**1. Introduction**

As the need for sustainability in mining is becoming increasingly important amongs<sup>t</sup> the public, decision makers and the industry itself, detailed investigations into what ore deposits actually contain in terms of various minerals, potential by-products and industrial minerals are needed. By making use of a larger proportion of the mined ore (recovering also the trace metals) mining operations can be more sustainable and this will potentially also be beneficial in gaining public acceptance for mining (social license to operate). Precious metals such as Au and Ag are already readily produced as mainor by-products in many mining ventures even if they occur only in trace amounts and numerous metals could potentially follow the precious metals as by-products in a number of mining operations worldwide. Many European ore deposits contain various amounts of trace metals classified as "Critical Raw Material" (CRM) by the European Commission, i.e., they are of high economic importance for the EU but with a high risk associated with their supply [1].

While trace metal production may not be economically profitable at the moment this could change in the future as metal prices increase and the pressure is increasing for more sustainable mining. Hence, for sustainability as well as economic reasons, the trace mineral and metal characterization of an ore deposit should be considered when planning for a mining operation, and also in operating mines.

In order to predict trace metal deportment during processing of the ore, a good understanding of their mineralogical and textural characterization is necessary. Due to their low abundance in ore deposits and often fine-grained (<50 μm) nature, identification and quantification of trace minerals is di fficult and requires the use of advanced micro-analytical techniques. Many capable techniques were developed over the last few decades, each with its own advantages and disadvantages [2], but especially, Automated Scanning Electron Microscopy (ASEM) systems found wide-spread acceptance and application in the mining industry. These systems provide fast and reliable quantification of the mineralogy and textures in a sample. Most prominent are the Quantitative Evaluation of Mineralogy by a SCANning electron microscope (QEMSCAN ®) system and the Mineral Liberation Analyzer (MLA) system [3,4].

The QEMSCAN ® system is the third generation of automated mineral analysis systems based on the then-named QEM\*SEM ® system. QEM\*SEM ®, was developed at the request of the mining industry by the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia in the 1970s and marked the first automated mineral analyzer [5,6]. The MLA system is based on the concepts of Hall [7] and became commercially available in 2000 through FEI Company and JKTech, whilst QEMSCAN ® was marketed by Intellection Pty Ltd. Both systems, QEMSCAN ® and MLA, utilize backscattered electrons (BSE) and energy dispersive X-ray spectra (EDS) to create digital mineral images. In the QEMSCAN ® system, low-count X-ray mapping is preferentially used for mineral classification. This is done by comparison of the X-ray element-spectra to existing mineral databases. BSE brightness is used to distinguish particles from the mounting media. A summary of the QEMSCAN ® system and its various application modes is provided by Gottlieb et al. [3], Goodall et al. [8], and Pirrie and Rollinson [9]. By contrast, in the MLA system, particles are often defined through the BSE brightness and subsequently classified by one X-ray spectrum per particle. For particles of similar BSE brightness, X-ray mapping is used. The MLA system is described in detail by Gu [4]. While both systems are still widely applied in the industry and by research institutions, their commercial production has currently been terminated. This has given rise to new ASEM systems, most prominently the ZEISS Mineralogic Mining system and the TESCAN Integrated Mineral Analyzer (TIMA) [10]. These systems come with some improvements, such as faster speed of analysis. An introduction to the ZEISS Mineralogic Mining system is provided by Graham et al. [11] and references therein, and the principles and applications of the TIMA system are described by Hrstka et al. [10].

In the mining industry, ASEM systems are mostly applied for routine scans of particulate samples of ore and tailings concentrate to identify and quantify the mineralogy of the ore feed and products. Instruments are typically calibrated for fast acquisition rates to enable a high sample throughput. This comes at the expense of precision and resolution. As a consequence, trace minerals are often undetected due to their grain size being at or below the scan resolution. Most ASEM systems provide an analytical mode targeted towards the analysis of trace minerals (such as TMS mode for QEMSCAN ®) and its usefulness for characterization of, e.g., Au has been demonstrated [8,12–14]. However, this analytical mode hardly finds application for deposits where trace minerals are only by-products, or of no current economic interest. Furthermore, since the TMS mode utilizes a BSE brightness threshold to filter for trace minerals, it is hardly applicable if the sample is enriched in Pb- and Bi-minerals due to their similar BSE brightness compared to Au-minerals. This forces the system to analyze many more particles than necessary (so-called false particles) and is thus more time-consuming. Hence, there is a need to improve detection of trace phases in general analyses.

Here, we compare results of analysis of a polished thin section from a Cu-(W-Au) ore between two QEMSCAN ® systems; one is an industry-system (Boliden AB), the other a research-system (Camborne School of Mines). For the research-oriented scan, the setup of the analysis was thoroughly planned and much time was spent on the post-processing of the raw data, so this scan is assumed to be of the highest quality and used as a measure for the relative quality of the routine industrial scan. The goal was to determine the overall quality of general routine industrial scans and the possibility of detecting and quantifying trace phases at or below the scan resolution. Ideally, a scan should provide a basic idea of trace mineral mineralization in a sample and help the operator/decision maker decide if more detailed analysis is worth pursuing. In this case, the trace mineral Au was used to find an optimum methodology for detecting and quantifying trace minerals but the methodology presented applies to all trace minerals in an ore body. A guide towards analysis is provided. This analysis is novel in its collaborative inter-lab comparison between the industry and a scientific institution.

#### **2. Materials and Methods**

To promote analysis of uncrushed rock samples by ASEM systems prior to processing, a thin section sample of a drill core was chosen instead of a particulate sample for this analysis, despite the more common usage of particulate samples in the mining industry. Uncrushed samples have a higher uncertainty of representativeness, but they allow the study of original features like mineral distribution, structures and textures which carry important information for processing of the ore but are partly lost during crushing. Hence, for comprehensive ore characterization to aid in early mine planning, uncrushed rock samples are most suitable. To limit uncertainties, appropriate sampling and su fficient volume are necessary [15], in fact, possibilities to routinely scan drill core pieces are currently tested at Boliden AB. Furthermore, ideally, analysis should be performed on both crushed and uncrushed rock samples.

The sample selected was from the Liikavaara Cu-(W-Au) deposit, an intrusion-related vein-style deposit in Northern Sweden (Figure 1a,b), located close to the world-class Aitik Cu-Au deposit where the Liikavaara ore will be processed. Chalcopyrite, pyrite and pyrrhotite constitute the major ore minerals. Sphalerite, galena, scheelite, molybdenite, marcasite and magnetite are minor. The deposit also hosts several trace metals including Au, Ag, Bi and Sn which commonly occur in fine-grained minerals (<20 μm) [16]. The trace metal mineralogy is presented in Table 1, and a detailed description of the geology and mineralogy of the deposit is given by Zweifel [17] and Warlo et al. [16].

The deposit is currently in the pre-production stage, and production is estimated to start in 2023. Copper will be the primary commodity and Au and Ag will be by-products. Production of W, despite its enrichment and classification as a CRM, would require an additional processing step and is thus unprofitable at present. Bismuth is known for its potential to contaminate and lower the quality of the Cu concentrate, thus having good control over its mineralogy and distribution is beneficial.

The pre-production stage of the Liikavaara deposit, its enrichment in several trace metals of interest, a diverse fine-grained mineralogy, and previous studies, make the Liikavaara Cu-(W-Au) deposit an ideal candidate for this type of study.


**Table 1.** Trace metal mineralogy of the Liikavaara Cu-(W-Au) deposit.

**Figure 1.** (**a**) Location of the Liikavaara Cu-(W-Au) deposit in Northern Sweden; (**b**) geological map of the Liikavaara deposit at 100 m below surface. Location of the drill hole for the sample analyzed in this study is shown; (**c**) thin section prepared from a drill core intersecting a mineralized quartz vein within an aplite dike. Modified from Warlo et al. [16].

The selected core sample (mineralized quartz vein from the proximal ore zone) was prepared into a polished thin section of 27 × 46 mm with a sample size of 23 × 37 mm (Figure 1c). In the corresponding other half of the drill core, an Au-grade of ca. 6 ppm was measured over a 1.3 m section.

The sampled vein is composed of quartz with minor tourmaline and scattered patches altered by fine-grained (<20 μm) calcite and chlorite (Figure 2a,e). It is strongly mineralized by pyrite and pyrrhotite, and by minor chalcopyrite and sphalerite (Figure 2b,f). Pyrite and pyrrhotite vary in grain sizes from a few microns to several centimeters in width. Grains are often fractured but pyrite retains a subhedral shape (Figure 2b,f). Chalcopyrite and sphalerite exist mostly as crack fillings and along grain boundaries in pyrite and quartz, but are also associated with tourmaline and disseminated (<50 μm) in areas altered by calcite and chlorite (Figure 2b,f). Several grains of scheelite (>1 cm), and one 400 μm grain of pilsenite, are observed (Figure 2c–e). SEM-BSE imaging coupled with EDS analysis revealed the occurrence of native bismuth, hessite, bismuthinite and electrum. Grains were mostly below 10 μm in size (Figure 3a–d).

**Figure 2.** Petrographic images of the thin section analyzed by QEMSCAN® in this study. (**<sup>a</sup>**,**<sup>e</sup>**) are plane polarized light images, (**b**–**d**,**f**) are reflected light images; (**a**) grains of quartz surrounded by patches of calcite, and pyrrhotite and pyrite; (**b**) massive pyrrhotite and subhedral pyrite. Sphalerite and chalcopyrite occur along the edges and in cracks of pyrite; (**c**) scheelite grain within pyrite; (**d**) grain of pilsenite with patches of pyrrhotite surrounded by calcite; (**e**) and (**f**) assemblage of sphalerite, pyrite, calcite and tourmaline surrounded by quartz. Abbreviations: Cal—calcite, Ccp—chalcopyrite, Pil—pilsenite, Po—pyrrhotite, Py—pyrite, Qz—quartz, Sch—scheelite, Sp—sphalerite, Tour—tourmaline.

**Figure 3.** Backscattered (**<sup>a</sup>**–**<sup>c</sup>**) and secondary (**d**) electron images of the thin section prior to QEMSCAN® analysis; (**a**) intergrowth of native Bi and hessite in a crack between grains of pyrite and sphalerite; (**b**) droplet-shaped grains of native bismuth with Au in quartz; (**c**) grains of electrum at the border of sphalerite and tourmaline, respectively; (**d**) magnified image of (c). Abbreviations: Au—gold, Bi—native bismuth, Cal—calcite, Ccp—chalcopyrite, Chl—chlorite, Ele—electrum, Hes—hessite, Pil—pilsenite, Py—Pyrite, Qz—quartz, Sp—sphalerite, Tour—tourmaline.

Petrography of the sample prior to QEMSCAN® analysis was carried out with a petrographic microscope (Nikon ECLIPSE E600 POL) in transmitted and reflected light, and with a scanning electron microscope (Zeiss Merlin FEG-SEM) at Luleå University of Technology. The same SEM was used for verification of the trace minerals detected by the QEMSCAN® analyses.

The polished thin section was first analyzed with the QEMSCAN® system at Camborne School of Mines (CSM), University of Exeter, Penryn, UK, to comprehensively characterize the mineralogy of the sample with emphasis on the detection and identification of trace metal minerals. This consists of a QEMSCAN® 4300 (Zeiss EVO®50 SEM with W-filament, four EDS, and an electron backscatter detector) using iMeasure version 4.2 SR1 software for data collection, and iDiscover 4.2SR1 and 4.3 software for data processing. The sample was carbon coated to 25 nm at CSM prior to analysis. The fieldscan measurement mode was performed at an X-ray resolution of 10 μm using a horizontal field width of 1500 μm (150 × 150 analysis points per field), with a measurement area of approximately 19 mm × 35.5 mm (Figure 4), resulting in ~7 million analysis points and a scan time of 10:20 h. The X-ray count per pixel used the default of 1000 counts. For mineral identification, a modified version of the standard LCU5 Species Identification Protocol (SIP) was used, following the guidance in Section 7 of Rollinson et al. [18]. During data processing, particular emphasis was placed on the trace metal minerals to enable identification of these and take into account their small size (some were at the single pixel scale), which results in mixed spectra. This included electrum, bismuth minerals, molybdenite and the silver minerals. However, the SIP (mineral database) was customized to the entire sample, to ensure all the minerals in the sample were identified as accurately as possible, which involved checking all the minerals present and developing the database entries as required. This, for example, involved improving existing entries, adding boundary categories for existing minerals caused by mixed spectra, and adding new entries for the trace metal minerals to ensure they were as accurately captured as possible given their small size.

**Figure 4.** Optical scan of the sample and corresponding QEMSCAN® images (backscattered electrons (BSE) and mineral map) from Camborne School of Mines (CSM) and Boliden AB.

The same thin section was then measured at Boliden AB, Boliden, Sweden with a similar objective. However, settings were chosen to reflect a routine industrial application. At Boliden AB, a QEMSCAN® 650 (FEI with W-filament, two EDS, and an electron backscatter detector) was used with iMeasure version 5.4 software for data collection and iDiscover 5.4 software for data processing. The fieldscan measurement mode was performed at an X-ray resolution of 5 μm using a horizontal field width of 1500 μm (300 × 300 analysis points per field), with a measurement area of approximately 21.5 mm × 32 mm (Figure 4), resulting in ~24.6 million analysis points and a scan time of 23:50 h. The X-ray count per pixel used the default of 1000 counts. For mineral identification, a custom SIP for the Aitik deposit, based on several scientific and in-house mineralogical studies, was modified and adapted to the mineralogy of the Liikavaara Cu-(W-Au) deposit. After the measurement, an initial search for unknown phases was performed and corresponding minerals added to the SIP. This was followed by a data processing routine. Comparison of the results with the analysis at CSM led to application of the "boundary phase processor" and to several more additions to the mineral list (especially for Au-phases) to improve data quality (see Section 3).
