Electrochemical Detection of Trace Arsenic(III) by Nanocomposite of Nanorod-Like α-MnO2Decorated with ∼5 nm Au Nanoparticles: Considering the Change of Arsenic Speciation.
It has been reported that the majority of groundwater shows weak alkaline in which the As(III) species would be present as neutral H3AsO3species and ionized H2AsO3-species. However, as most reported previously, electrochemical detection of As(III) has been operated under acidic conditions and the nonionic As(III) (H3AsO3) is the dominant species. Therefore, considering the change of As(III) speciation in different pH conditions, to develop a reliable method for the detection of As(III) in alkaline media might be more meaningful for practical applications. Here, combined the multilayer adsorption of nanorod-like α-MnO2with the excellent electrocatalytic ability of ∼5 nm Au nanoparticles (AuNPs), an efficient and ultrahigh anti-interference electrochemical detection of As(III) with AuNPs/α-MnO2nanocomposite in alkaline media (nearly real water environment) was developed. Notably, we have provided a thorough electrochemical analytical investigation to confirm the advantage of As(III) detection in alkaline media. The system was evaluated by a series of interference tests, and no obvious interference from commonly coexisting substances (referring to the groundwater, Togtoh region, Inner Mongolia, China) was observed in alkaline media. Furthermore, electrodes robust stability and excellent reproducibility were obtained. Under the optimized conditions, the limit of detection (3σ method) toward As(III) was 0.019 ppb, and the obtained sensitivity was 16.268 ± 0.242 μA ppb-1cm-2. Finally, the proposed method has been successfully employed for detection of As(III) in a real water sample.
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.|Department of Materials Science and Engineering, University of Science and Technology of China , Hefei 230026, PR China.
Meng
M
Yang
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.
Xing
X
Chen
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.|Department of Materials Science and Engineering, University of Science and Technology of China , Hefei 230026, PR China.
Tian-Jia
TJ
Jiang
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.
Zheng
Z
Guo
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.
Jin-Huai
JH
Liu
Institute of Intelligent Machines, Chinese Academy of Sciences , Hefei 230031, PR China.|Department of Materials Science and Engineering, University of Science and Technology of China , Hefei 230026, PR China.
Xing-Jiu
XJ
Huang