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Dual-sensitized hollow SnO2 nanospheres with rGO and Pd for highly sensitive detection of acetone in exhaled breath

  • Arunkumar Shanmugasundaram
  • , Kun Woo Baek
  • , Changung Paeng
  • , Longlong Li
  • , Goeun Cha
  • , Jonghyeon Woo
  • , Dong Su Kim
  • , Changyong Yim
  • , Jongsung Park
  • , Jung Sang Cho
  • , Dong Weon Lee
  • Chonnam National University
  • Chungbuk National University (CNU)
  • Kyungpook National University
  • Chungbuk National University Hospital
  • Chungbuk National University

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Detecting acetone in human breath is crucial for the early diagnosis of metabolic disorders such as diabetes. Metal oxide semiconductor (MOS) based acetone breath sensors have received considerable attention due to their compactness and noninvasive nature. However, their limited sensitivity and interference from humidity present challenges in selectively detecting acetone. Herein, we propose sensors based on tin oxide hollow spheres dual-sensitized with reduced graphene oxide and ultrafine palladium nanoparticles (rGO-Sn-HS-Pd) for enhanced and selective detection of acetone. The Sn-HS are synthesized using a spray pyrolysis technique, followed by a hydrothermal process to achieve the rGO-Pd-NPs dual-sensitized SnO2 hollow spheres. The rGO-Sn-HS-Pd sensor demonstrate high sensitivity to acetone, exceptional selectivity, and fast response/ recovery. Furthermore, by utilizing a linear fitting approach on the experimental response data for acetone concentrations, it is estimated that the rGO2-Sn-HS-Pd2 sensor can detect acetone as low as 220 ppb. The optimized rGO2-Sn-HS-Pd2 sensor demonstrates performance that is 7.35, 5.38, 3.87, 4.57, 1.27, and 1.15 times higher compared to the bare Sn-HS, rGO1-Sn-HS, rGO2-Sn-HS, rGO3-Sn-HS, rGO2-Sn-HS-Pd1, and rGO2-Sn-HS-Pd3 sensors. Sensor arrays incorporating rGO2-Sn-HS-Pd2 can distinguish breath patterns between healthy and simulated diabetic breath through principal component analysis, presenting a promising avenue for noninvasive diabetes screening and monitoring.

Original languageEnglish
Article number162959
JournalApplied Surface Science
Volume696
DOIs
StatePublished - 1 Jul 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Acetone sensor
  • Exhaled breath analysis
  • Pd catalysts
  • Reduced graphene oxide
  • SnO hollow spheres

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