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Magnetic‐optical dual functional Janus particles for the detection of metal ions assisted by machine learning

Authors :
Jianhang Liu
Yingdi Lv
Xinghai Li
Shi Feng
Wenbo Yang
Yumeng Zhou
Shengyang Tao
Source :
Smart Molecules, Vol 1, Iss 2, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Functional polymer microspheres have broad application prospects in various fields, such as metal ion detection, adsorption, separation, and controlled drug release. However, integrating different functions in a single microsphere system is a significant challenge in this field. In this work, we prepared multicompartmental emulsion droplets utilizing microfluidic technology. Fe3O4 magnetic nanoparticles were added to one of the compartments of the emulsion droplets as functional particles, and Janus microspheres were obtained after curing. Fluorescent probes enter the two compartments of the Janus microspheres by diffusion. The fluorescence changes of the microspheres were observed in situ and captured through a fluorescence microscope. The images are processed by image recognition software and a Python program. The “fingerprint” of the detected metal ions is obtained by dimensionality reduction of the data through Principal Component Analysis. We employ different algorithms to build Machine Learning models for predicting the metal ion species and concentration. The variation of fluorescence intensity of the three fluorescent probes and the corresponding R, G, and B channel values and time are used as descriptors. The results show that the Random Forest, K‐neighborhood (KNN), and Neural Network models demonstrated a better predicted effect with a variance (R2) greater than 0.9 and a smaller root mean square error; among them, the KNN model predicted the most accurate results.

Details

Language :
English
ISSN :
27514595 and 27514587
Volume :
1
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Smart Molecules
Publication Type :
Academic Journal
Accession number :
edsdoj.0b8f734260894c66bef030fdbfe79b7a
Document Type :
article
Full Text :
https://doi.org/10.1002/smo.20230006