Article ; Online: Using Magnetic Micelles Combined with Carbon Fiber Ionization Mass Spectrometry for the Screening of Trace Triazine Herbicides from Aqueous Samples
Molecules, Vol 29, Iss 1, p
2023 Volume 137
Abstract: Triazine herbicides are commonly used in agriculture to eliminate weeds. However, they can persist in the environment. In this study, we explored a new method for detecting triazine herbicides in aqueous samples. We selected two triazine herbicides, ... ...
Abstract | Triazine herbicides are commonly used in agriculture to eliminate weeds. However, they can persist in the environment. In this study, we explored a new method for detecting triazine herbicides in aqueous samples. We selected two triazine herbicides, namely, prometryn and ametryn, as model herbicides. To generate magnetic probes, we mixed aqueous Gd 3+ with aqueous sodium dodecyl sulfate (SDS), which created magnetic probes made of Gd 3+ -SDS micelles. These probes showed a trapping capacity for the model herbicides. Results indicated that the trapping capacities of our magnetic probes for ametryn and prometryn were approximately 466 and 468 nmol mg −1 , respectively. The dissociation constants of our probes toward ametryn and prometryn were 2.92 × 10 −5 and 1.27 × 10 −5 , respectively. This is the first report that the developed magnetic probes can be used to trap triazine herbicides. For detection, we used carbon fiber ionization mass spectrometry (CFI-MS), which can be used to directly detect semi-volatiles from the samples in the condensed phase. Because of the semi-volatility of triazine herbicides, the herbicides trapped by the magnetic probes can be directly analyzed by CFI-MS without any elution steps. In addition, we also demonstrated the feasibility of using our approach for detecting triazine herbicides in lake water and drinking water. |
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Keywords | triazine herbicides ; magnetic probes ; magnetic metal ions ; sodium dodecyl sulfate ; carbon fiber ionization ; Organic chemistry ; QD241-441 |
Subject code | 333 |
Language | English |
Publishing date | 2023-12-01T00:00:00Z |
Publisher | MDPI AG |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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