Toward Point-of-Care chronic disease Management: Biomarker detection in exhaled breath using an E-Nose sensor based on rGO/SnO2 superstructures

CHEMICAL ENGINEERING JOURNAL(2022)

引用 21|浏览0
暂无评分
摘要
Detecting specific biomarkers in human breath is essential for diagnosing various diseases, including lung cancer, asthma, and halitosis. Formaldehyde (HCHO) is a vital biomarker found in the exhaled breath of lung cancer patients. The threshold concentration of HCHO in lung cancer patients is 83 parts per billion (ppb), as opposed to 48 ppb in healthy people. Over the years, several semiconductor metal oxide (SMO)-based gas sensors have been proposed to detect HCHO. However, the detection of HCHO at ppb levels in complex environments at relatively low operating temperatures remains challenging. In this paper, we have discussed a high-performance HCHO sensor that employs three-dimensional (3D) reduced graphene oxide-incorporated SnO2 nanosphere superstructural architectures (rGO-SnO2-SS). The proposed sensor exhibited excellent sensitivity (as low as 100 ppb with a detection limit of 10 ppb at 125 degrees C). The rGO-SnO2-SS sensor exhibited a 4.15-fold, 3.59-fold, 1.44-fold and 2.58-fold increase in sensing response compared to the bare SnO2-nanospheres (SnO2-NS), rGO-SnO2 tiny superstructures (rGO-SnO2-TSS), rGO-SnO2 partial superstructures (rGO-SnO2-PSS) and rGO-SnO2 nanocomposite (rGO-SnO2-NC) sensors. An evaluation of the ability of the proposed sensor to diagnose lung cancer by detecting HCHO in exhaled breath revealed that in the rGO-SnO2-SS hybrid nanocomposite-based e-nose sensor arrays, the signals from healthy and simulated lung cancer breaths did not overlap, i.e., healthy, and unhealthy breaths, could be differentiated with pinpoint accuracy. Thus, the proposed sensor based on rGO-SnO2-SS can be effectively used to easily screen lung cancer patients and monitor indoor HCHO concentrations.
更多
查看译文
关键词
Superstructural architectures,Nanocomposites,HCHO,Breath sensing,Excellent sensitivity,Selectivity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要