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We use phenomenological modelling and detailed experimental studies of charge carrier transport to investigate the dependence of the electrical resistivity, ρ, on gate voltage, V g , for a series of monolayer graphene field effect transistors with mobilities, μ, ranging between 5000 and 250 000 cm2 V−1 s−1 at low-temperature. Our measurements over a wide range of temperatures from 4 to 400 K can be fitted by the universal relation μ = 4 / e δ n max for all devices, where ρ max is the resistivity maximum at the neutrality point and δn is an ‘uncertainty’ in the bipolar carrier density, given by the full width at half maximum of the resistivity peak expressed in terms of carrier density, n. This relation is consistent with thermal broadening of the carrier distribution and the presence of the disordered potential landscape consisting of so-called electron–hole puddles near the Dirac point. To demonstrate its utility, we combine this relation with temperature-dependent linearised Boltzmann transport calculations that include the effect of optical phonon scattering. This approach demonstrates the similarity in the temperature-dependent behaviour of carriers in different types of single layer graphene transistors with widely differing carrier mobilities. It can also account for the relative stability, over a wide temperature range, of the measured carrier mobility of each device.

Pristine graphene and graphene-based heterostructures can exhibit exceptionally high electron mobility if their surface contains few electron-scattering impurities. Mobility directly influences electrical conductivity and its dependence on the carrier density. But linking these key transport parameters remains a challenging task for both theorists and experimentalists. Here, we report numerical and analytical models of carrier transport in graphene, which reveal a universal connection between graphene’s carrier mobility and the variation of its electrical conductivity with carrier density. Our model of graphene conductivity is based on a convolution of carrier density and its uncertainty, which is verified by numerical solution of the Boltzmann transport equation including the effects of charged impurity scattering and optical phonons on the carrier mobility. This model reproduces, explains, and unifies experimental mobility and conductivity data from a wide range of samples and provides a way to predict a priori all key transport parameters of graphene devices. Our results open a route for controlling the transport properties of graphene by doping and for engineering the properties of 2D materials and heterostructures. Graphene exhibits both extremely high electrical conductivity and electron mobility but an incomplete understanding of the underlying mechanisms so far limits potential applications in electrical devices. Here, the authors theoretically and experimentally investigate the role of charged impurities and optical phonons on the conductivity properties of graphene and establish a universal connection between the mobility and conductivity.

The evolution of human cognitive function is reliant on complex social interactions which form the behavioural foundation of who we are. These social capacities are subject to dramatic change in disease and injury; yet their supporting neural substrates remain poorly understood. Hyperscanning employs functional neuroimaging to simultaneously assess brain activity in two individuals and offers the best means to understand the neural basis of social interaction. However, present technologies are limited, either by poor performance (low spatial/temporal precision) or unnatural scanning environment (claustrophobic scanners, with interactions via video). Here, we solve this problem by developing a new form of hyperscanning using wearable magnetoencephalography (MEG). This approach exploits quantum sensors for MEG signal detection, in combination with high-fidelity magnetic field control – afforded by a novel “matrix coil” system – to enable simultaneous scanning of two freely moving participants. We demonstrate our approach in a somatosensory task and an interactive ball game. Despite large and unpredictable subject motion, sensorimotor brain activity was delineated clearly in space and time, and correlation of the envelope of neuronal oscillations between people was demonstrated. In sum, unlike existing modalities, wearable-MEG combines high fidelity data acquisition and a naturalistic setting, which will facilitate a new generation of hyperscanning.

© 2020 The Authors. Advanced Functional Materials published by Wiley-VCH GmbH 2D materials have unique structural and electronic properties with potential for transformative device applications. However, such devices are usually bespoke structures made by sequential deposition of exfoliated 2D layers. There is a need for scalable manufacturing techniques capable of producing high-quality large-area devices comprising multiple 2D materials. Additive manufacturing with inks containing 2D material flakes is a promising solution. Inkjet-printed devices incorporating 2D materials have been demonstrated, however there is a need for greater understanding of quantum transport phenomena as well as their structural properties. Experimental and theoretical studies of inkjet-printed graphene structures are presented. Detailed electrical and structural characterization is reported and explained by comparison with transport modeling that include inter-flake quantum tunneling transport and percolation dynamics. The results reveal that the electrical properties are strongly influenced by the flakes packing fraction and by complex meandering electron trajectories, which traverse several printed layers. Controlling these trajectories is essential for printing high-quality devices that exploit the properties of 2D materials. Inkjet-printed graphene is used to make a field effect transistor and Ohmic contacts on an InSe phototransistor. This is the first time that inkjet-printed graphene has successfully replaced single layer graphene as a contact material for 2D metal chalcogenides.

© 2017 The Authors Advances in the field of quantum sensing mean that magnetic field sensors, operating at room temperature, are now able to achieve sensitivity similar to that of cryogenically cooled devices (SQUIDs). This means that room temperature magnetoencephalography (MEG), with a greatly increased flexibility of sensor placement can now be considered. Further, these new sensors can be placed directly on the scalp surface giving, theoretically, a large increase in the magnitude of the measured signal. Here, we present recordings made using a single optically-pumped magnetometer (OPM) in combination with a 3D-printed head-cast designed to accurately locate and orient the sensor relative to brain anatomy. Since our OPM is configured as a magnetometer it is highly sensitive to environmental interference. However, we show that this problem can be ameliorated via the use of simultaneous reference sensor recordings. Using median nerve stimulation, we show that the OPM can detect both evoked (phase-locked) and induced (non-phase-locked oscillatory) changes when placed over sensory cortex, with signals ~4 times larger than equivalent SQUID measurements. Using source modelling, we show that our system allows localisation of the evoked response to somatosensory cortex. Further, source-space modelling shows that, with 13 sequential OPM measurements, source-space signal-to-noise ratio (SNR) is comparable to that from a 271-channel SQUID system. Our results highlight the opportunity presented by OPMs to generate uncooled, potentially low-cost, high SNR MEG systems.

Magnetoencephalography (MEG) is a sophisticated tool which yields rich information on the spatial, spectral and temporal signatures of human brain function. Despite unique potential, MEG is limited by a low signal-to-noise ratio (SNR) which is caused by both the inherently small magnetic fields generated by the brain, and the scalp-to-sensor distance. The latter is limited in current systems due to a requirement for pickup coils to be cryogenically cooled. Recent work suggests that optically-pumped magnetometers (OPMs) might be a viable alternative to superconducting detectors for MEG measurement. They have the advantage that sensors can be brought to within ~4 mm of the scalp, thus offering increased sensitivity. Here, using simulations, we quantify the advantages of hypothetical OPM systems in terms of sensitivity, reconstruction accuracy and spatial resolution. Our results show that a multi-channel whole-head OPM system offers (on average) a fivefold improvement in sensitivity for an adult brain, as well as clear improvements in reconstruction accuracy and spatial resolution. However, we also show that such improvements depend critically on accurate forward models; indeed, the reconstruction accuracy of our simulated OPM system only outperformed that of a simulated superconducting system in cases where forward field error was less than 5%. Overall, our results imply that the realisation of a viable whole-head multi-channel OPM system could generate a step change in the utility of MEG as a means to assess brain electrophysiological activity in health and disease. However in practice, this will require both improved hardware and modelling algorithms.

Photonic integrated circuits based on III-V semiconductor polarization-maintaining waveguides were designed and fabricated for the first time for application in a compact cold-atom gravimeter1,2 at an operational wavelength of 780 nm. Compared with optical fiber-based components, semiconductor waveguides achieve very compact guiding of optical signals for both passive functions, such as splitting and recombining, and for active functions, such as switching or modulation. Quantum sensors, which have enhanced sensitivity to a physical parameter as a result of their quantum nature, can be made from quantum gases of ultra-cold atoms. A cloud of ultra-cold atoms may start to exhibit quantum-mechanical properties when it is trapped and cooled using laser cooling in a magneto-optical trap, to reach milli-Kelvin temperatures. The work presented here focuses on the design and fabrication of optical devices for a quantum sensor to measure the acceleration of gravity precisely and accurately. In this case the cloud of ultra-cold atoms consists of rubidium (87Rb) atoms and the sensor exploits the hyperfine structure of the D1 transition, from an outer electronic state of 5 2S ½ to 5 2P3/2 which has an energy of 1.589 eV or 780.241 nm. The short wavelength of operation of the devices dictated stringent requirements on the Molecular Beam Epitaxy (MBE) and device fabrication in terms of anisotropy and smoothness of plasma etch processes, cross-wafer uniformities and alignment tolerances. Initial measurements of the optical loss of the polarization-maintaining waveguide, assuming Fresnel reflection losses only at the facets, suggested a loss of 8 dB cm-1, a loss coefficient, α, of 1.9 (±0.3) cm-1.

We have investigated the geometry-induced magnetoresistance (MR) observed in a high mobility AlGaAs/GaAs electron billiard device. Our billiard is shaped by a surface gate arrangement incorporating a `bridging interconnect' fabrication technique which allows independent control of the cavity's central circular antidot and evolution from a regular square to a nominally chaotic environment in a single device. The low field MR signature of the device displays a marked fractal form with MR structure on a magnetic field scale much finer than that previously reported for generically similar electron-wave billiards.

We determine the one-dimensional periodic potential required to produce an energy band structure in which the effective mass m at the bottom of the first miniband is minimized, and the peak group velocity within the miniband is maximized, subject to the constraint of maintaining a fixed specified energy gap 1 between the first and second bands. This problem is of considerable interest for the design of semiconductor superlattices and optical lattices that exhibit high carrier mobility combined with low interband Zener tunneling. We show that the problem is solved by a class of periodic potentials, known as 1-gap potentials, which, remarkably, support only two distinct energy bands separated by a single energy gap. We use the unique properties of 1-gap potentials to derive semi-analytical formulae that can be used to predict, ab initio, the potential profile required to generate any physically possible value of m or 1. Our results provide a simple, but powerful, band structure engineering tool that should facilitate the design of superlattice structures and optical lattices with optimized transport properties.