|
|
|
|
|
|
Plastic Reference Material (PRM) Combined With Partial Least Square (PLS) in Laser-Induced Breakdown Spectroscopy (LIBS) in the Field of Quantitative Elemental Analysis |
WANG Bin1, 2, ZHENG Shao-feng2, GAN Jiu-lin1, LIU Shu3, LI Wei-cai2, YANG Zhong-min1, SONG Wu-yuan4* |
1. State Key Laboratory of Luminescent Materials and Devices, South China University of Technology,Guangzhou 510641, China
2. State Key Testing Laboratory of Consumer Products,Huangpu Customs Technology Center,Dongguan 523070, China
3. Technical Center for Industrial Product and Raw Materical Inspection and Testing, Shanghai Customs, Shanghai 200135, China
4. Guangzhou Customs District Technology Center,Guangzhou 510623, China
|
|
|
Abstract Laser-induced breakdown spectroscopy was widely used for quantitative elemental analysis of the field for its rapid, efficient, harmless, full spectrum advantage of direct reading and almost do not need sample preparation. In order to establish a simple method, developed by using polypropylene (PP) plastic reference material(RM), combined with partial least squares (PLS), using laser-induced breakdown spectroscopy (LIBS), the PRM-PLS-LIBS model of Pb and Cr was established. PP reference materials were developed by the requirements of international standards. The content gradient of Pb and Cr were set in the range of 0~1 000 mg·kg-1 according to the limitation requirements of various countries and regions. The certification results combined with uncertainty gave the specific values, and the certified reference material had good homogeneity and stability. The correlation coefficients of the standard curves of Pb and Cr were 0.999 2 and 0.998 9, respectively, and the detection limits were 35 and 28 mg·kg-1, respectively, which had reached the quantitative analysis ability. In order to improve the accuracy of the quantitative analysis model, it was necessary to optimize the data of standard curve further. Partial least squares (PLS) and classical least squares (CLS) were compared by multiple optimizations of baseline types for small data volume. Experimental results showed that the root mean square error of calibration (RMSEC) and correction coefficient (Corr. Coeff) of PLS were better than that of CLS. By optimizing the analytical wavelength range and baseline type of Pb and Cr, the correction coefficient between the given value and the predicted value of the correction curve reached 1.000 0, which further improved the model’s accuracy. A set of PP-certified reference materials were then selected to verify the calibration curve. High content samples (PP-306) and low-content samples (PP-302) were taken for determination, and Pb and Cr determination data were substituted into the PRM-PLS model. The Pb and Cr determination values in PP-306 were 998 and 96 mg·kg-1, respectively. The determination values of Pb and Cr in PP-302 are 980 and 95 mg·kg-1, respectively, within the given range. The method was effective and reliable.
|
Received: 2022-02-08
Accepted: 2022-10-20
|
|
Corresponding Authors:
SONG Wu-yuan
E-mail: swyciq@126.com
|
|
[1] Restriction of Hazardous Substances(DIRECTIVE 2011/65/EU).
[2] American National Standard on Toys, ASTM F963, Standard Consumer Safety Specification for Toy Safety.
[3] International Standard on Safety of Toys, ISO 8124, Part 3: Migration of Certain Elements.
[4] The International Electrotechnical Commission Standard on Electrotechnical Products, IEC 62321-3-1: 2013, Determination of Certain Substances in Electrotechnical Products—Part 3-1: Screening—Lead, Mercury, Cadmium, Total Chromium and Total Bromine by X-ray Fluorescence Spectrometry.
[5] The International Electrotechnical Commission Standard on Electrotechnical Products, IEC 62321-5, Determination of Certain Substances in Electrotechnical Products—Part 5: Cadmium, Lead and Chromium in Polymers and Electronics and Cadmium and Lead in Metals by AAS, AFS, ICP-OES and ICP-MS.
[6] CPSC-CH-E1002-08.3: Standard Operating Procedure for Determining Total Lead (Pb) in Nonmetal Children’s Product.
[7] Miziolek Andrzej W, Palleschi V, Schechter I. Laser-Induced Breakdown Spectrosopy (LIBS). New York: Cambridge University Press , 2006.
[8] Cremers D A, Radziemski L J. Handbook of Laser-Induced Breakdown Spectroscopy. England: John Wiley & Sons, Ltd., Chichester, West Sussex, 2006.
[9] Terán E J, Montes M L, Rodríguez C, et al. Microchemical Journal, 2019, 144: 159.
[10] Meng Deshuo, Zhao Nanjing, Ma Mingjun, et al. Plasma Science and Technology, 2015, 17: 632.
[11] Trautner Stefan, Lackner Johannes, Spendelhofer Wolfgang, et al. Analytical Chemistry, 2019, 91(8): 5200.
[12] Syed Kifayat Hussain Shah, Javed Iqbal, Pervaiz Ahmad, et al. Radiation Physics and Chemistry, 2020, 170: 108666.
[13] Urbina I, Carneiro D, Rocha S, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2020, 170: 105902.
[14] Díaz Pace D M, Miguel R E, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2017, 131: 58.
[15] Roberto-Jesús Lasheras, Daniel Paules, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2020, 171: 105918.
[16] Quienly Godoi, Flavio O Leme, Lilian C Trevizan, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2011, 66: 138.
[17] Steven Millar, Sabine Kruschwitz, Gerd Wilsch et al. Cement and Concrete Research, 2019, 117: 16.
[18] Lidiane Cristina Nunes, Edenir Rodrigues Pereira-Filho, Marcelo Braga Bueno Guerra,et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2019, 154: 25.
[19] Pavel Yaroshchyk,Richard J S Morrison,Doug Body, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2005, 60: 1482.
[20] Yu Youli, Zhou Weidong, Qian Huiguo, et al. Plasma Science and Technology, 2014, 16: 683.
[21] Wen Guanhong, Sun Duixiong, Su Maogen, et al. Plasma Science and Technology, 2014, 16: 598.
[22] Dietz T, Klose J, Kohns P, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2019, 152: 59.
[23] Ale( sˇ ) Hrdlička, Jitka Hegrová, Eva Havrlová, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2020, 170: 105919.
[24] Imran Rehan, Muhammad Zubair Khan, Kamran Rehan, et al. Analytical Letters,2020, 53: 2571.
[25] WANG Bin, FANG Cheng, LAN Li-li, et al(王 斌,方 成,兰丽丽,等). PTCA (Part B: Chem. Anal.)(理化检验化学分册), 2018, 54(11): 1292.
[26] Mello C, Ribeiro D, Novaes F, et al. Anal. Bioanal. Chem., 2005, 383: 701.
[27] Andrade J M, Cristoforetti G, Legnaioli S, et al. Spectrochim. Acta B: Atomic Spectroscopy, 2010, 65: 658.
[28] Leticia Gómez-Nubla, Julene Aramendia, Silvia Fdez-Ortiz de Vallejuelo, et al. Microchemical Journal, 2018, 137: 392.
[29] Duan Fajie, Fu Xiao, Jiang Jiajia, et al. Spectrochimica Acta Part B: Atomic Spectroscopy, 2018, 143: 12.
[30] Forina M, Casolino C, Pizarro Millan C, et al. J. Chemom., 1999, 13: 165.
[31] Chen D, Hu B, Shao X, et al. Analyst, 2004, 129: 664.
[32] HU Li, ZHAO Nan-jing, LI Da-chuang, et al(胡 丽,赵南京,李大创,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2017,37(8): 2585.
[33] LUO Zi-yi, HUANG Lin, LIU Mu-hua, et al(罗子奕,黄 林,刘木华,等). Chinese Journal of Analysis Laboratory(分析试验室),2018, 37(12): 1384.
[34] WANG Bin, ZHANG Jiang-feng, WEN Jian-chang, et al(王 斌,张江锋,温健昌,等). Journal of the Chinese Society of Rare Earths(中国稀土学报), 2015, 33(1): 124.
[35] ISO GUIDE 35: 2017 Reference Materials—Guidance for Characterization and Assessment of Homogeneity and Stability.
[36] NIST (National Institute of Standards and Technology).
|
[1] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
[2] |
FANG Zheng, WANG Han-bo. Measurement of Plastic Film Thickness Based on X-Ray Absorption
Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3461-3468. |
[3] |
JIA Hao1, 3, 4, ZHANG Wei-fang1, 3, LEI Jing-wei1, 3*, LI Ying-ying1, 3, YANG Chun-jing2, 3*, XIE Cai-xia1, 3, GONG Hai-yan1, 3, DING Xin-yu1, YAO Tian-yi1. Study on Infrared Fingerprint of the Classical Famous
Prescription Yiguanjian[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3202-3210. |
[4] |
LUO Dong-jie, WANG Meng, ZHANG Xiao-shuan, XIAO Xin-qing*. Vis/NIR Based Spectral Sensing for SSC of Table Grapes[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2146-2152. |
[5] |
CHENG Xiao-xiang1, WU Na2, LIU Wei2*, WANG Ke-qing2, LI Chen-yuan1, CHEN Kun-long1, LI Yan-xiang1*. Research on Quantitative Model of Corrosion Products of Iron Artefacts Based on Raman Spectroscopic Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2166-2173. |
[6] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
[7] |
ZHENG Zhi-jie1, LIN Zhen-heng1, 2*, XIE Hai-he2, NIE Yong-zhong3. The Method of Terahertz Spectral Classification and Identification for Engineering Plastics Based on Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1387-1393. |
[8] |
ZHENG Li-na, FENG Zi-kang, HAN Zhen, LI Jia-lin, FENG Wen-ting. Quantitative Analysis of Microplastics Based on Micro-Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1645-1650. |
[9] |
XU Wei-xin, XIA Jing-jing, WEI Yun, CHEN Yue-yao, MAO Xin-ran, MIN Shun-geng*, XIONG Yan-mei*. Rapid Determination of Oxytetracycline Hydrochloride Illegally Added in Cattle Premix by ATR-FTIR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 842-847. |
[10] |
LI Zi-yi1, LI Rui-lan1, LI Can-lin1, WANG Ke-ru2, FAN Jiu-yu3, GU Rui1*. Identification of Tibetan Medicine Zhaxun by Infrared Spectroscopy
Combined With Chemometrics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 526-532. |
[11] |
WANG Chao1, LIU Yan1*, XIA Zhen-zhen2, WANG Qiao1, DUAN Shuo1. Fast Evaluation of Freshness in Crayfish (Prokaryophyllus clarkii) Cased on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 156-161. |
[12] |
ZHAO Jian-ming, YANG Chang-bao, HAN Li-guo*, ZHU Meng-yao. The Inversion of Muscovite Content Based on Spectral Absorption
Characteristics of Rocks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 220-224. |
[13] |
SHANG Chao-nan1, XIE Yan-li2, GAO Xiao3, ZHOU Xue-qing2, ZHAO Zhen-dong2, MA Jia-xin1, CUI Peng3, WEI Xiao-xiao3, FENG Yu-hong1, 2*, ZHANG Ming-nan2*. Research on Qualitative and Quantitative Analysis of PE and EVA in Biodegradable Materials by FTIR[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3380-3386. |
[14] |
LI Qing-bo1, BI Zhi-qi1, CUI Hou-xin2, LANG Jia-ye2, SHEN Zhong-kai2. Detection of Total Organic Carbon in Surface Water Based on UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3423-3427. |
[15] |
WU Xue1, 2, FENG Wei-wei2, 3, 4*, CAI Zong-qi2, 3, WANG Qing2, 3. Study on Rapid Recognition of Microplastics Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3501-3506. |
|
|
|
|