Spectroscopy and Spectral Analysis, Volume. 42, Issue 2, 490(2022)

Accurate Quantitative Analysis of Valuable Components in Zinc Leaching Residue Based on XRF and RBF Neural Network

Yuan LI1、1; 2;, Yao SHI2、2; *;, Shao-yuan LI1、1; *;, Ming-xing HE3、3;, Chen-mu ZHANG2、2;, Qiang LI2、2;, and Hui-quan LI2、2; 4;
Author Affiliations
  • 11. Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
  • 22. CAS Key Laboratory of Green Process and Engineering, National Engineering Laboratory for Hydrometallurgical Cleaner Production Technology, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China
  • 33. School of Information and Electrical Engineering, Hebei University of Engineering, Handan 056038, China
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    References(7)

    [2] Piet N L Lens, David Huguenot, Manivannan Sethurajan et al. Environmental Science and Pollution Research International, 23, 75024(2016).

    [3] Rashchi Fereshteh, Khanlarian Misagh, Roshanfar Melina et al. Journal of Cleaner Production, 266(2020).

    [5] K Ossipov, F Seregina I, A Bolshov M. Spectrochimica Acta Part B: Atomic Spectroscopy, 177, 106050(2021).

    [6] I Komorowicz, B Markiewicz, Belter Sajnóg A et al. Talanta, 132, 814(2015).

    [7] . Materials and Manufacturing Processes, 35, 1455(2020).

    [8] Merkaj Eglantina, Civici Nikolla. Open Journal of Applied Sciences, 10, 305(2020).

    [9] J Backhouse D, W Deng, T Bell A M et al. Minerals, 10, 442(2020).

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    Yuan LI, Yao SHI, Shao-yuan LI, Ming-xing HE, Chen-mu ZHANG, Qiang LI, Hui-quan LI. Accurate Quantitative Analysis of Valuable Components in Zinc Leaching Residue Based on XRF and RBF Neural Network[J]. Spectroscopy and Spectral Analysis, 2022, 42(2): 490

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    Paper Information

    Category: Research Articles

    Received: Dec. 25, 2020

    Accepted: Apr. 28, 2021

    Published Online: Apr. 2, 2022

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2022)02-0490-08

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