Our work manifests that the manipulation of metal size-dependent charge transfer between metal and support opens new avenues for developing high-active catalysts.Metal–support interaction is of great significance for catalysis as it can induce charge transfer between metal and support, tame electronic structure of supported metals, impact adsorption energy of reaction intermediates, and eventually change the catalytic performance. Here, we report the metal size-dependent charge transfer reversal, that is, electrons transfer from platinum single atoms to sulfur-doped carbons and the carbon supports conversely donate electrons to Pt when their size is expanded to ~1.5 nm cluster. The electron-enriched Pt nanoclusters are far more active than electron-deficient Pt single atoms for catalyzing hydrogen evolution reaction, exhibiting only 11 mV overpotential at 10 mA cm The charge transfer between metal and support is significant for catalysis, but little attention has been focused on charge transfer tuned by metal size. Here, authors report a metal size-dependent reversal of charge transfer between metal and carbon support in hydrogen evolution electrocatalysts. Classic strong metal–support interaction (SMSI) was proposed and termed first by Tauster et al. in 1978, involving the migration of oxide supports and encapsulation of metal particles during high-temperature reductive treatment, which effectively suppress CO adsorption1. After decades of research, SMSI has been intensively investigated and covered many kinds of interaction mechanisms including oxide encapsulation3, charge transfer7, synergistic reaction in catalytic process10 as well as anti-sintering of nanoparticles11.Supported nanoparticle catalysts play a crucial role in modern chemistry industry. It has been demonstrated in literature that the support, more than a carrier to finely disperse and stabilize metal, would interplay with supported metal and influence catalytic reactivity and selectivity15. The importance of charge transfer and electronic perturbations on reactivity was manifested recently by Rodriguez and coworkers, in which Pt nanoparticles contacting with ceria support showed enhanced ability to dissociate O–H bonds in water and finally achieved the best catalytic activity at the greatest electronic perturbation4. Such an electronic perturbation, arising from charge transfer between metal and support, was termed as electronic metal–support interaction (EMSI) by Campbell5. Many works have demonstrated that the charge transfer was relevant to the properties of supports, such as the reducibility16. Meanwhile, it was also reported that the preparation method17 could influence the d-band centers of supported metals. Although these studies concerning the effects of supports and treatment methods on charge transfer boost our understanding of EMSI, much less attentions have been focused on charge transfer tuned by metal itself, especially the particle size19.Charge transfer, as a typical SMSI that occurs at the interface between metal nanoparticle and support, can introduce electronic modification on metal particles and directly influence their adsorption behavior during catalytic process, which will eventually change their catalytic reactivity and selectivity20. Hydrogen is generally produced by water electrolysis, photocatalytic water splitting, and steam reforming of methane23. Among these technologies, water electrolysis transforms electrical energy to chemical energy directly with the merits of high efficiency, green and pure production, emerging a nice prospect for commercialization. Hydrogen evolution reaction (HER) is a vital reaction in water electrolysis and thus, looking for active, stable, and low cost catalyst to drive the HER and cut the cost for commercialization is significantly important and highly desired. Platinum-group metal (PGM) are the best catalysts for HER, however, the high price and the low abundance restrict their wide usage. The grand challenge is therefore to develop low cost PGM-free electrocatalysts25, or to greatly decrease the Pt loading by enhancing the specific activity of Pt or improving the utilization efficiency of Pt atoms29.As the diminishment of fossil fuel and deterioration of environment, hydrogen has become the focus of research and aroused interests of scientists around the world for its cleaning and reproductionHerein, we report the metal size-dependent charge transfer based on the mesoporous sulfur-doped carbon (S–C) supported Pt single atom and nanocluster catalysts Fig. . By spec2 g−1 were prepared by carbonization of molecular precursors with silica nanoparticles as templates  analyses revealed that the doped sulfur in S–C existed primarily in the form of C–S–C, together with a small amount of S–Ox species  was first performed to reveal the atomic-resolution structure of the Pt/S–C catalysts. For the PtSA/S–C catalyst prepared at 300 °C, we observed numerous atomically dispersed Pt species as well as a few loose ensembles of Pt atoms on the S–C support Fig. . When th Pt Fig. . X-ray dS–C Fig. . Energy-2, indicating the partially oxidized Pt species in these catalysts. The k space of k2-weighted Pt L3-edge in the Supplementary Fig. k2-weighted Fourier transform of extended X-ray adsorption fine structure (EXAFS) of Pt L3-edge of the Pt/S–C catalysts, as well as reference samples were shown in Fig. 32. The peak of PtSA/S–C at 1.8 Å in EXAFS could be ascribed to the Pt–S coordination by comparing with the EXAFS of PtS2 and PtO2. In contrast, PtNC/S–C showed an additional peak at 2.6 Å, close to the Pt–Pt contribution of Pt foil, suggesting the coexistence of Pt–Pt bonds along with the Pt–S bonds in the PtNC/S–C catalyst.We then measured X-ray absorption fine structure (XAFS) and XPS to characterize the coordination environments and the electronic structures of Pt species in the catalysts. The normalized X-ray absorption near edge structure (XANES) present in Supplementary Fig. k2-weighted EXAFS spectra was obtained in Fig. R space and k space. The WT intensity maximum of PtSA/S–C and PtS2 both occurred near R space of 1.7–1.8 Å and k space of 6 Å−1, confirming the similar coordination structure of Pt–S bonds in the first coordination shell. As for PtNC/S–C, besides the Pt–S bond, a new WT intensity maximum near 2.8 Å and 9 Å−1 appeared, which was associated with Pt–Pt bonding. Further quantitative analysis of the coordination structure was conducted by the fitting of R space of Pt/S–C  of the f spectra, rather close to the binding energy of PtS2 (73.1 eV), revealing the same nature of high oxidation state. Such high oxidation state of Pt in PtSA/S–C suggested the electron transfer from Pt atoms to S–C via the interfacial Pt–S bonds as revealed by above XAFS analyses. Compared to PtSA/S–C, the PtNC/S–C catalyst exhibited a negatively shifted binding energy of 71.8 eV. It is rather interesting that the binding energy of PtNC/S–C is similar to that of Pt/C, although the particle size of latter is larger, which may suggest that electron transfer reversely from the S–C support to Pt clusters. To rule out the possible influence of particle size-induced change of the binding energy shift34, we prepared the Pt nanoclusters supported on high-surface-area carbon black BP2000 support (PtNC/BP2000-300) with the similar Pt size as the ones supported on S–C (PtNC/S–C-500) and then compared their Pt 4f binding energy . In particular, about 0.069 electrons are transferred from Pt atom to S-Graphene in Pt1/S-Graphene, and conversely, 0.657 electrons are transferred to Pt38 from S-Graphene in Pt38/S-Graphene  and commercial Pt/C (0.684 A mg−1), respectively. Also, the activity comparison of PtNC/S–C with recently reported noble metal electrocatalysts in terms of the overpotential at 10 mA cm−2 and loading amount clearly indicated that PtNC/S–C exhibited almost the smallest loading and the best HER activity simultaneously , suggesting that both of them share the same rate-determining step, where two hydrogen intermediates desorb and form H2 molecular (Tafel step)28. Differently, PtSA/S–C showed a high Tafel slope of 46.92 mV dec−1, indicating the slow reaction kinetics of the Pt–S single sites. Moreover, PtNC/S–C exhibited remarkable exchange current density as high as 1.732 mA cm−2 . The Nyquist plots show a much smaller charge transfer resistance of PtNC/S–C than that of PtSA/S–C, demonstrating the rapid HER kinetics  with similar particle size but a lower electron density , PtNC/S–C showed a negligible loss of activity with a negative shift only about 4 mV at 60 mA cm−2, indicating the outstanding stability of the PtNC/S–C catalyst  was performed to explore the stability of the catalysts in Nyst Fig. . HAADF Syst Fig. . EDS eleyst Fig. .43. The corresponding hydrogen absorption free energy ΔG was −0.32, −0.28, −0.29, and −0.33 eV, respectively. The comparison of free energies of hydrogen atom on Pt slab, Pt38, and Pt38/S-Graphene are illustrated in Fig. 1/S-Graphene, the calculated free energy of hydrogen was 1.08 eV, implying that the single Pt atom loaded on S-Graphene exhibits low catalytic activity toward HER. Differently, the calculated free energy of hydrogen on Pt38/S-Graphene was as low as −0.07 eV on S5 site of Pt38 cluster, implying the superior catalytic activity of Pt38/S-Graphene over the Pt(111) surface and Pt1/S-Graphene. All the hydrogen absorption configuration of Pt38, Pt1/S-Graphene, and Pt38/S-Graphene were summarized in Supplementary Figs. 38 and was closed to that of Pt(111). However, the free energy dramatically reduced to −0.07 eV if Pt38 was supported on S-doped graphene, suggesting the pivotal role of the S-Graphene substrate in regulating the electronic structures of Pt and the HER performance  of hydrogen atom on surface of Pt slab and cluster were considered, as illustrated in Fig. nce Fig. .Fig. 6Hy1/S-Graphene and Pt38/S-Graphene, the charge analysis results (Δe) were correlated to the change of calculated absorption energies (δG) of hydrogen atom  slab, respectively. The HER catalytic activity of all four absorption sites (S1–S4) were enhanced when Pt(111) were negatively charged and the activity change trend was converse when Pt(111) were positively charged  and a decrease in bonding interaction at some other adsorption sites (δG > 0)  and 1.0 g Co(NO3)2·6H2O  were dissolved in 120 mL tetrahydrofuran  before 2.0 g SiO2 nanoparticles  were added under vigorous stirring to form a homogeneous solution. Then the solution was dried by a rotary evaporator and grinded to yield a mixed powder, which was subjected to pyrolysis at 800 °C (5 °C min−1) under N2 atmosphere for 2 h. Finally, the pyrolyzed product was etched successively in 2.0 M NaOH solution for 3 days at room temperature and in 0.5 M H2SO4 for 8 h at 90 °C to remove SiO2 templates and cobalt, respectively. Inductively coupled plasma-atomic emission spectrometer (ICP-AES) measurement indicated that the left cobalt content in S–C was negligible (<0.1 wt%).Mesoporous S–C supports were fabricated by the cobalt-assisted pyrolysis of molecular precursors with silica nanoparticles as templates2PtCl6 by ultrasonic treatment. Then the H2PtCl6/S–C solution was dried by using a rotary evaporator. Afterwards, the dried powder was subjected to tube furnace and reduced at 300 and 700 °C (5 °C min−1), respectively, under flowing Ar/H2 for 2 h to produce the PtSA/S–C and PtNC/S–C catalysts.The PtSA/S–C and PtNC/S–C catalysts were synthesized by conventional wet-impregnation method. Briefly, 50 mg S–C was well dispersed in 30 mL deionized water containing 7.0 mg H−1 with 2θ range of 10–90°. TEM analyses was conducted by a JEOL-2010F transmission electron microscope with an acceleration voltage of 200 kV. The aberration-corrected HAADF-STEM images were obtained using JEM ARM200F TEM operated at 200 kV. EDS mapping images were carried out on FEI Talos F200X, equipped with Super X-EDS system  at 200 kV. ICP-AES measurement was carried out using Optima 7300 DV. XPS measurements were carried out on a VG ESCALAB MK II X-ray photoelectron spectrometer with an exciting source of Mg Kα = 1253.6 eV.X-ray powder diffraction was performed with Japan Rigaku DMax-γA rotation anode x-ray diffractometer using Cu K-α radiation. The operation voltage and current were 40 kV and 150 mA. The scan speed was set at 1.2° min3-edge were acquired at the 1W1B beamline of the Beijing Synchrotron Radiation Facility operated at 2.5 GeV and 200 mA and at the BL14W1 beam line of Shanghai Synchrotron Radiation Facility (SSRF) operated at 3.5 GeV and 220 mA. The raw data analyses were conducted by using Athena program in IFEFFIT software package. The energy was first calibrated, then the pre-edge background of spectrum was subtracted and post-edge was normalized. k2-weighted EXAFS oscillations ranging from 2.5 to 12.2 Å were Fourier transformed to obtain a radial distribution function. The data fitting was carried out using Artemis program in IFEFFIT44. The passive electron factors, S02, were first determined by fixing Pt–Pt coordination number (CN) of experimental Pt foil data to be 12 and then were fixed to analyze other samples.XAFS data of Pt L2-saturated 0.5 M H2SO4 and potentials in this work are with respect to RHE.Electrochemical measurement was conducted by using Pine Instruments in a three-electrode electrochemical cell. Ag/AgCl was used as the reference electrode and graphite rod instead of Pt wire was chosen as the counter electrode to avoid the dissolution and re-deposition of Pt on the working electrode. A rotating disk glassy-carbon with diameter of 5 mm (Pine Instruments) was used as working electrode. The Ag/AgCl reference electrode was calibrated in HPt cm−2) and dried under ambient temperature. For comparison, the ink of commercial 20 wt% Pt/C (Johnson Matthey) was also prepared and deposited on the working electrode (10.2 μgPt cm−2). Before measurement, the catalysts were cycled, about 50 cycles between −0.25 and +1.0 V (vs. Ag/AgCl) to maximize the activity. Linear sweep voltammetry was taken from −0.15 to +0.05 V (vs. RHE) in N2-saturated 0.5 M H2SO4 at the scan rate of 2 mV s−1. The rotating speed of working electrode was set at 1600 r.p.m. to remove H2 gas bubble during the test. For the ADT, cyclic voltammetry was cycled between −0.15 and +0.15 V (vs. RHE) with the scan rate of 100 mV s−1 for 10,000 cycles. After that, the catalysts were cycled again between −0.25 and +1.0 V (vs. Ag/AgCl) for about 100 cycles before LSV measurement. The Nyquist plot of Pt/S–C and commercial Pt/C were obtained using Zahner work station at a potential of −0.24 V (vs. Ag/AgCl) over a frequency range of 0.1 Hz–100,000 Hz.2.0 mg catalysts was dispersed in 2.0 mL isopropanol containing 40 μL 5 wt% Nafion solution (Sigma-Aldrich) and then stirred for 1 day and sonicated for 2 h to get a homogeneous ink. Afterwards, a certain amount of ink was dropped on the working electrode  measurement was performed by utilizing CHI760 electrochemical workstation (Chenhua) to obtain solution resistance. The frequency range is between 0.01 and 100,000 Hz and initial voltage and amplitude voltage are set at 0 and 0.005 V (vs. Ag/AgCl), respectively.b is the Tafel slope, η is the overpotential, j is the current density, c is the intercept.Tafel slopes were obtained by linear fitting the plot derived from logarithm of current density vs. overpotential. The Tafel slopes were determined from Tafel equation:27:The exchange current density was obtained by formula46. The generalized gradient approximation (GGA) of the Perdew–Burke–Ernzerhof (PBE) functional and the projector augmented-wave (PAW) potential were employed48. An energy cutoff of 500 eV was used for the plane-wave expansion of the electronic wave function. All structures were fully relaxed until the maximum force on atom was <0.05 eV Å−1 and the convergence criterion of self-consistent calculation was 10–5 eV. Van der Waals correction was included by using the DFT-D3 method49. The thickness of vacuum layer was >12 Å.Spin-polarized DFT simulations were performed with the Vienna ab initio simulation package (VASP)n/S-Graphene, where n is the number of Pt atoms). A seven layers 2 × 2 × 1 supercells of Pt(111) slab with the atoms in the bottom three layers fixed at their bulk positions was used. A set of 7 × 7 × 1 k-points was sampled by using Monkhorst–Pack scheme50. Supercells of 6 × 6 and 8 × 8 graphene unitcells were used to model the Pt1/S-Graphene and Pt38/S-Graphene, respectively. A set of 2 × 2 × 1 k-points were sampled by using gamma-centered Monkhorst–Pack scheme to describe the Brillouin zone.To investigate the HER activity, we built models of Pt(111) slab and S-doped graphene supported Pt cluster (PtG) of the adsorption of hydrogen atom was calculated according to Eq.  and free H2 molecule, respectively. T is the temperature, which was chosen as 298.15 K. ΔEH was calculated according to Eq.  – ΔG(Pt38), where ΔG(Pt38/S-Graphene) and ΔG(Pt38) denote the free energy of the absorption of sites Pt38/S-Graphene and Pt38, respectively.The Gibbs free energy  – ρ(substrate) – ρ(Ptn), where ρ(system) denotes the charge density of the whole system, ρ(substrate) denotes the charge density of S-doped carbon substrate removing Ptn without relaxation, and ρ(Ptn) denotes the charge density of Ptn removing substrate and keeping the Pt atoms frozen. The difference in bader charge of each Pt atom is calculated according to Δe = e(Pt38/S-Graphene) − e(Pt38), where e(Pt38/S-Graphene) and e(Pt38) are the charge of each Pt atom in Pt38/S-Graphene and fully relaxed Pt38, respectively.To uncover the effect of S–C on the HER activity of PtSupplementary InformationPeer Review File


C) can not be effecively deceased guided by the Moore’s Law as before. The GFET has the problem of the device can not be effectively turned off, since the band-gap of the graphene is zero. To solve these problems, noticing the amount of the carriers in the 2 dementional semiconductor material is limited, we propose a Matel-Semi-Insulator-Semiconductor Field-Effect-Transistor (MSIS-FET) to replace the traditional MOS-FET. We verify our idea by fabricating the graphene MSIS-FETs using the natural Aluminium-oxide (Al-oxide) as the semi-insulator gate dielectric. From MSIS-FETs fabricated, we obtain following experimental results. The graphene MSIS-FET is turned off very well, a recorded high Ids on/off ratio of 5 × 107 is achieved. A saddle and close-loop shape transfer feature of Ids-Vgs is obtained first time for transistors. A non-volatile memory characteristics is observed. A carrier re-injection principle and a super-Low PC mechanism for semiconductor devices and integrated circuits (ICs) are found from the transfer feature of the graphene MSIS-FET. It is shown that the PC of the semiconductor devices and (ICs) can be reduced by over three orders of magnitude by using this new mechanism.The state-of-art Si Matel-Oxide-Semiconductor Field-Effect-Transistor (MOS-FET) meets the problem of the Power Consumption (P The operating principle of the Graphene-Field-Effect-Transistor (GFET) was similar to that of the Si MOS-FET, the gate dielcetric was still a insulator3. The present information technology based on the MOS-FET faces two problems which looks uncorrelated. The one is the Power Consumption (PC) of the Integrated Circuit (IC) is becoming a big problem, along with the information technology enters the cloud calculation and big date era, resulted from that, with the channel length or feature size of the MOS-FET scaling down, the PC can only be reduced linearly changed from previous squarely9. The second is that since the band-gap of the graphene is zero, the GFET can not be effectively turned off17. We think that the research discoveries from the GFET which is made from a single atomic layer can provide the solution to the first problem, because the substrate thickness of the Si Complementary-Metal-Oxide-Semicondector (CMOS) IC is becoming thin and thin. In decades, the feature size of the CMOS ICs using Si as the semiconducor material keeps being scaled down guided by the Moore’s Law. Nowaday, the 7 nm technology has developped to the industral production6, the 5 nm7 and even 3 nm8 technology are in the research period. In the advanced FINFET, the channels are at the two sizes of the FIN, so the effective thickness of the Si substrate is the half width of the FIN9. When the FIN width goes down to 3 nm8, the effective thickness of the Si substrate is 1.5 nm which is less than the thickness of 3 atomic layers of Si (0.543 × 3 nm)18.Since the silicon (Si) MOS-FET was born, the fuction of the device gate was to induce the carriers (electrons or holes) in the semiconductor channel by applying an electric field to the channel through the gate dielcetric which was an insulator22 and bilayer graphene26. But only limited sucsseses were achieved resulting GFET can not be used in digital logic Very Large Scale Integtation (VLSI) circuits up to now. Nobel prize winner, Dr. Novoselov predicted that the utility of graphene in logic circuits could be realized after 202511. The highist ratio of the Ids on/off was achieved by the GNR20 with the ratio value of 1 × 107. However, the GNR is too small to be applied to the VLSI circuits which need large chip area fabricated by the semiconductor planar process. Perhaps for this reason, people turned to investigate the devices made of 2D MOS2 materials with the band-gap recently31.Many efforts were done to solve the turn-off problem of the GFET, for example, by the way of the Graphene-Nano-Ribben (GNR)gs on which the electrons with negative charges in the channel would move toward the gate through the semi-insulaor gate dielectric.Recongnizing the traditional methods to turn off the GFET had a lot of problems and noticing a fact which may be ignored by people, the number of carriers in the 2D semiconductor is much smaller than that in the 3D semiconductor, we propose a novel device structure named as the MSIS-FET correspoding to tradtional MOS-FET. Namely, the semi-insulaor is used to replace the oxided layer or the insulator in the MOS-FET. We predicted that the graphene MSIS-FET could be turned off by the postive gate voltage Vds on/off ratio of 5 × 107 is achieved which is about 5 times lager than the previous record of 1 × 107 created by the GNR20. A saddle and close-loop shape transfer feature of Ids~Vgs is obtained which is obviously different from that of the semiconductor devices reported. A kind of the non-volatile memory characteristics is observed in the measurement of the graphene MSIS-FET, which gives out an important evidence to our turned-off thorey of the MSIS-FET device.Based on the analysis above, we fabricate the graphene MSIS-FET by using the natural Al-oxide as the gate dielectric. By testing the graphene MSIS-FETs fabricated, we obtain following experimental results. The graphene MSIS-FET with monolayer atom is turned off and on very well, the IC reduction may be, the transfer features of the reported FINFET8 and the Si MSIS-FET inferred from the graphene MSIS-FET are shown.We find a carrier re-injection principle and a super-Low power mechanism from the tested features of the graphene MSIS-FET. In order to show how the super-low power mechanism works and the degree of the P2 or HaO2, a layer of the natural Al-oxide is used as the gate dielectric. Figure gs) increasing during the turning-off procedure of the graphene MSIS-FET.The schematic diagram of the graphene MSIS-FET is shown in Fig. The fabrication process of the graphene MSIS-FET with the top gate is described in details in the Supplementary Information  substrate to the SiOgs = 9 V, the device is turned off very well, Ids(off) = 8 pA, Ids(on) = 0.4 mA, the Ids on/off ratio is 5 × 107 which is about 5 times larger than the best reported ratio created by the GNR20. This experimental result has verifies that the graphene MSIS-FET can be turned off by a postive Vgs.After the fabrication, the graphene MSIS-FETs with the top gate are tested by the semiconductor parameter analysor of Agilent 4155B. Shown in Fig. 2 respectively. Both devices have the back-gate as shown in the schematic diagrams Fig. 2 can not. Both devices have the same graphene material and sizes. The Igs~Vgs features of two devices are shown in Fig. gs~Vgs features of the top-gate graphene MSIS-FET is shown in Fig. 3 MΩ, the resisitance of the 15 nm natural Al-oxide is about 1.8 × 104 MΩ, while the resisitance of the 5 nm natural Al-oxide plus 20 nm HaO2 is infinite. For the reason of the resisitance of the natural Al-oxide is quite large but it is not infinite, the natural Al-oxide is called as a semi-insulator.In order to verify the turn-off characteristics of the graphene MSIS-FET was caused by using the gate dielectric of the natural Al-oxide, the compaision experiments were done by fabricating both graphene transistors with the natural Al-oxide and natural Al-oxide plus HaOgs in about 24 hours. This phenomenon is similar to the performance of the floating gate non-volatile semiconductor memory, when the power supply is off, the state of device is keeping18. This experimental phenomenon provides a strong support to our turn-off principle because it indicates that, at this time, there are almost no electrons remaining in the graphene channel. The related tested results are shown and discussed in Supplementary Information . The Vgs corresponding to the LP point is named VLP. The appearance of the LP point for our graphene MSIS-FET is the result of the balance between the functions of the gate extracting electrons and inducing electrons. When Vgs is higher than the VLP, the function of the gate extracting electrons is stronger than that of inducing electrons, as a result, the Ids gets deceasing, until Vgs reaches the value corresponding to the point C, the graphene MSIS-FET is turned off.For importance and convenience of discussions, LP point is named for the point B in Fig. ds on-state will be.When we obtained the close-loop shape transfer feature of the graphene MSIS-FET shown in Fig. 8. The performance of the Si MSIS-FET shown in Fig. In order to explain more clearly how the super-low power mechanism works, Fig. 16, it can be seen that if the Vds is defined as 0.7 V, the Ids is fixed at 2 × 10−4 A. The black line in Fig. gs rising, the Ids rises like the AB line in Fig. gs reaches the VLP, the Ids reaches its maximum. When the Vgs exceeds VLP, the Ids deceases rapidly, until Vgs reaches 0.7 V, the Ids reaches its minimum, the device is turned off. The blue, purple and green lines indicate that by choosing different negative gate voltages during the turning on procedure, people can get the Ids of the Si MSIS-FET, IdsMSIS-FET, equaling to 1/10 (the blue line), 1/100 (the purple line) or 1/1000 (the green line) of 2 × 10−4 A. As a result, the PC can be reduced by orders of magnitude, since PC = Vds × IdsMSIS-FET. Therefore, the reduction of PC of the Si MSIS-FET is in a leaping or revolutionary way.Shown in Fig. C reduction discussed above can be understood by reviewing the way of the PC reduction for a traditional Si MOS-FET guided by the Moore’s Law. When the feature size is scaled down by a fact of 2, the PC can only be reduced by 2~4 times4.The importance of the amount of P2 and black phosphorus will have the same shape as in Fig. From Fig. Dirac, the operating carriers are holes, after the Vgs equals to the VDirac, the operating carriers are electrons3, however, for the MSIS-FETs with the band-gap, for example, for the Si NMOS, the operating carriers are electrons at all the time. In short, since no Ids mimium point caused by the Dirac point existing in the Si MSIS-FET, the saddle shape will not appear in its transfer feature. It needs to point out that the top edge of the parallelogram may not be horizontal. It may has a positive or negative slope depended on which fuction of the gate extracting and inducing the carriers is stronger. If the extracting one is stronger, the top edge will be down to the left before the LP point. Reversely, if the inducing one is stronger, then the top edge will be up to the left before the LP point. The other 2D material MSIS-FETs beside the graphene MSIS-FET may also be important applications of the MSIS-FET, because they can also realize the super-low power based on the machanism found in this paper.Since the existance of the Dirac point in the graphene MSIS-FET, before the Vgs equals to the Dirac Voltage Vgs. The saddle and close-loop transfer feature of the graphene MSIS-FET is measured first time. The non-volatile memory feature of the graphene MSIS-FET is observed which provides an evidence to our turn-off principle and may be used to form a new type semiconductor memory products.In this paper, we propose and experimentally demonstrate the graphene MSIS-FET. The graphene MSIS-FET is turned off and on very effectively by changing the polar of the VThe contribution of this paper to graphene electronics is that the planar fabrication process of the graphene MSIS-FET may let the graphene material be used much easier in the future. The most important contribution of this paper is the discoveries of the carrier re-injection principle and the super-low power mechanism of the graphene MSIS-FET by which the amount of electrons or holes in the semiconductor channel can be controlled first time by the people. The scientific significace of the MSIS-FET verified by our graphene MSIS-FET is that it makes people changing from passtively accepting the carrier amount in the MOS-FET channel fixed by the operating voltage to actively adjusting the carrier amount in the MSIS-FET channel, as a result, it creates a new way to realize the extremely low power semiconductor devices and ICs.Supplementary Information for A Novel Graphene Metal Semi-Insulator Semiconductor Transistor and Its New Super-Low Power Mechanism


In this paper, we carry out researches on randomized local binary features. Randomized local binary features have been used in many methods like RandomForests, RandomFerns, BRIEF, ORB and AKAZE to matching keypoints. However, in those existing methods, the randomness of feature operators only reflects in sampling position. In this paper, we find the quality of the binary feature space can be greatly improved by increasing the randomness of the basic sampling operator. The key idea of our method is to use a Randomized Intensity Difference operator  as a basic sampling operator to observe image patches. The randomness of RID operators are reflected in five aspects: grids, position, aperture, weights and channels. Comparing with the traditional incompletely randomized binary features , a completely randomized sampling manner can generate higher quality binary feature space. The RID operator can be used on both gray and color images. We embed different kinds of RID operators into RandomFerns and RandomForests classifiers to test their recognition rate on both image and video datasets. The experiment results show the excellent quality of our feature method. We also propose the evaluation criteria for robustness and distinctiveness to observe the effects of randomization on binary feature space. Many computer vision tasks such as vision-based sensors , action In this paper, we propose using more general randomized intensity difference sampling operator  to construct binary feature space for keypoints recognition. Comparing with the traditional randomized intensity tests sampling operators  used in BRIEF , ORB 1313, RandoRandomized local binary features have been widely used in keypoints matching and patches recognition. Their main characteristics are two points: one is randomly sampling within size-fixed image patch, the other is binary encoding of the sampling values. Many methods, including BRIEF , ORB 1313 and AKAfter reviewing the existing randomized local binary feature methods, we find that the common ground of these methods is that they all use nonrandom-weighted aperture-fixed point-pairs single-channel basic sampling operators to construct binary feature space. However, our researches in this paper indicate that those incompletely randomized sampling operators are not conducive to the separability and diversity of binary feature space and can can not give full play to the performance of the local binary feature method.In this subsection, we discuss the design of basic sampling operators. The traditional basic sampling operators used in ,18,19 arThe RIT operator is also used in the sampling patterns such as RSLBP , ORB 1313, FREAKn is the number of sampling cells within one RID operator. Each sampling cell Differently, we use completely randomized RID (Randomized Intensity Difference) sampling operators to construct binary feature space. RID operator is random-weighted random-distributed multi-granular multi-channel sampling operator, which can be defined as follows:n) to represent the number of cells within a RID operator. For example, RID(4) means n = 4. As discussed in M-dimensional feature space, we need pre-generate numbers of RID operators and arrange them into M groups. Within each group, the number of sampling cells among different RID operators can be different from each other. RID means there are two kinds of RID operator in each group: RID(2) and RID(4). RID means there are three kinds of RID operator in each group: RID(2), RID(4) and RID(6). The aperture size of RID operators within each group is also randomly pre-selected in a specified range. Because keypoint neighborhood is usually a 31 × 31 image patch, the aperture range of RID operator cannot be larger than 31 × 31. In our paper, RID(2) means the aperture size of RID(2) operator is randomly selected in the range . RID(4) means the aperture size of RID(4) operator is randomly selected in the range . The weights of sampling cells within each RID operator are also randomly generated according to the condition in Equation (Equations  and 3)  3) definEquation  and haveEquation , which aIn this subsection, we discuss how to construct binary feature space using numbers of basic sampling operators.M-dimensional feature vector extracted from an image patch as: We denote T is a threshold that always equals the theoretical average value of sampling operators in The mapping F is controlled by the number of basic sampling operators in each group: V is S bits according to Equation  in those experiments.Therefore, the value size of feature space Equation  and we hT can be set to zero. If we put the RIT operator of Equation , , , ⋯. Under each aperture constraint, we test the recognition rate of RandomFerns classifier embedded with different RID operators. Finally, we plot the curves of recognition rate with respect to operator aperture range. The experiment results on both gray images and color images are illustrated in In this subsection, we keep M and S are fixed, the larger the operator aperture is, the more sampling redundancy exits in feature space. When the operator aperture become too small or too large, the recognition rate curves of random ferns classifier become falling down in both gray images and color images. The reason behind this phenomenon is that large aperture sampling operators can resist noises but omit the details. On the contrary, small aperture sampling operators can capture details, but cannot resist noises. Therefore, sampling operator aperture should be selected randomly in a specified proper range. The best aperture range of the six kinds of RID sampling operators are different from each other, which can be due to the number of sampling cells is different in their sampling templates. According to the experiment results in We can find from the experiment results in In this subsection, we make experiments to show the benefits of weights randomization to binary feature space. For comparison, we generate RID operators in two cases: in the first case the weights of sampling cells within every RID operator are non-randomized and kept fixed; in the second case the weights of sampling cells are randomly selected. In both cases the weights are set to meet the condition defined by Equation . Both raIn this subsection, we use different kinds of RID sampling operators to build binary feature space and combine the feature space with RandomFerns and RandomTrees classifiers  to test M = 40 and S = 8 within each method to keep the dimensions of feature space always same in the experiments. The experiments are made on both gray images and color images selected from VOC2011 dataset. The recognition rate of each tested method is computed in two cases: one test case is keeping the number of keypoints detected from each reference image fixed to be 300 while continuously increasing the number of training samples per keypoint, and the corresponding experiment results are illustrated in For the sake of fair, we set The experimental results illustrated in Now we discuss the computational burden of our method. To generate the sampling pattern, we only need to know the patch size of keypoint neighborhood, the aperture size range of sampling operator and the channels count of the image. This can be seen in algorithmic description in In this subsection, we compare the computational efficiency between our CBE-RID features and traditional MBE-RIT features. In the comparison experiment, we first randomly generate 100,000 image patches from some given images, just as The results in In this subsection, we compare the matching precision performance between our CBE-RID feature method and the existing state-of-art feature methods under different test situations including rotation, zooming, viewpoint changing, blurring, noises and light changing. The existing methods selected to be compared are as follows: ORB, BRIEF, SIFT, SURF, KAZE, AKAZE, CSLBP, RILBP, RandomFerns and RandomTrees. Some of these methods have its own keypoint detector while some are only provide descriptor extractor. If a method has detector, we will use it; if not, we use the detector same as the author used in his original paper. The implementation of the methods we selected to compare are from OpenCV library. Our CBE-RID feature method is also a descriptor extractor method and the ORB detector is used in our programs. Therefore, our method is denoted as ORB-CBERID(6), which use one kind of RID variants: RID(6) operator.The experimental results are illustrated in M = 40 and S = 8. In this subsection, we evaluate CBE-RID features in the real-world application of frame-to-frame matching on video dataset illustrated in The experiment results are illustrated in In this section, we first give the evaluation criteria for robustness and distinctiveness of local features, then make experiments using our evaluation criteria to obtain an insightful observation and explanation for our completely randomized local binary feature method. In this section, we try to answer three questions: the first question is how to measure robustness and distinctiveness; the second question is that how the aperture size of basic sampling operators influences robustness and distinctiveness; The third question is that how the weights randomization of basic sampling operators influences robustness and distinctiveness.f is a local feature method, P is an image patch, and v is descriptor vector of image patch P. Considering deformations occurring on image patch P as some kinds of disturbance, we have a mapping like this: Local feature method can be considered as a mapping from image space to a special feature space, expressed as: f has the ability of keeping invariant to some kinds of disturbance, which can be expressed as follows:P and the descriptor from distorted patch d is normalized descriptor distance from 0 to 1. We use 100 bins in the density histogram and ith bin. The robustness of a feature method requires that feature mapping f can make descriptor vectors from different keypoints separable as much as possible in their feature space. Let P and Q be image patches of two different keypoints, distinctiveness can be expressed as follows:P and Q, respectively. The greater the lower bound The distinctiveness of a feature method requires that the feature mapping Similar to Equation , distincIn this subsection, we discuss the effects of operator aperture on robustness and distinctiveness. To remove the influence of weights randomization and only consider the effect of the operator aperture, we use the nonrandom-weighted sampling operator to carry out the experiment. The quations  and 14)robustnesWe can see from the experimental results illustrated in In this subsection, we discuss the effects of weights randomization on robustness and distinctiveness. We use the random-weighted sampling operator to carry out the experiment to compare with the results in quations  and 14)robustnesWe can see from the experimental results illustrated in In this paper, we carry out researches on randomized local binary features under the background of keypoints recognition and image patches classification. We make experiments to analyze several key parameters that have significant impacts on the quality of the binary feature space. The parameters related to basic sampling operator mainly include position, aperture, weights, channel, pattern and count, which can control the sampling redundancy and multi-resolution observation of local image areas. Through our experiments, we find that the binary feature space constructed by completely randomized basic sampling operator has very good quality compared with the traditional incomplete randomized basic sampling operator. Further, the improvement of the quality of the binary feature space by the complete randomization of the sampling operator is consistent regardless of what classifier you use. It is worth mentioning that this complete randomization does not bring more computational burden and can be easily implemented without need of elaborate manual design.


L1 retrotransposons have co-evolved with their mammalian hosts for the entire history of mammals and currently compose ~ 20% of a mammalian genome. B1 retrotransposons are dependent on L1 for retrotransposition and span the evolutionary history of rodents since their radiation. L1s were found to have lost their activity in a group of South American rodents, the Sigmodontinae, and B1 inactivation preceded the extinction of L1 in the same group. Consequently, a basal group of sigmodontines have active L1s but inactive B1s and a derived clade have both inactive L1s and B1s. It has been suggested that B1s became extinct during a long period of L1 quiescence and that L1s subsequently reemerged in the basal group.Here we investigate the evolutionary histories of L1 and B1 in the sigmodontine rodents and show that L1 activity continued until after the L1-extinct clade and the basal group diverged. After the split, L1 had a small burst of activity in the former group, followed by extinction. In the basal group, activity was initially low but was followed by a dramatic increase in L1 activity. We found the last wave of B1 retrotransposition was large and probably preceded the split between the two rodent clades.Given that L1s had been steadily retrotransposing during the time corresponding to B1 extinction and that the burst of B1 activity preceding B1 extinction was large, we conclude that B1 extinction was not a result of L1 quiescence. Rather, the burst of B1 activity may have contributed to L1 extinction both by competition with L1 and by putting strong selective pressure on the host to control retrotransposition.The online version of this article (10.1186/s13100-019-0164-5) contains supplementary material, which is available to authorized users. They move through an RNA intermediate, but have non-homologous ends and use target-primed reverse transcription . L1  are relatively short, non-autonomous, non-LTR retrotransposons. SINEs do not encode proteins for their own retrotransposition and depend on the reverse transcriptase encoded by other transposable elements such as LINEs , 16. Alterential , 10, SINerential –17, and erential , 4. Amonerential , B1 is terential . B1s areerential , 21 and erential , 23. B1 erential , and theerential , 26.Both L1 and B1 have long histories of co-evolution with their host genomes. Unlike some LTR retrotransposons , 28, theLINEs and SINEs have considerable impact on the mammalian genome, although they were traditionally viewed as “junk DNA”. As LINEs and SINEs, including L1s and B1s, retrotranspose and recombine, they introduce genome instability  and causSince L1 retrotransposition is under strict control by multiple host defenses , it mighSigmodon carries inactive B1 and active L1, and the descendant genera carry both inactive L1 and B1 , four families shared by O. palustris and S. hispidus (L1-OS1 to L1-OS4) and two shared by P. maniculatus, O. palustris and S. hispidus . The other four B1 families (B1-OSP1–4) are shared by O. palustris, S. hispidus and P. maniculatus. The representation of these families in both O. palustris and S. hispidus genomes is fairly synchronized in time and comparable in copy number , and S. hispidus DNA was obtained from Texas Cooperative Wildlife Collection of the Texas A&M University (tissue ID: MUR15). Whole genome sequencing of each species was done in separate batches using MiSeq  at the IBEST Genomic Resources Core . Paired-end libraries were generated with an insert size of 450–550 bp; ~ 13 and 14 million total reads were generated for O. palustris and S. hispidus, respectively. Sequences were processed with SeqyClean (https://bitbucket.org/izhbannikov/seqyclean) and the paired-ends were joined with FLASH [O. palustris and 6.06 Gbp for S. hispidus, but we note that genome size within the sigmodontine rodents varies. Although the genome size of O. palustris is not documented to our knowledge, the genome size of sister species in Oryzomys suggest that Sigmodon genomes are 11–16% larger than those of Oryzomys [th FLASH . Genome Oryzomys .O. palustris and 214 Mbp for S. hispidus. P. maniculatus genome trace files were obtained from NCBI FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/TraceDB/peromyscus_maniculatus/). Reconstruction of the 3′ ends of O. palustris and S. hispidus L1s started with a 575 bp consensus seed in the 3′ half of L1 ORF2 generated following Cantrell et al. [O. palustris to capture the most recently active sequences; a higher percent identity (97–99%) and overhang length of at least 100 bp were used for S. hispidus. This assured a satisfactory consensus and exclusion of older L1 elements for each species. The 3′ 300 bp of the reconstructed L1s were then used as the reference sequences for COSEG analysis described below.L1 reconstructions for both species were generated based on partial genomic sequences generated by 454 Pyrosequencing  at the IBEST Genomic Resources Core, 203 Mbp of sequence for l et al. . A bioinl et al. . Brieflyl et al. , 73. TheO. palustris and S. hispidus were aligned with Lasergene MegAlign  and the consensus sequence (146 bp) was used as the reference sequence for COSEG analysis.B1 sequences from Rinehart et al.  were useO. palustris and S. hispidus were identified and characterized in similar fashion as described below and are summarized in Additional file L1 and B1 subfamilies in O. palustris and S. hispidus L1 ORF2 were each used as the initial L1 query sequences, and the full length B1 consensuses from each species, based on Rinehart et al. [O. palustris and S. hispidus MiSeq genomic DNA libraries (processed reads without assembly) were queried using RepeatMasker [http://www.repeatmasker.org/COSEGDownload.html) run to identify subfamilies based on shared, co-segregating sequence variants. All COSEG runs were conducted under default parameters except as noted. Parameters were set such that at least 250 sequences were required to form a L1 subfamily and 1000 were required to form a B1 subfamily. In order to identify older subfamilies, the consensus sequences of the subfamilies identified by the first COSEG run were used as queries to again search the O. palustris and S. hispidus MiSeq libraries using RepeatMasker. The identified sequences from the second RepeatMasker run were filtered for > 90% coverage and extracted. O. palustris and S. hispidus sequences are combined and a second COSEG run was carried out on the combined sequences. To avoid the possible formation of random subfamilies due to the short length of B1 and the high copy number of the detected sequences, the sequences required to form a subfamily was increased from 1000 (for the former separate run) to 2000, whereas this number for L1 remained unchanged at 250. The consensus sequences of the resulting COSEG subfamilies were trimmed to exclude ends that were not common to all subfamilies and the CpG sites were removed and, thus, treated as gaps by RepeatMasker and not counted for the divergence calculation. These modified subfamily consensus sequences were used for a final query of the individual O. palustris and S. hispidus MiSeq libraries using RepeatMasker. Sequences from this third run were assigned to subfamilies based on percent divergence and this information was stored for further analysis.The reconstructed 300 bp sequences from the 3′ end of t et al. , were usatMasker  with defatMasker   using the consensus sequences of subfamilies belonging to each family. Alignment and phylogeny of families were generated as described above for subfamilies. Histograms of L1 and B1 divergence distributions were generated by R [Subfamily consensus sequences generated by the second COSEG run of the ng PhyML  with theted by R  histograS. hispidus using RepeatScout [S. hispidus to find repetitive sequences. Identified repeats were then annotated using RepeatMasker. All L1-like sequences that overlaps with the 3′ 300 bp of S. hispidus L1 ORF2 were used as seeds to perform a COSEG analysis of L1s in S. hispidus following the approach described above. All RepeatScout-based L1 subfamilies Additional file 3:Table S1. Statistics and designation of L1 subfamilies and families. “Ory” stands for O. palustris and “Sig” stands for S. hispidus. “Peak” indicates the peak of the L1 divergence distribution of the subfamily or family identified by kernel smoothing. Copy numbers are normalized as copies per three Gbp of MiSeq sequence used for the search, which approximates the copy number per haploid genome. Designation of families is only shown after the first subfamily that belongs to it; all subsequent subfamilies belong to this family until the demarcation of the next family. Characters in family names: “S” represents S. hispidus-specific, “OS” for shared by O. palustris and S. hispidus and “OSP” for shared by O. palustris, S. hispidus and P. maniculatus. Numbers in the family names reflect their divergence among the family group with “1” being the youngest. Copy numbers of families are rounded sums of subfamily copy numbers per three Gbp of sequences and, thus, are occasionally off by one. (XLSX 14 kb)Additional file 4:Table S2. Statistics and designation of B1 subfamilies and families. “Ory” stands for O. palustris and “Sig” stands for S. hispidus. “Peak” indicates the peak of the B1 divergence distribution of the subfamily or family identified by kernel smoothing. Copy numbers are normalized as copies per three Gbp of MiSeq sequence used for the search. Designation of families is only shown after the first subfamily that belongs to it; all subsequent subfamilies belong to this family until the demarcation of the next family. Characters in family names: “OS” represents families shared by O. palustris and S. hispidus and “OSP” for families shared by O. palustris, S. hispidus and P. maniculatus. Numbers in the family names reflect their divergence within the family group with “1” being the youngest. Copy numbers of families are rounded sums of subfamily copy numbers per three Gbp of sequences.and S. hispidus genome. CpG sites with evidence of methylation-induced mutations were removed from the alignment. (XLSX 13 kb)Additional file 5:Alignment of L1 subfamily sequences used in the tables and figures. CpG sites with evidence of methylation-induced mutations were removed from the alignment. (FA 15 kb)Additional file 6:Alignment of B1 subfamily sequences used in the tables and figures. CpG sites with evidence of methylation-induced mutations were removed from the alignment. (FA 7 kb)Additional file 7:S. hispidus genome. CpG sites with evidence of methylation-induced mutations were removed from the alignment. (FA 21 kb)Alignment of L1 subfamily sequences based on RepeatScout-generated seeds and


Pseudomonas aeruginosa for the first time. Efficient and facile one step hydrothermal process adopted in the present work for the synthesis of graphene-tin oxide nanoparticles provides an ideal method for the economic large-scale production of the same. Graphene-tin oxide nanocomposites derived from wood charcoal possess a spherical morphology whereas rod like structures are seen in the case of coconut shell derivatives. An excitation independent fluorescence response is observed in graphene-tin oxide nanohybrids while graphene oxide nanostructures exhibited an excitation dependent behavior. These hydrophilic nanostructures are highly stable and exhibited no sign of luminescence quenching or particle aggregation even after a storage of 30 months. Bactericidal effects of the nanostructures obtained from coconut shell is found to be relatively higher compared to those procured from wood. This variation in antibacterial performance of the samples is directly related to their morphological difference which in turn is heavily influenced by the precursor material used. MIC assay revealed that coconut shell derived graphene-tin oxide composite is able to inhibit the bacterial growth at a lower concentration (250 μg/mL) than the other nanostructures. Nanocomposites synthesized from agro-waste displayed significantly higher antimicrobial activity compared to the precursor and graphene oxide nanostructures thereby making them excellent candidates for various bactericidal applications such as disinfectants, sanitary agents etc.Antibacterial screening of graphene-tin oxide nanocomposites synthesized from carbonized wood and coconut shell is investigated against  One of the biggest challenges in the modern era medicine and sanitation industry is the containment of the evolution and adaptation of various bacterial strains. The consistent improvement in the bacterial resistance towards drugs and other antibiotics has compelled the researchers to look for new antibacterial agents with improved screening7. It is established from the earlier researches that, graphene via its sharp edges can rupture the bacterial cell membranes, thereby making it a promising candidate for bactericidal applications12. Graphenic structures embedded with inorganic nanoparticles are also well known for their antibacterial performance and low cytotoxicity towards the mammalian cells13.Recently, quest for the bulk production of graphene based biocompatible materials has gained momentum owing to their wide range of applications as biosensors, purification membranes, sanitary agents etc16. Even though AgNPs are capable of antimicrobial screening, the studies on the adverse effects of nano-silver particles and Ag+ ions on human cells as well as on the environment poses a serious health concern18. Hence, development of alternative materials with comparable antibacterial performance is the need of the hour. Recently, metal oxides are highly sought after for composite preparations in the field of biomedicine primarily due to their high chemical reactivity making them extremely suitable for nanoparticle formation19. Studies have confirmed that metal oxide nanoparticles considerably decrease the attachment and viability of bacterial agents thereby making them befitting for many antibacterial applications22. Liu et al. reported an increased antimicrobial activity of graphene quantum dot/ZnO nanocomposite under UV photo irradiation due to the enhanced generation of reactive oxygen species (ROS)21.There are many reported studies on various synthesis methods of graphene-silver nanoparticles (AgNPs) and their antimicrobial activity2) is one of the notable metal oxides which possess excellent electrochemical, optical and electronic properties. Recently, Amininezhad et al. reported the inactivation efficiency of tin oxide (SnO2) nanoparticles for gram-negative Escherichia coli and gram-positive Staphylococcus aureus under UV and dark conditions23. Wu et al. investigated the antibacterial activity of graphene-stannous dioxide nanoparticles against Staphylococcus aureus and Pseudomonas aeruginosa (P. aeruginosa) using optical density and plate counting methods12. It was concluded that the presence of SnO2 particles on the graphene framework enhanced the cytotoxicity of the latter because of synergic effect12.Tin oxide  play an important role in regulating the morphology of metal oxide nanoparticles such as SnO2 during the formation of nanocomposite32. Production of graphene nanostructures from materials like graphite and its oxides involves procedures which are either expensive or use hazardous chemicals like hydrazine monohydrate33. Also, the scissoring of large graphene domains into smaller ones is tedious and time consuming34. Barbolina et al. has suggested that the antibacterial mechanism and bacterial viability of graphene oxide heavily depends on the precursor as well as on the methods employed in the production of the same before the antibacterial screening36. Hence, search for an effective precursor that can be developed into a strong antibacterial agent is necessary. In this regard, graphene and metal oxide nanoparticles showcasing relatively high antibacterial properties are worth investigating. However, the quest for a facile and viable means of production of these graphene nanohybrids with metal oxides is often hindered either by herculean protocols or expensive ways of manufacturing. An economically scalable, large-scale route of production of graphene-metal oxide nanohybrids is quite essential to facilitate their usage in variant applications37.Most often, the precursor material used in the studies reported earlier are either graphene/graphite powder or other relatively expensive materials which are commercially available39. Yadav et al. has recently reported the high antibacterial potential of iron nanoparticles synthesized from Aloe vera against various pathogenic bacteria42. In the current study, we present the synthesis of graphene oxide from the burnt remnants of wood and coconut shell thereby recycling these otherwise waste materials which are rich in activated carbon. A facile and scalable synthesis of graphene oxide nanolayers and nanodots from agro waste materials via a modified Hummers’ method is reported. A simple one step hydrothermal route is adopted for the synthesis of graphene-tin oxide (GTO) nanocomposite. Antibacterial property of the GTO nanocomposites is investigated against P. aeruginosa, one of the highly resilient bacterial strain known to mankind.Use of renewable resources for the synthesis of nanostructures has been gaining limelight in recent yearsGO obtained by a simple, scalable oxidative treatment of wood charcoal (WC) and coconut shell charcoal (CSC) is code named as WC-HS (WC-Hummers’ treated) and CSC-HS (CSC-Hummers’ treated) respectively. The GTO nanocomposites derived from WC-HS and CSC-HS is further coded as WCT and CSCT respectively. The effective inherent reduction of GO to graphene is facilitated by the use of the one-step hydrothermal treatment with tin . Unlike the conventional methods used, absence of hazardous chemical reagents and toxic industrial waste or byproducts during the nanoparticle formation is an added advantage. In addition to this, the adopted method has also achieved the otherwise time-consuming scissoring of large particles into smaller domains.45. With the hydrothermal treatment, XRD profiles are modified with the appearance of the distinctive peaks of SnO2 suggesting the successful incorporation of tin oxide nanoparticles in the graphene network. In GTO composites, the (002) peak corresponding to graphene domain is seen to be overlapping with the diffraction peak of SnO2 from (110) plane. Inherent reduction of graphene oxide during the hydrothermal treatment is apparent from the decreased width along with a slight shift in position of the (002) peak in the composite spectra46. In addition to the graphitic peaks, GTO spectra also features peaks at ~26°, ~33°, ~38°, ~51° and ~64° corresponding to (110), (101), (200), (211) and (112) planes of SnO2 respectively47. From XRD analysis, it is observed that the nanocomposite derived from coconut shell charcoal has distinctively well-defined characteristics in comparison with that obtained from wood charcoal. The presence of oxygen functionalities is also confirmed by Fourier Transform Infrared (FTIR) spectral analysis , C=O (~1590 cm−1) and C-OH (~1200 cm−1) in the oxidized samples. GTO nanocomposites showed the existence of O-H (~3400 cm−1), C=C (~1610 cm−1), C-H (~1187 cm−1), C=O (~1030 cm−1) and Sn-O (~600 cm−1) stretching vibrations substantiating the successful incorporation of SnO2 nanoparticles in the graphene matrix32.X-ray diffractograms of GO and GTO nanocomposites derived from wood charcoal and coconut shell charcoal are given in Fig. −1) and graphitic (G) band (at ~1585 cm−1) in the synthesized material49. Raman analysis of the precursors is given in Supplementary Information Fig. D) to graphitic (IG) band intensity ratio is found to be 0.68, 0.92 and 0.93 for WC, WC-HS and WCT respectively indicating the formation of defects or functional groups in the graphene layers. This ratio is calculated to be 0.69, 0.88 and 0.89 for CSC, CSC-HS and CSCT respectively. The higher value of ID/IG ratio conventionally indicates the effectiveness of the oxidation process which rises the number of defects49. The increased intensity of D band is also attributed to the edge effects present in the graphene network of the sample. From Raman analysis, it is evident that the incorporation of SnO2 nanoparticles has not caused much change in the graphene skeletal network51. It can be concluded that the derived nanomaterials mainly consist of sp2 carbon with some sp3 carbon structures embedded with oxygen functional groups on their surface.Raman spectra of nanocarbon derivatives obtained from carbonized botanical waste materials are presented in Figs 52. Hence, after a relative increase seen in the number of defects via oxidative and hydrothermal treatments, one could expect the rise of antibacterial performance of the respective samples.The defects present in the sample are speculated to increase the ROS formation thereby contributing to an increased antibacterial activity of the sample. Moreover, the presence of edges and other induced defects enhances the available surface area for molecular attachments resulting in an elevated toxicity which aids the bacteriostatic and bactericidal performance of the nanostructures2 nanoparticles. The even distribution of oxygen functional groups on the graphene sheets facilitates the uniform dispersion of SnO2 nanoparticles on the graphene backbone. HRTEM images of WCT show tin oxide nanoparticles with size <3 nm evenly distributed throughout the graphene surface  analysis of WC-HS and WCT are shown in Figs HRTEM images of the chemically oxidized coconut shell charcoal (CSC-HS) is depicted in Fig. 2 nanoparticles on the carbon dots framework has resulted in their effective separation. Tin oxide nanoparticles appear to be stacked in the nanocarbon matrix. The lattice fringe width is found to be 0.33 nm which corresponds to (110) plane of SnO2. Particle size measured from the HRTEM image evidently falls into two categories: carbon dots with size ranging from 5–11 nm and Sn nanorods of length 20–34 nm. Nanorods are particularly believed to be a better shape among the others in combating the infectious bacteria due to their exposed planes and increased reactivity53. Smaller the size of the nanoparticles, higher the surface to volume ratio, which in turn increase the availability of ROS in the sample. ROS plays a pivotal role in enhancing the antibacterial activity by causing membrane damage to the bacterial cells54. SAED pattern clearly shows the high crystallinity of the sample with twinning planes belonging to carbon and tin.HRTEM images of graphene-tin oxide nanocomposite obtained from CSC-HS is depicted in Fig. 55. When WC displayed sheet like carbon domains, CSC possessed relatively smaller polygonal structures. The larger size of the carbon domains present in WC was retained by WC-HS during the oxidative treatments whereas in the case of coconut shell, oxygen group embodiment has resulted in the separation and scissoring of larger particles in to smaller dots. The size and shape of the tin oxide nanostructures adhering to the graphene surface is greatly controlled by the physicochemical traits of GO used in the nanocomposite synthesis32. As a result, post-hydrothermal treatment, spherical SnO2 nanoparticles are observed in WCT whereas rod-shaped structures are formed in CSCT. Thus, from the structural and morphological analysis, it is suggested that the nanoparticle formation and properties are heavily influenced by the precursor characteristics.Comparing WC and CSC derived nanostructures, a difference in morphology is very evident. Considering the fact that the protocol used for the synthesis of both nanocomposites are the same, this variation in morphology of the two can be ascribed to the structural difference in the precursor materials used. The degree of oxidation of nano-systems is known to be greatly influenced by the morphology of the precursor materials2 nanoparticles, a transition of PL characteristics from an excitation dependent to an excitation independent form could be observed. As the excitation changes, the emission intensity was found to be ascending to a maximum at 320 nm and starts decreasing with further increase in the excitation wavelength. The bell curve pattern is still evident in the emission intensities. Absence of the broad satellite peak corresponding to the oxygen functionalities is also noted which supports our claim of a high degree of reduction during the hydrothermal treatment56. A fine tuning of the emission peaks from the carbon core is observed with the incorporation of tin nanoparticles. Both quantum size effect and surface effect could be responsible for this excitation independent behavior showcased by GTO nanocomposite58.Photoluminescence (PL) spectrum of the samples are recorded and compared as a function of excitation wavelength. PL spectrum of GO obtained from WC and CSC is presented in Fig. Nanostructured CSC-HS excited from 280 to 400 nm exhibits a fluorescent dependent behavior with the emission maxima of the carbon core centered at ~310 nm. A broad emission from the functional groups could also be seen at a higher wavelength range. With the incorporation of tin nanoparticles, the fluorescence properties changed altogether. From the PL spectrum of CSCT, it is evident that the change in excitation wavelength has no particular influence on the emission characteristics. The removal of oxygen functional groups could also be noted from the absence of the peaks at higher wavelengths. Both GO and GTO nanostructures obtained from WC and CSC showcases similar pattern of emission intensities with change in excitation wavelengths. So, from the PL analysis of the samples, it is deduced that the nanostructures derived from WC and CSC via Hummers’ treatment show an excitation dependent behavior while with the incorporation of tin nanoparticles, PL response becomes independent of the excitation wavelength. Also, the coconut shell derived GTO nanocomposite manifest a better refined excitation independent PL behavior in comparison with those obtained from wood. The synthesized water-soluble nanostructures are found to be highly stable and showed no sign of aggregation even after a storage period of 30 months. They also retained their fluorescence property without any quenching after such extended period of storage.P. aeruginosa on nutrient agar plates and the zone of inhibition is measured after incubating for 24 hours. The repeatability of the antibacterial screening of all the samples are also tested for three times. Gram-negative bacterial strain additionally possesses an outer layer of lipopolysaccharides and phospholipids as compared to the gram-positive bacteria and this outermost membrane often acts as a coverage wall for the bacteria thereby rendering it protection from the attack of foreign bodies59. At the end of incubation period of the disc diffusion assay with the synthesized nanomaterials, a clearance zone is seen to be developed around the well indicating the antimicrobial activity of the sample. Absolute alcohol is used as the negative control and antibiotic cephalexin is used as the positive control for the study. Figure The bactericidal test of the synthesized samples (conc. 1 mg/mL) is performed against gram-negative bacteria 60. Sharp edges of the graphene nanosheets also aids in the rupturing of the bacterial cell wall making it forego the cell integrity. A considerable increase in the antimicrobial effects with a relative decrease in size of the particles is also reported61. Hence, the smaller size of nanoparticles formed post-hydrothermal treatment plays a significant role in the enhancement of antibacterial activity of the obtained nanocomposites.The antibacterial screening is observed to be more in the case of GTO nanohybrids comparing to its virgin and GO counterparts. This can be ascribed to the inclusion of tin oxide nanoparticles together with an increase in number of defects in GTO composites causing an increased surface to volume ratio and more oxidative stress in the bacterial cell walls. The oxidative stress induced in the bacterial membrane helps in incapacitating the inherent anti-oxidant defense mechanism of the bacterial cells61. A slight decrease in the observed antibacterial activity of WC-HS points to the earlier reports that the purity of GO depends on the precursor material used and consequently has a direct relation to its antimicrobial effects. The comparatively less surface area of larger GO domains in WC-HS decreases the interaction sites of the nano-system with bacterial surface leading to a diminished antibacterial activity. In comparison with the nanostructures obtained from wood charcoal, those derived from coconut shell manifests a higher antibacterial activity towards P. aeruginosa. CSCT showcases 40.7% higher bactericidal capability when compared to WCT. This is a direct consequence of the morphological difference between the two. Nanostructures synthesized from coconut shell charcoal is found to be smaller in size and possess a superior rod like morphology which contributes in enhancing its microbial activity. The increased surface to volume ratio of CSCT nanoparticles significantly increases the surface area available for interaction with the bacterial membrane leading to a higher bactericidal efficacy. Also, larger particles tend to get adsorbed on the bacterial surface whereas the smaller ones get absorbed in to the bacterial cell resulting in internal damage and alterations in the cell activity62. Hence, CSC nanostructures possessing smaller carbon domains are more effective in eradicating the bacterial strains. The increase in number of defects in the graphene backbone, release of toxic ions in to the bacterial cell and the diminution of surface negative charge after nanocomposite formation might have also benefited the cause13. GTO nanohybrid appears to combine the antibacterial properties of both GO and SnO2 particles, effectively enhancing the antibacterial effect of both the base materials11.Zone of inhibition measured in this study is by far one of the highest reported. Graphene by itself can help in enhancing the antibacterial performance of the nanocarbon by adsorbing to the bacteriaP. aeruginosa is determined by microdilution plate method with resazurin63  implying the efficacy of the coconut shell derived GTO nanocomposite.Minimum inhibitory concentration (MIC) of the synthesized nanostructures against From the disc diffusion assay and MIC analysis of WC and CSC derivatives, it is evident that GTO nanocomposites have better antibacterial efficacy in comparison with the respective precursor and GO counterparts. Zone of inhibition measured in the case of GTO nanocomposite from CSC is comparable to that of the standard antibiotics used. This is in turn corroborated by the low MIC value of CSCT in MIC assay. Thus, GTO nanocomposite derived from coconut shell seems to be promising for various antimicrobial applications.Pseudomonas aeruginosa are 27 ± 1 mm and 38 ± 0.7 mm respectively. This measured antibacterial activity is one of the highest reported of its kind. MIC assay has revealed that CSCT nanocomposite could impede the bacterial growth at lower concentrations than the other synthesized nanostructures. The rod-shaped morphology and well-defined structural characteristics of GTO nanocomposite derived from coconut shell has made them more efficient antimicrobial agents in comparison with WC nanostructures. The effective increase in number of defects as a consequence of the chemical treatments employed has contributed strongly towards the enhancement of antibacterial performance of the nanocomposites. The upgradation of fluorescence behavior to an excitation independent response after the hydrothermal treatment makes GTO nanocomposite a potential benign candidate for biomedical applications. The nanomaterials synthesized are highly stable and showed no sign of aggregation or photo quenching even after extended storage periods. It can be concluded that, CSC derived GTO nanocomposite holds great promise as an antimicrobial agent in various applications like food packaging, sanitary agent manufacturing, sewage treatments, etc. and needs to be investigated further.In summary, an efficient and easily scalable strategy for the economic large-scale synthesis of water-soluble graphene oxide and graphene-tin oxide nanocomposites from agricultural green carbon wastage is demonstrated. A uniform distribution of tin oxide nanoparticles in the graphene matrix is observed. Morphological difference between WCT and CSCT nanocomposites produced using identical chemical protocol indicates that the initial precursor material used for the graphene oxide synthesis plays a pivotal role in the nanocomposite formation. All the synthesized nanostructures exhibited high antibacterial activity and among them, GTO nanocomposites showcased a marked raise in antibacterial screening. Zone of inhibition exhibited by GTO nanocomposites derived from wood charcoal and coconut shell charcoal against 3 was dispersed in 26 ml of H2SO4. 6 g of KMnO4 was added slowly in steps to the above mixture. The system was kept in an ice bath to prevent overheating. The mixture was stirred for 48 hours in order to facilitate complete oxidation. The reaction was terminated by adding 500 ml 5 °C distilled water and 5 ml 30% H2O2 in order to facilitate the exfoliation of the graphitic domains. The mixture was washed repeatedly with dil. HCl, ethanol and distilled water to get rid of the unoxidized reactants and metal ions. It was further subjected to dialysis for the removal of any leftover acid traces. Once a neutral pH was attained, the samples were sonicated and dried under vacuum to obtain WC-HS (~1.2 g) and CSC-HS (~1.7 g). Third step comprised of a one pot hydrothermal treatment of WC-HS and CSC-HS to obtain GTO nanocomposites and is described as follows. 0.05 g of GO is dissolved in 25 mL ethanol via sonication to ensure the exfoliation of the graphitic domains. At the same time, 2.25 g of SnCl2.2H2O is dissolved in 25 mL ethanol. Both the assortments were then transferred to a beaker and sonicated for 90 minutes to ensure thorough mixing of the two systems. Sn2+ ions get anchored on to the GO sheets during this step. The resultant mixture was heated at 150 °C for 24 hours in a sealed high-pressure Teflon lined autoclave. In this phase, GO undergoes gradual inherent reduction whereas tin nanoparticles get oxidized simultaneously and gets deposited on the graphene surface. The mixture was washed repeatedly with distilled water to eliminate the unwanted chloride ions. The resultant product was then dried in vacuum at 60 °C to obtain GTO nanocomposites WCT (~0.4 g) and CSCT (~1.2 g). The chemicals used were of analytical grade and was purchased from Sigma-Aldrich.The formation of GTO nanocomposites was done in three steps. The remnants obtained after the carbonization of wood (~1 kg for ~320 g WC) and coconut shell (~1 kg for 300 g CSC) were grounded and washed thoroughly as the first step. In the second step, dried samples were subjected to oxidative treatment by using a modified Hummers’ method described as follows. 2 g of the respective precursor along with 2 g of NaNOP. aeruginosa using disc diffusion assay. Sterile Muller-Hinton agar was prepared by autoclaving at 121 °C for about 20 minutes and poured into sterile petri plates under LAF. The plates were allowed to solidify and 100 µL of bacterial suspension P. aeruginosa (0.5 OD) was spread over the nutrient agar using sterile cotton swabs. Thereafter 3 wells (7 mm diameter) were made on the nutrient agar using a sterile cork borer. 0.01 g of the synthesized sample was dissolved in 10 mL of absolute ethanol. 100 µL of this sample was loaded into each well. The plates were then wrapped using a cling film and incubated at 37 °C for 24 hours. Zone of inhibition produced by the nanostructures was then measured using Antibiotic Zonescale supplied by HiMedia Laboratories Pvt. Ltd. Antibiotic cephalexin and clarithromycin (10 μg/disc) were used as positive controls. Negative control was absolute alcohol without any sample. The experiment was performed in triplicate to minimize the experimental errors.Antibacterial studies of the samples were carried out against gram-negative bacterial strain of P. aeruginosa was carried out using 96 well micro-titer plate method63. 100 μL of sterilized Luria Bertani broth was dispensed to each well of the titer plate. 2 mg/mL solution of each sample was prepared in DMSO (Dimethyl Sulfoxide). 100 μL of the sample solution was added to a row of the titer plate and serial dilutions were carried out thereafter. The obtained concentration range was from 1000 to 7.8 μg/mL. 10 µL of bacterial suspension (106 CFU/mL) along with 30 µL of 0.1% of resazurin were added to the sample wells. Antibiotic cephalexin was used as the control. A column of wells dispensed with resazurin was taken as color blank. An adjacent column with both resazurin and bacterial suspension was taken as culture control. The plates were prepared in triplicates and the inoculated plates was incubated at 37 °C for 20 hours.MIC assay of the precursors, GO and GTO nanocomposite against Structural and morphological properties of the samples were studied using various characterization techniques. X-ray diffraction measurements were carried out using a a Bruker AXS D8 Advance X-ray diffractometer. Functional groups were identified using a Shimadzu FT-IR-8400 spectrometer and a RF-5301 PC, Shimadzu fluorescence spectrometer was used to obtain PL spectra of the samples. Raman analysis was carried out using a Horiba LABAM-HR spectrometer at 514 nm. High resolution transmission electron microscope (HRTEM) images of the samples were obtained using a JEM-2100 (JOEL) model system.Supplementary Information


A green and facile method using jet cavitation (JC) was utilized to prepare few layer graphene (FLG) derived from artificial graphite delamination without adding any strong acids and oxidants. The JC method not only provides high quality FLG with high yield but also demonstrate excellent electrochemical performance as anode materials for Li-ion batteries. Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM) as well as BET isotherms and XPS are carried out in this study. The results of atomic force microscopy (AFM) further revealed that up to 85% of the prepared FLG were less than 10 layers. This exfoliation process happened mainly due to the cavitation-induced intensive tensile stress acting on the layered materials. Electrochemical measurements demonstrate that graphite anode delivered only 240 mAh/g while FLG anode achieved more than 322 mAh/g at 5C rate test. These results indicate that JC method not only paves the way for cheaper and safer production of graphene but also holds great potential applications in energy-related technology. By down-sizing graphite from micro to nano-scale, namely graphene, the applications would future widen to polymer composites, anode materials for Li-ion batteries, supercapacitors, hydrogen storage materials, adsorbers and catalysts8.Owing to excellent properties of graphene reported so far, such as Young’s modulus (>1060 GPa), electron conductivity (6000 S/cm), thermal conductivity (~3000 W/m K), light and inexpensive10, growth on SiC12, chemical vapor deposition14, molecular beam epitaxy, chemical synthesis18, chemical routes and other methods21. Mass production of graphene or few layer graphene is being hindered by the expensive cost and environmental threat of its conventional synthesis. For example, disadvantages of chemical vapor deposition are high cost and limitation of area. Chemical routes, so called Hummers’ method, suffered from usage of strong acid and oxidants during oxidation processes. A vast amount of waste acids resulted in environmental pollution and problems. Based on these issues, many researchers focus on green process to synthesize graphene or FLG, such as electrochemical exfoliation24, ultrasonicaion process26 and so on. However, many problems, such as low yields and poor quality of as-synthesized FLG still need to overcome.The synthesis of graphene has been carried out by various methods such as exfoliation and cleavage, ultrasonic exfoliation27 and sonication28 to delaminate the graphene or using jet cavitation method and obtained few layer graphene29. Yi et al. showed the feasibility of delamination by JC for unmodified graphite and other layered materials and investigated the influence of feed concentration and processing time on yield and morphology of the product32. Moreover, Yi et al. demonstrated 10 L batch graphene production by a jet cavitation (JC) method and obtained few-layer graphene with low defect concentration29. The processing time, however, was quite long (8 h). Nacken et al. reported an environmentally friendly method for graphene production in large quantities (5 L batches) in processing times <3 h by top-down processing of isostatic and unmodified graphite in an industrial high pressure homogenizer27. According to the above researches, these solvents are organic-based solvents, like NMP, DMF or acetone in the preparation process, even the surfactants including sodium carboxymethyl cellulose (CMC), non-ionic surfactant TWEEN®80 (TW80) or sodium dodecyl sulfate (SDS) are used. In addition, the production of few-layer graphene was got after using centrifuge. In this paper, we propose a green process by using jet cavitation. Here we use an industrial low temperature ultra-high pressure continuous flow cell disrupter (LTHPD) as a delamination device for delamination of graphite suspension continuously by JC method. In this device the graphite suspension is pumped through a nozzle with a defined flow rate to adjust the system pressure. The cavitation and pressure yields a lateral force that induces exfoliation. Through the combination of velocity gradient-induced shear stress, turbulence-induced Reynolds shear stress, and shear effects that emerged from turbulence and flow-induced collisions, a lateral force is generated causing exfoliation. This normal force caused the bulk material to self-exfoliate to single or few layers through their lateral self-lubricating ability32. This method is simple, scalable and does not require toxic chemicals, graphite oxidation or ultrasound post processing to achieve exfoliation. In this study, we propose a green process by using jet cavitation. Here we use an industrial low temperature ultra-high pressure continuous flow cell disrupter (LTHPD) as a delamination device for delamination of graphite suspension continuously. This method is simple, scalable and does not require toxic chemicals, graphite oxidation or ultrasound post processing to achieve exfoliation.Recently, there were reported in many kinds of literature by using the high pressure homogenizer36. As for applications of graphene anode for Li-ion batteries, Lian et al.37, Jusef et al.38 and Wang et al.39 reported graphene nanosheets synthesized by chemical synthesis demonstrate good electrochemical performances as anodes in lithium-ion cells. However, it suffers from problems of poor electronic conductivity, larger hysteresis and irreversible capacity loss in the first cycle due to structural defects and functional groups in graphene nanosheets resulted from oxidation processes. In addition, Haiyan et al.40 reported the fabrication of anodes for lithium-ion batteries (LIBs) based on graphene nanoflakes. Moreover, the device cycled at 0.5 A/g of current densities present only 200 mAh/g. In 2011, Zhou et al.41 prepared foam-like graphene as an anode for Li-ion batteries. Its capacity at a current density of 0.2 A/g was about only 200 mAh/g.Lithium-ion batteries are among the most widely used energy storage device today. Two-dimensional graphene has drawn much attention because of its admirable properties including conductivity, mechanical strength and high charge carrier mobility which make graphene a suitable electrode material for LIBsTo the best of our knowledge, there are few researches concerning electrochemical behavior and measurements of FLG synthesized from jet cavitation process for Li ion battery. Thus, in this study, we will discuss detail characterizations of FLG in terms of SEM, TEM, BET, AFM as well as Raman and XPS to understand surface morphologies, lateral size, thickness distribution, structural defects, functional groups of as-synthesized FLG. The corresponding electrochemical coin tests, such as C/D tests, cycle life as well as differential capacity plots and AC impedances are carried out.39. In this study, FLG is prepared by JCD without chemical intercalation. Thus, d spacing in 002 plane was closed to 0.34 nm.Figure 43. The average thickness of FLG was 4 nm, which approached 8 layers of graphene (0.5 nm for one layer of graphene) in Fig. 2 adsorption–desorption isotherms of graphene sheets are shown in Fig. 2/g, respectively. FLG demonstrated much larger specific surface area, which indicates that the evidence of graphite exfoliation after our processes.Figure −1, ~1350 cm−1 and ~2700 cm−1 44. The D band is consider the demonstration of the presence of defect and the degree can be estimated by the intensity ratio of the D peak to G peak (ID/IG). The graphite and FLG of intensity ratio of the D peak to G peak (ID/IG) increased from 0.208 to 0.350 through the evolution of ID/IG clearly revealed by comparison of curves. This result demonstrated that defect increased in FLG after exfoliation processes. Furthermore, the oxygen content of graphite and FLG were analysis by XPS is shown in Fig. Raman spectra were analysis so as to examine the defect content of graphite and FLG. Typical spectra for graphite and FLG are shown in Fig. 45. However, graphene is known to have good flexibiltiy compared to graphite. It is believed that graphene will retain the integrity of its shape during rapid lithiation process thus, providing better electrochemical performance. Figure −1 and 369 mAh∙g−1 for graphite and FLG at a current density of 0.1 C (0.035 A/g), corresponding to a coulombic efficiency of 93% and 90, respectively. The reversibility of FLG is comparable to graphite. The solid electrolyte interface (SEI) layer plays an essential role in the reversibility of the capacity. SEI layer is formed by the reaction between graphite and ethylene carbonate (EC) in the electrolyte. It provides kinetic stability to the cell and permits the use of graphite as anode material at the expense of some inevitable irreversible capacity46. Vital properties of energy storage devices such as irreversible capacity loss, cycle life, electrode corrosion, self-discharge rate and safety are highly influenced by the thickness of the SEI layer47. Similar to other literature, as-prepared FLG displayed an irreversible capacity ~0.75 V in the initial cycle attributable to the formation of SEI layer and the reaction of Li+ ions with residual H or O groups in the carbonaceous materials37. Lithium atoms are known to bind quasi-reversibly on the hydrogen terminated edges of graphene. In this study, our few layer graphene is not synthesized by Hummer’s method, namely, reduced graphene oxides. Thus, there is littele functional groups and structural defects in our FLG  and graphene-based (FLG) anode materials for lithium ion battery. During lithiation and de-lithiation, the anode may change its shape51. Rate capability operated at different current rates from 0.1 C to 10 C run for five cycles each  are shown in Fig. 52. An equivalent circuit  formed on the electrode. RCT and CPE2 represent the charge-transfer resistance and the double layer capacitance, respectively, and W1 is the Warburg impedance related to the diffusion of lithium ions into the bulk electrode52. The fitting values from this equivalent circuit are presented in Table S, RSEI and RCT of the graphite electrode are 5.9, 269.9 and 299.9 Ω, respectively, much higher than those of the FLG electrode , which means that both SEI resistance and charge-transfer resistance are significantly reduced in the presence of exfoliation. It is most likely that a more favorable SEI was formed for the FLG electrode than the graphite, which facilitates the lithium ion transfer at the interface between the electrolyte and the electrode. Besides, the thin characteristic was good for the reaction kinetics and diffusion of Li ion53. The Li+ diffusion coefficient can be calculated by the following equation54:R is the gas constant (8.314 J K−1 mol−1), T is the absolute temperature (293.15 K) at room temperature, A is the surface area of the electrode (~1.54 cm2), n is the number of electrons per molecule during oxidization (n = 1), F is Faraday’s constant (96500 C mol−1), and C is the concentration of lithium ions (0.001 mol cm−3). According to the equation  of both graphite and FLG are shown in Fig. ces Fig. 53. Thus,+ intercalation of FLG is faster than that of graphite. The diffusion coefficients of lithium of FLG were increased from 4.39 × 10−11 cm2/s to 2.67 × 10−9 cm2/s. It shows great advantages and is thus proved to be a suitable convenient approach for massive production of graphene. As FLG has been successfully produced by this device and these results indicate that it is potential applications of FLG as anode material for lithium ion battery system.In summary, we develope a method to prepare FLG by JCD. SEM and TEM results indicated that it is transparent and folded, which coincides well with the typical feature of the reported FLG. Beyond the HRTEM and AFM presented in this study, the FLG exhibits thickness of the as-synthesized FLG approaches 10 layers of graphene. Furthermore, the obtained graphene were applied as anode material for lithium ion batteries. During the fast charge and discharge rates (5C), graphite delivered ~239.6 mAh/g while FLG exfoliated in DI water achieved ~322.2 mAh/g, respectively. The FLG presented the lower polarization and the LiThe artificial graphite  was used as feed material for the delamination experiment. All materials were used as supplied without further purification. Deionized water was used for the preparation of all graphite suspensions (10 wt.%). All delamination experiments were carried out in a low temperature ultra-high pressure continuous flow cell disrupter . In this device, the graphite suspension is achieved by high pressure forcing the sample through a small orifice at high speed. At the effect of the shearing, hole and impact, graphite of the sample are crushed; substances of the sample are dispersed and emulsified. And the few layer graphene would be kept the suspension at the crash which operated in circulation cooling device at 14–16 °C circulating water bath. The principle and schematic illustration of JC device are shown in Fig. 2 adsorption by using a Micromeritics TriStar 3000 (USA) analyzer at liquid nitrogen temperature. Spectra were all captured at a resolution of 4 cm−1, and by averaging 10 scans. X-ray photoelectron spectroscopy analysis was performed with a Thermo Scientific K-Alpha using a monochromated Al Kα X-ray source (1486 eV).Raman spectra were obtained with a micro-Raman spectroscopy system; a 532 nm laser was used as the excitation source. Scanning electron microscope (SEM) images were collected by a Hitachi S-4100. Atomic force microscope (AFM) images were captured by a Bruker Dimension Icon. The samples for AFM were prepared by dropping the dispersion directly onto freshly cleaved mica wafer with an injector. Bright-field transmission electron microscope (TEM) and high-resolution TEM (HRTEM) images were taken with a JEM-2100 operating at 200 kV. TEM specimens were made by diluting the suspension in alcohol and pipetting several drops onto holey carbon mesh grid. Brunauer–Emmett–Teller (BET) specific surface area was determined from N6 in ethylene carbonate (EC) and ethyl methyl carbonate (EMC) (1:1 in volume ratio). The discharge/charge test were analysed by AcuTech System in the voltage range of 0.01–3.5 V at room temperature. The Cyclic voltammograms (CV) were measured by CH Instruments Analyser CHI 6273E at a scan rate of 0.001 mVs−1 between 0.01 V and 3.5 V, then tested the AC impedance in the frequency range from 1 Hz ~ 100000 Hz in litigation state of 0.001 V.The electrochemical performance of the products were measured by using CR2032 coin cells. The working electrode was composed of 92 wt.% active materials, 3 wt.% KS-6 ), 1 wt.% Super P  and 4 wt.% PVdF, coating on the 10 μm copper foil, then dried at 120 °C for 8 h in vacuum system to remove the residual water. The electrolyte consisted of 1M LiPFSupporting Information