The c. 1.89 Ga Garpenberg Zn-Pb-Ag-(Cu-Au) deposit is hosted by dolomite marble, skarn and felsic metavolcanic rocks. Extensive marble units host part of the mine infrastructure, including sections of bright-colored, chemically pure marble. Assessing the potential of carbonates as by-products to base metal mining is of interest for a sustainable and efficient use of resources and for securing a domestic supply of carbonates. This study characterizes marble units proximal to the Dammsjön and Lappberget ore bodies at Garpenberg based on their optical, chemical, mineralogical, and textural properties to delineate controls on their brightness, color, and purity. Methods employed include drill core logging, whole-rock lithogeochemistry, petrography, SEM-EDS, μXRF, spectrophotometric brightness measurements, and tests of AIR and magnetic separation. The marble units are divided into bright calcite marble (white, gray, and green varieties), dark calcite marble (salmon pink, spotted, brecciated, and ophicalcite varieties) and dolomite marble. Brightness and purity of the marbles are highly correlated, with Fe having a particularly detrimental effect on brightness, both via substitution in the dolomite and calcite lattices, but also via presence of accessory minerals that grind to dark powders. Ore-proximal dolomite marble shows a hydrothermal signature, with elevated base metals, Fe, S and Mn content, whereas impurities in calcite marble seem to mainly be of detrital origin, reflecting co-settled volcaniclastic and siliciclastic material in the limestone precursors. Mainly the bright calcite marble varieties are of potential industrial quality and are present in Garpenberg in significant volumes, but the technoeconomic feasibility of by-product valorization requires further analysis.

The end-of-life recycling of crystalline silicon photovoltaic (PV) modules and the utilisation of waste is of fundamental importance to future circular-economy societies. In the present work, the wet-chemistry synthesis route – a low-temperature dissolution–precipitation process – was explored to produce aluminosilicate minerals from waste c-Si solar cells. Nanostructured crystals were produced in an alkaline medium by increasing the reaction temperature from room temperature to 75 °C. The morphology of the produced crystals varied from nanolayered aggregates to rod-shaped crystals and was found to be dependent on the temperature of the reaction medium. Chemical and phase composition studies revealed that the synthesised compounds consisted of structurally different phases of aluminosilicate minerals. The purity and elemental composition of produced crystals were evaluated by energy dispersive spectroscopy (EDS) and micro X-ray fluorescence (μXRF) analysis, confirming the presence of Al, O, and Si elements. These results give new insights into the processing of aluminosilicate minerals with sustainable attributes and provide a possible route to reducing waste and strengthening the circular economy.

In order to maximise profit and sustainability of a mining operation, knowledge of the chemistry, mineralogy, texture, and structure of the ore is essential. Continuous advancements in analytical techniques enable studying these features with increasing detail. Synchrotron radiation X-ray fluorescence is unparalleled in its simultaneously high spatial resolution and detection range. Yet, its application in ore geology research and the mining industry is still in its infancy. This study investigated opportunities of extreme-resolution synchrotron X-ray fluorescence mapping of ore samples. Analysis was performed at the NanoMAX beamline at the MAX IV synchrotron facility in Lund, Sweden. The samples investigated are from the Liikavaara Östra Cu-(W-Au) deposit, northern Sweden. Analysis covered areas of several hundreds of ÎŒm2 in grains of molybdenite, pyrite, and native Bi. Key results included successful mapping of the lattice-bound distribution of Re, Se, and W in molybdenite at 200 nm spot/step size and detection of nanometre inclusions of Au in native Bi at 50 nm spot/step size. Challenges were encountered concerning data acquisition and processing. In order to achieve satisfactory resolution of both light and heavy elements and to limit mapping artefacts, repeated scans of the same area with varied experimental parameters and very thin (quasi-2d) samples are required. For complex geological samples, the software used for analysing spectral data (PyMCA) requires a considerable degree of human examination, which may be a source of error. Overall, synchrotron X-ray fluorescence mapping has a strong analytical potential for ore geology research, in analysing and imaging trace elements that would constitute potential by-products in mining operations. Knowing in detail how these trace elements occur in the ores, appropriate metal extraction programs can be developed, and a larger part of the ore may then be utilized.

The variety and amount of metals consumed by human society is ever increasing. Meeting the demand requires exploration for new ore deposits, efficient production of active mines, and improved efficiency in metal recycling. A key element in mining-related enterprises is the improvement of ore characterisation. The study of the geology and mineralogy of ore deposits allows us to infer the processes behind ore genesis. This knowledge guides important exploration and processing decisions. Over the last few decades, technological advancements have enabled ore characterisation at increasing levels of detail. This has brought the trace metal mineralogy of ore deposits into focus. In many cases, trace metals occur as extremely fine-grained minerals or as lattice-bound impurities in the more common minerals in ore deposits. Hence, their study requires the use of micro-analytical techniques. Trace metals and their minerals can carry crucial information on the conditions of ore formation. They can be of economic value, harmful to the environment, or of strategic economic and geopolitical interest (e.g. Critical Raw Materials). Trace metal characterisation is therefore highly relevant to research, industry, and society.  In this project, micro-analysis was performed on the Liikavaara Östra Cu-(W-Au) deposit in northern Sweden to research the trace metal mineralogy of Au, Ag, Bi, Mo, Re, and W. The main goal of the project was the development, optimisation, and integration of various micro-analytical techniques for ore characterisation. The project was subdivided into four studies (scientific contributions): (1) Drill core logging, whole-rock geochemistry, and light microscopy were applied to identify lithology, alteration, and mineralisation of the deposit. An intrusion in the footwall, potentially related to ore genesis, was dated with LA-ICP-MS. Scanning electron microscopy with energy dispersive spectrometry was used to gain insight into the trace metal mineralogy of the deposit. This study provided an overview of the geology and mineralogy of the deposit and served as a basis for sample selection and data interpretation of subsequent studies. (2) A polished thin section of the ore containing trace metal minerals was scanned by automated mineralogy (QEMSCAN) at Boliden AB to assess the potential of trace metal mineral quantification in a production-focused environment. To delineate instrument limitations from operator input the same sample was also scanned at Camborne School of Mines, UK. Detection of trace metal minerals was generally difficult due to their fine-grained nature. Yet, quantification could be improved by optimisation of the mineral classification library. (3) Four polished epoxy-mounted drill core pieces of ore were analysed by automated mineralogy (Mineralogic) and x-ray computed tomography (XCT). In two samples, a smaller region of interest was drilled and re-analysed at higher resolution. Results from automated mineralogy were used to segment and interpret the XCT data. Vice versa, XCT data provided 3D spatial context for the 2D scans. (4) Three polished thin section pieces with grains of molybdenite, pyrite, and native Bi, all with Au-inclusions, were analysed by synchrotron radiation x-ray fluorescence mapping at the NanoMAX beamline of the MAX IV synchrotron facility in Lund, Sweden. Element fluorescence maps down to 50 nm pixel size revealed the distribution of micro- and nano-inclusions and lattice-bound impurities in the mineral grains. The studies demonstrated benefits and challenges of the various micro-analytical techniques, and how and what they may contribute to ore characterisation. Results allowed linking and integrating the techniques into a smart analytical flow to optimise the characterisation of trace metal minerals in ore deposits. This is useful for both ore geology research and the mining industry. 

Ore characterization is crucial for efficient and profitable production of mineral products from an ore deposit. Analysis is typically performed at various scales (meter to microns) in a sequential fashion, where sample volume is reduced with increasing spatial resolution due to the increasing costs and run times of analysis. Thus, at higher resolution, sampling and data quality become increasingly important to represent the entire ore deposit. In particular, trace metal mineral characterization requires high-resolution analysis, due to the typical very fine grain sizes (sub-millimeter) of trace metal minerals. Automated Mineralogy (AM) is a key technique in the mining industry to quantify process-relevant mineral parameters in ore samples. Yet the limitation to two-dimensional analysis of flat sample surfaces constrains the sampling volume, introduces an undesired stereological error, and makes spatial interpretation of textures and structures difficult. X-ray computed tomography (XCT) allows three-dimensional imaging of rock samples based on the x-ray linear attenuation of the constituting minerals. Minerals are visually differentiated though not chemically classified. In this study, decimeter to millimeter large ore samples were analyzed at resolutions from 45 to 1 μm by AM and XCT to investigate the potential of multi-scale correlative analysis between the two techniques. Mineralization styles of Au, Bi-minerals, scheelite, and molybdenite were studied. Results show that AM can aid segmentation (mineralogical classification) of the XCT data, and vice versa, that XCT can guide (sub-)sampling (e.g., for heavy trace minerals) for AM analysis and provide three-dimensional context to the two-dimensional quantitative AM data. XCT is particularly strong for multi-scale analysis, increasingly higher resolution scans of progressively smaller volumes (e.g., by mini-coring), while preserving spatial reference between (sub-)samples. However, results also reveal challenges and limitations with the segmentation of the XCT data and the data integration of AM and XCT, particularly for quantitative analysis, due to their different functionalities. In this study, no stereological error could be quantified as no proper grain separation of the segmented XCT data was performed. Yet, some well-separated grains exhibit a potential stereological effect. Overall, the integration of AM with XCT improves the output of both techniques and thereby ore characterization in general.

With the development of QEM*SEM, the first automated scanning electron microscopy (ASEM) system, by CSIRO in the 1970s, mineral and texture quantification in the extraction industries was revolutionised. Since then, several systems have emerged (QEMSCAN, MLA, Mineralogic, TIMA, AMICS, INCA-mineral) that now find widespread application not only in the industry but also in science. The popularity of these systems is owed to their ability to rapidly and reliably quantify the mineralogy and textures in a variety of sample types including polished rock samples, thin sections and epoxy mounts of both whole and particulate samples. However, despite their apparent automatization, to guarantee high quality data and reliable results, a key role falls to the operator. It is through a mineral database that the raw data collected by EDS-detectors is converted into quantitative mineralogical data, and the database is adjusted by the operator on a case by case basis.

In this study we qualitatively compare analyses of the same sample at two different QEMSCAN labs, Camborne School of Mines (CSM) in the UK and Boliden AB in Sweden, to highlight differences in their approach towards analysis and set-up of the database, and the consequences this has for the results. Furthermore, through modification of the database used at Boliden AB, several methods of how the results can be influenced are demonstrated.

The selected sample is a polished thin section of mineralised vein from a drill core from the Liikavaara East Cu-(W-Au) deposit in northern Sweden. The sample contains massive pyrite and pyrrhotite associated with quartz, silicates, and fine-grained clusters of carbonates and Fe-oxides. Chalcopyrite fills cracks in pyrite. Some sphalerite and scheelite are observed as well as traces of cassiterite, molybdenite, and Au-, Ag-, Bi-, and Te-minerals.

Compared to the analysis at CSM, the analysis at Boliden AB showed an overestimation of the chalcopyrite content, limited differentiation of gangue phases, and problems with identification of phases at scan resolution (~5 µm). These differences could subsequently be reduced through editing of the database.

Application of a software-tool called the ‘boundary-phase processor’  was used to correct erroneous mineral classifications resulting from mixed signals at grain boundaries, which had caused pyrite grains to show a false coating of chalcopyrite. Gangue phases were differentiated through subdivision of phase-categories, although for higher accuracy comparison with standards and fine-tuning of mineral-entries in the database would be necessary. Element-filters in the database allowed identification of phases of specific elements, e.g. Au, at or below scan resolution despite mixed signals with the surrounding phases.

While data from both analyses was generally similar, the inter-lab comparison clearly demonstrated that more detailed information could be attained with ASEM systems through optimisation of the database. In the mining industry, a loss in the level of detail is often accepted in favour of time spent on data processing. However, particularly the characterisation and quantification of complex ores and critical metals, which often occur only in traces and fine grain sizes in ore deposits, require a high level of detail to allow efficient processing of the ore.

The Liikavaara Östra Cu-(W-Au) deposit is situated close to the operating Aitik Cu-Au mine in northern Sweden. It is scheduled for production in 2023. Modern geological descriptions of the deposit are lacking though knowledge of geological and mineralogical details prior to operation is beneficial to avoid surprises. In this study, petrological, mineralogical and geochemical investigations of the wall rocks, host rock and mineralisation, and zircon U-Pb analysis of a footwall granodioritic intrusion were carried out. The mineralisation is hosted by quartz±tourmaline-calcite veins, calcite veins and aplite dykes that cross-cut biotite-amphibole schists and gneisses. The wall rocks to the ore are metavolcaniclastic rocks of basaltic to andesitic composition. A granodiorite intrusion occurs in the footwall. The mineralisation is mainly chalcopyrite, pyrrhotite and pyrite with some sphalerite, galena, scheelite, molybdenite and magnetite. It shows slight enrichments in Au, Ag and Bi. Gold and Ag occur as electrum and Ag also in hessite and an Ag-sulphide. The Bi mineralogy includes native Bi, Bi-tellurides and Bi-sulphides. These minerals are found as inclusions, along the borders of and in cracks in chalcopyrite, pyrite, pyrrhotite, sphalerite, molybdenite and quartz. The footwall granodiorite intrusion was dated at 1.87 Ga. It is suggested here to be the source for ore genesis based on its spatial relation to the mineralisation, as well as on high-salinity fluids and metal composition of the ore. The aplite dykes may have acted as pathways for the magmatic hydrothermal fluids that carried the metals from the intrusion to the host rock.

Automated Scanning Electron Microscopy (ASEM) systems are applied in the mining industry to quantify the mineralogy of the ore feed and products. With society pushing towards sustainable mining, this quantification should be comprehensive and include trace minerals since they are often either deleterious or potential by-products. Systems like QEMSCAN^® offer a mode for trace mineral analysis (TMS mode); However, it is unsuitable when all phases require analysis. Here, we investigate the potential of detecting micron-sized trace minerals in fieldscan mode using the QEMSCAN^® system with analytical settings in line with the mining industry. For quality comparison, analysis was performed at a mining company and a research institution. This novel approach was done in full collaboration with both parties. Results show that the resolution of trace minerals at or below the scan resolution is difficult and not always reliable due to mixed X-ray signals. However, by modification of the species identification protocol (SIP), quantification is achievable, although verification by SEM-EDS is recommended. As an add-on to routine quantitative analysis focused on major ore minerals, this method can produce quantitative data and information on mineral association for trace minerals of precious and critical metals which may be potential by-products in a mining operation

The Liikavaara Cu-(W-Au) deposit in northern Sweden is scheduled for production by the mining company Boliden AB in 2023. The ore will be processed in the plant of the nearby Aitik Cu-Au deposit. Copper will be the primary product and the trace metals Au andAg will be byproducts.The trace mineralogy of Liikavaara, however, differs from that of Aitik and this might have implications on the mineral processing and recovery efficiency. Gold occurs mostly as free <10μm-sized grains of native Au and electrum. Some Au is associated with native Bi, typically in <5μm Bi-melt drops. Gold grains commonly form inclusions in quartz and sulfide minerals. Silver is found in electrum, hessite and acanthite. Hessite is the most abundant Ag mineral and it is commonly intergrown with pilsenite. Similar to Au, inclusions and crack-fillings of Ag in sulfides and quartz are most prominent. The small grain size, the diverse mineralogy, the association with Bi-phases, and the occurrence as inclusions in quartz may lower the recovery of Au and Ag in Liikavaara compared to Aitik, where Au and Ag phases are mostly bound in sulfides. Hence, adaptation of the processing parameters may be necessary in order to increase recovery of Au and Ag from the Liikavaara ore.