Staff directory Ramón García Cortadella

Ramón García Cortadella

Doctoral Student
LA CAIXA SO
ramon.garcia(ELIMINAR)@icn2.cat
Advanced Electronic Materials and Devices

Publications

2020

  • Distortion-Free Sensing of Neural Activity Using Graphene Transistors

    Garcia-Cortadella R., Masvidal-Codina E., De la Cruz J.M., Schäfer N., Schwesig G., Jeschke C., Martinez-Aguilar J., Sanchez-Vives M.V., Villa R., Illa X., Sirota A., Guimerà A., Garrido J.A. Small; 16 (16, 1906640) 2020. 10.1002/smll.201906640. IF: 10.856

    Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented. This accurate description of the input–output relation of the g-SGFETs allows to define the voltage- and frequency-dependent transfer functions, which can be used to correct distortions in the transduced signals. The effect of signal distortion and its subsequent calibration are shown for different types of electrophysiological signals, spanning from large amplitude and low frequency cortical spreading depression events to low amplitude and high frequency action potentials. The thorough description of the distortion mechanisms presented in this article demonstrates that g-SGFETs can be used as distortion-free signal transducers not only for neural sensing, but also for a broader range of applications in which g-SGFET sensors are used. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim


  • Improved metal-graphene contacts for low-noise, high-density microtransistor arrays for neural sensing

    Schaefer N., Garcia-Cortadella R., Calia A.B., Mavredakis N., Illa X., Masvidal-Codina E., Cruz J.D.L., Corro E.D., Rodríguez L., Prats-Alfonso E., Bousquet J., Martínez-Aguilar J., Pérez-Marín A.P., Hébert C., Villa R., Jiménez D., Guimerà-Brunet A., Garrido J.A. Carbon; 161: 647 - 655. 2020. 10.1016/j.carbon.2020.01.066. IF: 7.466

    Poor metal contact interfaces are one of the main limitations preventing unhampered access to the full potential of two-dimensional materials in electronics. Here we present graphene solution-gated field-effect-transistors (gSGFETs) with strongly improved linearity, homogeneity and sensitivity for small sensor sizes, resulting from ultraviolet ozone (UVO) contact treatment. The contribution of channel and contact region to the total device conductivity and flicker noise is explored experimentally and explained with a theoretical model. Finally, in-vitro recordings of flexible microelectrocorticography (μ-ECoG) probes were performed to validate the superior sensitivity of the UVO-treated gSGFET to brain-like activity. These results connote an important step towards the fabrication of high-density gSGFET μ-ECoG arrays with state-of-the-art sensitivity and homogeneity, thus demonstrating the potential of this technology as a versatile platform for the new generation of neural interfaces. © 2020 Elsevier Ltd


  • Low-frequency noise parameter extraction method for single-layer graphene FETs

    Mavredakis N., Wei W., Pallecchi E., Vignaud D., Happy H., Cortadella R.G., Schaefer N., Calia A.B., Garrido J.A., Jimenez D. IEEE Transactions on Electron Devices; 67 (5, 9042866): 2093 - 2099. 2020. 10.1109/TED.2020.2978215. IF: 2.704

    In this article, a detailed parameter extraction methodology is proposed for low-frequency noise (LFN) in single-layer (SL) graphene transistors (GFETs) based on a recently established compact LFN model. The drain current and LFN of two short channel back-gated GFETs (L = 300 and 100 nm) were measured at lower and higher drain voltages, for a wide range of gate voltages covering the region away from charge neutrality point (CNP) up to CNP at p-type operation region. Current-voltage (IV) and LFN data were also available from a long-channel SL top solution-gated (SG) GFET (L = 5 μm), for both p- and n-type regions near and away CNP. At each of these regimes, the appropriate IV and LFN parameters can be accurately extracted. Regarding LFN, mobility fluctuation effect is dominant at CNP, and from there, the Hooge parameter αH can be extracted, whereas the carrier number fluctuation contribution which is responsible for the well-known M-shape bias dependence of output noise divided by squared drain current, also observed in our data, makes possible the extraction of the NT parameter related to the number of traps. In the less possible case of a Λ-shape trend, NT and αH can be extracted simultaneously from the region near CNP. Away from CNP, contact resistance can have a significant contribution to LFN, and from there, the relevant parameter SΔ R2 is defined. The LFN parameters described above can be estimated from the low drain voltage region of operation where the effect of velocity saturation (VS) mechanism is negligible. VS effect results in the reduction of LFN at higher drain voltages, and from there, the IV parameter hΩ which represents the phonon energy and is related to VS effect can be derived both from drain current and LFN data. © 1963-2012 IEEE.


  • Multiplexed neural sensor array of graphene solution-gated field-effect transistors

    Schaefer N., Garcia-Cortadella R., Martínez-Aguilar J., Schwesig G., Illa X., Moya Lara A., Santiago S., Hébert C., Guirado G., Villa R., Sirota A., Guimerà-Brunet A., Garrido J.A. 2D Materials; 7 (2, 025046) 2020. 10.1088/2053-1583/ab7976. IF: 7.343

    Electrocorticography (ECoG) is a well-established technique to monitor electrophysiological activity from the surface of the brain and has proved crucial for the current generation of neural prostheses and brain-computer interfaces. However, existing ECoG technologies still fail to provide the resolution necessary to accurately map highly localized activity across large brain areas, due to the rapidly increasing size of connector footprint with sensor count. This work demonstrates the use of a flexible array of graphene solution-gated field-effect transistors (gSGFET), exploring the concept of multiplexed readout using an external switching matrix. This approach does not only allow for an increased sensor count, but due to the use of active sensing devices (i.e. transistors) over microelectrodes it makes additional buffer transistors redundant, which drastically eases the complexity of device fabrication on flexible substrates. The presented results pave the way for upscaling the gSGFET technology towards large-scale, high-density μECoG-arrays, eventually capable of resolving neural activity down to a single neuron level, while simultaneously mapping large brain regions. © 2020 IOP Publishing Ltd.


  • Switchless multiplexing of graphene active sensor arrays for brain mapping

    Garcia-Cortadella R., Schäfer N., Cisneros-Fernandez J., Ré L., Illa X., Schwesig G., Moya A., Santiago S., Guirado G., Villa R., Sirota A., Serra-Graells F., Garrido J.A., Guimerà-Brunet A. Nano Letters; 20 (5): 3528 - 3537. 2020. 10.1021/acs.nanolett.0c00467. IF: 12.279

    Sensor arrays used to detect electrophysiological signals from the brain are paramount in neuroscience. However, the number of sensors that can be interfaced with macroscopic data acquisition systems currently limits their bandwidth. This bottleneck originates in the fact that, typically, sensors are addressed individually, requiring a connection for each of them. Herein, we present the concept of frequency-division multiplexing (FDM) of neural signals by graphene sensors. We demonstrate the high performance of graphene transistors as mixers to perform amplitude modulation (AM) of neural signals in situ, which is used to transmit multiple signals through a shared metal line. This technology eliminates the need for switches, remarkably simplifying the technical complexity of state-of-the-art multiplexed neural probes. Besides, the scalability of FDM graphene neural probes has been thoroughly evaluated and their sensitivity demonstrated in vivo. Using this technology, we envision a new generation of high-count conformal neural probes for high bandwidth brain machine interfaces. © 2020 American Chemical Society.


2019

  • High-resolution mapping of infraslow cortical brain activity enabled by graphene microtransistors

    Masvidal-Codina E., Illa X., Dasilva M., Calia A.B., Dragojević T., Vidal-Rosas E.E., Prats-Alfonso E., Martínez-Aguilar J., De la Cruz J.M., Garcia-Cortadella R., Godignon P., Rius G., Camassa A., Del Corro E., Bousquet J., Hébert C., Durduran T., Villa R., Sanchez-Vives M.V., Garrido J.A., Guimerà-Brunet A. Nature Materials; 18 (3): 280 - 288. 2019. 10.1038/s41563-018-0249-4. IF: 38.887

    Recording infraslow brain signals (<0.1 Hz) with microelectrodes is severely hampered by current microelectrode materials, primarily due to limitations resulting from voltage drift and high electrode impedance. Hence, most recording systems include high-pass filters that solve saturation issues but come hand in hand with loss of physiological and pathological information. In this work, we use flexible epicortical and intracortical arrays of graphene solution-gated field-effect transistors (gSGFETs) to map cortical spreading depression in rats and demonstrate that gSGFETs are able to record, with high fidelity, infraslow signals together with signals in the typical local field potential bandwidth. The wide recording bandwidth results from the direct field-effect coupling of the active transistor, in contrast to standard passive electrodes, as well as from the electrochemical inertness of graphene. Taking advantage of such functionality, we envision broad applications of gSGFET technology for monitoring infraslow brain activity both in research and in the clinic. © 2018, The Author(s), under exclusive licence to Springer Nature Limited.


2018

  • Flexible Graphene Solution-Gated Field-Effect Transistors: Efficient Transducers for Micro-Electrocorticography

    Hébert C., Masvidal-Codina E., Suarez-Perez A., Calia A.B., Piret G., Garcia-Cortadella R., Illa X., Del Corro Garcia E., De la Cruz Sanchez J.M., Casals D.V., Prats-Alfonso E., Bousquet J., Godignon P., Yvert B., Villa R., Sanchez-Vives M.V., Guimerà-Brunet A., Garrido J.A. Advanced Functional Materials; 28 (12, 1703976) 2018. 10.1002/adfm.201703976. IF: 13.325

    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 fulfill 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, it is reported here that this technology is suitable for μ-ECoG recordings through 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. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim


  • Understanding the bias dependence of low frequency noise in single layer graphene FETs

    Mavredakis N., Garcia Cortadella R., Bonaccini Calia A., Garrido J.A., Jiménez D. Nanoscale; 10 (31): 14947 - 14956. 2018. 10.1039/c8nr04939d. IF: 7.233

    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. © The Royal Society of Chemistry.


2017

  • Frequency response of electrolyte-gated graphene electrodes and transistors

    Drieschner S., Guimerà A., Cortadella R.G., Viana D., Makrygiannis E., Blaschke B.M., Vieten J., Garrido J.A. Journal of Physics D: Applied Physics; 50 (9, 095304) 2017. 10.1088/1361-6463/aa5443. IF: 2.588

    The interface between graphene and aqueous electrolytes is of high importance for applications of graphene in the field of biosensors and bioelectronics. The graphene/electrolyte interface is governed by the low density of states of graphene that limits the capacitance near the Dirac point in graphene and the sheet resistance. While several reports have focused on studying the capacitance of graphene as a function of the gate voltage, the frequency response of graphene electrodes and electrolyte-gated transistors has not been discussed so far. Here, we report on the impedance characterization of single layer graphene electrodes and transistors, showing that due to the relatively high sheet resistance of graphene, the frequency response is governed by the distribution of resistive and capacitive circuit elements along the graphene/electrolyte interface. Based on an analytical solution for the impedance of the distributed circuit elements, we model the graphene/electrolyte interface both for the electrode and the transistor configurations. Using this model, we can extract the relevant material and device parameters such as the voltage-dependent intrinsic sheet and series resistances as well as the interfacial capacitance. The model also provides information about the frequency threshold of electrolyte-gated graphene transistors, above which the device exhibits a non-resistive response, offering an important insight into the suitable frequency range of operation of electrolyte-gated graphene devices. © 2017 IOP Publishing Ltd.