一种基于紫外可见光谱的多金属离子浓度检测方法

doi:10.11949/j.issn.0438-1157.20161709

化工学报 ›› 2017, Vol. 68 ›› Issue (3): 998-1004.DOI: 10.11949/j.issn.0438-1157.20161709

一种基于紫外可见光谱的多金属离子浓度检测方法

朱红求, 陈俊名, 尹冬航, 李勇刚, 阳春华

中南大学信息科学与工程学院, 湖南长沙 410083

收稿日期:2016-12-05 修回日期:2016-12-12 出版日期:2017-03-05 发布日期:2017-03-05
通讯作者: 陈俊名,cjmrise@outlook.com
基金资助:
国家自然科学基金重点项目（61533021）；国家创新研究群体科学基金项目（61621062）。

A UV-Vis analytical method for polymetallic solutions

ZHU Hongqiu, CHEN Junming, YIN Donghang, LI Yonggang, YANG Chunhua

School of Information Science & Engineering, Central South University, Changsha 410083, Hunan, China

Received:2016-12-05 Revised:2016-12-12 Online:2017-03-05 Published:2017-03-05
Contact: 10.11949/j.issn.0438-1157.20161709
Supported by:
supported by the State Key Program of National Natural Science Foundation of China (61533021) and the Foundation for Innovative Research Groups of National Natural Science Foundation of China (61621062).

摘要/Abstract

摘要：

针对Cu²⁺，Co²⁺，Zn²⁺ 3种金属离子混合溶液的紫外可见分光光度法（UV-Vis）光谱重叠而难以检测的问题，提出了一种基于改进型Monte Carle无信息变量消除（MC-UVE）方法的多金属离子浓度检测方法。在MC-UVE的基础上引入指数衰减函数（EDF），提出了一种改进的MC-UVE方法，并基于该方法对料液的紫外-可见光谱进行波长筛选；然后，利用筛选出的波长建立PLS模型并进行各组分浓度检测计算；最后，分别对基于MC-UVE方法和改进型MC-UVE方法PLS模型的计算结果进行对比分析。结果表明：改进型MC-UVE方法可筛选出对模型贡献度高的变量，基于该变量选择方法的PLS模型精度高。

关键词: 紫外可见光谱, Monte Carle无信息变量消除, 变量筛选, 重叠光谱分离, 偏最小二乘法, 光化学, 计算化学

Abstract:

A polymetallic analytical method based on an improved Monte Carlo uninformative variable elimination (MC-UVE) was proposed to determine ion concentration by ultraviolet visible (UV-Vis) spectra of Cu²⁺, Co²⁺ and Zn²⁺ mixture solution. The improved MC-UVE, developed by incorporating exponential attenuation function (EDF), was applied to selecting wavelength of UV-Vis spectra. And the partial least squares calibration model was built on concentrations of polymetallic components at the selected wavelength. Experimental results showed that the improved MC-UVE could select higher contributing model variables and develop more precise PLS model than MC-UVE.

Key words: UV-Vis spectrometry, MC-UVE, wavelength selection, overlapping spectral separation, PLS, photochemistry, computational chemistry

中图分类号:

O657.32

朱红求, 陈俊名, 尹冬航, 李勇刚, 阳春华. 一种基于紫外可见光谱的多金属离子浓度检测方法[J]. 化工学报, 2017, 68(3): 998-1004.

ZHU Hongqiu, CHEN Junming, YIN Donghang, LI Yonggang, YANG Chunhua. A UV-Vis analytical method for polymetallic solutions[J]. CIESC Journal, 2017, 68(3): 998-1004.

参考文献 30

[1]	WANG G W, YANG C H, LI Y G, et al. State-transition-algorithm-based resolution for overlapping linear sweep voltammetric peaks with high signal ratio[J]. Chemometrics and Intelligent Laboratory Systems, 2016, 151:61-70.
[2]	邓仕钧, 阳春华, 李勇刚, 等. 锌电解全流程酸锌离子浓度在线预测模型[J]. 化工学报, 2015, 66(7):2588-2594. DENG S J, YANG C H, LI Y G, et al. On-line prediction model for concentrations of zinc ion and sulfuric acid in zinc electrowinning process[J]. CIESC Journal, 2015, 66(7):2588-2594.
[3]	ANTHEMIDIS A N, ZACHARIADIS G A, STRATIS J A. Determination of arsenic(Ⅲ) and total inorganic arsenic in water samples using an on-line sequential insertion system and hydride generation atomic absorption spectrometry[J]. Analytica Chimica Acta, 2005, 547(2):237-242.
[4]	CARLETTO J S, ROUX K C D P, MALTEZ H F, et al. Use of 8-hydroxyquinoline-chitosan chelating resin in an automated on-line preconcentration system for determination of zinc(Ⅱ) by F AAS[J]. Journal of Hazardous Materials, 2008, 157(1):88-93.
[5]	HU Q F, YANG G Y, ZHAO Y Y, et al. Determination of copper, nickel, cobalt, silver, lead, cadmium, and mercury ions in water by solid-phase extraction and the RP-HPLC with UV-Vis detection[J]. Anal. Bioanal. Chem., 2003, 375(6):831-835.
[6]	AMMANN A A. Speciation of heavy metals in environmental water by ion chromatography coupled to ICP-MS[J]. Anal. Bioanal. Chem., 2001, 372(3):448-452.
[7]	DEITRICH C L, CUELLO-NUÑEZ S, KMIOTEK D, et al. Accurate quantification of selenoprotein P (SEPP1) in plasma using isotopically enriched seleno-peptides and species-specific isotope dilution with HPLC coupled to ICP-MS/MS[J]. Anal. Chem., 2016, 88(12):6357-6365.
[8]	?AHIN S, DEMIR C, GÜÇER ?. Simultaneous UV-vis spectrophotometric determination of disperse dyes in textile wastewater by partial least squares and principal component regression[J]. Dyes and Pigments, 2007, 73(3):368-376.
[9]	张宇博, 张威, 车得福. 利用分光光度法测定混合电解质溶液中铁氰化钾的浓度[J]. 化工学报, 2013, 64(4):1226-1230. ZHANG Y B, ZHANG W, CHE D F. Measurement of potassium ferricyanide concentration in electrolyte solution using UV-VIS spectrophotometry[J]. CIESC Journal, 2013, 64(4):1226-1230.
[10]	彭雄威. 多金属离子极谱重叠峰在线分离方法研究与应用[D]. 长沙:中南大学, 2014. PENG X W. On-line resolution for overlapped polarographic peaks of polymetallic ion and its application[D]. Changsha:Central South University, 2014.
[11]	汤斌, 魏彪, 毛本将, 等. 紫外-可见吸收光谱法水质检测系统的噪声分析与处理研究[J]. 激光与光电子学进展, 2014, (4):201-207. TANG B, WEI B, MAO B J, et al. Noise analysis and denoising research on the UV-visible absorption spectroscopy water quality detection system[J]. Laser & Optoelectronics Progress, 2014, (4):201-207.
[12]	ZHU H Q, WANG G W, YANG C H, et al. Overlapped peaks resolution for linear sweep polarography using Gaussian-like distribution[J].Transactions of Nonferrous Metals Society of China, 2013, 23(7):2181-2186.
[13]	HÖSKULDSSON A. PLS regression methods[J]. Chemometrics, 1988, 2(3):211-228.
[14]	GHASEMI J, NIAZI A. Simultaneous determination of cobalt and nickel. Comparison of prediction ability of PCR and PLS using original, first and second derivative spectra[J]. Microchemical Journal, 2001, 68(1):1-11.
[15]	LI H D, LIANG Y Z, XU Q S. Uncover the path from PCR to PLS via elastic component regression[J]. Chemometrics and Intelligent Laboratory Systems, 2010, 104(2):341-346
[16]	NORGAARD L, SAUDLAND A, WAGNER J, et al. Interval partial least-squares regression (iPLS):a comparative chemometric study with an example from near-infrared spectroscopy[J]. Appl. Spectrosc., 2000, 54(3):413-419.
[17]	李倩倩. 无信息变量消除法在三种谱学方法中的定量分析研究[D].北京:中国农业大学, 2014. LI Q Q. Uninformative variable elimination combined with three spectroscopy methods for quantitive analysis[D]. Beijing:China Agricultural University, 2014.
[18]	FERRÃO M F F, VIERA M D S, PAZOS R E P, et al. Simultaneous determination of quality parameters of biodiesel/diesel blends using HATR-FTIR spectra and PLS, iPLS or siPLS regressions[J]. Fuel, 2011, 90(2):701-706.
[19]	CENTNER V, MASSART D L, DE NOORD O E, et al. Elimination of uninformative variables for multivariate calibration[J]. Anal. Chem., 1996, 68(21):3851-3858.
[20]	WU D, CHEN X J, SHI P Y, et al. Determination of α-linolenic acid and linoleic acid in edible oils using near-infrared spectroscopy improved by wavelet transform and uninformative variable elimination[J]. Analytica Chimica Acta, 2009, 634(2):166-171.
[21]	KOSHOUBU J, IWATA T, MINAMI S. Elimination of the uninformative calibration sample subset in the modified UVE(uninformative variable elimination)-PLS (partial least squares) method[J]. Analytical Sciences, 2001, 17(2):319-322.
[22]	郝勇, 孙旭东, 潘圆媛, 等. 蒙特卡罗无信息变量消除方法用于近红外光谱预测果品硬度和表面色泽的研究[J]. 光谱学与光谱分析, 2011, (5):1225-1229. HAO Y, SUN X D, PAN Y Y, et al. Detection of firmness and surface color of pear by near infrared spectroscopy based on Monte Carlo uninformative variables elimination method[J]. Spectroscopy and Spectral Analysis, 2011, (5):1225-1229.
[23]	CAI W S, LI Y K, SHAO X G. A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra[J]. Chemometrics and Intelligent Laboratory Systems, 2008, 90(2):188-194.
[24]	HAN Q J, WU H L, CAI C B, et al. An ensemble of Monte Carlo uninformative variable elimination for wavelength selection[J]. Analytica Chimica Acta, 2008, 612(2):121-125.
[25]	XU D, FAN W, LV H Y, et al. Simultaneous determination of traces amounts of cadmium, zinc, and cobalt based on UV-Vis spectrometry combined with wavelength selection and partial least squares regression[J]. Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy, 2014, 123:430-435.
[26]	LI H D, LIANG Y Z, XU Q S, et al. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration[J]. Analytica Chimica Acta, 2009, 648(1):77-84.
[27]	TAN B B, LIANG Y Z, YI L Z, et al. Identification of free fatty acids profiling of type 2 diabetes mellitus and exploring possible biomarkers by GC-MS coupled with chemometrics[J]. Metabolomics, 2009, 6(2):219-228.
[28]	WU D, SUN D W. Application of visible and near infrared hyperspectral imaging for non-invasively measuring distribution of water-holding capacity in salmon flesh[J]. Talanta, 2013, 116:266-276.
[29]	李江波, 郭志明, 黄文倩, 等. 应用CARS和SPA算法对草莓SSC含量NIR光谱预测模型中变量及样本筛选[J]. 光谱学与光谱分析, 2015, (2):372-378. LI J B, GUO Z M, HUANG W Q, et al. Near-infrared spectra combining with CARS and SPA algorithms to screen the variables and samples for quantitatively determining the soluble solids content in strawberry[J]. Spectroscopy and Spectral Analysis, 2015, (2):372-378.
[30]	刘国海, 夏荣盛, 江辉, 等. 一种基于SCARS策略的近红外特征波长选择方法及其应用[J]. 光谱学与光谱分析, 2014, (8):2094-2097. LIU G H, XIA R S, JIANG H, et al. A wavelength selection approach of near infrared spectra based on SCARS strategy and its application[J]. Spectroscopy and Spectral Analysis, 2014, (8):2094-2097.

一种基于紫外可见光谱的多金属离子浓度检测方法

A UV-Vis analytical method for polymetallic solutions

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