Detection of trace triclocarban in water sample using solid-phase extraction-liquid chromatography with stochastic...

Area of Science:

• Analytical Chemistry
• Environmental Science

Background:

• Detecting trace amounts of triclocarban in water samples presents challenges due to weak High-Performance Liquid Chromatography/Ultraviolet (HPLC/UV) signals.
• Existing methods struggle with low signal-to-noise ratios (SNR), limiting accurate quantification.

Purpose of the Study:

• To develop and validate a novel algorithm based on stochastic resonance theory to enhance SNR for weak HPLC/UV signals.
• To improve the detection and quantification limits for triclocarban residue in water samples.

Main Methods:

• A new algorithm utilizing stochastic resonance principles was developed to optimize system parameters for signal enhancement.
• The algorithm was applied to experimental weak HPLC/UV signals of triclocarban in noisy water samples.
• Solid-phase extraction coupled with High-Performance Liquid Chromatography (SPE-HPLC) was used for triclocarban residue analysis.

Main Results:

• The stochastic resonance algorithm significantly enhanced the SNR of weak HPLC/UV signals.
• The limit of detection (LOD) for triclocarban was improved from 10 ng/L to 1 ng/L.
• The limit of quantification (LOQ) was improved from 50 ng/L to 5 ng/L.
• An excellent quantitative relationship between triclocarban concentrations and chromatographic responses was observed.

Conclusions:

• The proposed stochastic resonance-based algorithm effectively enhances SNR for weak HPLC/UV signals.
• This method significantly improves the sensitivity of triclocarban detection and quantification in water samples.
• The enhanced analytical method provides a reliable approach for monitoring triclocarban contamination in environmental water.