Hollow Pt-Functionalized SnO2 Hemipill Network Formation Using a Bacterial Skeleton for the Noninvasive Diagnosis of Diabetes

Hi Gyu Moon, Youngmo Jung, Dukwoo Jun, Ji Hyun Park, Young Wook Chang, Hyung Ho Park, Chong Yun Kang, Chulki Kim, Richard B. Kaner

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


Hollow-structured nanomaterials are presented as an outstanding sensing platform because of their unique combination of high porosity in both the micro- and nanoscale, their biocompatibility, and flexible template applicability. Herein, we introduce a bacterial skeleton method allowing for cost-effective fabrication with nanoscale precision. As a proof-of-concept, we fabricated a hollow SnO2 hemipill network (HSHN) and a hollow Pt-functionalized SnO2 hemipill network (HPN). A superior detecting capability of HPN toward acetone, a diabetes biomarker, was demonstrated at low concentration (200 ppb) under high humidity (RH 80%). The detection limit reaches 3.6 ppb, a level satisfying the minimum requirement for diabetes breath diagnosis. High selectivity of the HPN sensor against C6H6, C7H8, CO, and NO vapors is demonstrated using principal component analysis (PCA), suggesting new applications of HPN for human-activity monitoring and a personal healthcare tool for diagnosing diabetes. The skeleton method can be further employed to mimic nanostructures of biomaterials with unique functionality for broad applications.

Original languageEnglish
Pages (from-to)661-669
Number of pages9
JournalACS Sensors
Issue number3
Publication statusPublished - 2018 Mar 23

Bibliographical note

Funding Information:
This work was partly supported by the KIST Institutional Program (Project No. 2E27270), the Global Top Project funded by the Korea Ministry of Environment (GT-11-F-02-002-1).

Publisher Copyright:
© 2018 American Chemical Society.

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Instrumentation
  • Process Chemistry and Technology
  • Fluid Flow and Transfer Processes


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