An electrodeposited nano-porous and neural network-like Ln@HOF film for SO2 gas quantitative detection via fluorescent sensing and machine learning-Reference-Cited by-同舟云学术

An electrodeposited nano-porous and neural network-like Ln@HOF film for SO2 gas quantitative detection via fluorescent sensing and machine learning

Published:2021 Issue:46 Volume:9 Page:26391-26400
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Xu Xin¹^ORCID,Ma Wanpeng¹,Yan Bing¹^ORCID

Affiliation:

1. Shanghai Key Lab of Chemical Assessment and Sustainability, School of Chemical Science and Engineering, Tongji University, Siping Road 1239, Shanghai 200092, China

Abstract

A nano-porous and neural network-like Tb@HOF film was prepared to be utilized as a luminescent sensor for detecting SO2 gas and a BPNN model for SO2 concentration analysis has been constructed by deep machine learning.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/TA/D1TA08431C

Reference74 articles.

1. Amino-Functionalized Luminescent Metal–Organic Framework Test Paper for Rapid and Selective Sensing of SO2 Gas and Its Derivatives by Luminescence Turn-On Effect

2. The use of cyclic voltammetry for wine analysis: Determination of polyphenols and free sulfur dioxide

3. Organosulfate Formation through the Heterogeneous Reaction of Sulfur Dioxide with Unsaturated Fatty Acids and Long-Chain Alkenes

4. DNA damaging effects of sulfur dioxide derivatives in cells from various organs of mice

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