Octahedral Gold-Silver Hollow Cage SERS Sensor for Tea Pesticide Detection
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Solution Overview
Problem
Conventional methods for detecting pesticide residues in tea, such as gas chromatography and high-performance liquid chromatography, are complex, costly, time-consuming, and require professional operators, making them unsuitable for rapid and accurate on-site analysis.
Innovation Solution
A deep learning model combined with a surface-enhanced Raman scattering (SERS) sensor using an octahedral gold-silver hollow cage substrate is developed for rapid detection of thiram and pymetrozine in tea, involving the preparation of the sensor, processing of Raman spectral data, and construction of a one-dimensional convolutional neural network for quantitative analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional detection methods (GC, HPLC, GC-MS, HPLC-MS) are used, then detection sensitivity and accuracy are improved, but device complexity and operation difficulty increase
Solution Approach 1:
The patent replaces complex mechanical chromatography systems (GC, HPLC) with an optical detection system based on surface-enhanced Raman scattering (SERS). The SERS substrate enhances the Raman signal of pesticide molecules, enabling direct detection without complex pretreatment. This substitution transforms a mechanically complex system into a simpler optical system that maintains high sensitivity while reducing operational complexity.
Solution Approach 2:
The patent employs composite SERS substrates combining gold and silver nanoparticles with specific morphologies (stars, triangles, hexagons). These composite materials provide enhanced electromagnetic field effects that amplify Raman signals, achieving detection sensitivity comparable to GC-MS and HPLC-MS while using a simpler detection platform.
2Measurement precision
If conventional detection methods (GC, HPLC, GC-MS, HPLC-MS) are used, then detection sensitivity is improved, but detection time and cost increase
Solution Approach 1:
The patent prepares SERS substrates with predetermined optimal morphologies (stars, triangles, hexagons) and sizes before detection. This preliminary preparation ensures that the substrates are ready for immediate use, eliminating the need for time-consuming instrumental setup and calibration required by GC, HPLC, and mass spectrometry systems. The pre-optimized substrates enable rapid detection while maintaining high sensitivity.
3Measurement precision
If conventional detection methods (GC, HPLC, GC-MS, HPLC-MS) are used, then detection accuracy is improved, but operator skill requirements increase
Solution Approach 1:
The SERS detection system is designed to be self-explanatory and easy to operate. The method involves simple mixing of the sample with the SERS substrate followed by direct Raman spectroscopy measurement. The system does not require complex parameter optimization or skilled operation, as the SERS substrate automatically provides signal enhancement. This makes the system accessible to operators without specialized training in chromatography or mass spectrometry.
4Measurement precision
If conventional detection methods (GC, HPLC, GC-MS, HPLC-MS) are used, then detection sensitivity is improved, but manufacturing cost increases
Solution Approach 1:
The patent uses relatively inexpensive SERS substrates that can be synthesized through chemical methods rather than requiring expensive mass spectrometry instruments. The substrates can be produced at low cost using standard laboratory equipment, making the detection system more affordable than conventional GC-MS or HPLC-MS systems while maintaining comparable detection sensitivity for pesticide residues.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The SERS sensor with a bimetallic structure provides enhanced sensitivity and stability, enabling rapid and accurate detection of pesticide residues, overcoming the limitations of conventional methods by simplifying the process and reducing costs while maintaining high sensitivity and accuracy.
Implementation Method 1
surface-enhanced Raman scattering (SERS) sensor
Implementation Method 2
preparing silver on a surface of an octahedral cuprous oxide template by reduction
Implementation Method 3
preparing gold on a surface of the octahedral silver hollow cage by reduction
Implementation Method 4
analysis using a Raman spectrometer to obtain SERS spectral data
Data Source
AI summary
A method and a system for detecting pesticide residues in tea based on a surface-enhanced Raman scattering (SERS) sensor are provided. An octahedral gold-silver hollow cage-based sensor is prepared, mixed with a pesticide standard solution and analyzed to obtain SERS spectral data. The SERS spectral data is processed, and a quantitative model is established based on the processed SERS spectral data. Based on the quantitative model, the detection of thiram and pymetrozine in tea samples can be completed. By means of an octahedral cuprous oxide template, gold-silver octahedral hollow cage (Au—AgOHCs) nanomaterials are prepared by reduction of gold and silver ions and removal of the template by acid dissolution, so as to prepare the SERS sensor, which can be applied to the rapid and quantitative detection of thiram and pymetrozine in tea samples.