Some Difficulties and Status in the Application of X-Ray Spectrometry in Geological Analysis: A Review
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摘要:
X射线荧光光谱法(XRF)具有无损、快速、环保和分析精度高等特点，常作为地质样品中主量和微量元素分析的首选方法。然而，由于地质样品的矿物组成、物理结构特征(如尺寸、形状和分层等)和化学成分(如元素组成、化学形态等)的复杂性与多样性，XRF在地质样品分析的实际应用中存在一些技术难点。本文从小样品量和珍贵样品的分析、XRF的散射效应的应用、易挥发元素分析、变价元素分析和稀有金属分析等方面，对XRF在地质分析中的难点进行了总结与评述。指出制备易于保存和便于反复测量的小尺寸样片是小样品量和珍贵样品XRF分析的合适方法；XRF散射效应可用于成分未知的样品中更多化学成分信息的获取以及异质性样品原位分析误差的校正；超细粉末制样、稳定剂的加入和标准加入法建立工作曲线是解决易挥发元素XRF分析困难的方法。认为元素的特征X射线相对强度可用于变价元素价态和形态的分析；优化校准曲线、降低熔融制样的稀释比、高压激发和改善谱线重叠干扰是解决稀有金属分析困难的有效途径。
要点(1) 制备便于保存和反复测量的小尺寸样片是XRF定量分析小样品量和珍贵样品的关键。
(2) XRF散射效应能够为成分未知样品的分析、异质性样品原位分析的误差校正提供有力贡献。
(3) 超细粉末制样、稳定剂的加入和标准加入法建立工作曲线是利于XRF准确测定易挥发元素的有效方法。
(4) 采用人工配置的标样或与样品性质相似的二级标样建立并优化工作曲线、降低熔融制样的稀释比、高压激发和改善谱线重叠干扰是解决稀有金属XRF分析难题的有效途径。
HIGHLIGHTS(1) Preparation of small beads or pellets which are easy to preserve and repeated measurement is the key for quantitative analysis of small size samples and precious samples with XRF.
(2) The XRF scattering effect can provide a powerful contribution to the analysis of samples with unknown composition and the error correction of the in situ analysis of heterogeneous samples.
(3) Preparation of ultrafine powder pellet, addition of stabilizer and standard addition method establishing work curve are effective approaches for volatile element analysis by XRF.
(4) Constructing and optimizing the work curve with artificial standard samples or secondary standard samples, preparing low-dilution (sample to flux ratios) glass beads, exciting samples at high X-tube voltage and overcoming overlap interference of spectral lines are effective ways to analyze the rare metals with XRF.
Abstract:X-ray fluorescence spectrometry (XRF) has become one of the widely used methods for main and trace elements analysis in geological samples, due to its characteristics of non-destructive, fast, environmentally-friendly and high analytical precision. Currently, XRF can qualitatively and quantitatively analyze most of the major and trace elements (4Be−92U, especially 10Na−92U) with the concentration ranges from μg/g to percent. However, there are still some difficulties in practical analysis of geological samples with XRF due to the complexity and diversity of mineral composition, physical structural characteristics (e.g. size, shape, delamination and inclusions) and chemical composition (e.g. elemental composition, chemical morphology) of geological samples. This paper elaborates difficulties and corresponding possible solutions of XRF analysis in geological samples from five aspects including small size samples or precious samples analysis, the application of scattering effect, the analysis of volatile elements, variable valence elements and rare metals. Finally, the limitations and challenges of the XRF technique that still exist in the geological analysis are presented. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202403150052.
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Keywords:
- X-ray fluorescence spectroscopy /
- small size samples and precious samples /
- scattering effect /
- volatile elements /
- variable valence elements /
- rare metals
BRIEF REPORTX-ray fluorescence spectrometry (XRF) analysis of geological samples is often performed using solids or powder, which can avoid the time-consuming complex pretreatment process of wet chemical technology and the use of a large number of toxic and harmful chemical reagents[2-5]. Nowadays, XRF has been widely used in the fields of petrology, geochemistry, chronology, mineral resources and environmental geoscience[9-11]. However, there are often some difficulties in the practical analysis of geological samples using XRF due to the complexity of geological samples and the characteristics of the elements themselves. Some difficulties and the corresponding possible solutions in geological analysis with the method of XRF are reviewed here, including small size samples or precious samples analysis, the application of scattering effect, the analysis of volatile elements, variable valence elements and rare metals.
1. Analysis of small size samples and precious samples
Preparation of small beads or pellets which are easy to preserve and repeated measurement is the key for XRF quantitative analysis of geological samples on a small scale. Sometimes, it is necessary to analyze small size samples or precious samples with XRF, such as meteorites or extraterrestrial samples (for example, lunar samples) as well as banded iron formation[12], loess strata[13] and periodically banded rocks within zebra rock[14] which can be drilled from banded positions using micro drilling. Such samples can only be qualitative or semi-quantitative by scanning electron microscopy, micro X-ray fluorescence spectrometry or laser ablation-inductively coupled plasma-mass spectrometry as in previous studies. Some researchers have found that preparation of small beads or pellets which are easy to preserve and repeated measurements yield more accurate quantification with XRF.
2. Application of the scattering effects
Scattering effects are used to obtain more information about the chemical composition in samples with unknown elemental composition. The calibration curve of Compton-to-Rayleigh intensity ratio versus average atomic number can provide important information when samples with unknown compositions are studied under the same geometrical conditions and at the same energy. First, construct a calibration curve of Compton-to Rayleigh intensity ratio with respect to the average atomic number using reference materials with well-known chemical composition. Then, the concentration of the elements might be indirectly obtained from scattering X-ray peaks of the samples[19]. This method of the evaluation of an unknown specimen is particularly sensitive for a light matrix.
Scattering effects are beneficial for matrix correction of heterogeneous sample in situ analysis. Researchers have studied the element distribution characteristics of bryophyte-soil-rock interface samples[20]. It was found that the correction method with Ray*Ray/Com is suitable for CaKα, MnKα, FeKα, CuKα, ZnKα and PbLα whereas the correction with Ray/Com is good for KKα. When the elements’ intensity was corrected by the respective suitable methods, the spectra of K, Ca, Pb, Zn and Cu reached the maximum peaks at the soil layer in interface samples. This exploration is useful for the study of biogeochemical interface processes of the interest elements.
3. Analysis of the volatile elements
Volatile elements such as C, S and halogen are difficult to analyze accurately with XRF in both the fusion method and pressed powder pellet in general conditions. The fusion method often leads to the measured value drop. Whereas the measurement accuracy is not ideal either using the pressed powder pellet because of the influence of mineral effect and particle effect. Researchers found that the mineral effect and particle effects can be minimized by ultra-fine grind, and that the uncertainty of the analysis results reduced in response[21]. Besides, The addition of stabilizer can inhibit the volatilization of volatile elements such as S at high-temperature in the melting process, so the analytical accuracy can also be improved[26].
4. Analysis of the variable valence elements
The characteristic X-ray spectral peak position, and the shape and relative intensity of the spectral line can be affected by the atomic valence states and coordination states[32-33]. Some researchers used the relative intensity of Fe Kβ5/Kβ1,3 as an analytical parameter to analyze the content of divalent iron (FeO) in igneous rocks. Chubarov, et al.[33] analyzed the valence state and form of manganese in various kinds of manganese ore by S8 Tiger-type wavelength dispersive X-ray fluorescence spectrometer, so that the quality of manganese ore can be accessed quickly without complex processes.
5. Analysis of the rare metals
Constructing and optimizing the work curve with artificial standard samples or secondary standard samples are effective ways to analyze the rare metals with XRF[36]. Zhou et al.[37] expanded the word curve linear range of La, Ce and Y by adding high purity rare earth oxides La2O3, CeO2 and Y2O3 in the analysis of rare earth minerals and mineralized samples. Silva et al.[38] added the secondary standard to establish the work curve and used the empirical coefficient method to optimize the calibration curve for analysis of La, Ce, Nd, Sm and Gd in Amazon cassiterite tailings. The results of precision and accuracy tests using the CRM (Diorite Gneiss-CCRMP) was satisfactory. Coefficients of variation of five analyzed elements except Gd were less than 5%. The analytical recovery of five elements were between 103% and 116%.
Preparing low-dilution (sample to flux ratios) glass beads facilitates the determination of rare metals using XRF. Nakayama et al.[40] determined 42 components in felsic rocks using XRF. Low-dilution glass beads with 1∶1 of sample-to-flux ratios were prepared to measure Sc, Sn, Cs, Hf, Ta and rare earth elements. Calibration curves of the components showed good linearity (r=0.991−1.000). Ichikawa et al.[41] developed a low-dilution glass-bead method to determine 34 components including rare metals in basaltic and granitic rocks using XRF. The calibration curves present good linearity (r>0.990).
High-energy excitation may help the determination of rare metals in geological samples. Generally, the L line of rare elements is selected as the analytical line because the K line of rare elements cannot be excited by conventional X-ray tubes. However, high-energy polarization XRF can effectively stimulate the K series of rare metals. The overlap interference of K line of rare metals is less and the excitation factor of the K line is larger than the L line, so the excitation efficiency is greatly improved. Researchers developed a method for multi-element analysis of rare earth elements in soil, rock and deposits using high-energy polarized energy dispersive X-ray fluorescence spectrometer. The excitation voltage of the rare earth elements is up to 100kV. The calibration lines show great linearity (the correlation coefficients r>0.99 for La, Ce, Pr, Nd and Y, the rest of rare earth elements r>0.969)[44].
Overlap interference correction of the spectral lines sometimes plays a key role in rare metals analysis [42,45]. For example, Maritz et al.[45] analyze the trace elements in soil. There were significant differences between the measured values and recommended values of Hf and Ta elements because of the ignoring of overlap interference between Cu Kα1 lines and Hf Lα1 and Ta Lα1 lines. Some other researchers fully considered the overlap interference of Ta Lα1 (0.1522nm) and Cu Kα1 (0.1541nm) in the determination of Ta, Cs and other rare metals in rocks[42]. The measurement bias was not significant according to the criterion of negligible error and student’s distributions.
6. Challenges and perspectives
The limitations and challenges of the application of XRF technology in geological analysis are still prominent: (1) The accuracy of analysis results depends on standard material, especially for geological samples with complex composition, which requires samples with similar physical and chemical properties to participate in the calibration curve; (2) It is still difficult to quantitatively determine the light elements whose atomic number Z<8. In the future, with advances in particle physics, optical systems and detection devices, it is believed that these limitations will be overcome. In addition, with the integrated development of earth sciences in recent years, XRF technology has also developed toward a broader and more dimension-focused direction. New technologies related to XRF, such as micro XRF, X-ray absorption spectrum and portable XRF, are playing an increasingly important role in geoscience field.
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金(Au)是中国重要的战略性资源，但金矿的金品位普遍较低，需借助半自磨机或搅拌磨降低颗粒粒度并促进金相颗粒解离［1-2］。为获得较高的金精矿品位，提高金元素富集比，通常需利用复杂的多次粗选扫选和精选配合的浮选工艺，而在长流程浮选体系中，以镍、铜、镉、铅等为代表的有害元素选择性富集或随机分散在各工艺产品中［3-4］，影响了各金矿浮选产品的质量，但当前针对金矿浮选过程中有害元素定量的研究较少，有必要建立金矿浮选样品中有害元素的检测方法。
金矿中有害元素含量与金品位相当，但相对于金矿主量伴生元素则存在巨大的浓度差异；而高基体背景下准确定量有害元素的关键是如何有效地控制或消除基体差异带来的非质谱干扰［5-6］。虽然目前分析检测手段已逐步应用于选矿领域，但较多的是针对原矿的工艺矿物学分析，即在分析含金组分的赋存形态、嵌布特征基础上为金矿磨浮工艺优化提供支撑［7-9］。一些痕量元素定量的检测方法包括电感耦合等离子体发射光谱或质谱法(ICP-OES/MS)［10-13］、辉光放电质谱法［14-16］、X射线衍射法(XRD)［17-18］等，在分析复杂基体样品时通常会使用基体纯净的标准溶液或物质，难以高质量校正待测元素标准溶液与样品消解液之间的基体差异。上述检测手段配合基体匹配方法的检测领域，多为基体唯一的合金钢中杂质元素定量，譬如张馨元等［19］分别利用无基体匹配和2000μg/mL镍基体的铜、锌、钡元素标准溶液来定量镍基高温合金标准物质中痕量铜锌钡，前者测试结果较认定值存在15%～20%偏差，而后者检测结果均在标准物质中痕量元素认定浓度范围内。沈健等［20］利用基体匹配ICP-MS测定煤中钽铀镱含量时，采用标准煤样消解液为基体，配制待测元素标准溶液,但未关注标准煤样消解液中无机组分的基体影响，欠缺标准煤样所含微量钽铀镱元素对标准曲线线性和方法检测下限的讨论。因此，当前针对复杂基体自然矿产中有害元素的准确定量方法，仍需进一步优化研究。
本文以金矿浮选过程样品为研究对象，采用基体匹配ICP-MS测试方法，在明确各样品基体元素种类后，开展高浓度基体溶液添加痕量有害元素的测定实验，分析基体种类和浓度对有害元素定量结果相对偏差的影响。在此基础上，利用高浓度基体有害元素标准溶液对金矿各浮选样品进行定量实验，与纯试剂有害元素标准溶液定量结果和测试过程内标回收率比对，并通过消解加标、测试加标以及平行实验分析基体匹配ICP-MS方法的准确度和精密度，评估方法的测试质量。
1. 实验部分
1.1 样品信息
研究对象为金矿浮选矿浆产品，采自紫金矿业集团股份有限公司某金矿选厂，采集物料包括浮选入料、各浮选段精矿和尾矿产品。取样前准备足够数量的料筒并做好标记，样品采集工具为取样勺。浮选入料由溜槽给入浮选设备，取样时使用取样勺对整个料流截面均匀取样；浮选精矿泡沫取样则是用取样勺截取全部溢流面；浮选尾矿取样是用取样勺对准矿浆流取样。每个样品采集点的取样时间均为10min。
1.2 样品前处理
采用实验室小型过滤机处理某金矿浮选流程的22个矿浆产品(样品编号为样品1～样品22)，获得各样品滤饼及滤液。滤饼置于烘箱中105℃干燥3h后冷却，缩分后用于样品消解与元素组成分析。为确保有害元素全部从固体矿物转移至溶液，减少有害元素定量的制样误差，样品消解以溶液澄清、无固体颗粒残留为目标。消解实验采用耗酸少、速度快的微波消解，经探索确定了如下消解方案。
(1) 样品称取0.1g，置于可溶性聚四氟乙烯消解罐中；
(2) 向消解罐中加入3.75mL盐酸、1.25mL硝酸和2mL氢氟酸；
(3) 将消解罐置于微波消解仪中，升温到150℃，保持20min；再升温至220℃，保持40min，取下冷却后在通风橱内缓慢泄压后打开消解罐；
(4) 将消解罐置于石墨赶酸仪中，180℃开盖赶酸，待样品蒸干后取下冷却，加入1mL浓硝酸复溶后加超纯水定容至100mL。
经测试，微波消解过程空白中镍、铜、镉和铅元素含量分别为0.2741μg/L、0.3435μg/L、0.0019μg/L和0.0263μg/L。消解过程空白溶液中的有害元素含量较低，对样品中的有害元素定量结果影响较小。
1.3 标准物质和主要试剂
镍、铜、镉、铅单元素标准储备液(1×106μg/L，美国Agilent公司)；Re内标储备溶液(100μg/mL，美国Agilent公司)，使用时稀释至0.5μg/mL。
硫标准溶液(2×104μg/mL，购自钢研纳克有限公司)；铁和铝则分别选用分析纯标准物质三氧化铁和三氧化铝，用硝酸溶解，获得质量浓度为10mg/mL的单元素溶液。
UPS级纯硝酸、盐酸和氢氟酸(晶锐电子材料股份有限公司)。
超纯水(ELGA Option Q15 纯水机纯化，电阻率≥18MΩ·cm)。
1.4 实验仪器
浮选样品元素组成分析采用S8 Tiger型X射线荧光光谱仪(德国Bruker有限公司)，并通过元素校正曲线定量。
样品中痕量有害元素定量采用Aglient 7900电感耦合等离子体质谱仪(美国Aglient公司)，仪器测试参数列于表1。
表 1 电感耦合等离子体质谱仪测试条件Table 1. Measurement parameters of ICP-MS instrument工作参数 设定值 工作参数 设定值 射频功率 1550W 截取锥直径 0.45mm 取样深度 8mm 扫描方式 跳峰方式 等离子气体(Ar)流速 15L/min 每峰点数 1 辅助气体(Ar)流速 0.80L/min 扫描次数 100 载气(Ar)流速 1.05L/min Cd元素积分时间 1s 镍采样锥直径 1mm Ni、Cu、Pb等
元素积分时间0.30s 本文使用的Agilent 7900型电感耦合等离子体质谱仪，配备了碰撞反应池，可有效地降低有害元素含量测试的质谱干扰；此外，定量测试中还针对性地选择了质量数干扰最低的同位素，即60Ni、65Cu、111Cd和208Pb。金矿浮选样品消解液中的主量基体元素在测试过程会产生非质谱干扰，对有害元素离子流形成抑制。为削弱该影响，本文采用高浓度的代表性基体元素标准溶液稀释有害元素储备溶液后，形成复杂基体有害元素标准溶液。与纯试剂有害元素标准溶液相比，复杂基体有害元素标准溶液与金矿浮选样品消解液具有同一数量级的基体背景［21］，再配合内标元素铼(Re，浓度0.50μg/mL)后，可有效地抑制非质谱干扰。
基体匹配ICP-MS方法研究中(技术路线如图1所示)，首先使用XRF确定主量基体元素，然后利用基体元素标准溶液配制具有浓度梯度的有害元素标准溶液；利用ICP-MS测试具有浓度梯度的有害元素标准溶液后，获得各有害元素标准曲线；在读取有害元素测试背景值后，调整配制复杂基体有害元素标准溶液所需的基体元素标准溶液与有害元素储备液体积，进而获得有害元素浓度准确的复杂基体有害元素标准溶液，提升基体匹配ICP-MS方法测试结果的准确性。
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图 1 基体匹配ICP-MS法测定金矿浮选样品中有害元素的实验流程Figure 1. Experimental flow chart for the determination of harmful elements in flotation samples of gold ore by the method of matrix matching coupled with ICP-MS1.5 数据质量控制
方法准确性：在样品消解和测试环节，采用标准加入方式评价金矿浮选样品中痕量有害元素定量方法的准确性。称取0.10g的14号样品两份，其中一份加入有害元素镍、铜、镉和铅各10μg，消解后定容至100mL测试。分别称取0.10g的6号和13号样品，消解定容至100mL后取两份平行样，一份直接测试，一份加入浓度100μg/L等体积的复杂基体有害元素标准溶液后混匀后测试。
方法精密度：分别称取6份5号和12号样品，每份质量0.10g，按照1.2节样品前处理方法消解获得平行消解溶液后测试各样品中有害元素含量，并计算各有害元素定量结果的相对标准偏差(RSD)。
2. 结果与讨论
2.1 浮选样品的主量基体元素组成
22个金矿浮选样品的主量元素及含量分析结果列于表2。受浮选过程的各组分分离和富集作用影响，样品中主量基体元素种类及含量有所差异。依据元素组成，将样品分为铝基体(样品编号：1、7、14和22)，铁硫基体(样品编号：2、3、8、10、12和13)，铁铝基体(样品编号：4～6、9、11和15～21)共计三类(Si元素在消解中与氟结合形成四氟化硅SiF4挥发［22-23］，因而未将Si列为基体元素)。4种铝基体样品中铝含量接近(1号样品主量元素仅为Si，为简化样品种类将其归类为铝基体样品)；6种铁硫基体各样品中铁和硫元素含量差异在10%附近(8号样品主量元素仅为Fe，为简化样品种类将其归类为铁硫基体样品)；12种铁铝基体样品的Si、Fe、Al元素含量均较为接近。
表 2 金矿浮选样品的主量基体元素种类及含量Table 2. Major matrix elements in flotation samples of gold ore样品编号 基体类型 主要元素及含量 样品编号 基体类型 主要元素及含量 1 铝基体 Si (29.75%) 5 铁铝基体 Si (27.66%); Fe (10.60%); Al (10.27%) 7 Si (29.84%); Al (9.78%) 6 Si (28.66%); Fe (8.27%); Al (10.58%) 14 Si (31.27%); Al (10.43%) 9 Si (27.93%); Fe (9.35%); Al (11.02%) 22 Si (30.47%); Al (9.63%) 11 Si (24.76%); Fe (15.85%); Al (10.99%) 2 铁硫基体 Si (14.92%); Fe (22.87%); S (12.76%) 15 Si (26.64%); Fe (10.74%); Al (10.23%) 3 Si (19.06%); Fe (22.36%); S (13.52%) 16 Si (28.45%); Fe (10.33%); Al (10.95%) 8 Si (13.16%); Fe (23.50%) 17 Si (27.75%); Fe (10.97%); Al (10.60%) 10 Si (14.08%); Fe (20.57%); S (17.27%) 18 Si (25.64%); Fe (10.92%); Al (10.17%) 12 Si (13.59%); Fe (26.39%); S (22.35%) 19 Si (28.27%); Fe (11.21%); Al (10.71%) 13 Fe (30.48%); S (24.16%) 20 Si (26.96%); Fe (9.39%); Al (10.38%) 4 铁铝基体 Si (25.89%); Fe (14.46%); Al (10.37%) 21 Si (27.43%); Fe (10.62%); Al (10.84%) 2.2 高浓度基体对镍铜镉铅元素测试准确性的影响
为探究高浓度基体加入对Ni、Cu、Cd和Pb元素含量测试准确性的影响，分别利用基体元素浓度为500μg/mL和1000μg/mL的一种和两种基体元素溶液稀释500μg/L纯试剂有害元素标准溶液，获得理论浓度为10μg/L的复杂基体有害元素标准溶液。随后，利用纯试剂有害元素标准溶液测试(内标选用185Re)并扣除基体溶液中有害元素含量(譬如1000μg/mL铝基体中，Cu元素浓度为11μg/L)，计算测试结果的相对偏差，结果列于表3。整体上，高浓度基体元素溶液对痕量有害元素在ICP-MS测试过程的影响较小。与理论值(10μg/L)相比，不同浓度和基体元素种类溶液中各有害元素定量结果的相对偏差在±10%以内。因此，利用复杂基体有害元素标准溶液进行金矿浮选样品中有害元素的定量测试，是可行的。
表 3 不同浓度/种类基体元素溶液中痕量有害元素定量的相对偏差Table 3. Relative deviation of each hazardous element after adding different concentrations/types of matrix elements基体元素及浓度
(μg/mL)各有害元素测定值与理论值的相对偏差(%) Ni Cu Cd Pb 铝(500) −0.85 7.96 −0.74 3.00 铁(500) −4.62 6.74 −2.31 −0.79 硫(500) −5.22 3.46 −3.85 6.29 铁硫(500) 0.97 9.72 −9.32 2.03 铁硫(1000) −1.97 8.31 −7.07 1.22 铁铝(1000) 5.74 −5.42 −2.70 −2.48 2.3 基体元素对金矿浮选样品中有害元素定量影响
选择金矿浮选8号样品(铁硫基体)、9号样品(铁铝基体)、13号样品(铁硫基体)和17号样品(铝基体)共4种代表性样品，在分别配制1000μg/mL铝元素、铁元素、硫元素、铁硫、铁铝元素基体溶液后，将有害元素标准储备液逐级稀释至10、20、50、100、200和500μg/L(因铝基体溶液中含一定量Cu，配制铝和铁铝基体的有害元素标准溶液时，依据Cu含量再次计算所用有害元素标准储备液、铝溶液、铁溶液和稀硝酸的用量)，测试样品中Ni、Cu、Cd、Pb含量。此外，同步开展纯试剂(2%硝酸)有害元素标准溶液对代表性样品中有害元素定量测试。依据公式(1)将液体样品中的有害元素含量(单位μg/L)转换为固体中的有害元素含量［24］(单位μg/g)。
$$ c=\frac{\left(c_1-c_0\right) \times V \times d}{m} \times 10^{-3} $$ (1) 式中：c为样品中有害元素含量(μg/g)；c1和c0分别为消解稀释液和消解过程空白中有害元素浓度(μg/L)；V为消解液体积，此处为100mL；d为稀释倍数，根据样品浓度与方法定量上限确定；m为样品质量，此处为0.10g。
不同基体有害元素标准溶液对部分金矿浮选样品中有害元素的定量结果列于表4。譬如，铁硫基体样品分别用铁基体、硫基体、铁硫基体和纯试剂有害元素标准溶液测试，其他样品测试安排以此类推。表4数据显示在1000μg/mL基体浓度前提下，复杂基体有害元素标准溶液中基体元素种类和数量，对金矿浮选样品中有害元素测试结果并未产生明显影响。复杂基体与纯试剂有害元素标准溶液，对4个代表性金矿样品中有害元素定量结果的相对标准偏差小于7.73%(大部分小于5%)。因此，可利用有害元素标准溶液开展不同基体类型的所有金矿浮选样品中有害元素的定量分析。
表 4 不同基体有害元素标准溶液对部分金矿浮选样品中有害元素定量分析结果Table 4. Quantification results of harmful elements in some gold ore flotation products using standard solutions of harmful elements in various matrixes样品编号 有害元素标准溶液
基体元素Ni测定值
(μg/g)Cu测定值
(μg/g)Cd测定值
(μg/g)Pb测定值
(μg/g)8号样品
(铁硫基体)铁硫 363.38 596.78 24.61 1540.22 铁 344.59 547.18 23.88 1569.77 硫 372.52 564.39 24.15 1611.48 纯试剂 356.31 574.64 23.50 1625.51 RSD(%) 3.28 3.63 1.94 2.46 9号样品
(铁铝基体)铁铝 112.66 186.65 2.32 263.37 铁 113.77 196.41 2.52 292.44 铝 117.31 210.64 2.57 294.22 纯试剂 115.64 194.62 2.32 264.84 RSD(%) 1.79 5.07 5.41 6.06 13号样品
(铁硫基体)铁硫 336.18 311.63 17.54 1135.47 铁 294.45 315.54 19.18 1199.29 硫 301.20 321.80 19.05 1145.17 纯试剂 317.10 366.45 18.89 1322.70 RSD(%) 5.95 7.73 4.07 7.17 17号样品
(铝基体)铝 124.75 303.10 2.23 275.80 2%硝酸 118.06 288.17 2.20 257.33 RSD(%) 3.90 3.57 0.96 4.90 本文首先使用不同基体元素的复杂基体有害元素标准溶液测试对应基体类型样品中有害元素含量，然后利用铁硫基体有害元素标准溶液开展铝基体和铁铝基体样品中有害元素测试。不同基体的有害元素标准溶液对金矿浮选样品中有害元素定量结果列于表5。利用不同基体元素的有害元素标准溶液对各金矿浮选样品中有害元素的定量结果接近，各有害元素的回收率在80%～120%范围内。因此，在1000μg/mL基体浓度前提下，有害元素标准溶液的基体元素差异并未对测试过程产生影响，基体匹配方法中使用铁硫基体有害元素标准溶液，能够获得准确的测试结果。
表 5 不同基体有害元素标准溶液对铝基体和铁铝基体金矿浮选样品中有害元素测试结果Table 5. Quantification results of harmful elements in gold ore flotation samples with Al- and Fe-Al matrix using standard solutions of harmful elements in various matrixes.样品编号 有害元素标准溶液基体元素 Ni
(μg/g)Cu
(μg/g)Cd
(μg/g)Pb
(μg/g)有害元素标准溶液基体元素 Ni
(μg/g)Cu
(μg/g)Cd
(μg/g)Pb
(μg/g)1 铝 58.62 67.33 1.60 102.58 铁硫 57.22 63.85 1.61 90.96 7 44.56 102.80 0.71 96.42 42.56 98.20 0.63 96.06 14 59.10 125.33 1.00 108.18 59.10 116.57 0.82 119.4 22 34.18 63.03 0.32 70.24 36.13 65.14 0.34 66.88 4 铁铝 160.93 282.57 5.40 497.02 160.93 267.77 5.41 513.4 5 94.30 249.38 5.21 436.7 116.83 206.86 5.89 377.65 6 82.92 159.46 2.45 265.68 92.34 140.05 2.24 254.67 9 112.66 186.65 2.32 263.37 120.39 161.81 2.05 225.93 11 197.97 340.82 6.22 697.57 197.97 290.04 6.31 663.41 15 105.21 428.65 2.25 303.61 111.45 365.18 1.86 303.45 16 107.84 338.23 1.87 186.06 96.84 297.13 1.55 183.48 17 124.75 303.10 2.23 275.8 115.88 297.02 2.10 264.64 18 149.36 422.74 2.51 266.65 136.23 441.74 2.15 268.78 19 68.25 384.89 1.85 256.20 56.95 341.4 1.74 263.90 20 86.69 250.90 1.99 152.05 95.12 253.08 1.83 173.13 21 94.00 349.36 2.40 282.20 92.33 358.58 2.30 276.88 为进一步比较复杂基体与纯试剂有害元素标准溶液对金矿浮选样品有害元素测试过程的影响，对比两类有害元素标准溶液测试22个金矿样品内标回收率，如图2所示(图中样品编号1~7为标准溶液，编号8~29代指金矿浮选的1~22号样品)。基体匹配方法测试各样品内标回收率较纯试剂测试稳定，前者的回收率分布在90%～110%之间，后者则在85%～100%之间。基体匹配测试各样品内标回收率与100%差值绝对值的平均差为1.64%，而后者则为2.16%(平均差，即各差值绝对值与其平均数的离差绝对值的算术平均数)，基体匹配法内标回收率平均差较无基体匹配测试低24.07%。纯试剂有害元素标准溶液与消解样品之间有较大的基体差异，在一定程度上对元素离子化产生抑制作用。采用基体匹配方法可降低非质谱干扰，削弱测试过程的信号波动。
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图 2 铁硫基体与纯试剂有害元素标准溶液测试金矿浮选样品的内标回收率Figure 2. Recovery of internal standard of gold ore floatation samples using harmful element standard solutions with Fe-S matrix compared with that of pure regent2.4 基体匹配ICP-MS法的测试质量评估
2.4.1 方法准确度
在样品消解和测试环节，采用标准加入方式评价金矿选冶样品中有害元素定量方法的准确性。消解和测试加标实验参照1.6节所述，各元素加标回收率列于表6。根据表中数据计算，消解加标实验中各有害元素加标回收率在92.08%～105.36%之间，表明微波消解过程中各有害元素基本无损失；而测试加标实验中各有害元素加标回收率在95.68%～106.05%之间，显示不同基体类型样品的消解溶液对加标有害元素回收率影响较小，与2.2节实验结果相呼应。较好的加标回收率指标表明此测试方法准确性高。
表 6 消解和测试加标回收实验结果Table 6. Results of spiked recovery experiment for the dissolution and measurement样品名称 Ni测定值
(μg/g)Cu测定值
(μg/g)Cd测定值
(μg/g)Pb测定值
(μg/g)14号样品 59.10 116.57 0.82 119.40 14号样品+10μg各元素(消解) 161.72 221.93 97.55 211.48 加标回收率(%) 102.62 105.36 96.73 92.08 6号样品 92.34 140.05 2.24 254.67 6号样品+等体积标液(测试) 97.08 122.16 50.22 177.92 加标回收率(%) 101.82 104.27 98.20 101.17 13号样品 336.18 311.63 17.54 1135.47 13号样品+等体积标液(测试) 215.93 208.84 57.71 619.26 加标回收率(%) 95.68 106.05 97.88 103.05 2.4.2 方法精密度
两组样品的6个平行消解实验样品中有害元素的测定结果列于表7。整体上，平行实验中元素含量较低的Cd元素的RSD值相对较高，但高浓度元素的RSD值则较低。各元素的RSD在1.21%～4.69%之间。精密度实验的指标较高，数据波动小，重现性高。
表 7 加标回收实验结果Table 7. Results of spiked recovery experiments样品编号 元素 6次平行实验检测值(μg/g) 平均值
(μg/g)RSD
(%)5号样品 Ni 116.83 119.04 114.52 121.75 118.08 111.61 116.97 3.04 Cu 206.86 208.96 212.57 204.88 210.73 209.09 208.85 1.31 Cd 5.89 5.98 5.66 5.42 6.07 6.15 5.86 4.69 Pb 377.65 360.19 384.57 366.42 379.76 359.97 371.43 2.86 12号样品 Ni 330.05 344.47 327.59 335.04 338.73 349.62 337.58 2.50 Cu 356.31 347.87 342.46 360.93 354.52 361.42 353.92 2.11 Cd 20.18 18.25 18.57 19.62 19.74 20.09 19.41 4.16 Pb 1227.43 1268.87 1239.15 1241.06 1251.53 1231.50 1243.26 1.21 3. 结论
提出采用基体匹配ICP-MS法定量金矿浮选样品中的痕量有害元素。首先采用XRF确认各浮选样品的主量基体元素后，将其分为铝基体、铁铝基体和铁硫基体三类。在500μg/mL和1000μg/mL基体溶液中，基体元素种类和数量对痕量有害元素定量结果差异较小，其相对偏差在±10%以内。表明采用高浓度的基体元素溶液配制有害元素标准溶液，不会对有害元素定量结果产生影响，且复杂基体有害元素标准溶液在定量金矿浮选样品中有害元素时还可起到削弱基体差异的作用。在有害元素标准溶液基体浓度相同(1000μg/mL)的前提下，金矿浮选样品中有害元素定量结果不受基体元素种类和数量影响，且与纯试剂有害元素标准溶液定量结果的相对标准偏差小于7.73%，而内标回收率与100%理想值差值绝对值的平均差较纯试剂有害元素标准溶液测试低24.07%。因此，采用了铁硫基体有害元素标准溶液测试不同基体类型的金矿浮选样品，该方法消解和测试的加标元素回收率在92.08%～105.36%之间，测试环节加标回收率为95.68%～106.05%，精密度(RSD)为1.21%～4.69%，具有准确度高的特点。
本文方法虽仅针对金矿浮选样品中部分有害元素的定量测试，但对于其他复杂金属矿产或合金类等样品中的痕量有害元素测试仍具有借鉴意义和实践参考，在地质矿产样品检测领域具有一定实用性。
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图 1 (a)制备微玻璃珠试样时，将混合粉末放置在Pt-Au坩埚中的工艺原理图；(b)用硅胶聚合物黏合剂将微玻璃珠(直径约3.5mm)安装在直径35mm的空白玻璃片上；(c)附着在35mm空白玻璃片上的微玻璃珠的两个表面：(1)平面；(2)半球面。修改自文献［16］
Figure 1. (a) Schematic diagram of process to place the mixture powder in a Pt crucible for preparation of a micro glass bead specimen; (b) Top-view photograph of the micro glass bead (approximately 3.5mm diameter) after mounting on the 35mm glass bead blank using silicone polymer adhesive; (c) Comparison of the two available analytical surfaces of the micro glass bead attached on the 35mm glass bead blank: (1) Flat-surface and (2) Hemispherical-surface. Modified from the reference［16］.
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图 2 在45kV，用多毛细管X射线光学仪器在散射角为155.5°的几何结构下，用Rh靶X射线管激发获得的康普顿散射与瑞利散射强度比(ICo/IRa)与平均原子序数(Z)的校准曲线。修改自文献［19］
Figure 2. Calibration curve for the Compton-to-Rayleigh intensity ratio (ICo/IRa) versus mean atomic number (Z) for an excitation with a Rhodium anode X-ray tube, at a high voltage of 45kV, using polycapillary X-ray optics and under a geometry with a scattering angle of 155.5°. Modified from the reference［19］.
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图 3 在相同的实验条件下测量了两种托帕石晶体的XRF光谱(a)。为了更好地呈现散射线的细节，将17keV到23keV的区域(b)放大显示，对应托帕石2的谱线平移到更高能量0.3keV处。修改自文献［19］
Figure 3. XRF spectra of two topaz crystals measured under the same experimental conditions (a). For better visibility of the details of the scattering contributions, a magnified region from 17keV to 23keV is shown (b). Note that the energy scale corresponding to the topaz 2 spectrum has been shifted to higher energies by 0.3keV. Modified from the reference［19］.
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图 5 (a)波长0.151～0.156nm的X射线荧光光谱谱图(CRM-MA-N元素含量：Ta 290mg/kg，Cu 140mg/kg)；(b)波长0.128～0.136nm的X射线荧光光谱图(CRM-MA-N元素含量：Ta 290mg/kg，Ga 59mg/kg，Zn 220mg/kg，W 70mg/kg，Nb 173mg/kg)。修改自文献［42］
Figure 5. (a) X-ray spectrum within the range of wavelengths from 0.151nm to 0.156nm. CRM-MA-N with the elemental contents: Ta 290mg/kg, Cu 140mg/kg; (b) The spectral distribution within the range of wavelengths from 0.128 to 0.136nm. CRM-MA-N with the elemental contents: Ta 290mg/kg, Ga 59mg/kg, Zn 220mg/kg, W 70mg/kg, Nb 173mg/kg. Modified from the reference［42］.
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