Quantitatively Discriminating Alcohol Molecules by Thermally Modulating NiO-Based Sensor Arrays

Meng Li, Hongyu Liu, Junqing Chang, Tiantian Dai, Kazuki Nagashima, Zanhong Deng, Takeshi Yanagida, Xiaodong Fang, Gang Meng

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Although temperature modulation of a single (nonselective) semiconductor gas sensor has demonstrated its great capability on discriminating gas molecules, quantitative analysis of the type and concentration of structurally similar volatile organic compounds (VOCs) molecules remains a significant challenge. In this work, as an alternative to a single oxide sensor, sensor arrays composed of four types of NiO-based sensor synchronously perform thermal modulation with a unique programmed cooling temperature profile. Apart from improved category discrimination by using entire sensor arrays, the peak temperature of the temperature profile plays an important role in distinguishing the concentration difference induced by subtle variations of the electrical responses. A high peak temperature of ≈300 °C facilitates concentration discrimination (with an accuracy ratio of 85.9%). This work highlights the importance of the peak temperature in (simultaneous) quantitative analysis of the types and concentrations of VOCs molecules with similar properties.

Original languageEnglish
Article number2100762
JournalAdvanced Materials Technologies
Issue number3
Publication statusPublished - Mar 2022

All Science Journal Classification (ASJC) codes

  • General Materials Science
  • Mechanics of Materials
  • Industrial and Manufacturing Engineering


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