4.8 Article

Graphene quantum dot-functionalized three-dimensional ordered mesoporous ZnO for acetone detection toward diagnosis of diabetes

Journal

NANOSCALE
Volume 11, Issue 24, Pages 11496-11504

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c9nr00942f

Keywords

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Funding

  1. National Key Research and Development Program [2016YFC0207101]
  2. National Natural Science Foundation of China [61874049, 11874181, 61775080, 11674126, 11674127, 61674067]
  3. Special Project of the Province-University Co-constructing Program of Jilin Province [SXGJXX2017-3]
  4. Jilin Province Natural Science Foundation of China [20180101210JC, 20170101170JC]
  5. Jilin Province Science Fund for Excellent Young Scholars [20170520129JH, 20170520111JH]

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The development of a high-performance semiconductor oxide sensor for the accurate detection of trace disease biomarkers in exhaled breath is still a challenge that urgently needs to be addressed. Here, we proposed a self-assembly strategy and spin-coating process to create a graphene quantum dot (GQD)-functionalized three-dimensional ordered macroporous (3DOM) ZnO structure. The strong synergistic effect and the p-n heterojunction between the p-type GQDs and n-type ZnO effectively enlarged the resistance variation due to the change in oxygen adsorption. The specific 3DOM structure induced a hierarchical pore size (286 nm in macroscale and 26 nm in mesoscale) and 3D interconnection, which guaranteed high gas accessibility and fast carrier transportation. As a result, the GQD-modified 3DOM ZnO sensor exhibited a remarkably high response (R-air/R-gas = 15.2 for 1 ppm acetone), rapid response/recovery time (9/16 s), extremely low theoretical detection limit (8.7 ppb), and good selectivity towards acetone against other interfering gases. In particular, the proposed sensor could accurately distinguish trace acetone in the simulated breath of diabetic patients. These results demonstrate a high potential for the feasibility of the GQD-modified 3DOM SMO structure as a new sensing material for the possibility of noninvasive real-time diagnosis of diabetes.

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