3.8 Proceedings Paper

Fast Vapor Detection by a Micropillar Array integrated Colorimetric Sensor

Journal

2022 IEEE SENSORS
Volume -, Issue -, Pages -

Publisher

IEEE
DOI: 10.1109/SENSORS52175.2022.10015718

Keywords

micropillar array; vapor sensing; volatile analytes; colorimetric sensor

Funding

  1. NASA [AS-0280-0]
  2. Australian National Fabrication Facility (ANFF) [AS-0280-0]
  3. Australian Academy of Science Regional Collaborations Programme
  4. infrastructure at the South Australia Node of ANFF (ANFF-SA)

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This paper reports an optofluidic sensor for rapid detection of gas-phase analytes towards wearable colorimetric sensing. The sensor consists of a metal-insulator-metal thin-film structure integrated with a quartz micropillar array to improve the delivery of vapor analytes onto the sensing surface. Experimental results demonstrate that the micropillar array significantly reduces the sensor response time compared with conventional chamber experiments. The concentration-dependent response of the sensor confirms its potential for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples.
An optofluidic sensor for rapid detection of gasphase analytes from a flowing micro-volume fluid sample towards wearable colorimetric sensing is reported. The sensor is comprised of a metal-insulator-metal (MIM) thin-film structure integrated with a quartz micropillar array for improved delivery of vapor analytes onto the sensing surface. For our proof-ofprinciple demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated its response to ethanol vapors that were delivered in close proximity to the sensing material via the micropillar array. It is demonstrated that the micropillar array reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response also confirms its potential for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples.

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