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IJAT Vol.12 No.1 pp. 52-63
doi: 10.20965/ijat.2018.p0052
(2018)

Paper:

Bioanalytical Method Based on Extended-Gate Field-Effect Transistor Modified by Self-Assembled Monolayer

Taira Kajisa*,† and Toshiya Sakata**

*PROVIGATE Inc.
The University of Tokyo Entrepreneur Plaza, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan

Corresponding author

**Department of Material Engineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

Received:
June 9, 2017
Accepted:
November 23, 2017
Published:
January 5, 2018
Keywords:
field-effect transistor, self-assembled monolayer, extended-gate
Abstract

In this paper, we introduce semiconductor biosensors for detecting or monitoring various biological substances and for surface chemical technologies tailored to target molecules. To fabricate the semiconductor biosensor best suited to the target biomolecules, the gate electrodes for extended-gate type field-effect transistors (EGFETs), which are separated from semiconductor part, must be constructed by interfacial chemical modification. First, ion-sensitive EGFET was developed by self-assembled monolayer (SAM) modification on gold gate electrode. Polar functional-group-terminated alkanethiol SAM-coated-gate FET showed pH dependency. In particular, carboxy-terminated alkanethiol SAM-coated gate FET showed higher sensitivities from 42 to 56 mV/pH, which was close to the Nernstian response, in a wide range of biological environments. By using the ion-sensitive EGFET, the hydroxyapatite biomineralization process was successfully monitored by increasing the gate surface potential. Furthermore, saccharides were quantified using EGFET by changing the functional group of SAM, with phenylboronic acid as a functional molecule. In conclusion, target-specific surface modification on gate electrodes makes it possible for semiconductor devices to be applied as biosensors.

Cite this article as:
T. Kajisa and T. Sakata, “Bioanalytical Method Based on Extended-Gate Field-Effect Transistor Modified by Self-Assembled Monolayer,” Int. J. Automation Technol., Vol.12, No.1, pp. 52-63, 2018.
Data files:
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