This paper describes the development of a graphene-based dry flexible electrocardiography (ECG) electrode and a portable wireless ECG measurement system. First, graphene films on polyethylene terephthalate (PET) substrates and graphene paper were used to construct the ECG electrode. Then, a graphene textile was synthesized for the fabrication of a wearable ECG monitoring system. The structure and the electrical properties of the graphene electrodes were evaluated using Raman spectroscopy, scanning electron microscopy (SEM), and alternating current impedance spectroscopy. ECG signals were then collected from healthy subjects using the developed graphene electrode and portable measurement system. The results show that the graphene electrode was able to acquire the typical characteristics and features of human ECG signals with a high signal-to-noise (SNR) ratio in different states of motion. A week-long continuous wearability test showed no degradation in the ECG signal quality over time. The graphene-based flexible electrode demonstrates comfortability, good biocompatibility, and high electrophysiological detection sensitivity. The graphene electrode also combines the potential for use in long-term wearable dynamic cardiac activity monitoring systems with convenience and comfort for use in home health care of elderly and high-risk adults. Cardiovascular disease, which includes both coronary heart disease and stroke, is one of the most prevalent causes of death worldwide. In addition to these fatal cases, at least 20 million people experience nonfatal heart attacks and strokes every year; many of these people subsequently require prolonged and costly medical care ,2. ElectFollowing the development of flexible and stretchable electronics, alternative electrodes that do not require electrolytic gel (referred to as active dry electrodes) have been reported by many groups ,14,15,16In this study, flexible graphene textile was synthesised by the reduction of graphene oxide with the help of vacuum filtration to improve the amount and degree of adsorption, and then the graphene textile was used to construct electrodes for long-term wearable ECG monitoring applications. The structural properties of graphene were first characterized by Raman spectroscopy and scanning electron microscopy (SEM), and then the electrical properties of the designed electrode were evaluated by diverse testing based on alternating current (AC) impedance spectroscopy and connect impedance with skin, according to frequency changes. Subsequently, we measured ECG signals in different states of human body motion and studied the feasibility of long-term monitoring through continuous measurements. The experimental result and statistical comparative study demonstrates the potential usefulness of the proposed graphene electrodes for routine electrophysiological activity monitoring of the heart and other vital organs.Numerous methods can be used to fabricate graphene, including chemical vapor deposition (CVD) , organicRaman spectroscopy and SEM are widely used characterization methods for examination of the microstructures of materials. Raman spectroscopy provides information about the characteristic vibrational states, while SEM gives surface profile information. In this paper, the Raman spectra of graphene electrodes were measured using a Horiba Jobin Yvon confocal LabRAM HR800 spectrometer with an excitation wavelength of 532 nm, and the SEM was performed using a Hitachi TM3030 electron microscope with an accelerating voltage range of 3–15 kV. The electrical properties of the ECG electrodes were characterized via electrochemical impedance spectroscopy (EIS) measurements that were performed using a CS350 electrochemical workstation , which worked with a sweeping frequency range from 50 mHz to 10 Hz and an AC perturbation of 10 mV. Skin–electrode contact impedance measurement has always been of interest due to the desire to prove the reliability of the collected biopotential . Here, tFor performance evaluation of the graphene electrode, ECG signals were measured in different human body motion states in 24-year-old male volunteers. Two electrodes were fixed on the left and right sides of the ribcage of each test subject, and the reference ground was located in their lower right abdomen. To ensure similar test conditions for comparison, these electrodes were positioned in the same locations for every measurement. The resting-state ECG signals were measured first, and then the motion artifacts that result from walking and swinging of the subject’s arms were investigated. To study the effects of moisture on the quality of the ECG signals, measurements were also taken after exercise. Finally, the ECG signals were measured using the graphene textile electrodes over a period of one week to evaluate their long-term monitoring capabilities.The Raman spectra of graphene for various thicknesses are shown in hickness ,29, and In the graphene textile and the graphene paper, the Raman spectra show two main peaks, the G- and D-peaks, which lie at approximately 1580 cmc G band . CompareThe morphological studies of the graphene samples performed using SEM are shown in Bode plots of the graphene electrodes and of commercial Ag/AgCl electrodes within the 0.05 to 10 Hz frequency range are presented in To estimate the ECG detection performances of the different kinds of graphene electrode, typical ECG signals are collected, as shown in When compared with graphene–PET and graphene paper, the graphene textile electrode shows the best flexibility and assembly characteristics, and thus it was selected for further study in terms of its performance in daily ECG monitoring applications. Skin–electrode contact impedance directly influenced the reliability of collected signals, low contact impedance resulting in less noise and a higher quality ECG signal. Here, we measured the skin–electrode contact impedance of graphene textile with different contact force, and compared that to standard Ag/AgCl electrode. Four examples of motion artifacts are shown in Furthermore, we compared the performance of graphene textile electrode with commercial Ag/AgCl electrode at different motion states, the peak-to-peak amplitude (P–P), heart rate, SNRs, and standard deviation (SD) of collected ECG signals are summarized in In order to assess the performance in long-term measurement, the ECG signal was collected over seven days of continuous wear of the graphene textile electrode. The waveforms of ECG signals in days 1, 3, 5, and 7 are displayed in Mobile health care systems have increased in popularity because of their noninvasive features and convenience for use in daily life. In this study, we aimed to develop wearable flexible electrodes for daily ECG monitoring, which would be very helpful in the detection of sudden onset heart disease, especially in elderly patients. Electrodes that are highly sensitive, comfortable, and offer biological compatibility and persistence are essential components for daily ECG monitoring systems. The results presented here have demonstrated that the proposed graphene-based electrode offers sensitivity comparable to that of commercial Ag/AgCl electrodes; this research also indicates opportunities to transfer graphene for use in other biological applications, such as electroencephalography (EEG) and electromyography (EMG) detection.However, one challenge that remains for the use of graphene materials in daily ECG monitoring is their intrinsically high hydrophobicity, which might lead to a weak binding force to the substrate and high impedance between the graphene and electrolyte surfaces. In our early study of graphene electrodes on a soft elastic PDMS substrate, the graphene films were found to fall off easily, and they showed much higher resistance due to broken parts of the graphene structure. In this study, graphene was adsorbed on polyester fibers using a vacuum suction filter; the intrinsic internal resistance of the graphene textile reached several megaohms, indicating that the adsorption amount and the combination degree must be further improved to enhance the detection sensitivity and the frictional resistance. We will apply our efforts to the selection of a more suitable substrate, and will increase the binding force between the graphene films and the substrate by introducing molecules with grafting chains. With regard to toxicity, carbon is commonplace and has a stable structure; previous studies have demonstrated the biological compatibility of carbon group elements, including carbon nanotubes and graphene , and thuIn this paper, we have fabricated graphene-based electrodes and a corresponding wireless ECG collection system. The results demonstrated that ECG signal recording can be carried out using a flexible graphene electrode with high SNR. The graphene electrode provides effective electrical performance, high flexibility, satisfactory biocompatibility and wearability, and offers detection capabilities in various states of motion. The design presented here provides a potential electrode structure for long-term wearable monitoring, and offers convenience and comfort for home health care management of the elderly population, with collection and computer display of the results performed via wireless communication using the developed graphene electrode.


A general three-dimensional continuum model of phonons in two-dimensional materials is developed. Our first-principles derivation includes full consideration of the lattice anisotropy and flexural modes perpendicular to the layers and can thus be applied to any two-dimensional material. In this paper, we use the model to not only compare the phonon spectra among the group-IV materials but also to study whether these phonons differ from those of a compound material such as molybdenum disulfide. The origin of quadratic modes is clarified. Mode coupling for both graphene and silicene is obtained, contrary to previous works. Our model allows us to predict the existence of confined optical phonon modes for the group-IV materials but not for molybdenum disulfide. A comparison of the long-wavelength modes to density-functional results is included. Phonon spectra in two-dimensional 2D) nanomaterials have almost exclusively been computed using density-functional theory (DFT) based codes. One of the earliest applications to group-IV elemental 2D materials was for the important prediction of the stability of silicene and germanene . These aD nanomatk = 0. One of the earliest such models applied to an ionic crystal slab is that of Fuchs and Kliewer neglecting the DC component (static polarization) to the electric displacement. Confinement of the optical phonon modes implies  are constants, the Maxwell–Poisson equation and the boundary conditions are fulfilled if εzz(ω) = 0. Hence confined optical phonons exist in graphene.where D3d point group.We refer to silicene as the canonical example of the other group-IV materials even though the following derivation and qualitative properties apply to all of them since they all have the same symmetry of the buckled hexagonal structure, leading to the trigonal D3d trigonal structures isThe general form of the stiffness tensor for and the stress–strain relations becomec14.The only difference compared to the corresponding equations for graphene are the terms containing The elastic equations for silicene then reador, in terms of the displacements,c14 terms. The electric equation for trigonal structures is exactly the same as for hexagonal structures since the permittivity matrix is the same. Hence, the general method for finding surface optical phonon modes repeats the description of graphene. Qualitatively, there is therefore no difference among the phonons for all the group-IV elemental 2D materials.Again, the differences compared to graphene are the 2 as a prototypical compound 2D material because of its extensively studied properties. As already mentioned, the lack of inversion symmetry leads to the new phenomenon of piezoelectricity.While the primary focus of this paper is on the properties of phonons of the group-IV elemental materials, it is important to know if there are properties of the phonons that are due to these being elemental. Hence, we will now consider the phonons for MoS2 is the same as for graphene, The stiffness tensor for MoSe-tensor:by use of the piezoelectric and the equationEj is the internal electric field.In the above, 2With the above result for the stress tensor including piezoelectric contributions, we find the elastic equations for MoS2, the displacement field Di isThis system of equations is only complete if we also solve for the Maxwell–Poisson equation. For MoSPsp being the spontaneous polarization contribution. The dielectric function is the same as for graphene  and the displacements ux, uy and uz.because the spontaneous polarization 2, the general solutions are more complicated. One can still make the plane wave ansatz,In the case of MoSfx, fy, fz and Now, inserting whereky = 0, we have C = D2 = E2 = 0 and uy decouples from ux, uz and . The wave equation for the uy mode is the same as for graphene. To determine the general solution for the other displacement components, we once again solve the determinantal equation for the 3 × 3 sub-matrix in the components fx, fz and  . The result isFor the case, whereand six roots (three pairs of opposite signs) exist. It also follows thatHence the general solution is, using a notation similar to the case of graphene,i are unknown coefficients.where β) has the general solutionThe Maxwell–Poisson equation in vacuum 0 is the vacuum permittivity. Solving the determinantal equation for the 8 × 8 matrix equation as a function of kx specifies a discrete set of (band) eigenfrequencies ωi(kx) and the corresponding eigenmodes fx, fz and , where i denotes the band index.where εky = 0,An important result concerning confined optical phonons can be obtained without solving the determinantal equations. From the elastic equations  and the Inspection of the above set of equations reveals that confined phonon solutions can be sought in the form [type I]or in the form [type II]ikxx − iωt). The above choice reflects an expectation that four roots are real (two pairs of opposite-signed roots) and two imaginary (one pair of opposite-signed roots).apart from a multiplying factor exp = 0 and  using continuity in the transverse electric field at the interfaces. since this construction implies m, this latter condition, in general, would lead to a different ωm. However, a normal mode is characterized by a unique frequency ω. Hence, for confined optical phonon modes, only one term in m is allowed in the general Fourier series expansions above. Further, imposing continuity in the normal electric displacement component at z = ±h by use of the third equation in For each term  unless accidentally εzz(ωm) = 0 (treated separately in the next paragraph). For εzz(ωm) ≠ 0, it follows from Ax,m = 0 and Az,m = 0. The conclusion is that confined optical phonons in the general case cannot exist in MoS2! Note that for graphene, since it is a non-piezoelectric material, confined optical phonon modes do exist. The difference between the two materials lies in and zz = 0, continuity of the normal electric displacement component requires, as before,  and we return to the situation treated in the previous subsection about confined optical phonons. We need to consider two possible cases: (a) εxx(ω) = 0 when εzz(ω) = 0 and (b) εxx(ω) ≠ 0 when εzz(ω) = 0. In case (a), we immediately obtain  from continuity in the normal electric displacement. Further, ux = 0 everywhere as a function of z. If εand and the conditionxx(ω) = εzz(ω) = 0. In case (b), m values do not fulfill εzz(ω) = 0. In conclusion, confined optical phonon modes do not exist in the case εzz = 0.which is not fulfilled, unless accidental degeneracy applies, simultaneous with εIn order to illustrate the validity of the phonon dispersion relations obtained from our model, we compare them to DFT calculations. The continuum theory will require as input elasticity constants, piezoelectric coefficients, and dielectric functions.c direction. Structure optimizations are performed on Γ-centered 24 × 24 × 1 k-meshes. A direct method based on 4 × 4 × 1 supercells is used for obtaining the phonon dispersions within the harmonic approximation [k-meshes, including long-range dipole contributions to the dynamical matrix following the method of [k-meshes.We first give the standard phonon dispersion relation as obtained from DFT calculations . They arximation . Forces ethod of . Born efethod of  and elasethod of . The elac11d = 345 Pa·m, c12d = 73 Pa·m, c13d = 0.00387 Pa·m, c33d = 0.531 Pa·m, c44d = 0.0535 Pa·m, c66d = 136 Pa·m, d = 3.4·10−8 m, and ρ2D = 7.61·10−7 kg/m2. For the permittivity data we used the DC values εxx = 4.4ε0 and εzz = 1.3ε0.The following parameters are found using DFT calculations as explained above: kx) dispersion in the vicinity of the Γ point (ky = 0). Evidently, one mode shows a parabolic dispersion and one mode is linear. There are two higher-order modes originating from the boundary conditions along the z coordinate. The dispersion curves associated with the uy vibrations decoupled from the ux − uz vibrations are not shown in the plots. We emphasize that for graphene optical and acoustic phonon modes decouple and are computed separately as described above. In In 2, we use the following parameters: c11d = 140 Pa·m, c12d = 33 Pa·m, c13d=-0.013 Pa·m, c33d = 0.078 Pa·m, c44d = −1.07 Pa·m, c66d = 53.7 Pa·m, d = 6.2·10−10 m, ρ2D = 3.1 ·10−6 kg/m2, ex1 = 0.5 C/m2. These elasticity parameters were again computed using VASP. The frequency-dependent permittivity values are taken from [ex1 is from Ref. [2, all optical and acoustic phonon modes are computed by solving the combined set of elastic and electric equations and associated slab boundary conditions as described above. We note in passing that both confined and surface acousto-optical phonon modes are found using the present formalism. In kx) dispersion in the vicinity of the Γ point (ky = 0).For single-layer MoSken from  and the rom Ref. . In the 2 revealed a number of interesting results. The out-of-plane vibrations were coupled to the in-plane motion for graphene (and for silicene as well), contrary to previous results using infinitely thin sheets. Acoustic modes with linear and quadratic dispersions were obtained, in agreement with experimental results and other models. We predict the existence of confined optical modes in all of the elemental group-IV materials and the nonexistence of confined optical modes in MoS2. Our model will be applied to other 2D materials as well as to multilayers in future work. Additionally, the results of this model can be combined with the solution to the electron problem to compute electron–phonon scattering rates. The latter would be useful for understanding a number of physical properties as well as for applications.A three-dimensional, first-principles, continuum elasticity theory was developed for two-dimensional materials. Piezoelectric materials required the simultaneous consideration of the electrostatics equations. Application to graphene, silicene and MoS


I-V characterization behavior in the dark and the resistance dramatically decreases under the white light. Furthermore, the photosensitivity of the device is as large as 1110% with a rapid response time, which is much higher than pristine SnSe nanostructure reported. The results shown here may provide a valuable guidance to design and fabricate the photodetector based on the 2D-2D nanocomposites even beyond the SnSe nanoplate-graphene nanocomposites.The multi-functional nanomaterial constructed with more than one type of materials has gained a great attention due to its promising application. Here, a high white light photodetector prototype established with two-dimensional material (2D) and 2D nanocomposites has been fabricated. The 2D-2D nanocomposites were synthesized with SnSe nanoplate and graphene. The device shows a linear  Among tI-V characterization behavior in the dark, and the resistance dramatically decreases under the white light. The photosensitivity of the device is as large as 1110% with a rapid response time. The results shown here may provide a valuable instruction to design and fabricate photodetectors based on graphene and even extend to other 2D-2D nanocomposites.In this report, the 2D-2D nanocomposites namely SnSe nanoplate-graphene nanocomposites were synthesized. As an important p-type semiconductor, SnSe has attracted intense attention in solar cells, photodetectors, and near-infrared optoelectronic devices due to its narrow band gap (~0.90 eV indirect and ~1.30 eV direct), earth-abundance, less toxicity, and chemical stability –20. Then2·2H2O; ≥98%), polyvinylpyrrolidone , and benzyl alcohol (≥98%) were purchased from Tianjing Fuchen Chemical Reagents Factory. Selenium dioxide  were obtained from Chengdu Ai Keda Chemical Technology Co., Ltd. Graphite oxide (GO) was prepared through Hummers method [All chemical materials were of analytical grade and used as received without further purification. Tin (II) chloride dihydrate (SnCls method . Some co2 (0.8 mmol/L), SnCl2·2H2O (0.8 mmol/L) and poly (vinyl pyrrolidone) , GO (0.075 g/mL) is added into benzyl alcohol (20 mL) at room temperature. The mixed solution was transferred into a three-neck round-bottom flask, sealed, and then degassed with pure N2 (99.99%) under magnetic stirring. Then the mixture was heated up to 200 °C and allowed to be aged for another 12 h at this temperature in N2 atmosphere. Finally, the solution was cooled down to room temperature naturally, and the products were obtained by centrifugation at 10,000 rpm for 10 min to purify at least twice by re-suspending them into absolute alcohol. The products could then be well re-suspended in ethanol for further characterization.In a typical synthesis of the SnSe nanoplate-graphene nanocomposite, SeOλ = 0.15418 nm). The UV-Vis-NIR was characterized by the Perkin Elmer Lambda 950. The scanning electron microscopy (SEM) was characterized by Hitachi SU-8010. Transmission electron microscopy (TEM) attached with selected area electron diffraction (SAED) was characterized by JEOL ARM-200F. The Raman spectroscopy was recorded at room temperature using HORIBA Jobin Yvon Evolution with laser excitation at 532 nm with power less than 5 mW. The interdigital gold electrode (the separation between them was 5 μm) on the SiO2 substrate was fabricated by photolithography with lift-off technology. The electronic property was measured by Keithley 4200 semiconductor characterization systems. The SAN-EI ELECTRIC XES-40S1 Solar Simulator (100 mW/cm2) was used as the white light source.The powder X-ray diffraction pattern (XRD) is characterized by PANalytical X’Pert ProMPD ), which is consistent with the previous reports [The powder X-ray diffraction (XRD) pattern is performed to elucidate the phase structure of the SnSe nanoplate-graphene nanocomposites. As shown in Fig.  reports . It is wThe as-synthesized products were then characterized by SEM and the typical results are shown in Fig. In order to obtain the detailed crystal structure and crystal quality of the as-synthesized products, the SnSe nanoplate-graphene nanocomposites were characterized by transmission electron microscopy (TEM), HRTEM, and the selected-area electron diffraction (SAED). As shown in Fig. −1 respectively are clearly observed, which are consistent with the previous report [−1 belongs to the B3g phonon mode originated from the rigid shear modes of a layer with respect to its neighbors in the c directions. It has the highest intensity, indicating the layer structure of the SnSe nanoplates, which is consistent with the XRD results shown above. On the other hand, the D band at approximately 1349.8 cm−1 originated from the disorder and the G band at 1588.4 cm−1 coming from the in-phase vibration were all observed clearly (Fig. Furthermore, the Raman spectroscopy was also performed to investigate the quality of the SnSe nanoplate-graphene nanocomposites. As illustrated in Fig. s report , 22. Theπ → π* transitions of aromatic C–C bonds, and a weak shoulder near 300 nm, attributing to σ → π transitions of C–O bonds [The optical absorption behavior of the SnSe nanoplate-graphene nanocomposites and GO dispersed in ethanol were studied by UV-Vis-NIR spectroscopy in the region of 400–1600 nm. As seen in Fig. –O bonds . On the 2 substrate. The electrode was fabricated by photolithography, and the separation between the adjacent fingers was 5 μm. The white light response of the device was measured by Keithley 4200 apparatus under the periodical illumination of a sunlight simulator with a power density of 100 mW/cm2. The typical I-V characterization of the device is shown in Fig. In order to evaluate photo-electronic property of the SnSe nanoplate-graphene nanocomposites for the white light, the photodetector device prototype was fabricated as described in the inset of Fig. The 2D-2D nanocomposites namely SnSe nanoplate-graphene nanocomposites have been successfully synthesized and investigated. The photodetector device prototype of the as-synthesized products was fabricated and characterized carefully. The device shows a linear behavior in the dark and the resistance decreases sharply under the white light. Furthermore, the photosensitivity of the device is much larger than one order of magnitude with reversible and stable under a rapid response time, which is much better than previous reported. The high performance of the device may originate from the larger interface region from the face-to-face contact and special energy band of SnSe nanoplates and graphene. The results may hopefully be guidance to design and fabricate the photodetector based on the 2D-2D nanocomposites even beyond the SnSe nanoplate-graphene nanocomposites.


Raman spectroscopy and electrical transport measurements showed the n-doping effect of graphene by KNO3. The effect was most dominant in single layer graphene, and the mobility of single layer graphene was improved by the factor of more than 3. The chemical doping by using KNO3 provides a facile approach to improve the electrical properties of graphene layers sustaining their unique characteristics.Although the electronic properties of graphene layers can be modulated by various doping techniques, most of doping methods cost degradation of structural uniqueness or electrical mobility. It is matter of huge concern to develop a technique to improve the electrical properties of graphene while sustaining its superior properties. Here, we report the modification of electrical properties of single- bi- and trilayer graphene by chemical reaction with potassium nitrate (KNO The fAnother important theme in current graphene-based research is to explore the doping effect of graphene with different number of layers, where the band structures are distinct , 23. The3) solution which was dissolved in deionized water. Potassium ions in aqueous solution adsorbed on the top surface of graphene inducing the n-type doping effect.Potassium (K) doping plays an important role in adjusting the electronic properties of carbon materials. The potassium atoms donate their valence electrons to the graphene surface layer, making the n-type doping effect. There were a number of reports on the doping effect of graphene by deposition of potassium atoms in vacuum –30. Ther3 solution in this paper provides unique advantages because it enhances the mobility of graphene layers without inducing defects in graphene as we confirmed by Raman spectroscopy. However, the adsorbed molecules form covalent bonding with graphene surface in some other chemical doping methods. The covalent bonding between chemical species and carbon atoms changes basic electronic structure of graphene and causes substantial reduction of the carrier mobility [The chemical doping of graphene with KNOmobility , 33–35. mobility , 36–41.3 solution. The electrical transport measurements and Raman spectroscopy techniques revealed that chemical reaction with KNO3 induced n-doping of graphene and reduced the impurity scattering to enhance the performance in SLG, BLG and TLG devices. The n-doping effect was enhanced with increasing the reaction time. This kind of chemical doping provides a facile approach to tune the electrical properties of graphene layers.Here we report modification of electrical properties of mechanically exfoliated single layer graphene (SLG), bilayer graphene (BLG) and trilayer graphene (TLG) field-effect transistors (FETs) by chemical reaction with KNO2.2.1.2 wafer [2 substrate. For complete device fabrication and electrical measurements the fine electrodes were made by e-beam lithography and then Cr/Au (12/60 nm) were also deposited by thermal evaporation technique. The scanning electron microscopy (SEM) images of final graphene devices are shown in the insets of figure The SLG, BLG and TLG were obtained by mechanical exfoliation of natural graphite flakes by using the Scotch tape and then transferred on Si/SiO2 wafer . These gen Cr/Au 2/60 nm w2.2.3 was investigated by electrical transport measurements and Raman spectroscopy. Measurements were performed on the same devices before and after different reaction time of KNO3 treatment for SLG, BLG and TLG samples. Potassium nitrate is a chemical compound and an ionic salt of potassium ions K+ and nitrate ions NO3−. It was dissolved in deionized water to make the concentration of 0.1 M solution. The Raman spectra were taken at room temperature with a Renishaw microspectrometer. A 514 nm laser was used for excitation, and its power was kept at 1.0 mW to minimize the laser-induced heating effect. The area of laser spot is around 1 μm2 and the spectral resolution is better than 1 cm−1. The SLG, BLG and TLG samples were dipped in the KNO3 solution for a certain reaction time and then dried with nitrogen gas and heated at 100 °C on hot plate for 2 min. Furthermore, we put these samples in vacuum for 2 h to completely dry. The Dirac points of graphene layers were examined in vacuum by gate voltage dependent resistivity measurement using 4-probe configuration with standard lock-in amplifier.The modification of graphene properties by KNO3.−1, respectively. The intensity ratio of 2D and G peaks is found to be 2.6 which confirms the signature of SLG. In figure −1 and 1586 and 2710 cm−1, respectively. The absence of D peak in SLG, BLG, and TLG is a signature of high quality of graphene layers.Raman spectroscopy is a standard nondestructive and fast tool to characterize and identify the number of graphene layers , 43. Fig3 for different reaction times . It is already reported that the shift of the G and 2D peaks positions toward lower wavenumbers is attributed to n-type doping [3-doped SLG. A red shift in the G and 2D peak positions is observed after KNO3 treatment, the shift increases with increasing the reaction time.Figure e doping , 44, 45,e doping –48. Figu3-doping are also shown in figures Figure 2D/IG) before and after KNO3 treatment for SLG, BLG and TLG for different treatment time. The I2D/IG decreases with increasing of the reaction time for SLG, BLG and TLG. This reduction indicates the doping of graphene layers with KNO3 [3 treatment. The FWHM decreases with increasing of the treatment time by KNO3, which indicates that impurity scatterings are suppressed [3 did not change the band structure of graphene layers and made non-covalent bonding with carbon atoms [Figure ith KNO3 , 23, 49.ppressed . In addion atoms .g) before and after KNO3 treatment of SLG, BLG and TLG is shown in figure Dirac) of SLG towards negative gate voltage as we increase the reaction time. The Dirac point of pristine SLG was observed at +47 V and then shifted towards +4 V after 1 min treatment time. The shift increased gradually with increasing treatment time and was saturated at −49 V after 20 min treatment. Figures The n-doping effect of exfoliated SLG, BLG, and TLG is also confirmed by electrical transport measurements. The resistivity as a function of gate voltage  of SLG, BLG, and TLG as a function of KNO3 reaction time. Figure 3 treatment. The changes in charge carrier density (Δn) of graphene layers were estimated by using the relation Δn = Cg(Vg − VDirac)/e, where Cg is the gate capacitance ∼115 aF μm−2 for our Si/SiO2 substrate, VDirac is the Dirac point of SLG, BLG, and TLG, Vg is the back gate voltage and ‘e’ is the electronic charge. The change in charge carrier density of graphene layers is related with change in Fermi level of graphene layers by KNO3-doping.Figure 3 reaction time. The field effect mobilities of the different graphene layers were obtained using relation μ = (1/Cg) (∂σ/∂Vg), where σ = 1/ρ is the conductivity of samples. The mobility of pristine and doped graphene was calculated on the basis of slope fitted to the linear region of their respective conductivity data. The charge carrier mobility of SLG, BLG and TLG increases with increasing the treatment time. The electron mobility of SLG, BLG and TLG was improved by 424%, 178% and 130% respectively after 20 min reaction with KNO3 solution. Similarly the hole mobility of SLG, BLG and TLG was enhanced by 183%, 23% and 11% respectively after 20 min reaction with KNO3 solution. The mobility improvement was most dominant for SLG because the entire graphene layer is directly exposed to KNO3 solution. This is a surprising result, since the doping treatments of graphene mostly have shown reduction of mobility [Figure mobility , 53, 54.4.3 solution. The electrical transport measurements and Raman spectroscopy confirmed that KNO3 imposes the n-doping for all graphene layers. The shift of G and 2D band positions and intensity ratios of I2D/IG for SLG, BLG and TLG are analyzed for different reaction times. The magnitude of I2D/IG for SLG, BLG, and TLG decreases as the doping effect increases. For all graphene layers the D peak intensity does not increase after the reaction with KNO3 solution. So this indicates that KNO3 does not change the band structure of graphene layers. The shift of Dirac points toward negative gate voltage also confirmed the n-doping by KNO3 treatment. The mobilities have been found to be gradually improved with reaction time. These results indicate that chemical modification is a useful approach to tailor the electrical properties of graphene layers while enhancing the mobility of graphene FET devices. Chemical doping using KNO3 can play an important role in modulating the electronic properties of graphene layers for future graphene-based transparent electronics.We have investigated the electrical properties of mechanically exfoliated SLG, BLG and TLG by reaction with KNO


Predictive biomarkers for antibodies against programmed death 1 (PD-1) remain a major unmet need in metastatic melanoma. Specifically, response is seen in tumors that do not express programmed death ligand 1 (PD-L1), highlighting the need for a more sensitive biomarker. We hypothesize that capacity to express PD-L1, as assessed by an assay for a PD-L1 transcription factor, interferon regulatory factor 1 (IRF-1), may better distinguish patients likely to benefit from anti-PD-1 immunotherapy.Samples from 47 melanoma patients that received nivolumab, pembrolizumab, or combination ipilimumab/nivolumab at Yale New Haven Hospital from May 2013 to March 2016 were collected. Expression of IRF-1 and PD-L1 in archival pre-treatment formalin-fixed, paraffin-embedded tumor samples were assessed by the AQUA method of quantitative immunofluorescence. Objective radiographic response (ORR) and progression-free survival (PFS) were assessed using modified RECIST v1.1 criteria.p = 0.044). There was an insignificant trend toward higher PD-L1 expression in patients with PR/CR (p = 0.085). PFS was higher in the IRF-1-high group than the IRF-1-low group (p = 0.017), while PD-L1 expression had no effect on PFS (p = 0.83). In a subset analysis, a strong association with PFS is seen in patients treated with combination ipilimumab and nivolumab (p = 0.0051).Nuclear IRF-1 expression was higher in patients with partial or complete response (PR/CR) than in patients with stable or progressive disease (SD/PD)  contains supplementary material, which is available to authorized users. Blockade of the PD-1/PD-L1 axis has revolutionized treatment of metastatic melanoma in recent years, with five-year survival rates as high as 34% for patients treated in the initial trials of nivolumab –5. DespiGiven this risk-benefit profile, there is no broadly accepted diagnostic assay to identify patients that are most likely to respond to PD-1 blockade. In melanoma and other tumor types, clinical trials have focused on immunohistochemical (IHC) staining of programmed death ligand-1 (PD-L1) as a potential predictive biomarker for response. PD-L1 isOne potential explanation for PD-L1 protein expression’s relatively poor performance as a predictive biomarker is its markedly heterogeneous staining pattern . In multde novo in response to IFNγ binding, making it uniquely amenable to IHC assays. While it is possible that IRF-1 expression correlates with that of PD-L1, detection of this transcription factor may represent a method to determine a cell state that is capable of expression of PD-L1, when facilitated by local molecular microenvironment [Thus, we hypothesized that identifying a tumor’s capability to express PD-L1 under the appropriate conditions might identify a broader range of cases that may respond to anti-PD-1 agents than assessment of PD-L1 alone. Specifically, we considered the expression of the PD-L1 transcription factor interferon regulatory factor-1 (IRF-1) as a possible marker for this capability. IRF-1 lies immediately upstream of PD-L1 in the IFNγ-driven JAK/STAT signaling cascade , and hasironment .To evaluate IRF-1 as a predictive biomarker, we sought to quantitatively compare PD-L1 expression with a comparable IHC assay for IRF-1 in predicting response to anti-PD-1 immunotherapy. We hypothesized that high IRF-1 expression may reflect a tumor’s ability to benefit from anti-PD-1 therapy independent of its PD-L1 expression status.Melanoma cell lines were grown to 80% confluency, serum-starved for 24 h and then treated with IFNγ or control media for 24 h. Cells were then fixed directly on chamber slides, lysed for Western blotting, or fixed with formalin to generate paraffin-embedded (FFPE) pellets. Cells grown on chamber slides were washed twice in 1X phosphate-buffered saline (PBS) and then fixed in 4% paraformaldehyde (PFA) with 88 mM sucrose. For FFPE cell pellets, five ten-centimeter plates grown to confluency were first rinsed with PBS, and fixed in a solution 4% PFA at 4° Celsius overnight. Cells were then resuspended and rinsed three times in PBS before being washed twice in 80% ethanol (EtOH). Cell pellets were spun at 12,000 RPM and embedded in 2.2% melted agarose in PBS. Agarose-embedded pellets were incubated in 70% EtOH overnight and then sequentially dehydrated with one-hour incubations of 90% EtOH and 100% EtOH, two one-hour xylene washes, and submerged in molten paraffin for two hours before embedding.Antibodies for IRF-1  and PD-L1  were validated  by migraCells were lysed in ice-cold M-PER mammalian Protein Extraction Reagent (Thermo Scientific) supplemented with protease inhibitors. To determine protein concentration a Bradford assay was conducted using the Bio-Rad protein assay reagent . Proteins (30 μg) were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to a nitrocellulose membrane . The resulting blots were blocked for 1 h at room temperature (RT) in 5% skimmed dry milk diluted in 1X Tris-buffered saline supplemented with Tween-20 (TBST). Blots were incubated at 4 °C overnight in primary antibodies specific for PDL-1  or IRF-1 . Following incubation, blots were washed with 5% milk/TBST before incubation with a horseradish peroxidase, labeled goat anti-rabbit IgG  at RT for 1 h. Blots were washed with 5% milk/TBST and bands were visualized using electrochemiluminescence detection reagents (Thermo Scientific).Medical records and tissue samples were identified for melanoma patients with non-ocular primary tumors treated with pembrolizumab or nivolumab within the Yale-New Haven Health system before April 1, 2016 under a protocol approved by Yale Human Investigations Committee. 51 cases with available pre-treatment tissue specimens were identified and selected by a board-certified pathologist. Of these, 47 had appropriate imaging available  to determine response and PFS by objective criteria. Of the 47 cases, 21 (45%) demonstrated a partial or complete response, including one case of pseudo-progression. Objective radiographic response (ORR) and PFS were determined by review of available CT or MRI scans using modified RECIST v1.1 criteria . To accoFFPE whole-tissue sections, tissue microarrays (TMAs) and cell pellets were processed and stained as previously described. BrieflyPrimary antibodies were followed by incubation with Alexa 546–conjugated goat anti-mouse secondary antibody (Life Technologies) diluted 1:100 in rabbit EnVision reagent (Dako) for 1 h. Signal was amplified with Cy5-Tyramide (Perkin Elmer) for 10 min, and then nuclei were stained with DAPI in BSA-tween for 10 min. Slides were mounted with ProlongGold (Life Technologies). Two TBS-T washes and one TBS wash were performed between each step after the primary antibody.For cells fixed on chamber slides, samples were washed twice in PBS after fixation and permeabilized with 0.25% Triton X-100 in PBS for 10 min. Cells were washed twice in PBS and blocked with 1% BSA in PBS for 1 h at room temperature. Block was decanted off slides and the primary antibody cocktail as described above was applied. Subsequent steps were identical to the staining of FFPE tissue, except the DAPI stain was substituted for mounting Prolong Gold with DAPI (Life Technologies). One PBS-T and one PBS wash were performed between each step after the primary antibody.Immunofluorescence was quantified using automated quantitative analysis (AQUA) on all fields of view containing tumor on each slide. Briefly, fluorescent images of DAPI, Cy3 (Alexa 546-S100/HMB45), and Cy5 (PD-L1 or IRF-1) for each field of view (FOV) were collected. Image analysis was carried out using the AQUAnalysis software (Genoptix), which generated an AQUA score for each compartment by dividing the sum of target pixel intensities by the area of the compartment in which the target is measured . PD-L1 wFFPE cases were stained for IRF-1 as described above through the secondary antibody incubation. Then, slides were incubated with 3,3'-diaminobenzidine peroxidase substrate (Vector Laboratories) for 8 min and counterstained with Tacha’s Auto Hematoxylin . Slides were then dehydrated in washes of 70% EtOH, 100% EtOH, and xylenes before mounting. Chromogenic staining for PD-L1 was performed using the FDA-approved 22C3 assay on the DAKO Link 48 automated staining platform.t test; PFS and OS between groups were compared using the log-rank test. A Cox proportional hazards model was constructed with age, sex, race, mutational status, prior checkpoint blockade, and IRF-1 status. All univariate statistical analyses was performed using GraphPad Prism 7 (GraphPad Software), and multivariate analysis was performed with JMP 11 (SAS Institute). All p values reported for subset analyses are descriptive and were not adjusted for multiple comparisons. For each biomarker, the sample size of 47 patients was sufficient to detect an 83% standard-deviation difference in AQUA scores between responders (CR/PR) and non-responders (PD/SD) with 80% power at p = 0.05.AQUA scores between responders (PR/CR) and non-responders (SD/PD) were compared using an unpaired To identify IRF-1 expression patterns in melanoma tissue, two TMAs of unselected melanoma cases (YTMA 98 and YTMA 59) were stained for IRF-1 Fig. . Of 115 To assess IRF-1 as a predictive marker for response to PD-1 blockade, serial whole-tissue sections from 47 melanoma patients treated with anti-PD-1 immunotherapy were then stained for IRF-1 and PD-L1 in three batches. Batch-to-batch assay reproducibility was assessed by correlating scores from an index tissue microarray run with each batch . To determine if there was biologic significance to this cutpoint, we determined the limit of detection for IRF-1 by staining five serum-starved melanoma cell lines for IRF-1 and identifying the lowest AQUA score a FOV with positive nuclear staining. Of five cell lines, only YUSOC had positive IRF-1 staining in the absence of IFNγ; the lowest FOV AQUA score was for YUSOC was 171 . Similarly, cases were stratified into PD-L1-high and PD-L1-low cohorts using a visual cutoff of 120. There was no difference in PFS  between these two cohorts.When classified by best ORR, AQUA scores for nuclear IRF-1 expression was higher in patients with PR/CR than in patients with SD/PD (p = 0.0002). However, within the PD-L1-low cohort, four cases were classified as IRF-1-high. An example of one of these cases with high IRF-1 and low PD-L1 is shown in 4B and C. Despite this small sample size, there was a trend toward better PFS in those patients compared to those classified as IRF-1-low, PD-L1-low (p = 0.083).PD-L1 expression correlated with IRF-1 expression with a Pearson’s correlation coefficient of 0.52 , but this difference did not reach statistical significance in patients treated with single-agent nivolumab or pembrolizumab .When patients were grouped by therapy , IRF-1 predicted longer PFS in the combination ipilimumab/nivolumab group (p = 0.0023) when adjusted for age at diagnosis, race, sex, stage group at diagnosis, mutational status, and prior checkpoint blockade.In a Cox proportional hazards model for PFS, IRF-1-low status conferred a hazard ratio of 7.13 , marked differences in stromal cell expression of IRF-1 were noted across cases. Also, it is possible that combination of IRF-1 and PD-L1 or other contributory transcription factors could increase the predictive power of this assay—a multiplex assay including both markers would be most appropriate for testing this hypothesis. In doing so, alternative antibodies for PD-L1 could be considered, as the SP142 clone used in this study has recently been shown to equivalent to other antibodies, including those used in current companion diagnostic tests . HoweverWhile the underlying mechanisms remain unclear, there are a number of biological explanations that could explain the association between IRF-1 expression and response to anti-PD-1 immunotherapy. With further validation, it is possible that an IHC-based assay for IRF-1 could be readily transferred to the clinical setting. The concept of a companion diagnostic tested based on capability to express the target of PD-1 axis therapy may address some of the current assays deficiencies related to heterogeneity or other less well defined variables.This study is this first report of IRF-1 as a tissue-based biomarker to predict response to anti-PD-1 immunotherapy in melanoma. Compared to PD-L1 status, nuclear IRF-1 staining better predicted objective radiographic response and progression-free survival in a retrospective cohort of 47 melanoma patients. Furthermore, this effect was greatest in patients treated with combination ipilimumab and nivolumab, which is rapidly being adopted as a standard of care. Given the limited utility of PD-L1 as a predictive biomarker in this disease, assays for IRF-1 warrant further investigation in randomized controlled trials to determine if they could serve as clinically useful alternatives to guide treatment decisions.


We demonstrate how terahertz time-domain spectroscopy (THz-TDS) operating in reflection geometry can be used for quantitative conductivity mapping of large area chemical vapour deposited graphene films on sapphire, silicon dioxide/silicon and germanium. We validate the technique against measurements performed with previously established conventional transmission based THz-TDS and are able to resolve conductivity changes in response to induced back-gate voltages. Compared to the transmission geometry, measurement in reflection mode requires careful alignment and complex analysis, but circumvents the need of a terahertz transparent substrate, potentially enabling fast, contactless, in-line characterisation of graphene films on non-insulating substrates such as germanium. Chemical vapour deposition (CVD) has become the dominating technique to synthesise large area “electronic-quality” graphene2, with the size of single mono-layer graphene crystals now on the cm-scale3 and continuous films now routinely produced roll-to-roll or at a size just limited by the reactor4. In fact, progress in growth reached a level where detailed, adequate characterisation over such large areas has become a key challenge. Prevailing electrical characterisation for instance is based on the fabrication of field-effect or Hall bar devices typically combined with Raman spectroscopy. This is time-consuming for large samples and for statistically relevant sample numbers in particular also as the as-grown graphene typically has to be transferred away from the growth substrate. Among a range of emerging contactless characterisation methods, terahertz time-domain spectroscopy (THz-TDS) operating in transmission geometry has been demonstrated to allow the direct, accurate mapping of graphene conductivity and mobility over large areas, producing data consistent with the Drude model to describe graphene intra-band transitions10. Graphene’s complex conductivity is determined by the terahertz pulse transmitted through the graphene film relative to the support, and analysed using Fresnel coefficients where graphene is modelled as an infinitely thin conducting film. Drift and field-effect mobilities can then be extracted by fitting the conductivity spectra to the Drude model9, and measuring graphene conductivity changes as a function of the applied back-gate voltages on a gate-stack support8, respectively. By repeating the measurement and analysis across the entire graphene area, a conductivity or mobility map can be reliably produced. While these demonstrations could potentially enable a rapid in-line graphene monitoring and large-area characterisation, to date THz-TDS has been carried out in transmission mode that necessitates a terahertz transparent support.The development of scalable integrated manufacturing pathways for graphene is crucial to all its emerging applications and industrial development15. As schematically outlined in Fig. 10 on the same graphene sample. For this we use CVD grown graphene synthesised on commercial Cu foils and transferred to a sapphire substrate, which has the required transparency in the THz frequencies. We then show that by sample back-gating, our proposed method can be used to resolve graphene conductivity changes and hence to directly determine the graphene mobility on a p-doped Si substrate with a 300 nm thick SiO2 layer, which is one of the most commonly used substrates for graphene device manufacturing. To illustrate that this technique has potential as a tool for in-line graphene quality monitoring, we show that the graphene conductivity can also be directly mapped on a substrate like Ge, which has a considerable number of intrinsic carriers at room temperature (42 Ω·cm) and exhibits a Drude like carrier absorption16. In particular we demonstrate THz-TDS mapping for graphene that has been directly grown on Ge.Here we overcome this restriction and demonstrate, as a proof-of-concept, the quantitative contactless measurement of the electrical conductivity of CVD graphene on a range of application relevant supports using THz-TDS operating in reflection geometry. Reflection based THz-TDS has previously been used to characterise optically dense materials where due to the high energy loss within the sample, transmission based measurement cannot be used17. We use standard Cu foils  and CH4 as the carbon precursor18. For transfer, PMMA (poly methyl-methacrylate) was used as support, followed by FeCl3 chemical etching to remove the Cu. As target substrates we used sapphire (430 μm thick), Si/SiO2 wafer (300 nm/525 ± 25 μm thick), and intrinsic single crystalline Ge (110) wafer . Raman spectroscopy was performed using a 532 nm laser for characterising the transferred graphene. The Si wafer support was boron-doped (100 Ω·cm) to allow back-gating. The process conditions for graphene CVD directly on Ge were similar to recent reports in literature19 and we used Ge (110) wafer substrates and a 1:52 precursor gas mixture of CH4/H2 at a growth temperature of 920 °C in a Aixtron Black Magic cold wall CVD reactor.As reference process and material, we use well-established graphene CVD on commercial Cu foil and subsequent PMMA transfer, which is widely used in literature20 that in turn allows us to estimate the spot size of approximately 420 μm with Gaussian beam optics21. One of the main barriers for accurately extracting optical parameters in reflection geometry is the great sensitivity to any phase misalignment between the sample and reference measurements. In general, the phase misalignment can be mitigated by performing additional measurements with a slab of material of known optical constants14, maintaining same path length change for both terahertz and optical beam15 and numerical correct phase correction using the maximum entropy method22. Attention was given to precise sample positioning by having both the Al mirror and the sample mounted on a motorised stage and positioning the respective front surfaces in order to ensure that the particular reflecting plane reflects the incident wave into the detector at maximum level12. It should also be noted that the substrate refractive index measured is not adversely affected by phase misalignment, as in the case for the extinction coefficient13. As an experimental check, the measured substrate refractive index for s-polarisation23 was always compared against the literature values. The reflection coefficient depends on the polarisation of the incident terahertz wave and the angle of incidence. Given the substrate refractive index and using Tinkham’s formulae to describe the effect of a thin conducting film24, the equation for obtaining conductivity from s-polarisation reflection measurements can be derived as:0 is the vacuum impedance (376.7 Ω), θi and θt are the incident and transmitted angles, respectively, and 26. At normal incidence and assuming zero conductivity, we get the well-known Fresnel coefficient for the reflection at the interface:Reflection based THz-TDS experiments were conducted with a Terahertz Pulsed Imaging (TPI) Imaga 2000 system , as schematically shown in Fig. 27.The analysis becomes simpler at normal incidence but such a reflection system in turn would require a beamsplitter that is not commonly implemented due to reflection lossesUsing Snell’s law 28; (2) determining reflections from graphene and the substrate using the Fresnel coefficients, the real part of the materials refractive index in the literature16 and a constant graphene conductivity value for CVD graphene grown on Cu foil29; and (3) applying the derived expressions to obtain conductivity for comparison against the conductivity defined in step 2. The use of only the real part of the materials refractive index is justified by the use of substrate materials such as sapphire and intrinsic Ge that have a negligible extinction coefficient in the relevant frequency range between 0.5 to 1 THz16. The simulation highlighted that, where there is a phase shift deliberately introduced between the sample reflection and the reference reflection, the slope of the derived conductivity spectra is no longer zero (see Supporting Information). This fact is exploited in the automated analysis of our measurement for phase correction. It should be noted that phase misalignment can be due to several reasons, such as fibre drifts and mechanical jittering of the optical delay stage, and that these problems are most severe in fibre-coupled terahertz systems as used in this study. Our phase correction method therefore shifts the acquired reflection pulse with respect to the reference measurement in the time-domain in order for the real part of the calculated conductivity spectra to have a slope close to zero. A single step shift in time here corresponds to a sample being placed approximately 2.5 μm with respect to the reference mirror, and a positive value means that the sample position is shifted in the direction of the incident beam. We note that the phase compensation scheme can be alternatively implemented in the frequency domain by multiplying the phase shift term6.We performed analytical simulations to double check the derived expressions and optical constants, whereby the simulations involved (1) simulating a terahertz pulse generated from a photoconductive antenna switch with realistic parameter settings such as 120 fs, 300 fs and 180 fs being the laser pulse duration, emitter/detector carrier recombination and collision time, respectively30. From the raster scanned measurement, the region of the substrate covered by graphene was isolated by masking the data with an intensity threshold value given that the graphene covered area corresponds to regions of higher reflectivity relative to the plain sapphire substrate. As the primary reflection was well separated from the first reflection in the time-domain, a time windowing function was used to process the acquired waveforms in the regions of interest in order to remove Fabry-Perot or etalon effects that would otherwise corrupt the conductivity measurement. A conductivity map was subsequently generated. In order to validate our proposed method, the same sample was scanned with THz-TDS operating in transmission mode. In particular, measurements were acquired with the Tera K15 T-Light  where the 60 mW pump pulse was focused to a 40 μm spot onto the terahertz photoconductive antenna, generating terahertz radiation with a beam diameter of approximately 1 mm at 1 THz. The sample was placed between the terahertz emitter and the detector at normal incidence without nitrogen purge, and data were acquired at an integration time of 10 ms at 200 μm step intervals. The integration time constant corresponded to an average of 700 waveform traces. The region of the substrate covered by graphene was again obtained by intensity masking, where graphene covered areas correspond to regions with a reduction in transmitted intensity due to the higher carrier absorption in graphene10. By performing the analysis detailed in recent literature10, a comparative conductivity map for approximately the same sample area was generated.Transferred graphene on sapphire was measured with TPI at a step size of 200 μm, where 15 waveform traces were averaged to represent a measurement for one single pixel. Here the number of waveforms acquired for averaging is relatively small as would be the requirement for potential in-line applications. Before the measurement, however, terahertz reflection from the Al mirror placed nominally at the same position as the sample was used as reference measurement. An Al mirror generally works as an almost perfect reflector in the terahertz regimehttps://doi.org/10.17863/CAM.12742.Additional data sets related to this publication are available from the Cambridge University data repository at 16. This value was then used to obtain flat conductivity spectra29 (see Supporting Information) without any phase correction, which in turn was used to generate the transmission conductivity map shown in Fig. 7. Here we use transmission measurements to validate our measurements in reflection geometry. The substrate refractive index measured in reflection mode was approximately 3. The slight discrepancy may be due to sample surface related imperfections, leading to scattering losses and measurement with a focused beam as opposed to a collimated beam31. In a manner similar to the literature29 and our transmission measurements, the graphene conductivity spectra on sapphire for a well-aligned reflection measurement have a real part characterised by a flat spectral response near to its DC value well below the Drude roll-off frequency or the inverse scattering time, while the imaginary part is close to zero (see Supporting Information). The spectrally resolved conductivity in turn can be represented by a single real number. It has been shown that phase misalignment would only significantly affect the imaginary part of the conductivity6 and therefore emphasis is placed only on the real part of the conductivity. As the conductivity spectra are approximately constant over the spectral range, the representative conductivity is taken as the average between 0.6 to 0.9 THz because at higher frequencies, the transmission conductivity spectra (see Supporting Information) become affected by water vapour absorption under ambient conditions. This effect become visibly more pronounced with increasing optical path length. Similarly, for the conductivity measurement in reflection mode, the representative pixel conductivity is taken as the average over the same spectral range of 0.6 to 0.9 THz.Figure 6, as opposed to the first echo in a transmission measurement, even though the measurement robustness is lower for direct transmission analysis10. Overall, we were able to validate our proposed approach with good agreement against established transmission measurements.Figure 32 via a graphene film transferred to a p-doped Si substrate  where various different DC voltages between −160 to 160 V were applied. The back-gate leakage current was negligible. At a fixed point on graphene and at every 20 V back-gate voltage increments, reflection measurements were acquired on the TPI at 15 waveforms per average. The acquired waveforms were then analysed and the sequence of steps were then repeated for 2 other randomly selected locations on the graphene. The measurements were performed in ambient conditions at room temperature. Figure g between 40 and 60 V, reflection is the weakest indicating that the Fermi energy at this gate voltage is closest to the Dirac point. At all other voltages below 40 V terahertz reflection increases monotonically with Vg as shown in Fig. 8. Due to the aforementioned reasons, the spectrally resolved conductivity is represented by a single real-value conductivity value taken as the average conductivity between 0.4–0.9 THz. Figure g ≤ 60 V representing the field-effect mobility of the hole-carriers. For Vg > 60 V, a slow conductivity change is observed indicating that electron-mobility is impaired in this graphene film. Linear curve-fitting was used to extract the line slope to determine hole-mobility. A R2 value of 0.986 was achieved in the fit that corresponded to a conductivity change of 0.0083 mS Vg−1. This value was then used to determine a mobility of 721 cm2V−1s−1, where 2 gate oxide. The extracted back-gated mobility value is comparable to the mobility values extracted from graphene transistor measurements of graphene films prepared in a similar manner34. Air-exposed graphene on SiO2 is typically found to be p-doped34, consistent with the charge neutrality point VCNP at a positive bias34. Even though not demonstrated here, mobility mapping with terahertz reflection measurement across the sample could in principle be performed by raster scanning the sample at different back-gate voltages.In order to demonstrate that our proposed method can be used to resolve graphene conductivity changes, we implemented simultaneous back-gating2, but other substrates such as flexible polymers are in principle possible too provided sufficient contrast can be observed, which is generally the case as the real part of the refractive index is less than 2 and the extinction coefficient is negligible at less than 2 THz36. This has been highlighted already for transmission measurements7. The challenge of adequate characterisation of the graphene still on the growth catalyst/support however remains. For instance, even individual Raman measurements of graphene on transition metals can be challenging, not to speak of mapping large graphene areas. As a first step towards direct contactless graphene conductivity mapping on technologically relevant growth substrates, we here focus on Ge substrates. As a starting point we first transferred graphene on intrinsic Ge(110), and then applied our method to graphene directly grown on Ge(110). The Ge (110) orientation is chosen because it yields higher quality graphene under the CVD process used here37. For our initial analysis, the imaginary part of the complex refractive index of Ge can still be assumed to be negligible. For the undoped Ge(110) reference substrate, the graphene conductivity can be expected to be close to the values measured on sapphire, except some minor deviations based on, for instance, charge transfer between graphene and Ge38. Hence we can also assume that the real conductivity spectra remain constant over the THz spectral range29. For reflection measurements on highly doped Ge, the assumption of a negligible extinction coefficient will no longer hold39 and therefore the frequency dependent extinction coefficient needs to be accounted for in the conductivity analysis. Accurate measurement of the extinction coefficient in turn would require very high precision alignment between the sample and reference13. Analogous to our measurements of graphene on sapphire, the graphene film transferred on Ge was measured with TPI at a step size of 200 μm where 15 waveform traces were averaged. A conductivity map was then generated from the raster scanned measurement by applying the aforementioned analysis where the region of graphene coverage was obtained by intensity masking the data, where the graphene covered area corresponds to regions with higher reflection relative to Ge. The measured substrate refractive index of Ge was approximately 4 in close agreement with literature16. It should be noted that the contrast i.e. reflection change from bare Ge substrate to graphene covered area is approximately 5% for graphene with conductivity of 1.2 mS. This can be compared against graphene on sapphire where for the same conductivity, the contrast is approximately 10%, allowing a clear discrimination between graphene covered areas and the bare substrate. With a lower contrast, the measurement becomes more susceptible to noise and therefore we defined the threshold for intensity masking by considering an average of the substrate reflection. Figure 38.Utilising a reflection rather than a transmission geometry allows contactless mapping of the graphene conductivity on a wider range of substrates. In terms of integrated graphene CVD manufacturing and process optimisation, a clear need is to probe graphene at each process step. We here so far discussed two examples of graphene conductivity measurements after graphene transfer on substrates like sapphire and Si/SiO40. In principle, these substrates could also work with transmission THz-TDS, though the measurement may slightly overestimate the conductivity due to increased carrier absorption as the terahertz pulse makes a return path inside the substrate. The fact that there is an observable contrast in the reflection measurement is promising for future conductivity mapping of graphene synthesised directly on Ge. It can be expected that in samples where contrast is lower, either because of a higher substrate refractive index at terahertz frequencies, a lower graphene conductivity, or a combination thereof, the conductivity measurement in reflection geometry becomes increasingly susceptible to the effect of signal fluctuations and hence become less reliable. For instance, on growth substrates such as Cu2, no contrast could be observed relative to Cu for a sample of similar graphene conductivity because of the high Cu conductivity (59 MS/m) leading to a refractive index (~730) at least two orders of magnitude larger than that observed for sapphire or Ge at 1 THz. At the same time, it should also be pointed out that with the possibility of making changes to the graphene manufacturing process, such as intercalation of a micron-thick oxide layer41, these changes potentially could be useful to increase the measurement contrast for future in-line characterisation of graphene on e.g. Cu.As final validation, we apply our method to graphene directly grown on Ge(110). After CVD on Ge of a uniform graphene coverage (see Methods), we subsequently used drop casted PMMA photoresist and oxygen plasma etching  to define graphene patterns to allow for reference contrast against the plain underlying Ge. After oxygen plasma etching, the remaining photoresist was removed with acetone. We then measured with TPI at a step size of 75 μm where 50 waveform traces were averaged for one pixel. Figure 2 support, we have further demonstrated the sensitivity of the technique to resolve conductivity changes during electrostatic gating and hence the ability to directly determine graphene mobilities, whereby our values were consistent with standard electrical measurements. To illustrate that this technique has the potential as a tool for in-line graphene quality monitoring, we showed that the graphene conductivity can also be directly mapped on a substrate like Ge, where only half the contrast is seen relative to the sapphire substrate due to an approximately 30% increase in refractive index in the relevant frequency range. For the graphene films synthesised directly on Ge(110), the Ge substrate became highly doped after graphene synthesis and hence high precision alignment is required to accurately determine graphene conductivity. It should be noted that the proposed technique also assumes flat conductivity spectrum, which is not the case for all graphene samples, such as graphene grown on a single Cu crystal. For these samples, provided the shape of the conductivity spectra is known, a similar slope fitting method could be used. A more robust approach, however, would involve high precision alignment that is the subject of ongoing research. Our data shows that while measurement and analysis are understandably more complex and can be less robust when measuring in reflection compared to transmission, especially considering that there is less terahertz interaction with the sample, terahertz time-domain reflection spectroscopy is a highly interesting contactless, quantitative characterisation technique with clear potential to complement existing characterisation techniques for graphene and other related 2D materials and to open new opportunities for the rapid screening of large-area 2D crystals and films, which is crucial towards emerging applications and industrial development of these materials.In summary, we have demonstrated the feasibility and potential of measuring the electrical conductivity of CVD graphene with THz-TDS in reflection geometry. Using terahertz transparent sapphire support, we have validated the technique against current state-of-the-art THz-TDS transmission measurements, where after taking into account the differences in terahertz spot sizes, we find a close agreement between the conductivity histograms. Using back-gated Si/SiOSupplementary information


This research reports micro-Raman measurements on the in-plane E2g optical phonon peaks (~ 1580 cm−1 in graphene layers and ~ 1362 cm−1 in h-BN layers) as a function of temperature from − 194 to 200 °C. The h-BN flakes show higher sensitivity to temperature-dependent frequency shifts and broadenings than graphene flakes. Moreover, the thermal effect in the c direction on phonon frequency in h-BN layers is more sensitive than that in graphene layers but on phonon broadening in h-BN layers is similar as that in graphene layers. These results are very useful to understand the thermal properties and related physical mechanisms in h-BN and graphene flakes for applications of thermal devices.Thermal properties of sp The mul2ghigh peak become smaller. It is in good agreement with the experimental results reported in references [−4 cm−1/(°C nm) in h-BN layers and − 3.5 × 10−4 cm−1/(°C nm) in graphene layers, respectively, in the temperature range from − 194 to 200 °C. The frequency shift in the c direction of the E2ghigh peak is ~ 2.5 times that of G peak as the temperature varied by Δt~400 °C. Meanwhile, the slopes of the FWHM of both G peak and E2ghigh peak have a slight increase with increasing thickness. The FWHM broadenings related to the c direction thickness are evaluated to be 5.5 × 10−5 cm− 1/(°C nm) in h-BN layers and 5.9 × 10−5 cm−1/(°C nm) in graphene layers, respectively, in the temperature range from − 194 to 200 °C. The FWHM broadening in the c direction of the E2ghigh peak has the same sensitivity to temperature as that of G peak. This means that the thermal effect in the c direction on phonon frequency in h-BN layers is more sensitive than that in graphene layers but on phonon broadening in h-BN layers is similar as that in graphene layers. However, we can hardly find relevant theoretical calculations about the frequency shift and the FWHM broadening of E2g phonons with increasing h-BN or graphene thickness to explain the physical mechanism of our experiment. We think our results are attributed to joint contributions of anharmonic interaction and other more complex couplings. The mechanisms are still not well understood and need further study.In addition, with increasing thickness, the frequency shifts of both G peak and Eferences , 17, in ferences , and the2 structures exhibit a similar hexagonal structure with similar lattice parameters, and they are usually stacked to form a multilayer in a stable configuration of AB stacking when prepared by mechanical exfoliation. Given the similarities of an atom structure, the properties of these two materials are expected to be similar to facilitate the comparison. Raman spectroscopy is a powerful characterization tool for graphene and h-BN materials with respect to thermometry. We performed a Raman scattering study of in-plane E2g phonons in layered h-BN and graphene flakes in the temperature range from − 194 to 200 °C. The frequency shifts and FWHM broadenings of E2ghigh peak and G peak indicate that h-BN flakes are more sensitive to temperature than graphene flakes with similar thickness. The effect of the thermal conduction in the c direction on phonon frequency in h-BN layers is better than that in graphene layers but on phonon broadening in h-BN layers is similar as that in graphene layers. These results are very useful to further understand the thermal properties and related physical mechanisms in h-BN and graphene flakes for applications of thermal devices.Graphene and h-BN layers are isoelectronic materials. Their in-plane sp


In public health surveillance, measuring how information enters and spreads through online communities may help us understand geographical variation in decision making associated with poor health outcomes.Our aim was to evaluate the use of community structure and topic modeling methods as a process for characterizing the clustering of opinions about human papillomavirus (HPV) vaccines on Twitter.The study examined Twitter posts (tweets) collected between October 2013 and October 2015 about HPV vaccines. We tested Latent Dirichlet Allocation and Dirichlet Multinomial Mixture (DMM) models for inferring topics associated with tweets, and community agglomeration (Louvain) and the encoding of random walks (Infomap) methods to detect community structure of the users from their social connections. We examined the alignment between community structure and topics using several common clustering alignment measures and introduced a statistical measure of alignment based on the concentration of specific topics within a small number of communities. Visualizations of the topics and the alignment between topics and communities are presented to support the interpretation of the results in context of public health communication and identification of communities at risk of rejecting the safety and efficacy of HPV vaccines.We analyzed 285,417 Twitter posts (tweets) about HPV vaccines from 101,519 users connected by 4,387,524 social connections. Examining the alignment between the community structure and the topics of tweets, the results indicated that the Louvain community detection algorithm together with DMM produced consistently higher alignment values and that alignments were generally higher when the number of topics was lower. After applying the Louvain method and DMM with 30 topics and grouping semantically similar topics in a hierarchy, we characterized 163,148 (57.16%) tweets as evidence and advocacy, and 6244 (2.19%) tweets describing personal experiences. Among the 4548 users who posted experiential tweets, 3449 users (75.84%) were found in communities where the majority of tweets were about evidence and advocacy.The use of community detection in concert with topic modeling appears to be a useful way to characterize Twitter communities for the purpose of opinion surveillance in public health applications. Our approach may help identify online communities at risk of being influenced by negative opinions about public health interventions such as HPV vaccines. The human papillomavirus (HPV) vaccine was first introduced to reduce the incidence of HPV and the majority of cervical cancers . DespiteThe use of social media information in public health applications has previously centered on forecasting clinical outcomes that have traditionally been measured using surveys and registries. Applications of data mining using Twitter have included influenza surveillance -14 and mPeople interact and form relationships to each other on social media. With these relationships, communities are formed. The structure of online communities influences—and can be influenced by—the information that enters and is diffused through them. Studies examining the spread of information through online communities, social media, and news media have shown that the heterogeneous social structure of the network and external factors can play a role in how far and fast new information spreads ,27. ThatDifferences in the content of the information posted in online news and social media influence the variation in opinions and beliefs in online communities. While the opinions held by community members and the content they post are not equivalent, we assume that the content provides a reasonable proxy for the opinions that might influence decision making. Topic modeling methods are appropriate for identifying thematic structure (topic) within a set of tweets because they can be applied to an unstructured corpus of documents and there is no requirement that the topic be defined in advance . The priWe expected to find that homophily and contagion would lead to a clustering of opinions in online communities, but to date there has been little research done to measure this important information for vaccines. Our aim was to evaluate the combination of community structure and topic modeling methods in measuring the distribution of topics about HPV vaccines from the tweets posted by users within communities on Twitter, with the broader goal of evaluating a new process for characterizing online communities by the public health information expressed by the community members.Using repeated searches via the Twitter Search Application Programming Interface, we collected tweets about HPV vaccines between October 1, 2013, and October 29, 2015, using the keywords shown in We pre-processed the tweets prior to topic modeling. For words that were hashtags (beginning with “#”) or usernames (beginning with “@”), we made no further modifications. The remaining words in the text of the tweet were converted to lowercase, and we removed stop words, the word “RT” (which represents a retweet), and any numerical values. We then applied the Porter stemmer . We exclWe ran Latent Dirichlet Allocation (LDA) and the Dirichlet Mixture Model (DMM) to infer the topics of the 125,003 unique tweets that were identified within the set of 284,303 tweets after pre-processing the text. After inferring the topics using LDA and DMM, we mapped those topics back onto the full set, so that each tweet was associated with a single topic.We constructed the network from the 4,387,524 follower connections among the 101,519 users using an undirected graph. A node represents a user, and an edge between two users is established if one was found to be following the other. The network included 100,826 (99.32%) users comprising the single largest connected component, 500 (0.49%) users who formed smaller islands disconnected from the largest connected component, and 193 (0.19%) disconnected users with no connections to the core. Within the largest connected component, the average number of social connections was 86.98 and the largest number of connections was 18,635. We measured the alignment between topics and communities for the users who were part of the largest connected component. More details on network construction are provided in Community detection algorithms aim to find sets of nodes in a graph that have a greater density of connections within their set compared to across sets. Traditionally, community detection algorithms produced a hard clustering—where each node belongs to only one community -47. SomeThe Infomap algorithm was developed to extract community structure in large complex networks . Using rThe Louvain algorithm is a relatively fast community detection algorithm to compute and can therefore scale to large networks . The algTopic modeling is used to find natural clusters based on the co-occurrence of words. We used the Latent Dirichlet Allocation (LDA) model  and the The aim of measuring the alignment between topics and communities is to determine if the topics appear more frequently within some communities relative to all others. Since each tweet was associated with a single topic, we represented communities by the distribution of topics in the tweets posted by the users in that community. We adapted measures of alignment that are typically used to quantify the quality of an estimated clustering against an observed clustering to compare between the clustering methods that use the observed structure  and the clustering methods that use the observed content (topics in tweets). There are several appropriate metrics for assessing cluster quality in this scenario, including purity, normalized mutual information (NMI), and the adjusted Rand index (ARI) ,58 (see TC). We defined a TC value by the smallest number of communities required to cover a specified percentage of the tweets about a given topic, so TC95 is the number of communities required to cover 95% of the tweets in that topic, and TC100 is the number of communities that covers every tweet labeled with that topic. A lower TC95 value therefore implies a higher concentration of topics within a small number of communities.While these typical metrics provide a general measure of the alignment between community structure and the topics of the tweets posted by users in those communities, they were not useful for summarizing how topics may be disproportionately represented within a small subset of the communities. We therefore additionally considered a measure of topic concentration  were produced rather than single values, so we used a two-sample Kolmogorov Smirnov test to compare the distributions. The Kolmogorov-Smirnov test statistic varies between 0 and 1, and a higher test statistic means that the topics were more concentrated within individual communities than would be expected if the same number of tweets per topic were randomly distributed across the communities.When comparing measures of topic concentration across multiple networks to determine alignment, the differences in the number of tweets associated with each topic can influence the measures independently of the alignment, so we used permutation tests to produce a fair comparison. The permutation tests create a baseline distribution of y chance . To do tWe performed intrusion tests on the topics from the tweets. One investigator, blinded to the results of the topic modeling, was presented with sets of five test cases per pairwise combination of topics. Each test case included the text of five tweets chosen at random from one topic and one tweet chosen at random from a different topic. The investigator was tasked with identifying the tweet that did not belong to the topic. The results of these intrusion tests indicated how well the topic modeling was able to capture semantic differences in the tweets. We additionally used the results of the intrusion tests to construct a hierarchy of topics based on their semantic dissimilarity by applying multidimensional scaling -62. The The two community detection algorithms were applied to the largest connected component of 100,826 users. Applying the Louvain algorithm, we identified 38 distinct communities of sizes between 3 and 21,733 users. The Infomap algorithm identified 1334 distinct communities, ranging in size from 2 to 18,974 users.We constructed a series of LDA and DMM models by varying the number of topics between 5 and 200. From the purity, NMI, and ARI scores, we found that the alignment between the community structure and the topics was higher across all measures for DMM compared to LDA. The highest purity score (0.495) and the highest ARI scores (0.166) were found when applying the DMM model with the Louvain algorithm. The highest NMI score (0.185) was found when applying the DMM model with the Infomap algorithm. The results of these experiments suggest that the DMM topic model may have produced a more realistic clustering of the tweets by topic.TC95 scores were consistently higher when using the DMM model compared to the LDA model  and the Louvain algorithm to demonstrate the characterization of the communities by topic in what follows.The To illustrate how the topics tend to cluster within communities, we selected three representative topics and visualized them in the network constructed from the set of followers among the 100,826 users . The topTopic 27 includes words that are common to published studies about the efficacy of the vaccine such as “prevent,” “protect,” “study,” “news,” and “research.” Links to news media alongside other published articles and related media tended to be grouped within this topic, and the topic is broadly represented throughout the majority of the core network, including among the users with the greatest number of connections .Topic 0 captures a large number of tweets from users describing their own experiences with the vaccine, including temporal words such as “today,” “get,” “got,” and “go.” Tweets including phrases such as “my arm hurts like a...” were commonly assigned to this topic, and these users appeared to share fewer connections with other users posting about HPV vaccines.In Topic 26, emotive words like “kill,” “victim,” and “death” are common. Tweets that include links to specific antivaccine websites were commonly assigned to this topic, and users posting tweets in Topic 26 appeared to cluster with different densities in three distinct groups that were separated from the groups of users posting tweets labeled as Topic 27.We measured the quality of the topic modeling using the manual intrusion tests. Overall, the correct intruder was identified in 63.7% of the 4650 tests, which is a clear departure from the 16.7% that would be expected by chance. The hierarchy constructed from the manual intrusion tests revealed the semantically similar topics . The topUsing the topics groups, we were then able to characterize the communities by the distribution of topics among the set of tweets posted by the users in those communities. Across the set of all communities, we found that users posting about their own experiences with the HPV vaccine belonged to communities for which the majority of tweets were related to evidence and advocacy. Of the 4548 users who posted tweets labeled as experiential, 3449 (75.84%) belonged to communities for which the majority of tweets were related to evidence/advocacy, 674 (14.8%) belonged to communities for which the majority of tweets were related to harms/conspiracies, 196 (4.3%) belonged to communities for which the majority of tweets were experiential, and 229 (5.0%) belonged to the group of users who were not connected to the core of the network. In this study, we sought to measure the alignment between the community structure implicit among the follower network of Twitter users posting tweets about HPV vaccines and the topics about which they posted. Given what is already known about the variable quality of information about HPV vaccines on Twitter ,23, we eA growing set of methods has been developed using either structural information to improve inferences about the content of a corpus, or the information characterizing the nodes in a network to improve the analysis of the structure. Those aiming to understand the content of tweets have used social connections to improve tweet classification ,63-65. TA limitation of this work is that we considered a single application domain. While the uptake of vaccines is of critical importance to public health, further testing on other application domains would be required to determine the generalizability of assessing topic concentrations as a way of characterizing Twitter communities. A further limitation in our work is that we did not consider the temporal dynamics of the topics or the community structure in any detail. Given that the topics related to HPV vaccines are likely to produce similar temporal patterns to those observed by Leskovec et al , future Our work here has potential implications for public health practices. Applying topic modeling and community detection methods in concert to a corpus of tweets about HPV vaccines, we found that it was possible to characterize online communities by the topics that are most heavily concentrated among their tweets. One way of translating these methods into public health practice would be to use these methods in combination with new spatial and demographic estimation methods -76, to pIn this work, we demonstrated a novel process for characterizing the concentration of certain opinions in online communities by independently applying existing community detection and topic modeling methods, and quantifying the differences in the topic distributions across communities. Among tweets about HPV vaccines, we found that there were clear differences in the distribution of topics across communities defined by the follower network. In practice, public health organizations may wish to consider identifying the locations and demographics of communities that are at risk of exposure to antivaccine information in order to intervene with positive messages targeting the specific concerns identified through topic modeling. The value of this work in public health includes a more nuanced representation of the variety of concerns expressed about HPV vaccines online and some practical steps towards the development of an automated system for the surveillance of public opinions with the purpose of understanding localized differences in decision making and health behaviors.