Machine learning intelligently selects feature values to construct a sensor array based on tri-functional Mn-doped...

Area of Science:

• Biomimetic Chemistry
• Nanomaterials Science
• Analytical Chemistry

Background:

• Nanozymes offer advantages over natural enzymes, including stability and cost-effectiveness.
• Developing selective and sensitive methods for analyzing bioactive compounds like flavonoids is crucial.
• Covalent organic polymers (COPs) provide a versatile platform for designing functional nanomaterials.

Purpose of the Study:

• To synthesize a novel tri-functional nanozyme based on manganese-doped covalent organic polymer (Mn-COP).
• To develop a sensor array utilizing Mn-COP for the accurate identification and quantification of flavonoids.
• To employ machine learning for optimizing feature selection and enhancing analytical performance.

Main Methods:

• Synthesis of a tri-functional Mn-COP nanozyme exhibiting peroxidase-, oxidase-, and laccase-like activities.
• Fabrication of a nanozyme sensor array incorporating Mn-COP for flavonoid detection.
• Application of the Random Forest (RF) algorithm to analyze sensor signals and identify flavonoids.
• Optimization of reaction time and feature value selection for improved accuracy.

Main Results:

• The Mn-COP nanozyme demonstrated significant enzyme-like activities, which were inhibited by flavonoids in a time-dependent manner.
• The sensor array, leveraging three distinct chemical reactions, achieved enhanced accuracy in flavonoid recognition.
• The RF algorithm enabled the accurate identification and prediction of seven different flavonoids within a concentration range of 10-500 μM.
• The developed method successfully analyzed flavonoids in various traditional Chinese medicines.

Conclusions:

• The novel Mn-COP nanozyme offers a promising platform for developing advanced biosensors.
• The integration of the RF algorithm provides an intelligent approach for feature selection, improving sensor performance.
• This work presents a sophisticated nanozyme sensor array for the reliable detection of flavonoids, with potential applications in quality control and pharmaceutical analysis.