Wang Hui, Ramnani Pankaj, Pham Tung, Villarreal Claudia Chaves, Yu Xuejun, Liu Gang, Mulchandani Ashok
Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education and Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture China Agricultural University, Beijing, China.
State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Front Chem. 2020 May 12;8:362. doi: 10.3389/fchem.2020.00362. eCollection 2020.
Porphyrins, with or without metal ions (MPs), have been explored and applied in optical and electrochemical sensor fields owing to their special physicochemical properties. The presence of four nitrogen atoms at the centers of porphyrins means that porphyrins chelate most metal ions, which changes the binding ability of MPs with gas molecules via non-specific binding. In this article, we report hybrid chemiresistor sensor arrays based on single-walled carbon nanotubes (SWNTs) non-covalently functionalized with six different MPs using the solvent casting technique. The characteristics of MP-SWNTs were investigated through various optical and electrochemical methods, including UV spectroscopy, Raman, atomic force microscopy, current-voltage (I-V), and field-effect transistor (FET) measurement. The proposed sensor arrays were employed to monitor the four VOCs (tetradecene, linalool, phenylacetaldehyde, and ethylhexanol) emitted by citrus trees infected with Huanglongbing (HLB), of which the contents changed dramatically at the asymptomatic stage. The sensitivity to VOCs could change significantly, exceeding the lower limits of the SWNT-based sensors. For qualitative and quantitative analysis of the four VOCs, the data collected by the sensor arrays were processed using different regression models including partial least squares (PLS) and an artificial neural network (ANN), which further offered a diagnostic basis for Huanglongbing disease at the asymptomatic stage.
卟啉,无论有无金属离子(金属卟啉),因其特殊的物理化学性质,已在光学和电化学传感器领域得到探索和应用。卟啉中心存在四个氮原子,这意味着卟啉能螯合大多数金属离子,进而通过非特异性结合改变金属卟啉与气体分子的结合能力。在本文中,我们报道了基于单壁碳纳米管(SWNTs)的混合化学电阻传感器阵列,该阵列通过溶剂浇铸技术用六种不同的金属卟啉进行非共价功能化。通过各种光学和电化学方法研究了金属卟啉 - 单壁碳纳米管的特性,包括紫外光谱、拉曼光谱、原子力显微镜、电流 - 电压(I - V)和场效应晶体管(FET)测量。所提出的传感器阵列用于监测感染黄龙病(HLB)的柑橘树释放的四种挥发性有机化合物(十四碳烯、芳樟醇、苯乙醛和乙基己醇),其中这些化合物的含量在无症状阶段会发生显著变化。对挥发性有机化合物的灵敏度可能会发生显著变化,超过基于单壁碳纳米管的传感器的下限。为了对这四种挥发性有机化合物进行定性和定量分析,使用包括偏最小二乘法(PLS)和人工神经网络(ANN)在内的不同回归模型对传感器阵列收集的数据进行处理,这进一步为无症状阶段的黄龙病提供了诊断依据。