Bulk microanalysis of assemblages of small fluid inclusions by LA-ICP-MS: Methodology and application to orogenic gold systems

Journal Pre-proof Bulk microanalysis of assemblages of small fluid inclusions by LA-ICP-MS: Methodology and application to orogenic gold systems ´ Zajacz, Joseph A. Petrus Gy¨orgyi Tuba, Daniel J. Kontak, Zoltan

PII:

S0009-2541(19)30433-4

DOI:

https://doi.org/10.1016/j.chemgeo.2019.119326

Reference:

CHEMGE 119326

To appear in: Received Date:

15 March 2019

Revised Date:

29 September 2019

Accepted Date:

3 October 2019

Please cite this article as: Tuba G, Kontak DJ, Zajacz Z, Petrus JA, Bulk microanalysis of assemblages of small fluid inclusions by LA-ICP-MS: Methodology and application to orogenic gold systems, Chemical Geology (2019), doi: https://doi.org/10.1016/j.chemgeo.2019.119326

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Bulk microanalysis of assemblages of small fluid inclusions by LA-ICP-MS: Methodology and application to orogenic gold systems Györgyi Tuba1, Daniel J. Kontak, Zoltán Zajacz2, Joseph A. Petrus Mineral Exploration Research Centre, Harquail School of Earth Sciences, Laurentian University, 935 Ramsey Lake Road, Sudbury, ON, P3E 2C6, Canada

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Zoltán Zajacz2 Department of Earth Sciences, University of Toronto, 22 Russell Street, Toronto, ON, M5S 3B1,

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Canada and Joseph A. Petrus

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Mineral Exploration Research Centre, Harquail School of Earth Sciences, Laurentian University,

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935 Ramsey Lake Road, Sudbury, ON, P3E 2C6, Canada 1

Corresponding author e-mail address: [email protected]

Present address: Mineral Resources and Geofluids, Section of Earth and Environmental Sciences,

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University of Geneva, 13 Rue des Maraîchers, 1205 Geneva, Switzerland Present address: Mineral Resources and Geofluids, Section of Earth and Environmental Sciences,

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University of Geneva, 13 Rue des Maraîchers, 1205 Geneva, Switzerland

Highlights

A new approach to bulk analyzing fluid inclusions by laser ablation is proposed

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Ablation of masses of small fluid inclusions returned viable and reproducible data

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Fluid-chemical changes on the micron scale may be traced with the method

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Applicable to fluid inclusions not suitable for individual laser ablation analysis

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Abstract 1

Microanalysis of individual fluid inclusions by laser ablation inductively coupled mass spectrometry (LA-ICP-MS) is a powerful tool for reconstructing the composition of hydrothermal fluids, but it demands a sample quality that is unattainable in many cases. In orogenic gold deposits, the need for direct fluid microanalysis has been present for several decades, but due to the high fluid flux and prolonged hydrothermal and tectonic history that typifies these systems,

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most samples do not meet the criteria of fluid inclusion size and distribution that allow LA-ICPMS analysis of individual isolated fluid inclusions. To overcome this difficulty, a method has been

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developed and tested, whereby areas of quartz densely populated with fluid inclusions (e.g., growth zones, secondary planes) are analyzed along a single continuous laser ablation profile; the

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generated signals are subsequently converted to time-slice datasets and plotted as element ratios

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in ternary diagrams to reconstruct specific major- and trace-element ratios. The estimated fluid compositions are in good agreement with previous analytical results of the same material

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(microthermometry, evaporate mound and conventional LA-ICP-MS) and are shown to be geologically viable on a boarder scale when compared to literature data from similar ore

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environments. The method has high spatial and chemical resolution, which allows the reconstruction of micro-scale fluid chemical changes, such as significant fluctuation in the relative element concentration (e.g., K, Rb, Ba, Sr and V versus Na, Li and As) during crystal growth, as observed in one of the test samples. The significance of this bulk LA protocol is that it allows the

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quick, easy and cost-effective microanalysis of samples that are typically inundated with fluid inclusions, such as those in orogenic and epithermal systems, which would otherwise not be amenable for further quantitative analysis to constrain fluid chemistry.

Keywords: fluid inclusions, LA-ICP-MS, fluid chemistry, orogenic gold deposits

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1. Introduction In situ LA-ICP-MS (laser ablation inductively coupled mass spectrometry) analysis of individual fluid inclusions (FI) has been shown to be an effective method for directly determining fluid chemistry in fossil hydrothermal systems (e.g., Audétat et al. 1998, Günther et al. 1998). The

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method has been widely applied and become essential for advancing our understanding of fluid evolution and metal transport in several ore systems: in particular porphyry Cu (e.g., Heinrich et

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al. 1999, Ulrich et al. 2002, Williams-Jones & Heinrich 2005, Landtwing et al. 2005), but also SnW (Audétat et al. 2000) and orogenic gold (Garofalo et al. 2014, Morales et al. 2016, Fusswinkel

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et al. 2017) deposits. An inevitable limitation of this method, however, is that it requires relatively

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large (>10 µm) and isolated FIs to prevent contaminating the target volume by accidentally breaching nearby inclusions and thus generating a mixed signal. The latter requirement is very

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rarely fulfilled in samples from some ore deposit settings, in particular orogenic gold deposits, where the quartz host, most often than not, is densely populated by multiple superimposed

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assemblages of small (typically 2–7 µm or less) FIs (Fig. 1). Other cases where such small, densely populated FIs occur are in epizonal settings where it is not uncommon to find primary growth surfaces of minerals inundated with FIs (e.g., Bodnar et al. 1985). This issue severely limits the availability of suitable material for in situ LA-ICP-MS analysis of single FIs and thus providing

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the essential fluid chemistry for some ore deposit types. Fluid inclusion microthermometric studies generally only provide limited and approximate

compositional data (i.e., XCO2, wt.% equiv. NaCl, major cation ratios; Roedder 1984, Bodnar & Vityk 1994, Bodnar et al. 2014). Consequently, despite several decades of research and numerous studies, such work has not contributed significantly new information and thus has limited

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advancing our understanding of the nature of orogenic fluids implicated in gold formation (see Bodnar et al. 2014 for summary). Whereas evaporate mound SEM-EDS analysis (Kontak 2004) provides the means to at least semi-quantitatively determine major- and minor-element chemistry (e.g., Kontak & Kyser 2011, Kontak & Tuba 2017, 2018), such analysis does not allow the characterization of fluids on the trace-element level or the characterization of individual inclusions

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with certainty. Similarly, whereas crush-leach methods provide quantitative chemical data to low detection limits (Banks & Yardley 1992, Gleeson 2003), they have the shortcoming of lack of

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resolution and the averaging of FI populations. An alternative approach is needed in order to advance further the database of fluid chemistry in different ore-deposit systems.

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This paper provides a summary and preliminary results of a new protocol which addresses

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the issues above: a complementary method to traditional LA-ICP-MS analysis of FIs that provides semi-quantitative chemical data for ore forming fluids trapped in minute, densely spaced

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inclusions. We address this by first describing the theoretical approach, protocol and sampling, analytical parameters and then provide results for two contrasting gold-deposit settings in the

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Archean Abitibi greenstone belt, Canada.

2. Theory of the Method

The concept of using laser ablation for fluid inclusion analysis emerged not long after the

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LA-ICP-MS method itself became an acknowledged micro-analytical method (e.g., Shepherd & Chenery 1995, Ghazi et al. 1996, Moissette et al. 1996, Audétat et al. 1998, Günther et al. 1998, Heinrich et al. 1999). The method involves the sampling of individual fluid inclusions by a focused laser beam that bores into the mineral host, breaches the inclusion and ablates the contained solid and/or fluid material, which is then transported from the sample chamber to the ICP-MS by an Ar

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or He carrier gas. Absolute element concentrations are calculated after subtracting the gas and matrix backgrounds and standardizing the fluid chemical signature against Na, which can be predetermined for each inclusion by using salinity estimates obtained by microthermometry. The method requires analyte FIs that are relatively isolated (to avoid breaching surrounding inclusions) and large enough (>10 µm) to produce reliable quantitative data by adequate signal to background

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ratio (Gagnon et al. 2003). Typical examples of orogenic vein quartz are very rarely suitable for the analysis of

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individual inclusions. These samples are inundated with FI, which merely reflect the nature of these systems: extended exposure to hydrothermal fluids and periods of deformation. In such

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situations, the high abundance of FIs warrants that LA-ICP-MS analysis of the host should result

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in a mixed chemical signal that reflects varying proportions of the quartz matrix and contained FIs. In theory, therefore, processing of such signals should generate chemical data about the fluid

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composition if the abundance of inclusions is high enough in the unit volume of quartz. The composition of fluid in this theoretical mixed signal, however, will be an average of all the

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(potentially different) fluid inclusion assemblages (FIA) present. In this case, the value of such information would be considered modest, thus the method has to have the resolution (either spatial or statistical) to distinguish among chemical subgroups. In order to address the above, we have designed a series of tests using the classic LA-ICP-

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MS method with a different approach. Here we use laser scanning along a line path to acquire a chemical profile across areas in quartz that are densely populated with FI and then process the element signals into a time-slice dataset (TSD), where each data point represents one complete analysis of the selected element list (i.e., one sweep of the MS; e.g., Gourcerol et al. 2018). The rationale behind this type of acquisition follows:

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(1) Spatial resolution and visual proofing. The nature and diversity of the FIA to be analyzed can be visually established before analysis and the TSD spatially matched to that, which allows one to track variations in chemical composition as a function of the FIA population(s). Potential contamination (e.g., epoxy in cracks, solid inclusions in quartz, etc.) can be verified visually and addressed.

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(2) Acquiring statistically robust data. Unlike analyzing an individual FI via breaching and complete extraction of a single inclusion volume, this method uses relatively fast ablation of

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multiple FIs which may result in highly variable individual readings for mechanical reasons (e.g., partial ablation of individual inclusions). By acquiring and plotting the individual data points

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extracted from the TSD, we generate a large database where clustering of results in confined

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compositional space would be considered to represent a meaningful chemical signal and haloes (i.e., outliers) would be plausibly attributed to contamination, such as solid inclusions in quartz.

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Among the theoretical limitations of the method, a significant one is the lack of absolute concentrations in ppm. To calculate concentration data, Si can be used as an internal standard

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(46.74 wt.% for quartz), as the quartz matrix is always present in the analysis, but that in itself skews the data since the quartz:fluid, and therefore the Si:Na, ratio is constantly changing as the beam traverses across variably inclusion-populated areas. Another possible limitation is that the elemental concentration in a given reading depends on both the volume of FI material analyzed

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and its composition, generally expressed as the inclusion salinity. Working with element ratios can, however, eliminate this problem (e.g., Samson et al. 2008) and may render chemical subgroups, if present, distinguishable. This approach is also necessary because of the lack of a fluid-representative internal standard (e.g., Na) that is based on previous microthermometric measurements of the ablated inclusions. The FIs primarily targeted in this study are those that are

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extremely challenging and time-consuming or impossible to carry out microthermometry on because of the minute size and the limitations on visual observations arising from that. In such inclusions, precise registration of phase changes that would allow an approximation of salinity and cation composition hinders using Na as an internal standard. Using element ratios without the need of such standard also allows a quick and effective identification and chemical characterization of

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distinct fluid groups (i.e., FIA). Expressing the fluid chemistry as element ratios also has the advantage of eliminating the

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problem of partial ablation of FIs. Partial ablation is unavoidable with this method as the laser beam targets an area with multiple FIs as opposed to a single, isolated object, and opening of

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additional inclusions in the damage zone around the laser trace is very probable. The contribution

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of these partially opened inclusions to the signal may raise the absolute concentrations, but inasmuch as the FIA is homogeneous and the analyzed elements are contained in a single phase in

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the inclusions (i.e., in the aqueous component with no daughter phases), the ratio of these elements will not be affected. If daughter minerals are left behind in the FI cavity during partial ablation,

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the escaping fluid phase represents neither the whole FI nor the original element ratios, and it may affect the analytical results depending on the size of the damage zone (and, thus, the relative amount of elements contributed by partially ablated heterogeneous FIs).

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3. Protocol and Sampling

The first phase of the study was designed to assess if the approach itself was viable and to

determine what fundamental sample requirements were necessary to ensure the generation of high quality, meaningful data. The main questions addressed were: (1) the detectability and robustness

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of signals coming from FI, (2) the viability and (3) the reproducibility of the generated data, and (4) the optimal instrumental conditions. For the initial testing of the method, two samples with contrasting attributes were used in the experiments. The first sample (GF-185) is a gold-bearing, crustiform quartz-carbonate vein from the Archean Grey Fox orogenic gold deposit (Ontario, Canada) (Fig. 2). The sample contains

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euhedral, coarse-grained (up to 1 cm) quartz (Fig. 2a, b) with a relatively simple fluid inclusion record. Primary FIAs present along densely-packed growth zones (Fig. 2c, d) have a moderate-

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salinity (avg. 7.1 wt.% NaCl equiv.), NaCl-K(-Ca?) aqueous fluid based on first and last ice melting temperatures (Te -26.8 to -22.6°C and Tmice -5.3 to -3.7°C, respectively), whereas cross-

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cutting secondary FIAs (Fig. 2b, e) represent several generations of NaCl-K(-Ca?) aqueous fluids

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with variable salinities (3.9 to 19.1 wt.% NaCl equiv.), again based on first and last ice melting (Te<-26.5°C and Tmice between -15.6 and -2.3°C, respectively). The lower first melting

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temperature of the secondary population as compared to primary FIAs may indicate higher amounts of additional, possibly divalent, cations to Na and K (Steele-MacInnis et al. 2016). Both

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types of inclusions are typically ≤2 µm in diameter and are therefore unsuitable for being ablated and analyzed individually using LA-ICP-MS. The areas selected for the experiment exhibit several growth zones representing a single primary FIA with high (typically 6 to 10 vol% in any unit volume of quartz) FI abundance and are essentially devoid of secondary FIA. Primary FIs have a

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generally homogeneous 3D distribution and size within the individual growth zones, warranting in theory a relatively constant fluid:matrix ratio in each sweep of the laser analysis. Occasional secondary FIAs are observed along fluid inclusion planes (FIP) in quartz sections otherwise devoid of primary FIAs; the fluid:matrix ratio in these areas depends on the orientation of the FIP relative

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to the laser path, and therefore may vary greatly from sweep to sweep. Sample GF-185 was also used to test viability and reproducibility of data using different instrumental settings. The second sample (144Gap) is a mineralized Archean orogenic quartz vein from the 144 Gap zone at Timmins West (Ontario, Canada) (Fig. 3). The area selected for analysis hosts three types of secondary inclusions: carbonic, aqueous-carbonic and aqueous inclusions (Fig. 3b to e).

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Based on our microthermometric and LA data of similar FIAs from the 144 Gap zone, the fluids are of NaCl-CaCl2 (aqueous-carbonic) and NaCl-KCl-CaCl2 (aqueous) composition with moderate

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(ca. 6 wt.% NaCl equiv.) to high (ca. 24 wt.% NaCl equiv.) salinity, respectively. In the sample used for the study, FIPs are relatively isolated in a FI-poor, clear area of quartz (Fig. 3a). The 2D

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distribution of FIs along the selected FIP was relatively homogeneous but the size of FIs within

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the FIAs varied from 1 to 10 µm. All selected FIPs had a subvertical orientation to the sample surface to maximize the fluid:matrix ratio during analysis. These FIAs were used to test the

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viability and spread of data acquired at relatively low (ca. 2 vol%) fluid:matrix ratios and to test whether chemical contrasts between the individual FIPs could be detected.

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In both of the samples described, FI-free areas of quartz were also analyzed by means of spot analysis to determine the composition of the host quartz.

4. Analytical and Data Processing Methods

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Approximate fluid:matrix ratios in the selected samples were determined from multifocal

photomicrographs using the image analysis software ImageJ (Schindelin et al. 2015). Laser ablation ICP-MS analyses were carried out at the Magmatic and Ore-Forming

Processes Research Laboratory at the University of Toronto (Canada), on a system comprising an NWR-193 UC excimer laser ablation system and an Agilent 7900 quadrupole mass spectrometer.

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The instrument was tuned to robust plasma conditions indicated by near equal sensitivity for Th and U; ThO production rates of <0.3% and doubly charged ion production rate <0.35% (monitored using 42Ca/Mass 21 ratios). The laser was operated at 10 Hz repetition rate with 12 J/cm2 energy density on the sample surface in all runs. Analyzed isotopes are 7Li, 11B, 23Na, 25Mg, 27Al, 29Si29, 34

S, 35Cl, 39K, 44Ca, 49Ti, 51V, 55Mn, 56Fe, 59Co, 62Ni, 65Cu, 66Zn, 75As, Br79, 85Rb, 88Sr, 107Ag, 118Sn, Sb, 133Cs, 137Ba, 140Ce, 182W, 197Au, 208Pb and 209Bi. The dwell time for all the elements was 10

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121

ms, except for Au (30 ms), adding up to a total sweep time of 402 ms (including 2 ms quadrupole

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settling between each mass). Feed time of the system was ca. 1 s; a glass mixing device for He and auxiliary Ar with about 20 cm3 internal volume was used in which the turbulent flow averages

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about 2-3 sweep-worth of ablated aerosol out. Line profiles were acquired by a rectangular laser

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beam (26x26 to 100x100 µm) with lateral scanning speed of the stage between 2 and 13 µm/s (Table 1). Beam size for square spot analysis of visually FI-free quartz varied between 50x50 to

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100x100 µm. The NIST SRM 610 silicate glass was used as an external standard and was measured twice at the beginning and end of each analysis block to allow for drift correction. Correction for

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Si16O with

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Ca was applied based on ThO production rates assuming

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the interference of

Ca/29Si = 0.0002. The raw data were processed by Iolite v3.6 (Paton et al. 2011) using the trace

elements data reduction scheme (Woodhead et al. 2007) and Si (46.7 wt. %) as the internal reference. Note that although an internal standard was used, the data are still considered semi-

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quantitative. The time resolved semi-quantitative data were exported from Iolite and further processed in the geochemical data analysis software ioGAS. Raw and TSD processed data are given in Tables A1 and A2, respectively. As Figure 4 demonstrates, the raw time-resolved LA signals closely mirror changes in FI abundance during acquisition, and are suitable for further studies. After acquisition and processing,

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data were handled in the same manner for all line profiles. For visual verification, the TSD of selected elements representing the contained fluid were plotted on elapsed time versus concentration diagrams and then matched to the photomicrographs showing the trace of line analyses by lining up the respective endpoints of the line diagram (excluding signals for gas blank and epoxy, if present) and the laser trace. Areas of major visual contrasts (i.e., growth zones with

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variable FIA abundances in GF-185 and the presence or absence of FIA in 144Gap) were distinguished in the photomicrograph and data points of the matching TSD sections assigned into

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data groups by using the data selection feature of ioGAS, where processing and plotting of all data groups were carried out as well.

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Spot analyses of relatively inclusion-free quartz was gathered to establish the background,

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but instead of calculating a single bulk composition for the spots, data were processed as TSD to get a “depth profile” in the selected areas. This means of data processing is necessary because FIs

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in these samples are typically so abundant that their accidental analysis cannot be avoided as the laser drills deeper into the grain, even if the analyzed area appears to be relatively inclusion-free

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on the surface. In such cases, even a small amount of FIs can raise the level of “fluid-indicator” elements (e.g., Na, K) in the analyses. By looking at the TSD data, those contaminating parts can be discarded and the rest of the analysis plotted as a data cloud, similarly to the line profile data, to get the quartz background for future reference.

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Calculated TSD data of profile and quartz spot analyses were compared to establish which

elements have higher affinity to FI-rich areas, i.e., which ones can be regarded as indicative for fluid composition in the mixed signals. Aluminum values were found to increase significantly and unrealistically in the FI-rich zones of GF-185 (cf. Tables A1 and A2) and were confirmed by means of CL imagery to have been caused by submicron grains of the gamma-alumina polishing agent

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collecting in the opened FI pits on the sample surface. Aluminum values, therefore, were disregarded from further studies. Sample GF-185 also contains pyrite and native gold in the vein assemblage, and a spike at the start of Fe, Pb and more rarely As signals in some profiles suggest possible smearing of these on the sample surface that may raise the measured absolute

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concentrations of these elements.

5. Analytical Results

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5.1 High fluid:matrix ratio profiles

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Seven line profiles across variably inundated growth zones and three spot analyses from FI-free areas of quartz were collected from sample GF-185 (Figs. 5 to 7). In all cases, the TSD

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profile diagrams lined up very well with the traces of the line profiles visually and the topology of certain element concentrations typical of fluid inclusions (e.g., Na, K; see Figs. 5b and 7b) closely

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follow the changes from FI-dominated zones to quartz-dominated areas, indicating that the fluid signature is reflected by the signal at the detector. Element concentrations in profile segments with

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high and relatively constant fluid:matrix ratios (i.e., primary FIA in growth zones) were selected and compared to those in quartz spot analyses (Fig. 8). Based on their general abundance and affinity to either the quartz matrix or the FI-rich areas, three element groups can be distinguished: 1) elements generally below detection limit in both phases, 2) elements with significantly more

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analyses above detection limit in the FI-rich areas, and 3) elements generally detectable in both phases. In sample GF-185, group 1 elements are Co, Ni, Ag, Ce, W, Au and Bi (Fig. 8). Among group 2 elements, average concentration values of B, V, Rb, Sr, Cs and Ba are at least a magnitude higher in FI-rich areas; other elements of the group (Mg, Ti, Mn, Fe, Cu, Zn and Pb) are more often detected in these sections but their average concentrations are not significantly higher than

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those in the quartz spot analyses. Similarly, in group 3, Li, Na, K and Sb are significantly enriched in the high fluid:matrix zones (Fig. 8), whereas Ca shows values similar to those in quartz. Profiles a03 to a05 in sample GF-185 transect euhedral quartz having a simple primary zonation that is composed of FI-inundated inner growth zones (zones 1 and 2) and a FI-poor mantle (zone 3) with occasional and isolated secondary FIPs (Fig. 5). The aim of these three profiles was

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to check the viability and reproducibility of the acquired data along different profiles in the same crystal. The Na-K-Ca ternary (Fig. 5c) shows that primary FIs of all three profiles plot into two,

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slightly overlapping data clouds in the K-rich part of the ternary, each representing a fluiddominated growth zone (zones 1 and 2), whereas inclusion-free quartz (spot analyses a22 to a24)

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cluster in the Ca apex. In contrast, where the beam intersected the transitional areas between zones

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of different FI abundance (i.e., mixture of zones 2 and 3), the resulting data plot along trends. Trend 1 is defined between zones 1 and 2 and the FI-free quartz composition at the Ca-dominated

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apex, whereas trends 2 and 3 originate in the quartz and primary (zones 1 and 2) fields, respectively, and converge towards a mixed Na-K-Ca composition. Based on the presence of

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secondary FIPs in the quartz-dominated zone 3, we interpret the Na-K-Ca domain where trends 2 and 3 terminate as the compositional field for secondary FIs in the sample. It is important to emphasize, however, that secondary FIAs were not directly analyzed in this sample, and so this is an indirect method for determining a hypothetical chemistry for this group of inclusions.

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Trace-element data for profiles a03, a04 and a05 are plotted in representative ternary

diagrams (Li-Sr-Ba and As-Rb-V, Fig. 5c). As with the major element plot for Na-Ca-K, groups are defined which equate the distinctly different chemical signatures for the primary FIs in zones 1 and 2 and the secondary FI population in zone 3. The FIs in zone 1 appear to be relatively more enriched in Ba, Sr, Rb and V than zone 2, whereas both primary zones have markedly different FI

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compositions than the inferred secondary FIAs. Furthermore, it is noted that the chemistry for the host quartz is depleted in Sr, Ba, Rb and V and falls at the Li and As apices of the ternaries and thus very different than the fields for the FIs. Profiles for another euhedral quartz grain from the same sample with multiple growth zones (Fig. 6) were used to check for internal consistency of data obtained with different instrumental

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settings, and to confirm primary fluid composition by analyzing multiple grains of the same sample. Ten consecutive growth zones were analyzed along two profiles, a07 and a08 (Fig. 6a, b),

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with contrasting beam diameters and scanning speeds of 50x50 µm and 3 µm/s versus 26x26 µm and 13 µm/s, respectively (Table 1). Data were plotted in the same ternary diagrams as above with

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the fields, as established for primary and secondary FIs as well as quartz, included (Fig. 6c). Note

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that due to the overlap of the major element data (Na-K-Ca) for zones 2 and 3 with 4 and 5, they are plotted in separate ternaries.

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Zone 1 in profiles a07 and a08 represents FI-poor quartz with occasional secondary FIPs and with additional low numbers of primary FIs in a08 (Fig. 6a). Furthermore, subzone 1a has

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lower fluid:matrix ratios than subzone 1b. Analyses of subzones 1a and 1b overlap in both profiles and in a07 they define a trend between quartz and the previously defined secondary FI field (Fig. 6b), whereas the trend in a08 is slightly more towards the K apex. This slight difference between the two profiles may reflect the higher amounts of FIs encountered in subzone 1b during the laser

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traverse. Data for zones 2 and 3 overlap and fall along the Na-K tie with low Ca, and are somewhat similar to the signature for the primary FIs in profiles a03 to a05 but less K-rich. The data for the a08 traverse again have slightly higher K:Na ratios than the a07 data. There is considerable overlap of the FI data for zones 2 and 3 with that of zone 4 and 5 and, in addition, collectively the entire data for zones 2 to 7 are noted to define a broad cluster with a change to higher K:Na ratios for

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zones 6-7. In contrast to zones 6-7, the data for zones 8 and 9 show a dramatic change in fluid chemistry with a shift to Na-rich compositions. The final zone analyzed, zone 10, which was only measured in profile a08, overlaps best with the FI data for zones 6-7. The compositional data for FIs from the second grain is in good agreement with not only the major element chemistry (i.e., Na-K-Ca) for profiles a03 to a05 for the first grain, but also for

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the trace elements as seen in the Li-Sr-Ba and As-Rb-V ternary plots (Fig. 6b). The Li-Sr-Ba data for all zones 1-10 overlap well with the field for zone 2 in profiles a03-05, whereas for As-Rb-V

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the data for zones 6 and 7 define a mixing trend between the two major clusters for primary fluid composition measured in profiles a03-05, and data for the other zones mainly fall in the field for

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zone 2 FIs in a03-05, but with some being skewed towards the area for secondary FIAs. The

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similarity of profiles a07 and a08 and the good agreement with compositional data from the previous analyses (a03 to a05) suggest that the contrasting instrumental settings (i.e., beam

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diameter and scanning speed) do not influence data reproducibility. The third quartz grain analyzed from sample GF-185 (Fig. 7) was used to further test data

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validation and its consistency. In this euhedral grain, a total of 12 growth zones with varying abundances of primary FIs are defined and were analyzed along profiles a18 and a21 (Fig. 7a, b). The data set generated in the two profiles was found to be very similar to those from the previous runs, as shown using the same ternary diagrams (Fig. 7c). Zones with low fluid:matrix ratio (zones

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1a, b and 12a, b) plot along compositional trends between the quartz host and the field for primary as well as secondary fields (identified previously). Zones 2 to 8 cluster tightly and overlap with the previously defined fields for primary FIs having high K:Na ratio, whereas zones 9 to 11 plot along a trend between the Na apex and the primary fields, similarly to zones 8 to 10 in profiles a07 and a08. Of particular note is the difference for the analyses in zones 9 and 10 for profiles a18

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versus a21. For profile a18 the data are more Na-rich whereas for a21 the data are coincident with the field for high K:Na primary FI. For the trace element ternary plots Li-Sr-Ba and As-Rb-V (Fig. 7c), the data plot in fields that coincide with the other profiles. 5.2 Low fluid:matrix ratio profiles Five line profiles were analyzed in sample 144Gap in areas having relatively low

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fluid:matrix ratios. In profiles a26, a29, a34 and a36, single FIAs aligned along FIPs were ablated (Fig. 9a), whereas profile a38 cuts across several FIAs having different types of FIs (Fig. 9b). The

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FIAs selected for analyses represent a spectrum of fluid compositions: 1) aqueous (a26 and a38);

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2) aqueous-carbonic with different H2O:CO2 ratios (a36 and a38); 3) carbonic (a38); and 4) two FIAs containing a heterogeneous population of aqueous-carbonic FIs due to post-entrapment

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modification (a29, a34 and a38). The line profiles were supplemented by 5 spot analyses of FIfree quartz to establish the matrix background (a27, a28, a35, a37, a39; Fig. 9a, Table 1).

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As expected, the influence of FIs in the 144Gap profiles is much less significant than in sample GF-185 with the high fluid:matrix ratio. Instead of clustering as seen in the primary FIAs

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of GF-185, the profile data points of the 144Gap sample plot along trends in Na-K-Ca ternaries (Fig. 9c). Data clouds for the different aqueous-carbonic and carbonic FIA (profiles a29, a34, a36 and a38) reveal very little compositional difference and define trends along the Na-Ca tie between the Ca apex, which represents the host quartz composition, and the Na-rich domain. The profile

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for the aqueous FIA in traverse a26 is somewhat different in that the trend terminates in a more Krich field compared to all the other FIAs. Because of the low fluid:matrix ratio, establishing the fluid-indicative elements in these profiles is somewhat problematic for two reasons: 1) many of the analytes remain close or below detection limit probably due to the high proportion of quartz in the mixed signals, and 2) average

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values are not a good approximation for fluid composition as the profile data do not form welldefined clusters and the fluid:matrix ratio is not constant from data point to data point. Although elements in the a26 profile were more frequently above detection limit than in the rest of the FIP and quartz analyses, Ti, V, Mn, Fe, Co, Ni, Cu, Ag, Ce, W, Au and Bi analyses commonly returned values below detection limit in all three environments (Fig. 10a). Among the elements more

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frequently detected in the fluid-bearing profiles, a26 shows at least two orders of magnitude increase in average Na, K, Sr and Pb as compared to the quartz analysis (Fig. 10b). This is a

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significant contrast in composition even though the average values in the fluid-bearing profiles are strongly influenced by the low fluid:matrix ratio, and therefore these are the elements best

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indicating the presence of the fluid in this profile. Additionally, at least an order of magnitude

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increase is showing in average Li, B, Zn, Rb, and Cs as well as a moderate increase in Ca (Fig. 10c). Fluid-bearing profiles a29, a34, a36 and a38 showed at least an order of magnitude

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enrichment in B, Na, K and As compared to quartz analyses and a moderate Ca-increase (Fig. 10b, c). The average concentrations of other detected elements are generally constant among the fluid-

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bearing profiles and quartz analyses (Fig. 10d).

In the density-contoured ternaries of the a26 profile (Fig. 9d), the major-element composition appears to converge toward the field for secondary FIs established in the Grey Fox sample, and the data set largely overlaps with the secondary FI field in the Li-Sr-Ba ternary too.

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The As-Rb-V ratios of a26 define a trend between the slightly Rb enriched field to the As apex (Fig. 9d), representative of the Grey Fox secondary FIs and the FI-free quartz composition, respectively.

6. Discussion

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6.1 Viability and reproducibility of bulk LA data for contrasting fluid:matrix ratios Trial runs to test for acquisition of fluid-characteristic elements were successful in samples with both high (GF-185) and significantly lower (144Gap) fluid:matrix ratios, but with varying quality of results. In sample GF-185, the signatures acquired from FI-inundated growth zones proved to be well clustered and generally identical - (1) within profiles, (2) among profiles in the

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same grain, and (3) among texturally identical FIAs contained in different quartz grains – which indicates good internal consistency of data. Scanning speed and beam diameter do not seem to

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have a significant effect on the analysis, as suggested by the good compositional agreement of data between profiles a07 and a08. The fluid-representative chemical signature was strong enough in

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these profiles to allow the characterization of the contained FIAs at the major-, minor- and trace-

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element levels.

In contrast to results for GF-185, analyses for relatively FI-poor zones in 144Gap fail to

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cluster, which is most likely a result of the low fluid:matrix ratio in the analyzed host. Thus, unlike for the FI-rich growth zones in GF-185 where it is possible to get a high number of consecutive

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readings at relatively constant and high fluid:matrix ratios, the fluid:matrix ratio varies from reading to reading depending on the dip angle of the analyzed FIP relative to the sample surface and its abundance of FIs, hence total abundance of FIs ablated and fluid volume released. Consequently, minor- and trace-element components of the fluid are either below detection limit

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or get masked by the trace-element composition of quartz, which is the case for all profiles but a26 in the 144Gap sample. With this method, it was possible to trace the chemical contrast between the quartz matrix,

primary FIs and several types of secondary FIAs. The major-element results in GF-185 are in general agreement with the composition of FIs determined using microthermometry; that is a

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contrast between the Na-K primary FIs and Na-K-Ca secondary FIs is clearly present in the LA data. However, as it was not possible to predetermine the absolute Na-K-Ca and trace-element concentrations by in situ LA-ICP-MS analysis of individual FIs, it cannot be gaged how accurately the compositional fields outlined with the bulk method reflect actual fluid compositions. Nevertheless, the excellent reproducibility and robustness of the data for both major (Na, K, Ca)

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and minor to trace element levels (e.g., Li, Ba, Sr, As, V, Rb) and the general agreement with independent chemical analysis suggest that the results are internally consistent and can, therefore,

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be used in context with other types of FI analyses.

The lack of data clustering in the low fluid:matrix ratio sample (144Gap) makes it

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somewhat less straightforward to assess fluid composition. The example of secondary FI in GF-

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185 showed that it is possible to infer a fluid composition from trends where one endmember is known. In the 144Gap sample, the mixed signals always come from the quartz matrix and one

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specific FIA that is either homogeneous or composed of FIs modified by post-entrapment deformation. Modification may result in the change of absolute salinity, but does not alter the ratio

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of contained cations (in inclusions without daughter minerals), therefore the only factor that may cause the Na-K-Ca ratio to shift is the amount of contained quartz (with high Ca:Na) versus fluid (lower Ca:Na). Logically it can be assumed, therefore, that the compositional field closest to representing the fluid itself lies at the Na-proximal extremity of the acquired trends. Naturally, this

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approximation only allows a very rough estimate, whereby the a26 profile for secondary FIA in 144Gap would have a Na-rich Na-K-Ca composition and all the others were Na-rich Na-Ca fluids. Even though these estimates are very approximate, the inferred composition of the aqueouscarbonic FIAs are in general agreement with LA-ICP-MS data for individual FIs from petrographically similar FIAs from samples in this deposit (Fig. 11a).

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The inferred composition of the aqueous FIA in profile a26 is very similar to the secondary aqueous fluid composition analyzed in sample GF-185 (Fig. 9d) in terms of both major- and minorto trace-element contents. Although the two deposits are geologically unrelated, both contain secondary, post-mineralization aqueous fluids that likely represent regional basinal brines reported for many orogenic deposits in the Canadian Shield (e.g., Olivo et al. 2006, Neumayr et

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al. 2007, Rezeau et al. 2017, Kontak & Tuba 2018). Laser-ablation data of individual FI and evaporate mound analysis carried out on this late fluid in other Abitibi deposits (Kontak & Tuba

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2018) are in good agreement with the estimated compositions based on the bulk LA method (Fig.

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11b).

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6.2 Comparison of the LA bulk analysis method with conventional fluid inclusion studies This study provides insight into a new analytical protocol to acquire chemical data for FIs

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that, due to their size and population density, preclude being analyzed with more conventional methods. In addition, the results validate the procedure applied to representative samples from

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relevant orogenic gold deposit settings. Some of the important implications of the LA bulk analysis method in the context of FI studies applied to ore deposit settings are provided below. 1. The LA bulk method can effectively distinguish among fluids with different chemical properties even in samples with relatively small FIs. As we have noted above, such material is common in a

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variety of high fluid flux settings and/or where rapid growth textures occur (Fig. 1). The chemistry acquired from such analyses can thus be used to both detect and discriminate the chemical evolution of an ore system where conventional microthermometry and evaporate mound analysis on such FI populations would fail. Thus, the method provides insight unattainable otherwise.

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2. Sample preparation and analysis are fast and easy and the method does not require an internal standard established by often laborious microthermometry. 3. This method can provide invaluable insight into fluid evolution in growth-zoned samples, such as GF-185, due to its spatial resolution. Also relevant is the visual trace provided by the method for future reference if needed. The applicability of the method to such samples has been well

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illustrated using several profiles (e.g., a03-05, a07-08, a18, a21; Figs. 5 to 7), which clearly show that not only do the individual growth zones define well-constrained chemical groups, but also

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apparent are gradual to abrupt changes in fluid composition during crystal growth in regards to both the major- and trace-element chemistry. For this study, the latter is reflected by the recurring

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relative enrichment or depletion of fluid chemistry in multi-element chemical space using selected

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ternary plots – Na-K-Ca, Li-Sr-Ba, As-Rb-V (Fig. 12). Such a fluid-chemical path would not be possible to reconstruct using any of the conventional methods employed in FI studies, either

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because of the lack of adequate chemical and/or spatial resolution (e.g., microthermometry, evaporate mound analysis) or because the inundated growth zones are not suitable for conventional

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in situ LA microanalysis. This has important implications for ore deposit studies, as changes in fluid chemistry is both expected and observed in many ore deposit types and often equates with onset of mineralization (e.g., Audétat et al. 2000, Kontak & Clark 2002, Rottier et al. 2018).

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6.3 External data integrity in comparison with existing LA-ICP-MS data To further assess data validity, the profiles representative of primary fluid compositions in

the Grey Fox orogenic gold deposit (GF-185) are compared to LA-ICP-MS data acquired for individual FIs for orogenic gold, intrusion-related gold (IRG) and Ag-Ag veins, and porphyry ore deposit settings in Figure 13. The data are plotted in three ternaries - Rb-As-Ba, Rb-B-Sr and Cu-

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Sb-Zn - to accommodate available literature data and be discriminative in regards to the different deposit types. We note that this is not intended to be an in-depth assessment of such plots, but merely an attempt to compare and contrast the newly generated data of this study with some similar data in the literature. The individual GF-185 profiles cluster and overlap with the exception of profiles a03 to 05, which appear to be more enriched in Cu than the other profiles relative to Sb

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and Zn (Fig. 13a). Compared with various barren and variably mineralized orogenic veins (Fig. 13b), the Grey

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Fox data is similar to: 1) barren orogenic quartz veins of the Rhenish Massif, Germany (Marsala et al. 2013) in the Rb-As-Ba ternary; 2) barren and gold-bearing orogenic veins in the Rb-B-Sr

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ternary (Rauchenstein-Martinek et al. 2016, Fusswinkel et al. 2017); and 3) mineralized orogenic

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veins from the Neoarchean of Finland (Fusswinkel et al. 2017) in the Cu-Sb-Zn plot. Also overlapping with the latter, are data for Ag-Sb vein deposits of the Coeur d’Alene district, USA,

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which Hofstra et al. (2013) argue are mixed magmatic-metamorphic fluids. Of note is that the data for Grey Fox differ for FI data for the Carlin samples in all the ternary plots. Large et al. (2016)

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argue based on the FI data that the deposits studied are of magmatic origin. Lastly, data for Neoarchean BIF-hosted gold vein systems in Brazil differ from the Grey Fox data in the Cu-SbZn ternary.

In terms of magmatic-related ore systems, the Grey Fox data are also compared to FI data

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for IRG (Ridley 2008, Schindler et al. 2016) and porphyry (Ulrich et al. 2002, Williams-Jones & Heinrich 2005, Landtwing et al. 2005, Klemm et al. 2007) systems. As is evident from the plots, there is no strong overlap of any of the fluid chemistry, which strongly suggests a non-magmatic geochemical affinity of these fluids.

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This summary and comparison of the data for the Grey Fox sample analyzed shows that the bulk LA method for analyzing FIs is capable of producing fluid-chemical data that are both specific to an ore system and allows comparison with similar data for other hydrothermal ore settings. In this case, the data presented suggest that for Grey Fox the fluid chemistry, as

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constrained by element ratios, is more similar to data for metamorphic settings.

6.4 Evaluation of the method and future work

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The results of the current study, the first of its kind that we are aware of, show that bulk

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analysis of FIs using a modified laser ablation analytical protocol offers promise for determining elemental ratios of FI populations. Among the advantages of the method are the fast and easy

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sample preparation and the excellent visual control on data acquisition. Relatively low salinity and small FI size do not seem to preclude using such material such that a robust chemical signal can

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be obtained if the FI abundance (i.e., fluid:matrix ratio) in the sample is adequate. It is apparent from the above that element ratios work well and provide a basis for fluid discrimination.

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Importantly, it appears that the ratios are not influenced by partial ablation (if no daughter mineral is present) or deformation/modification of fluid inclusions. In addition, fluid salinity estimates, which can be an issue for some FIAs, are not needed. Where good quality signals are obtained reflecting high fluid:quartz ratios, minor- and trace-element ratios can be obtained which are

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critical for contrasting fluid types and fluid evolution in an evolving hydrothermal system. Beside the positive results, the bulk LA method also has, at present, some significant

limitations in the areas of sample requirements and methodology, which are addressed in detail in the following sections. 6.4.1 Required FI abundance and size

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The minimum FI abundance needed to generate meaningful data is a crucial question, as illustrated by the 144Gap sample. Low fluid:matrix ratios may become critical for elements whose total mass in the volume of ablated fluid approaches that of the mass of the same element in the ablated host (in this case quartz). Loosely and/or heterogeneously distributed FIs in the analyzed FIAs and FIPs oriented at a high angle to the laser path also result in very variable fluid:matrix

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ratio along the profile, which, together with low fluid:matrix ratios, prohibits the clustering of the data, as seen in the 144Gap sample and the secondary FIAs intersected in GF-185. To breach a

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high number of inclusions in any one pulse is also important considering that the timing of inclusion burst within the sweep cycle coupled with the possible fractionation of elements due to

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different wash out times may result in skewing the laser spectrum (Pettke et al. 2000). Petrographic

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estimations shows that in the densely populated growth zones of sample GF-185 the number of FIs breached during a complete sweep cycle is several tens at minimum, therefore the above issue

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is likely insignificant in this case. As a contrast, in the loosely packed secondary FIPs of sample 144Gap this number is very low (<5 inclusions) and this may be reflected in the data quality.

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Another aspect that may play a role in the contrast of data quality between the two studied samples is the size of inclusions and thus the mechanism by which they decrepitate upon ablating. The growth zones of GF-185 are composed of minute FIs with a very homogeneous size distribution of typically 1-2 µm. These inclusions were analyzed with a significantly greater beam

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size of 50x50 µm and thus most of them likely ablated in their entirety into the plasma. Partial ablation, splashing and/or bleeding into the chamber (Günther et al. 1998) probably occurs at the fringe of the beam area in the damage zone, but these not necessarily affect the analysis significantly as the proportion of these areas is low compared to the ablated volume and the FIs contain no daughter minerals that would skew the element ratios if removed. Partial opening

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instead of total ablation within the analyzed volume is much more likely in the 144Gap sample, where the size distribution in some of the FIAs ranges from 1 µm up to 10 µm. These aspects demonstrate that the minimum required FI abundance varies for each case as it logically depends on fluid salinity and chemistry (i.e., concentration of elements in the fluid), but the example of GF-185 shows that about 5-6 vol% uniformly distributed, moderate-salinity

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inclusions are adequate to acquire a good quality data set. Small (<3 µm) inclusions are likely better candidates for the method than larger ones.

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6.4.2 Homogeneity of the analyzed FIA

Our experiments presented here have been set up so that the target either contained a single

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fluid (growth zones in GF-185 and secondary FIPs in profiles a26, a29, a34 and a36 of 144Gap)

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or the different analyzed FIAs were spatially separated (profile a38 crossing various FIAs in 144Gap), which allows the extraction of FIA-specific data from the respective TSD section.

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Although data from sample 144Gap are of lower quality due to the low fluid:matrix ratio, the results presented here proved to be remarkably consistent and effective in measuring densely fluid-

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populated growth zones (GF-185) to the point where minor- and trace-element variations can be outlined, potentially suggesting changes in fluid composition during quartz growth. Thus, with the protocol used here, i.e., analysis of large numbers of FIs and plotting elemental ratios, extracting meaningful signals from complicated FI populations would be possible if the FIAs are spatially

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separated. Although the euhedral, crustiform quartz of the Grey Fox veins is somewhat atypical to orogenic gold deposits based on our experience, such crystal types are abundant in epithermal deposits where this method could be of potential use. Another application is where minerals opaque to white light are known to contain abundant FIs, such as pyrite, wolframite, stibnite, and enargite (e.g., Lüders & Ziemann 1999, Hagemann & Lüders 2003, Kouzmanov et al. 2010,

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Lüders 2017). By first locating areas of high FI populations using infrared light, such regions can be analyzed in the manner described here and large amounts of fluid-chemical data generated, although high elemental background concentrations will of course be an issue. This method may be particularly relevant in cases where salinity values are compromised due to the variability of infrared intensity and mineral chemistry which is known to affect Tmice and thus inferred fluid

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chemistry, as discussed by Lüders (2017). The lack of spatial separation, i.e., the overlap of several FIAs of chemically distinct fluids

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remains a problem, and assessing the method’s viability in such complex samples, which commonly typify orogenic quartz vein samples, remains to be investigated. In this case we cannot

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rely on the spatial resolution of the proposed bulk method and likely would have to focus on

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statistical solutions. 6.4.3 Absolute element concentration data

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One of the most significant limitations of the method is that it can offer no absolute concentration data as the number of inclusions analyzed and, thus, the amount of contained fluid-

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specific elements vary from detection to detection. Of course, this problem can be obviated if sufficient salinity determinations can be obtained to ensure a similar salinity in the FIA. In such cases, a similar protocol as used in conventional in situ LA-ICP-MS analysis of individual FIs would be employed.

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A logical step towards an attempt to calculate absolute concentration data with the bulk

method would be the subtraction of the quartz matrix from the acquired signals; however, the heterogeneity of quartz poses a problem, as the composition of quartz can vary considerably depending on its setting and even within a single grain (Allan & Yardley 2007, Jacamon & Larsen 2009, Breiter et al. 2013, Ackerson et al. 2015, Müller et al. 2015, Mao et al. 2017). To assess the

26

effect of heterogeneous matrix contribution to fluid composition in the present study, we subtracted the different quartz profiles from the respective bulk FI analyses, and summarized the results in Figure 14. Assuming homogeneous fluid compositions throughout the analyzed FIAs, all intervals of the raw profile signals representing the targeted FIA (i.e., intervals with relatively high fluid:matrix ratios) were integrated to calculate the (averaged) absolute fluid composition by

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using the LA-ICP-MS data reduction software SILLS (Guillong et al. 2008). As an internal standard, the average salinity of 7.7 wt% NaCl equiv. was used for GF-185 profiles a03-05, a07-

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08 as well as a18 and a21, whereas for a26, a29 and a36 in 144Gap we used 16.1 wt% and 4.7 wt% NaCl equiv. respectively (based on microthermometry data of similar FIAs in the same

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samples). For matrix subtraction, homogeneous intervals at least 10 seconds long were integrated

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in profiles a23-24 (GF-185) as well as a27-28, a35, a37 and a39 (144Gap). The selected box plots in Figure 14 show that the calculated fluid compositions are highly variable regarding elements

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with significant heterogeneity in quartz (e.g., Ca, Li), and that the 144Gap matrix composition is more homogeneous, and thus produces narrower compositional ranges, than the Grey Fox quartz.

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The implication of these findings is that if, in the future, attempts are being made to quantify element concentrations acquired by this method, matrix heterogeneity has to be taken into consideration and analyses designed such that it can be overcome as a difficulty. Establishing the matrix composition as spatially close as possible to the analyzed profile would be essential, but

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given the nature of these samples (i.e., very highly populated with FIs) in itself will prove to be problematic. Furthermore, by integrating the entire profile signal into one averaged data point assuming homogeneous fluid chemistry over the whole analysis may be misleading, as seen in the case of Grey Fox profiles a07-08, a18 and a21. This is an area of future development; however, we see the major application of the method as a tool to distinguish chemically contrasting fluids

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and resolve small-scale chemical fluctuations, and these are entirely possible by using element ratios without the need of quantification. 6.4.4 Intragrain matrix heterogeneity As Figure 14 demonstrates, the average trace element composition of the quartz matrix may vary significantly among grains of the same sample. This variation in itself does not affect

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the mapping of fluid chemical changes within a single grain when element ratios are used. Chemical zonation within the host, however, may influence the element ratios in the mixed fluid-

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quartz signals, therefore this issue needs to be addressed.

Cathodoluminescence (CL) imagery reveals an essentially homogeneous quartz matrix in

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sample 144Gap (Fig. 15a), thus the problem of matrix heterogeneity is negligible in this case.

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However, strong intragrain zonation is present in GF-185 (Fig. 15b, c). The chemical nature of this quartz zonation cannot be directly determined because of the large amount of FIs in the growth

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zones but inferences can be made on the level of contribution of certain elements to the mixed LA signals due to quartz heterogeneity. Considering the fluid-indicative elements (Fig. 8), the depth

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profiles of FI-free quartz spot analyses a23 and a24 show no significant zonation of B, V, Rb, Sr, Ba and As, slight zonation of Na as well as coupled zonation of Li and K in a24 on an order of magnitude level in concentration (Fig. 15d, e). The depth profiles also reveal that these elements, zoned or not, remain on concentration levels significantly below those measured in FI-rich profiles

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(cf. Fig. 8). Similarly, FI-poor and FI-rich segments within other profiles (e.g., zone 3 in a03 to a05, zones 1a, 1b, 12a and 12b in a18 and a21 compared to the rest of the signal) also show this sharp contrast in element concentrations (Figs. 5b and 7b). (Note that the depth profiles of a23 and a24 only represent ca. 120-µm segments of quartz and would not be sufficient to reveal chemical zonation on a larger scale.)

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Comparing the CL zonation pattern to the growth zonation delineated by FIs in GF-185, it appears that the two do not necessarily match. The underlying CL zonation in the hosts for profiles a18 and a21 is much finer and more complicated than suggested by the FI growth zonation (Fig. 15b), and the CL response of the two grains themselves are different along the profiles. As a contrast, in the grain hosting profiles a03 to a05 the CL zonation shows a similar core-mantle type

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of zonation as the FIAs (Fig. 15c). Despite this, the semi-quantitative data for the primary FIAs measured in the five profiles hosted by three variably zoned quartz grains overlap (Figs. 5c and

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7c), suggesting that the matrix composition has insignificant effect on the analytical results.

It may be assumed, therefore, that chemical zonation of the quartz host does not influence

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significantly the characteristic element ratios of the FIAs. An addition to this in the special case of

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sample GF-185 is that since these are primary FIAs representing the fluid from which the host itself precipitated, any change in the host chemistry (i.e., zonation) should be traceable directly in

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the primary FIAs. The chemical change also should be amplified in the fluid phase because of the low compatibility of these elements in quartz.

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6.4.5 Requirements for future work

The intention of present study was to evaluate whether useful in situ chemical information could be obtained from fluid inclusion groups that otherwise would be deemed unsuitable for microanalysis. Although we see much promise in the technique based on the preliminary results

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presented here, these are only the first steps towards a fully functioning and routinely applied method. The next, and most important, step should focus on quantifying data precision by comparing element ratios acquired by the bulk method versus analysis of individual fluid inclusions of the same FIA. This should be carried out on natural or synthetic samples that host

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FIs in homogeneous, densely populated FIAs that are suitable for both individual and bulk LA analysis. Experiments on FIAs with high-salinity FIs containing daughter minerals should be carried out in order to evaluate the effect of partially ablated heterogeneous inclusions on the calculated

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element ratios. The effect of inclusion size on data quality should also be studied closely.

7. Conclusions

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Orogenic gold deposits are not well understood from the fluid chemistry point of view (e.g., Bodnar et al. 2014, Kontak & Tuba 2017), partly because in situ LA-ICP-MS analyses of

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individual FIs are, in many cases, limited by the high density of variable FI types in superimposed

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FIAs that populate vein quartz. In an attempt to overcome the challenge of fully characterizing the fluid chemistry of FIs in such settings beyond the conventional salinity estimates, a new bulk

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analysis approach using laser ablation traversing of FI-rich areas in quartz has been outlined and preliminary tests evaluated. These results show that: (1) a robust chemical signal from ablated FI

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populations can be detected at a high spatial resolution; (2) the acquired data are reproducible with high precision; (3) the estimated compositions equate to LA-ICP-MS data of individual FIs from the same sample; (4) the method is capable to distinguishing fluid populations at major- and minorto trace-element concentrations; and (5) the results are representative of the ore system based on

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the comparison with LA-ICP-MS data on individual FIs from other studies. As such, the method provides application to a variety of ore deposit settings where conventional LA-ICP-MS methodology of analyzing individual FIs is challenging. Results reveal that the main limiting factor of the method is probably FI abundance and, thus, the low volume fraction of the aqueous component of the FI, such that the fluid chemical signal is masked by that of the ablated host.

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8. Acknowledgements This work was supported financially by the Goodman School of Mines, the Geological Survey of Canada TGI program (TGI-5), and the Mineral Exploration Research Centre of Laurentian University. Thanks in particular to Drs. B. Jago and R. Sherlock for their support,

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encouragement and recognition of the value of this work. The fluid inclusion laboratory used in this project at Laurentian University was established using NSERC funding granted to Daniel

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Kontak. Zoltán Zajacz acknowledges the financial support of NSERC in the form of a Discovery

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Grant. The LA-ICP-MS facility used for this research was constructed with the financial support of a Canada Foundation for Innovation – Leaders Opportunity Fund grant and an Ontario Research

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Fund – Small Infrastructure grant to Zoltán Zajacz. We thank Willard Desjardin of the Harquail School of Earth Sciences for preparation of fluid inclusion sections and Primero Gold Mining, now

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McEwen Mining Inc., for access and sampling at the Grey Fox deposit site, as well as Tahoe Resources for access and sampling the 144 Gap zone at Timmins West mine. The review of the

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paper by Thomas Ulrich and an anonymous reviewer is gratefully acknowledged.

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9. References

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ACKERSON M. R., TAILBY N. D. & WATSON E. B. 2015. Trace elements in quartz shed light on sediment provenance. Geochemistry, Geophysics, Geosystems 16: 1894–1904. ALLAN M. M. & YARDLEY B. W. D. 2007. Tracking meteoric infiltration into a magmatic-hydrothermal system: A cathodoluminescence, oxygen isotope and trace element study of quartz from Mt. Leyshon, Australia. Chemical Geology 240: 343–360. AUDÉTAT A., GÜNTHER D. & HEINRICH C. A. 1998. Formation of a magmatic-hydrothermal ore deposit: Insights with LA-ICP-MS analysis of fluid inclusions. Science 279: 2091–2094. AUDÉTAT A., HEINRICH C. A. & GÜNTHER D. 2000. Causes for large-scale metal zonation around mineralized plutons: Fluid inclusion LA-ICP-MS evidence from the Mole Granite, Australia. Economic Geology 95: 1563–1581. BANKS D. A. & YARDLEY B. W. D. 1992. Crush-leach analysis of fluid inclusions in small natural and synthetic samples. Geochimica et Cosmochimica Acta 56: 245–248. BODNAR R. J., LECUMBERRI-SANCHEZ P., MONCADA D. & STEELE-MACINNIS M. 2014. Fluid inclusions in hydrothermal ore deposits. In: Treatise on Geochemistry (Ed. by H. D. Holland & K. K. Turekian), pp. 119–142. Elsevier, Oxford, UK ; San Diego, CA, USA. BODNAR R. J. & VITYK M. O. 1994. Interpretation of microthermometric data for H2O-NaCl fluid inclusions. In: Fluid inclusions in minerals: Methods and applications (Ed. by Benedetto. De Vivo & M. Luce. Frezzotti), pp. 117–130. Virginia Technical Institute, Blacksburg, VA. BODNAR R., REYNOLDS T. J. & KUEHN C. A. 1985. Fluid inclusion systematics in epithermal systems, in Berger, B.R., and Bethke, P.M., eds., Geology and Geochemistry of Epithermal Systems. Reviews in Economic Geology 2: 73–97. BREITER K., ACKERMAN L., SVOJTKA M. & MÜLLER A. 2013. Behavior of trace elements in quartz from plutons of different geochemical signature: A case study from the Bohemian Massif, Czech Republic. Lithos 175–176: 54–67. FUSSWINKEL T., WAGNER T. & SAKELLARIS G. 2017. Fluid evolution of the Neoarchean Pampalo orogenic gold deposit (E Finland): Constraints from LA-ICPMS fluid inclusion microanalysis. Chemical Geology 450: 96–121. GAGNON J., SAMSON I., FRYER B., SAMSON I., ANDERSON A. & MARSHALL D. 2003. LA-ICP-MS analysis of fluid inclusions. In: Fluid Inclusions: Analysis and Interpretation pp. 291–318. Mineralogical Association of Canada. GAROFALO P. S., FRICKER M. B., GÜNTHER D., BERSANI D. & PAOLO LOTTICI P. 2014. Physical-chemical properties and metal budget of Au-transporting hydrothermal fluids in orogenic deposits. Geological Society, London, Special Publications 402: 71–102. GHAZI A. M., MCCANDLESS T. E., VANKO D. A. & RUIZ J. 1996. New quantitative approach in trace elemental analysis of single fluid inclusions: applications of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Journal of Analytical Atomic Spectrometry 11: 667–674. GLEESON S. A. 2003. Bulk analysis of electrolytes in fluid inclusions. In: Fluid inclusions: Analysis and interpretation (Ed. by I. M. Samson, A. Anderson & D. Marshall), pp. 233–247. Mineralogical Association of Canada. GOURCEROL B., KONTAK D. J., THURSTON P. C. & PETRUS J. A. 2018. Application of LA-ICP-MS sulfide analysis and methodology for deciphering elemental paragenesis and associations in addition to multistage processes in metamorphic gold settings. Canadian Mineralogist 56: 39–64. GUILLONG M., MEIER D. L., ALLAN M. M., HEINRICH C. A. & YARDLEY B. W. D. 2008. SILLS: A MATLAB-based program for the reduction of laser ablation ICP-MS data of homogeneous materials and inclusions. In: pp. 328–333. Mineralogical Association of Canada.

32

Jo

ur na

lP

re

-p

ro

of

GÜNTHER D., AUDÉTAT A., FRISCHKNECHT R. & HEINRICH C. A. 1998. Quantitative analysis of major, minor and trace elements in fluid inclusions using laser ablation–inductively coupled plasma mass spectrometry. Journal of Analytical Atomic Spectrometry 13: 263–270. HAGEMANN S. G. & LÜDERS V. 2003. P-T-X conditions of hydrothermal fluids and precipitation mechanism of stibnite-gold mineralization at the Wiluna lode-gold deposits, Western Australia: Conventional and infrared microthermometric constraints. Mineralium Deposita 38: 936–952. HEINRICH C. A., GÜNTHER D., AUDÉTAT A., ULRICH T. & FRISCHKNECHT R. 1999. Metal fractionation between magmatic brine and vapor, determined by microanalysis of fluid inclusions. Geology 27: 755–758. HOFSTRA A. H., MARSH E. E., TODOROV T. I. & EMSBO P. 2013. Fluid inclusion evidence for a genetic link between simple antimony veins and giant silver veins in the Coeur d’Alene mining district, ID and MT, USA. Geofluids 13: 475–493. JACAMON F. & LARSEN R. B. 2009. Trace element evolution of quartz in the charnockitic Kleivan granite, SWNorway: The Ge/Ti ratio of quartz as an index of igneous differentiation. Lithos 107: 281–291. KLEMM L. M., PETTKE T., HEINRICH C. A. & CAMPOS E. 2007. Hydrothermal evolution of the El Teniente deposit, Chile: Porphyry Cu-Mo ore deposition from low-salinity magmatic fluids. Economic Geology 102: 1021–1045. KONTAK D. J. 2004. Analysis of evaporate mounds as a complement to fluid-inclusion thermometric data: Case studies from granitic environments in Nova Scotia and Peru. Canadian Mineralogist 42: 1315–1329. KONTAK D. J. & CLARK A. H. 2002. Genesis of the giant, bonanza San Rafael lode tin deposit, Peru: Origin and significance of pervasive alteration. Economic Geology 97: 1741–1777. KONTAK D. J. & KYSER K. 2011. A fluid inclusion and isotopic study of an intrusion-related gold deposit (IRGD) setting in the 380 Ma South Mountain Batholith, Nova Scotia, Canada: Evidence for multiple fluid reservoirs. Mineralium Deposita 46: 337–363. KONTAK D. J. & TUBA G. 2017. How can fluid inclusion studies better constrain orogenic gold deposit models: Case studies from the Superior Province and Meguma Terrane, Canada. In: Volume Proceedings of Extended Abstracts p. 55. Quebec, Canada. KONTAK D. J. & TUBA G. 2018. Summary of results of a fluid inclusion (FI) study of gold deposit settings in the Archean Abitibi greenstone belt: A TGI-5 initiative. In: p. 61. Unpublished Report, Geological Survey of Canada. KOUZMANOV K., PETTKE T. & HEINRICH C. A. 2010. Direct analysis of ore-precipitating fluids: Combined IR microscopy and LA-ICP-MS study of fluid inclusions in opaque ore minerals. Economic Geology 105: 351–373. LANDTWING M., PETTKE T., HALTER W., HEINRICH C., REDMOND P., EINAUDI M. & KUNZE K. 2005. Copper deposition during quartz dissolution by cooling magmatic–hydrothermal fluids: The Bingham porphyry. Earth and Planetary Science Letters 235: 229–243. LARGE S. J. E., BAKKER E. Y. N., WEIS P., WÄLLE M., RESSEL M. & HEINRICH C. A. 2016. Trace elements in fluid inclusions of sediment-hosted gold deposits indicate a magmatic-hydrothermal origin of the Carlin ore trend. Geology 44: 1015–1018. LÜDERS V. 2017. Contribution of infrared microscopy to studies of fluid inclusions hosted in some opaque ore minerals: possibilities, limitations, and perspectives. Mineralium Deposita 52: 663–673. LÜDERS V. & ZIEMANN M. 1999. Possibilities and limits of infrared light microthermometry applied to studies of pyrite-hosted fluid inclusions. Chemical Geology 154: 169–178. MAO W., RUSK B., YANG F. & ZHANG M. 2017. Physical and chemical evolution of the Dabaoshan porphyry Mo deposit, South China: Insights from fluid inclusions, cathodoluminescence, and trace elements in quartz. Economic Geology 112: 889–918.

33

Jo

ur na

lP

re

-p

ro

of

MARSALA A., WAGNER T. & WÄLLE M. 2013. Late-metamorphic veins record deep ingression of meteoric water: A LA-ICPMS fluid inclusion study from the fold-and-thrust belt of the Rhenish Massif, Germany. Chemical Geology 351: 134–153. MOISSETTE A., SHEPHERD T. J. & CHENERY S. R. 1996. Calibration strategies for the elemental analysis of individual aqueous fluid inclusions by laser ablation inductively coupled plasma mass spectrometry. Journal of Analytical Atomic Spectrometry 11: 177–185. MORALES M. J., FIGUEIREDO E SILVA R. C., LOBATO L. M., GOMES S. D., GOMES C. C. C. O. & BANKS D. A. 2016. Metal source and fluid–rock interaction in the Archean BIF-hosted Lamego gold mineralization: Microthermometric and LA-ICP-MS analyses of fluid inclusions in quartz veins, Rio das Velhas greenstone belt, Brazil. Ore Geology Reviews 72: 510–531. MÜLLER A., IHLEN P. M., SNOOK B., LARSEN R. B., FLEM B., BINGEN B. & WILLIAMSON B. J. 2015. The chemistry of quartz in granitic pegmatites of Southern Norway: Petrogenetic and economic implications. Economic Geology 110: 1737–1757. NEUMAYR P., HAGEMANN S. G., BANKS D. A., YARDLEY B. W., COUTURE J.-F., LANDIS G. P. & RYE R. 2007. Fluid chemistry and evolution of hydrothermal fluids in an Archaean transcrustal fault zone network: The case of the Cadillac Tectonic Zone, Abitibi greenstone belt, Canada. Canadian Journal of Earth Sciences 44: 745–773. OLIVO G. R., CHANG F. & KYSER T. K. 2006. Formation of the auriferous and barren North Dipper veins in the Sigma Mine, Val d’Or, Canada: Constraints from structural, mineralogical, fluid inclusion, and isotopic data. Economic Geology 101: 607–631. PETTKE T., HEINRICH C. A., CIOCAN A. C. & GÜNTHER D. 2000. Quadrupole mass spectrometry and optical emission spectroscopy: Detection capabilities and representative sampling of short transient signals from laser-ablation. Journal of Analytical Atomic Spectrometry 15: 1149–1155. RAUCHENSTEIN-MARTINEK K., WAGNER T., WÄLLE M., HEINRICH C. A. & ARLT T. 2016. Chemical evolution of metamorphic fluids in the Central Alps, Switzerland: Insight from LA-ICPMS analysis of fluid inclusions. Geofluids 16: 877–908. REZEAU H., MORITZ R. & BEAUDOIN G. 2017. Formation of Archean batholith-hosted gold veins at the Lac Herbin deposit, Val-d’Or district, Canada: Mineralogical and fluid inclusion constraints. Mineralium Deposita 52: 421–442. RIDLEY J. R. 2008. Differentiating crustal fluids in the Eastern Tintina gold province of Alaska and Yukon: Implications for the genesis and distribution of gold ores. In: p. 25. Technical Report, US Geological Survey. ROEDDER E. 1984. Fluid inclusions. Mineralogical Society of America. ROTTIER B., KOUZMANOV K., CASANOVA V., WÄLLE M. & FONTBOTÉ L. 2018. Cyclic dilution of magmatic metalrich hypersaline fluids by magmatic low-salinity fluid: A major process generating the giant epithermal polymetallic deposit of Cerro de Pasco, Peru. Economic Geology 113: 825–856. SAMSON I. M., WILLIAMS-JONES A. E., AULT K. M., GAGNON J. E. & FRYER B. J. 2008. Source of fluids forming distal Zn-Pb-Ag skarns: Evidence from laser ablation-inductively coupled plasma-mass spectrometry analysis of fluid inclusions from El Mochito, Honduras. Geology 36: 947–950. SCHINDELIN J., RUEDEN C. T., HINER M. C. & ELICEIRI K. W. 2015. The ImageJ ecosystem: An open platform for biomedical image analysis. Molecular Reproduction and Development 82: 518–529. SCHINDLER C., HAGEMANN S. G., BANKS D., MERNAGH T. & HARRIS A. C. 2016. Magmatic hydrothermal fluids at the sedimentary rock-hosted, intrusion-related Telfer gold-copper deposit, Paterson orogen, Western Australia: Pressure-temperature-composition constraints on the ore-forming fluids. Economic Geology 111: 1099–1126. SHEPHERD T. J. & CHENERY S. R. 1995. Laser ablation ICP-MS elemental analysis of individual fluid inclusions: An evaluation study. Geochimica et Cosmochimica Acta 59: 3997–4007.

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ur na

lP

re

-p

ro

of

STEELE-MACINNIS M., RIDLEY J., LECUMBERRI-SANCHEZ P., SCHLEGEL T. U. & HEINRICH C. A. 2016. Application of low-temperature microthermometric data for interpreting multicomponent fluid inclusion compositions. Earth-Science Reviews 159: 14–35. ULRICH T., GÜNTHER D. & HEINRICH C. A. 2002. The evolution of a porphyry Cu-Au deposit, based on LA-ICPMS analysis of fluid inclusions: Bajo de la Alumbrera, Argentina. Economic Geology 97: 1889–1920. WILLIAMS-JONES A. E. & HEINRICH C. A. 2005. Vapor transport of metals and the formation of magmatichydrothermal ore deposits. Economic Geology 100: 1287–1312.

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Figure captions Fig. 1. Examples of typical orogenic vein samples from the Archean Abitibi greenstone belt inundated by secondary (a, b) and primary (c, d, e) FIs. Laser ablation ICP-MS analysis of individual FIs is precluded by the abundance of FIs in such samples. (a) Abundant subparallel planes of decrepitated FIs reflecting postentrapment ductile deformation; sample from Black Fox deposit. (b) High abundance of secondary FIs reflecting increased fluid flux in an area of high fracture density (outlined by white dashed line; Bell Creek deposit). (c-e) Densely packed FIs outlining primary growth zones in drusy quartz. The area highlighted in

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Figure 1c is enlarged in Figure 1d; samples from the Ashley (c, d) and Kirkland Lake (e) deposits.

Fig. 2. Petrographic features of FIs observed in sample GF-185 from the Grey Fox deposit. (a) Crustiform vein texture with abundant primary FIs defining growth zones in quartz (qtz) and carbonate (carb) vein fill. (b) Representative vein sample showing typical appearances of FIAs. Primary (p) inclusions are located in growth zones (highlighted area), whereas pseudosecondary (ps) and secondary (sec) FIs are associated with 36

healed fractures either confined within a single grain (ps) or cutting grain boundaries (sec). (c) Primary FIs inundating the outer growth zone of quartz that shows commonly observed radial texture with the long axis parallel to growth direction (cf. Bodnar et al. 1985). (d) Primary aqueous FIs in quartz growth zone. Although abundant, the FIs are very small, usually below 2 µm. The opaque areas are decrepitated FI cavities at or near the sample surface. (c) Trails of secondary aqueous FIs defining healed fracture planes.

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These FIs are significantly less abundant than primary FIs, but are of similar size.

Fig. 3. Petrographic features of FIs observed in sample 144Gap from the Gap Zone deposit. Note that all FIAs observed are of secondary origin. (a) Coarse-grained quartz from vein cutting syenitic host (syn). Note that the vein quartz exhibits areas both inundated and relatively barren of secondary FIPs. Laser ablation analysis targeted well-isolated secondary FIPs in the relatively FI-poor areas to avoid the presence of

37

multiple FIAs in the same ablation volume. (b) Plane of aqueous FIA used for the LA profile a26 in Figure 8a. (c) A modified FIA with heterogeneous aqueous-carbonic FIs (LA profile a29 in Figure 8a). (d) A FIA with homogeneous aqueous-carbonic FIs (profile a36 in Figure 8a). (e) A FIA of single-phase carbonic FIs

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(part of profile a38 in Figure 8a).

Fig. 4. Visual comparison of an unprocessed LA-ICP-MS acquisition signal and the trace of the respective profile (a07 of sample GF-185) in a zoned euhedral quartz grain variably inundated with FI. (Spot size: 50 µm by 50 µm; scanning speed: 3 µm/s.) Note that the fluid-indicative elements are defined by signals which closely follow the variance in the quartz:FI ratio, namely K, Sr, Rb, Ba, Na, Sb, As and Zn in this example. Other elements are either independent of the quartz:FI ratio (Si) or inversely proportional to it (Li), hence

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indicating an affinity to the quartz matrix. Note that whereas both the Ca and B signals do follow the variance in FI abundance, they are not as sensitive indicators of FIs as for example K or Sr because their background concentration in the matrix is relatively high (cf. zones 1a and 1b).

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of ro -p re lP ur na Jo Fig. 5. Laser ablation traces and profiles and time series data for high FI-density quartz growth zones in sample GF-185. (a) Traces of LA profiles a03 to a05 across euhedral quartz having a simple, 3-fold growth zonation. These profiles were used to assess data reproducibility across zones with the same primary FIA. (b) Comparison of the LA trace profiles in quartz and their equivalent TSD diagram converted from the

39

acquired LA-ICP-MS signals. Data representative to specific zones and transitional areas between them were selected by lining up the TSD with the beam trace (a05 not shown), color-coded and plotted on ternary diagrams. (c) Ternary diagrams with the TSD for the different zones in the LA profiles color-coded and additional data for quartz spot analysis (a22 and a24) included for comparison. Data from specific zones (zones 1 and 2, secondary FI and quartz) cluster in contrasting compositional fields whereas transitional areas (i.e., analyses across zone boundaries) define three trends among endmembers. The four main clusters defined in the Na-K-Ca ternary are also seen in the two selected trace-element ternaries provided, Li-Sr-Ba and As-Rb-V. Given that the element ratios of the specific zones are very similar in all three profiles, good

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reproducibility of the data in the different zones is indicated.

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Fig. 6. Laser ablation traces and time series data for high FI-density quartz growth zones in sample GF-185. (a) Traces of LA profiles a07 and a08 across a single euhedral quartz grain having multiple primary growth zones with variable abundances of FIs and hence fluid:matrix ratios with different instrumental settings. (b) Ternary diagrams for major- (Na-K-Ca) and minor- to trace-element (Li-Sr-Ba and As-Rb-V) compositional data from profiles a07 and a08. The data groups were selected and plotted as for Figure 5 with the compositional fields established in Figure 5c overlain here on the same ternary diagrams to show similarities in element ratios. Unlabeled compositional fields represent primary FIA in profiles a03 to a05.

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Note that whereas data from zones 1a and 1b plot along trends between quartz (qtz) and the field for secondary FI (sec), data for primary FIA (zones 2 to 10) overlap with the primary fields from Figures in 5c with the exception of two growth zones; see Section 5.1 for further discussion. Data of specific zones are

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generally similar regardless of the beam settings.

Fig. 7. Laser ablation traces and profiles and time series data for high FI-density quartz growth zones in sample GF-185. (a) Traces of LA profiles a18 and a21 across a single euhedral quartz grain having multiple primary growth zones with variable abundances of FIs and hence fluid:matrix ratios. (b) Comparison of the LA trace profiles in quartz and their equivalent TSD diagram converted from the acquired LA-ICP-MS

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signals. The different data groups are selected and plotted as above. (c) Ternary diagrams for major- (NaK-Ca) and minor- to trace-element (Li-Sr-Ba and As-Rb-V) compositional data from profiles a07 and a08. The data groups were selected and potted as for Figure 5 with the compositional fields established in Figures 5c and 6b overlain here on the same ternary diagrams to show similarities in element ratios (fields representing primary compositions are not labelled). Note that the element ratios and clustering of data are identical to the other profiles.

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of ro -p re lP ur na Jo Fig. 8. Comparison of average element concentrations in FI-rich growth zones (primary FIA; n=2384) and FI-poor quartz spot analyses (qtz; n=151) in sample GF-185. Note that the concentration data are semiquantitative and emphasis should be given to the relative difference between FI zones and quartz matrix rather than to absolute ppm values. Analyses above detection limit plotted. (a) Group 1 elements are

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detected in less than 50% of the analyses in both FI-rich growth zones and the quartz matrix. Group 2 elements are variably detected in the quartz matrix but are above detection limit in more than 80% of the FI-rich analyses where they are either (b) significantly or (c) moderately enriched compared to quartz. Group 3 elements are detected in both phases with a frequency of over 90% and are either (d) enriched in

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primary FIA or (e) show generally the same levels in both phases.

Fig. 9. Laser ablation traces and time series data of low FI-density secondary FIPs in quartz from sample 144Gap. (a) Traces of LA profiles and sampled FI types. (Line width and spot sizes not to scale.) Note that the last parts of profiles a26 and a29, oblique to the FIP trace, were analyzed to acquire proxies for FI-poor quartz as a reference, but as the data were more scattered than for the spot analyses (a27, a28, a35, a37,

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a39) they were discarded. The LA traces a26, a29, a34 and a36 sample a single FIP along strike, whereas trace a38 crosses several different FIAs. (aq: aqueous, aq-carb: aqueous-carbonic, het: heterogeneous) (b) Close-up of LA trace a38 showing analyzed FIA (i.e., carb, het, aq-carb) along the beam path. The concentration changes of Na and K in the fitted time series data diagram reflects the contrasting sections of FI-rich and –poor areas along the profile. The TSD diagram was used to extract FIA-specific data. (c) Ternary Na-K-Ca plots for the different FIA and FI types acquired from various LA profiles along with spot analyses for quartz. Because of the relatively low fluid:matrix ratios of these LA profiles, the data do not cluster and instead define trends along the Na-Ca tie between the Ca-dominated quartz matrix and a

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more Na-rich endmember fluid that likely reflects the actual composition of the FIs. All the compositional trends are essentially similar, except for the aqueous FIA in profile a26 that shows a distinctly K-rich trend.

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(d) Density-contoured ternary diagrams for the aqueous FIA data in profile a26, with overlays for quartz (qtz), secondary FIs (sec) and transitional trend, as defined in Figure 5c (sample GF-185). The data for profile a26 plot in and along these fields for both the major- (Na-K-Ca) and minor- to trace-element (Li-

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Sr-Ba and As-Rb-V) ratios.

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Fig. 10. Comparison of average element concentrations in aqueous secondary FIP (sec FIA (a26); n=688), aqueous-carbonic secondary FIA (sec FIA (excl. a26); n=3929) and FI-poor quartz spot analyses (qtz; n=437) in sample 144Gap. Note that the concentration data are semi-quantitative and emphasis should be given to the relative difference between FI zones and quartz matrix rather than to absolute ppm values. Analyses above detection limit plotted. a) Group 1 elements are detected in less than 50% of the analyses in all types of secondary FIPs and the quartz matrix. b, c) Group 2 elements are variably detected in the quartz matrix but are above detection limit in more than 90% of the aqueous secondary FIP and 70% of the other secondary FIPs. The aqueous secondary FIP is significantly enriched in Na, K, Sr and Pb compared

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are usually above detection limit and are equally enriched in all three phases.

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to the quartz matrix (b) and moderately enriched in various other group 2 elements (c). d) Group 3 elements

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Fig. 11. Comparison of selected FI compositions in sample 144Gap acquired using the bulk LA method from this study versus LA-ICP-MS data for individual FI and evaporate mound analysis (EMA) using the SEM-EDS. (a) Ternary Na-K-Ca plot for aqueous-carbonic FIs showing data acquired from LA profiles in this study versus LA-ICP-MS data for individual FIs (Kontak & Tuba 2018). The two datasets are seen to overlap along the Na-Ca limb of the ternary. (b) Ternary Na-K-Ca plot for secondary aqueous FIAs in different Abitibi orogenic gold deposits (Kontak & Tuba 2018) determined by EMA and single-inclusion LA-ICP-MS analysis versus secondary aqueous FIAs analyzed by the LA bulk method of this study. Highlighted areas show the secondary aqueous field established in GF-185 (sec?) and the 0.4 points/cell

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density boundary of profile a26.

Fig. 12. Reconstruction of the inferred evolution of the fluid composition for major- and trace elements

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during quartz crystal growth in sample GF-185 based on the bulk LA analysis method of this study. The model path, which summarizes all profile measurements, suggests the initial fluid (1) became slightly more K, Ba, Sr, and V enriched (2) before a sudden relative increase in Na, Li and As occurred (3). Fluctuation of these element ratios resulted in another increase in K, Ba, Sr and As (4) and finally a less pronounced shift toward Na, Li, Rb, and V (5) and lastly As (6). The composition of the inferred secondary fluid (S) is

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in contrast with all of these chemical fluctuations.

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Fig. 13. Selected trace element data plotted as ratios in ternary diagrams (Rb-As-Ba, Rb-Ba-Sr, Cu-Sb-Zn)

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which compares data for sample GF-185 acquired with bulk LA to literature data for various hydrothermal fluid types and ore systems obtained using individual FI analysis by LA-ICP-MS analysis. (a) Data for sample GF-185 showing results from primary growth zones only. (b) Data for mineralized and barren vein

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samples from orogenic and sediment-hosted hydrothermal environments. Red field marks the area where 75% of the GF-185 data are contained. Note the GF-185 field is proximal to or overlaps with data for barren

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and mineralized orogenic veins in the Rb-As-Ba and Rb-B-Sr ternaries, whereas for the Cu-Sb-Zn ternary there is good agreement with the orogenic gold data. Results for Carlin and BIF-hosted gold systems plot in different fields. (c) Data for intrusion-related gold (IRG) and porphyry deposits compared to field for

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GF-185 (red outline). Although partially overlapping with outlier analyses for other deposit types, the Grey Fox data generally plot distal to the main fields for both IRG and porphyry deposits. (Data from Ulrich et al. 2002, Williams-Jones & Heinrich 2005, Landtwing et al. 2005, Klemm et al. 2007,

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Ridley 2008, Marsala et al. 2013, Hofstra et al. 2013, Garofalo et al. 2014, Morales et al. 2016, Schindler

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et al. 2016, Large et al. 2016, Rauchenstein-Martinek et al. 2016, Fusswinkel et al. 2017)

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of ro -p re lP ur na Jo Fig. 14. Box plot diagram demonstrating the variability of selected absolute element concentrations calculated by subtraction of different quartz matrix analyses. Calcium, Ti and Fe are highly variable in both samples. Additionally, wide compositional ranges of Li, K and Sr are present in GF-185 (light grey),

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whereas in 144Gap (dark grey) B and Ba change quite significantly, suggesting a compositional contrast among quartz grains not only within a given sample but also between the two quartz veins. (Whiskers indicate minimum and maximum values, bottom and top of boxes are Q1 and Q3, lines and black circles

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depict median and mean values, respectively.)

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Fig. 15. Zonation characteristics of the quartz host in 144Gap and GF-185. (a) Cathodoluminescence image showing a homogeneous quartz matrix in the analyzed area of 144Gap. (b) Cathodoluminescence image of the quartz grains hosting profiles a18 and a21 (GF-185). Outlines of growth zones as delineated by FIs are overlain (yellow dashed line). The fine zonation of quartz as shown by CL does not line up with the boundaries of growth zones indicated by primary FIs. (c) Cathodoluminescence image of the quartz grains hosting profiles a03 to a05 (GF-185). Outlines of growth zones as delineated by FIs are overlain (yellow dashed line). The zonation of quartz as shown by CL matches the boundary of growth zones 2 and 3 as indicated by primary FIs. (Halo around LA channels are edge effect on the CL image.) (d) Time-slice data

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set of the quartz depth profile a23 in GF-185. Slight zonation of Na occurs with concentrations dropping between about 17 to 27 s; other element concentrations are constant. The data set represents ca. 120 µm of

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material. (e) Time-slice data set of the quartz depth profile a24 in GF-185. Slight zonation of Na occurs

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along with a coupled zonation of K and Li. The data set represents ca. 120 µm of material.

Table 1. Summary of instrumental settings for line and spot analyses Table 1. Summary of instrumental settings for line and spot analyses 52

Profi le

Target

Analysi s type

Scan geometr y

Signal collection time1

Beam size

Scanni ng speed

Num ber of laser pulse s / spot

Depth of ablati on2

3 µm/s

167

60 µm

5 µm/s

100

50 µm

2 µm/s

250

70 µm

3 µm/s 13 µm/s

167

60 µm

20

20 µm

3 µm/s

167

60 µm

3 µm/s

167

60 µm

2 µm/s

300

100 µm

3 µm/s

233

80 µm

3 µm/s

167

70 µm

3 µm/s

167

70 µm

250

100 µm

a23

quartz

spot

a24

quartz

spot

a07 a08 a18

line line line line line

77 s 170 s 294 s 72 s 486 s 530 s 17 s 44 s 32 s

line

a27

quartz

spot

53 s

a28

quartz secondary FIP secondary FIP

spot

47 s

quartz secondary FIP

spot

quartz secondary FIP

spot

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ur na

144Gap secondary a26 FIP

a29 a34 a35 a36 a37 a38

along FIP

386 s

line

along FIP

431 s

line

along FIP

329 s

line

line

ro

spot

a05

line

145 s

-p

quartz

a04

line

50x50 µm 50x50 µm 50x50 µm 50x50 µm 26x26 µm 50x50 µm 50x50 µm 100x100 µm 60x60 µm 60x60 µm

re

a22

a03

across zones across zones across zones across zones across zones across zones across zones

lP

a21

growth zone growth zone growth zone growth zone growth zone growth zone growth zone

of

GF185

51 s along FIP

483 s 48 s

across FIP

748 s

60x60 µm 60x60 µm 60x60 µm 70x50 µm 50x50 µm 60x60 µm 50x50 µm 50x50 µm 50x50 µm

2 µm/s

53

a39

quartz

spot

48 s

50x50 µm

1

Jo

ur na

lP

re

-p

ro

of

Collection of gas blank not included 2 Measured post experiment. All spot analyses ablated through the 120µm thick quartz wafer.

54