Laser-induced Breakdown Spectroscopy for Quantitative Analysis of Multi-Target Elements in Uranium Ore

被引:4
作者
Shu, Kai-qiang [1 ]
Chen, You-yuan [2 ]
Peng, Zheng-ying [2 ]
Fan, Qing-wen [1 ]
Lin, Qing-yu [1 ]
Duan, Yi-xiang [1 ]
机构
[1] Sichuan Univ, Sch Mech Engn, Chengdu 610064, Peoples R China
[2] Sichuan Univ, Coll Life Sci, Chengdu 610064, Peoples R China
关键词
Laser-induced breakdown spectroscopy; Uranium ore; Quantitative analysis; Univariate analysis; Multivariate analysis; Principal component regression; Support vector regression; SUPPORT VECTOR REGRESSION; SOIL;
D O I
10.19756/j.issn.0253-3820.221523
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Uranium is one of the most important strategic nuclear resources, which plays an important role in national strategy and nuclear energy. Therefore, it is significant to explore uranium ore precisely and smelt effective. Laser-induced breakdown spectroscopy (LIBS) is a process analytical technology, which is good at quantitative analysis of multiple elements quickly and in situ. It has unique advantages in detection of multiple elements in uranium ore. How to break through the problem of accurate quantification is still the key research content of LIBS technology. In this work, the quantitative models of U, Si, Al and Ti in uranium ore were established, based on univariate analysis (UVA), principal component regression (PCR) and support vector regression (SVR). The predictive coefficients (R2) of the two multivariate models for U, Si, Al and Ti were all better than 0.99. The quantitative accuracy of the SVR model for Si, Al and Ti was better, and the relative errors (Er) were 0.01%, 1.41% and 0.13%, respectively. The quantitative accuracy of the PCR model for U was the best, with the minimum Er of 0.64%. Compared with UVA, multivariate analysis (MVA) could overcome the quantitative bias caused by spectral line interference and matrix effect. Hence, it made the LIBS technique more accurate in quantification of multiple elements in uranium ore.
引用
收藏
页码:1195 / 1203
页数:9
相关论文
共 25 条
  • [1] A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy
    Boucher, Thomas F.
    Ozanne, Marie V.
    Carmosino, Marco L.
    Dyar, M. Darby
    Mahadevan, Sridhar
    Breves, Elly A.
    Lepore, Kate H.
    Clegg, Samuel M.
    [J]. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2015, 107 : 1 - 10
  • [2] Laser-induced breakdown spectroscopy of light water reactor simulated used nuclear fuel: Main oxide phase
    Campbell, Keri R.
    Judge, Elizabeth J.
    Barefield, James E., II
    Colgan, James P.
    Kilcrease, David P.
    Czerwinski, Ken R.
    Clegg, Samuel M.
    [J]. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2017, 133 : 26 - 33
  • [3] Chen J., 2021, METALL ANAL, V41, P13
  • [4] Enrichment of uranium in seawater by glycine cross-linked graphene oxide membrane
    Chu, Jian
    Huang, Qinggang
    Dong, Yuhua
    Yao, Zeen
    Wang, Jieru
    Qin, Zhi
    Ning, Zhigang
    Xie, Jianjun
    Tian, Wei
    Yao, Huijun
    Bai, Jing
    [J]. CHEMICAL ENGINEERING JOURNAL, 2022, 444
  • [5] Multi-element analysis of iron ore pellets by laser-induced breakdown spectroscopy and principal components regression
    Death, D. L.
    Cunningham, A. P.
    Pollard, L. J.
    [J]. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2008, 63 (07) : 763 - 769
  • [6] Quantification of Mn in glass matrices using laser induced breakdown spectroscopy (LIBS) combined with chemometric approaches
    Devangad, Praveen
    Unnikrishnan, V. K.
    Tamboli, M. M.
    Shameem, K. M. Muhammed
    Nayak, Rajesh
    Choudhari, K. S.
    Santhosh, C.
    [J]. ANALYTICAL METHODS, 2016, 8 (39) : 7177 - 7184
  • [7] Strategies for Mars remote Laser-Induced Breakdown Spectroscopy analysis of sulfur in geological samples
    Dyar, M. Darby
    Tucker, Jonathan M.
    Humphries, Seth
    Clegg, Samuel M.
    Wiens, Roger C.
    Lane, Melissa D.
    [J]. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2011, 66 (01) : 39 - 56
  • [8] Artificial neural network for Cu quantitative determination in soil using a portable Laser Induced Breakdown Spectroscopy system
    Ferreira, Edilene C.
    Milori, Debora M. B. P.
    Ferreira, Ednaldo J.
    Da Silva, Robson M.
    Martin-Neto, Ladislau
    [J]. SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2008, 63 (10) : 1216 - 1220
  • [9] Advanced technology paths to global climate stability: Energy for a greenhouse planet
    Hoffert, MI
    Caldeira, K
    Benford, G
    Criswell, DR
    Green, C
    Herzog, H
    Jain, AK
    Kheshgi, HS
    Lackner, KS
    Lewis, JS
    Lightfoot, HD
    Manheimer, W
    Mankins, JC
    Mauel, ME
    Perkins, LJ
    Schlesinger, ME
    Volk, T
    Wigley, TML
    [J]. SCIENCE, 2002, 298 (5595) : 981 - 987
  • [10] A new analysis workflow for discrimination of nuclear grade graphite using laser-induced breakdown spectroscopy
    Horsfall, John P. O.
    Trivedi, Divyesh
    Smith, Nick T.
    Martin, Philip A.
    Coffey, Paul
    Tournier, Stella
    Banford, Anthony
    Li, Lin
    Whitehead, David
    Lang, Adam
    Law, Gareth T. W.
    [J]. JOURNAL OF ENVIRONMENTAL RADIOACTIVITY, 2019, 199 : 45 - 57