Application of a SEM-EDS-Based Automated Process Mineralogy Analyzing System on the Occurrence State of Silver in Copper Ore Flotation Tailings
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摘要:
元素赋存状态及工艺矿物学特征是决定其选矿工艺及回收指标的关键因素，对指导矿产资源高效综合回收利用有重要意义。由于银矿物种类繁多且含量低、粒度细小不易识别，传统人为鉴别目标矿物并统计工艺矿物学参数的方法在银的赋存特征研究方面存在局限性，制约了资源高效综合利用。本文利用基于扫描电子显微镜(SEM)和X射线能谱仪(EDS)的工艺矿物学参数自动分析系统(BPMA)对某铜矿浮选尾矿样品(Ag 41.96µg/g，Cu 0.44%)进行矿物学分析，展示其在尾矿样品中铜和银的赋存状态及工艺矿物学特征研究中的具体应用。结果表明：样品中铜矿物主要为辉铜矿和斑铜矿；铜硫化物及其集合体的嵌布粒度细微且解离程度低，是影响铜回收的主要矿物学因素。样品中银主要以独立矿物的形式存在，(含)银矿物有自然银、辉银矿/螺状硫银矿、硒银矿、硒铜银矿、硫铜银矿和含银辉铜矿，银在各(含)银矿物中的分布率分别为95.62%、2.07%、1.33%、0.15%、0.80%和0.03%；银矿物嵌布粒度不均匀，粗粒(＞74µm)、中粒(74～37µm)、细粒(37～10µm)、微粒(＜10µm)银矿物的占有率分别为32.25%、30.35%、21.44%和15.95%；银矿物的解离程度较高，单体含量高达88.28%，可采用浮选法与铜硫化物一起回收。该研究为提高资源的选矿回收率提供了矿物学依据，同时采用的BPMA & SEM-EDS分析方法为矿物种类复杂、含量低、粒度细小的稀贵金属元素赋存状态及工艺矿物学研究提供了一种技术借鉴。
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关键词:
- 银；赋存状态 /
- 工艺矿物学 /
- 矿物粒度 /
- 矿物解离度 /
- 工艺矿物学参数自动分析系统
要点(1) BPMA & SEM-EDS技术联用测定铜矿浮选尾矿的矿物学组成及铜矿物的粒度、解离度、连生关系等工艺矿物学参数，并快速查找鉴定银矿物的种类、分析银的赋存特征。
(2)铜矿物主要为辉铜矿和斑铜矿，嵌布粒度细微，且解离程度较低。
(3)银在自然银、辉银矿/螺状硫银矿、硒银矿、硒铜银矿、硫铜银矿和含银辉铜矿中的分布率为95.62%、2.07%、1.33%、0.15%、0.80%和0.03%，银矿物粒度不均，解离程度较高，可采用浮选法与铜硫化物一起回收。
HIGHLIGHTS(1) BPMA & SEM-EDS technology was used to investigate the mineral composition of the flotation tailings, characterize the particle (and/or grain) size distribution, mineral liberation and interlocking relationships of main copper sulfide minerals in the tailings, and quickly identify the types of silver minerals and occurrence characteristics of silver.
(2) The copper minerals in the flotation tailings are mainly chalcocite (Cu2S) and bornite (Cu5FeS4), embedded with fine disseminated grain size and poor mineral liberation degree.
(3) The silver in the flotation tailings mainly occurs in native silver (Ag), argentite/acanthite (Ag2S), naumannite (Ag2Se), eucairite (CuAgSe), stromeyerite (AgCuS), and silver-bearing chalcocite [(Cu,Ag)2S], accounting for 95.62%, 2.07%, 1.33%, 0.15%, 0.80%, and 0.03%, respectively. The silver-bearing minerals with uneven grain size distribution and relatively high degree of liberation, can be recovered with copper sulfides using the flotation method.
Abstract:The silver occurrence state and process mineralogical characteristics are critical to its beneficiation process and recovery indicators, which can be used for assisting in process development, plant design, and improvement of silver recovery. In order to define the occurrence state of silver in copper ore flotation tailings with low-grade Ag 41.96g/g & Cu 0.44%, BGRIMM process mineralogy analyzing system (BPMA) with version 2.0 BPMA software, scanning electron microscopy (SEM) and energy dispersive X-ray spectrometer (EDS) were applied to investigate the copper mineralogical characteristics and silver occurrence state of the flotation tailings. The copper minerals in the tailings are mainly fine-grained and poorly liberated copper sulfide minerals; the silver mainly occurs as independent silver minerals, with high liberation and non-uniform grain size. The analytical results show that the BPMA & SEM-EDS in situ analysis method can serve as a technical reference for the study of the occurrence state and process mineralogy of rare precious metal elements. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202310250165.
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Keywords:
- silver; occurrence state /
- process mineralogy /
- mineral particle size /
- mineral liberation /
- automated process mineralogy analyzing system
BRIEF REPORTSignificance: The occurrence state of elements and process mineralogical characteristics are critical to the availability of mineral resources, which is conducive to optimizing the ore extraction and smelting process and improving the comprehensive utilization of mineral resources. Due to the wide variety and low content of silver minerals, as well as their fine particle size, it is difficult to identify the occurrence state of silver. The traditional manual method, that is, mineral identification and parameter statistics mainly performed manually particle by particle, has limitations in investigating the occurrence characteristics of silver, which is difficult to effectively guide mineral processing production and greatly restricts the high-efficient utilization of mineral resources. We developed an in situ automated mineralogical analysis method of silver minerals in flotation tailings by SEM-EDS-based BPMA to give analytical technical support for the efficient utilization of silver resources. Our results indicate that the method can be used to find, identify and determine low-grade and fine-grained silver minerals in flotation tailings. It provides strong technical support for the study of the occurrence state and process mineralogy of rare precious metal elements.
Methods: The BPMA with version 2.0 BPMA software, which is a SEM-EDS-based automated mineralogy (AM) system, developed independently by BGRIMM Technology Group (China), was used to analyze the silver occurrence state and process mineralogical characteristics of low-grade flotation tailings (Ag 41.96g/g & Cu 0.44%) from a copper mine. The BPMA particle liberation analysis (BPLA) mode was applied to investigate the mineral composition, the particle (and/or grain) size distribution, and liberation and interlocking relationships of main copper sulfide minerals automatically. The BPMA specific particle liberation analysis (SPLA) mode was applied to find and identify silver-bearing minerals, and to determine their occurrence, mineral composition and size distribution of silver-bearing minerals in the tailings quickly and efficiently.
Data and Results: The results show that the copper minerals in the tailings are mainly chalcocite (Cu2S), with 0.45%, followed by bornite (Cu5FeS4), with 0.09%, and trace chalcopyrite (CuFeS2), which is less than 0.01%; silver mainly occurs in native silver (Ag), argentite/acanthite (Ag2S), naumannite (Ag2Se), eucairite (CuAgSe), stromeyerite (AgCuS), and silver-bearing chalcocite [(Cu,Ag)2S], accounting for 95.62%, 2.07%, 1.33%, 0.15%, 0.80%, and 0.03%, respectively. The copper sulfide minerals are embedded with fine particle size (more than 90% of grains smaller than 20m) and poor mineral liberation degree (the mass of copper sulfide minerals monomer accounts for less than 20%; the mass of copper sulfide minerals with a liberation degree below 25% accounts for more than 64.60%), which is the main mineralogical factor affecting beneficiation indexes of copper. The grain size range of silver-bearing minerals in the tailings is wide, and the contents of coarse-grained (>74m), medium-grained (74−37m), fine-grained (37−10m) and micro-grained (<10m) silver-bearing minerals are 32.25%, 30.35%, 21.45%, and 15.96%, respectively. The silver-bearing minerals are highly liberated, the content of liberated silver-bearing mineral monomer is up to 88.28%, which can be recovered with copper sulfides using the flotation method. However, a small amount of silver-bearing minerals (1.30%) wrapped in gangue minerals such as quartz and calcite are difficult to recycle through flotation.
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铂族元素(PGEs)具有优良的理化性能，被广泛应用于航空航天、特种功能材料、催化剂、电化学等尖端技术领域，是重要的战略性矿产资源。近年来，随着中国高新技术和航空航天的飞速发展，对铂族金属的需求空前高涨，铂族元素的准确测定能够为地质找矿提供重要技术支撑［1-2］。
铂族元素通常分布在非均质的微矿物相中，多以金属或金属互化物的形式存在，由于其在矿物中分布极不均匀且有明显的粒金效应，因此需要增大样品取样量来保证代表性。在样品的分解过程中，锇和钌易形成挥发性四氧化锇和四氧化钌，通常采用强碱保护熔融-蒸馏的方法进行测定，但该方法无法同时测定铂族六项元素［3-5］。漆亮等［6］、赵正等［7］使用改进的卡洛斯管结合高压釜的溶样方法，解决了锇和钌的挥发问题。该方法中试剂用量少，空白低，而且在电感耦合等离子体质谱(ICP-MS)测定前，使用阳离子交换树脂去除铜和镍等阳离子，有效地解决了质谱干扰问题，能够同时测定铂族六项元素，但流程较为复杂，不适合大批量地质样品分析测试。镍锍试金可有效地富集数十克地质样品中的铂族元素，与具有高灵敏度的ICP-MS相结合，能够很好地降低方法检出限［8-15］；但应用在超痕量铂族元素分析中仍面临很大困难，最关键的问题是镍锍试金全流程空白较高。为实现0.1ng/g样品的准确测定，需要降低试剂空白并优化测定模式。吕彩芬等［16］、毛香菊等［17］、Ni等［18］在镍锍试金全流程空白方面开展了大量工作，对镍锍试金的空白来源进行了讨论，并对各种提纯镍方法的效果和实用性进行了对比。其中，试金-碲共沉淀法对镍的提纯效果最好，实际操作简单易行，将试金滤液合并后经碳酸镍沉淀、洗涤、干燥、焙烧后可得纯氧化镍，而且氧化镍可以循环使用，既降低了成本又解决了废液的排放问题。该方法的缺点是采用ICP-MS标准模式测定铂族元素，待测溶液中残留的铜和镍会严重干扰钌和钯的测定。
本文对镍锍试金配料及各类溶剂空白值进行检验，确定空白来源及试剂提纯方法，降低全流程空白。利用镍锍试金富集铂族元素，试金过程中，加入羰基铁粉，使锍扣在水浸泡的条件下自行粉化松散，以简化分析流程，且避免因机械碎扣而产生污染的风险。采用ICP-MS动能歧视模式测定待测溶液，通过消除多原子离子干扰降低方法检出限［19-21］。
1. 实验部分
1.1 标准溶液和主要试剂
钌、铑、钯、锇、铱、铂单元素标准储备溶液：100µg/mL(购自北京钢铁研究总院)。分取钌、铑、钯、锇、铱、铂单元素标准储备溶液，逐级稀释，配制成钌、铑、锇、铱浓度为0.1、0.5、1.0、5.0、10.0ng/mL，铂和钯浓度为1.0、5.0、10.0、50.0、100.0ng/mL混合标准工作溶液，王水(10%)介质，保存期为两周。
镥标准溶液：100µg/mL(购自中国计量科学研究院)。分取镥标准溶液稀释配制内标溶液，Lu浓度为10ng/mL，3%硝酸介质。
碳酸钠(工业纯)，粉状；硼砂(工业纯)，粉状；二氧化硅(分析纯)，粉状；羰基镍(工业纯)，粉状；羰基铁(工业纯)，粉状；面粉(食用级)；升华硫(分析纯)；覆盖剂(3∶1)：轻质氧化镁(分析纯)+碳化硅(分析纯)；盐酸(分析纯)；硝酸(分析纯)；王水。
实验用水为去离子水。
1.2 主要仪器和装置
Agilent 7900型电感耦合等离子体质谱仪(美国Agilent公司)，测定前使用Li、Co、Y、Tl混合调谐液对仪器调谐至双电荷产率小于3%，氧化物产率小于2%，使仪器的强度、灵敏度均达到最优。ICP-MS仪器工作参数见表1。
表 1 ICP-MS仪器工作参数Table 1. Working parameters of ICP-MS instrument工作参数 设定值 工作参数 设定值 射频功率 1550W 冷却气流速 15L/min 采样深度 8mm 载气流速 1L/min 雾化室温度 2℃ 辅助气流速 1L/min 提取透镜电压 −165V 碰撞气(He)流速 3.6L/min GWL-1400℃试金炉(洛阳炬星窑炉有限公司)；试金坩埚(黏土)。
1.3 实验方法
1.3.1 试金配料的配制
地质样品主要包括土壤和水系沉积物，根据不同样品的物质组成特征按表2配制试金配料。
表 2 镍锍试金配料组成Table 2. Composition of nickel sulfide fire assay ingredients样品类型 称样量
(g)硫
(g)羰基镍
(g)羰基铁
(g)硼砂
(g)碳酸钠
(g)二氧化硅
(g)面粉
(g)土壤 20 2 1.6 4 25 20 5 1 水系沉积物 20 2 1.6 4 25 20 6 1 1.3.2 样品的熔融
称取样品20g与试金配料充分混匀后放入试金坩埚，并均匀覆盖20g覆盖剂。坩埚置于升温至1050℃的高温炉中，待炉温回升到1050℃后计时30min，取出坩埚，将熔融体倒入铁模中，冷却后敲碎玻璃渣滓，取出锍扣。
1.3.3 锍扣的分解
将锍扣放入磨口锥形瓶中，用20mL水浸泡锍扣，至粉化松散后加入20mL盐酸，加装风冷管，150℃低温微沸分解至溶液清亮且不再冒气泡。
1.3.4 样品中铂族元素的测定
采用滤膜过滤，用50℃左右的10%热盐酸反复冲洗沉淀。将沉淀及滤膜转入原磨口锥形瓶，加入5mL王水，加装风冷管，于150℃加热至完全溶解，冷却后定容至25mL容量瓶中，摇匀，以三通在线加入镥(10ng/mL)为内标，ICP-MS动能歧视模式测定。
2. 结果与讨论
2.1 试剂空白及提纯
2.1.1 盐酸中的铂族空白及提纯方法
根据实验方法，取50mL不同厂家(记为Ⅰ和Ⅱ)、不同纯度盐酸，低温蒸干，加入使用相同批次盐酸制备的王水5mL，低温提取，再加入20mL水，ICP-MS测定，按20g取样量计算。从表3中数据可见，盐酸中含有一定量的铂、钯和钌，样品分析前要检查盐酸空白，当盐酸空白超过0.02ng/g时，无法进行超痕量铂族元素分析。
表 3 不同盐酸对应的流程空白Table 3. Blank values corresponding to different classes of hydrochloric acid试剂 Ru
(ng/g)Rh
(ng/g)Pd
(ng/g)Os
(ng/g)Ir
(ng/g)Pt
(ng/g)Ⅰ-分析纯 0.0350 0.0003 0.0023 0.0006 ＜0.0001 0.0019 Ⅰ-优级纯 0.0346 0.0004 0.0013 0.0005 ＜0.0001 0.0015 Ⅱ-分析纯 0.0018 0.0001 0.0016 0.0002 ＜0.0001 0.0012 Ⅱ-优级纯 0.0015 0.0002 0.0013 0.0002 ＜0.0001 0.0011 盐酸提纯：取1000mL盐酸，加热后，加入1g/L亚碲酸钾溶液5mL，滴加1mol/L氯化亚锡(6mol/L盐酸介质)至产生大量黑色沉淀，加热煮沸，使沉淀凝聚，过滤后再重复沉淀一次，即可得到空白较低的盐酸。
2.1.2 熔剂二氧化硅中的铂族空白
取不同厂家(记为Ⅲ和Ⅳ)、不同纯度的二氧化硅10g，加入40mL王水(50%)，煮沸2h，过滤，滤液低温蒸干，加入5mL王水溶解沉淀，加入20mL水，ICP-MS测定。结果表明两个厂家的分析纯二氧化硅和优级纯二氧化硅所引入的铂族六项元素全流程空白均低于0.01ng/g，能满足铂族六项元素含量在0.1ng/g级别地质样品的测定需求，对镍锍试金全流程空白的影响可忽略不计。
2.1.3 其他熔剂中的铂族空白
按照实验方法，固定羰基镍粉用量不变，按比例混匀碳酸钠、硼砂、硫粉、羰基铁粉和面粉，分别取20、40、60、80g混合熔剂，按照试金流程处理和测定。从表4中数据可见，当碳酸钠、硼砂、硫粉、羰基铁和面粉用量呈整数倍增加时，对应的铂族六项元素流程空白测定结果没有增大，说明试剂空白对镍锍试金全流程空白贡献很小。
表 4 不同熔剂用量对应的流程空白Table 4. Blank values corresponding to different amounts of flux熔剂用量
(g)Ru
(ng/g)Rh
(ng/g)Pd
(ng/g)Os
(ng/g)Ir
(ng/g)Pt
(ng/g)20 0.390 0.051 0.340 0.010 0.014 0.141 40 0.511 0.076 0.366 0.008 0.008 0.126 60 0.303 0.071 0.361 0.009 0.009 0.125 80 0.414 0.064 0.349 0.010 0.009 0.128 2.1.4 捕集剂中的铂族空白及提纯方法
固定其他熔剂，分别加入不同厂家生产的氧化镍、硝酸镍和羰基镍(Ⅴ和Ⅵ)，按照实验方法熔融、捕集、测定铂族元素。从表5中数据可见，不同镍粉中铂族元素的含量差别较大。根据上述实验结果，可以认为全流程空白主要来自镍粉。
表 5 不同镍基体的铂族元素含量Table 5. PGE contents in different Ni matrices试剂 Ru
(ng/g)Rh
(ng/g)Pd
(ng/g)Os
(ng/g)Ir
(ng/g)Pt
(ng/g)镍粉 0.469 0.095 0.509 4.977 1.962 0.590 硝酸镍 0.779 0.169 0.918 1.107 0.573 0.753 氧化镍 0.560 0.159 0.452 0.480 0.744 0.597 Ⅴ-羰基镍 0.175 0.109 0.096 0.050 0.006 0.120 Ⅵ-羰基镍 0.012 0.010 0.091 0.009 0.009 0.125 镍提纯：取10g氧化镍溶解于30mL盐酸中，加入0.5g/L亚碲酸钾溶液4mL，滴加1mol/L氯化亚锡溶液至产生黑色沉淀，再多加2mL，加热1h使沉淀凝聚，冷却后用0.45μm滤膜过滤。滤掉杂质后，将滤液在电热板上加热浓缩至较小体积，加入碳酸钠中和至pH=8，产生碳酸镍沉淀，水洗至中性，离心，弃清液，将沉淀转入瓷皿，于105℃烘干，再放入马弗炉，于500℃焙烧2h，即可得空白较低的氧化镍粉末。
2.2 溶液中镍和测定模式的影响
2.2.1 溶液中镍对铂族元素测定的影响
以丰度高和不受同量异位素干扰为原则，选择195Pt、105Pd、101Ru、103Rh、190Os和193Ir作为测定同位素。实际测定中发现，195Pt、105Pd、103Rh、190Os和193Ir的测定相对稳定，而钌易受到多原子离子的干扰。干扰101Ru的多原子离子有：12C89Y、16O85Rb、16O1H84Kr、14N87Rb、1H100Ru、1H100Mo、14N87Sr、40Ar61Ni、13C88Sr、16O1H84Sr、36Ar65Cu。采用镍锍试金分离富集样品中铂族元素，能使其与大部分贱金属元素有效分离。但是，由于捕集剂为硫化镍，过滤时很难洗净镍离子，待测试液中残留的镍会形成一系列多原子离子：61Ni40Ar、64Ni37CI、64Ni40Ar等。其中，61Ni40Ar对101Ru的测定形成严重干扰。
标准模式下，测定0.04ng/mL钌单元素标准溶液在0.5～500μg/mL镍基体中的回收率，从表6中数据可见，当镍质量浓度低于1μg/mL时，钌的回收率小于116%，此时由镍形成的多原子离子质谱干扰可忽略不计，当镍质量浓度超过1μg/mL(镍和钌浓度比为25000∶1)，其形成的多原子离子质谱干扰越来越明显，严重影响钌的测定。
表 6 镍元素对钌元素测定结果的影响Table 6. Influence of Ni on the determination results of Ru样品编号 Ru的加入量
(ng/mL)Ni的加入量
(ng/mL)Ru的测定值
(ng/mL)Ru的回收率
(%)1 0.04 500 0.042 105 2 0.04 1000 0.047 116 3 0.04 5000 0.053 133 4 0.04 10000 0.060 150 5 0.04 50000 0.086 214 6 0.04 100000 0.122 304 7 0.04 500000 0.209 521 根据实验结果，发现当溶液中镍含量在500～500000ng/mL范围时，线性关系良好。以溶液中镍的质量浓度(ng/mL)为已知量，镍干扰形成的钌质量浓度(ng/mL)为未知量，可以得到镍元素对钌元素的干扰校正方程，见公式(1)。
$$ \rho_{\mathrm{Ru}}=0.00007 \rho_{\mathrm{Ni}}^{0.6017}$$ (1) 式中：ρRu—由于镍干扰形成的钌的质量浓度(ng/mL)；ρNi—溶液中镍的质量浓度(ng/mL)。
因此，采用标准模式测定钌时，当镍与钌的浓度比大于25000∶1时，根据公式(1)能够基本扣除镍对钌的干扰，但当镍的浓度过大时，此消除干扰方式效果不佳。
2.2.2 标准模式和动能歧视模式测定结果的比较
在标准模式和动能歧视模式两种模式下测定0.04ng/mL钌单元素溶液在0.50～500μg/mL镍基体中的回收率，来考察不同测定模式下镍对钌测定的影响。由图1可知，在标准模式下，当镍质量浓度小于5μg/mL时，钌回收率约在120%以内，标准模式和动能歧视模式测定结果无明显差别；当镍质量浓度超过10μg/mL后，标准模式下钌回收率明显升高，说明镍所形成的61Ni40Ar+质谱干扰较为严重。而在动能歧视模式下，镍质量浓度在0.50～500μg/mL范围内，钌的测定值相对稳定。
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图 1 两种模式下干扰元素镍对钌测定的影响Figure 1. Effect of interference element Ni on the determination of Ru in two modes为进一步研究ICP-MS在动能歧视模式下消除质谱干扰的优势，在标准模式和动能歧视模式下分别采集500μg/mL镍溶液中钌的信号强度进行对照试验。标准模式下钌元素背景等效浓度(BEC)为0.16ng/mL，动能歧视模式下可降至0.0040ng/mL，在动能歧视模式下，钌元素的背景等效浓度比标准模式降低近2个数量级。综上，实验选择动能歧视模式进行测试。
2.3 方法检出限和测定下限
根据条件实验结论，按照实验方法进行20次全流程空白试验，在仪器设定工作条件下，使用动能歧视模式测定，计算20次空白标准偏差，取样量按20g计，考虑稀释倍数，以3倍空白标准偏差计算方法的检出限，以10倍空白标准偏差计算方法的测定下限。钌的检出限达到0.005ng/g(表7)，使铂族六项元素检出限同时满足超痕量铂族元素的测定要求。
表 7 动能歧视模式下铂族元素检出限和测定下限Table 7. Detection limits and quantification limits for PGEs in kinetic energy discrimination model.方法参数 Ru
(ng/g)Rh
(ng/g)Pd
(ng/g)Os
(ng/g)Ir
(ng/g)Pt
(ng/g)空白平均值 0.013 0.008 0.155 0.015 0.011 0.112 检出限(3s) 0.005 0.008 0.050 0.012 0.007 0.058 测定下限(10s) 0.015 0.024 0.150 0.036 0.021 0.174 2.4 方法精密度和正确度
为了考察本文方法测定超痕量铂族元素的精密度和正确度，选择超痕量铂族元素地球化学成分分析标准物质(中国地质科学院地球物理地球化学勘查研究所研制)，按照实验方法对每个样品平行测定12次，进行精密度试验和加标回收试验。从表8中数据可见，6个元素相对误差(RE)为−10.9%～11.8%，相对标准偏差(RSD，n=12)小于9.37%，加标回收率为92%～110%，满足《地质矿产实验室测试质量管理规范》(DZ/T 0130.4—2006)中关于1∶200000分析方法的准确度和精密度控制限(3倍检出限内，RE≤±23%，RSD≤17%；大于3倍检出限，RE≤±12%，RSD≤10%)及DZ/T 0130.3—2006中关于加标回收率允许限(组分含量在10−6～10−4时，加标回收率90%～110%；组分含量＞10−4时，加标回收率95%～105%)。
表 8 标准物质分析结果Table 8. Analytical results of PGEs in national reference materials标准物质编号 元素 测定值
(ng/g)RSD
(%)标准值
(ng/g)相对误差
(%)加标量
(ng/g)测定总值
(ng/g)回收率
(%)GBW07288
(土壤)Ru 0.053 7.21 0.05 6.00 0.05 0.101 94 Rh 0.019 7.31 0.017 11.8 0.05 0.068 98 Pd 0.290 9.23 0.26 11.5 0.5 0.750 92 Os 0.055 8.05 0.05 10.0 0.05 0.109 108 Ir 0.035 8.55 0.032 9.38 0.05 0.081 92 Pt 0.280 6.93 0.26 7.69 0.5 0.790 102 GBW07289
(水系沉积物)Ru 0.110 5.38 0.1 10.0 0.1 0.220 110 Rh 0.103 7.08 0.095 8.42 0.1 0.198 95 Pd 2.200 7.66 2.3 −4.35 5 7.660 109 Os 0.066 7.96 0.06 10.0 0.05 0.120 108 Ir 0.054 7.16 0.05 8.00 0.05 0.103 98 Pt 1.700 5.33 1.6 6.25 1 2.790 109 GBW07294
(土壤)Ru 0.588 6.28 0.66 −10.9 0.5 1.051 93 Rh 1.080 5.88 1.1 −1.82 1 2.010 93 Pd 15.100 3.85 15.2 −0.66 10 25.600 105 Os 0.650 9.37 0.64 1.56 0.5 1.170 104 Ir 1.110 3.88 1.2 −7.50 1 2.131 102 Pt 14.100 3.99 14.7 −4.08 10 23.500 94 3. 结论
建立了镍锍试金富集ICP-MS测定地质样品中的超痕量铂族元素的方法。通过试剂的筛选及采用水浸泡锍扣，使锍扣自行粉化松散，省略了机械碎扣步骤，避免了污染并控制了实验过程产生的空白。同时，采用ICP-MS动能歧视模式测定铂、钯、铑、铱、锇和钌，解决了钌的质谱干扰问题，降低了方法检出限。该方法应用于超痕量地球化学标准物质分析，测定值与标准值一致，适用于大批量地质样品中超痕量铂、钯、铑、铱、锇和钌的同时测定。
采用该方法分析了中国地质科学院地球物理地球化学勘查研究所承担的《东南亚及中亚地区多尺度地球化学填图及成果集成应用》等项目中铂族元素的测定，测定结果满足相关规范要求，成图效果良好，为地球化学调查提供技术支撑。今后将该方法应用于地质样品分析的同时，还需深入探索硫化镍与金的共存机理，提高镍锍试金对金的捕集效果，进一步增加可同时测定元素的数量。
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图 1 尾矿试样的BSE图像和BPMA矿物组成伪彩色图
a—BPMA扫描BSE图像(局部，25个视域拼接图); b—BPMA矿物组成伪彩色图(局部，25个视域拼接图); c—含辉铜矿颗粒BPMA伪彩色图; d—含斑铜矿颗粒BPMA伪彩色图。
Figure 1. BSE image and BPMA false-colored mineral map of the tailing samples
a—BSE image of the tailings (partial); b—BPMA false-colored mineral map of the tailings (partial); c—BPMA false-colored chalcocite-bearing mineral particles; d—BPMA false-colored bornite-bearing mineral particles.
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图 2 尾矿中银矿物嵌布特征(BSE图像)
a—粒径较大的自然银单体颗粒; b—自然银与方解石连生; c—微细粒自然银被石英包裹; d—微细粒裂纹椭球状辉银矿/螺状硫银矿被石英包裹; e—螺状硫银矿呈菱形片状、板状集合体; f—微细粒硒银矿(Nau-1)嵌布于方解石裂隙中，硒银矿(Nau-2)被方解石包裹; g—硒铜银矿沿方解石颗粒内部的裂隙发育; h—硫铜银矿与石英连生; i—含银辉铜矿与钾长石连生。Slv—自然银; Arg—辉银矿; Aca—螺状硫银矿; Nau—硒银矿; Euc—硒铜银矿; Str—硫铜银矿; Chc-(Ag)—含银辉铜矿; Qtz—石英; Cal—方解石; Kln—高岭石; Ab—钠长石; Chc—辉铜矿; Kfs—钾长石。
Figure 2. BSE images of silver-bearing minerals in tailing samples
a—Natural silver particles with larger size; b—Natural silver coexists with calcite; c—Fine grained natural silver particles wrapped in quartz; d—Fine grained ellipsoidal argentite/acanthite with cracks，wrapped in quartz; e—Rhombic or plate-like acanthite aggregate; f—Fine grained naumannite (Nau-1) embedded in calcite cracks，naumannite (Nau-2) wrapped in calcite; g—Eucairite developed along calcite fractures; h—Stromeyerite coexists with quartz; i—Silver-bearing chalcocite coexists with K-feldspar. Slv—Natural silver; Arg—Argentite; Aca—Acanthite; Nau—Naumannite; Euc—Eucairite; Str—Stromeyerite; Chc-(Ag)—Silver-bearing chalcocite; Qtz—Quartz; Cal—Calcite; Kln—Kaolinite; Ab—Albite; Chc—Chalcocite; Kfs—K-feldspar.
表 1 尾矿试样粒度筛析结果
Table 1 Particle size sieving analysis results of the tailing samples
粒级
(mm)质量
(g)产率
(%)元素品位 分布率 Cu(%) Ag(µg/g) Cu（%） Ag（%） +0.074 30.5 31.57 0.41 29.4 29.26 22.12 −0.074至+0.038 20.8 21.53 0.22 69.2 10.71 35.51 −0.038至+0.023 13.0 13.46 0.21 24.3 6.39 7.79 −0.023 32.3 33.44 0.71 43.4 53.65 34.58 合计 96.6 100.00 0.44 41.96 100.00 100.00 
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表 2 BPMA系统预设测量参数
Table 2 Operation conditions of the BPMA system
仪器工作参数 设定条件 全颗粒测量 选择颗粒测量 加速电压 20keV 20keV 工作距离 15mm 15mm 束流强度 3nA 3nA 放大倍率 400 1000 视场宽度 692.02µm 276.77µm 图像分辨率 1024×768pixel 1024×768pixel 像素尺寸 0.67µm 0.27µm 最大可测量帧数 1320 8426 背底阈值 30 100 最小颗粒面积 50pixel 1pixel 最大颗粒面积 − − 亮相灰度 100 100 亮相最小打点相面积 4pixel 1pixel 暗相最小打点相面积 4pixel 1pixel 分相精度 3 5 能谱采谱时间 60ms 60ms 测量终止条件 颗粒数: 105000 帧数: 8426 指定目标灰度 / 100～255 指定目标元素 / Ag
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表 3 尾矿试样的矿物组成分析结果
Table 3 Analytical results of mineral composition for the tailing samples
序号 矿物名称 分子式 矿物
颗粒数矿物含量
(wt.%)序号 矿物名称 分子式 矿物
颗粒数矿物含量
(wt.%)1 自然银 Ag 50 0.004 17 方解石 Ca[CO3] 5498 5.55 2 辉银矿/螺状硫银矿 Ag2S 21 0.0001 18 白云石 CaMg[CO3]2 4596 4.77 3 硒银矿 Ag2Se 55 ＜0.0001 19 绢云母 K{Al2[AlSi3O10](OH，F)2} 10001 4.74 4 硒铜银矿 CuAgSe 13 Trace 20 斜长石 (Na，Ca)[(Si，Al)4O8] 7100 1.66 5 硫铜银矿 AgCuS 13 Trace 21 辉石 (Ca，Mg，FeⅡ，FeⅢ，Al)(Si，Al)2O6 4373 1.51 6 辉铜矿 Cu2S 454 0.45 22 黑云母 K{Mg，Fe)3[AlSi3O10](OH)2 4893 1.23 7 斑铜矿 Cu5FeS4 182 0.09 23 绿泥石 {(Mg，Fe，Al)3[(Si，Al)4O10](OH)2}·(Mg，Fe，Al)3(OH)6 844 0.38 8 黄铜矿 CuFeS2 10 ＜0.01 24 金红石 TiO2 397 0.26 9 黄铁矿 FeS2 16 ＜0.01 25 重晶石 Ba[SO4] 255 0.20 10 方铅矿 PbS 20 ＜0.01 26 磷灰石 Ca5[(PO4)3]F 263 0.20 11 闪锌矿 ZnS 8 ＜0.01 27 高岭石 Al4[Si4O10](OH)8 276 0.09 12 磁铁矿 FeⅡFeⅢ2O4 560 0.59 28 锆石 Zr[SiO4] 68 0.03 13 钛铁矿 FeTiO3 104 0.01 29 独居石 Ce[PO4] 22 0.03 14 石英 SiO2 28976 54.21 30 其他 / 961 0.21 15 钾长石 K[AlSi3O8] 23726 13.10 合计 / 105386 100.00 16 钠长石 Na[AlSi3O8] 11627 10.66
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表 4 尾矿中主要铜矿物嵌布粒度分布
Table 4 Grain size distribution of main copper minerals in tailing samples
粒级(mm) 辉铜矿 斑铜矿 铜硫化物集合体 含量(%) 累积(%) 含量(%) 累积(%) 含量(%) 累积(%) +0.038 — — — — — — −0.038至+0.020 7.81 7.81 — — 8.55 8.55 −0.020至+0.015 9.04 16.85 — — 12.45 21.00 −0.015至+0.010 23.65 40.50 23.54 23.54 18.94 39.94 −0.010至+0.005 31.25 71.75 33.16 56.70 32.64 72.58 −0.005 28.25 100.00 43.31 100.01 27.42 100.00 注：铜硫化物集合体是将样品中辉铜矿、斑铜矿、黄铜矿等铜硫化物作为一个整体进行统计计算，下同。
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表 5 尾矿中主要铜矿物解离度分析结果
Table 5 Mineral liberation degree analysis results of main copper minerals in tailing samples
矿物名称 目标矿物占比(%) 合计
(%)0＜x≤25 25＜x≤50 50＜x≤75 75＜x＜100 100 辉铜矿 70.12 8.25 4.52 1.56 15.55 100.00 斑铜矿 67.28 7.82 4.06 1.63 19.22 100.00 铜硫化物集合体 64.60 12.94 3.36 1.67 17.43 100.00 注：“x”为复合颗粒中目标矿物的质量百分比。
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表 6 尾矿中主要铜矿物连生关系分析结果
Table 6 The interlocking relationships of main copper minerals in tailing samples
矿物名称 矿物单体含量
(%)连生体含量(%) 合计
(%)与其他铜硫化物连生 与石英连生 与长石连生 与方解石、白云石连生 与云母连生 与其他矿物连生 辉铜矿 15.55 6.73 40.90 21.77 7.50 5.56 1.99 100.00 斑铜矿 19.22 17.60 21.16 15.92 12.61 4.18 9.31 100.00 铜硫化物集合体 17.43 / 38.17 24.05 9.57 5.39 5.39 100.00
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表 7 尾矿中银矿物的种类及相对含量
Table 7 Mineral composition and relative content of silver-bearing minerals in tailing samples
银矿物种类 银矿物含量 矿物中银元素的
平均含量(%)银的分布率
(%)银矿物颗粒数 相对质量百分比(%) 自然银(Ag) 50 93.55 99.09 95.62 辉银矿/螺状硫银矿(Ag2S) 21 2.30 87.11 2.07 硒银矿(Ag2Se) 55 1.84 70.33 1.33 硒铜银矿(CuAgSe) 13 0.41 35.43 0.15 硫铜银矿(AgCuS) 13 1.51 51.15 0.80 含银辉铜矿[(Ag，Cu)2S] 4 0.39 6.88 0.03 合计 156 100.00 / 100.00
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表 8 尾矿中银矿物的嵌布特征及占有率统计结果
Table 8 Occurrence characteristics and distribution ratio of silver-bearing minerals in tailing samples
银矿物种类 银矿物赋存形式 嵌布特征 颗粒数 相对质量百分比
(%)合计
(%)自然银 单体 单体解离 39 84.13 84.13 连生 与石英连生 4 7.40 8.92 与方解石连生 2 1.38 与钠长石连生 2 0.14 包裹 被石英包裹 2 0.47 0.49 被方解石包裹 1 0.02 辉银矿/螺状硫银矿 单体 单体解离 17 2.01 2.01 连生 与钠长石连生 1 0.07 0.07 包裹 被石英包裹 3 0.22 0.22 硒银矿 单体 单体解离 4 0.42 0.42 连生 与方解石连生 6 0.54 0.57 与钠长石连生 2 0.03 裂隙 嵌布于方解石裂隙中 16 0.25 0.34 嵌布于石英裂隙中 3 0.09 包裹 被方解石包裹 23 0.48 0.50 被石英包裹 1 0.02 硒铜银矿 单体 单体解离 1 0.16 0.16 裂隙 嵌布于方解石裂隙中 12 0.26 0.26 硫铜银矿 单体 单体解离 9 1.24 1.24 连生 与白云石连生 1 0.15 0.19 与石英连生 1 0.03 包裹 被石英包裹 2 0.09 0.09 含银辉铜矿 单体 单体解离 3 0.32 0.32 连生 与钾长石连生 1 0.07 0.07 合计 156 100.00 100.00 注: “连生”是指银矿物与其他矿物共伴生但其表面裸露的嵌布形式，下同。
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表 9 尾矿中银矿物粒度分布
Table 9 Size distribution of silver-bearing minerals in tailing samples
粒级
(µm)银矿物* 自然银 辉银矿/螺状硫银矿 硒银矿 颗粒数 质量百分比
(%)累积
(%)颗粒数 质量百分比
(%)累积
(%)颗粒数 质量百分比
(%)累积
(%)颗粒数 质量百分比
(%)累积
(%)+74 1 32.25 32.25 1 34.47 34.47 — — — — — — −74+37 1 30.35 62.60 1 32.44 66.91 — — — — — — −37+20 2 14.99 77.59 2 16.03 82.94 — — — — — — −20+10 4 6.45 84.04 4 6.90 89.84 — — — — — — −10+5 20 8.69 92.73 13 6.77 96.61 3 50.75 50.75 1 15.29 15.29 −5+4 14 2.39 95.12 4 1.02 97.63 2 11.33 62.09 3 26.43 41.71 −4+3 23 2.61 97.73 12 1.79 99.42 5 21.08 83.17 3 13.20 54.91 −3+2 30 1.49 99.22 5 0.34 99.77 7 13.22 96.38 8 22.58 77.49 −2+1 29 0.65 99.88 8 0.23 100.00 3 3.49 99.87 16 17.56 95.05 −1 32 0.12 100.00 0 0.00 100.00 1 0.13 100.00 24 4.95 100.00 注： “银矿物粒度”是指将试样中自然银、辉银矿/螺状硫银矿、硒银矿、硒铜银矿、硫铜银矿等所有的银矿物作为整体统计其粒度。
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1. 施雨航，王帅，宋宝旭，马芳源，南楠，黄恩铭，杨光，周兰，韩济全. 内蒙古某多金属硫化矿石工艺矿物学研究. 现代矿业. 2025(02): 104-108 . 
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