Rapid Determination of Trace Impurity Elements in Pure Molybdenum by Inductively Coupled Plasma-Mass Spectrometry Based on the Online-Standard-Addition Method
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摘要:
纯钼的纯度或杂质含量对材料性能有重要的影响，痕量杂质的准确测量是产品质量控制的关键。电感耦合等离子体质谱法(ICP-MS)由于具有高灵敏、多元素同时测量的优势，是测量痕量杂质的最有效方法之一；但在测量高浓度纯钼基体中的痕量杂质时，会产生较强的基体抑制效应，严重影响测量结果准确性。基体匹配法、标准加入法以及基于同位素丰度比值测量的同位素稀释质谱法(IDMS)可以有效地补偿复杂的基体效应，获得准确的测量结果；但步骤繁琐、分析效率低、分析成本高使其难以满足高通量的测量需求。本万工作集成了标准加入法的准确性及在线自动分析的高效性，基于标准加入法的原理，通过双路进样，将样品溶液与标准溶液(系列标准溶液依次自动进样)同时引入三通进行混合，然后经过雾化进入ICP-MS进行检测，从而建立了基于在线加标的ICP-MS法。该方法有效地补偿了高浓度试样的基体效应，通过样品-标准进样流量差异的校正，提高了测量结果的准确性，实现了纯钼中29种痕量杂质元素的快速准确测量，满足了纯钼中痕量杂质标准物质的准确定值要求。经考察，本工作建立的方法对29种元素的方法检出限(MDL)在0.004～0.90μg/g之间，标准加入法标准曲线的线性相关系数r基本大于0.999，除Ca、Zn由于沾污问题导致的测量准确性较差外(Ca、Zn相对偏差分别为32%、13%)，27种元素的测量相对偏差在−6.8%～5.1%之间。将Cr、K测量结果与IDMS法比较，进一步验证了该方法的可靠性。结果表明，两种方法测量结果偏差在1%以内，且具有相当的精密度(本方法对于Cr、K的RSD为1.8%～3.2%，IDMS法的RSD为0.9%～1.4%)，但本方法分析效率与分析成本具有明显的优势，经评估15min可完成29种元素的测量，分析效率比IDMS法可提高上百倍，能够满足高通量的样品测试需求。
Abstract:BACKGROUNDMolybdenum (Mo) is widely used in aerospace, nuclear industry, integrated circuits, flat display and photovoltaic solar energy and other fields[2-4]. The purity or impurity content of high purity molybdenum has an important effect on material properties, so the accurate measurement of trace impurities is the key to quality control. In the China national standard “Molybdenum Powder” (GB/T 3461—2016), the limits of impurities such as Pb and Bi which are commonly in the range of 5 to 50mg/kg, are specified. Rapid and accurate analysis of trace or ultra-trace impurities is necessary with the development of high purity Mo requirements of high throughput analysis. The ICP-MS method has become the most powerful method for trace impurities analysis in high purity Mo, but the tedious and time-consuming matrix effect calibration strategies makes it a big challenge to achieve rapid and accurate analysis. ICP-MS has the advantages of high sensitivity, good accuracy and the possibility of simultaneous measurement of multiple elements, compared with AAS, ICP-OES, and GD-MS methods. However, the matrix effect is heavy in the analysis of high purity Mo, which seriously affects the accuracy of the measurement results. Matrix matching method, standard addition method and isotope dilution mass spectrometry (IDMS) based on isotope abundance ratio measurement can effectively compensate for the complex matrix effect, and accurate analytical results can be obtained, but the analysis processes are complicated, the efficiency is low, and the cost is high, making it difficult to meet the measurement requirements of high throughput. To meet the requirements of rapid analysis, on-line analysis based on flow injection[28] and tandem calibration[29] was used. The online matrix separation and pre-concentration process for flow injection not only eliminates the matrix effect and reduces the detection limits, but also improves the automation level, and achieves high throughput measurement[31-33]. Wang et al.[32] measured a variety of trace metal elements in seawater samples within 28.5min based on online ion exchange. An online calibration process through a new analytical methodology called tandem calibration could be achieved based on a dual sample introduction system with two nebulizers working in parallel[29] or a multiple-channel nebulizer[34], for which the special design of the nebulizer is necessary.
OBJECTIVESTo develop a rapid and accurate method for the analysis of trace impurities in high purity molybdenum to meet the requirements of high throughput sample tests.
METHODSA dual-channel simultaneous sampling ICP-MS measurement method based on online-standard-addition was established by calibrating the difference in sample-standard injection flow rate. The in-house online platform was set up based on an auto-sampler and two peristatic pumps. The pure Mo reference material candidates containing homogeneous impurities with mass fraction of 0.1-200μg/g were used as samples. About 0.1g sample was digested based on the China national standard GB/T 4325.26—2013 and diluted about 1000-fold for analysis. The digested sample solution was introduced from a tube (designated as A) continuously by using a peristaltic to a T-joint in which the sample solution and a series of standard solutions from another tube (B) using an auto-sampler were mixed thoroughly. The mixed solutions were introduced through a nebulizer and rotary spray chamber, ionized in the plasma, and then introduced to mass spectrometry for analysis. For more accurate results, the difference flow rate between the sample and standard tube (the internal diameter of the sampling tube was 0.25mm and 0.38mm for the sample and standard, respectively) was calibrated by using the 20ng/mL standard solution. The ratio (R1) of intensity using A tube injection to the intensity using B tube injection was 1.54±0.06 for each element, indicating the difference of injection flow for A and B tube. The ratio of intensities for simultaneous sample injection to the sum intensities of A and B injection respectively was about 1.
RESULTSMethodological parameters for ICP-MS method based on online-standard-addition were evaluated in terms of method detection limit (MDL), linearly dependent coefficient, precision and accuracy. The limits of detection of this method based on the 3-σ criterion ranged from 0.004μg/g to 0.90μg/g for 29 elements, which meets the requirements of trace impurities analysis. The linear correlation coefficient r of the standard curve was mostly more than 0.999 at the concentration range of 0-500ng/g. The precision was evaluated by introducing the Mo digested solutions from A tube and 5ng/mL standard solution from B tube simultaneously, and the relative standard deviations (RSDs) of 6 repeated measurements were low, ranging from 0.8%-3.9% for 28 elements, in spite of the relative high RSD for Nb (6.1%). The multi-elements standard solution of GBW(E)082429, GBW(E)082430, GBW(E)082431were used for accuracy evaluation. After flow rate calibration, the relative deviation (RDs) between measured values and certified values ranged from −6.8% to 5.1% for 27 elements. For Ca and Zn, the RDs were relatively large (32% for Ca and 13% for Zn), which was probably due to the contamination. To further evaluate the method reliability, the analytical results of K and Cr were compared with those by using the IDMS method. Relative deviation of less than 1% between the two methods was found. Calibration of the difference for flow rate between the sample and standard injection. When the sample and standard is introduced from different tubes or nebulizers, the efficiency should be calibrated. The mathematical correction used was first introduced by Salin et al.[36] A dual sample introduction system based on two nebulizers working in parallel was set up by Canals et al.[29] The transport efficiencies for online standard addition were calibrated and the deviations of less than 3% for Na, K, Ba and Rb elements analysis in different matrixes were obtained. Different from the reported systems which needed to be specially designed[29,34], the online platform in this work was simple and easy to apply, because it only used a T-joint for the mixing of the sample and standard. This similar setup was found elsewhere[37-38]. In this setup, the same nebulizer was used for the sample and standard solution, and thus the same nebulization efficiency was obtained. The difference of signals between using A tube injection and B tube injection only resulted from the flow rates. In the flow process, fractionation could not occur. Therefore, the very consistent R1 factors were found for different elements, which indicated that it was not needed for the measurement of R1 factors for all elements. The merits of online-standard-addition ICP-MS method.Satisfactory limits of detection were obtained for 29 elements ranging from 0.004μg/g to 0.90μg/g, which was better than the MDL derived from the China national standard GB/T 4325.26—2013(1μg/g) and was comparable with the reported method based on ICP-MS/MS[6]. In fact, compared with the traditional standard addition method, the online method would attenuate the MDL due to the dilution of sample solution, although Schwartz et al.[37] deemed that there was no obvious difference between online and traditional methods in terms of SNR (Signal to Noise Ratio) and precision. The good precision 0.8%-3.9% for 28 elements was better than literature[37-38]. Apart from Ca and Zn, the satisfactory accuracy for 27 elements (relative deviation ranged from −6.8% to 5.1%) was obtained, which was better than the online internal standard method[39] because of the calibration of matrix effect for the standard-addition method. The comparative results of Cr and K by using the online-standard-addition method (this work) and the IDMS method showed good agreement of ±1%, which further validates the reliability of this work. It can be concluded that the accuracy and precision of this established method were comparable with the IDMS method. However, the analysis efficiency and cost showed obvious advantages, because the measurement of 29 elements could be completed in 15min, and thus the analysis efficiency was hundreds of times higher than that of the IDMS method.
CONCLUSIONSThe method combined the properties of high accuracy and high throughput, and thus can achieve rapid and accurate trace impurities analysis in pure Mo.
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Keywords:
- standard addition method /
- online sample introduction /
- high purity molybdenum /
- trace impurity analysis /
- matrix effect /
- inductively coupled plasma-mass spectrometry
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砂岩型铀矿是一种具有重要工业价值的铀矿类型[1]，具有规模大、埋藏浅、开采成本低等特点[2-3]，是我国目前铀矿资源勘查开发的主要矿床类型。详细研究砂岩型铀矿矿物学岩石学特征、矿物共生组合关系和铀矿物赋存状态特征，对成因探究及找矿勘探具有重要意义，也可为该类型矿床的选冶开采及资源评价提供依据。
砂岩型铀矿中铀矿物粒度细小，赋存形式多样，因此很难准确地对矿床中铀矿物赋存状态进行全面系统的研究。目前主要采用放射性照相和电子探针两种分析手段，前者可一次性得到光片中所有铀矿物位置、形态及分布特征等信息，并可由此推断其矿物种类以及在光片中的大致含量，是早期铀矿物研究的主要手段，但该方法需要在暗室中进行曝光，再根据径迹形态特征对放射性元素进行定性定量解释[4]；后者可以通过背散射图像详细观察铀矿物形态特征及其与其他矿物的接触关系，并可获得详细的元素含量数据，但该方法需要分析人员在高倍数背散射图像下对整个样品逐区扫描、寻找疑似铀矿物，再结合能谱、波谱数据判断矿物种类和共生矿组合[5]，且在黑白的背散射电子图像下只能通过亮度区分矿物，极容易忽略亮度相近但成分不同的矿物。矿物自动定量分析系统是一套基于扫描电镜的软件[6]，可对样品自动进行扫描、测量和统计[7]，目前常见的矿物自动定量分析系统有AMICS、MLA、QSMSCAN等[8]。AMICS是被广泛应用的矿物自动识别和表征系统，数据库超过2000种矿物，测试过程时间短、能量消耗少、测试精度较高，主要应用于矿床和工艺矿物学研究[6, 9]。
本文运用AMICS系统，与扫描电镜(SEM)、能谱仪(EDS)相结合，对鄂尔多斯盆地砂岩型铀矿床的铀矿物种类和赋存状态进行研究，并由此建立了一套AMICS-SEM-EDS原位分析技术，实现了矿石矿物的快速识别与鉴定，查明了研究区铀矿物类型和其他伴生矿物，为砂岩型铀矿的基础研究提供技术方法支撑。
1. 地质背景
鄂尔多斯盆地是一个古生代地台及台缘坳陷与中新生代台内坳陷叠合的克拉通盆地[10-11]，蕴含丰富的铀、石油、天然气等多种能源矿产，北起伊盟隆起，南至渭北隆起，西自西缘逆冲带，东达晋西挠褶带(图 1)，跨陕、甘、宁、蒙、晋5省(区)[12]。鄂尔多斯地区的基底岩系具有明显的双层结构，结晶基底由太古界及下元古界的麻粒岩相、角闪岩相的变质岩和混合花岗岩组成；基底岩系之上的沉积盖层各时代地层发育全、沉积类型多、旋回性明显，其中三叠系、侏罗系和白垩系下统是盆地沉积盖层的主体[13-16]，铀矿化主要在中侏罗直罗组[17-18]，铀矿化受灰绿色-灰色砂岩控制, 矿(化)体位于二者过渡部位近灰色砂体一侧，以层状、板状为主[19-20]。盆地构造及演化控制了含铀岩系、容矿砂体和成矿深度[21-22]，铀是在同一成岩动力作用和相似物化条下逐步富集成矿的[23-24]，同位素年代学研究数据表明，鄂尔多斯盆地铀成矿时代具有多期多阶段性，且多期成矿作用通常相互叠加[25-27]。
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图 1 鄂尔多斯盆地区域构造纲要及研究区位置图(据刘池洋等，2005修改)Figure 1. Regional structure and study area location map of Ordos Basin (According to Liu, et al., 2005)鄂尔多斯盆地从边缘到中心，含铀砂岩的颜色呈现红-绿-灰垂直分带现象[28]。本次所采集的赋矿砂体主要为浅绿色-灰色中粗粒杂砂岩、灰色细粒砂岩，还有部分为紫红色粉砂岩、砂质泥岩和含碳砂岩。赋矿砂岩的矿物成分主要为石英、钾长石、斜长石以及岩屑，还含有黄铁矿、金红石、钛铁矿、云母、细粒黏土矿物和碳质碎屑等，填隙物主要为泥质、碳质物，还含有少量黄铁矿等金属矿物。
2. 实验部分
2.1 样品采集与制备
鄂尔多斯盆地是我国砂岩型铀矿勘查和研究的热点地区，具有铀矿化分布广泛、绕盆地边缘产出、矿化层位较多且分布不均、铀矿物种类较多等特点[29]。盆地北缘含矿砂岩主要为灰色-灰绿色岩屑长石石英砂岩，云母含量较高(5%~8%)，接触胶结为主，该地区铀矿物类型以铀石为主，还有少量沥青铀矿[30]；盆地南缘含矿砂岩以灰色、灰绿色长石石英砂岩，黄铁矿及有机质含量较高，多为泥质胶结，局部钙质胶结，铀矿物类型以晶质铀矿、沥青铀矿为主，含少量铀石和硅钙铀矿[31]；盆地西缘宁东地区蚀变分带明显，含矿砂岩主要为绿灰色中粗粒砂岩，铀矿物主要有沥青铀矿、铀石和少量胶磷矿[32]。
本次样品主要采集于鄂尔多斯盆地北缘的塔然高勒(样品号15EE-01、16NM01、16NM02)，南缘的黄陵(样品号16HL01)，西缘宁东地区(样品号16NX01-02)，如图 1所示。北缘地区样品主要为浅灰色-灰绿色中粗粒砂岩，南缘多为灰色含炭屑中砂岩，部分样品含黄铁矿及有机质条带，西缘主要为灰色、绿灰色中-粗粒长石石英砂岩，可见炭屑及黄铁矿等还原介质。
选取不同地区具有代表性的样品磨制探针片103件，并对全部探针片进行表面喷碳处理以增加样品导电性。
2.2 实验仪器和测试条件
本文主要的实验分析工作在河南省岩石矿物测试中心完成。测试系统包括一台德国蔡司的MERLIN Compact场发射扫描电镜、一台德国布鲁克XFlash6160电制冷能谱仪以及AMICS矿物自动定量分析软件系统。运用AMICS系统识别鉴定矿石矿物，实验条件为：加速电压12kV，工作距离10.2mm，物镜光栏60μm，高真空模式。随后通过AMICS系统驱动扫描电镜到达选定区域进行局部放大观察并拍照，利用能谱仪获得制定矿物元素含量，实验条件为激发电压20kV，工作距离8.5~11.8mm，点分析采集时间达到250kcps自动停止，高真空模式。
后期电镜赋存状态研究与电子探针定量分析是在中国地质调查局天津地质调查中心完成的。使用库塞姆EM-30Plus台式电镜，在高倍数下观察铀矿物形态、粒度及嵌布特征，加速电压为20kV，工作距离10.8mm，高真空模式；利用岛津公司EPMA-1600电子探针，对通过AMICS系统识别的矿物进行定量分析，以验证AMICS系统识别的准确性，加速电压为15kV，束流20nA，束斑直径5μm，采用ZAF法校正。
2.3 实验方法
样品经表面喷碳处理后置于扫描电镜样品室，在高真空模式下调节并进行观察。首先，整体观察。在较小倍数下运用AMICS软件扫描矿石薄片，识别并鉴定矿石矿物组成及分布特征，查找铀矿物并确定其位置。此步单次扫描范围较广，重点在于整体把握岩石薄片情况，在测试中通常会出现局部信息缺失，但若缺失部分不影响整体观察，可不必在此步耗费大量时间调节参数设置。
第二步，局部扫描。选取铀矿物所在位置或其他感兴趣区域，运用AMICS系统驱动电镜到达制定位置，在高倍数背散射图像下仔细观察铀矿物赋存特征，用能谱详细分析铀矿物元素种类和含量，用AMICS系统获得伴生矿物组成及相互关系。此步骤需根据样品特征精确调试AMICS相关测试参数，在测试过程中若出现“未识别”或“计数率低”等情况需不断尝试不同参数值，直到找到适合该区域的参数范围，从而获得更加精准的数据和图像。
最后，综合对比AMICS面分析图、背散射电子图和能谱数据，获得矿石矿物组成及其嵌布关系、铀矿物种类及其赋存特征等信息，对关键矿物再运用电子探针进行进一步确认。
3. 结果与讨论
3.1 铀矿物赋存状态特征
砂岩型铀矿床中铀矿物主要赋存于矿化砂岩的填隙部位，部分以分散形式被黏土矿物、碎屑物或矿物颗粒表面或裂隙吸附[33]。利用扫描电镜和AMICS技术对鄂尔多斯北缘、南缘地区样品铀矿物及其共生组合进行观察、识别，发现几个地区铀矿物赋存状态特征整体较为一致，以独立铀矿物为主，多与黄铁矿、金红石、石英、长石等共生。
首先，空间上，铀矿物主要赋存于矿化砂岩的裂隙部位、碎屑物或矿物的孔洞和解理中，或矿物颗粒的晶隙或边缘部位(图 2a，b)，部分以分散形式存在的铀矿物被砂岩缝隙中的黏土矿物、碎屑物等吸附[34]。
其次，形态上，研究区铀矿物主要以隐晶质集合体的形式产出，集合体通常在几十到几百微米不等，多以皮壳状(图 2c)、星点状或球粒状(图 2d)、网脉状(图 2e)、不规则状等形式产出；铀矿物内部或边缘常见不规则状干裂纹，球粒状、皮壳状集合体内部则经常可见同心或韵律条环带，这主要与矿物沉积间断有关[35]。铀矿物晶体非常细小且很少能见到，主要呈显微粒状、棱角状，他形，独立分布在其他矿物晶隙中(图 2f)，粒度在1~30μm不等，仅在电子显微镜下可见，在背散射图像下亮度明显高于周围其他矿物，内部则较为均一。
在矿物共生组合方面，利用AMICS系统分析得到的图像上可以看出，研究区与铀矿物共生的矿物主要有石英、黄铁矿、金红石、钾长石、斜长石、黑云母、方解石、钛铁矿、高岭石等。其中铀矿物与黄铁矿关系密切[36]，总是分布在黄铁矿边缘以及内部的孔洞和裂隙中，有些甚至边界不清，相互穿插(图 3)。金红石也常与铀矿物紧密伴生，关系密切；另外，在石英、长石的晶隙之间也常见铀矿物集合体，铀矿物和这些矿物接触边界清晰，基本无相互穿插现象。
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图 3 沥青铀矿及其共生矿物组合背散射电子图像和AMICS分析图像Figure 3. Backscattered electron images and AMICS diagrams of uraninite and its association minerals3.2 铀矿物的种类和成分特征
铀矿物是指以铀元素为基本组分的矿物[1]。本文铀矿物种类和成分信息均通过扫描电镜和能谱仪分析得到，加速电压均为20kV。对研究区铀矿物进行能谱点分析，得到谱图及元素百分比，整理发现研究区铀矿物种类较多，成分方面均以O、Si、U等元素为主但不同类型矿物含量差别明显，并且常常含有Th、V、Ti、S、Ca等元素(图 4和图 5)。本次样品中发现的铀矿物包括有铀石、沥青铀矿、晶质铀矿、硅钙铀矿和其他含铀矿物。
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图 4 四种铀矿物背散射电子图像和能谱图像a—铀石；b—晶质铀矿；c—沥青铀矿；d—硅钙铀矿。Figure 4. Backscattered electron images and energy dispersive spectrometer diagrams of four uranium minerals![]()
图 5 三种铀矿物背散射电子图像和能谱图像a—钍石；b—钍石；c—金红石。Figure 5. Backscattered electron images and energy dispersive spectrometer diagrams of three uranium minerals3.2.1 铀石
铀石是铀矿床中较为常见的原生铀矿物，理想化学式为U[SiO2]1-x(OH)4x，四方晶系[37-39]，晶体呈短柱状或粒状，集合体呈放射状、晶簇状、星点状等。铀石常与沥青铀矿在成矿过程中交替形成，且不十分稳定，易转化为沥青铀矿[39-40]。铀石是鄂尔多斯盆地常见的铀矿物类型[14, 19]。
本工作中，铀石多出现在鄂尔多斯盆地北缘的样品中，主要以集合体的形式存在，分布范围较为广泛，可达几百微米，呈晶簇状、放射状等，与金属硫化物主要是黄铁矿紧密伴生，赋存在黄铁矿内部空洞、边缘或粒间晶隙中，其他伴生矿物主要有长石、石英、绢云母和独居石等(图 4a)。能谱分析得到铀石的平均化学组成为：O 32.29%，U 53.17%，Si 13.86%，Na 0.68%。
3.2.2 沥青铀矿
沥青铀矿又称非晶质铀矿，是晶质铀矿的变种。理想化学式为(U4+，U6+)O2，沥青黑色，等轴晶系[37]，常呈肾状、钟乳状、鲕粒状和细脉状等[38-39]。
盆地南缘和西缘的样品中沥青铀矿更为常见[29]，以胶状集合体的形式分布于矿物边缘，有时作为胶结物分布在石英、长石的颗粒间。沥青铀矿在北缘样品中经常与铀石、黄铁矿密切共生，三者成分差异很大，在背散射图像显示出来的亮度有明显区别：沥青铀矿最亮，呈亮灰白色，铀石亮度相对较弱[35]，呈浅灰色，而黄铁矿亮度最小，呈深灰色。三者经常相互掺杂，边界模糊(图 4c)。沥青铀矿成分中主要元素的平均含量为：U 13.28%，O 69.11%，Si 12.60%，Al 3.91%，Ti 0.59%，Fe 0.51%。
3.2.3 晶质铀矿
晶质铀矿理想化学成分为UO2[37]，晶体属等轴晶系的氧化物矿物，晶形呈立方体或八面体[38-39]，一般呈他形细粒状产出。样品中晶质铀矿含量较少，通常以粒状或粒状集合体的形式出现，与黄铁矿关系密切，部分可见赋存于石英、长石的颗粒周围以及裂隙间，粒度通常在1~5μm左右，他形粒状或不规则棱角状(图 4b)；能谱得到成分中主要元素的平均含量为：O 36.36%，U 53.21%，Si 7.65%，Na 0.99%，Ca 1.17%，Al 0.62%。
3.2.4 硅钙铀矿
硅钙铀矿化学式为Ca[UO2(SiO3OH)2·5H2O，单斜晶系[37-39]，晶体呈针状或长柱状，集合体呈放射状、纤维状、薄膜状或致密块状[35, 40]。
硅钙铀矿大量发现于鄂尔多斯盆地南缘的样品中[28]，主要呈他形，单矿物颗粒在几微米到几十微米不等，但集合体分布范围较为广泛，这些集合体在石英等矿物的表面及裂隙中呈网脉状、脉状、星点状、毛刺状等分布，局部与黄铁矿紧密共生(图 4d)。能谱分析显示硅钙铀矿主要元素的平均含量为：O 22.60%，U 65.14%，Si 8.38%，V 1.23%，Ca 1.92%，Na 0.73%。
3.2.5 其他含铀矿物
除铀矿物外，本次样品中还发现大量含铀副矿物，铀元素以类质同象形式[5]赋存于钍石、锆石、金红石等矿物中。
(1) 钍石。钍石的化学组成为Th[SiO4]，晶体属四方晶系的岛状结构硅酸盐矿物[38]，钍石的成分变化很大，钍可以被铀、钙、稀土等类质同象代替[39]。样品中发现的含铀钍石呈他形粒状，赋存在石英的裂隙间，被石英包裹，粒度在20μm左右，颗粒破碎严重、裂隙较多，在背散射图像下亮度明显高于其他不含铀矿物。能谱分析显示其主要元素有Th、O、Si、U，还有少量P、Ca等(图 5a)。
(2) 锆石。锆石的化学组成为Zr[SiO4]，晶体属四方晶系的岛状结构硅酸盐矿物[38]，有时含有Th、U、Ti、Mn、Ca、Fe等元素。样品中锆石主要呈他形粒状，粒度几微米到几十微米不等，能谱分析显示，其主要元素为Zr、O、Si，有时还有少量Al、Ca等(图 5b)，铀元素含量在0.3%~1.5%之间。
(3) 金红石。金红石的成分均为TiO2，类质同象替代有Fe、Th、U等元素。样品中金红石呈他形粒状，背散射下亮度略高于其他不含铀矿物，但比铀矿物亮度低。主要元素有Ti、O、Fe，还有少量Al，铀元素含量在0.3%~1.2%不等，普遍高于普通金红石中铀元素的含量(图 5f)。
3.3 鄂尔多斯盆地北-南-西缘铀矿物赋存状态异同
研究发现，鄂尔多斯盆地北缘、南缘和西缘常见的铀矿物均为沥青铀矿和铀石，铀矿物普遍与黄铁矿和钛氧化物紧密共生，但不同地区铀矿物赋存状态也存在差异。盆地北缘矿物类型与其他两地略有不同，铀矿物以铀石为主，而沥青铀矿含量较少。扫描电镜观察到铀石主要呈晶簇状或粒状集合体形式出现，主要赋存于碎屑颗粒填隙部位，与黄铁矿、金红石、长石、石英、黏土矿物等伴生。盆地南缘以沥青铀矿为主，铀石次之，还有部分硅钙铀矿。沥青铀矿主要呈胶状，赋存于碎屑颗粒边缘形成镶边结构，尤其是黄铁矿边缘，常见的伴生元素有V、Se、S等。盆地西缘以沥青铀矿为主，其次为铀石，伴生矿物主要有黄铁矿、石英、方解石、锐钛矿等。
综上，鄂尔多斯盆地铀矿物以沥青铀矿和铀石为主，还可见少量硅钙铀矿、晶质铀矿等，伴生矿物主要为黄铁矿、钛氧化物等。中国北方其他大型砂岩型铀矿还有二连盆地、松辽盆地等，二连盆地铀矿物有沥青铀矿、铀石、铀的磷酸盐等，与鄂尔多斯盆地铀矿物种类较为相似[41]，而松辽盆地多为铀石和富铀-铁钛氧化物，与鄂尔多斯盆地区别较大[42]。
3.4 铀矿物常用分析方法在实际应用中的优势与不足
砂岩型铀矿中的铀矿物通常粒度细小，赋存于裂隙、孔洞中，形态复杂多样，分布较为分散，因此在进行铀矿物赋存状态研究中，寻找铀矿物并鉴定其类型、查明矿物共生组合需结合多种测试手段[30]。本文对同一批样品分别采用目前铀矿物赋存状态研究中经常使用的几种测试方法进行测试，通过实际操作对比了这些方法的优势与不足。
首先是放射性照相法。该方法是将光片粘贴在胶片上，在暗室中接受铀矿物辐照，一段时间后取出底片冲洗，根据成像特征获取铀矿物所在位置赋存状态。实验中发现，放射性照相通常在光片上进行，薄片成像的效果较差；放射性照相必须在暗室中进行，整个实验周期在30~40天左右；实验可以得到铀矿物赋存位置、赋存形态和放射性形态，但无法得到具体矿物种类以及伴生矿物组合，还需要配合较长时间的光学显微镜和电子探针进行鉴定，分析时间及经济成本较高。
然后是电子探针法。首先利用背散射图像，在高倍数下人为逐区蛇形扫描光薄片，寻找亮度较高的矿物再结合能谱快速获得元素种类及含量，从而鉴定其矿物类型，随后选点进行波谱分析。能谱可准确地对含量达千分之一的元素进行分析，每个点分析时长仅需不到1min；波谱分析精度较高，能准确对含量达万分之一的元素进行分析。通常，在200~300倍下扫描一个薄片需3h左右(无论该薄片中是否有铀矿物)，若还需进行波谱点分析，则每个点分析时间在20min左右。该方法可以得到精美的铀矿物背散射照片以及较为精确的元素含量，但在黑白的背散射图像下，只能通过亮度来判断矿物种类的差异，容易忽略画面中亮度相同但种类不同的矿物，无法准确获得矿物伴生组合，后期还需光学显微镜辅助。
AMICS系统软件可以驱动扫描电镜，结合能谱仪可以实现测试样品所选区域自动位移扫描并同时采集不同物相的X射线能谱数据，根据AMICS矿物标准库的X射线能谱信息进行物相鉴定，通过计算机自动拟处理，可以帮助研究者快速、直观、准确地获得被测样品所选区域矿物种类、嵌布特征、形态、粒度、元素含量等信息[7-8]。首先，整体快速扫描，在较小倍数下运用AMICS软件扫描矿石薄片，识别矿石矿物组成及分布特征，查找铀矿物并确定其位置。此过程每个薄片需30min左右，若未找到铀矿物，则直接进行下一个薄片。若发现研究对象，则进行下一步局部精细扫描：选取感兴趣区域，运用AMICS系统驱动电镜到达指定位置，在高倍数背散射图像下仔细观察铀矿物赋存特征，能谱详细分析铀矿物元素种类和含量，AMICS系统获得伴生矿物组成及相互关系。此过程仪器自动扫描，测试时长与目标区域矿物复杂程度有关，一般在30min~3h不等。
AMICS-SEM-EDS分析技术联用可以同时获得物相信息和元素含量，且仅需在配有能谱仪和AMICS软件系统的扫描电镜下，就能完成对各矿物总体形貌、类型等观察并拍摄背散射图像，从而清楚、直观地识别出各铀矿物的形态、空间分布以及与其他矿物的共存关系，亦可以同时获得铀矿物的各项元素分析数据，较大地提高了工作效率。在实际测试中，有时由于样品表面不够平整或参数设置等问题，会导致局部信息无法识别或计数率低，一般会有1%~5%的未知物相无法定名和归类[43]。因此需要根据不同类型的样品选择不同的测试参数，在测试过程中根据所出现的问题及时调整，从而找到适合被测样品的参数范围，以求获得更加精准的数据和图像。另外，由于AMICS系统基于计算机软件的分析计算，遇到复杂的矿物边缘或细小的矿物时通常会存在一定误差，因此需要我们在研究中综合对比BSE图像和AMICS图像，从而获得更为准确的结论。在未来的研究中，可进一步探究AMICS参数设置对不同样品分析数据和图像的影响，以获得更加精准的数据和图像。
4. 结论
本文运用自动矿物分析系统-扫描电镜-能谱相结合的原位分析方法，对鄂尔多斯盆地北-南-西缘砂岩型铀矿的矿石矿物进行了识别、鉴定和赋存状态研究，查明了研究区铀矿物类型包括铀石、沥青铀矿、晶质铀矿和硅钙铀矿，与铀矿物共生的矿物有石英、黄铁矿、金红石、长石、云母、高岭石等。其中铀矿物与黄铁矿关系密切。盆地北缘铀矿物以铀石为主，而西缘、南缘则以沥青铀矿为主。
本文通过AMICS整体快速扫描—局部观察及能谱分析—AMICS精细扫描三个步骤，为砂岩型铀矿基础研究工作提供了一种行之有效的测试方法，建立了AMICS-SEM-EDS分析技术，为铀矿物及其共生矿物组合的快速识别鉴定、赋存状态研究以及矿物相扫描提供了一套便捷、高效、可靠的分析方法。在未来的研究中，可进一步探究AMICS参数设置对不同样品分析数据和图像的影响，找到适合砂岩型铀矿分析的合适参数范围，以获得更加精准的数据和图像。该方法在铀矿床矿物学、岩石学等基础研究中有望得到更广泛的应用，并可在其他不透明金属矿物研究中进行推广。
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图 1 在线加标ICP-MS测量方法平台示意图(实验室搭建)
Figure 1. Schematic diagram of the ICP-MS measurement method platform based on online-standard-addition. The platform was in-house set up based on an auto-sampler and two peristaltic pumps. The digested sample solution (③) was introduced from B tube continuously by using a peristaltic (④) to a T-joint (⑤) in which the sample solution from B and a series of standard solutions (②) from A tube using an auto-sampler (①) were mixed thoroughly. After that, the mixed solutions were introduced through nebulizer (⑥)and rotary spray chamber (⑦), ionized in the plasma (⑧), and then introduced to mass spectrometry (⑨) for analysis.
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图 2 不同管路进样的元素(按质量数排序)离子强度比较：(a)离子强度值；(b)离子强度比值
Figure 2. Comparison of signal intensities of elements or ratios of signal intensities by using different pipelines for sample injections. The elements shown were in order of mass numbers shown in Section 2.1. The intensities of elements for sample injection from A (or B) tube represent the intensities that the standard solution with nominal mass fraction of 20ng/mL was introduced from A (or B) tube，and at the same time the blank solution (2% HNO3) was introduced from B (or A) tube，shown in Fig.2(a). For the simultaneous sample injection means that the 20ng/mL standard solution was introduced from A and B tube at the same time. The intensities of elements for simultaneous sample injection were compared with the sum of the intensities using A tube and B tube sample injection, respectively, shown in Fig.2(a). The ratio of intensity using A tube injection to the intensity using B tube injection was about 1.5 for each element, indicating the difference of injection flow for A and B tube, shown in Fig.2(b). The ratio of intensities for simultaneous sample injection to the sum intensities of A and B injection respectively was about 1, shown in Fig.2(b).
表 1 在线加标ICP-MS法检出限、精密度、标准曲线线性方法学参数
Table 1 Methodological parameters for ICP-MS method based on online-standard-addition. The method detection limit (MDL) was evaluated based on the 3σ criterion. The precision was represented by the relative standard deviation (RSD) of 6 repeated measurements. The linearly dependent coefficient r was evaluated based on the concentration range of 0-500ng/g.
元素 检出限
(μg/g)RSD
(%，n=6)线性相关系数
r元素 检出限
(μg/g)RSD
(%，n=6)线性相关系数
rB 0.44 3.3 0.9566 Zn 0.10 2.2 0.9999 Na 0.19 1.7 0.9998 Ga 0.004 3.3 0.9998 Mg 0.17 3.9 0.9995 As 0.10 3.5 0.9997 Al 0.25 0.8 0.9999 Sr 0.013 2.0 0.9997 Si / / 0.7839 Zr 0.075 2.0 1.0000 P 0.32 1.3 0.9986 Nb 0.057 6.1 0.9999 K 0.90 3.9 0.9998 Cd # # −0.3704 Ca 0.16 3.2 0.9998 Sn 0.018 1.8 0.9986 Ti 0.12 1.1 1.0000 Sb 0.054 1.1 0.9905 V 0.018 2.6 0.9999 Ba 0.071 3.9 0.9998 Cr 0.033 2.0 0.9997 Hf 0.023 3.8 0.9990 Mn 0.046 1.7 0.9999 Ta 0.059 2.9 0.9985 Fe 0.18 1.4 0.9999 W 0.12 2.0 0.9999 Co 0.014 1.6 0.9999 Pb 0.021 3.4 0.9997 Ni 0.080 1.0 0.9998 Bi 0.012 2.7 0.9997 Cu 0.10 3.0 0.9995 注：“/”表示对于Si元素，由于空白值较高，故未列出检出限及RSD数据；“#”表示对于Cd元素，由于MoO及MoN的干扰在非基体分离条件下无法去除，故未列出检出限及RSD数据。 
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表 2 在线加标ICP-MS法方法验证
Table 2 Method validation for ICP-MS method based on online-standard-addition. The calibrated values were calculated based on the measured values multiplied by the intensity ratio R1. For the certified values (or nominal values), the calculated values were used based on the certified values of standard solutions and the dilution factors. The relative deviations (RDs) between the calibrated values and certified values were used to evaluate the method reliability and accuracy and calculated by using the equation: RD=(calibrate values-certified values)/certified values×100%.
元素 测量值
(ng/g)强度比值
R1*校正值
(ng/g)理论值**
(ng/g)相对偏差##
(%)B 14.1 1.48 20.9 20.6 1.8 Na 13.2 1.60 21.0 21.6 −2.5 Mg 14.4 1.52 21.9 21.6 1.3 Al 13.8 1.54 21.3 21.6 −1.5 Si 79.5 1.12 88.8 20.6 /＆ P 13.3 1.59 21.1 20.6 2.8 K 13.5 1.54# 20.8 21.6 −3.5 Ca 18.2 1.57 28.6 21.6 32.0 Ti 12.9 1.60 20.7 20.6 0.5 V 13.8 1.58 21.7 21.6 0.6 Cr 13.6 1.56 21.2 21.6 −1.7 Mn 13.5 1.63 22.0 21.6 2.1 Fe 13.2 1.62 21.4 21.6 −0.9 Co 12.8 1.67 21.4 21.6 −0.8 Ni 14.4 1.58 22.7 21.6 5.1 Cu 13.0 1.66 21.5 21.6 −0.4 Zn 15.2 1.60 24.3 21.6 13.0 Ga 13.5 1.61 21.8 21.6 0.9 As 14.1 1.55 21.7 21.6 0.8 Sr 13.9 1.53 21.2 21.6 −1.8 Zr 13.4 1.52 20.4 20.6 −0.9 Nb 12.9 1.52 19.6 20.6 −4.6 Cd 17.6 1.51 26.5 21.6 /＆ Sn 16.1 1.50 24.1 24.3 −0.7 Sb 15.7 1.59 25.0 24.3 2.8 Ba 14.0 1.50 21.0 21.6 −2.5 Hf 16.8 1.50 25.3 24.3 4.2 Ta 13.5 1.53 20.5 20.6 −0.1 W 13.3 1.50 19.9 20.6 −3.4 Pb 13.8 1.46 20.1 21.6 −6.8 Bi 14.3 1.48 21.1 21.6 −2.1 注：“*”表示R1为标准进样管(A管)与样品进样管(B管)相同浓度溶液信号强度比，为流量差异校正因子； “**”表示理论值为标准溶液稀释(500倍)后计算得出的浓度值，标准物质原浓度为10mg/kg，扩展不确定度为3(k=2)； “#”表示采用其他元素的比值平均值；“＆”表示对于111Cd，由于受到95Mo16O的干扰，因此采用简单酸基体溶液难以评估其可靠性，故未列出相对偏差；对于Si，由于使用氢氟酸导致测量空白严重偏高，故未列出相对偏差；“##”通过公式计算：(校正值-理论值)/理论值×100%。
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表 3 在线加标-ICP-MS法与同位素稀释质谱法的测量结果比较
Table 3 Comparison of the measurement results by using ICP-MS method based on online-standard-addition and using isotope dilution mass spectrometry, respectively. The relative standard deviations (RSDs) and standard deviations (SDs) of 4 repeated measurements were listed for each element.
元素 含量测定值(μg/g) 在线加标ICP-MS法* RSD
(%)同位素稀释质谱法* RSD
(%)Si / / 24.8±1.5 6.0 K 87.4±2.8 3.2 87.7±0.8 0.9 Cr 50.1±0.9 1.8 50.4±0.7 1.4 注：“*”表示平均值±SD(n=4)；“/”表示由于采用氢氟酸消解，Si空白较高，故未列出测量结果及RSD数据。
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表 4 纯钼粉标准物质候选物样品中杂质元素测量结果
Table 4 Measurement results of impurity elements in high purity molybdenum powder reference material candidate sample by using ICP-MS method based on online-standard-addition. The relative standard deviations (RSDs) of 4 repeated measurements were listed.
元素 含量测定值
(μg/g)RSD
(%，n=4)元素 含量测定值
(μg/g)RSD
(%，n=4)B ＜1.5 / Zn ＜0.3 / Na 73.4 5.7 Ga 0.4 46 Mg 85.1 1.8 As 1.2 24 Al 18.1 1.3 Sr 17.8 3.4 Si / / Zr 16.4 3.0 P 83.3 1.9 Nb ＜0.2 / K 87.4 3.2 Cd / / Ca 18.6 7.0 Sn 171.2 2.6 Ti 99.6 2.2 Sb 150.1 2.9 V 17.7 3.4 Ba 18.2 3.0 Cr 50.1 1.8 Hf 16.7 1.4 Mn 178.4 1.5 Ta 19.4 1.7 Fe 122.5 2.8 W 18.7 5.1 Co 20.2 0.9 Pb 1.5 9.4 Ni 31.6 0.6 Bi 1.5 10 Cu 199.2 1.5 / / /
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[1] 安耿, 李晶, 刘仁智, 等. 钼溅射靶材的应用、制备及发展[J]. 中国钼业, 2011, 35(2): 45−48. doi: 10.3969/j.issn.1006-2602.2011.02.013 An G, Li J, Liu R Z, et al. The application, manufacture and developing trend of molybdenum sputtering target[J]. China Molybdenum Industry, 2011, 35(2): 45−48. doi: 10.3969/j.issn.1006-2602.2011.02.013
[2] 刘元元. 高纯镁和高纯钼的质谱纯度分析及其结果不确定度评定[D]. 北京: 钢铁研究总院, 2018. Liu Y Y. Study on the purity analysis method by mass spectrometry and its uncertainty evaluation for magnesium & molybdenum[D]. Beijing: Central Iron & Steel Research Institute, 2018.
[3] Ye Z, Tan C, Huang X, et al. Emerging MoS2 wafer-scale technique for integrated circuits[J/OL]. Nano-micro Letters (2023-01-18)[2023-07-18]. https: //link. springer. com/article/10. 1007/s40820-022-01010-4.
[4] Santagata A, Pace M L, Bellucci A, et al. Enhanced and selective absorption of molybdenum nanostructured surfaces for concentrated solar energy applications[J]. Materials, 2022, 15(23): 8333. doi: 10.3390/ma15238333
[5] 杨帆, 王快社, 胡平, 等. 高纯钼溅射靶材的研究现状及发展趋势[J]. 热加工工艺, 2013, 42(24): 10−12. doi: 10.14158/j.cnki.1001-3814.2013.24.020 Yang F, Wang K S, Hu P, et al. Research status and development tread of high purity molybdenum sputtering target material[J]. Hot Working Technology, 2013, 42(24): 10−12. doi: 10.14158/j.cnki.1001-3814.2013.24.020
[6] 符靓, 施树云, 唐有根, 等. 高纯钼粉中超痕量杂质的质谱分析[J]. 光谱学与光谱分析, 2018, 38(8): 2588−2594. Fu L, Shi S Y, Tang Y G, et al. Analysis of ultra-trace impurities in high purity molybdenum powder trough inductively coupled plasma tandem mass spectrometry[J]. Spectroscopy and Spectral Analysis, 2018, 38(8): 2588−2594.
[7] 夏明星, 郑欣, 王峰, 等. 钼粉制备技术及研究现状[J]. 中国钨业, 2014, 29(4): 45−48. Xia M X, Zheng X, Wang F, et al. Preparation technology and research status of molybdenum powder[J]. China Tungsten Industry, 2014, 29(4): 45−48.
[8] Benedik L, Pilar A M, Prosen H, et al. Determination of ultra-trace levels of uranium and thorium in electrolytic copper using radiochemical neutron activation analysis[J]. Applied Radiation and Isotopes, 2021, 175: 109801. doi: 10.1016/j.apradiso.2021.109801
[9] Messaoudi M, Begaa S, Hamidatou L, et al. Determination of selenium in roasted beans coffee samples consumed in Algeria by radiochemical neutron activation analysis method[J]. Radiochimica Acta, 2018, 106(2): 141−146. doi: 10.1515/ract-2017-2782
[10] Silver B R. Atomic absorption spectroscopy reveals anomalous transfer of heavy metal across a water/1, 2-DCE interface[J]. Portugaliae Electrochimica Acta, 2021, 39: 415−420. doi: 10.4152/pea.2021390603
[11] Zhong W S, Ren T, Zhao L J. Determination of Pb (lead), Cd (cadmium), Cr (chromium), Cu (copper), and Ni (nickel) in Chinese tea with high-resolution continuum source graphite furnace atomic absorption spectrometry[J]. Journal of Food and Drug Analysis, 2016, 24(1): 46−55. doi: 10.1016/j.jfda.2015.04.010
[12] 林建奇. 双通道-原子荧光光谱和固体进样-冷原子吸收光谱测定岩石中痕量汞[J]. 岩矿测试, 2021, 40(4): 512−521. doi: 10.15898/j.cnki.11-2131/td.202006180093 Lin J Q. Determination of trace mercury in rocks by dual-channel atomic fluorescence spectrometry and solid sampling-cold atomic absorption spectrometry[J]. Rock and Mineral Analysis, 2021, 40(4): 512−521. doi: 10.15898/j.cnki.11-2131/td.202006180093
[13] Karlidağ N E, Toprak M, Demirel R, et al. Development of copper nanoflowers based dispersive solid-phase extraction method for cadmium determination in shalgam juice samples using slotted quartz tube atomic absorption spectrometry[J]. Food Chemistry, 2022, 396: 133669. doi: 10.1016/j.foodchem.2022.133669
[14] Aghahoseini M, Azimi G, Amini M K. An on-line matrix separation and preconcentration procedure for ICP-OES determination of Cd, Co, Cu, Mn and Pb traces in Zr and Zr-Nb alloys using a cation-exchange resin microcolumn[J]. Journal of Analytical Atomic Spectrometry, 2021, 36(5): 1074−1083. doi: 10.1039/D1JA00033K
[15] Dong X, Xiong Y, Wang N, et al. Determination of trace elements in high-purity quartz samples by ICP-OES and ICP-MS: A normal-pressure digestion pretreatment method for eliminating unfavorable substrate Si[J]. Analytica Chimica Acta, 2020, 1110: 11−18. doi: 10.1016/j.aca.2020.03.006
[16] Hommel C, Hassler J, Matschat R, et al. A fast and robust direct solid sampling method for the determination of 27 trace, main and minor elements in soda-lime glass based on ETV-ICP OES and using a gaseous halogenating modifier[J]. Journal of Analytical Atomic Spectrometry, 2021, 36(8): 1683−1693. doi: 10.1039/D1JA00081K
[17] Khan S R, Sharma B, Chawla P A, et al. Inductively coupled plasma optical emission spectrometry (ICP-OES): A powerful analytical technique for elemental analysis[J]. Food Analytical Methods, 2022,15(3): 666-688.
[18] 王焕文. 高纯钼成分分析用标准样品的研制[D]. 北京: 北京有色金属研究总院, 2020. Wang H W. Manufacturing of reference material for composition analysis of high purity molybdenum[D]. Beijing: General Research Institute for Nonferrous Metals, 2020.
[19] 王焕文, 陈雄飞, 孙泽明, 等. GD-MS用高纯钼成分分析质量控制样品的研制[J]. 稀有金属, 2022, 46(1): 131−136. Wang H W, Chen X F, Sun Z M, et al. Manufacturing of quality control samples for composition analysis of high purity molybdenum by GD-MS[J]. Chinese Journal of Rare Metals, 2022, 46(1): 131−136.
[20] 张见营, 李昕霓, 周涛, 等. 脉冲-辉光放电质谱法测量稀土合金中的关键元素[J]. 分析化学, 2018, 46(5): 757−764. Zhang J Y, Li X N, Zhou T, et al. Measurement of key elements in rare earth alloy by pulsed glow discharge mass spectrometry[J]. Chinese Journal of Analytical Chemistry, 2018, 46(5): 757−764.
[21] Dong J, Qian R, Zhuo S, et al. Development and application of a porous cage carrier method for detecting trace elements in soils by direct current glow discharge mass spectrometry[J]. Journal of Analytical Atomic Spectrometry, 2019, 34(11): 2244−2251. doi: 10.1039/C9JA00265K
[22] 龚仓, 丁洋, 陆海川, 等. 五酸溶样-电感耦合等离子体质谱法同时测定地质样品中的稀土等28种金属元素[J]. 岩矿测试, 2021, 40(3): 340−348. Gong C, Ding Y, Lu H C, et al. Simultaneous determination of 28 elements including rare earth elements by ICP-MS with five-acid dissolution[J]. Rock and Mineral Analysis, 2021, 40(3): 340−348.
[23] 李丽君, 薛静. 微波消解-电感耦合等离子体质谱法测定高岭土中10种微量元素[J]. 岩矿测试, 2022, 41(1): 22−31. Li L J, Xue J. Determination of 10 trace elements in Kaolin by ICP-MS with microwave digestion[J]. Rock and Mineral Analysis, 2022, 41(1): 22−31.
[24] Cobelo-García A, Mulyani M E, Schäfer J. Ultra-trace interference-free analysis of palladium in natural waters by ICP-MS after on-line matrix separation and pre-concentration[J]. Talanta, 2021, 232: 122289. doi: 10.1016/j.talanta.2021.122289
[25] Sloop J T, Gonçalves D A, O’Brien L M, et al. Evaluation of different approaches to applying the standard additions calibration method[J]. Analytical and Bioanalytical Chemistry, 2021, 413: 1293−1302. doi: 10.1007/s00216-020-03092-8
[26] Ni Y, Bu W, Xiong K, et al. Trace impurity analysis in uranium materials by rapid separation and ICP-MS/MS measurement with matrix matched external calibration[J]. Microchemical Journal, 2021, 169: 106615. doi: 10.1016/j.microc.2021.106615
[27] 张肇瑞. 高纯钼、钛的分析方法研究[D]. 北京: 北京有色金属研究总院, 2012. Zhang Z R. Study on trace elemental analysis of high-purity molybdenum and titanium[D]. Beijing: General Research Institute for Nonferrous Metals, 2012.
[28] Trojanowicz M, Kołacińska K. Recent advances in flow injection analysis[J]. Analyst, 2016, 141(7): 2085−2139. doi: 10.1039/C5AN02522B
[29] Aguirre M Á, Kovachev N, Almagro B, et al. Compensation for matrix effects on ICP-OES by on-line calibration methods using a new multi-nebulizer based on Flow Blurring® technology[J]. Journal of Analytical Atomic Spectrometry, 2010, 25(11): 1724−1732. doi: 10.1039/c004854b
[30] Søndergaard J, Asmund G, Larsen M M. Trace elements determination in seawater by ICP-MS with on-line pre-concentration on a Chelex-100 column using a ‘standard’instrument setup[J]. MethodsX, 2015, 2: 323−330. doi: 10.1016/j.mex.2015.06.003
[31] Hathorne E C, Haley B, Stichel T, et al. Online preconcentration ICP-MS analysis of rare earth elements in seawater[J]. Geochemistry, Geophysics, Geosystems, 2012, 13(1): 1−12.
[32] Wang W, Evans R D, Newman K, et al. Automated separation and measurement of 226Ra and trace metals in freshwater, seawater and fracking water by online ion exchange chromatography coupled with ICP-MS[J]. Microchemical Journal, 2021, 167: 106321. doi: 10.1016/j.microc.2021.106321
[33] Poehle S, Schmidt K, Koschinsky A. Determination of Ti, Zr, Nb, V, W and Mo in seawater by a new online-preconcentration method and subsequent ICP–MS analysis[J]. Deep Sea Research Part Ⅰ: Oceanographic Research Papers, 2015, 98: 83−93. doi: 10.1016/j.dsr.2014.11.014
[34] Ido K, Matsushita R, Fujii S I, et al. Multiple-channel concentric grid nebulizer for online standard addition in inductively coupled plasma optical emission spectrometry[J]. Analytical Sciences, 2020, 36(6): 717−722. doi: 10.2116/analsci.19P385
[35] Lum T S, Leung K S Y. Strategies to overcome spectral interference in ICP-MS detection[J]. Journal of Analytical Atomic Spectrometry, 2016, 31(5): 1078−1088. doi: 10.1039/C5JA00497G
[36] Hamier J, Salin E D. Tandem calibration methodology: Dual nebulizer sample introduction for inductively coupled plasma atomic emission spectrometry[J]. Journal of Analytical Atomic Spectrometry, 1998, 13(6): 497−505. doi: 10.1039/a801689e
[37] Schwartz A J, Ray S J, Hieftje G M. Automatable on-line generation of calibration curves and standard additions in solution-cathode glow discharge optical emission spectrometry[J]. Spectrochimica Acta Part B: Atomic Spectroscopy, 2015, 105: 77−83. doi: 10.1016/j.sab.2014.08.035
[38] 卫碧文, 缪俊文, 龚治湘, 等. 在线标准加入火焰原子吸收光谱法测定钮扣电池中铅和镉[J]. 理化检验(化学分册), 2006, 42(10): 815−817. Wei B W, Miao J W, Gong Z X, et al. FAAS determination of lead and cadmium in button-shaped cell with on-line standard addition[J]. Physical Testing and Chemical Analysis (Part B: Chemical Analysis), 2006, 42(10): 815−817.
[39] 张雅丽, 孙巍, 张磊, 等. 在线内标浓度对电感耦合等离子体质谱法测定栀子金属元素的影响[J]. 药物评价研究, 2017, 40(4): 500−505. Zhang Y L, Zhang W, Zhang L, et al. Effect of determination of metals in Cardenia jasminoides Ellis by ICP-MS from on-line internal standard solution[J]. Drug Evaluation Research, 2017, 40(4): 500−505.
[40] 张颖. 电感耦合等离子体质谱法测定高纯铼酸铵中 19 种痕量杂质元素[J]. 硬质合金, 2013(6): 337−342. Zhang Y. Determination of 19 trace impurities in high purity ammonium rhenate by inductively coupled plasma mass spectrometry[J]. Cemented Carbide, 2013(6): 337−342.
[41] 刘跃, 林冬, 王记鲁, 等. 四种碰撞/反应模式-电感耦合等离子体串联质谱法测定土壤和水系沉积物样品中的银[J]. 岩矿测试, 2022, 41(6): 1017−1028. doi: 10.15898/j.cnki.11-2131/td.202112230206 Liu Y, Lin D, Wang J L, et al. Determination of silver in soil and stream sediments by ICP-MS/MS with four collision/reaction modes[J]. Rock and Mineral Analysis, 2022, 41(6): 1017−1028. doi: 10.15898/j.cnki.11-2131/td.202112230206
[42] Yamamoto M, Horigome K, Kuno T. Accurate and precise measurement of uranium content in uranium trioxide by gravimetry: Comparison with isotope dilution mass spectrometry and its uncertainty estimation[J]. Applied Radiation and Isotopes, 2022, 190: 110460. doi: 10.1016/j.apradiso.2022.110460
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