High-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors. Nature Materials, (2019). 18.

Brain-computer interfaces and neural prostheses based on the detection of electrocorticography (ECoG) signals are rapidly growing fields of research. Several technologies are currently competing to be the first to reach the market; however, none of them fulfil yet all the requirements of the ideal interface with neurons. Thanks to its biocompatibility, low dimensionality, mechanical flexibility and electronic properties, graphene is one of the most promising material candidates for neural interfacing. After discussing the operation of graphene solution-gated field-effect transistors (SGFET) and characterizing their performance in saline solution, we report here that this technology is suitable for μ-ECoG recordings through the studies of spontaneous slow wave activity, sensory evoked responses on the visual and auditory cortices, and synchronous activity in a rat model of epilepsy. An in depth comparison of the signal-to-noise ratio of graphene SGFETs with that of platinum black electrodes confirms that graphene SGFET technology is approaching the performance of state-of-the art neural technologies.

This letter investigates the bias-dependent low frequency noise of single layer graphene field-effect transistors. Noise measurements have been conducted with electrolyte-gated graphene transistors covering a wide range of gate and drain bias conditions for different channel lengths. A new analytical model that accounts for the propagation of the local noise sources in the channel to the terminal currents and voltages is proposed in this paper to investigate the noise bias dependence. Carrier number and mobility fluctuations are considered as the main causes of low frequency noise and the way these mechanisms contribute to the bias dependence of the noise is analyzed in this work. Typically, normalized low frequency noise in graphene devices has been usually shown to follow an M-shape dependence versus gate voltage with the minimum near the charge neutrality point (CNP). Our work reveals for the first time the strong correlation between this gate dependence and the residual charge which is relevant in the vicinity of this specific bias point. We discuss how charge inhomogeneity in the graphene channel at higher drain voltages can contribute to low frequency noise; thus, channel regions nearby the source and drain terminals are found to dominate the total noise for gate biases close to the CNP. The excellent agreement between the experimental data and the predictions of the analytical model at all bias conditions confirms that the two fundamental 1/f noise mechanisms, carrier number and mobility fluctuations, must be considered simultaneously to properly understand the low frequency noise in graphene FETs. The proposed analytical compact model can be easily implemented and integrated in circuit simulators, which can be of high importance for graphene based circuits' design.

Mapping the entire frequency bandwidth of brain electrophysiological signals is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously DC-shifts, infraslow oscillations (<0.1Hz), typical LFP signals (0.1-80 Hz) and higher frequencies (80-600 Hz) using the same recording site would particularly benefit preclinical epilepsy research and could provide clinical biomarkers for improved seizure onset zone delineation. However, commonly used metal microelectrode technology suffers from instabilities that hamper the high-fidelity of DC-coupled recordings, which are needed to access signals of very low frequency. Here, we use flexible graphene depth neural probes (gDNP), consisting of a linear array of graphene microtransistors, to concurrently record DC-shifts and high frequency neuronal activity in awake rodents. We show that gDNPs can reliably record and map with high spatial resolution seizures, pre-ictal DC-shifts and seizure associated spreading depolarizations together with higher frequencies through the cortical laminae to the hippocampus in a mouse model of chemically-induced seizures. Moreover, we demonstrate functionality of chronically implanted devices over 10 weeks by recording with high fidelity spontaneous spike-wave discharges and associated infraslow oscillations in a rat model of absence epilepsy. Altogether, our work highlights the suitability of this technology for in vivo electrophysiology research, and in particular epilepsy research, by allowing stable and chronic DC-coupled recordings.

Graphene solution-gated field-effect transistors (SGFETs) are a promising platform for the recording of cell action potentials due to the intrinsic high signal amplification of graphene transistors. In addition, graphene technology fulfills important key requirements for for in-vivo applications, such as biocompability, mechanical flexibility, as well as ease of high density integration. In this paper we demonstrate the fabrication of flexible arrays of graphene SGFETs on polyimide, a biocompatible polymeric substrate. We investigate the transistor's transconductance and intrinsic electronic noise which are key parameters for the device sensitivity, confirming that the obtained values are comparable to those of rigid graphene SGFETs. Furthermore, we show that the devices do not degrade during repeated bending and the transconductance, governed by the electronic properties of graphene, is unaffected by bending. After cell culture, we demonstrate the recording of cell action potentials from cardiomyocyte-like cells with a high signal-to-noise ratio that is higher or comparable to competing state of the art technologies. Our results highlight the great capabilities of flexible graphene SGFETs in bioelectronics, providing a solid foundation for in-vivo experiments and, eventually, for graphene-based neuroprosthetics.

Graphene devices for analog and RF applications are prone to Low Frequency Noise (LFN) due to its upconversion to undesired phase noise at higher frequencies. Such applications demand the use of short channel graphene transistors that operate at high electric fields in order to ensure a high speed. Electric field is inversely proportional to device length and proportional to channel potential so it gets maximized as the drain voltage increases and the transistor's length shrinks. Under these conditions though, short channel effects like Velocity Saturation (VS) should be taken into account. Carrier number and mobility fluctuations have been proved to be the main sources that generate LFN in graphene devices. While their contribution to the bias dependence of LFN in long channels has been thoroughly investigated, the way in which VS phenomenon affects LFN in short channel devices under high drain voltage conditions has not been well understood. At low electric field operation, VS effect is negligible since carriers' velocity is far away from being saturated. Under these conditions, LFN can be precicely predicted by a recently established physics-based analytical model. The present paper goes a step furher and proposes a new model which deals with the contribution of VS effect on LFN under high electric field conditions. The implemented model is validated with novel experimental data, published for the first time, from CVD grown back-gated single layer graphene transistors operating at gigahertz frequencies. The model accurately captures the reduction of LFN especially near charge neutrality point because of the effect of VS mechanism. Moreover, an analytical expression for the effect of contact resistance on LFN is derived. This contact resistance contribution is experimentally shown to be dominant at higher gate voltages and is accurately described by the proposed model.

Organic electrochemical transistors (OECTs) from poly(3,4-ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS) are used as amplifying transducers for bioelectronics. Although the impact on performance of device geometry parameters such as channel area and thickness has been widely explored, the overlap between the semiconductor film and the source and drain contacts has not been considered. Here we vary this overlap and explore its impact on transconductance and noise. We show that increasing contact overlap does not alter the magnitude of the steady-state transconductance but it does decreases the cut-off frequency. Noise was found to be independent of contact overlap and to vary according to the charge noise model. The results show that high-quality contacts can be established in PEDOT:PSS OECTs with minimal overlap.

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