journal article·2019-10

High Signal‐to‐Noise Chemical Sensors Based on Compensated Organic Transistor Circuits

Yingli Chu, Hui Li, Jia Huang, Howard E. Katz

Advanced Materials Technologies· Volume 4· Issue 10
Publisher page

Abstract

Abstract Operational stability and sensitivity are key issues for the practical application of organic field‐effect‐transistor (OFET)‐based sensors. Instability over time due to intrinsic device bias stress and conductance drift induced by the ambient environment can obscure responses to analytes of interest. These instabilities are well‐known hindrances to the practical application of OFET sensors. It is demonstrated for the first time that an innovative and simple two‐OFET circuit design can effectively compensate the drifts originating from bias stress and/or the environment while maintaining chemical sensitivity and increasing signal‐to‐noise ratio. This is enabled by illumination of one photosensitive OFET to compensate the drift of the other chemical‐sensing OFET, though in principle a pair of OFETs with opposing drifts generated by any mechanism could be used. The circuit, compared with individual OFET‐based sensors, achieves significantly increased environmental stability, and its enhanced response to chemical vapors is also demonstrated by detecting the representative pollutants nitrogen dioxide (NO2) and ammonia (NH3). This shows that OEFTs with drifts being compensated by any mechanism can lead to stabilized sensor circuits.
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Research context

OpenAlex topics: Analytical Chemistry and Sensors · Conducting polymers and applications · Gas Sensing Nanomaterials and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Materials Science and Engineering Tongji University Shanghai 201804 P. R. China

Department of Materials Science and Engineering Johns Hopkins University Baltimore MD 21218 USA

Funding

National Basic Research Program of China · China Scholarship Council · National Science Foundation

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