FET-based integrated charge sensor for organ-on-chip applications
| Autor: | Hande Aydogmus, Massimo Mastrangeli, Pasqualina M. Sarro, M. Dostanic, Rajarshi Sinha, Mojtaba Jahangiri, W. F. Quiros-Solano |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Materials science
business.industry Capacitive sensing 010401 analytical chemistry 01 natural sciences 0104 chemical sciences Electrochemical gas sensor Threshold voltage 03 medical and health sciences Microelectrode 0302 clinical medicine Logic gate Electrode Optoelectronics Field-effect transistor business 030217 neurology & neurosurgery Microfabrication |
| Zdroj: | IEEE Sensors, SENSORS 2020-Conference Proceedings |
| ISSN: | 1930-0395 |
| Popis: | We present an extremely compact field effect transistor (FET)-based electrochemical sensor for in situ real-time and label-free measurement of ion concentrations in the cell culture area of organs-on-chip (OoCs) devices. This sensor replaces the functionality of an external reference electrode, crucial in standard electrochemical sensing, by controlling the FET threshold voltage via a capacitive control gate. The silicon- and polymer-based charge sensor can be integrated in OoC platforms by means of a wafer-scale and CMOS-compatible microfabrication process. This fabrication approach inherently allows a superior level of accuracy, repeatability and scalability compared to common OoC manufacturing methods. The sensor combines in a single device the complementary benefits of silicon-based electronics and of flexible polymer membranes with integrated microelectrodes – congenial substrates to sustain dynamic stimuli and mimic physiological tissue microenvironments. The integration of the polymer membrane in the sensing region makes this miniature sensor a preferable option for high sensitivity biochemical measurements in OoC applications, including monitoring the pH of cell culture media and of tissue culturing microenvironments, quantification of ion displacement in cells, and complementary research on disease modeling. |
| Databáze: | OpenAIRE |
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