvolution, respectively. After deconvolution of the C 1s spectrum of graphene oxide, there are five peaks close to 284.5 ± 0.1, 285.4 ± 0.2, 286.5 ± 0.3, 287.6 ± 0.2 and 288.9 ± 0.3 eV, corresponding to the sp2 hybrid carbon atom , sp3 hybrid carbon atom , hydroxyl/epoxy/ether , carbonyl/quinone  and carboxyl group/ester/anhydride  [Figure 3 purple) , respect2 carbon atoms significantly increased, while the relative content of C–O significantly decreased. This indicates that a large amount of oxygen-containing functional groups is desorbed to increase the relative content of aromatic domains. This result agrees with that observed in the XRD and Raman spectra. The relative content of sp3 carbon atoms decreased from 12.11 to 8.29%, indicating that the content of aliphatic carbocyclic structures decreased, which is consistent with the weakening of the corresponding CH2 spectral intensity in the FTIR spectra. After ageing, the relative content of C=O decreased from 6.48 to 3.73%, and the relative content of O=C–O increased from 3.80 to 5.48%. The relative area of the sub-peak of the O 1s peak of GO-a and the absolute content of all oxygen-containing functional groups decreased.After ageing, the C 1s spectrum of graphene oxide significantly changed and the peak area of the O 1s spectrum was significantly reduced. The content ratio of each group can be estimated as per the area of the secondary peak . Table 1et al. [2. Another study by Zhou & Bongiorno revealed that the reaction of C–H with epoxide and hydroxyl occurs easily. They argued that these reactions may be attributed to the metastable properties of multilayer extended graphene oxide. This conclusion agrees with the lack of a C–H absorption peak in the infrared spectrum of GO-a [Zhou & Bongiorno  demonstret al.  demonstr of GO-a .−1, as illustrated in figure 4a. The thermal decomposition of graphene oxide was a disproportionation reaction. During the thermal decomposition process, a part of C atoms was oxidized to escape in the form of CO2 or CO, while another part of C atoms was reduced. Calculating the second derivative of the TG curve to identify the corresponding inflection points of the curve could be used to roughly divide the decomposition stages of the sample. The thermal decomposition process of GO after preparation could be divided into four stages. The first stage was from 50°C to 112°C, the mass loss in this stage was approximately 5.92%, which was primarily attributed to the volatilization of adsorbed water. The second stage was from 112°C to 215°C. The weight loss in this stage was approximately 67.52%, which was mainly due to the desorption of oxygen-containing groups. The third stage was from 215°C to 522°C, and the weight in this stage first increased by approximately 1.93% (to approx. 323°C) and then decreased by approximately 3.72%. This may have been attributed to the adsorption of free radicals during the decomposition process and subsequent depth decomposition of intermediate products of graphene oxide. The fourth stage was from 522°C to 900°C. The weight in this stage first increased by approximately 2.76% (to 532°C) and then decreased by approximately 1.26%. This may reflect the process of adsorption and desorption of trace O2 in the protective gas.Thermogravimetric (TG) curve of graphene oxide was obtained at a heating rate of 20°C min−1. The third stage is from 195°C to 365°C, and the weight loss was approximately 1.50%. The fourth stage was from 365°C to 900°C, in which the weight first increased by 0.45% (to approx. 377°C) and then decreased by 8.74%, which may be related to the free decomposition process. The adsorption of radicals and the decomposition of carbon atoms caused by the reaction with trace oxygen in the carrier gas under high-temperature conditions were related. Zhang et al. [The thermal decomposition process of GO-a was similar to that of GO and could be roughly divided into four stages. The first stage was from 50°C to 147°C, and the weight loss was approximately 11.39%, primarily because of the volatilization of adsorbed water and the desorption of oxygen-containing functional groups. The second stage was from 147°C to 195°C, and the weight loss was approximately 50.82%. In this stage, the GO-a was violently decomposed to produce a large amount of gas, which blew away certain samples from the crucible. This occurred in the TG test of GO at a heating rate of 20°C ming et al.  reportedb shows the relationship between gas generated during the thermal decomposition of graphene oxide and temperature. After ageing, the infrared signal of gas released by the thermal decomposition of graphene oxide was significantly weaker, indicating that the amount of gas produced was smaller. The peak temperature of gas generated by the decomposition of GO-a was close to 195°C; however, that of GO was close to 216°C. This demonstrates that ageing can reduce the thermal decomposition temperature of graphene oxide, which is consistent with the phenomenon reflected by the TG curve. Interestingly, before the violent decomposition of graphene oxide, the infrared absorption intensity of the gas produced by the decomposition of graphene oxide briefly decreased. As illustrated in the inset of figure 4b, for GO, this temperature point appears close to 210°C, while the corresponding temperature point for GO-a appears close to 188°C.Figure 4a,b). Figure 5a shows that the gaseous decomposition products of graphene oxide exhibit a strong infrared absorption signal that corresponds to the severe weight loss during decomposition. As the temperature increases, the gaseous products produced by the decomposition of graphene oxide lead to a weak, continuous gaseous infrared absorption signal. This indicates that the thermal decomposition process of graphene oxide is a continuous and uninterrupted process when the temperature increases. The thermal decomposition process of GO-a illustrated in figure 5b is similar to that of GO. Both GO and GO-a are violently decomposed close to 200°C and maintain weaker decomposition under high-temperature conditions. The difference is that the temperature corresponding to the violent decomposition of GO-a is 195°C, whereas the temperature corresponding to that of GO is 216°C.To examine the thermal decomposition process of GO and GO-a more comprehensively, contour plots were drawn of the infrared absorption signals of the decomposition products a,b. Figua, the decomposition products of GO at 216°C exhibit several obvious infrared absorption signals, which correspond to the infrared absorption of water vapour between 1400–1750 and 3483–3759 cm–1; the infrared absorption peaks of CO2 close to 671, 1377 and 2358 cm–1; and the infrared absorption peaks of CO close to 2115 and 2183 cm–1 [figure 6b exhibits infrared absorption bands of CO2, CO and water vapour at the corresponding positions during the thermal decomposition process at 195°C. Furthermore, it is difficult to completely remove sulfur during the preparation of graphene oxide. It is possible that the weak infrared absorption band close to 1168 cm–1 in figure 6a,b corresponds to SO2 [figure 6a,b correspond to the infrared absorption signals of water vapour. The infrared absorption intensity of water vapour in figure 6a is obvious, while that in figure 6b is only obvious at the peak temperature (197°C). This indicates that the decomposition of GO produces more water vapour than the decomposition of GO-a.The three-dimensional infrared absorption spectrum of the gaseous decomposition products can be analysed by the temperature profile to examine the gas types at different temperatures, as illustrated in figure 6183 cm–1 –43. Simis to SO2 . The gre2 (2358 cm–1), CO (2115 cm–1), water vapour (1509 cm–1) and SO2 (1168 cm–1). As per the Lambert–Beer law, infrared absorption intensity is positively correlated with substance content. Figure 7a–d presents the changes in infrared absorbance of CO2, CO, water vapour and SO2 with temperature, respectively. As illustrated in figure 7a–d, the CO2, CO, water vapour and SO2 generated by the decomposition of graphene oxide all have peaks during the violent decomposition, regardless of whether the sample has been aged. The difference is that the content of CO and water vapour generated by the decomposition of GO-a is slightly lower than that of GO, and the amount of SO2 generated is considerably lower than that of GO; however, the amount of CO2 generated does not appear to change.To determine the relationship between the gaseous product content and temperature more accurately, infrared signals with greater intensity and less interference were selected to represent the corresponding gaseous products, such as COe, GO can be decomposed to produce CO2 at 60°C, and the amount of production increases with an increase in temperature. In figure 7f, there is little difference between the infrared absorption intensity at 50°C and 60°C. The infrared intensity of CO2 increases at 70°C, which indicates that GO-a may generate CO2 close to 70°C. The corresponding temperature of GO is approximately 60°C.In the middle-temperature section (greater than 300°C), almost no water vapour generated by the GO-a decomposition is observed. Compared with GO-a, GO contains more C-H and generates additional water vapour during the decomposition process. Furthermore, it decomposes to generate water vapour when the temperature is greater than 300°C. The decrease in CO content generated by the decomposition of GO-a may be related to the decrease in oxygen content. As illustrated in figure 7−1) differential scanning calorimetry tests were performed on GO and GO-a, as illustrated in figures Ea) was calculated by the Kissinger formula. The results demonstrate that after ageing, the apparent activation energy (Ea) of graphene oxide decreased from 150 to 134 kJ mol−1.To clarify the influence of ageing on kinetic parameters of the thermal decomposition of graphene oxide, non-isothermal (5, 10, 15 and 20°C min. 42 produced at different temperatures, it could be inferred that graphene oxide may have begun to decompose at approximately 70°C. When the temperature exceeded 100°C, the weight loss rate of GO-a was significantly accelerated.The results presented in this study suggest that the aliphatic hydrocarbon groups and oxygen-containing functional groups in the graphene oxide structure are degraded during long-term ageing. The average interlayer spacing of graphene oxide decreased from 0.660 to 0.567 nm. The process of desorption of physically adsorbed water in the graphene oxide interlayer during the ageing process caused the average layer spacing of graphene oxide to decrease. The desorption of water and oxygen-containing functional groups resulted in the appearance of graphene sheets with a lower degree of oxidation, which appeared as a broad peak at 21.04° in the XRD pattern. During ageing, the types of graphene oxide functional groups did not significantly change, but the proportion changed. The content of oxygen-containing functional groups significantly decreased. By comparing the amount of CO−1. Thus, after reaching a certain time limit, graphene oxide may not be able to meet the requirements of users. Because light affects the decomposition of graphene oxide [The results of thermal analysis–mass spectrometry indicated that the ion current intensity peak of OH radicals appeared at approximately 190°C during the decomposition of graphene oxide, and it then began to violently decompose at approximately 195°C. The lower decomposition temperature of graphene oxide limits its application under higher temperature conditions. The graphene oxide underwent slow structural changes when stored at room temperature, and the structural changes led to changes in the physical and chemical properties. Prolonged contact with moisture in the air caused the activation energy of graphene oxide to decrease from 150 to 134 kJ molClick here for additional data file.


Tar-DNA/RNA binding protein 43 (TDP-43) occurs in 97 percent of amyotrophic lateral sclerosis (ALS), ~40% of frontotemporal dementia (FTD) and in many cases of Alzheimer’s disease (AD). Cytoplasmic TDP-43 inclusions are seen in both sporadic and familial forms of these disorders, including those cases that are caused by repeat expansion mutations in the C9orf72 gene. To identify downstream mediators of TDP-43 toxicity, we expressed human TDP-43 in a subset of Drosophila motor neurons. Such expression causes age-dependent deficits in negative geotaxis behavior. Using this behavioral readout of locomotion, we conducted an shRNA suppressor screen and identified 32 transcripts whose knockdown was sufficient to ameliorate the neurological phenotype. The majority of these suppressors also substantially suppressed the negative effects on lifespan seen with glial TDP-43 expression. In addition to identification of a number of genes whose roles in neurodegeneration were not previously known, our screen also yielded genes involved in chromatin regulation and nuclear/import export- pathways that were previously identified in the context of cell based or neurodevelopmental suppressor screens. A notable example is SF2, a conserved orthologue of mammalian SRSF1, an RNA binding protein with roles in splicing and nuclear export. Our identification SF2/SRSF1 as a potent suppressor of both neuronal and glial TDP-43 toxicity also provides a convergence with C9orf72 expansion repeat mediated neurodegeneration, where this gene also acts as a downstream mediator.Cytoplasmic aggregation of  Drosophila genes to identify downstream mediators that suppress an age-dependent motor dysfunction phenotype when they are knocked down by RNA interference. We identified both previously implicated pathways and several novel genes whose knock down is sufficient to dramatically and robustly rescue TDP-43 toxicity both in neuronal and glial contexts. Notably, we demonstrate that SF2/SRSF1, which was previously reported as a suppressor of C9orf72 hexanucleotide expansion repeat toxicity, also is a potent suppressor of TDP-43 mediated neurodegeneration.Loss of nuclear function of TDP-43 and its mislocalization into cytoplasmic inclusions are central features to a suite of neurodegenerative disorders. We screened 2700  C9orf72 repeat expansions [Protein aggregation pathology of TDP-43 is a central feature in a suite of neurodegenerative disorders, including ALS, FTD and AD or those with an AD like presentation  . In ALS pansions , which iDrosophila developmental context in photoreceptor neurons offering the advantage of being both a metazoan and neuronal context. Together, these studies have identified important core cell biological pathways including dysfunction in nucleocytoplasmic transport [To identify mediators of TDP-43 neurodegeneration, several previous studies have capitalized on the toxicity of overexpressing TDP-43. Such over-expression often leads to nuclear clearance and accumulation of cytoplasmic inclusions. This strategy has been successfully employed to identify genes that enhance or suppress TDP-43 aggregation and toxicity, and many of these have been validated in human disease. For instance, screening for suppressors and enhancers in yeast led to the identification of several relevant downstream mediators of TDP-43, FUS and C9ORF72 toxicity –17, inclransport ,22 and cransport  as conveDrosophila. We used an unbiased RNAi screen of over 2700 genes and identified over 30 that suppressed the locomotion phenotype even in aged animals. This screen identified genetic pathways that have previously been implicated in neurodegeneration, as well as novel robust suppressors not previously connected to TDP-43 toxicity. Among these is the SF2/SRSF1 gene, which is a known suppressor of C9ORF72 models of ALS/FTD [To identify downstream effectors in the context of an intact neural circuit, we conducted a behavioral screen for suppressors of age dependent decline in negative geotaxis locomotion in  ALS/FTD .UAS-hTDP-43) transgene [E49-Gal4) driver [E49-Gal4 and the UAS-hTDP-43 were maintained together in a single strain, the motor deficit diminished dramatically over a period of approximately five generations. This suggested that naturally occurring variants within the genetic background could be selected over time to act as modifiers of TDP-43 toxicity. We therefore postulated that individual gene knock downs might also be used effectively to identify mediators of the toxicity of TDP-43 to motor neurons.Expression of a codon-optimized human TDP-43 (ransgene  using th) driver  is suffi) driver  adult flE49-Gal4 driver  and the UAS-TDP-43 transgene insertion, but also a ubiquitously expressed tub-Gal80 repressor  on the X chromosome. The presence of the Gal80 repressor in this strain prevents expression of the UAS-TDP-43, and thereby prevented accumulation of modifying alleles within the strain. However, when males of this strain are crossed to wild-type females, the tub-Gal80 is easily segregated, in male progeny, from the E49-Gal4 and UAS-TDP-43 transgenes which reside on autosomes. We found that such male offspring consistently and stably produced severe adult motor defects even after the parental stock was maintained for many (>20) generations. We used this Gal80;E49>TDP-43 strain to conduct an unbiased genetic screen for suppressors of the adult locomotion defect. By crossing males from this parental strain with females that contained individual UAS-driven shRNAs typically targeting a single gene, we screened the impact of each shRNA on locomotion in approximately one week old male progeny that had lost the Gal80 repressor .To avoid the confounding impact of selected suppressors emerging among natural variants in the strain, we created a new recombinant stock that contained not only the UAS-TDP-43 and the UAS-shRNAs via the same E49-Gal4 driver. We were cognizant of the fact that the presence of two loci that contain the same Gal4 responsive UAS enhancer might titrate the available Gal4 transcription factor available for each. To mitigate against the possibility that differences in such titration across shRNAs could yield false positive or negative effects, we limited this screen to shRNAs from a single collection that all use an identical “VALIUM20” vector as their RNAi expression system. Additionally, we only used the subset of strains [UAS-shRNA inserted into a specific AttP2 landing site on the third chromosome. This collection of VALIUM20 shRNA insertions at this defined chromosomal location consisted of 2724 strains, generally targeting a specific Drosophila genomic locus. We crossed females from each of these 2724 UAS-shRNA containing strains with males from our tub-GAL80;E49>TDP-43 strain . We then quantified negative geotaxis locomotion behavior [Fig 1C) that allowed multiple strains to be tested in parallel. We established a stringent locomotion value  to identify candidate suppressors, and then each candidate suppressor was re-screened with an independent cross to validate the findings from the primary screen . This also permitted us to calculate both the overall false positive and false negative rates . The vast majority of the crosses yielded F1 progeny that had severe locomotion defects. In many cases there either were too few surviving male progeny to screen, or we found that none of the flies were able to climb past the 10cm marker within the allotted time (S2 Table). We identified 33 shRNA crosses  that resulted in greatly improved locomotion, with greater than 35% of the animals crossing threshold in both the primary screen and the independent validation crosses . As a further validation, 22 of these screen hits were retested after being equilibrated  with 5 generations of back-crossing into the w1118(isoCJ1) genetic background (a derivative of Canton S) both to match that of the GAL80;E49>TDP-43 strain and to test for robustness of the effects in a new genetic background. The suppression of the negative geotaxis behavioral defect persisted with 21/22 tested in this second genetic background (Table 1).The design of this screen involves expressing both the  strains  that conbehavior  among F1These TDP-43 suppressors fall into several broad functional categories. First, we identified a number of novel genes that have not previously been implicated in neurodegeneration and a relatively large group that are components of the Mediator complex. Mediator proteins integrate signals between transcription factors (TFs) and RNA polymerase, with different subunits showing some specificity for interactions with distinct subsets of TFs . Second SF2/SRSF1 and msk/importin-7.  We designed guide RNAs (gRNAs) targeting these genes and we generated transgenic animals that constitutively express these gRNAs by integrating into the same AttP2 landing site that was used for the shRNA screen. As controls, we used gRNAs targeting either GFP or the lst gene, which was not identified as a suppressor in our shRNA screen and is not known to be expressed in motor neurons. We tested the impact of expressing each of these gRNAs in animals that also contained the E49-Gal4 line, UAS-TDP-43 and UAS-Cas9 transgenes.We used CRISPR/Cas9 gene editing as an independent means to validate that TDP-43 toxicity to motor neurons can be suppressed by knockout of SF2/SRSF1 gRNA. In contrast, such deletions were not detected from gut .As a first test of the efficacy and specificity of our cell type specific gRNA targeting strategy, we dissected thoracic ganglia, which contain motor neurons vs gut as a control. DNA from these tissues was extracted and the region flanking the gRNA target sites were queried by PCR and sequencing. Despite the presence of unedited non-motor neuron cells in the thoracic ganglion sample, we were able to detect and sequence internal deletions in the region that is targeted by the lst, mks/importin-7 and SF2/SRSF1. We quantified negative geotaxis behavior over the course of a 4 week aging time period and found that relative to the gRNAs targeting GFP or lst, the gRNA that targets the SF2/SRSF1 gene suppressed the effects of TDP-43 in animals that were 7, or 28 days old . Similarly, with msk/importin-7, each of two independent gRNAs were sufficient to suppress the negative geotaxis defect caused by TDP-43 expression in motor neurons, with msk gRNA1 showing significant effects at 7 and 28 days and gRNA2 showing significant effects at 28 days of age .We next tested the effects on negative geotaxis behavior of the gRNAs against GFP, S1 Fig; Table 1). These were selected to span each of the categories of gene function among the hits from the primary screen. In parallel, we tested a series of 6 negative controls shRNAs. As negative controls, we used UAS-shRNAs against three genes  that had not impacted negative geotaxis in our primary screen. And we also tested 3 different shRNA lines that targeted heterologous transcripts that are not present as endogenous sequences in the fly genome . Together, these 6 shRNAs controlled for several potential confounds, including the possibility that providing a second UAS-driven transgene might provide functionally relevant reduction in the levels of the UAS-TDP-43 transgene. We view this possibility as unlikely because with several of our shRNA suppressors, we observe robust expression of GFP in animals that contain the E49-Gal4 driver, UAS-GFP and a UAS-shRNA compared with controls that do not contain the shRNA . In addition to providing a robust set of controls for the possibility of titrating the expression of UAS-TDP-43, these 6 shRNAs also controlled for the possibility that overwhelming the shRNA silencing system might impact TDP-43 neurotoxicity. As with the 20 shRNA suppressors, the 6 control shRNAs are inserted at the common AttP2 PhiC31 landing site, and were equilibrated into the same genetic background.Because neurodegenerative phenotypes exhibit a marked age-dependence, we tested whether our identified suppressors were capable of ameliorating the effects of motor neuron TDP-43 toxicity over an aging time course. For this experiment, we tested 20 of the suppressors that had been equilibrated into a common genetic background . Each of the six negative control shRNAs exhibited severe defects in locomotion at 1 week post eclosion, consistent with their failure to suppress the geotaxis assay in the primary screen. Animals carrying each of these control shRNA also exhibited rapid deterioration in climbing ability at subsequent age time points. By the end of 6 weeks, most of the surviving flies in the negative control groups were largely incapable of climbing . In contrast, 19 out of the 20 shRNA lines that we identified as suppressors in the primary screen exhibited robust climbing ability, with nearly 100% of animals crossing the 10cm distance within 10 seconds. And remarkably, this amelioration of the climbing defects caused by TDP-43 expression in motor neurons was largely resistant to age over a 6 week period . The only exception to this is the shRNA targeting the sbr/NXF1 gene, which was identified as a suppressor in the primary screen  but whose suppression was eliminated when it was crossed into the w1118 (iso CJ1) background.Negative geotaxis behavior was quantified among F1 males for each of these 26 crosses beginning 1 week after eclosion, and every 7 days thereafter (S5 Table), we made use of an inducible glial expression system in which a temperature sensitive Gal80 repressor is used to modulate the expression of TDP-43 and the shRNA, under control of the Repo-Gal4 that expresses in most glial cells. We have previously shown that inducing pan glial TDP-43 expression after development is sufficient to greatly reduce lifespan, and cause both glial death and non-cell autonomous toxicity of TDP-43 expressing glia that also kills adjacent neurons[GAL80TS, Repo-Gal4; UAS-TDP-43 animals (hereafter referred to as RepoTS>TDP43) with each of the UAS-shRNAs and examined lifespans of the F1 offspring after heat-shift induction of TDP-43.The primary shRNA screen described above was conducted with TDP-43 expression in motor neurons. But there is a growing recognition of the importance of glial cells in neurodegeneration , and we t neurons. We crosecd gene (shRNA 41676), which did not impact the motor neuron phenotypes with E49>TDP-43 also had no impact on the severely shortened lifespan of RepoTS>TDP-43. Two independent experiments in which this control shRNA were expressed exhibited median survival of ~11 days . In contrast, we observe significant lifespan extension with 9/10 shRNAs that target genes identified in the motor neuron suppressor screen. The effect was modest with 2/10 shRNA suppressors  and was more robust for 6/10 . It also is worth noting that one shRNA, against the Chd1 gene, was identified as a suppressor in the context of motor-neuron toxicity (Table 1) but has the opposite sign in the context of glial TDP-43 toxicity. The shRNA against Chd1 significantly decreased lifespan of the RepoTS>TDP-43 animals. Thus, action of this gene on TDP-43 toxicity may be cell type dependent. Finally, the most potent suppressor in this glial context was SF2/SRSF1, which yielded a median survival of ~22 and ~29 days in independently replicated experiments (green lines). Despite the expression of TDP-43 in most glia, the lifespan of animals that express SF2/SRSF1 shRNAs is near that expected from wild type animals under these temperature conditions (30°C). Because the suppression that we observed was so robust with SF2/SRSF1 knock down, we used Western immunoblotting to verify that TDP-43 protein was equivalently expressed in these animals. We found that 5 days after induction, the levels of TDP-43 in the presence of the SF2/SRSF1 shRNA are indistinguishable from those seen with the mCherry control shRNA . This supports the conclusion that SF2/SRSF1 mediates toxicity of TDP-43 rather than its production.Control flies expressing an shRNA against the Overexpression of either wild type or disease alleles of TDP-43 triggers concentration dependent TDP-43 protein aggregation and can lead to TDP-43 clearance from the nucleus and appearance of hyperphosphorylated cytoplasmic inclusions. This approach has been used in yeast ,14, mammDrosophila motor neurons as the basis for an shRNA knockdown screen to identify suppressors of TDP-43 neurotoxicity. Young (newly eclosed) adult flies with such motor neuron expression of TDP-43 exhibit mild defects in climbing behavior in a negative geotaxis assay, but this defect becomes dramatically worse with age. Using this approach, we screened a collection of shRNAs that covered approximately 15–20% of protein coding genes in the Drosophila genome, and found that approximately 1% of shRNAs can abrogate TDP-43 toxicity. For the majority of these, shRNA knockdown also potently prevented the age-dependent decline in locomotion. Additionally, for most of the cases tested, effects on lifespan from TDP-43 expression in glia also was ameliorated.We used over-expression of human TDP-43 in a subset of Chd1 and moira, for instance, are chromatin remodeling factors that were identified [Chd1 exacerbated the toxicity of TDP-43 to photoreceptor neurons, leading to a more severe rough eye phenotype. This is the opposite sign of effect that we observed in the context of our motor-neuron based behavioral screen. On the other hand, when we screened hits in the context of effects of glial TDP-43 on lifespan, we found that Chd1 knockdown exacerbated the toxicity, consistent with the sign of effect seen in the previous study. This drives home the importance of cellular context, and the importance of testing impact within both glia and neurons.The majority of suppressors described here have not previously been implicated in neurodegeneration. But several of the hits have been identified in previous screens for TDP-43 suppressors, and a number of others play roles in cellular pathways that have established impact on TDP-43 related neurodegeneration. For example, we identified 8 genes with roles in chromatin remodeling. These include several specific genes that have been found in previous screens. entified  in a preChd1, which promotes chromatin silencing, the 7 other genes in this category all promote open chromatin. E(y)3, polybromo, ash1, moira, br and br140 are all part of the trithorax and SWI/SNF (Brahma) complexes and enok is a histone acetyltransferase that interacts with trithorax group genes and also promotes open chromatin. With each of these, TDP-43 toxicity is ameliorated by shRNA knock down, suggesting that chromatin silencing normally helps keep TDP-43 toxicity in check. This idea is consistent with the hypothesis that loss of silencing of retrotransposons and endogenous retroviruses contributes to TDP-43 toxicity [In the case of the 8 chromatin modulators identified as suppressors, their functional roles may also provide some mechanistic insight. With the exception of toxicity ,56,57,60Su(Tpl), which was found in a previous rough eye suppressor screen [Su(Tpl) suggests that a similar process could be at play in motor neurons and glia.A second category of suppressor identified here are factors involved in basal transcription. This includes 8 components of the Mediator complex, and several basal transcription factors. Although it is difficult to distinguish specific vs artifactual causes for identification of factors regulating fundamental aspects of transcription, it is worth pointing out that we also identified the transcription elongation factor, r screen . In thatmsk, one of the nuclear import factors that we identified is the Drosophila orthologue of Importin 7, a nuclear import protein that has a role in nuclear entry of HIV retrovirus [The third major category of suppressor includes genes with known roles in nuclear import/export control, a pathway that was also convergently identified in several previous screens ,22, supptrovirus ,63 and Ltrovirus . Thus, aSF2/SRSF1 as a particularly robust suppressor. We found that knock down of SF2/SRSF1 abrogated the locomotion defect caused by TDP-43 expression in motor neurons, prevented the age-dependent decline in climbing ability out to 6-weeks of age, and potently extended lifespan in animals that over-express TDP-43 in glial cells. In fact, glial knock down of SF2/SRSF1 is sufficient to all but eliminate the severe lifespan effect seen in animals that overexpress TDP-43 in glia. This RNA binding protein functions in both splicing and as a nuclear export of adaptor for RNA export. It has previously been identified in a Drosophila screen for suppressors of a rough eye phenotype caused by C9orf72 hexanucleotide expansion repeat RNA [SF2/SRSF1 knock down could suppress the toxicity of a C9orf72 repeat RNA that encoded dipeptide repeats. This was demonstrated both in the Drosophila context and in a co-culture system in which astrocytes from C9orf72 derived patient fibroblasts are grown with motor neurons. In the induced astrocyte context, knock down of SF2/SRSF1 was sufficient to ameliorate the toxicity of patient derived astrocytes to motor neurons. This is reminiscent of our observation of highly potent suppression of the effect on lifespan of glial TDP-43 expression in flies, an effect that we previously have documented to involve toxicity of the glia to neurons [C9orf72, the effect of SF2/SRSF1 knock down was shown to be mediated by modulation of the export of the repeat RNA to the cytoplasm. The reduced repeat RNA export in turn was proposed to reduce the repeat associated translation to produce toxic dipeptide repeats. In fact, SF2/SRSF1 knockdown was not sufficient to significantly ameliorate the toxicity of arginine rich dipeptides expressed from non-repeat RNAs[SF2/SRSF1 is to aid export of the repeat RNA to the cytoplasm.Finally, we identified peat RNA . In that neurons . In the peat RNAs, consistSF2/SRSF1 as a suppressor of TDP-43 toxicity in neurons and glial cells in Drosophila suggests convergence with the effects previously observed on the C9orf72 repeat. In principle, this convergence could reflect the fact that C9orf72 patients typically exhibit TDP-43 cytoplasmic inclusions [C9orf72 expansion toxicity also can exhibit TDP-43 proteinopathy [SF2/SRSF1 has strong suppressive effects on the toxicity of TDP-43 that occurs in the absence of any C9orf72 repeat RNAs. So in this case, effects of SF2/SRSF1 knock down on toxicity of TDP-43 is independent of any impact on C9orf72 repeat RNA export. The mechanism by which SF2/SRSF1 knock down reduces toxicity is unknown. Previous work in Drosophila [SF2/SRSF1 was sufficient reduce expression from a hTDP-43 transgene when it contained its own 3’UTR that includes an element called TDPBR (TDP-43 Binding Region), which is believed to be responsible for its auto-regulation. Based on these findings, they proposed that SF2/SRSF1 may modulate TDP-43 autoregulation. But this is not likely to be an explanation for the potent suppression that we observe with SF2/SRSF1 knockdown because the TDP-43 construct that we utilized here does not contain the auto-regulatory region, but instead contains a heterologous 3’ UTR from alpha-tubulin [S3 Fig). SF2/SRF1 is a multifunctional protein, involved in splicing regulation, RNA export, and other aspects of RNA metabolism- for example, there is evidence that suggests that SF2/SRSF1 can also bind the TAR region of HIV [SF2/SRSF1 is mediated by reducing deleterious effect of TDP-43 toxicity to neighboring glial or neuronal cells [Our identification of clusions . Indeed clusions . Furtherinopathy . On the osophila  reported-tubulin . Moreoven of HIV , which ial cells .Drosophila. Unlike previous screens, we used an age-dependent behavioral defect as a primary readout. This age-dependent effect on a neurobehavioral readout may enrich for effects that are related to the age-dependent degenerative rather than neurodevelopmental effects, but also is sensitive to disruptions to the interactions among each of the relevant cell types to a locomotion circuit, including motor neurons and glia. One open question not addressed in this study is whether the toxicity of TDP-43 expression in motor neurons is accompanied by neuronal loss, and whether the mechanisms of toxicity are the same in glia and neurons. Previous work in Drosophila has not established loss of motor neurons, but there is evidence of deleterious synaptic remodeling at the neuromuscular junction upon ectopic hTDP-43 expression [SF2/SRSF1 provides a point of convergence between TDP-43 proteinopathy and C9orf72 familial ALS/FTD and points to unexplored mechanistic underpinnings of that overlap.We have used a genetic screening approach to identify suppressors of TDP-43 toxicity in pression . Nonethepression ,41. Our GAL80;E49>TDP-43 animals were crossed to females that contained either the UAS-shRNA or the gRNA and UAS-Cas9. In each case, Male F1 animals that had lost the Gal80  were collected shortly after eclosing and transferred to fresh vials with food. Behavioral testing took place between 12PM and 4PM in an isolated environmentally controlled room. Lighting conditions were kept as consistent as possible for all geotaxis screening. For the assay, a maximum of 20 flies were quickly transferred (without being anesthetized) by tapping the housing vial and transferring to an assay vial without food. Flies were placed into two 95mm vials whose open mouths were held together by black plastic gaskets. A frame capable of holding ten sets of vial pairs was used to simultaneously tap flies to the bottom of the vials. A timer and video camera were started prior to tapping the flies down. Video of climbing activity was recorded for three trials per experiment. Scoring of geotaxis was performed by determining the percentage of the flies in each vial that crossed to the top vial (10cm) within 10 seconds (recording proceeded for 15 to 20 seconds).Male Male and virgin female flies were collected over a period of 72 hours. Groups of approximately 20 flies were placed in each of 3 separate vials (n = 60 for most assayed genotypes). Males and females were tested separately. Flies were kept in temperature and humidity controlled incubators. To induce TDP-43 expression in glia, the flies were transferred to a 30°C incubator. Flies were flipped to vials of new food every other day to avoid mortality from becoming stuck in food and dead flies were removed and counted every day.https://www.flyrnai.org/crispr3/web/ [S3 Table.Candidate gRNAs were designed by a publicly available computational prediction method pr3/web/ . For eacS4 Table) were ordered from IDTDNA and included overhangs for Bbs1 restriction sites. Oligos were annealed and cloned into a linearized pCFD3.1 vector [white phenotype rescue. CRISPR cutting in motor neurons was assessed as described in Fig 4B. Screening primers can be found in S3 Table.Oligos  was performed for 30 cycles then amplification fragments were evaluated by agarose gel electrophoresis (1.8% w/v TE buffer). Bands indicated in Fig 2B were excised with a scalpel, purified using Zymoclean Gel DNA Recovery Kit (Zymo Research) and cloned into TOPO TA Cloning vectors (Thermo Fisher Scientific).Cas9 gRNA F1 Male flies were anesthetized and pinned to a dissecting plate. The gut and thoracic ganglia were separately dissected from 10 flies and placed into DNA extraction buffer, homogenized, and treated with Proteinase K. PCR amplification using KAPA2G Fast HotStart Genotyping Mix (Kapa Biosystems) with flanking oligos  for 15 minutes, then degassed in fixative at room temperature for 45 minutes. 3 washes with PBST (10 minutes each) were performed, and ganglia were incubated with a mouse anti-GFP 1° antibody (1:250 dilution MilliporeSigma #11814460001) in 1x PBST  overnight at 4°C. Ganglia were then washed 3 times (10 minutes each) with 1x PBS and then incubated with 2° antibody  in 1x PBST  for 1 hour at room temperature, then washed with 1x PBST 3 times (10 minutes each) and placed on a concave dissecting dish. The PBST was removed, and the tissue was briefly rinsed with 1x PBS, then as much of the liquid was removed as possible with a pipette before adding FocusClear (CelExplorer) directly to the tissue. After tissue clearing occurred, the ganglia were transferred to a slide with a drop of ProLong Diamond AntiFade Mountant with DAPI (Thermo Fisher Scientific) and a glass coverslip placed over the preparation. The cover was glass was sealed with nail polish and allowed to set overnight in a dark 4°C refrigerator. Images were generated with a Zeiss Confocal microscope.S5 Table for all Drosophila stocks used in this study. TRiP stocks were not treated for the possible presence of Wolbachia.See S1 Table(XLSX)Click here for additional data file.S2 TableSheet 1: first screen of full TRiP line assembly. Sheet 2: retest summary of candidate rescues for validation.(XLSX)Click here for additional data file.S3 TableSheet 2: gRNA oligonucleotide sequences ordered for cloning into pCFD3.1 vector.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S1 Fig1118 with a miniwhite transgene inserted into AttP2 were crossed to males from the desired TRiP line. F1 offspring males heterozygous on the third chromosome were again crossed to virgins from the w1118 background to yield F2 virgin females homozygous on the X for w- and heterozygous on the 3rd chromosome for introgression. Introgression and backcrossing: F2 virgin females heterozygous on the third (very light orange eyes) were backcrossed to males from the w1118 background. This was repeated with the every subsequent generation (F3-F6) of females heterozygous on the third to gradually replace more of the 3rd chromosome containing the AttP2<shRNA> with the third chromosome from the w1118 background. Sibling cross: after 6 generations of introgression, male and female siblings with light orange eyes were crossed to each other, and F7 offspring with white eyes were selected .TRiP lines carry the vermillion (v) marker on their AttP2 integration site. Initial setup: virgin w(PDF)Click here for additional data file.S2 Figmsk, (B) Su(Tpl), (C) SF2, (D) Polybromo.All images are single-plane on 10X objective. shRNAs were (A) (TIFF)Click here for additional data file.S3 FigSF2 was used. The hTDP-43 transgene and shRNA were induced using the TubGAL80TS system (by switching from 21°C to 29°C) and controlled by the pan-glial Repo-GAL4 driver. (a) Chemiluminescent output of blots on two separate experiments. Top blot used rabbit polyclonal hTDP-43 antibody (target band indicated by arrow), The bottom blot used anti alpha-tubulin as a loading control (indicated by arrow). The sample loaded on each lane is indicated at the top. 2U (wild type cantonized control strain) and non-induced (21°C) samples were included as negative controls. (b) Quantitative assessment of hTDP-43 band intensity was performed using ImageJ and normalizing to alpha-tubulin of the 2U sample. Intensity is average across the two experiments. Error bars: SEM. Statistical significance was assessed by unpaired two-tailed Student’s T-test (95% CI). Significant changes were detected in SF2 sample after induction . induction with the mCherry-shRNA control showed a trend that was not significantly different in the two experiments. No significant differences in hTDP-43 induction were detected when mCherry control shRNA and SF2 shRNA induced samples were compared.Lanes indicate whether a control shRNA (mCherry) or the shRNA against (TIF)Click here for additional data file.