Supplementary Information Electrical Pulse Fabrication of Graphene Nanopores in Electrolyte Solution Aaron T. Kuan,1 Bo Lu,2 Ping Xie,3 Tamas Szalay1 and Jene A. Golovchenko1,2a) 1School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, 02138, USA 2Department 3Oxford a) of Physics, Harvard University, Cambridge, Massachusetts, 02138, USA Nanopore Technologies, One Kendall Square, 02139, Cambridge, Massachusetts, USA Corresponding author, email: golovchenko@physics.harvard.edu 1 Supplementary Information Outline 1. TEM image of suspended graphene membrane 2. Electrical pulse characteristics 3. Correlation between enlargement steps and pore size 4. Pore characteristics 5. Finite element models 6. TEM imaging of electrical pulses fabricated nanopores 7. RAMAN characterization of graphene 2 1. TEM image of suspended graphene membrane (a) TEM micrograph of a suspended graphene membrane. >50% of the graphene surface area is atomically clean. (b) Electron diffraction of suspended graphene membrane. The single hexagonal diffraction pattern indicates that the suspended membrane is Fig. S1: TEM image of suspended graphene single-layer, single-grain graphene. 2. Electrical pulse characteristics Pulses were supplied by an HP 8110A pulse generator using the 50Ω to 10kΩ output impedance setting and 10 ns rise time. A 5V, 250 ns input pulse (blue trace) was measured using a 10kΩ/50Ω voltage divider (exponential rise and fall presumably due to ~2 pF of parasitic capacitance). The response of a suspended graphene membrane device to such a pulse was measured across a 50Ω terminating resistor (green trace), showing an RC charging time constant of about 30 ns. The device can be approximated by the Fig. S2: Voltage Pulse Characteristics equivalent circuit shown in the diagram. The voltage drop across the membrane during the pulse is Vin – Vout(t). This measurement shows that the membrane is charged to the full voltage (Vout ≈ 0) for most of the duration of the 250 ns pulse. 3 3. Correlation between enlargement steps and pore size Fig. S3 shows the change in diameter due to standard enlargement pulses (5V 250 ns), ΔDE, plotted as a function of the calculated pore diameter before the pulse. Spearman’s rank-order correlation coefficient (rs) was used to quantify the correlation, giving rs = 0.03, with an associated p-value of 0.38 (n = 702). These data suggest that the changes in diameter due to enlarging pulses are independent from the pore diameter, which was an assumption made in the simple Monte Carlo simulation in Fig 2b. Fig. S3: Correlation between ΔDE and Pore Diameter 4. Pore Characteristics Fig. S4a shows IV curves of a graphene membrane before and after fabrication of a 5.5 nm nanopore. After fabrication, a marked increase in linear conductance is observed. Generally, this conductance is stable over periods of time as long as several days. Fig. S4b shows the noise power spectrum of the same nanopore with 100 mV applied bias. The noise is dominated by a 1/f-like component. The red line is a 1/f fit to the data. There is large sample-tosample variation in the 1/f noise (up to an order of Fig. S4: Pore Characteristics magnitude). The source of this 1/f noise is still unknown. 4 5. Finite element model An axisymmetric finite element model of the pore was built using the COMSOL Multiphysics software (COMSOL, Inc.) to predict open pore currents and DNA translocation blockages (Fig. S5) for various pore diameters and thicknesses. The model included electrostatics and fluid dynamics (coupled Poisson-Boltzmann and Navier-Stokes equations)5. Uncoated graphene membranes were modeled as an insulating membrane of thickness T = 0.6 nm6. Coated graphene membranes used T = 4.1 nm (0.6 nm + 2L, Fig. Fig. S5: Finite element model S4), and the DNA was modelled as an insulating, charged rod 2.3 nm in diameter7. The predicted current blockage is the difference between the open pore current and the current with DNA. The color map in the images shows the magnitude of the current density (5 nm diameter, 3 M KCl, 200 mV bias). 6. TEM imaging of electrical pulse fabricated nanopores Direct TEM imaging of pulse-fabricated graphene nanopores was very difficult and was not achieved reliably enough to serve as a precise verification of pore sizes. Contamination during drying of the sample, in air, and under the electron beam often obscured the pores. Locating small pores was difficult because the contrast of the pore edges is no stronger than the patterns of surface contamination on the graphene. Moreover, standard TEM electron energies (80-200kV) can create or enlarge pores in graphene during the search process1,2. For larger pores, the pore can sometimes be successfully imaged, but the accuracy of pore size measurements is limited due 5 to the complications just mentioned. Fig. S6 shows a suspended membrane containing a single ~10 nm pore, which is near the middle of the aperture and approximately circular. 7. Raman characterization of graphene Direct Raman characterization of the samples used in this study was not feasible because the silicon nitride adds a large background to the Raman signal and the areas of suspended graphene (~100 nm) are much smaller than a Raman laser spot size (~3 µm). However, we performed Raman analysis of graphene transferred to SiO2. Figure S7a shows a typical Fig. S6: TEM image of electrical pulse fabricated pore Raman spectrum, showing the characteristic graphene G and 2D bands. Figures S7b and S7c show spatial maps of the 2D/G and D/G ratios, respectively. These images suggest that there are local areas of defective and/or multilayer graphene throughout the sample, but the majority of the sample is single layer, good quality graphene. Therefore, it is likely that most small-area suspended graphene membranes are single layer and defect free, as observed in our experiments. Fig. S7: (a) Raman spectrum of graphene on SiO2, showing D, G, and 2D bands. (b) Raman scan image showing 2D/G ratio. (c) Raman scan image showing D/G ratio. Color scale on images is a linear scale where white indicates the largest value and black the smallest. 6 References 1 C. J. Russo and J.A. Golovchenko, Proc. Natl. Acad. Sci. U.S.A. 109, 5953–5957 (2012). 2 Q. Xu et al., ACS Nano 7, 1566–72 (2013). 3 W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery, Numerical Recipes: The Art of Scientific Computing (Cambridge University Press, Cambridge, 2007) pp. 805–818. 4 G.F. Schneider, et al. Nat. Commun. 4, 1–7 (2013). 5 B. Lu, D.P. Hoogerheide, Q. 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