Extinction learning, the process of ceasing an acquired behavior in response to altered reinforcement contingencies, is not only essential for survival in a changing environment, but also plays a fundamental role in the treatment of pathological behaviors. During therapy and other forms of training involving extinction, subjects are typically exposed to several sessions with a similar structure. The effects of this repeated exposure are not well understood. Here, we studied the behavior of pigeons across several sessions of a discrimination-learning task in context A, extinction in context B, and a return to context A to test the context-dependent return of the learned responses . By focusing on individual learning curves across animals, we uncovered a session-dependent variability of behavior: (1) during extinction, pigeons preferred the unrewarded alternative choice in one-third of the sessions, predominantly during the first one. (2) In later sessions, abrupt transitions of behavior at the onset of context B emerged, and (3) the renewal effect decayed as sessions progressed. We show that the observed results can be parsimoniously accounted for by a computational model based only on associative learning between stimuli and actions. Our work thus demonstrates the critical importance of studying the trial-by-trial dynamics of learning in individual sessions, and the power of “simple” associative learning processes.The online version contains supplementary material available at 10.1007/s10071-021-01521-4. Extinction learning is also relevant during therapy and other learning settings, where, for example, patients are trained to withdraw undesired behaviors, or when children are required to suppress recurrent spelling mistakes.Animals modify their behavioral repertoire based on the consequences of their own actions. Whether a certain behavior is reinforced or not, respectively, increases or decreases the likelihood that this behavior is repeated in a similar situation Skinner . This prAlthough extinction may involve some erasure of the previously acquired memory  of unknown sex and age obtained from private breeders were used as subjects in the present experiment. Birds were housed in individual wire-mesh cages or local aviaries within a colony room. The housing facilities were controlled for light cycles (12 h light/dark cycles starting at 8 am), temperature, and humidity. All animals had ad libitum access to water and were kept between 80 and 90% of the free-feeding body weight. The food deprivation was necessary to keep the animals engaged in the experimental procedures. All animals were treated in accordance with the German guidelines for the care and use of animals in science. The experimental procedures were approved by a national ethics committee of the State of North Rhine-Westphalia, Germany and were in agreement with the European Communities Council Directive 86/609/EEC concerning the care and use of animals for experimental purposes. Pigeons were part of an electrophysiological experiment in which single units were recorded over multiple sessions of learning. Prior to session onset, we checked whether neural signals were present and could be isolated on the channels. If so, the animals were tested and a behavioral session was generated. In the results section, pigeons were enumerated according to the number of sessions they contributed: 1–3 (26 sessions), 4 (23 sessions), 5 (22 sessions), 6 (13 sessions), 7 (11 sessions), and 8 (6 sessions).Eight experimentally naive, adult pigeons  OnFinally, the renewal-test phase was used to study the return of the learned choice when the context was switched back to the acquisition context A Fig. a. Importk), and expressed them as a proportion of the total number of trials (N) in that phase (response rate = k/N). To assess the significance of a response count k, we calculated the probability p(k) of obtaining at least k responses by chance in N random trials under the null hypothesis. Since responses to the extinction stimulus are not rewarded during the extinction and renewal-test phases, our null hypothesis assumes unbiased random responses, such that each one of the three possible outcomes  can occur with probability 1/3. If the probability of observing at least k responses by chance was below a threshold of 0.05, we regarded the count as significant. This method, however, overlooks those cases where a non-significant number of responses are arranged in a chain of persistent responses, which is also unlikely to occur by chance. To consider those cases, we also measured the length L of the longest chain of persistent responses found on a specific phase, and calculated the probability p(L) of obtaining a chain of at least L trials by chance in N random trials. Finally, the choice behavior was regarded as significant, if one of the aforementioned tests yielded a p value below 0.05. We also used this measure to quantify the prevalence of a target response, which was defined as the proportion of animals expressing a significant number of target responses in a given session. To quantify the dependency of these response measures on the session number, we calculated the rank-order correlation (Spearman’s r) between session number and both preference and prevalence. Since the number of animals contributing with data gradually decreased with session number, we grouped the data in blocks encompassing a comparable number of data points: sessions 12–23 in blocks of two sessions (9–12 data points per block), and the data from sessions 24 to 26 in one single block (9 data points). The rank-order correlations (Spearman's r) between the session number and the preference/prevalence of a particular response across animals was obtained from the grouped data unless stated otherwise. The p values accompanying the reported correlations correspond to a t test for the significance of the respective correlation coefficient (r).To quantify the preference for a target choice in a given phase, we counted the corresponding responses , and the behavioral transition is considered abrupt. Otherwise, the behavioral transition is considered smooth.To visualize the behavior in response to a specific stimulus within single sessions, we plotted the cumulative record of responses to that stimulus as a function of trial number. For each trial, the choice behavior of the animal, namely, omissions, alternative choice, and learned choice, was encoded as 0, −1, and 1, respectively. To assess the presence of abrupt transitions of behavior upon the onset of the extinction phase, we focused on the responses to the first five presentations of the extinction stimulus under context B. In this case, our null hypothesis is that animals continue to emit the learned choice with at least 80% probability required to accomplish the acquisition phase . Thus, if animals emit at least three non-reinforced choices  within the first five trials of the extinction phase, the null hypothesis is rejected . ReLU(x) = 0 if x < 0, and ReLU(x) = x if x ≥ 0. The behavioral choice corresponds to the motor unit with the highest activation in the presence of a given stimulus and contextThe model consists of a simple network that associates sensory input with two motor outputs (triangles), one each for the left (L) and right (R) responses Fig. . Binary If the total input (synaptic plus noise) to both motor units is equal or lower than 0, no response is selected, resulting in a choice omission.i with motor unit j, If a reward is delivered upon responding, excitatory connections between the active sensory units and the responding motor unit are reinforced. Otherwise, excitatory connections remain unchanged. Conversely, when a reward is not delivered, inhibitory connections between the active sensory units and the responding motor unit are reinforced. Otherwise, inhibitory connections remain unchanged. The value of the synapses  are updated according toλe) were set to 0.02. The learning rate of inhibitory connections (λi) was set either to 0.005, 0.01, or 0.02. This was a way to test the effect of three different ratios of inhibitory/excitatory learning rates. All synaptic weights saturated at a value of 20. All synaptic weights were initialized to zero, except for the excitatory weights corresponding to the familiar control stimuli, which were initialized at their saturation value to model the extensive experience that animals had with the familiar stimuli prior to training on the novel stimuli and their near perfect performance. As the familiar stimuli are never subject to extinction, their corresponding inhibitory weights were initialized to zero. The results depicted in Figure S3 correspond to a simplified version of the protocol, where only one extinction context was used, and the familiar stimuli were omitted, to demonstrate the principles of operation of the model more clearly. All other simulations included the two familiar stimuli and two extinction contexts, as described in Fig. For simplicity, all the synapses in the pigeon models had the same parameters: the learning rates of all the excitatory connections to motor units  during the extinction phase . This indicates that animals successfully learned the correct mapping between the novel stimulus and the pecking side repeatedly. During the 2nd half of the extinction phase, on the other hand, the low expressions of learned choices show that animals successfully extinguished the learned association in context B. Again, this behavior was also not significantly correlated with session number . Upon return to context A, the preference for the learned choice reemerged when the extinction stimulus was presented in the absence of reinforcements, which constitutes the ABA renewal effect. Indeed, the proportion of learned choices during the renewal testing phase was significantly higher than during the second half of extinction in 14 out of the 18 session blocks analyzed . We note that in individual pigeons, the strength of the renewal effect was variable . Furthermore, the largest response rates for the learned choice during renewal test occurred within the first four sessions for every individual pigeon , except for two individual animals . In spite of this weak correlation to session number, we nevertheless observed that the prevalence of the alternative choice was not evenly distributed across sessions . To confirm this asymmetry, we also compared every other session to all the remaining sessions, and found no significant difference in the proportions .Figure p < 0.05; z test; stars in Fig. p > 0.05; z test; Fig. In our experiment, extinction of one of the novel stimulus–response pairings could have led to a general bias against the response and/or the context that was associated with this extinction learning. Such biases could be driven, for example, by the fact that during the extinction phase, the response and the context associated with the extinction stimulus are rewarded at a ratio of 1:2 relative to the other options. To control for these generalization effects, we also analyzed the responses in the presence of the novel and familiar control stimuli that were presented in interspersed trials Fig. b. In ourA general response bias against the response associated with extinction learning would lead to increased pecking on the other side, which we classified as alternative choice. There indeed was a slight significant increase in the alternative choices in response to the Fam-ipsilateral control in 10 of the 18 blocks . According to this criterion, 39% of the sessions exhibited such abrupt transitions.Another puzzling aspect uncovered by the bipolar encoding were the abrupt transitions upon the onset of the extinction phase. According to a widespread view of extinction learning, as animals experience a withdrawal of reinforcers upon the onset of context B, they initially persist on the previously reinforced choice for several trials before gradually changing their behavior towards omissions Nevin , 2010. IFour extinction types and their session to session variability. So far, we have identified two remarkable features of extinction learning, namely, the preference for the alternative choice, and abrupt transitions of behavior upon the onset of the extinction phase. Based on the presence or absence of these features, we arranged the learning curves in four classes, and then assessed the prevalence of these classes across pigeons and sessions .ons Fig.  to see wons Fig. a1. The mons Fig. a4. Next,ons Fig. b. To getses Fig. c. Curvesses Fig.  to deterCan associative learning account for the observed behavioral complexity? So far, we have reported three key findings in our behavioral data: (1) Smooth transitions of behavior at the onset of context B are more prevalent during the first exposure to the extinction task than in later sessions. (2) During extinction, pigeons express a preference for the alternative choice intermittently across sessions, most prominently in the first session. And (3), the renewal effect appears intermittently in individual pigeons, but shows an overall decay as sessions progress. To study the mechanisms underlying these phenomena, we implemented a parsimonious model aimed at capturing the associative aspect of the task , which allowed us to test the effect of three different ratios of inhibitory/excitatory learning rates , where we used a simplified version of the protocol consisting of only two stimuli and one context. In a nutshell, the model embodies three core assumptions: (1) that context and stimuli can both drive and inhibit a given response in parallel, (2) that drives are upmodulated by the presence of reinforcements, whereas inhibitions are increased when reinforcements are absent, and (3) the response with the strongest net drive is expressed. As this model is subject to repeated sessions of learning and extinction, a gradual build-up of drivers and inhibitors within and throughout sessions ensues. Here, we aim at describing an extinction scenario where, under the same context, some previously learned stimulus–response mappings continue to be rewarded (our control stimuli) but one is not (our extinction stimulus). Since stimuli are session-unique, but context and responses recur in multiple sessions, previously established context–response drives and inhibitions can be carried over subsequent sessions, and thereby bias the responses to new stimuli presented in the same context. Thus, once the first session is completed, two processes with different time-scales will compete in the upcoming sessions: a fast process triggered by the previously established context–response mappings, and a slow process of learning the new stimulus–response mapping. The fast process can drive an abrupt change of behavior upon a context switch, but the larger the number of trials, the stronger the effect of the slow cumulative process becomes. More specifically, within extinction sessions, negative associations between context B and the learned choice are established due to the absence of reinforcers. Conversely, positive associations between context B and the contralateral response are also established during the interspersed trials where the control stimuli are presented, and their learned responses still rewarded. Together, these associations act synergistically to tilt the balance in favor of the alternative choice. As sessions progress, the associative strengths maintaining this imbalance saturate quickly, favoring the expression of alternative choices during the first session. The prevalence of smooth transitions during the first session can be explained as follows: upon the first exposure to the extinction phase, negative associations between the context and specific motor responses require several trials to build up  Upon the onset of the extinction phase, pigeons tended to persist on the learned choice mostly during the first session, whereas abrupt transitions of behavior emerged exclusively in later sessions. (2) During extinction, the expression of alternative choices in individual pigeons appeared intermittently from session to session, most prevalently in the first session. And (3), the renewal effect in individual pigeons was also intermittent and variable, but its strength and prevalence decayed as sessions progressed. To reveal potential mechanisms of this behavioral variability, we used a computational model to show that associative learning, in combination with an instantaneous winner-takes-all decision process, can reproduce the aforementioned features observed in the data.Experimental paradigm and methodology. There are several aspects in our paradigm that differ from previous studies of repeated extinction. These differences allowed us to focus both on the expression of alternative behaviors during extinction and the dynamics of the renewal effect. First, our discrimination-learning task comprises more than one operant response , in contrast to previous studies that used a single response key  might have been concealed by averaging in the previous studies . Under uncertainty , animals might simply opt for the response that is most often rewarded, which is the alternative choice for the extinction stimulus. This is particularly the case during the initial phase of the first extinction session, where animals experience for the first time that the previously learned responses to the extinction stimulus are no longer rewarded. At some point during the extinction phase, the animal has collected enough evidence that pecks to the side contralateral to the learned response for the extinction stimulus are more often rewarded than the ipsilateral responses. Therefore, the contralateral response would be the most “reasonable” to go for under uncertainty . The fact that alternative choices occur more often during the first sessions than in later ones is consistent with this view. As animals need to be exposed to at least one session to “understand” the structure of the task, repeated extinction reduces the uncertainty and, hence, the proportion of alternative choices. While this apparently “rational behavior” is consistent with our data, this interpretation is not necessary, since this pattern of behavioral changes emerges in a simple associative learning model.Yet another possibility to explain some of our results would be in terms of learned equivalence Below is the link to the electronic supplementary material.


The composite material prepared with the two-step stir casting method showed significant hardness and high melting point attributes. Scanning electron microscopy (SEM), along with energy dispersive X-ray spectroscopy (EDS) analysis, indicated 83.65%, 17.32%, and 97.00% of boron carbide + 0% graphene nanoparticles chemical compositions for the C-atom, Al-atom, and B4C in the compound studied, respectively. The physical properties of all samples’ B4C–G like density and melting point were 2.4 g/cm3 density and 2450 °C, respectively, while the grain size of B4C–G was in the range of 0.8 ± 0.2 µm. XRD, FTIR, and Raman spectroscopic analysis was also performed to investigate the chemical compositions of the B4C–G composite. The molding press composite machine was a fabrication procedure that resulted in the formation of outstanding materials by utilizing the sintering process, including heating and pressing the materials. For mechanical properties, high fracture toughness and tensile strength of B4C–G composites were analyzed according to ASTM standard designs. The detailed analysis has shown that with 6% graphene content in B4C, the composite material portrays a high strength of 134 MPa and outstanding hardness properties. Based on these findings, it is suggested that the composite materials studied exhibit novel features suitable for use in the application of shielding frames.In this work, boron carbide and graphene nanoparticle composite material (B The industry requires those functional materials which can sustain extreme conditions and perform dependably for the shielding frame. Several studies have been conducted to investigate the chemical and mechanical characteristics, and the hardness of B4C material. Subramanian et al. [4C and suggest its use in the shielding industry due to its low density and notable hardness. The mechanical properties and microstructure of B4C–G platelet composites were also investigated. The highest toughness mechanisms for the increased fracture toughness are crack deflection, crack branching and crack bridging [4C nanoparticles were synthesized through a carbon thermal process for successful photo-electro catalytic hydrogen generation activity in water reduction [4C nanoparticles were prepared from ball milling, and their potential use as a novel agent in T-cell-guided boron neutron capture therapy, were investigated [4C nanoparticles was also reported by a solid-state thermal reaction in a conventional high-temperature furnace reactor [4C manifested the high-density twin structure. The computational studies on B4C oxidation suggest B4C degradation can be manipulated to directly influence global bundle degradation  4C–G nanoparticles were studied in detail and exhibited enhanced strength and chemical bonding. The Raman spectra and XRD results for boron carbide reveal that the carbon atoms in all samples were preferentially substituted by taking boron atoms, and the atoms’ effective distances at the end of the B4 units was shorter than that of C–B–C atom chains, which can cancel out the increased bonding length affected by B substitution [Furthermore, the percentage of chemical components in the experimental material’s chemical composition is in the range of 0.2–0.4%, and the purity of boron carbide is within the range 97–98% according to standard ASTM C750-18 . In thistitution . Boron atitution . The achtitution .4C composite studied has shown strong suitability for shielding frames due to its improved hardness, and its high melting (2450 °C) and boiling points (3500 °C). Furthermore, graphene-based composite materials are of high interest to researchers due to their considerably good physical, microstructure, chemical, mechanical, and morphological properties. The challenge is to show the effect of the nanoparticles during the preparation of the studied materials. In the mechanical formation process, the mixing of graphene into the B4C was undertaken in a steel molding press to obtain composite shielding materials that could be used in a shielding frame. All of the properties of the composite materials are discussed in this work.This research study’s novelty is that it refers to B4C, which is among the most promising shielding material and in high demand for novel applications in the shielding industry. By incorporating the newest technology, high shielding proficiency can lead the way to numerous new applications. The B4C in powder form was used with boron and carbon, whose percentages fell within the range 78–81% and 17–22%, respectively, according to the Sigma Aldrich material specifications. The B4C specimens were synthesized in the experimental laboratory facilities provided by Majmaah University. A sufficient and pure grade of fixed B4C, typical element size: 0.2 µm concentration >98%) and formless boron  powders were synthesized by roll milling to make B4C–G nanoparticles. Based on ASTM standards, a fabricated pressing machine was then used to investigate the B4C–G mechanical properties. The crystal structure of the B4C used was rhombohedral with an average grain size of about 0.8 ± 0.2 µm. Multilayer graphene was added to the boron carbide by constant percentages from 0–0.6% according to the main specifications of the ASTM WK56764 [In this work, B WK56764 .4C–G prepared nanoparticles was performed in an air furnace at graphene absorption concentrations of 0%, 0.2%, 0.4%, and 0.6%. The process was completed in two hours, with the maximum temperature of the furnace raised to 160 °C. In the next step, the carbonization was achieved by raising the temperature to 1200 °C in nitrogen with a 10 Psi pressure for 2 h . In this process, 0% oxygen content was used to avoid engaging the materials in a leaching process, as that would have affected the result, its differentiation between the heat treatment process of the solubility, and the chemical composition.The calcination process of the B4C particles on the mechanical and physical properties of four base composite samples was examined using B4C of 0, 0.2, 0.4, and 0.6 wt % of graphene. All samples were prepared and tested at the laboratories of the College of Science at Majmaah University. A two-step stir casting method was used to make the composite samples. The composite was squeezed into solidification for 5 min with a squeezing pressure of 89 MPa, using a hydraulic press (YKC Series H-type Fin Press Line). The cast samples were later heated to 300 °C for 3 h for stress release, and then allowed to cool in the air. The stir casting and squeezing systems utilized are presented in The effect of B4C with different nanoparticle content. The SEM images have a visibility feature to define the high porosity level of all the boron carbide B4C/micro-size graphene samples. This analysis has fully observed low and dense sintering at low temperatures during the forming of boron carbide B4C and graphene particles. The scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) measurements were performed using a field emission scanning electron microscope (FE-SEM)—JEOL Model (JSM-6500). MEYEB specimens’ fracture surfaces were glazed in gold (8 nm thick), which enabled scanning by using an ion beam sputter coater Hummer VII, and maximum resolution images (below 2 µm) were obtained. 16-kV beam energy was used on the specimens (roughly 2.5 mm thick) in the internal chamber with continuous vacuuming. SEM spectroscopy was used to measure the nano- or micro-particles size in the morphology of the material’s chemical components, and to measure the powders’ micro-grain structure size . SEM ima2 detectors used for measuring. The detector has a 115 eV at Mn-Kα resolution. The X-ray peaks were collected from the pre-specified points on the sample to view its appearance with the maximum 13 kV SEM electron beams. X-ray diffraction and particle size analyses has been carried out for the B4C powder in detail. The X-ray energies were detected with high accuracy and improved resolution. In order to minimize the noise level and recognize closely packed X-ray peaks, the accepted practice is to specify the EDS resolution at Mn-kα . EDS was performed on the SEM, including AMTEK EDAX, Model (Octane), with 40 mmThe Raman spectroscopy technique is an excellent tool for examining microelement structures. The Raman analysis was undertaken using a Kaiser Model (Holo-Pro) spectrograph built-in a (CCD) camera from Princeton Instruments. It functioned at 967 nm by using a 35 mW power supply as the excitation source. The laser light was focused on the fibers and then back dispersed at 180 °C and recorded by an f/1.5 collection lens. The crystal orientation intensity peaks were obtained according to the average from 10 samples. The lower and higher frequency regions were observed in terms of the Raman bands ratio . The str4C–G samples. The measurement started at around 36 °C and was ramped up to 420 °C in a platinum pan. FTIR analysis was concluded using a Bruker spectrometer. Infrared spectra were detected in the wavenumber range of 500–4000 cm−1.Fourier transform infra-red (FTIR) spectroscopy is a beneficial tool for defining chemical interaction through the annealing of B4C–G. The chemical composition of the aluminum wire used, and the percentage composition breakdown between B4C and graphene, are demonstrated in Standard specimens were prepared according to ASTM D3039-17, and the computer control universal testing device model MTS (E45) manufactured in the US was utilized, which has a tensile speed rate of 0.2 mm/min at room temperature. The four samples were tested for tensile and hardness for B4C–G, according to standard ASTM D3039-17 [The thickness of the tensile test specimen significantly affected the selection of the sample configuration, and the tensile test sample’s main dimensions. The standard methods have been classified as the configuration of tensile test specimen according to the application’s thickness, such as sheet, plate, pipe, and composite structures. D3039-17 . The gauD3039-17 .4C material is one of the hardest and most brittle materials that suffers from brittle fracture behavior under certain operating conditions. Therefore, the indentation fracture toughness test was the most suitable method for predicting the fracture toughness, and the KIC for boron carbide material-based hardness test according to standard ASTM C1327-15 [The fracture toughness test is a simple technique used to define the fracture toughness of brittle materials compared with traditional methods of measuring a specimen’s toughness. BC1327-15 . The maiP is the applied load, and d is the average length of the two indentation area diagonals for the Vickers indenter. The Vickers’ indentation area and the length of the diagonals’ indentation area was d1 and d2. The configuration of the indentation area plays an essential role in determining the hardness values. The acceptable and the unacceptable regions according to the Vickers indenter can accurately portray the prediction of a hardness test according to ASTM C1327-15 [Moreover, a variation in specimen thickness does not affect the hardness value. It increases the accuracy for measuring the hardness values, and the standard test recommended is to use at least five to ten specimens in each hardness test. The Vickers hardness test method was used to calculate the hardness of boron carbide according to Equation (1) as follows:P is the load used, E is Young’s modulus or modulus of elasticity from the tensile test, the diagonal length of the indentation area is 2a, the Vickers hardness, Hv, and crack length is 2c.In this work, the indentation fracture toughness of boron carbide was calculated according to Equation (2) :(2)Kic=04C small particles in the base matrix, and it clearly shows no voids or discontinuities. 4C composite and B4C–G with 0.2% of graphene content examined under 500 µm magnification, respectively. The effect of grain size was not prominent for the lower concentration of graphene doping, that is, below 0.2% treatment, particularly at the nanoparticles’ surface. For B4C composite specimens, at the higher graphene concentrations of 0.4% and 0.6%, the nanoparticle size was observed to be in the range of 30–50 µm. The composite specimens with high graphene concentration showed a surface improvement, as demonstrated in 4C, which led to increased transport properties in the materials.The composite microstructure developed was observed using a scanning electron microscope (SEM). The resulting micrographs confirm a uniform distribution of B4C formed during graphene nanoparticle treatment did not increase B4C particle thickness in the morphology in all SEM images with particle size ~30 µm. B4C retained its small particle morphology even after undergoing the process. The nanostructure aging enhanced the mechanical properties, as discussed in the mechanical analysis section. The effect of the light from electrons is clearly shown in The nanoparticles decreased systematically with increasing graphene concentrations, as shown in 4C–G nanoparticles are illustrated in 4C + 0% graphene nanoparticle composite specimen was observed to be pure material without treatment in the EDS spectrum. In the observed spectrum, the impurity element weight of C and Al were 79.12% and 7.83%, respectively, as shown in The SEM merged with EDS analysis is a powerful tool for material characterization. The EDS analyzer is highly useful for many applications due to its ability to identify continuous material shrinking dimensions, and several other elements in composite specimens. In EDS mapping analysis, the amount of penetrated electrons directly relates to the X-ray signals. The SEM + EDS results for the B4C) and the graphene component. Boron was not detected for two reasons: the boron has very low, about 0.18 keV, energy at nearly zero, and the EDS analysis scale was not detected. Secondly, due to the heat treatment’s high temperature of 1200 °C, this carbonized all samples, which could have led to boron being hard to detect. As shown in 4C–G composites were detected by utilizing XRD analysis, as shown in 4C. Graphene nanoparticle peaks were observed at low intensity for the composite specimens, with a low percentage content of graphene. XRD patterns of specimens with 0.2 and 0.4% of graphene content revealed the presence of a characteristic peak for graphene (002) at 22.34° with a d-spacing of 2.78 Å, as shown in 4C phases for the rhombohedral crystal (PDF No. 35-0798) [4C structure can be described in terms of a hexagonal lattice with a (0001) axis, which is in correspondence with the (111) axis in the rhombohedral lattice structure [XRD pattern B35-0798) . The bastructure . It dedi4C and graphene. At a high loading of graphene nanoparticles, the diffraction peak for boron carbide was observed to disappear, and only diffraction peaks representing the presence of graphene were observed. Various other investigators observed carbon atom peaks in the boron carbide matrix [e matrix ,23. Carbe matrix .4C initially, with no graphene content on the sanded specimen in the strain testing where probes were attached at the laboratory. Additionally, in −1 and 1580 cm−1, and the small peak, was observed at 2700 cm−1, indicating that during the sintering process, the graphene structure was not distorted [4C and graphene. The boron carbide crystal lattice consisted of rhombohedral systematic alignment made up of the 12-atom, which are icosahedra, and 3-atom were linear chained as per peaks, as shown in RAMAN spectroscopy was used in this study to obtain the morphology of the crystals at the microscale level. In this technique, the laser beam is incident on the specimen, which is then reflected back at 180 degrees and is detected by the f/1.5 mm focal length of the collection lens. RAMAN spectra were observed for specimens of boron carbide and graphene composites, with different ratios of graphene as a reinforcement, that is, 0%, 0.2%, 0.4%, and 0.6%. In istorted . There w4C and graphene composite has a perfect rhombohedral crystalline structure. The peaks  shown in 4C, and also the vibrations observed  due to icosahedra. In −1, indicating the layered nature of graphene nanoparticles in the B4C and graphene nanoparticle composite. A defect in the graphene nanoparticles (GNPs) is indicated at 1702 cm−1 by a shoulder near the G band. In the composite, a relatively lower band of G indicates the overlapping of the GNPs. 2-D graphene nanoparticles tend to align perpendicularly when high pressure is applied during sintering. The D/G ratio is so high due to the purity of B4C + 0% graphene. The Raman peaks at 1880 cm−1 (D band) are essential features of crystalline graphitic structures. The Raman spectrum of B4C 0% Graphene nanoparticles can be divided into three ranges: a range with three sharp peaks at 297, 350, and 915 cm−1 and a range of 250–1500 cm−1 with broad peaks. The Model (Holo-Pro) grating spectrograph disperses the light scattered into several frequency apparatuses and distinguishes them with the (CCD) array detector. In the strain sensing test, the specimen was sanded at locations where the probes were attached. The Raman spectra resulted in the diffraction peak, which could be moved and observed with increasing B4C and graphene ratio [The B−1 was acquired from FTIR analysis in which the chemical bonding peaks were observed. The peak observed at 1021 cm−1 showed the presence of a C-O bond stretching at 0% graphene nanoparticles, as shown in −1 in both curves, that is, for 0% graphene nanoparticles and 0.2% graphene nanoparticles, showed the presence of a C–H bond. However, after calcination with the graphene nanoparticles, an aromatic peak at 1600 cm−1 was observed for the C=C bond, which indicated the graphene molecules’ presence and signified the absorption of water molecules. The peak observed at 1043 cm−1 was due to the C-O groups stretching [−1 is due to the B–C functional group stretching. The presence of a high content of C might have increased the B–C stretching frequency [Fourier transform Infrared spectroscopy was utilized in this research to study the effect of annealing temperature on the chemical interaction of Boron carbide with different ratios of graphene nanoparticles . A broad FTIR spectrum in the range of 500–4000 cmretching . However4C on the mechanical properties of B4C was examined based on the tensile analysis of B4C/graphene nanoparticle composites. The tensile properties in terms of (a) yield strength, (b) tensile strength, and (c) modulus of elasticity for graphene nanoparticles reinforced composite specimens, along with the same reading for a composite specimen with 0% graphene nanoparticles content, was ascertained. The tensile analysis demonstrated an increase in tensile strength from 85 MPa to 98 MPa by incorporating only 0.2% of graphene nanoparticle content in the boron carbide matrix, as displayed in 4C also contributed significantly to upgrading the composite shield material’s tensile properties. Furthermore, the uniform dispersion of graphene nanoparticles enabled the transfer of load efficiently from the B4C matrix to graphene nanoparticles, and the high mechanical load-bearing ability of graphene nanoparticles increased the overall tensile properties of the composites, based on the ability to add different percentages of graphene nanoparticles, which increased the overall tensile properties of the composites [The mechanical properties of composites are of great significance for their potential use in the application of shielding frames. The impact of the addition of 0.2%, 0.4%, and 0.6% of graphene nanoparticles in Bmposites ,28.4C, and the elastic modulus values followed an increasing trend with the increase in the loading of graphene nanoparticles. A composite specimen manifested the maximum value of elastic modulus (84 MPa) with 0.6% of graphene nanoparticle content. The elastic modulus results clearly demonstrate the addition of graphene nanoparticles [4C, can efficiently and effectively reinforce the B4C matrix, which corresponds to the considerable increase in the modulus elasticity of composites. The elastic modulus values in GPa units were also acquired for all the composite specimens, along with yield stress and tensile strength values. A prominent increase in the elastic modulus values was observed by adding graphene nanoparticles in Barticles . Retaini4C had an effect on fracture toughness, which was also investigated. The fracture toughness results shown in 4C–G nanoparticle composites. The fracture toughness values acquired in terms of hardness by the Vickers Indentation Fracture (VIF) test are reported in kg/mm2 in 2. The composite specimen with 0% graphene content manifested a fracture toughness value of about 14 kg/mm2. The value for fracture toughness with the incorporation of 0.2% of graphene nanoparticle content reached 24 kg/mm2, and this increase highlights the toughening mechanism of graphene in the boron carbide matrix. The high level of graphene nanoparticle dispersion and distribution in the brittle matrix can absorb the crack propagation energy, and lead to the maximization of the toughening mechanism thanks to graphene’s structural configuration [Incorporating graphene nanoparticles in the Bguration .At high graphene nanoparticle content, that is, 0.4% and 0.6%, a continuous increase in the fracture toughness value was observed. The fracture toughness of all the composites was higher than the composite specimen with no graphene nanoparticles. This is due to the frequent occurrence of crack propagation-toughening mechanisms resulting from the graphene presence with 2D sheets of C-atom in honeycomb configuration . The pro4C–G samples were systematically analyzed in detail using XRD, FTIR, SEM-EDS, Raman spectroscopy, and mechanical analysis. It was found that B4C is among the most promising shielding materials and is vitally necessary for novel applications in the shielding industry. By substituting the graphene content in the B4C, extraordinary thermal and mechanical stability in the B4C–G composite was observed. Moreover, a graphene composition of 6% delivered the highest and strongest tensile strength of 134 MPa and yield strength of 87 MPa. The fracture toughness test also showed an increase in strength from 14 to 42 kg/mm2 with increasing doping content from 0% to 6%, respectively. Interestingly, the grain size was observed to decrease with an increase in graphene content in the B4C composite. This could have resulted from de-oxidation of the B4C–G samples  at 6% graphene content. RAMAN spectroscopic analysis suggests the B4C–G composite has a rhombohedral structure, and the highest peaks were observed at 188, 720, 813, 978 and 1068 cm−1. The boron has very low, about 0.18 keV, energy—nearly zero. The pristine B4C structure studied using RAMAN and XRD analysis has an affirmed rhombohedral structure, which is consistent with previously reported XRD results, and affirms the validity of these findings. B4C–G at 6% graphene dopant has shown qualities superior to the B4C composite and could be useful as a strong shielding material. B4C + %Graphene composites were prepared through fabrication, and under heat treatment, acted as a significantly enhanced shielding frame. Boron carbide has a wide solubility range, but its mechanical and microstructure response effects have shown good results.In conclusion, B


Polycrystalline graphene grown by chemical vapor deposition (CVD) is characterized by line defects and disruptions at the grain boundaries and nucleation sites. This adversely affects the stretchability and conductivity of graphene, which limits its applications in the field of flexible, stretchable, and transparent electrodes. We demonstrate a composite electrode comprised of a graphene/silver nanowires (AgNWs)/graphene sandwich structure on a polydimethylsiloxane substrate to overcome this limitation. The sandwich structure exhibits high transparency (>90%) and excellent conductivity improvement of the graphene layers. The use of AgNWs significantly suppresses the conductivity loss resulting from stretching. The mechanism of the suppression of the conductivity loss was investigated using scanning electron microscopy, atomic force microscopy, and lateral force microscopy. The results suggest that the high surface friction of the sandwich structure causes a sliding effect between the graphene layers would produce low crack or hole formation to maintain the conductivity. In addition to acting as conductive layers, the top and bottom graphene layers can also protect the AgNWs from oxidation, thereby enabling maintenance of the electrical performance of the electrodes over a prolonged period. We also confirmed the applicability of the sandwich structure electrode to the human body, such as on the wrist, finger, and elbow. Ie: ~84%) ,23. HoweAlthough various transparent graphene-based electrodes have been explored ,25,26,27−1 was used as a reference for wavenumber calibration prior to each measurement. The transmittance of the samples was measured using UV-Vis spectroscopy . Atomic force microscopy  was employed to measure the lateral force and observe the surface morphologies, which were also characterized using a field emission scanning electron microscope . The samples were strained using a custom uniaxial strain rig equipped with current-voltage measurements  on the Pt electrodes to measure the in-situ electrical resistance during stretching. The electrical resistance variations were calculated as0 is the electrical resistance before strain.Raman spectra were collected using a Horiba Raman system (iHR-550) with a wavelength of 532 nm. The Si peak at 520 cm−1) and a 2D-band (ca. 2680 cm−1) were clearly observed representing the sp2-hybridized C-C bonds, while the D-band (ca. 1345 cm−1) representing atomic defects in graphene was almost invisible. The intensity ratio (I2D/IG) of the 2D- to G-bands was all above 2.0 (see 2D/IG of 1.29 (see −1 (G band) and 2675 cm−1 (2D band) indicates the existence of graphene on the PDMS substrate [0/r0, where r is the electrical resistance after exposure to ambient conditions for 18 h, and r0 is the initial electrical resistance. It can be clearly seen that the resistance of AgNWs/G without graphene atop significantly increased by ~80% owing to the formation of silver oxide on the surface of the AgNWs, as shown in the SEM image in the inset of Before the preparation of the G/AgNWs/G sandwich structure, the quality of the CVD-grown single layer graphene (SLG) and double-layer graphene (DLG) were investigated using Raman and UV-Vis spectroscopies. A total of nine locations of a 3 cm × 3 cm graphene sheet were measured see . The Ram 2.0 see . The ave 2.0 see . Those r1.29 see  lower th1.29 see  which waubstrate . The bluubstrate ,38. The ubstrate ,40. By a0)/R0 under various tensile strains, as shown in The stretchable properties of the SLD, DLG, and sandwich structure were evaluated using the electrical resistance variation  and a significant resistance reduction of 85% in the CVD-grown SLG. In addition, the structure exhibited excellent long-term stability of the electrical properties under atmospheric conditions. The SEM and LFM results revealed that the high surface friction force induced a sliding effect owing to the presence of the AgNWs to release the strain stress, resulting in considerably less crack formation. The area of cracks and holes of the sandwich was only 43% of that of SLG. Therefore, the conductivity of the sandwich structure can be maintained during stretching. Finally, we demonstrated the potential applicability of the sandwich structure in wearable devices. The results revealed an inherent electrical stability, even after 100 stretching cycles on the human joints.


Thanks to their reduced size, great surface area, and capacity to interact with cells and tissues, nanomaterials present some attractive biological and chemical characteristics with potential uses in the field of biomedical applications. In this context, graphene and its chemical derivatives have been extensively used in many biomedical research areas from drug delivery to bioelectronics and tissue engineering. Graphene-based nanomaterials show excellent optical, mechanical, and biological properties. They can be used as a substrate in the field of tissue engineering due to their conductivity, allowing to study, and educate neural connections, and guide neural growth and differentiation; thus, graphene-based nanomaterials represent an emerging aspect in regenerative medicine. Moreover, there is now an urgent need to develop multifunctional and functionalized nanomaterials able to arrive at neuronal cells through the blood-brain barrier, to manage a specific drug delivery system. In this review, we will focus on the recent applications of graphene-based nanomaterials in vitro and in vivo, also combining graphene with other smart materials to achieve the best benefits in the fields of nervous tissue engineering and neural regenerative medicine. We will then highlight the potential use of these graphene-based materials to construct graphene 3D scaffolds able to stimulate neural growth and regeneration in vivo for clinical applications. Nanotechnology is a multidisciplinary field that involves the manipulation of novel materials at the nanometer scale to obtain specific properties and functions and to design innovative devices suitable for medical science and biology as well as engineering or physics applications.Those materials that measure between 1 and 100 nm at least for one of their dimensions can be termed “nanomaterials”, and they show remarkable distinction in their physicochemical fundamental properties in comparison with the bulk of the same materials. The shape is crucial to their properties; thus, two different shapes of the same materials can lead to different features. Moreover, the increased surface area per unit mass plays a key role in increasing chemical reactivity by about 1000-fold .2 hybridized carbon atoms covalently bonded together in the same planar monolayer  matrix with graphene nanoplatelets composites has been developed that is able to enhance the matrix electrical conductivity. In fact, primary cortical neurons plated on these innovative scaffolds showed a significant increase in the neuronal network interplay and activity, suggesting considerable potential for targeting therapies for neural disorders . In an iDue to the increase in the utilization of graphene-based materials, the assessment of biocompatibility, stability, and toxicity evaluation is a fundamental aspect. In Vivo testing of biocompatibility is a critical step in regeneration approaches. Graphene nanomaterials can be biocompatible or have toxic effects on cells, depending on their chemistry , doses, lateral size, purity, and hydrophilicity. In Vitro evaluation of toxicity required the involvement of macrophages, epithelial or endothelial cells, blood cells, or tumor cells . GO, forThe damage on humans and tissue can be also caused by the generation of reactive species, such as oxygen-free radicals. This kind of nanotoxicity has also been investigated in the zebrafish model, wherein the administration of GO induced adverse effects on development with an increase in oxidative stress . For G t2 after photocatalytic reduction or near-infrared light [The levels of toxicity of rGO/GO are affected by chemical functionalization, as shown by PEGylated GO, in which the cytotoxicity decreased, as well as in two-dimensional material coated with bovine serum albumin . Anothered light ,110. In G has been employed in a huge field of applications, and the regeneration of nervous system tissue is one of the most complex and attractive, providing the possibility to treat neurological disorders and understand their underlying mechanisms. Repair of central nervous system injury is a big challenge today, and many aspects must be taken into account to design a scaffold based on a biomaterial that can provide support to cell growth and induce tissue regeneration without inflammatory reactions.Several nanomaterials are suitable for neural growth but do not match all the characteristics required for an ideal scaffold. This limitation can be overcome by functionalizing the biomaterials and creating a composite with a gain of advantageous features.Graphene and its derivatives are still today the most promising nanomaterials for the regeneration of the nervous system. Indeed, graphene is a novel carbon-based material with extraordinary and unique nanostructure and characteristics. In fact, it is characterized by excellent mechanical, thermal, and electrical properties. Interestingly, it is also able to provide a better replacement for current nanofillers in polymer matrices. Thanks to their properties, graphene-based nanomaterials have shown high versatility, and they have been considered some of the most promising tools in the promotion of tissue regeneration, both for in vitro and in vivo applications. However, due to its limitations already discussed in the previous section, there is an urgent need to examine its mechanism of action in more depth. It is well documented that different formulations of nanomaterials are able to provide very similar results in terms of proliferation and differentiation. At the same time, small changes in scaffold formulation may lead to completely different developments. Accordingly, it would be useful to carry out a systematic study to analyze the repercussion of different nanomaterial compositions on proliferation and differentiation. Scientists researching the roles of each nanomaterial in depth will be able to perform an accurate comparison; as a result, on the basis of the specific characteristics of each scaffold, they will develop a finer rational design.The biological platforms that can be created with graphene and derivatives, due to their versatility in all its meanings, exhibit their therapeutic potential by exploiting the synergistic effect of different signals, such as topographical and chemical/biochemical cues. The shape, surface area, roughness, and stiffness are crucial to provide not only support to cell growth but to guide differentiation towards a specific lineage, and it is possible to increase these effects using biomolecules to functionalize the G surface to obtain an optimized and ideal device for complete and accelerated tissue regeneration. However, the path leading to the production of commercialized nanomaterials is long and involves exceeding limits presented by the current prototypes.


Background: Several studies using bronchoalveolar lavage fluid (BALF) reported that lung microbial communities were associated with the development and clinical outcome of idiopathic pulmonary fibrosis (IPF). However, the microbial communities in IPF lung tissues are not well known. This study is aimed to investigate bacterial microbial communities in lung tissues and determine their impact on the clinical outcomes of patients with IPF.Methods: Genomic DNA extracted from lung tissues of patients with IPF  and age- and sex-matched controls (n = 20) was amplified using fusion primers targeting the V3 and V4 regions of the 16S RNA genes with indexing barcodes.Results: Mean age of IPF subjects was 63.3 yr, and 65% were male. Alpha diversity indices did not significantly differ between IPF patients and controls, or between IPF non-survivors and survivors. The relative abundance of Lactobacillus, Paracoccus, and Akkermansia was increased, whereas that of Caulobacter, Azonexus, and Undibacterium decreased in patients with IPF compared with that in the controls. A decreased relative abundance of Pelomonas  and Azonexus  was associated with a diagnosis of IPF in the multivariable logistic analysis adjusted by age and gender. Multivariable Cox analysis adjusted for age and forced vital capacity (FVC) revealed that higher relative abundance of Streptococcus , Sphingomonas , and Clostridium  was independently associated with IPF mortality. The relative abundance of Curvibacter (r = 0.590) and Thioprofundum (r = 0.373) was correlated positively, whereas that of Anoxybacillus (r = −0.509) and Enterococcus (r = −0.593) was correlated inversely with FVC. In addition, the relative abundance of the Aquabacterium (r = 0.616) and Peptoniphilus (r = 0.606) genera was positively correlated, whereas that of the Fusobacterium (r = −0.464) and Phycicoccus (r = −0.495) genera was inversely correlated with distance during the 6-min walking test.Conclusions: The composition of the microbiome in lung tissues differed between patients with IPF and controls and was associated with the diagnosis, mortality, and disease severity of IPF. MUC5B), telomerase function (TERT), or immune responses  (Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrosing interstitial lung disease of unknown etiology . It is cd IL1RN) , 3, 7. Md IL1RN) –11, and d IL1RN) , 13. Thed IL1RN)  also sugn = 65), compared with controls (n = 44), is associated with a 10% decline in forced vital capacity (FVC) at 6 months and mortality (n = 40) showed very low bacterial abundance in IPF lung tissues that was similar to that of negative controls  gene sequencing , severalcontrols . These cn = 20; 10 non-survivors ) were aseptically obtained at the time of surgical biopsy for diagnosis, and those from age- and gender-matched controls  with no histological evidence of disease collected aseptically at the time of surgery were obtained from the Bio-Resource Center of Asan Medical Center. None of the patients with IPF or the controls had been treated with antibiotics, steroids, anti-fibrotic agents, or probiotics within 1 month before undergoing surgery. Lung tissues were procured under protocol #2016-1366. This study was conducted in accordance with the Declaration of Helsinki (2013) and was approved by the Institutional Review Board of Asan Medical Center (2018–1096). Written informed consent was obtained from all study participants.All participating patients with IPF were diagnosed between January 2011 and December 2013 at Asan Medical Center, Seoul, Republic of Korea and met the diagnostic criteria of the American Thoracic Society (ATS)/European Respiratory Society/Japanese Respiratory Society/Latin American Thoracic Association statement  determined by plethysmography and diffusing capacity for carbon monoxide (DLco) measured according to published recommendations are expressed as ratios (%) of normal predicted values –25. The Tissue samples were frozen in liquid nitrogen immediately after collection and stored at −80°C. Genomic DNA was extracted from lung tissues using Mo Bio PowerSoil® DNA Isolation Kits  according to the instructions of the manufacturer. The variable V3 and V4 regions of the 16S rRNA genes were amplified using the following specific forward and reverse primers with overhang adapters: 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACG GGNGGCWGCAG-3′ and 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVG GGTATCTAATCC-3′, respectively . The PCRhttp://ccb.jhu.edu/software/FLASH/), were used for 16S rRNA gene by merging pairs of reads when the original DNA fragments were shortened than two times the length of the reads (http://weizhongli-lab.org/cd-hit-otu/). Short reads  were filtered out and extra-long tails were trimmed. After filtering, the remaining reads were clustered at 100% identity. Chimeric reads  were filtered, and secondary clusters were recruited into primary clusters. After excluding reads with all other noise , the remaining reads  were clustered algorithm into OTUs at a cutoff of 97% (https://qiime.org) software (Fast Length Adjustment of Short (FLASH) reads, he reads . Pre-prof of 97% , 32. Feasoftware . Taxonomr). The risk of microbial relative abundance for a diagnosis of IPF was expressed as odds ratio (OR) with 95% CI using binary logistic regression. In addition, the risk of microbial relative abundance for IPF mortality was presented as hazard ratio (HR) with 95% CI using Cox proportional hazards regression analyses. Alpha diversity indices that estimate the number of unique OTU in each sample are represented using four indices; Observed estimated the actual number of different taxa evident in a sample, Chao 1 non-parametrically estimated the richness of the species (p < 0.05 (two-tailed) were considered statistically significant.Continuous data were analyzed using Mann–Whitney U tests, and categorical data were analyzed using Fisher exact tests. The decline rate of lung function and exercise capacity for one year was estimated by linear regression analysis. Correlations between the relative abundance of the microbiome and clinical parameters were assessed using Spearman's correlation coefficients , Paracoccus, , and Akkermansia  was higher, whereas that of Caulobacter , Azonexus , and Undibacterium  was lower in patients with IPF than in the controls , and Azonexus  and Olsenella  was significantly higher in non-survivors than in survivors , Sphingomonas , and Clostridium  genera as independent predictors of IPF mortality.The median follow-up period for patients with IPF was 3.0 yr (interquartile range: 1.5–5.4 yr), and the median survival period was 3.1 yr. Unadjusted Cox analysis significantly associated the relative abundance of the ortality . A multiCurvibacter and Thioprofundum was positively associated with FVC in patients with IPF, whereas Anoxybacillus, Enterococcus, Akkermansia, and Clostridium negatively correlated with FVC  during the 6MWT.The relative abundance of the the 6MWT . The rel2 during 6MWT compared with survivors. The relative abundance of Granulicatella and Paracoccus genera was positively correlated, while that of the Novosphingobium genus was negatively correlated with the decline rate in FVC  compared with controls (n = 44) (n = 6), compared with control mice  (p < 0.0001) and inhaled steroid therapy  between IPF and controls, and these might affect differences in alpha diversity in microbiome. Our findings were in line with those of Kitsios et al. who identified separate clusters on PCoA plots of Bray-Curtis dissimilarity distances among explanted lung tissues from patients with IPF (n = 40), cystic fibrosis (n = 5), and donors (n = 7)  . The Sha < 0.05) ; there w (n = 7) .Lactobacillus was increased in lung tissues from patients with IPF compared with controls. Lactobacillus generally resides in the gastrointestinal and reproductive tract, where it maintains a healthy microecology with lactic acid production -ß1, were elevated in lung tissues from patients with IPF (n = 6), compared with healthy persons (n = 6)  . TherefoStreptococcus genus with IPF mortality, which is in line with the previous reports  according to a multivariable Cox proportional hazard analysis adjusted for age, gender, smoking status, and desaturation during the 6MWT   . Our resleomycin , suggestThis study had some limitations. Although we matched the baseline characteristics, such as age and sex between the IPF and control groups, other confounding factors might have affected the microbial communities. However, we tried not to include patients who had been treated with agents that might affect the microbiota. The number of samples analyzed was not large. Nevertheless, we identified significant differences in the distribution and clinical impact of the microbiomes of patients with IPF compared with controls. Because non-malignant and non-fibrotic lung tissues from lung cancer patients were used as controls, the microbial community in the control group might be affected by lung cancer. However, in studies of lung tissue microbiome of other diseases, it is common to use normal tissue of lung cancer tissue as normal control , 50. EveIn conclusion, our finding suggests that specific microbial communities in lung tissues from patients with IPF and associations between the relative abundance of some genera and clinical parameters, such as diagnosis, mortality, disease severity, and progression in such patients, imply microbial communities in the lungs play roles in the pathogenesis of IPF.PRJNA761508.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI SRA BioProject, accession no: The studies involving human participants were reviewed and approved by Institutional Review Board of Asan Medical Center (2018-1096). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.JS was the guarantor of the manuscript for designing and supervising the entire study. H-YY and JS took responsibility for the data analysis. S-JM contributed to sample collection and preparation. H-YY and JS drafted the initial manuscript. All the authors discussed the results and reviewed the manuscript.This study was supported by a grant from the Basic Science Research Program of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Science and Technology (NRF-2019R1A2C2008541), South Korea. The sponsor had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Necrotizing sarcoid granulomatosis (NSG) has recently been termed “sarcoidosis with NSG pattern” for the disease entity representing nodular sarcoidosis with granulomatous pulmonary angiitis. It is characterized by sarcoid-like granulomas, vasculitis, and a variable degree of necrosis. Its rarity and nonspecific clinical symptoms can easily lead to misdiagnosis or delayed diagnosis.We report a 67-year-old female with a biopsy-confirmed sarcoidosis with NSG pattern mimicking pulmonary malignancy on initial chest computed tomography scan.Sarcoidosis with NSG pattern.The patient underwent video-assisted thoracoscopic surgery with a lung biopsy. No further treatment was performed after the lung biopsy.Follow-up imaging studies revealed spontaneous regression of the disease after 2 months.Awareness of this rare benign disease entity and overlapping radiologic manifestations with pulmonary malignancy or other granulomatous diseases can be helpful for making a precise diagnosis with a better differential diagnosis. It can be easily found in various conditions such as infection and foreign body reaction. NSG is no longer a term for a disease entity, but a pathologic finding. It is being replaced by “sarcoidosis with NSG pattern.”,7,8 Usual clinical manifestations of sarcoidosis with NSG pattern are nonspecific. On imaging evaluation, sarcoid-like granuloma can be presented as solitary or multiple pulmonary nodules or masses similar to other granulomatous diseases.,10 Therefore, it is difficult to differentiate NSG clinically and radiologically from malignancies and other granulomatous diseases. Herein, we report a case of sarcoidosis with NSG pattern mistakenly diagnosed as malignancy on initial evaluation. Differential characteristics of sarcoidosis with NSG pattern in comparison with pulmonary malignancy and other granulomatous diseases are discussed.Necrotizing sarcoid granulomatosis (NSG) was first described as a rare granulomatous pulmonary disease of unknown etiology in 1973 by Liebow and The.2This study was approved by the Institutional Review Board of our institution and the requirement for informed consent was waived (IRB No. SCHUH 2021-10-020).A 67-year-old female was referred to our pulmonology outpatient clinic due to incidental abnormality on screening evaluation. She was a never-smoker with diabetes mellitus. She had no respiratory or systemic symptoms. Her vital signs were stable with a blood pressure of 121/76 mm Hg, a pulse of 81/min, a respiration rate of 18/min, and a body temperature of 36.5°C. Initial laboratory findings were also unremarkable, which revealed normal ranges of white blood cell count at 6900/μL  and C-reactive protein at 0.04 mg/dL .Initial chest radiographs showed 2 less than 2 cm sized lobulated nodular opacities in the right middle lobe and the left lower lobe Fig. , which sWith consideration of malignant tumors, a fluorine 18-fluorodeoxyglucose (FDG) positron emission tomography-CT (PET-CT) scan was performed at 10 days after the initial visit to our hospital. Increased FDG uptakes were noted in the nodules of the right middle lobe and the left lower lobe . There were newly seen hypermetabolic nodules in both lower lobes on PET-CT scan Fig. . Right lA follow-up contrast-enhanced chest CT scan was performed in our institution, which was obtained a month after the initial outside chest CT. Follow-up CT showed enlargement of existing nodules in the right middle lobe and the left lower lobe  with central low-density necrosis. About 1 cm sized ovoid nodules were newly seen in both lower lobes with a relatively smooth peripheral margin and peribronchovascular distribution of pulmonary nodules was suspected Fig. . ConsideWe performed a video-assisted thoracoscopic surgery with a lung biopsy of nodules in the left lower lobe. Histopathological evaluation revealed multiple inflammatory nodules with confluent granulomas and large zones of necrosis Fig. . The graAfter the lung biopsy, the attending physician decided medical observation without further treatment because the patient did not reveal any clinical or laboratory abnormality. On follow-up, chest radiography after surgical lung biopsy, pulmonary nodules showed continuous enlargement on a follow-up period of 12 days and otherwise decreased size on a further follow-up after 2 months (figures not shown).3 Histologically, large areas of necrosis involving the lung parenchyma can be seen. They are related to occlusion of pulmonary vessels with granulomatous inflammation. It is unclear whether the sarcoid-like reaction occurred in necrotizing vasculitis or necrosis of the granulomas and vessels in sarcoidosis. In fact, vasculitis accompanying granulomatous lung disease can be seen in various conditions, including GPA, infection such as fungus, tuberculosis or schistosomiasis, and foreign body reaction such as chronic beryllium disease or foreign body pulmonary embolism in drug abusers.,11 Recently, it is accepted as a more convincing idea that NSG is a variant of sarcoidosis with extensive infarct-like necrosis.,12,13 Therefore, the term “sarcoidosis with NSG pattern” is being used instead of NSG to reflect the clinical entity of nodular sarcoidosis.,7,8Necrotizing sarcoid granulomatosis, previously considered an extremely rare disease category, is characterized by findings of sarcoid-like granulomas, vasculitis, and a variable degree of necrosis. It occurs more frequently in women than in men with variable prevalence of extrapulmonary involvement such as eyes, skin, and nerve systems. Karpathiou et al have reviewed clinical, radiologic, and histopathologic findings of NSG and found that the pattern of multiple lung nodules is the most common radiologic presentation, followed by a solitary nodule or mass. Thoracic lymphadenopathy and cavitation of nodules are often observed. Therefore, it is required to distinguish radiologic features of NSG from those of malignancy.Sarcoidosis with NSG pattern can be easily misdiagnosed as pulmonary malignancy or other pulmonary granulomatous diseases due to their similar radiologic findings and nonspecific clinical presentation. Sarcoidosis with NSG pattern has been reported in a wide range of age groups from 8 to 68 years, with a median age of 42 years.In our case, the initial radiologic findings of the patient were reminiscent of malignant tumors in the sense that they appeared to be enhancing pulmonary nodules with thoracic lymphadenopathy. Clinical features of an asymptomatic patient with incidental radiographic abnormality without specific laboratory finding raised a first impression of malignancy rather than inflammatory diseases. Furthermore, on PET-CT scan, the pulmonary nodules, and lymphadenopathy showed avid FDG uptakes. On retrospective review, microlobulation and low-density areas in the pulmonary nodules of the right middle lobe and the left lower lobe were well correlated with characteristic pathologic findings of aggregates of granulomas and relatively large areas of necrosis. In contrast with frequent central necrosis in metastatic lymph nodes on enhanced chest CT, homogeneously enhancing thoracic lymphadenopathy was found our case. Besides, inflammation can be a plausible explanation considering radiographic change during a month of follow-up period and distribution of pulmonary nodules along bronchovascular bundles. Unlike sarcoidosis with NSG pattern, nodular sarcoidosis consists of coalescent compact sarcoid granulomas without significant necrosis or vasculitis on histology. There is still a debate as to whether sarcoidosis with NSG pattern might be a variant or late stage of nodular sarcoidosis. Substantial overlap is seen between nodular sarcoidosis and NSG pattern in terms of clinical symptoms and extrapulmonary manifestations. Patients with NSG pattern are reported to be less likely to have hilar or mediastinal lymphadenopathy with increased serum angiotensin-converting enzyme than those with nodular sarcoidosis.,3,4 Vasculitis such as GPA or eosinophilic GPA can also present multiple lung nodules with solid or ground-glass opacity that often show air bronchogram or necrosis with cavitation. Accompanied ground-glass opacity and consolidation are more often seen in GPA than other granulomatous diseases due to alveolar hemorrhage resulting from necrotic infiltration or perfusion alterations by vasculitis of small vessels.,16 Extrapulmonary involvement is a common manifestation. It is particularly accompanied by upper respiratory tract disease, glomerulonephritis, or systemic vasculitis. Amyloidosis is also one of the diseases to be distinguished from other granulomatous diseases. Multiple nodular parenchymal amyloid deposits often show central or irregular patterns of calcification with sharp and lobulated margins. Circumferential wall thickening of trachea is a frequent radiologic finding of airway involvement. Less commonly, diffuse involvement of lung parenchyma including capillary vessels and interstitial alveolar septae can be seen.Various granulomatous lung diseases usually present multiple pulmonary nodules. However, differential radiologic characteristics should be taken into consideration. Nodular sarcoidosis, an uncommon form of sarcoidosis, can show variable sized distinct pulmonary nodules with peripheral predilection or unusually solitary nodule, which simulates metastatic tumor or primary pulmonary neoplasm. Unlike other systemic vasculitis or malignancy, good response with systemic corticosteroid treatment is expected. The disease also can show spontaneous regression. This was well demonstrated in our case. Overall prognosis of sarcoidosis with NSG pattern is favorable, which is a notable distinguishing feature in comparison with other differential disease entities. Therefore, minimally invasive diagnostic procedure can be considered for better management of the patient.The most commonly used treatment for sarcoidosis with NSG pattern is systemic steroid therapy (daily prednisone 40–60 mg for 4–8 weeks).4,9,11,13 However, only a few articles on its radiologic characteristics have been reported. In our case report, major radiological findings of sarcoidosis with NSG pattern were discussed with radiologic and pathologic correlation. Distinguishing characteristics from pulmonary malignancies and other granulomatous diseases were also reviewed. Recognizing and understanding the clinical and radiologic presentations of sarcoidosis with NSG pattern can lead to appropriate diagnosis and management. Further large case studies are needed to specify and better define this rare disease entity.There have been many pathological reports of sarcoidosis with NSG pattern.BDN was the guarantor of the entire study. JHK, BDN, JHH contributed to the conception, design, and acquisition of data, analysis and interpretation of data, and drafting of the paper. DWK contributed to the data collection, analysis, and interpretation of data and drafting of the paper. KUK contributed to the design and acquisition of data, analysis and interpretation of data. YWP contributed to the data collection, analysis, and interpretation of data and drafting of the paper.Conceptualization: Bo Da Nam, Jung Hwa Hwang.Supervision: Jun Hyeok Kim, Bo Da Nam, Jung Hwa Hwang, Dong Won Kim, Ki-Up Kim, Young Woo Park.Writing – original draft: Jun Hyeok Kim, Bo Da Nam, Jung Hwa Hwang.Writing – review & editing: Jung Hwa Hwang.


The electrical properties of polycrystalline graphene grown by chemical vapor deposition (CVD) are determined by grain-related parameters—average grain size, single-crystalline grain sheet resistance, and grain boundary (GB) resistivity. However, extracting these parameters still remains challenging because of the difficulty in observing graphene GBs and decoupling the grain sheet resistance and GB resistivity. In this work, we developed an electrical characterization method that can extract the average grain size, single-crystalline grain sheet resistance, and GB resistivity simultaneously. We observed that the material property, graphene sheet resistance, could depend on the device dimension and developed an analytical resistance model based on the cumulative distribution function of the gamma distribution, explaining the effect of the GB density and distribution in the graphene channel. We applied this model to CVD-grown monolayer graphene by characterizing transmission-line model patterns and simultaneously extracted the average grain size (~5.95 μm), single-crystalline grain sheet resistance (~321 Ω/sq), and GB resistivity (~18.16 kΩ-μm) of the CVD-graphene layer. The extracted values agreed well with those obtained from scanning electron microscopy images of ultraviolet/ozone-treated GBs and the electrical characterization of graphene devices with sub-micrometer channel lengths. Chemical vapor deposition (CVD) is the most effective method for uniformly growing monolayer graphene on a wafer scale in a reproducible way . However−1, G peak at ~1580 cm−1, and 2D peak at ~2690 cm−1) enables the location and shape of GBs and grains to be identified [Accordingly, various techniques for characterizing grain parameters have been actively studied over the last decade. In the case of grain size, it can be evaluated through structural characterization and identification of GBs using spectroscopic or microscopic measurements. For instance, spatial mapping of the Raman peak intensities for graphene  . An elecshR) as a function of channel length (chL). We show that the average grain size, grain sheet resistance, and GB resistivity of CVD graphene can be extracted simultaneously from the analytical resistance model that is fitted to the measured shR–chL curve. The three extracted values are then compared with those obtained using conventional methods and those reported in the literature.In this paper, we propose for the first time an electrical characterization method for extracting the average grain size, grain sheet resistance, and GB resistivity of monolayer CVD graphene simultaneously. For this purpose, we investigate the probability distribution of the number of GBs depending on the graphene–channel dimension, from which we develop an analytical resistance model that can explain the relationship between the electrical properties of polycrystalline graphene and its grain parameters. With this resistance model, we show that the three-grain parameters can be extracted simultaneously with an accuracy greater than 99% from the dependence of the material’s electrical property  on the channel dimension. To validate the developed resistance model and its applicability for parameter extraction, we fabricate a transmission-line model (TLM) pattern on monolayer CVD graphene and characterize the channel sheet resistance (2 (100 sccm) for surface treatment. Following the annealing step, monolayer graphene was grown at 1050 °C for 1 h under a chamber pressure of 2 Torr with a flow of Ar (570 sccm), H2 (100 sccm), and CH4 (2 sccm). The CVD chamber was then cooled down to room temperature in an Ar environment before the as-grown graphene sample was finally removed from the chamber.After the development of an analytical resistance model, to verify its applicability for grain-parameter extraction, we synthesized monolayer graphene on a 25-μm-thick Cu foil  by a thermal CVD system . To grow the polycrystalline graphene layer with uniform-size grains, electropolishing of the Cu surface was first performed in an 85% phosphoric acid bath using a constant voltage of 1.2 V for 20 min . The pol2) by the optimized poly (methyl methacrylate) (PMMA)-mediated transfer method [2 plasma ashing  for 3 min. The Cu foil was then etched using diluted ammonium persulfate solution  at room temperature for 24 h, after which the remaining PMMA/graphene stack was rinsed repeatedly with deionized water. The rinsed PMMA/graphene stack was finally transferred onto the oxidized Si substrate and the transferred sample was baked at 160 °C in a vacuum for 30 min to remove residual water and improve the adhesion between the graphene layer and the substrate. To minimize the PMMA residue and wrinkles, the PMMA layer was removed using acetic acid at room temperature for 3 h, followed by annealing at 300 °C for 3 h under an ultrahigh vacuum (~10−8 Torr) [For device fabrication, CVD-grown monolayer graphene was transferred onto thermally oxidized Si substrates  with a positive-tone photoresist , and graphene channels were defined using O2 plasma etching  for 2 min. Following the channel definition, the second photolithography process was performed using an image reversal photoresist  for source/drain electrode patterning. Then, a 20-nm-thick Pd and 50-nm-thick Au were sequentially deposited by an electron-beam evaporation system  for contact formation, after which the residual photoresist layer and the metal deposited on top of the photoresist were removed by the lift-off process in a warm acetone bath. CVD-graphene FETs with sub-micrometer channel lengths (0.18–0.75 μm) were fabricated using electron-beam lithography  and a positive-tone electron-beam resist . For patterning the graphene channels and source/drain electrodes, electron-beam conditions of an area dose of 200 μC/cm2, a step size of 5 nm, and an acceleration voltage of 30 kV were used.To extract the grain parameters of CVD graphene using the developed analytical resistance model, TLM patterns composed of back-gated field-effect transistors (FETs) with varying channel lengths (2–100 μm) were fabricated on CVD graphene transferred onto 90-nm-thick oxidized Si substrates. First, channel regions of the FETs were patterned by −7 Torr). Before the measurements, the graphene surface was annealed at 120 °C for 3 h in the vacuum probe station to remove any moisture, oxygen, and photoresist residue, which act as p-type dopants [2 under ambient conditions. The grain sizes of CVD graphene observed in the top-view SEM images after the UV/ozone treatment were measured using the ImageJ software provided by the National Institutes of Health, USA. Note that the grain-size estimation from the SEM images was performed to check the accuracy of the average grain size extracted by the proposed electrical characterization method.The electrical characteristics of the fabricated graphene FETs were measured using a semiconductor parameter analyzer  in a probe station under a high vacuum . In this study, the channel width was divided into 105 elements for the parallel-resistance modeling. Furthermore, to estimate the average channel resistance as a function of the channel length, we randomly generated 1000 polycrystalline structures with an average grain size of 5 μm using the VT method and repeated this calculation process , whereas the slope (dchR/dchL) varies with the channel length in the relatively short-channel region (particularly the chL around the average grain size). This indicates that the sheet resistance of the polycrystalline channel depends on the channel dimension, unlike the single-crystalline graphene or other single-crystalline semiconductors. The average channel sheet resistance (shR) as a function of channel length is shown in chR × chW/chL. The channel sheet resistance is constant for long channels; however, it decreases sharply as the channel length is reduced below approximately 25 μm. The decrease in channel sheet resistance is most prominent at channel lengths around the average grain size, which is due to the significantly lowered probability of the existence of GBs at those channel lengths [To develop a characterization method for extracting the average grain size, grain sheet resistance, and GB resistivity, it is necessary to investigate the effects of these parameters on the electrical characteristics of polycrystalline-graphene devices. Thus, we first theoretically calculated the channel sheet resistance of polycrystalline graphene as a function of channel length using a parallel-resistance model , and invparallel a. The eqterature ,5.  generated randomly using the VT method, as in the channel resistance calculation. The average histogram distributions of the proportion of the GB number within the channel region at three different channel lengths are shown in chL ≤ 5 μm), whereas it is evenly distributed at the channel length greater than the average grain size. This explains why there is a significant decrease in sheet resistance at channel lengths near the average grain size (α∙β is the mean and α∙β2 is the variance. When α = 3.85 × chL/Gl and β = 0.33 (where Gl is the average grain size), it was empirically confirmed that the gamma PDF agrees well with the envelope of the proportional distribution of the GB number for all channel lengths . Following this, to obtain the discrete distribution of the GB number from the continuous gamma PDF, we used the cumulative distribution function of the gamma distribution , which is an integral form of the gamma PDF as follows:n is the number of GBs. The proportion distribution of the GB number can be estimated from GamCDF (n + 0.5) − GamCDF (n − 0.5) with an accuracy greater than 98% for all channel lengths, as shown in the red symbols of As shown in ain size c. We inv lengths . FurtherchW) were grouped and rearranged by the number of GBs considering its proportion within the channel region estimated from the gamma CDF  can be expressed as follows:k is the maximum number of GBs existing within the divided width elements. Based on the rearranged width elements, Equation (2) can then be generalized as:Because the proportion distribution of the GB number within the channel region can now be accurately estimated without counting the number of GBs, we can develop an analytical resistance model that is more generalized for explaining the dependence between the sheet resistance and channel length. For this purpose, the divided narrow width elements , can be finally induced as a function of the channel length:Following that, the analytical model for the channel sheet resistance, composed of the three-grain parameters . As a result, the analytical model was fitted with the calculation result well, with a fitting accuracy greater than 99.98%  for the device fabrication. The material and layer quality of as-transferred CVD graphene was then evaluated using Raman spectroscopy measurements, confirming the defect-free monolayer graphene with an intensity ratio of 2D to G peaks of ~2.8 (see CR) was separated from the measured total device resistance (totR) by using the TLM method [chR = totR − 2CR (chR × chW/chL. The dots in shR–chL is similar to that observed in the theoretical calculation result (shR–chL curve as shown by the red line in To verify whether the proposed parameter extraction method is practical, we fabricated TLM patterns on CVD graphene and extracted three-grain parameters by characterizing the dependence of the channel sheet resistance on the channel length using the analytical resistance model. For this purpose, we synthesized monolayer graphene through CVD and transferred it onto thermally oxidized Si substrates (90-nm-thick SiO~2.8 see . To char~2.8 see a and theM method —i.e., Rcot − 2RC . Thereafn result c. From sLch of 0.18–0.75 μm (shR–chL obtained from simple TLM measurements will provide a convenient way for the electrical characterization of CVD graphene and its efficient device applications. Furthermore, it is expected that the proposed method can be extended to various 2D materials with polycrystalline structures.To confirm whether the extracted three-parameter values are rational, we compared the extracted values with those evaluated using conventional methods and those reported in the literature. First, the GB visualization technique based on UV/ozone treatment was used to estimate the average grain size of CVD graphene. –0.75 μm d. Becaus–0.75 μm e. The esshR–Lch curve. We believe that this method will be a useful tool for the electrical characterization of CVD graphene and other polycrystalline 2D materials.In summary, we demonstrated an electrical characterization method for extracting the average grain size, grain sheet resistance, and GB resistivity of monolayer CVD graphene simultaneously. We developed an analytical resistance model to explain the relationship between the electrical properties of polycrystalline graphene and the channel dimension by precisely estimating the proportion distribution of the number of GBs within graphene channels. With the developed analytical resistance model, we showed that the three-grain parameters can be extracted simultaneously from the dependence of the graphene sheet resistance on the channel dimension with an accuracy greater than 99%. The proposed parameter extraction method using the GB distribution-based analytical resistance model was experimentally verified by characterizing TLM patterns fabricated on monolayer CVD graphene. The result showed that the average grain size, grain sheet resistance, and GB resistivity of CVD graphene can be extracted simultaneously with high accuracy from the analytical resistance model fitted to the measured


With a direct bandgap, two-dimensional (2D) ZnSe is a promising semiconductor material in photoelectric device fields. In this work, based on first-principles methods, we theoretically studied the modulation of the Schottky barrier height (SBH) by applying horizontal and vertical strains on graphene/ZnSe heterojunction. The results show that the inherent electronic properties of graphene and ZnSe monolayers are both well-conserved because of the weak van der Waals (vdW) forces between two sublayers. Under horizontal strain condition, the n(p)-type SBH decreases from 0.56 (1.62) eV to 0.21 (0.78) eV. By changing the interlayer distance in the range of 2.8 Å to 4.4 Å, the n(p)-type SBH decreases (increases) from 0.88 (0.98) eV to 0.21 (1.76) eV. These findings prove the SBH of the heterojunction to be tuned effectively, which is of great significance to optoelectronic devices, especially in graphene/ZnSe-based nano-electronic and optoelectronic devices. Ever since graphene was exfoliated experimentally in 2004 2/ZnSe, and CdS/ZnSe heterostructures  heterostructure, as proposed by ructures . Howeverructures . How is Besides, the 2D heterojunction Schottky barrier height (SBH) can be controlled through interlayer coupling, electric field, biaxial strain engineering, and atomic doping . The mod–5 eV. The atomic structures considered were fully optimized until the convergence of force of 0.01 eV/Å. The Γ-centered Monkhorst–Pack Z-direction. The VASPKIT was used to do part of data post-processing  and projector augmented wave (PAW) ocessing .The binding energy is one of the physical quantities that determine the heterojunction structural stability . TherefoA is the interface area in the x-y plane.Here, Before constructing the graphene/ZnSe heterojunction, the lattice constants of graphene and ZnSe are relaxed to be 2.46 Å and 4.07 Å, respectively, being in great agreement with the data in the literature . To reduWe further investigated the binding energy of stack-III pattern under different interlayer distances, as shown in As expected, graphene shows a metallic nature with the Dirac point located at the K point and crossed by the Fermi energy level, as shown in As well known, the PBE method would underestimate the bandgap of semiconductors, and the HSE method can solve this problem extremely well. However, both the PBE and HSE would predict the same band structure shape and variation trends of the ZnSe monolayer under different strains, with limited resources, so we use the PBE method to calculate all properties of the considered systems. Next, we further researched the electronic properties of the graphene/ZnSe heterojunction by figuring out the band structures and density of states under different horizontal or vertical strains .In this study, we applied horizontal strain from −2% to +6% on the graphene/ZnSe heterojunction, with a span of 2%. The positive value indicates tensile strain, while the negative value represents compressive strain. The reason why more negative strains are not considered is that a much larger strain is hard to be experimentally achieved, and it will also make the nanomaterials nonstable . When thNext, to investigate the charge transfers and charge redistribution more clearly, the charge density difference of the graphene/ZnSe heterojunction was analyzed under different horizontal and vertical strains, as shown in To see the charge redistribution, the plane-averaged charge density difference (PCDD) was calculated as follows :Δρ=ρgraIn this case, . As shown in In The SBH of the metal/semiconductor interfacial system is an important parameter . TherefoF is the Fermi level. Without any horizontal or vertical strain, Based on Bardeeen’s  Schottkyg strain . TherefoAs shown in It should be noted that variation of heterojunction layer spacing can be achieved by experimental techniques , which hIn conclusion, we have systematically studied the electronic properties and the efficient modulations of SBH of the vdW graphene/ZnSe heterostructure by DFT calculations. The band structures, the charge density differences, and the Bader charge transfer are studied in detail. The results show that the electrons will be transformed from graphene to ZnSe, and the transfer amount can be tuned effectively by applying both horizontal and vertical strains. As a consequence, the positions of CBM and VBM as well as Fermi energy level will be changed with the strain, and thus, the SBH is modulated effectively. These findings would provide useful guidance for designing controllable graphene/ZnSe-based Schottky nanodevices.