Melt-electrowriting (MEW) is an emerging method that combines electrospinning and extrusion printing, allowing the fabrication of micron-scale structures suitable for tissue engineering. Compared to other additive fabrication methods, melt-electro written structures can offer more appropriate substrates for cell culture due to filament size and mechanical characteristics of the fabricated scaffolds. In this study, polycaprolactone (PCL)/graphene composites were investigated for fabrication of micron-size scaffolds through MEW. It was demonstrated that the addition of graphene can considerably improve the processability of PCL to fabricate micron-scale scaffolds with enhanced resolution. The tensile strength of the scaffold prepared from PCL/graphene composite (with only 0.5 wt.% graphene) was proved significantly (by more than 270%), better than that of the pristine PCL scaffold. Furthermore, graphene was demonstrated to be a suitable material for tailoring the degradation process to avoid undesirable bulk degradation, rapid mass loss and damage to the internal matrix of the polymer. The findings of this study offer a promising route for the fabrication of high-resolution scaffolds with micron-scale resolution for tissue engineering. Tissue engineering is an evolving strategy for repairing damaged tissues or organs. This approach offers an efficient alternative for complicated treatments such as organ transplantation or implantation of artificial prostheses ,2. The mThe solution, therefore, lies in the development of biocomposites that are composed of a matrix infiltrated with a filler to compensate the deficiencies of the matrix. Among synthetic polymers, polycaprolactone (PCL) is a popular candidate for developing biocomposites. PCL is a Food and Drug Administration (FDA) approved bioresorbable polyester and has been used for medical devices since the 1980s . It is oProcessing materials into scaffolds with appropriate properties is the next challenge in the tissue engineering field. The emergence of 3D printing opened new avenues for the fabrication of complex structures for a variety of biomedical applications. Compared to conventional manufacturing methods, such as mould casting, 3D printing provides the advantage of fabricating structures with higher resolution and complexity at a faster speed. This technique can also be used to fabricate customised structures to accurately mimic the biomechanical properties of damaged organs and tissues ,13. In eAs an implantable synthetic polymer, PCL has been studied extensively to understand the degradation mechanism and excretion pathway . HoweverIn this study, we developed micron-scale scaffolds with tailorable mechanical and degradation properties using MEW of PCL/graphene composites. We examined the effect of graphene addition on processability and thermal properties of the polymer to develop a suitable substrate for in vitro tissue models. MEW of the PCL/graphene composites was optimised to fabricate scaffolds with the finest possible strut size. The mechanical properties and degradation profile of the scaffolds were also investigated.PCL (MW of 45 KDa) was obtained from Sigma Aldrich Pty Ltd . Lipase from Pseudomonas sp. Type VIII was purchased from Sigma Aldrich. Dimethyl formamide (DMF) was purchased from Chem-Supply .DMF-dispersed graphene dispersion and PCL/graphene composites were prepared according to a method described in our previous work . BrieflyPCL-CCG composites with different graphene content were prepared by mixing PCL in an appropriate amount of DMF-dispersed CCG at 75 °C for 3 h. The mixture was then cooled to room temperature, precipitated in cold methanol, filtered, washed with ethanol and dried in a vacuum oven at 50 °C. The composites were labelled according to the weight percentage of the graphene content per PCL, with PCL-CCG 0.1 and PCL-CCG 0.5 containing 0.1 and 0.5 wt.% graphene, respectively. Composites with up to 10 wt.% graphene content could be prepared without observable aggregation; however, they were not processable through MEW due to increased viscosity and melting point.Samples were printed using a Bioscaffolder 3.2  fitted with an MEW module. The system is equipped with a pneumatic extrusion print head capable of performing high-voltage induced fibre deposition operating at pressures of 0–600 kPa. The positive voltage is placed on the needle tip and a negative voltage of the collecting tray. This dual voltage power supply setup is similar to methods reported in literature that increases the maximum number of layers for each construct . For fabt-test to assess the mass loss at individual time points. Significant difference was indicated by p < 0.05.An enzymatic degradation assay was conducted using the method published previously . Lipase SEM images of printed samples were taken using a Low Vacuum Scanning Electron Microscope (LVSEM) JEOL JSM-6490LV  operating in high vacuum mode. The samples were coated with 15 nm of platinum (Pt) using a Dynavac SC100MS magnetron sputter coating system . Secondary electron imaging was performed at 15 kV accelerating voltage with a probe current setting of 45 and the specimen at 20 mm working distance. Images were taken at random cross sections of the scaffolds to better image layer resolution and filament shape. Magnifications of 250×, 1500× and 2500× were taken. For degradation samples, images were taken at random locations from a top-down view at 48 h and 96 h with magnifications of 100×. A high magnification of 0.5 wt.% graphene composite at 500× and 1000× was also imaged to determine the mode of degradation.n = 5 samples per group) were measured using a Shimadzu tensile tester . The scaffolds (20 × 5 × 40 mm) were subjected to tensile test with a constant rate to measure the maximum force (at their breakage point) and the strain, which is the percentage change in the length of the sample before it breaks. Raman spectra were recorded on a Horiba LabRam HR Evolution Raman Spectrometer using a 633 nm laser line with a 300-lines mm−1 grating through a 100× magnification wide angle objective. TGA was performed using a TG 209 F1 Libra  with a ramp rate of 5 °C/min up to 900 °C under a nitrogen atmosphere. Differential Scanning Calorimetry (DSC) analysis was performed by using a DSC 204 F1 Phoenix  in two cycles at 5 °C/min under a nitrogen atmosphere. The sample presealed in an aluminium pan was first heated to 110 °C (above the melting point of the polymer) and then cooled to −10 °C to record melting and crystallization peaks. Rheological properties were measured using an AR-G2 rheometer  with a 12-millimetre parallel plate geometry at 100 °C, which is the processing temperature of PCL and composites. Viscosity values were measured across a shear rate range of 0.1 to 1500 1/s. The mechanical properties of the scaffolds , and their recovery behaviour was investigated, as shown in −1. The Raman spectrum of PCL shows the characteristic peaks of the polymer at 1060 cm−1 and 1106 cm−1 , 1281–1305 cm−1 (CH2 groups) and 1726 cm−1 (ν C=O stretching mode). The other peaks at 1470–1418 cm−1 (δCH2) and 912 cm−1 (νC–COO) are attributed to crystalline domains [−1 are observed corresponding to D and G bands of graphene sheets. The peaks due to PCL are less visible in the Raman spectra of composites as the intensity of the characteristic D and G bands of graphene are greater than that of PCL. No significant change was observed in the position or ratio of D and G bands of graphene, indicating that the structure of graphene has barely been changed when mixed with PCL. Raman spectra A were co domains ,30. In sn = 5) of the composites is consistent with the percentage of graphene added to the reaction initially, indicating homogeneous dispersion of graphene sheets in the polymer matrix.TGA B curves DSC results C showed MEW is a solvent-free technique that combines the principles of melt extrusion printing and electrospinning to produce polymeric highly ordered porous structures . The intOnce MW and processing temperatures are established, instrument-based parameters such as voltage, distance, pressure and speed becomes important in controlling the fibre’s diameter. In this study, PCL and composites were printed at 100 °C (max. temperature), voltage of 5 kV and collector distance of 4.8 mm. The selection of a low voltage and low distance is consistent with the findings by Brown et al , demonstPCL was able to be extruded at 5 kPa, while composite materials require a minimum of 10 kPa due to the higher viscosity. The minimum pressure determined for all samples were then held constant against a range of printing speeds to determine the critical translation speed (CTS) necessary to print a continuous filament. Study conducted by Brown et al.  observedSEM was conducted on printed scaffolds . InteresPCL is a semi-crystalline, hydrophobic aliphatic polyester that is currently used for sutures, wound dressing and is a common scaffold material for bone-related applications. As a long term stable polymer, PCL subjected to hydrolytic degradation requires 2–4 years for complete degradation depending on molecular weight (MW) . In vivoIn the current study, MEW-fabricated scaffolds showed continued degradation beyond 24 h, as indicated in Hydrolytic degradation can proceed via surface or bulk-degradation with the former allowing predictability of the erosion process and the latter often resulting in instantaneous failure . TypicalIn this study, MEW of PCL graphene composites was investigated for the first time. The PCL-CCG composite was shown to be a better material for melt-electro writing of high resolution, multi-layer scaffolds, as shown by circular filaments and distinct layer separation. As confirmed by rheology and DSC results, the addition of graphene can increase the elasticity of the polymer and help it solidify faster, which will play an important role in the formation of multilayer structures with well-defined layers. Furthermore, the addition of as low as 0.5 wt.% graphene could significantly improve the strength of fabricated scaffolds by more than 270%. Bulk degradation and rapid mass loss in PCL can result in undesirable scaffold integrity and failure of implant. SEM and in vitro degradation results indicated that filaments have become thinner over time without formation of hollow filaments or holes in the internal matrix of the polymer. The degradation mechanism was evident to occur through surface erosion and uniformly through the interconnected networks and scaffold design. Degradation profiles can be altered through graphene concentration as PCL-CCG 0.5 significantly decreased the rate of degradation and extended the time. Due to increased viscosity and limitations of the instrument in extruding the composites, PCL-CCG with higher than 0.5 wt.% graphene content could not be processed, which will be the subject of future investigations.


In this paper, efficient analysis of the plane wave scattering by periodic arrays of magnetically-biased graphene strips (PAMGS) is performed using the semi-numerical, semi-analytical method of lines (MoL). In MoL, all but one independent variable is discretized to reduce a system of partial differential equations to a system of ordinary differential equations. Since the solution in one coordinate direction is obtained analytically, this method is time effective with a fast convergence rate. In the case of a multi-layered PAMGS, the governing equations of the problem are discretized concerning periodic boundary conditions (PBCs) in the transverse direction. The reflection coefficient transformation approach is then used to obtain an analytical solution in the longitudinal direction. Here, magnetically-biased graphene strips are modeled as conductive strips with a tensor surface conductivity which is electromagnetically characterized with tensor graphene boundary condition (TGBC). The reflectance and transmittance of different multi-layered PAMGS are carefully obtained and compared with those of other methods reported in the literature. Very good accordance between the results is observed which confirms the accuracy and efficiency of the proposed method. The tunability of its surface conductivity by an applying electric or magnetic field bias is the main advantage of graphene over metals, which leads to the design of tunable devices including tunable THz absorbers6, graphene frequency selective surface with tunable polarization rotation characteristics7, etc. Moreover, the magnetically-biased graphene has anisotropic surface conductivity and shows non-reciprocal gyrotropy at microwave and optical frequencies8, which makes it a good candidate for designing nonreciprocal components9 and achieving enhanced Faraday rotation10.Graphene, as a 2D material with hexagonal honeycomb lattice, has remarkable mechanical, electrical, and thermal properties such as astonishing strength and stiffness, optical transparency, high electronic mobility, and tunable surface conductivity11. The discontinuous Galerkin time domain (DGTD) method for the analysis of magnetically-biased graphene is reported by Li et al.12. The finite-difference time-domain (FDTD) method13 and the MoL14 are also reported for modelling magnetized graphene. Besides, magnetically biased graphene sheets are analyzed analytically by Heydari et al.15.To model the electromagnetic characteristics of graphene various methods have been implemented numerically. The graphene has been characterized using a circuit model through the partial element equivalent circuit (PEEC) method by Coa et al.17 take advantage of the unique electromagnetic properties of graphene. The GPSs with numerous applications including THz absorbers18, THz filter19, and graphene-based frequency selective surfaces20, to name a few, have been reported in the literature. As a result, a fast and accurate method for the efficient analysis of GPSs is in need.Alternatively, graphene-based periodic structures (GPS) with fascinating properties like perfect absorption of light in a specific range of frequency21, finite-difference time-domain (FDTD)22, integral equations (IE)23, and Fourier modal method (FMM)26 have been reported for the diffraction analysis of GPSs in the absence of magnetic field bias while less effort has been made in case of magnetically-biased GPSs27.The study of electromagnetic waves interaction with periodic arrays of graphene has attracted great attention to the researchers recently. Different numerical methods, including the method of moments (MoM)et. al27.In this paper, the semi-numerical, semi-analytical MoL has been provided for the efficient analysis of the plane wave scattering by PAMGS. In this method, we use of PBCs to take the periodicity of the PAMGS into account. Hence, the fields and the derivatives are to be discretized with finite differences according to the PBCs. Besides, the constitutive parameters of the cross section as well as the surface conductivity of graphene strips are discretized. In those parts of the cross-section where there is no graphene, the conductivity value is zero. Hence, there is no need to introduce approximate boundary condition at the interface of two adjacent layers where graphene exists as done by Khoozani Moreover, unlike fully numerical methods, the solution of the problem in one coordinate direction is obtained analytically in MoL which means there is no need to use absorbing boundary condition (ABC) such as perfectly matched layers (PML) in this direction. Besides, the analytical nature of the method saves a lot of computing time compared to fully numerical methods. The reflection coefficient transformation approach is introduced to obtain an analytical solution in this direction. In this approach, the structure under the study is divided into homogeneous layers and the known reflection coefficient in the last layer is transformed through layers and interfaces to obtain the reflectance. Having known the reflection coefficient in each layer, the transmission coefficient is obtained by transforming the fields in the opposite direction.The rest of the paper is organized as follows: First, we present a brief description of the graphene properties. Then, we continue with the basic formulation of the problem. In this section, the MoL is introduced concisely. Afterwards, the plane wave incidence on a PAMGS for the two special cases of normal and oblique incidence is investigated. The reflection and transmission coefficients of a multi-layered PAMGS are obtained in the next subsection. Next, the numerical results of different PAMGSs obtained using the proposed method are presented.xy plane with a magnetic field bias 29 characterizing with an anisotropic surface conductivity to be obtained through a quantum mechanical analysis using Kubo formulation31. However, in the case of magnetic field bias, there exists an excitonic energy gap which is opened due to the interaction of electrons with the magnetic field that can be significant at low temperature. At high temperature, the carrier density increases and consequently the screening effect enhances. Hence, the gap disappears and the graphene sheet’s electronic band structure remains gapless32.Consider a graphene sheet in the mentclass2pt{minimxy plane under an electric field as shown in Fig. 8. For the case 827. Here, the optical properties of graphene are similar to those of Drude-type materials and as the result the quantum mechanical closed form expressions for 33e is the electron charge, T is the Kelvin temperature.The anisotropic nature of graphene’s conductivity can be interpreted by the electron motion in the surface conductivity, it can be electromagnetically treated as an special impedance boundary condition at the interface of adjacent layers called tensor graphene boundary condition (TGBC). The TGBCs are given byAlternatively, since the graphene sheet is modeled with a tensor These boundary conditions are then used in the next subsections to derive the reflection coefficient transformation formula through interfaces. Note that a time dependence of D as shown in Fig. y-direction.Consider a PAMGS with graphene strips of width entclass1pt{minima29. Besides, unlike infinite graphene sheets, graphene strips have non-uniform carrier density 33. For chemically doped graphene, the net charge is zero. Here, the edge effects are confined to a strip width in order of the dopant’s Wigner-Seitz radius. Hence, for wide enough strips these edge effects can be neglected and the graphene strips can be modeled with the same conductivity parameters as those of an infinite sheet33.Despite graphene sheets with gapless electronic band structures, one-dimensional graphene strips with finite width have been proposed to obtain tunable band gaps where the energy gap is controlled by the strip widthx-direction, we normalize the electromagnetic fields with respect to the phase as follows:x-direction and x-direction with period D.To start the analysis of a PAMGS and to consider its periodicity in Now we substitute Eq.  into Max34D and 34Next, we eliminate the longitudinal field components  in Eqs.  to obtaientclass1pt{minimas of Eq.  are discy-direction we put Besides, since there is no variation in the  in Eqs.  and 9)..y-directt refers to the matrix transpose, the solution to Eqs. (3434Using the definition  to Eqs.  and 14)\documentt refers to transverse components. In what follows, we investigate two special cases of normal and oblique incidence on a PAMGS using MoL.According to Maxwell’s curl equations 35 to obtain the field components in the correct position. Using the same definition for 8. Figure According to Fig.  in Eqs.  and 14)\documententclass1pt{minima of Eqs.  and 16)\documentg to Eq.  for the TE(H) and TM(E) polarized waves are investigated simultaneously. According to Fig. For the case of oblique incidence, the two particular cases of  in Eqs.  and 19)TE(H) andIn the analysis of a multilayer PAMGS as shown in Fig. i is the number of layer. On the other hand, By definitiontute Eq.  into Eq.To obtain the transmission coefficient of the structure we should transform the fields in the opposite direction from the input to the output as followsIn short, we considered graphene as an especial impedance boundary condition at the interface of two adjacent layers due to its 2D structure and computed the reflection coefficient transformation formula through the interfaces, accordingly. Other 2D materials including Group-IV monoelemental honeycomb materials and binary compounds of group III-V elements can be treated similarly provided that we can model them as an appropriate boundary condition.36. Then, a multilayer PAMGS as a tunable THz absorber shown in Fig. To validate the proposed method, the numerical results for two different PAMGSs are obtained and compared with those of other methods. As the first example, the Faraday rotation effect achieved by a PAMGS as shown in Fig. x-directed wave at normal incidence. In presence of a magnetic field bias, the direction of the transmitted electric field is deviated from that of the incident wave by angle 36y- and x-direction due to an x-directed incident wave, respectively.The PAMGS shown in Fig. 36On the other hand, the transmission efficiency is defined by36 and a commercial software as shown in Fig. Intel Core i7 8700K CPU, 32 GB RAM desktop computer while the MoL took less than 4 seconds on the same computer. As it is seen the three sets of results agree very well. According to Fig. The Faraday rotation angle and the transmission efficiency of the structure shown in Fig. Moreover, to investigate the effect of the chemical potential on reflectance and transmittance, the co- and cross-polarized reflectance and transmittance for different 6. This absorber is composed of a perfect electric conductor (PEC), a continuous graphene sheet (CGS), and the periodic array of graphene strips (PAGS). The PEC, CGS and PAGS are separated with an intermediate dielectric layer. The PEC is used to suppress the transmission and increase the absorption.The next example deals with a tunable THz absorber reported made of a multilayer PAMGS as shown in Fig.6 as shown in Fig. x-directed wave with normal incidence. As illustrated in Fig. To evaluate the efficiency and accuracy of the proposed MoL in analyzing this absorber with TE and TM polarizations is investigated. As shown in Fig. TE and TM polarizations are almost the same. As the result, this absorber can be referred to as a polarization independent absorber6.Next, the effect of incident angle on absorption for both TE and TM polarizations by multilayer periodic arrays of magnetically biased graphene strips (PAMGS). First, we discretized the governing equations in transverse directions concerning the periodic boundary condition using finite differences. Then, the reflection coefficient transformation approach was used to obtain the reflectance and transmittance of the multilayer structure analytically. Since the graphene parameters are discretized with finite differences in transverse directions, we set the surface conductivity to zero where graphene is absent. Hence, there is no need to introduce approximate boundary condition to model graphene. On the other hand, due to the semi-analytical nature of the method, there is no demand for the use of absorbing boundary conditions in the longitudinal direction unlike fully numerical methods. These advantages have made MoL a powerful computational tool for analyzing multi-layered graphene-based periodic structures. To validate the proposed method, numerical results for different PAMGSs are obtained using the proposed method and compared with those obtained by other methods reported in the literature. In all cases, the two sets of the results agree very well, which confirms the validity of the method. Analyzing 3D graphene-based periodic structures with 2D periodicity will be the subject of our future work.In summary, we used the semi-numerical, semi-analytical method of lines (MoL) for the efficient analysis of the plane wave scattering in the most general case of oblique incidence for both


The interest in theresearch of the structural and electronic propertiesbetween graphene and lithium has bloomed since it has been proventhat the use of graphene as an anode material in lithium-ion batteriesameliorates their performance and stability. Here, we investigatean alternative route to intercalate lithium underneath epitaxiallygrown graphene on iridium by means of photon irradiation. We growthin films of LiCl on top of graphene on Ir(111) and irradiate thesystem with soft X-ray photons, which leads to a cascade of physicochemicalreactions. Upon LiCl photodissociation, we find fast chlorine desorptionand a complex sequence of lithium intercalation processes. First,it intercalates, forming a disordered structure between graphene andiridium. On increasing the irradiation time, an ordered Li(1 ×1) surface structure forms, which evolves upon extensive photon irradiation.For sufficiently long exposure times, lithium diffusion within themetal substrate is observed. Thermal annealing allows for efficientlithium desorption and full recovery of the pristine G/Ir(111) system.We follow in detail the photochemical processes using a multitechniqueapproach, which allows us to correlate the structural, chemical, andelectronic properties for every step of the intercalation processof lithium underneath graphene. Among alkalimetals, lithium is especially interesting since, in addition to itscapability to engineer graphene doping,10 it bears direct technologicalapplications for graphene-based lithium-ion batteries.14 In that context, several strategies have appeared focusing on obtaininglithium-intercalated graphene as an anode material by chemical methodologies.11 Nanomaterials, and particularly crystallinecarbon materials, such as graphite or graphene, play a critical rolesince they present high mechanical flexibility (volume expansion)and higher electrical conductivity 17 and enhance the reaction/protection of the activematerial in batteries.18 Moreover, thecore processes happening in a lithium-ion battery (charge and discharge)are based on the rocking-chair19 or intercalationchemistry. Therefore, alternative routes allowing the intercalationof lithium underneath graphene as well as a detailed description atthe atomic level of the structures formed during the intercalationprocesses may be of interest in the field.Graphene (Gr) has been extensively studied over the past decade,In this work, wepresent a combined synchrotron-based X-ray photoemissionelectron microscopy/low-energy electron microscopy (XPEEM/LEEM) studyof the Li/Gr system. The combined use of diffracted low-energy electronsand photoelectrons allows us to follow in real time the chemical,structural, and electronic processes occurring during lithium intercalationthrough graphene. We show that LiCl thin films on top of a singlelayer of graphene grown on an Ir(111) substrate photodissociate uponexposure to soft X-ray photons. We observe rapid chlorine-ion desorptionand a sequence of rapidly evolving lithium intercalation processes.In the first stage, Li intercalates, forming an amorphous two-dimensional(2D) structure that successfully decouples graphene from the Ir(111)substrate. For increasing irradiation time, Li reorganizes below graphene,forming an intercalated (1 × 1) structure. Upon further extensiveirradiation, lithium diffuses into subsurface positions in the metal.220 Since the sample surface is homogeneous, wegenerally used the largest available aperture size of 10 μmdiameter for microspot measurements, having only occasionally employedthe 5 μm diameter one. For repeated or different measurements,the sample was moved to obtain a fresh area for each exposure cycle.Samples were prepared in an ultrahigh vacuum (UHV) chamber with abase pressure of 1 × 10–10 mbar. LiCl  was sublimated from a homemade Ta crucible annealedat 720 K controlled by a type-K thermocouple spot-welded to it withthe sample kept at room temperature. Ir(111) surfaces were cleanedby repeated cycles of argon-ion sputtering and annealing in an oxygenatmosphere (T = 1373 K and Poxygen= 2 × 10–8 mbar). To avoid anyresidual oxygen on the surface, the last cleaning cycle was carriedout without oxygen. Graphene was grown on a single crystal of Ir(111),crystallographic plane (111), in a decomposition process of ethylene.In the first step, ethylene (P = 1 × 10–8 mbar during 30 s) is adsorbed on the sample at roomtemperature (RT), and then the sample is flashed up to 1373 K for30 s. In the second step, the sample is exposed to a higher ethylenepressure (P = 1 × 10–7 mbar),again followed by thermal decomposition at 1373 K for 7 min.21All of the experiments have been carried out in the LEEM/PEEM experimentalend station of the CIRCE beamline at the ALBA Synchrotron.3hν = 136 eV, photonflux about 2.5 × 109 photons/s·μm2) activates the Li photochemistry and triggers the subsequent Liintercalation stages. Immediately after starting the irradiation,the LiCl layers start to photodissociate. During this photo-inducedreaction, LiCl dissociates, lithium reduces and intercalates, andchlorine oxidizes, presumably desorbing as Cl2, althoughwe cannot rule out the possibility of chlorine-ion desorption withoutrecombination. This leads to stage 2, which is obtained during thefirst 10–20 s of photon exposure and consists of an amorphousLi layer intercalated between graphene and Ir(111): Gr/a-Li/Ir(111).Because LiCl films are several monolayers thick, there is a gradualprocess of continuous intercalation that lasts for the first 100 s.When the coverage of intercalated Li reaches the monolayer (ML), lithiumorders in a Li(1 × 1) superstructure, resulting in stage 3: Gr/Li(1× 1)/Ir(111). After long irradiation times, 500–600 s,the LiCl thin film is completely photodissociated, and the next stageof evolution is reached. In stage 4, Li atoms penetrate into Ir(111)first few layers and adopt subsurface positions: Gr/Ir-Li/Ir(111).Stage 4 is the final stable stage observed in our experimental sessionsfor sufficiently long photon exposure times. It is therefore presumablythe most energetically favorable configuration while irradiating.In addition, we note that the pristine G/Ir(111) (stage 0) can berecovered from stage 4 by annealing the sample up to 900 °C.20 Thestructure evolution was followed by low-energy electron diffraction(LEED), the chemical evolution was tracked by X-ray photoemissionspectroscopy (XPS), and the band structure was measured with microspotangle-resolved photoemission spectroscopy (μ-ARPES). Althoughwe have used an ideal substrate to depict the process, the resultscan be extrapolated to other sp2-based materials, likegraphite, graphene on SiC, or free-standing graphene flakes, and morelikely to any other 2D van der Waals system.The full sequence of processes has been studiedin real time bya multitechnique in situ characterization in the PEEM/LEEM experimentalstation at the Alba Synchrotron.3.1Supporting Information Movie 1). All of the diffractionpatterns were measured at the same electron energy (65 eV) in realtime on the same sample, allowing a direct comparison between thedifferent irradiation stages. The largest illumination aperture (10μm diameter) was used in all cases. Control experiments showthat the low-energy electrons of the LEED alone have a negligibleeffect on the chemistry of LiCl films.22 In this pattern, iridium (blue arrow), graphene(black arrows), and the moiré spots are well resolved. In stage1, a thin film of LiCl is grown on the sample at room temperature;as a result, a new feature appears in the LEED pattern in the formof a ring (The diffraction patternof stage 0 is a flower-pattern structurearising from the moiré pattern observed on the pristine Gr/Ir(111)(t) zero, we start photon irradiationat 16° grazing incidence on the LiCl/Gr/Ir(111) sample. In thefirst 10–20 s, a dramatic change is observed in the diffractionpattern . Indeed, we observed a similar effect during intercalationof NaCl.22 Comparison of the evolutionwith and without X-ray irradiation demonstrates that the primary causefor LiCl dissociation and thus Li intercalation is the illuminationfrom the synchrotron, although we cannot fully rule out a small effectof the electron gun used for LEED, probably in the form of desorptionof a small fraction of LiCl. The detection of an intense graphenediffraction pattern and the absence of any moiré spots areclear signs of intercalation-induced decoupling.24 It has been reported that submonolayer lithium intercalationcan efficiently decouple graphene from the metal substrate, ironingout its corrugation.25 At stage 2, neitherthe Ir(1 × 1) spots nor any other Li-related features are resolved,pointing out the lack of crystallinity in the Li-intercalated layer.9At time (9 When Gr/Li(1 × 1)/Ir(111) is reached, thegraphene layer remains structurally decoupled from the metal surfaceand there are no moiré spots in the diffraction pattern. Inour experimental sessions, stage 3 lasts over 600 s of photon irradiationtime. During this long irradiation time, the background intensityaround the  spot gradually increases and finally the moiréLEED spots start to become visible. A sudden change at around 700s leads to stage 4  (1 × 1) spots (purple arrow) inthe diffraction pattern and 400 eV (Cl 2p and C 1s core levels), respectively. The photonenergy used to measure C 1s and Cl 2p is not the same as the one usedfor the lithium core-level and for the LEED studies presented above.Control experiments show similar evolution dynamics for both energies,suggesting that the photophysically induced processes are analogousin the X-ray energy range inspected here. 7/2 spectra are shown in Figure S1). The Ir4f7/2 core-level appears ata binding energy (BE) of 60.8 eV.26 Weresolve three different components for the Li 1s (27 The L2 componentintensity increases and shifts toward a lower BE (up to 55.2 eV) asthe Li-intercalated coverage increases up to the monolayer saturationcoverage and the system reaches stage 3 (Gr/Li(1 × 1)/Ir(111)).8 The L3 component also appears in the first stagebut dramatically increases in stage 4. We assign this component toLi atoms intercalated below the first iridium layers. At the end ofstage 3, LiCl has completely disappeared and the intercalated Li coveragesaturates but irradiation continues. As a consequence, Li atoms areforced to intercalate in subsurface positions, and the system wouldeventually reach stage 4, Gr/Ir-Li/Ir(111).25 The presence of the L3 component demonstrates that lithium is presentin the sample even though the LEED pattern resembles that of a cleanGr/Ir(111) system. Only after the high-temperature annealing (grayspectrum), all Li 1s components disappear and the structure, chemistry,and energy bands of pristine Gr/Ir(111) are recovered.Li 1s and Ir 4f28  to C atoms in the sp2 configuration and notea small shift (0.7 eV) toward a higher BE with respect to pristineGr/Ir (284.1 eV),25 which points toward an effectiven-type doping of graphene.8 At this stage,there is also a broad component (C1) at a higher BE that we assignto a combination of charge effects as a consequence of the insulatingLiCl film and the LiCl/Gr interface (mostly Li atoms interacting withGr). Component C1 is reduced drastically upon irradiation, disappearingcompletely at the end of stage 3 where no traces of LiCl can be detected.A smaller component (C2) appearing as a shoulder at a higher BE ofthe sp2 one (0.8 eV w.r.t. sp2) remains almostunperturbed during the evolution of the system and is related to then-doping of graphene. Such a component has been observed in the literaturefor graphitic systems interacting with lithium and other alkali metals.8 After annealing (gray spectrum) and recoveringstage 0, the C 1s peak shifts toward a lower BE and narrows, and onlythe sp2 component of graphene on Ir(111) is resolved.25Finally, we focus on the C 1score-level 3c. In st3.3hν = 136 eV), we trackthe changes in the band structure and therefore in the doping of grapheneacross all of the stages of evolution . All of thestructural and chemical changes introduced above will necessarilyhave a direct impact on the electronic band structure of the system.Using μ-ARPES , possibly due to electrostatic effectscreated by the insulating LiCl film  bands are completely recovered after annealing.In stage 0, the μ-ARPES energy cuts reveal the p-dopednatureof the Gr/Ir(111) system.4In summary, we present a methodto intercalate lithium at the graphene/iridiuminterface by photodissociation of an adsorbed LiCl thin film. A combinedcharacterization with LEEM, XPS, and μ-ARPES allows us to followevery step of the intercalation process in real time. We show thatupon photon exposure, LiCl dissociates, chlorine atoms desorb, andlithium intercalates graphene. This is evidenced by the changes ofthe diffraction patterns, the fast decrease of Cl 2p core-level intensity,and the evolution of the Li 1s peak. When the intercalated lithiumamounts to one monolayer, a 1 × 1 structure appears in the LEEDpattern. Finally, the process reaches a final state with lithium remainingin a subsurface position in the iridium substrate, as evidenced bythe lithium core-level signal and the LEED pattern. μ-ARPESmeasurements show a high n-doped graphene behavior from the beginningof the Li intercalation processes. As the intercalation process takesover, graphene bands evolve to an effective p-doped behavior. Thephoto-induced sequence does not damage the graphene layer, as evidencedby the fact that the Gr/Ir(111) original stage can be recovered uponhigh-temperature annealing. Our fundamental study contributes to abetter understanding of the Li intercalation process in graphiticmaterials upon photophysical methods, which may lead to new pathwaysfor the improvement of next-generation graphene-based anodes for lithium-ionbatteries.


Electronic medical records (EMRs) offer the promise of computationally identifying sarcoidosis cases. However, the accuracy of identifying these cases in the EMR is unknown.The aim of this study is to determine the statistical performance of using the International Classification of Diseases (ICD) diagnostic codes to identify patients with sarcoidosis in the EMR.index of suspicion to identify cases with a high index of suspicion for sarcoidosis (confirmed and probable) based on clinical and radiographic features alone using the American Thoracic Society practice guideline. Through medical record review, we determined the positive predictive value (PPV) of diagnosing sarcoidosis by two computational methods: using ICD codes alone and using ICD codes plus the high index of suspicion.We used the ICD diagnostic codes to identify sarcoidosis cases by searching the EMRs of the San Francisco and Palo Alto Veterans Affairs medical centers and randomly selecting 200 patients. To improve the diagnostic accuracy of the computational algorithm in cases where histopathological data are unavailable, we developed an high index of suspicion to identify confirmed sarcoidosis cases increased the PPV significantly to 100% (95% CI 96.5%-100%). Histopathology documentation alone was 90% sensitive compared with high index of suspicion.Among the 200 patients, 158 (79%) had a high index of suspicion for sarcoidosis. Of these 158 patients, 142 (89.9%) had documentation of nonnecrotizing granuloma, confirming biopsy-proven sarcoidosis. The PPV of using ICD codes alone was 79% (95% CI 78.6%-80.5%) for identifying sarcoidosis cases and 71% (95% CI 64.7%-77.3%) for identifying histopathologically confirmed sarcoidosis in the EMRs. The inclusion of the generated index of suspicion data elements could significantly improve the case-identification accuracy.ICD codes are reasonable classifiers for identifying sarcoidosis cases within EMRs with a PPV of 79%. Using a computational algorithm to capture  Sarcoidosis is a complex disease with an unknown etiology that can involve multiple organs, and no universal or standardized measures can fully secure its final diagnosis -3. In fastructured data, including billing codes such as the International Classification of Diseases (ICD) codes, laboratory test results, and procedural codes; and (2) narrative or unstructured data, including progress notes, pathology reports, and imaging reports. ICD codes cast a wider net to capture patients in the EMR because they include both inpatient and outpatient claims compared with other classifiers such as Diagnosis-Related Group that only capture inpatient claims [Data from electronic medical records (EMRs) are commonly used in research and by health care systems, including the United States Department of Veterans Affairs (VA), to predict outcomes or assess care quality . EMR datt claims . Unstruct claims ,7,8. A ft claims -13. Anott claims  but onlyt claims -17. Moret claims -24. For t claims , Bayesiat claims .As the first step in evaluating the knowledge gap in developing future sarcoidosis-specific “computationally identifying algorithms,” we designed this study (1) to estimate the statistical performance of using diagnostic codes (ICD-9 and ICD-10) alone compared with a new approach that uses additional information from radiology and clinical domains, but not histopathology, to inform the utility of these codes for performing clinical phenotyping of sarcoidosis cases in large EMR data sets of the VA and (2) to assess the computational challenges in querying sarcoidosis cases and extracting high-quality sarcoidosis-related research variables from the EMR accurately.This was an observational retrospective study of EMRs available through VA Informatics and Computing Infrastructure (VINCI). VINCI provides access to comprehensive and integrated veterans’ national deidentified data sets and offers the necessary computational and analytical tools in a secure, high-performance computing environment ,27. ThisWe searched the EMR data in VINCI from 1989 to 2019 and identified all patients coded as having sarcoidosis in the VA health care system, as defined by the documentation of the ICD-9 and ICD-10 codes of 135 and D86.x (including subcodes), respectively. Data were extracted through executing SQL queries in an SQL Server 2017 database. A total of 14,833 sarcoidosis cases were identified.lottery method to randomly select 100 patients from each site without a replacement [To determine the statistical performance of using diagnostic codes (ICD-9 and ICD-10) in identifying patients with sarcoidosis from the EMR, initially, we identified patients with at least one claim (inpatient or outpatient) of ICD diagnosis code for sarcoidosis. To ascertain the true diagnosis of sarcoidosis based on the ATS diagnostic criteria  , 2 clinilacement   based on clinical and radiographic information, regardless of the availability of biopsy data, and to assess whether this approach would improve the diagnostic accuracy. The index of suspicion was applied to the initial cohort of patients with ICD codes for sarcoidosis (n=200). The clinical and radiological features were extracted from the available structured and unstructured data without including the histopathology results. If the patients were documented to have one or more of these features, they were assigned to the high index of suspicion group Heerfordt syndrome Lupus pernio or erythema nodosumMaculopapular or erythematous skin lesions or nodulesFacial nerve palsySymmetrical parotid enlargementOptic neuritis, scleritis, uveitis, or retinitisLacrimal gland swellingEvidence of granulomatous disease on direct laryngoscopyHepatomegaly or splenomegalyShortness of breath, dyspnea on exertion, cough, dizziness, or chest painPulmonary function test with obstruction, restriction, or low diffusing capacity of the lungs for carbon monoxideCardiomyopathy, cardiac arrhythmia, or atrioventricular node blockHypercalcemia, hypercalciuria, nephrolithiasis, or abnormal vitamin D levelsElevated angiotensin-converting enzyme inhibitors or soluble interleukin-2 receptorsBronchoalveolar lavage lymphocytosisRadiologicalBilateral hilar lymphadenopathy Computed tomography chest with perilymphatic nodules tracking the peribronchovascular bundleDiffuse infiltrates  or computed tomography chest or chest radiograph with fibrosisCardiac magnetic resonance imaging or positron emission tomography–computed tomography consistent with sarcoidosisEnlargement or nodules in liver or spleen Magnetic resonance imaging brain with increased inflammationExtrathoracic enlarged lymph nodes sarcoidosis with confirmed biopsy. Patients with a high index of suspicion and either no documented biopsy in the EMR or a biopsy showing no histopathological evidence of nonnecrotizing granulomas were categorized into the group of sarcoidosis without confirmed biopsy (probable sarcoidosis). Finally, those with a low index of suspicion were categorized into the group of unlikely sarcoidosis  to determine whether the use of this index of suspicion could improve the PPV of identification of sarcoidosis cases in the EMR.Using the This approach provides more information than just relying on ICD codes alone to develop robust computational sarcoidosis-specific algorithms consistent with the recent ATS practice guideline recommendations.Organ involvement was assessed based on the clinical history obtained from physicians’ notes and imaging and biopsy reports available in the computerized patient record system. For this assessment, to adjust for the variability in providers’ documentation, we adapted a set of criteria previously introduced in the National Institutes of Health–sponsored Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study .We collected the following data from the chart review: clinical site, gender, race, ICD-9 and ICD-10 codes for sarcoidosis , the pathological diagnosis from any available biopsy, organ involvement as described in primary histopathological if the data were available in the pathology report domains and secondary if the data were available only in the clinical note domains because of either a remote history of biopsy or because the biopsy had been performed outside the VA. The PFT reports at the SFVA and PAVA used Crapo reference equations to calculate the lower limit of normal values for spirometry and lung volume measurements.Pathological diagnoses were categorized into multi-organ phenotype, which we defined as the involvement of ≥3 organs.Using the clinical data from chart abstraction, we classified the patients into the clinical phenotypes proposed by the GRADS study, with the exception of Organ and assessmentLungPositive lung biopsy and positive mediastinal or hilar lymph node biopsyChest x-ray, computed tomography (CT) chest, or positron emission tomography (PET) demonstrating bilateral hilar lymphadenopathy; CT chest with perilymphatic nodules tracking the peribronchovascular bundle; chest X-ray, CT chest, or PET with diffuse infiltrates; and CT chest or chest x-ray (CXR) with fibrosisPulmonary function test (PFT) with obstruction, restriction, or low diffusing capacity of the lungs for carbon monoxide (DLCO)SkinPositive skin biopsyLupus pernio and erythema nodosumEyePositive conjunctival or scleral biopsyOptic neuritis, scleritis, uveitis, or retinitisCardiacPositive heart or pericardium biopsyAtrioventricular node block (second or third degree)Cardiomyopathy responsive to treatmentCardiac arrhythmia Cardiac magnetic resonance imaging (MRI) or PET-CT consistent with sarcoidosisLiver or spleenPositive liver or spleen biopsyEnlargement or nodules in liver or spleen Abnormal liver enzymesNeurosarcoidosisPositive brain or dura or peripheral nerve biopsyClinical syndrome or symptoms consistent with central nervous system sarcoidosis along with a positive MRIEar, nose, and throatPositive biopsy from ear, nose, or throatDirect laryngoscopy consistent with granulomatous diseaseMulti-organ involvement≥3 organs involved based on other criteria in this tableindex of suspicion). We did not report the positive likelihood ratio, given that the specificity for using ICD codes alone could not be calculated because our study design did not include a review of noncases. The PPV for the criterion of using only the ICD code was calculated as the number of patients with an ICD code for sarcoidosis divided by the total number of patients verified to have sarcoidosis by chart review (gold standard). The PPV for the criterion of using the ICD codes and index of suspicion was calculated as the total number of patients with a high index of suspicion divided by the number of patients verified to have sarcoidosis by chart review (gold standard). The sensitivity of histopathology reports alone compared with chart review was calculated as the total number of patients with a high index of suspicion and confirmed biopsy divided by the number of patients verified to have sarcoidosis by chart review (gold standard). We computed 95% CIs using the exact binomial method. For our estimates, significance was defined as P<.05.All statistical analyses were performed with R software  using RStudio (version 1.2.5). Descriptive statistics were computed to summarize the data. Categorical variables were presented as the frequency in percentages, and continuous data were presented as means and SDs. We estimated the PPV of the two aforementioned computational diagnostic criteria for sarcoidosis  were identified with the ICD-9 code of 135 and 50 (31.6%) with the ICD-10 code of D86, and 142 (89.9%) had confirmed sarcoidosis based on histopathological evidence of nonnecrotizing granuloma and were classified as having sarcoidosis with confirmed biopsy; the remaining 16 (10.1%) patients with a high index of suspicion did not undergo a biopsy and were classified as having sarcoidosis without confirmed biopsy . Of the 200 patients, 158 (79%) had a P=.18). In terms of clinical phenotypes, 37.9% (60/158) had a multi-organ disease , followed by stage II or stage III treated . Our study cohort did not include any individuals with acute presentation . Some patients overlapped with multiple clinical groups.high index of suspicion to identify confirmed sarcoidosis cases increased the PPV significantly to 100% (95% CI 96.5%-100%) with 90% sensitivity of histopathology reports alone compared with chart review  for identifying sarcoidosis cases and 71% (95% CI 64.7%-77.3%) for identifying histopathologically confirmed sarcoidosis in the EMR. After chart review, the inclusion of the generated t review .index of suspicion to the initial cohort, we also demonstrated that including a high index of suspicion that incorporated information from radiology and clinical domains, but not histopathology, significantly increased the diagnostic accuracy to 100% (95% CI 96.5%-100%). The results of this study will help researchers and health care systems better understand the accuracy of using diagnostic codes alone versus using ICD codes with a high index of suspicion for sarcoidosis as classifiers in detecting a complex disease such as sarcoidosis in the EMR. Furthermore, the study highlighted other computational challenges in querying sarcoidosis cases and accurately extracting high-quality sarcoidosis-related research variables from the EMR. This approach could be adapted to develop automated chart review algorithms using additional data elements from structured and unstructured domains by applying advanced computational methodologies such as natural language processing (NLP) and machine learning.In this observational retrospective study of VA EMRs, we reviewed the medical records of 200 randomly selected patients with ICD diagnostic codes for sarcoidosis from the SFVA and PAVA medical centers . In thisThe randomly selected cohort of veterans in this study with sarcoidosis (with and without confirmed biopsy) consisted of 89.9% 142/158) of men and 10.1% (16/158) of women. Although the gender distribution in our study was different from that in A Case Control Etiologic Study of Sarcoidosis , it is c2/158 of Using ICD codes alone to extract health information is far more convenient than the time-consuming process of manually reviewing narrative data sets in unstructured data. However, using ICD codes to identify sarcoidosis cases in large data sets with thousands of patients poses several practical challenges. First, given the heterogeneity of sarcoidosis, it is challenging to efficiently confirm the presence of the disease. The verification process requires careful analysis of the available narrative data such as progress notes, imaging reports, and pathology reports to establish the case definition based on the sarcoidosis diagnostic criteria . Second,Moreover, there are no specific ICD codes for classifying the involvement of some organs in sarcoidosis  . Third, The definition of clinical phenotypes has become an essential goal for the sarcoidosis scientific community because genetic studies have identified different patterns of gene expression associated with disease severity and disease course ,41. In 2high-throughput phenotype algorithm using only structured data  and (2) a low-throughput phenotype algorithm that accesses structured and unstructured data to develop a sequential flowchart that should end with a case definition. Such a low-throughput approach uses high-performance computational tools such as NLP to process text and extract information using linguistic rules, thereby eliminating the need for a labor-intensive manual review by researchers [The two most applied approaches to defining computational phenotypes are (1) a earchers . Accordiearchers . Our stusecondary histopathological reports documented in the providers’ narrative within the clinical notes. This approach made the diagnosis of sarcoidosis less robust because the confirmatory biopsy reports in these patients could not be directly verified. However, we used the index of suspicion approach to define probable sarcoidosis cases regardless of whether a confirmatory biopsy report was available, which is consistent with the diagnostic algorithm recommended by the ATS practice guideline [multi-organ phenotype involved ≥3 organs, instead of ≥5 organs as proposed by the GRADS study [multi-organ phenotype. Lack of patients with involvement of ≥5 organs could be due to EMR-related limitations such as missing data and variability in documentation among providers or simply because these patients were cared for at non-VA tertiary medical centers. Third, the generalizability of our findings obtained from VA EMRs to other populations could be limited because the veterans form a special population with a different demographic distribution and exposure from the general population. However, the EMR data of the VA health care system cover >22 million veterans across the United States and >14,000 patients with sarcoidosis ICD diagnosis codes, providing an enormous number of patients to study a rare disease. Moreover, the number of patients whose records were examined in this study was 200, which could be considered a small sample size. However, we analyzed data from nearly two-third of all patients with diagnostic codes for sarcoidosis in the VA health care system across northern California.Our study includes several limitations. First, primary histopathological reports were not available for all the patients. In the cases where the biopsy report was unavailable (either because of a remote history of the biopsy or because the biopsy had been performed outside the VA), we relied on the uideline . Second,DS study . We chosindex of suspicion) from unstructured data could significantly improve the accuracy of case identification. Furthermore, to increase the efficiency of identifying sarcoidosis cases from large health care databases, more studies are required to develop a novel sarcoidosis-specific computational phenotype algorithm using automated emerging methods (such as machine learning and NLP). Moreover, our study sets the stage for promoting research on developing other such algorithms aiming to generate high-quality sarcoidosis-related research variables, such as determining the date of the diagnosis, organ involvements, Scadding stages, and the clinical status .Although ICD codes can be used as reasonable classifiers to identify sarcoidosis cases within EMRs with a PPV of 79%, using computational algorithms to extract clinical and radiographic information (


The effect of the size of nickel nanoparticles on the fabrication of a Ni–graphene composite by hydrostatic pressure at 0 K followed by annealing at 1000 and 2000 K is studied by molecular dynamics simulation. Crumpled graphene, consisting of crumpled graphene flakes interconnected by van der Waals forces is chosen as the matrix for the composite and filled with nickel nanoparticles composed of 21 and 47 atoms. It is found that the main factors that affect composite fabrication are nanoparticle size, the orientation of the structural units, and temperature of the fabrication process. The best stress–strain behavior is achieved for the Ni/graphene composite with Ni Graphene is a new two-dimensional 2D) structure  that is D structuperature ,5, to naperature ,7,8,9,10perature . Even a perature .The review by  containsLayered metal/carbon composites were also widely studied. In , it was The mechanical properties of layered graphene metal composites are strongly influenced by the graphene/metal interface. On the one hand, it can prevent the dislocations gliding, which reduces the strength properties of the composite. On the other hand, such interfaces can be a dislocation source in the metal matrix, leading to a degradation in mechanical properties or even failure ,27,28,29d strain ,36,37,38d strain ,40.Experimental production of carbon metal/graphene composites is a rather expensive and energy-consuming process. Since the structure peculiarities considerably depend on the experimental technique applied to obtain metal/graphene composite ,42,43, dIn most theoretical ,49,50,51In rly work . Taking z-axis to obtain a small flake. Graphene flakes filled with Ni nanoparticle were randomly rotated and translated x-, y-, and z-axes correspondingly to obtain 3D initial structure shown in The graphene flakes (GFs) initially were armchair carbon nanotubes , cut along the  results ,40.Periodic boundary conditions were applied in all directions. All of the simulations were conducted using the LAMMPS package with the AIREBO  interatoEquations of motion for the atoms were integrated numerically using the fourth-order Verlet method with the time step of 0.1 fs. A Nose-Hoover thermostat was used to control the system temperature under the NVT and NPT canonical ensembles (the substance amount (N), volume (V) or pressure (P) and temperature (T) are constant) when simulating the compression/tension of the structure and the annealing process, respectively.It was shown earlier by the authors of ,40 that x-, y-, and z-axes. The tension strain rate for each loading type was p= rotated so that the zigzag edges of the graphene flake extends along the I).In particle  and not I, II, III, and IV points in Annealing at 2000 K does not lead to a significant difference in the stress–strain state of the CG21 and CG47 composites: The process of fracturing the Ni/graphene composite after the ultimate tensile strength is achieved is shown on the example of GF filled with Nit 2000 K a–d. CarbFrom x-, y- and z-axes correspondingly after annealing at 1000 K (solid lines) and 2000 K (dashed lines) are presented together with the characteristic snapshots of the structure under tension. Only the main stress component . However, tensile stresses for CG47 after annealing at both temperatures have grown to the value of 120 GPa (points III and IV on the red curves).For the same reason, a difference of about 18% is observed in tensile stresses upon deformation of the CG47 composite after annealing at 1000 K and 2000 K at points x-axis, a gradual rearrangement of the graphene structure occurs due to the breaking of old bonds and the formation of new bonds between carbon atoms. As a result, the volume fraction of pores and voids remaining in the Ni/graphene composite CG47 after annealing at 1000 K significantly decreased and the structure of this composite under tension became almost identical to the structure obtained after annealing at 2000 K (see III and IV). This can explain the equality of stresses at points III and IV on the red curves. In this case, Ni atoms are evenly distributed throughout the CG47 composite. Comparatively, for the CG21 composite, Ni atoms are distributed inhomogeneously over the graphene surface during tension (see A and B), which inhibits the decrease in the volume fraction of pores due to the transformation of the graphene structure.Structural analysis showed that, during uniaxial tension along the sion see b A and Bx-axis. Atoms in blue show carbon atoms located along the zigzag direction of GF. Other graphene flakes after hydrostatic compression and annealing are oriented along the x-axis in almost the same way as in x-axis of the entire composite corresponds to the zigzag direction of graphene flake edge, which can lead to significant elongation of the obtained Ni/graphene structures to a strain of 3.5. As can be seen, bonds are straightened along x-axis before rved see d–f. In te formed f and amoy-axis and the corresponding snapshots of the structure at critical points. As for hydrostatic tension, an increase in the annealing temperature to 2000 K leads to an increase in the ultimate tensile strength for CG21 and CG47 by 15% and 23%, respectively , the stress/strain curves show a slow stress decrease.vely see a. A greavely see b; this cA, B, C, and D in y-axis . Tension of the composite results in a break in the carbon interatomic bonds . However, an increase in the annealing temperature to 2000 K leads to a significant increase in the ultimate tensile strength. The tensile strength for the CG21 (CG47) composite annealed at 2000 K is 72% (54%) more than that of the composite annealed at 1000 K. Such a large difference in tensile stress is associated with a decrease in the bulk porosity of composites with an increase of the annealing temperature.y axis, at ound see a–f.For correlation analysis, In x axis, and this direction coincides with the zigzag edge of the GF. It is known that the graphene strength along the zigzag direction is higher than that along armchair direction. Thus, the stress–strain curve for tension along the y-axis is lower for both composites. In the case of tension along the z-direction, a single flake is oriented by its open side. During compression, two edges of the initial flake can interconnect between each other and form something similar to a small nanotube. The fracture takes place along the armchair-type edge of this new structural element. However, it is the weakest direction since the edges around open side are not connected by covalent bonds and can be easily opened.The highest tensile stress value is achieved during uniaxial tension along the Composite CG21 exhibits better compression since the NiIn the structure with Nipression ,40,61. MFor all of the cases of uniaxial tension, structural amorphization occurred at The observed difference in the stress–strain curves in x-, y-, and z-axes.Molecular dynamic simulation is used to fabricate Ni/graphene composites with Nix, y, and z directions are very different. The most homogeneous structure is obtained for the CG47 composite after hydrostatic compression followed by annealing at 2000 K.It is found that all investigated composites have anisotropic strength properties. This is due to the fact that the volume fraction of pores and voids in the x-axis of composites annealed at 2000 K. In the process of uniaxial tension, the breaking of old and the formation of new covalent bonds took place, which led to the transformation of the graphene structure into an amorphous one. Thus, a high strain is achieved before the failure of the composites. At large strain, long mono-atomic carbon chains are formed with alternating double and triple bonds between carbon atoms.The best stress–strain behavior is observed under uniaxial tension along the It is found that, using hydrostatic compression followed by annealing at 2000 K, it is possible to fabricate a Ni/graphene composite; however, it is necessary to achieve a more homogeneous structure with a smaller volume fraction of pores and voids, which will lead to a decrease or complete disappearance in strength property anisotropy.


These findings establish the beginning of an atlas of endogenous L1 mRNA expression across a broad range of biological variables that will guide future studies.Expression of L1 mRNA, the first step in the L1 copy-and-paste amplification cycle, is a prerequisite for L1-associated genomic instability. We used a reported stringent bioinformatics method to parse L1 mRNA transcripts and measure the level of L1 mRNA expressed in mouse and rat organs at a locus-specific resolution. This analysis determined that mRNA expression of L1 loci in rodents exhibits striking organ specificity with less than 0.8% of loci shared between organs of the same organism. This organ specificity in L1 mRNA expression is preserved in male and female mice and across age groups. We discovered notable differences in L1 mRNA expression between sexes with only 5% of expressed L1 loci shared between male and female mice. Moreover, we report that the levels of total L1 mRNA expression and the number and spectrum of expressed L1 loci fluctuate with age as independent variables, demonstrating different patterns in different organs and sexes. Overall, our comparisons between organs and sexes and across ages ranging from 2 to 22 months establish previously unforeseen dynamic changes in L1 mRNA expression  L1 DNA , and Gf ,26–29. L, and Gf . L1 sequ, and Gf . Even th, and Gf . Here, wde novo L1 inserts  and 3 at 12.8 mo. Lungs were collected from 5 mice: 2 at 7.6 mo and 3 at 12.8 mo. Only testes and livers were collected from 6 additional mice: 2 at 1.9 mo, 1 at 3.6 mo, and 3 at 22.3 mo. Brains, lungs and ovaries were collected from nine mice: two at 2.2 mo, one at 3.2 mo, two at 8 mo, one at 8.6 mo, one at 8.7 mo and two at 16.5 mo. Uteri were collected from six mice: one at 2.2 mo, one at 8 mo, one at 8.6 mo, one at 8.7 mo and two at 16.5 mo. Testes, brains, livers, and lungs were collected from three rats, all 4.8 mo. Animals used in this study and their inclusion in downstream analyses is shown in 3 were bluntly dissected and then homogenized in 500–1000 ul of lysis buffer  to lyse the cytoplasmic membrane. The mixture was lightly homogenized in a Dounce homogenizer with an autoclaved B pestle, incubated on ice for 5 min and then centrifuged for 2 min at 1000 rpm at 4°C. Supernatant, containing the cytoplasmic fraction, was mixed with pre-chilled 7.5 ml of Trizol and 1.5 ml of chloroform and then centrifuged for 35 min at 4000 rpm at 4°C. The aqueous portion was transferred to 4.5 ml of chilled chloroform, mixed and centrifuged for 10 min at 4000 rpm at 4°C. The resulting aqueous portion was precipitated with 4.5 ml of isopropanol overnight at 80°C, centrifuged for 45 min at 4°C at 4000 rpm, washed with 10 ml of ethanol and re-suspended in RNase-free water.RNA was extracted as previously described . SpecifiCytoplasmic RNA samples were analyzed in an Agilent 2100 Bioanalyzer System according to the Agilent RNA 6000 Nano kit guide. Samples with RIN >8 were submitted for sequencing.Mus musculus 10 (mm10) or Rattus norvegicus 6 (rn6) genomes, and queried for alignments occurring within annotated L1 loci. Bioinformatics analysis was performed as previously described , which produces 150 bp read lengths, and Illumina sequencing, which produces 100 bp read lengths. We clipped 150 bp DNBseq sample reads to 100 bp and completed the analysis for the 150 bp reads and 100 bp reads in parallel to test whether these read length differences would affect the results. The analysis with different read lengths resulted in a difference of two authentically expressed L1 loci between the groups with 150bp reads producing 14 expressed L1 loci and 100bp reads producing 12 expressed L1 loci. For samples sequenced using Illumina sequencing, samples were pooled in groups of 5–7 and applied to a single lane of an Illumina HiSeq 2500/4000 instrument. Data were sorted based on barcodes attached to each individual sample, aligned to either the escribed . These mThe annotation for full-length L1 elements was downloaded from the L1Base 2 database , includiThe annotation for full-length, intact and non-intact L1 elements was downloaded from the L1Base 2 database  and intef, Gf, and A subfamily sequences, each containing two subfamily-specific promoter monomers. The paired-end alignment was performed using STAR v2.3.0e, allowing two alignments and 25 mismatches per read pair. Reads that aligned to the promoter regions in the sense orientation were included in our analysis of discarded reads. RSEM v1.2.31 was used to measure the expression of genes containing L1 loci and total RNA levels  . As the Mus musculus whole genome sequencing and ERR224469 for the Rattus norvegicus whole genome sequencing. Then we used the Bowtie1 alignment program to assign whole genome reads that mapped uniquely to the Mus musculus 10 (mm10) or Rattus norvegicus 6 (rn6) genomes . As. As68). t-test when making comparisons between two groups. Chi-square tests were used when comparing categorical groups. To measure linear correlation between two variables, Pearson correlation test was performed. Statistical analysis was performed with GraphPad Prism.Data are presented as mean with standard error bars. Data were analyzed by two-tailed Student's We previously reported a stringent, custom-designed strategy for aligning and validating L1 mRNA reads originating from full-length L1 loci . For thiThe second key element in our strategy was the inspection of each potentially expressed L1 locus in the Integrated Genome Viewer (IGV)  to confif, Gf, and A  and expressed 11 L1 loci at a higher level than any locus from the other organs . Testes also exhibited higher levels of expression at individual L1 loci. For example, L1 locus UID-5948  had the highest expression in testes with an FPKM of 3.05. In livers, the highest expressed L1 locus was UID-6143 with a 0.037 FPKM. In brains, the highest expressed L1 locus was UID-5181 with a 0.24 FPKM. In lungs, the highest expressed L1 locus was UID-6870 with a 0.83 FPKM. These data demonstrate that there is as much as a 100-fold difference in the expression levels of the highest expressed L1 loci among male organs of the same individual mouse, with testes being the highest and liver supporting the lowest levels of expression   Figure .We compared specific expressed L1 loci between male organs. We found substantial overlap in expressed L1 loci between the same organs collected from different mice. Among all organs analyzed in this study, testis exhibited the greatest degree of similarity with 85% of testes loci (346 loci) shared between all three animals Figures . Liver sIn contrast to this high number of shared L1 loci expressed in the same organs from different individuals, there was minimal overlap between organs collected from the same male mouse. Of the combined 461 L1 loci expressed by all male organs considered, none (0%) were shared by all four organs in any of the mice, four (0.8%) were shared between testis and brain in six mice, 1 (0.2%) was shared between testis and lung in five mice and 1 (0.2%) was shared between testis, brain and liver in six mice Figure .Female organs showed greater heterogeneity of expressed L1 loci than male organs. Of the 34 L1 loci expressed in ovaries, only five L1 loci (15%) were shared by all four samples. Of the 28 L1 loci expressed in uteri, only three loci (10%) were shared by all three samples. Of the 47 L1 loci expressed in female brains, 10 loci (21%) were shared by all four samples. Of the 30 L1 loci expressed in female lungs, 10 (36%) were shared by all four samples Figure . Similarf and Tf subfamilies, the youngest and most active of the mouse L1 subfamilies . The percentage of expressed L1 loci in testes belonging to the Tf subfamily was significantly higher than livers, male lungs, ovaries, female brains and female lungs . The higher numbers of expressed young L1 subfamily members in testes indicate that loci expressed in the testes are more likely to participate in active retrotransposition . The 135 L1 loci uniquely expressed in the 7.6 mo group accounted for 8.57 FPKM (20.6%) of the 41.56 FPKM for total L1 expression observed at 7.6 months . 22.3 mo testes expressed significantly more L1 loci on average than the 12.8 mo group with the 22.3 mo group expressing on average 134 more L1 loci than the 12.8 mo group . Of the 471 L1 loci expressed in testis of all age groups, 168 (36%) were shared between all age groups . Although a low number of expressed L1 loci was detected in livers collected from male mice of all age groups, livers collected from 7.6 mo male mice expressed an average of four more L1 loci, compared to the 1.9–3.6 mo age group . 12.8 mo livers expressed on average three fewer L1 loci than the 7.6 mo age group . 22.3 mo livers expressed on average two more L1 loci than the 12.8 mo age group  and three more than the 1.9–3.6 mo age group . In addition to the increase in the number of expressed L1 loci in brains of older female mice, total levels of L1 expression also increased from an average of 1.25 FPKM in the 2.2 mo group to 3.47 FPKM in the oldest age group  = 3.864, P = 0.05, X2 = 8.8147, P = 0.0029)  = 8.809, P = 0.0024, X2 = 20.219, p < 0.00001) . Thus phase   . 7.6 mo 0.00001) .2 = 9.9157, P = .00703). Similarly, the 21 expressed L1 loci shared between the 16.5 mo female age group and the 12.8 mo male age group is significantly greater than the two expressed L1 loci shared between the 2.2 mo female age group and the 1.9–3.6 mo male age group  = 29.6273, P < 0.00001). Taken together, this finding demonstrates that L1 loci expression is sex-specific and remains so with age even though there is a 10-fold (2–21 loci) increase in the number of shared L1 loci between sexes with age.We have demonstrated that L1 loci are expressed in an organ-specific manner in both male and female mice Figure . To deteX2 = 7.311, P = 0.007, females chi square, X2 = 16.27, P = 0.00006, X2  = 33.9183, P < 0.00001, We compared expression patterns of L1 loci between male and female organs of the same type and age group to better understand L1 mRNA expression in different sexes. Lungs collected from 8–8.7 mo females and 7.6 mo males expressed 30 and 23 L1 loci, respectively, and shared 4 (8%) expressed L1 loci Figure  and male2  = 23.2185, P < 0.00001, X2 = 12.9833, P < 0.0003, females chi square, X2 = 7.3134, P = 0.007, We also compared expressed L1 loci between male and female brains at different ages. Brains collected from 8 to 8.7 mo females and 7.6 mo males expressed 47 and 29 L1 loci, respectively, and shared 13 (21%) expressed L1 loci Figure  and malet-test, brains, P = 0.0006; lungs, P = 0.0001).Our analysis of L1 mRNA expression in mice identified hundreds of expressed L1 loci, allowing us to begin to understand what distinguishes L1 loci that are expressed from those that are not. We next investigated whether intragenic L1 loci are more likely to be expressed. First, by intersecting the genomic coordinates of expressed L1 loci with the known gene coordinates in the mm10 genome downloaded from the UCSC Genome Browser, we identified intragenic, expressed L1 loci and their orientation relative to genes Figure . We founr(92) = –0.1, P = 0.3), we did find that all genes, except one, that contain an expressed L1 locus are also expressed. Thus, gene expression provides a critical favorable environment, but does not determine L1 expression strength.Next, we considered whether expression of intragenic L1 loci correlated with expression of the genes in which they were present. We plotted L1 FPKM levels alongside the FPKM of their corresponding gene expressed in testes collected from 7.6 mo mice Figure . AlthougWe performed transcriptomic profiling of our RNA-sequencing data to identify potential mechanisms contributing to the observed patterns of L1 mRNA expression in testis because mechanisms governing L1 mRNA expression are numerous and complex . We usedt-test, P < 0.0001) and 12.8 mo testes   Figure . Quantif) Figure  and the ) Figure  revealed) Figure  and B. Ht-test, P = 0.01). This is despite the fact that we also observed upregulation of the basal transcription factors pathway in 7.6 mo testes with 25 of 33 basal transcription factors pathway genes upregulated in 7.6 mo testes compared to 1.9–3.6 mo testes and 30 of 33 basal transcription factors pathway genes upregulated in 7.6 mo testes compared to 12.8 mo testes , we compared the ‘mappability’ of L1 sequences in rn6 and mm10 genomes. This allows us to measure the likelihood of finding unique alignments for RNA-seq reads originating from L1 mRNA transcripts in mice and rats. The ‘mappability’ of L1 sequences in the rn6 and mm10 genome assemblies were calculated by aligning rattus norvegicus and mus musculus paired-end DNA sequencing reads to the rn6 or mm10 genome using the same bowtie alignment parameters utilized in our RNA analysis pipeline . We then plotted the number of uniquely mapped DNA reads to each L1 locus in the mm10 and rn6 genome assemblies , brains , or lungs   Figure . This an) Figure . L1 loci) Figure  and 8C.Calculating mappability correction section of the Materials and Methods. Normalizing to the ‘mappability’ of each locus did not change our comparison of L1 expression between organs and the mappability-corrected FPKM values for mouse testes remained significantly higher than mouse male livers, male brains, male lungs . This difference made us wonder how variability in L1 locus mappability may influence the ability to align L1 reads to unmappable regions and measure L1 FPKM levels between samples. To address this question, we corrected our RNA-seq FPKM values for differences in mappability to observe whether mappability differences between loci would alter our conclusions. We mappability-corrected FPKM values from our male mouse RNA-seq analysis by scaling the number of aligned reads for each locus to 400 reads, the average number of reads for a fully ‘mappable’ L1 locus, and multiplying the number by the original FPKM value . This eqin vivo unresolved (Detection of full-length L1 mRNA from individual loci is critical to understanding their impact on the host including potential to damage genomic DNA. To detect and measure L1 mRNA, methods used must be able to distinguish not only which locus is expressed, but whether that expression arises from the L1 promoter and is not a passive product of read-through transcription ,34,39,41resolved . Even meresolved . Additioresolved . In thisresolved .in vivo analysis of L1 mRNA expression in multiple organs from 18 mice also found that the number of L1 loci differs greatly between organs, with mouse testes expressing significantly more L1 loci (i.e. 409 L1 loci expressed in testes versus 7 L1 loci expressed in liver, Figures Patterns of L1 mRNA expression at the single-locus resolution are remarkably consistent within an organ, with testes from different mice sharing 85% of expressed L1 loci, male livers sharing 71%, male brains sharing 65%, male lungs sharing 52%, ovaries sharing 15%, uteri sharing 10%, female brains sharing 21%, and female lungs sharing 36%. Figures . Our in r = 0.1030, Figure in vivo and in cell lines (If the sequence or epigenetic architecture of genomic domains is responsible for L1 regulation, we would expect that expressed L1 loci would be enriched in the vicinity of expressed genes that might result in the overall domain being more active. The fraction of expressed L1 loci found in genes is quite variable among organs (10–63%, Figure ll lines ,33–35 arde novo somatic integration event (Although similarities in L1 mRNA expression between organs of the same type are not surprising based on previous findings ,33,34, ion event ,102. HowThe ability to monitor changes in both the levels of L1 mRNA expression and numbers of expressed L1 loci allowed us to discover unique and dynamic variations that occur with age in different organs. We found that L1 mRNA expression and the number of L1 loci expressed can change independently with age Figure . Testes In addition to differences between organs and ages, we found that the levels and patterns of expressed L1 loci exhibited sex-specific differences. Male and female mice shared significantly more expressed L1 loci with their respective sex, compared to the L1 loci shared with the opposite sex . The numFocusing only on reproductive organs, male testes share 85% of expressed L1 loci while ovaries and uteri share only 15% and 10% of expressed L1 loci, respectively Figure . We consOverall, we found that expression of individual L1 loci in rodents is strikingly organ specific, with a strong level of sex specificity, establishing the first atlas of endogenous L1 mRNA expression in male and female mice. In addition, there are distinct patterns of increased heterogeneity in expression at different ages in different organs. Our cross organ, sex, and age comparisons establish a baseline of endogenous L1 mRNA expression under normal conditions that can be utilized to understand the potential of these elements to create differential DNA damage in different tissues with age or environmental exposures. Our findings set the stage for identifying mechanisms that permit expression of some but not other L1 loci and mechanisms that govern sexual dimorphism in L1 mRNA expression. These studies also permit comparative exploration of L1 mRNA expression patterns in other L1-harboring organisms to understand the roots of its evolutionary conservation or diversity.http://genome.ucsc.edu/cgi-bin/hgTracks?db=mm10&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr12%3A56694976%2D56714605&hgsid=1015816353_RetTob8ARYR2ZUoUuEvAidjg9sZH and rn6, http://genome.ucsc.edu/cgi-bin/hgTracks?db=rn6&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr1%3A80608553%2D80639261&hgsid=1015816387_WqXYk74yEffaVVS0vEHi5DAjFxPO.The raw data files and analysis files for RNA-seq in this manuscript are available through GEO: GSE158831. The aligned RNA-seq files are available through the following UCSC genome browser links: mm10, gkab369_Supplemental_FilesClick here for additional data file.