Gold nanoclusters and mesoporous silica-encapsulated carbon dot fluorescent nanosensors combine with LightGBM algorithm for ultra-fast detection of Co2+

Published: 2 May 2024| Version 1 | DOI: 10.17632/g3wg5kfty4.1
Contributors:
, Chenyue Kang

Description

The LightGBM algorithm is utilized to establish a Co2+ prediction model. The entire detection process is within 10 s and the model prediction value is as high as 0.991 on average. In essence, the proposed fluorescent nanosensor enhanced by LightGBM algorithm has been successfully applied for ultra-fast and sensitive detection of Co2+.

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Institutions

Xi'an Jiaotong University, Shanxi University

Categories

Chemistry, Machine Learning, Spectral Analysis of Signal, Extreme Gradient Boosting

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