Electrochemically Gated Graphene Field-Effect Transistor for Extracellular Cell Signal Recording
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This work presents an experimental characterization of electrochemically gated graphene field-effect transistors (EGFETs) to measure extracellular cell signals. The performance of the EGFETs was evaluated using cardiomyocytes cells. Extracellular signals with a peak value of 0.4 pico-amperes (pA) embedded in a noise level of 0.1 pA were recorded. Signals in current mode were compared with signals recorded as a voltage. Signals below 28 µV of magnitude can be detected in a noise floor of 7 µV with a signal-to-noise ratio of 4.
KeywordsGraphene Field effect transistor Extra-cellular cell signal recording
Bioelectronic devices fabricated with emergent materials are currently being developed to establish electrical interfaces with living cells and tissues. The aim is to develop transducers that can record extracellular signals in complex biological environments [1, 2, 3, 4, 5, 6, 7, 8, 9]. In contrast with conventional semiconductors such as silicon some of these materials can be deposited into flexible, conformable and biocompatible substrates. Graphene deposited in thin layers is particular interesting for implantable biomedical devices because it offers a high electronic performance combined with biocompatibility and processing on a variety of flexible substrates [10, 11, 12, 13, 14].
The recent efforts in improving the fabrication of thin-layers of graphene have made possible to fabricate bioelectronic sensors know as electrochemically-gated field effect transistor (EGFETs). Although, these are field effect devices, unlike conventional transistors do not have a built-in dielectric layer. The gate dielectric is established when the device is immersed into the electrolyte solution. This occurs because when conductive or semiconductive materials are immersed into electrolytes a Helmholtz capacitive double-layer is established at the material/electrolyte interface. This type of device has been used to record extracellular electrophysiological signals from cells [15, 16].
In this paper, we show that a field effect transistor based in electrochemically graphene gate can be used for extracellular signal recording. The aim is to demonstrate the detection limit of these sensing devices. The performance of the EGFETs was evaluated using contractile cells (cardiomyocytes).
This paper is organized as follows: first the measuring system is presented. Then the basic working principle of EGFETs is explained, including the fabrication and characterization. Finally, extracellular signals recorded in current as well as in voltage mode are presented and discussed.
2 Technological Innovation for Cyber-Physical Systems
Brain-related illnesses affect more than two billion people worldwide. Advances in treatments for brain disorders have to date relied largely upon a pharmaceutical approach, however the development of drugs, which do not have intolerable side effects, is becoming extremely complex and difficult. It is now believed that an electronic engineering-driven approach is needed, to develop solutions based on electrical signals. This is supported by a number of progresses in electronic transducers working as prosthetic and electroceutical devices. These are devices that aim to establish an electrical and chemical bidirectional communication interface with cells and tissues. These devices measure the signals so that researchers can develop a ‘dictionary’ of patterns associated with health and disease states. Once the signals are decoded, devices can also generate the correct signal patterns to modulate the neural impulses controlling the body, repair lost function and restore health. Field effect transistors based on graphene reported in this contribution are an interesting approach towards the development of these implantable brain-machine interfaces.
3.1 CVD Growth and Graphene Field Effect Transistor Fabrication and Mouse Embryonic Stem Cells ESC Differentiation
Mouse embryonic stem cells (ESC) differentiated into cardiomyocytes were used. ESC differentiation was performed using the hanging-drop method in medium containing 20 % of fetal bovine serum without Leukemia inhibitory factor (LIF) supplementation (differentiation medium). Briefly, 1000 cells were cultured in 20 µl hanging drops of differentiation medium for 48 h to initiate embryonic bodies (EB) formation. Next, EB were grown in differentiation medium in suspension, for 3 days, in a bacterial petri dish before being transferred to the devices (0.1 %) to allow cell attachment and further differentiation. Cells were kept alive for two days by changing half of the medium every 24 h. The sensing devices with cells were maintained at 37°C in an incubator (HERACell®150) with a humidified atmosphere with 5 % of CO2. A photograph showing the cells on top of a recording device is shown in Fig. 2b.
All electrical measurements were performed with a Stanford low-noise current amplifier (SRS 570) or alternatively in voltage mode using a voltage amplifier (SRS 560) connected to a dynamic signal analyser (Agilent 35670A).
3.2 Interfacing of Cells with Graphene Based EGFETs
4 Results and Discussion
This paper reports on the use of a graphene based EGFET to record signals from contractile cells. During electrical measurements the transistor was not biased. In this operation mode the device is working as a simple microelectrode system. This strategy minimizes the electrical noise and the risk of electrochemical reactions. It allows us to explore the detection limits of this type of device. The noise level in current is below 1 pA and in current is below 10 µV. The signal-to noise ratio is approximately 5. This compares very well with the performance of current available microelectrode array technology to measure extracellular signals.
The measured signals are very weak. For contractile cells we would expect a much stronger signals. Among the possible reasons for these faint signals is a bad electrical coupling between the cells and the device. Clusters of cardiomyocytes do not adhere to the device surface. It is well possible that they float above the sensing surface.
- 3.Kotov, N.A., Winter, J.O., Clements, I.P., Jan, E., Timko, B.P., Campidelli, S., Pathak, S., Mazzatenta, A., Lieber, C.M., Prato, M., Bellamkonda, R.V., Silva, G.A., Kam, N.W.S., Patolsky, F., Ballerini, L.: Nanomaterials for neural interfaces. Adv. Mater. 21(40), 3970–4004 (2009)CrossRefGoogle Scholar
- 7.Pui, T.-S., Agarwal, A., Ye, F., Balasubramanian, N., Chen, P.S., Eschermann, J.F., Stockmann, R., Hueske, M., Vu, X.T., Ingebrandt, S., Offenhäusser, A.: CMOS-compatible nanowire sensor arrays for detection of cellular bioelectricity. Appl. Phys. Lett. 95, 083703-1–083703-3 (2009)Google Scholar
- 11.Anteroinen, J., Kim, W., Stadius, K., Riikonen, J., Lipsanen, H., Ryynanen, J.: Extraction of graphene-titanium contact resistances using transfer length measurement and a curve-fit method. World Acad. Sci. Eng. Technol. 6, 08–25 (2012) Google Scholar