Graphene Devices for Tabletop and High-Current Quantized Hall Resistance Standards

Abstract

We report the performance of a quantum Hall resistance standard based on epitaxial graphene maintained in a 5-T tabletop cryocooler system. This quantum resistance standard requires no liquid helium and can operate continuously, allowing year-round accessibility to quantized Hall resistance measurements. The ν = 2 plateau, with a value of R_K/2, also seen as R_H, is used to scale to 1 kΩ using a binary cryogenic current comparator (BCCC) bridge and a direct current comparator (DCC) bridge. The uncertainties achieved with the BCCC are such as those obtained in the state-of-the-art measurements using GaAs-based devices. BCCC scaling methods can achieve large resistance ratios of 100 or more, and while room temperature DCC bridges have smaller ratios and lower current sensitivity, they can still provide alternate resistance scaling paths without the need for cryogens and superconducting electronics. Estimates of the relative uncertainties of the possible scaling methods are provided in this report, along with a discussion of the advantages of several scaling paths. The tabletop system limits are addressed as are potential solutions for using graphene standards at higher currents.

I. Introduction

FOR decades, the National Institute of Standards and Technology (NIST) has used comparisons based on a bank of five 100-Ω standard resistors and several cryogenic current comparator (CCC) bridges to support the traceability chain that ties four-terminal resistance values to the quantized Hall resistance (QHR). The resistor bank has over 25 years of continuous measurement history at approximately half-yearly intervals based on a GaAs heterostructure QHR device. International consistency has been verified by resistor intercomparisons and on-site QHR comparisons [1]. One of the CCC bridges is a commercial system with binary windings and wideband superconducting quantum interference device (SQUID) feedback [2]. This system allows the exploration of many new measurement paths in scaling for four-terminal resistors, including precise direct comparisons between 1 kΩ and the QHR. Alternatively, higher resistance levels from 100 kΩ to 10 MΩ are compared directly to the QHR using a two-terminal CCC (2TCCC) bridge with similar high stability obtained using dc SQUID feedback and a single voltage source [3].

At present, most QHR standards are based on AlGaAs/GaAs heterostructures [4] and rely on the integer quantum Hall effect (QHE) as the foundation for traceability of the ohm (SI unit). Although the effect is well-tested [5], accessing the QHR with an uncertainty near one part in 10⁹ requires cumbersome and expensive infrastructure to reach low temperatures (0.3–1.6 K) and high magnetic fields (6–12 T), ultimately limiting the efficiency of calibrations and traceability.

Graphene, the 2-D honeycomb lattice of carbon atoms, exhibits the QHE at higher temperatures and lower magnetic fields than in gallium arsenide (GaAs) [6], allowing the operation of epitaxial graphene (EG) QHR devices in cryogen-free refrigeration systems fitted with compact superconducting magnets [7]. This concept motivates research in optimizing EG devices for metrology to promote accessibility to the QHR.

User friendly automated measurement systems based on direct current comparators (DCCs) [8] are operated without the need for liquid He. Earlier measurements have demonstrated that EG devices can potentially be used up to 10 V [6], [9], where the precision of DCC room temperature bridges can provide turn-key resistance traceability for the most demanding applications [10].

This paper emphasizes the versatility of graphene by presenting the following developments.

1. Scaling between the QHR ν = 2 plateau (as defined by R_k–90/2 = 12906.4035 Ω) directly to 100-Ω, 1-kΩ, and 100-kΩ resistors with the use of a cryogen-free tabletop QHR and CCC bridges. Overall system performance will also be evaluated.

2. Measurements performed with a room temperature DCC from R_K/2 to 1 kΩ and for decade ratios between 10 Ω and 100 kΩ to demonstrate an alternative scaling method, with results compared to those of a CCC.

3. Demonstration of scaling to high-valued resistors using a graphene device at measurement voltages up to 10 V and discussion of issues resulting from increased ohmic heating in the device.

II. Graphene-Based Qhr Preparation

The growth of EG on the Si-face of silicon carbide (SiC) is achieved by sublimating Si atoms at elevated temperatures, allowing the carbon-enriched surface to form a well-organized honeycomb lattice. The graphene-based devices are prepared by similar methods described rigorously in [9] and [11]–[13].

For EG growth square SiC substrates diced from the on-axis 4H-SiC(0001) semi-insulating wafers were used. The graphene sample taken for the experiments presented in Sections III–VI was processed by standard face-to-graphite (FTG) growth at 1900 °C in an argon atmosphere with the SiC (0001) facing toward a polished disk of glassy carbon. For the sample operating at high currents (775 μA, 10 V), a combined growth method using FTG and polymer-assisted-sublimation growth was applied. Both samples were processed in the same graphite-lined resistive-element furnace, with the chamber first flushed with argon gas and filled with 100-kPa argon from a 99.999% liquid argon source. Epitaxial growth occurs with heating and cooling rates of approximately 1.5 K/s and about 270-s annealing time at approximately 1900 °C.

For device fabrication, the graphene layer is protected by a layer of Pd–Au, followed by etching into Hall bar devices and electrical contacting using photolithography. The sample is mounted onto a transistor outline (TO-8) package or a 32-pin leadless chip carrier (LCC-32). The carrier density can be adjusted by gentle heating in vacuum or brief exposure to nitric acid vapor to shift the resistance plateau as desired. The device contact resistances, measured at 4.5 K, 9 T, and 77 μA, are below 1 Ω.

III. Cryogen-Free Tabletop System

The tabletop cryocooler system is mounted on an optical table and attached to a compressor with 3-m hoses. The cryogen-free system reaches temperatures as low as 2.7 K and was operated at 5 T for all measurements. The impact of capacitive coupling, or unwanted measurement signal because of time-varying electric fields from the external environment, had to first be evaluated. It remains of utmost importance that noise is minimized [7], mainly because large enough noise can interfere with proper DCC ampere-turn balancing or CCC SQUID feedback.

A transimpedance amplifier (TIA) and spectrum analyzer were used to detect the current signal from capacitive coupling over the range of several orders of magnitude. To accurately assess the current noise, the low bandpass frequency response of the TIA was measured. The data showing this response are summarized in Fig. 1(a). A low bandpass filter fitting function was used to characterize the frequency response, which allows one to apply a correction factor to the measured output of the spectrum analyzer.

Fig. 1.

Measurements are performed to determine noise impacts on the overall sensitivity of the cryogen-free tabletop system. (a) Frequency response of the TIA is measured, while its input was open and while enclosed in a Faraday cage. Data were fit with a low bandpass filter curve to reveal the expected noise floor of the system. The TIA was connected to wires which were galvanically isolated in the cryogenic system. The wires act as an antenna to pick up any capacitive coupling from the system. (b) Current noise is shown for the TIA (black curve), the system while OFF (blue curve), and the system while ON (red curve). The equipment used while operational includes the compressor, computer, temperature sensors, the magnet power supply, pressure gages, and cryostat wiring.

Fig. 1(b) shows a series of noise curves from various configurations of the system which includes the noise exclusively from the isolated TIA and spectrum analyzer, shown as a black curve. The noise is also measured from the entire cryostat system when all components are powered OFF, as seen by the blue curve. Finally, the red curve represents the case when the entire system is in full operation. In this case, two distinct contributing factors to the overall noise are the compressor, whose fundamental frequency can be seen at 1.4 Hz, and the various temperature sensors at 1.7 Hz with the accompanying higher harmonics.

IV. Additional Measurement Considerations

To provide resistance traceability, the bridge ratio must be well known and stable, so that the bridge is able to maintain reproducible uncertainties comparable to the stability of the standard resistors of the laboratory. Provided these ratios are well-maintained, room temperature bridge systems deliver improved reliability at low cost based on year-round availability without the need for liquid He. The precise ratios of a CCC system are used to calibrate DCC bridges and thus to improve the Type B uncertainty.

The first measurements use as their standard a robust graphene QHR device in the tabletop 5-T magnet system described in Section III [15]. This ensures that the measurements have excellent long-term stability. Precision resistance standards are maintained at constant temperature for scaling, and the Type A uncertainty for each CCC ratio is based on the standard deviation of the mean of a sequence of repeated measurement sets under very similar measurement conditions. A commercial binary-winding CCC (BCCC) was used to define most of the ratio values, with the number of windings giving optimum uncertainty for the current levels used. A 2TCCC with a winding ratio of 310-to-40 was used for measurements between the QHR standard and air-type 100-kΩ standard resistors [16].

V. Data And Results From Initial Qhr Transfers

A. BCCC Results

Fig. 2 shows the results using the BCCC bridge to scale from a graphene device to a 1-kΩ resistor using bridge voltages of 0.5, 1.0, and 1.5 V, corresponding to source-drain currents I_sD = 38.7, 77.5, and 116 μA, respectively. Here, the Hall resistances $R_{\mathrm{H}}^{(1)}$ and $R_{\mathrm{H}}^{(2)}$ were measured at two pairs of orthogonal contacts bordering a region of width ω = 0.4 mm and length l = 0.64 mm. Diagonal Hall resistance measurements using diagonal contacts of the same pairs reveal the influence of dissipation on the longitudinal resistance, indicated by R_H+xx in the third panel. The longitudinal resistivity is derived as ρ_xx = (ω/l) × {∣R_H+xx∣ – ∣R_H∣} ≈ 20 μΩ for I_SD = 38.7 μA, ρ_xx ≈ 47 μΩ for I_SD = 77.5 μA and ρ_xx ≈ 160 μΩ for I_SD = 116 μA. Measurements at the orthogonal contacts for lower currents of 38.7 and 77.5 μA were averaged to give a precise calibration result for the 1-kΩ standard with a combined standard uncertainty of 3 nΩ/Ω.

Fig. 2.

BCCC measurements performed using a graphene QHR standard in a NIST cryogen-free tabletop system. BCCC measurement data are displayed in three rows, with the blue, green, and red data corresponding to the source–drain currents of 38.7 μA, 77.5 μA, and 116 μA, respectively. Comparisons between the QHR in graphene and a 1-kΩ resistor are shown in three columns, using two orthogonal contact pairs corresponding to R_H⁽¹⁾ (green area) and R_H⁽²⁾ (off-white area), and both diagonal contact pairs labeled R_H+xx to evaluate the impact of the longitudinal resistance (red area). Type A measurement uncertainties are smaller than the data points. Type B uncertainties are under 0.002 μΩ/Ω.

B. Overall Device Performance

In Fig. 3(a), DCC measurements extend the range of source–drain current in scaling from the QHR device to the same 1-kΩ resistor. In the main graph of Fig. 3(a), the deviations from the low-current BCCC result exceed about 0.01 μΩ/Ω when I_sD ≥ 116μΩ in agreement with the earlier results. The inset of Fig. 3(a) shows a subset of five different currents that were applied to the device, along with the corresponding temperatures reported by the sensor beneath the TO-8 package. Maintaining a temperature below 4 K is still very feasible even after applying nearly 250 μA to the device and extrapolating the seemingly quadratic behavior of the temperature until 4 K reveals that currents as high as 550 μA could potentially be applied in the future devices mounted in the tabletop system.

Fig. 3.

(a) Current dependence of DCC ratios for a 1-kΩ resistor are shown in magenta, based on the same graphene QHR device used with the BCCC. The DCC results confirm that the device remains quantized to within 0.01 μΩ/Ω up to approximately 116 μA. The current dissipation effect on the sample temperature is shown in the inset with blue data points. Some Type A measurement uncertainties (in red) are smaller than the data points. (b) DCC data for QHR to 1 kΩ for increasing source–drain currents, normalized to the average results of BCCC scaling at 38.7 and 77.5 μA. The red error bars show the expanded (k = 2) correlated uncertainties whereas the blue error bars show the expanded (k = 2) uncertainty reported by the measurement device.

In Fig. 3(b), the number of DCC data points averaged was varied inversely with the square of the applied voltage V∣ I_SD × R_H to obtain a similar Type A uncertainty for all values of I_SD. The duration of the resulting data sets shown in Fig. 3(b) ranged from 110 min for the lowest measurement voltage (0.5 V) to 24 min for the highest (1.2 V), with the data from the first 10 min (20 points) of each set discarded to allow the DCC bridge nanovoltmeter balance to reach equilibrium. The smaller uncertainties, shown in blue, are produced by the measurement software and approximate standard deviations of the means for DCC results. The larger vertical bars, in red, are uncertainties adjusted to account for statistical correlations in the data sequence [17]. Both uncertainty results represent the coverage factor k = 2. The observed statistical differences between pairs of successive measurements with the same conditions show that both estimates of the standard deviations likely underestimate the Type A uncertainties, at least for the highest currents shown in Fig. 3(b). This underestimation may be caused by incomplete settling of the nanovolt balance and the effects of filters present in the measurement software. The noise caused by the cryogen-free mechanical refrigeration system may also interfere with the balancing algorithm or ampere-turns balance since the underestimation of Type A uncertainty is less pronounced for noncryogenic resistor comparisons.

The measured ratios using the DCC and CCC were corrected for the measured drift of the room temperature standard. This left only the DCC bridge ratio instability, which can be minimized over long periods if the DCC bridge, is maintained in well-controlled laboratory environmental conditions. We have not observed any significant drift in the bridge ratio since it was installed in our facility. Thus, we attribute the significant standard deviations of our results using the same measurement parameters to short-term instability in the bridge balance, qualifying it as a Type A uncertainty. The differences between these results for different measurement voltages or currents may be evidence of Type B bridge ratio errors or self-heating in the standard resistor at higher levels of power dissipation.

VI. Data and Results from Subsequent Resistance Scaling

DCC scaling results were obtained for four ratios of standard resistors and compared with the means of similar NIST CCC results. The applied voltages and balance equilibration times were adjusted to optimize those parameters for each decade. We varied the number of data in each DCC measurement to obtain similar Type A uncertainties over a wide range of applied voltage. Statistical adjustments were made to account for correlations within each data set, following Zhang [17]. These adjustments vary for each set and on average result in Type A uncertainties 1.8 ± 0.5 (k = 2) times larger than the software-calculated standard deviations.

For the decade resistance ratios graphed in Fig. 4, two results were obtained in succession before changing the measurement voltage. The uncertainty bars represent Type A results obtained from the autocorrelation adjustment. Fig. 4(a) used a voltage range of 1 V–5.07 V and measurement times ranging from 108 min to 5 min and is referenced to the ratio obtained using a 2TCCC. In Fig. 4(b), the 1-kΩ–10-kΩ scaling data sets were collected for a voltage range of 1 V–3.16 V and measurement times ranged from 85 min to 9 min. Fig. 4(c) shows the 100-Ω–1-kΩ ratio compared using voltages from 0.5 V to 1 V and measurement times between 65 min and 17 min. Finally, Fig. 4(d) shows the results of comparisons between 10 Ω and 100 Ω, for voltages of 0.16 V–1.0 V and measurement times of 65 min–2 min. The weighted mean (green lines in Fig. 4) of all the runs for a given ratio uses the autocorrelated errors as weights.

Fig. 4.

DCC bridge scaling for the following standards are shown: (a) 100–10 kΩ, (b) 10–1 kΩ, (c) 1 kΩ to 100 Ω, and (d) 100–10 Ω. For each run, the number of points was adjusted to maintain similar Type A uncertainties over the range of applied voltages. The error bars indicate expanded (k = 2) type A uncertainty after adjustment to account for correlations, respectively.

Similar ratios were measured at the National Research Council (NRC) Laboratory, Ottawa, ON, Canada, in the initial calibration of the DCC bridge in May 2017, and the values shown for the vertical scales in Fig. 4 are referenced to those calibrations. The measurement software automatically adjusts the measured data, based on a table of CCC results, in this case supplied by the NRC. To help estimating long-term drift in the bridge ratios, we also show the uncalibrated bridge zero as a dotted horizontal line in each graph.

Resistance standard uncertainty estimates (k = 2) of Type A and Type B influences in scaling with the DCC method are presented in Table I. Type B values represent combined estimates for all known influences of DCC scaling but are dominated by the bridge ratio stability.

TABLE I.

DCC Resistance Uncertainty Measurements

Resistance values (Ω)	Primary current (mA)	Secondary current (mA)	Meas. Time (min.)	Type A (μΩ/Ω)	Type B (μΩ/Ω)
100, 10	3.16	31.6	40	0.002	0.005
1 k, 100	1	10	20	0.002	0.015
10 k, 1 k	0.15	1.5	40	0.009	0.017
10 k, 1 k	0.27	2.7	20	0.007	0.017
RK/2,1 k	0.0775	1	30	0.012	0.012
RK/2,1 k	0.038	0.5	110	0.017	0.012
100 k, 10 k	0.034	0.34	30	0.1	0.25

VII. Compatibility of Graphene QHR With High-Current Comparisons

Among the advantages offered by graphene-based QHR standards is their ability to maintain the fully quantized state at high currents, such that voltages larger than 5 V can, in some cases, be utilized for better compatibility with high-resistance measurements up to 100 kΩ [6], [9]. The NIST cryogen-free system, as it is currently designed, would be unable to accommodate voltages much higher than 5 V, corresponding to approximately 387 μA, due to the rise in sample temperature shown in Fig. 3(a).

To illustrate the importance of power dissipation in the graphene QHR system, we employed a replenished liquid ⁴He cryogen system where the base temperature is 1.5 K. The specific heat capacity of liquid ⁴He at atmospheric pressure features a discontinuity at T_λ = 2.17 K which can be attributed to the transition of normal fluid (He I) to the superfluid phase (He II). The discontinuity, shown in Fig. 5(a), is colloquially named the Lambda point [18], [19]. Most importantly, the superfluid flows without loss of kinetic energy and with zero viscosity. The enhanced thermal properties of the superfluid helium allow for better rejection of heat, which has been generated by power dissipation near the hot spots on the corners of the device, where the two potentials meet [20]. In our liquid cryogen system, we fill the lower sample region with He I and then significantly reduce the liquid flow into the sample space while pumping on the evolved He gas above the liquid, where the sample resides. Below the Lambda point, He II forms a thin superfluid film, known as a Rollin film, which provides additional cooling power by making direct contact with the device. The comparative increase in cooling power is illustrated in Fig. 5(b) and (c)

Fig. 5.

(a) Lambda point is depicted from [18] as the discontinuity in the liquid helium’s specific heat capacity occurring at T_λ = 2.17 K. The specific heat capacity behavior is shown around the transition temperature in Kelvin and is separated by the two phases: He I (brown) and He II (gold). (b) While the temperature remains above the transition, heat is dominantly generated at the contacts (“hot” spots illustrated as white dots) and dissipates through the device in the plane, shown in red. Heat also transfers to the surrounding liquid (brown) out of plane, shown in purple. The excessive heat contributes to quantum Hall breakdown. (c) After cooling below the transition, the superfluid He II (gold) retains a higher specific heat capacity in addition to the unusual property of frictionless flow, allowing for heat in the local environment to be transferred away more effectively. This is illustrated as a significant reduction in sample heating and a larger heat transfer into the surrounding superfluid.

These unusual properties of superfluid He II drastically improve the cooling power for graphene devices operated at higher currents. Fig. 6 illustrates how the QHE transport characteristics are impacted by the superfluid, for a graphene device operated at 775 μA (10 V) and compared to a 100-kΩ standard resistor using a 2TCCC. In two separate measurement sequences, the heat was slowly applied to or removed from the sample region as we recorded the diagonal Hall resistance deviation, which incorporates any longitudinal resistance in the middle of the device (top) and the pure longitudinal resistance (bottom). The enhanced cooling power of the He II phase liquid reduced the deviation in R_xy to nearly zero at 6.5 T. Those points measured by coincidence during the transition show intermediate values due to averaging of measurements for both directions of measurement voltage. Above the transition, the thermometer rapidly tracked the change in power dissipated by the device, as observed each time the measurement voltage was reversed, while no such variations were observed in the presence of He II.

Fig. 6.

Diagonal Hall and longitudinal resistances are tracked as a function of time and temperature to illustrate the effects of the superfluid on the graphene device as it operates at high current (775 μA). Both panels have time as the horizontal axis and correspond to different measurements. The diagonal Hall resistance measured at B = 6.5 T to emphasize the improvement resulting from increased cooling below the Lambda point, and after the superfluid transition. This process is reversible when the liquid is warmed and enters the normal phase (top). A similar measurement is performed for the longitudinal resistance of the device at B = 9 T showing a decrease in more than 80% after the superfluid transition (bottom).

Fig. 7 shows orthogonal and diagonal Hall measurements at 10 V as a function of the magnetic flux density B. Above the transition (top), the diagonal measurements do not converge until B ≥ 9 T, while below the transition (bottom), the diagonal measurements overlap and the device retains metrologically useable resistances for magnetic fields as low as 6.8 T. The onset of metrologically useful QHR quantization abruptly drops to lower magnetic fields below the transition temperature, due to enhanced cooling.

Fig. 7.

Data from a graphene device with an applied voltage of 10 V measured in a liquid ⁴He cryostat. Two adjacent Hall resistances are measured and represented by yellow and green circles, whereas the two diagonal resistances are represented by magenta and blue triangles and include the effect of the device’s longitudinal resistance. These four measurements taken at T ≥ 2.27 K as a function of the applied magnetic field (top). The differences in convergence between the Hall and diagonal resistances are a result of a nonzero longitudinal resistance. The point of agreement between both diagonal resistance contact pairs is represented by a red “×.” Similar data as above but collected at T ≤ 2.15 K and with the point of agreement represented by a blue “×” (bottom).

One key takeaway message from this data is that sufficient cooling power is required for higher levels of ohmic heating, and efficient heat sinking of the device will be critical. One solution may be the use of larger devices, where both the source and drain are physically separated from the central region of the device, allowing heat to flow out of the substrate before reaching the region of metrological interest. An alternative is to use an array of devices, with series or parallel devices carrying nearly equal current.

VIII. Conclusion

We have evaluated measurements of QHR devices based on EG and describe an experimental process that requires no liquid He and yields scaling uncertainty of one part in 10⁸ in comparisons with room temperature standard resistors of value 1 kΩ. This may enable future developments for creating systems inherently simpler to use than those normally required for GaAs-based resistance standards.

DCC scaling results between the QHR standard and decade resistance values from 10 Ω to 100 kΩ are compared to similar results from CCC measurements as a preliminary study of DCC suitability for traceability of the ohm based on the QHR. Although tabletop cryocooler systems are inherently limited in their cooling power, they offer significant benefits in terms of overall simplicity to manufacture, assemble, and operate. For more specialized measurements requiring voltages above 5 V, wet cryogenic systems may still be required. However, in all cases, graphene has shown impressive levels of versatility throughout various facets of resistance metrology.

Biography

Albert F. Rigosi (M’17) was born in New York City, NY, USA, in 1989. He received the B.A., M.A., M.Phil., and Ph.D. degrees in physics from Columbia University, New York City, NY, USA, in 2011, 2013, 2014, and 2016, respectively.

From 2008 to 2015, he was a Research Assistant with the Columbia Nano Initiative, New York City, NY, USA. From 2015 to 2016, he was a Joint Visiting Research Scholar with the Department of Applied Physics, Stanford University, Stanford, CA, USA, and the SLAC National Accelerator Laboratory, PULSE Institute, Menlo Park, CA, USA. Since 2016, he has been a Physicist with the National Institute of Standards and Technology, Gaithersburg, MD, USA. His current research interests include 2-D electron systems and applications of those systems’ behaviors for electrical metrology.

Dr. Rigosi is a member of the American Physical Society and the Mellon-Mays Initiative of The Andrew W. Mellon Foundation. He was a recipient of the associateships and fellowships from the National Research Council, USA, the Optical Society of America, the Ford Foundation, and the National Science Foundation (Graduate Research Fellowship Program).

Alireza R. Panna was born in Mumbai, India. He received the B.S. degree in electrical engineering from the University of Maryland, College Park, MD, USA, in 2013.

From 2012 to 2013, he was a Guest Researcher for the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, where he was involved in magnet characterization for the NIST-4 watt balance. From 2013 to 2017, he was with the National Institute of Health, Bethesda, MD, USA, where he was involved in the controls and characterization of various X-ray imaging modalities. He is currently with NIST, where he is involved in the metrology of the ohm and the quantum conductance projects.

Shamith U. Payagala received the B.S. degree in electrical engineering from the University of Maryland, College Park, MD, USA, in 2015.

In 2014, he joined the National Institute of Standards and Technology, Gaithersburg, MD, USA, where he serves as an Electrical Engineer for the metrology of the ohm project.

Mattias Kruskopf was born in Hamburg, Germany, in 1984. He received the M.Sc. degree in electronics engineering, with a focus on metrology, from the Bremen University of Applied Sciences, Bremen, Germany, in 2013, and the Ph.D. degree from Physikalisch-Technische Bundesanstalt, Braunschweig, Germany, with a focus on epitaxial graphene for quantum resistance metrology in the working group of low-dimensional electron systems.

He is currently with the National Institute of Standards and Technology, Gaithersburg, MD, USA, where he is focusing on improving the scalability and the adoption of graphene-based resistance standards.

Marlin E. Kraft was born in Ransom, KS, USA, in 1951. He received the A.S. degree in electronic technology from Kansas State University, Manhattan, KS, USA, in 1980.

From 1980 to 2001, he was with the Primary Standards Laboratory, Sandia National Laboratories, Albuquerque, NM, USA, where was the Associate Project Leader and he specialized in all areas of dc metrology. Since 2002, he has been with the National Institute of Standards and Technology, Gaithersburg, MD, USA, for the metrology of the ohm in the Fundamental Electrical Measurements Group, where he has been involved in dc current, high and low dc resistance, and dc high voltage.

George R. Jones received the B.S. degree from Wake Forest University, Winston-Salem, NC, USA, in 1976, and the Ph.D. degree in physics from the University of Virginia, Charlottesville, VA, USA, in 1983.

Since 1983, he has been with the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA. Initially, he worked with E. R. Williams on the gyromagnetic ratio of the proton. Subsequently, he helped to develop new measurement standards to be used to characterize flat-panel displays for original equipment manufacturers and end users. Since 1997, he has been involved with the Metrology of the Ohm Group, NIST. His current research interests include the temperature and pressure characterization of precision resistors, writing the control software for the cryogenic current comparators used in the NIST resistance laboratory, and most recently, the graphene project at NIST.

Bi-Yi Wu received the B.S. degree in physics from National Cheng Kung University, Tainan, Taiwan, in 2013. He is currently pursuing the Ph.D. degree in applied physics with National Taiwan University, Taipei, Taiwan.

In 2016, he joined the NS2 Research Group, Universitei Paris-Sud, Orsay, France, as a Visitor. In 2017, he joined the National Institute of Standards and Technology, Gaithersburg, MD, USA, as a Guest Researcher. His current research interests include the electronic transport of CVD and epitaxial graphene at low temperatures and fabrication techniques for nanostructured devices.

Hsin-Yen Lee received the B.S. and M.S. degrees in physics from National Tsing Hua University, Hsinchu, Taiwan, in 2002 and 2004, and the Ph.D. degree in physics from National Taiwan University, Taipei, Taiwan, in 2012.

He fulfilled his mandatory Taiwanese military service in 2005. From 2006 to 2007, he was a Senior Process Integration Engineer with the United Microelectronics Corporation, Hsinchu, and from 2012 to 2016, he was a Post-Doctoral Researcher with the Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, and the Department of Physics, National Taiwan University, Taipei. Since 2016, he has been a Guest Researcher with the National Institute of Standards and Technology, Gaithersburg, MD, USA. His current research interests include the development of surface treatment techniques on transparent semiconductor heterojunctions, the pursuit of graphene quantum Hall resistance standards, and the fabrication of graphene and other 2-D material devices.

Yanfei Yang received the B.S. degree in applied optics from Sichuan University, Chengdu, China, in 1999, and the Ph.D. degree in physics from Georgetown University, Washington, DC, USA, in 2010. Her Ph.D. dissertation focused on quantum transport in carbon nanotubes and the investigation of possible intrinsic superconductivity in isolated carbon nanotubes.

From 2012 to 2017, she was an Associate Researcher with the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, where she was involved in the development of new resistance standards based on quantum Hall devices made of epitaxial graphene.

She was a recipient of the Physical Measurement Laboratory’s (NIST) Distinguished Associated Award for advancing quantum metrology through the development of graphene quantum Hall resistance standards that offer robust, accurate, and cost-effective dissemination of the ohm.

Jiuning Hu received the B.S. and M.S. degrees in electronic engineering and microelectronics from Tsinghua University, Beijing, China, in 2006 and 2008, respectively, and the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, IN, USA, in 2013.

Since 2013, he has been with the National Institute of Standards and Technology, Gaithersburg, MD, USA.

Dean G. Jarrett (S’88–M’90–SM’99) was born in Baltimore, MD, USA, in 1967. He received the B.S. degree in electrical engineering from the University of Maryland, College Park, MD, USA, in 1990, and the M.S. degrees in electrical engineering and applied biomedical engineering from Johns Hopkins University, Baltimore, MD, USA, in 1995 and 2008, respectively.

Since 1986, he has been with the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, where he was a Cooperative Education Student from the University of Maryland. During this time, he was involved in the dc resistance area on the automation of resistance calibration systems. In 1991, he joined NIST as a full-time Electrical Engineer, where he is involved in the development of an automated ac resistance calibration system and new resistance standards. Since 1994, he has been involved in the high-resistance laboratory developing automated measurement systems and improved standard resistors to support high-resistance calibration services and key comparisons. He is involved in sensor technologies for the detection of biological molecules and low-current source and measure techniques. Since 2014, he has been leading the Metrology of the Ohm Project, NIST.

David B. Newell received the B.S. degree in physics and the B.A. degree in mathematics from the University of Washington, Seattle, WA, USA, and the Ph.D. degree in physics from the University of Colorado, Boulder, CO, USA.

In 1996, he joined the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, as a full-time Staff Member. From 2004 to 2010, he was a Leader of the Fundamental Electrical Measurements (FEM) Group, where he was involved in measurements for realizing microscale and nanoscale forces traceable to the SI, helped to establish the use of graphene in quantum electrical standards, worked with a NIST team to construct a new watt balance to realize the kilogram from a fixed value of the Planck constant, and provided the exact values of the fundamental constants to be used in the new SI. He is currently a Leader of the FEM Group.

Dr. Newell is a member of the Philosophical Society of Washington, a Fellow of the American Physical Society, and the Chair of the CODATA Task Group on Fundamental Constants. He was a recipient of the NRC Postdoctoral Fellowship to work on the Watt Balance Project at NIST.

Randolph E. Elmquist (M’90–SM’98) received the Ph.D. degree in physics from the University of Virginia, Charlottesville, VA, USA, in 1986.

He leads the Quantum Conductance Project at the National Institute of Standards and Technology, Gaithersburg, MD, USA. Working for the past 32 years in the field of electrical and quantum metrology, he has contributed to the experimental design and measurement of the electronic Kilogram and calculable impedance standards for the determination of the von Klitzing constant and alpha, the unitless fine structure constant. He is involved in the development of cryogenic current comparator systems, the quantum Hall effect, and graphene electronic devices for metrology.

Dr. Elmquist is a member of the American Physical Society.