Issue 11, 2022
From the journal:

Analytical Methods

Correction: Accuracy improvement on quantitative analysis of the total iron content in branded iron ores by laser-induced breakdown spectroscopy combined with the double back propagation artificial neural network

Piao Su,ab   Shu Liu,*b   Hong Min,b   Yarui An,*a   Chenglin Yanb  and  Chen Lib  

* Corresponding authors

a Institute of Bismuth Science, University of Shanghai for Science and Technology, Shanghai 200093, China
E-mail: anyarui@usst.edu.cn

b Technical Center for Industrial Product and Raw Material Inspection and Testing of Shanghai Customs, Shanghai 200135, China
E-mail: liu_shu@customs.gov.cn

Abstract

Correction for ‘Accuracy improvement on quantitative analysis of the total iron content in branded iron ores by laser-induced breakdown spectroscopy combined with the double back propagation artificial neural network’ by Piao Su et al., Anal. Methods, 2022, 14, 427–437, DOI: 10.1039/D1AY01881G.

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Article information

DOI
https://doi.org/10.1039/D2AY90030K
Article type
Correction
Submitted
22 Feb 2022
Accepted
22 Feb 2022
First published
02 Mar 2022
This article is Open Access
Creative Commons BY license

Anal. Methods, 2022,14, 1169-1170

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Correction: Accuracy improvement on quantitative analysis of the total iron content in branded iron ores by laser-induced breakdown spectroscopy combined with the double back propagation artificial neural network

P. Su, S. Liu, H. Min, Y. An, C. Yan and C. Li, Anal. Methods, 2022, 14, 1169 DOI: 10.1039/D2AY90030K

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