Bordbar Mohammad Mahdi, Tashkhourian Javad, Hemmateenejad Bahram
Department of Chemistry, Shiraz University, 719468 Shiraz, Iran.
ACS Appl Mater Interfaces. 2022 Feb 16;14(6):8333-8342. doi: 10.1021/acsami.1c24194. Epub 2022 Feb 3.
A paper-based optical nose was fabricated by dropping bimetallic silver and gold nanoparticles on a paper substrate. The nanoparticles were synthesized by both natural (lemon, pomegranate, and orange juices) and chemical (citrate, gallic acid, and ascorbic acid) reducing agents. The performance of the assay was evaluated for identifying gasoline and five ignitable liquids such as diesel, ethanol, methanol, kerosene, and thinner. The interaction of the sensor with sample vapors caused aggregation, consequently changing the color of nanoparticles. The color changes, which were captured by a scanner, represented a specified colorimetric map for each analyte, allowing one to identify the studied fuels. The visual results were confirmed using multivariate statistical analysis such as principal component analysis and hierarchical clustering analysis. Also, partial least-squares regression was used to assist the proposed assay for estimating the amount of studied ignitable liquids as counterfeit species in the gasoline sample. The root-mean-square errors for prediction were 3.4, 2.1, 1.9, 2.0, and 1.7% for diesel, thinner, kerosene, ethanol, and methanol, respectively. Finally, the fabricated sensor indicated high efficiency for the on-site detection of pure industrial gasoline samples from adulterated ones.
通过将双金属银和金纳米颗粒滴在纸质基底上制备了一种基于纸张的光学鼻。纳米颗粒由天然（柠檬汁、石榴汁和橙汁）和化学（柠檬酸盐、没食子酸和抗坏血酸）还原剂合成。评估了该检测方法用于识别汽油和柴油、乙醇、甲醇、煤油和稀释剂这五种可燃液体的性能。传感器与样品蒸汽的相互作用导致聚集，从而改变了纳米颗粒的颜色。由扫描仪捕获的颜色变化代表了每种分析物的特定比色图，使人们能够识别所研究的燃料。使用主成分分析和层次聚类分析等多元统计分析方法对视觉结果进行了验证。此外，还使用偏最小二乘回归来辅助所提出的检测方法，以估计汽油样品中作为假冒成分的所研究可燃液体的含量。柴油、稀释剂、煤油、乙醇和甲醇预测的均方根误差分别为3.4%、2.1%、1.9%、2.0%和1.7%。最后，所制备的传感器在现场检测纯工业汽油样品与掺假汽油样品方面显示出高效性。
