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Record W3101351842 · doi:10.5194/epsc2020-824

Equilibration time of Fe & Zn concentrations and isotopes in metal-silicate partitioning experiments

2020· article· en· W3101351842 on OpenAlexaboutno aff
A. X. Seegers, Kirsten van Zuilen, Riemer Stelwagen, W. van Westrenen, Pieter Z. Vroon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsSilicateFractionationIsotopeMantle (geology)MetalChemistryIsotope fractionationStable isotope ratioEarth (classical element)Analytical Chemistry (journal)MineralogyGeologyGeochemistryEnvironmental chemistryPhysicsNuclear physics

Abstract

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IntroductionPresent geochemical models of planetary core formation commonly focus on either element abundances or isotope fractionation between mantle and core. Data gathered from these two techniques can be mutually inconsistent, leading to different conclusions concerning core formation processes. An example of this is the Si content of the Earth’s core. Element partitioning data and seismological observations indicate that the Earth’s core only contains minor amounts of Si [1], whereas isotopic data suggests significant amounts of Si may be present [9]. To address this data discrepancy problem, this study combines element partitioning behaviour and isotope fractionation of Fe and Zn through metal-silicate partitioning experiments. Metal-silicate partitioning experiments at high pressure and temperature allow for the distribution of elements and their isotopes between planetary cores (metal) and mantles (silicate) to be studied under controlled conditions [e.g. 6,7, 10]. As during planetary core formation it is assumed that some form of equilibrium is reached over millions of years, the experiments should reflect this as well. Therefore, it is essential to determine the time that is required for every experiment to achieve both elemental and isotopic abundance equilibrium. ApproachMetal-silicate partitioning experiments are performed under high pressure and temperature conditions using an end-loaded piston-cylinder press. To solely focus on the equilibration times, experiments of the same starting compositions were subjected to peak conditions of 1GPa and 1823K for a time ranging from 3 minutes up to 12 hours. The experiments consisted of a synthetic analogue of the lunar Apollo 15 Green Glass as silicate phase [3], along with a metal phase of Fe-metal doped with Zn.Element concentrations of metal and silicate phases of every experiment were measured with an electron microprobe (EMPA) for major elements and laser ablation ICP-MS (LA-ICP-MS) for trace elements. To analyse Fe and Zn isotopic fractionation, both Zn and Fe were isolated from the metal- and silicate phases through ion-exchange chromatography. The AG-X8 resin was used for the separation of Fe, and the AG-MP-1 resin for Zn [5]. The isotopes of Fe and Zn were subsequently measured using a multi-collector ICP-MS (MC-ICP-MS) with a double spike technique. The precision of the isotope analyses is determined by measuring isotopic reference materials. The standards IRMM-014 (Fe) and ETH-ZN indicate a precision of ± 0.03‰ (2SD) for Fe isotopes and ± 0.05‰ (2SD) for Zn isotopes respectively. Additionally, rock standards such as BHVO-2, BCR-2, AGV-2 and BIR-1 that had been processed exactly like the experiments were measured during the analyses. ResultsExperimental run products typically show a good separation of a metallic phase and quenched silicate melt. Disequilibrium within experiments can cause heterogeneous spots where groups of elements are clustered. These heterogeneous spots can be seen in experiments of run times of e.g. 3 and 5 minutes (Fig. 1), whereas they are absent in experiments with longer run times (Fig. 2). Results shown in Fig. 3 confirm these observations as the measured elements from short (30 minutes). Therefore, concentration analyses indicate that elemental equilibrium is reached within 30 minutes.Isotope equilibration times are significantly longer than concentration equilibration times (Fig. 4 and 5) [8]. Within the first two hours of an experiment, the fractionation factors Δ56Femetal-silicate and Δ66Znmetal-silicate are positive and variable. Between 2-4 hours, the fractionation factors become negative and start to stabilise. After approximately 4 hours, isotopic equilibrium is reached for both Fe and Zn with Δ56Femetal-silicate = -0.04‰ ± 0.07 and Δ66Znmetal-silicate = -0.11‰ ± 0.06, which corresponds with literature data [2,4]. Discussion and outlookAlthough the data described here cannot be directly applied to planetary core formation models yet, it is essential for creating models of core formation based on a combination of elemental abundances and stable isotope fractionation. This initial data set suggests that there is a relatively uniform Fe and Zn distribution between core (metal) and mantle (silicate) during core formation at high temperature. However, quantification of the effects of pressure, temperature and composition will be needed to further test this hypothesis. AcknowledgementsWe would like to thank the Netherlands Space Office for financial support through its User Support Programme. References[1] Badro, J., Côté, AS., and Brodholt, JP.: A seismologically consistent compositional model of Earth’s core, Proceedings of the National Academy of Sciences, 11, pp. 7542-7545, 2014.[2] Bridgestock LJ., Williams H., et al.: Unlocking the zinc isotope systematics of iron meteorites, Earth and Planetary Science Letters, 400, pp. 153-164, 2014.[3] Delano, JW.: Pristine lunar glasses : criteria, data and implications, Journal of Geophysical Research, 91, pp. 201-213, 1986.[4] Hin RC., Schmidt MW., Bourdon B.: Experimental evidence for the absence of iron isotope fractionation between metal and silicate liquids at 1GPa and 1250-1300°C and its cosmochemical consequences, Geochimica et Cosmochimica Acta, 93, pp. 164-181, 2012.[5] Moeller K., Schoenberg R., et al.: Calibration of the New Certified Reference Materials ERM-AE633 and ERM-AE647 for Copper and IRMM-3702 for Zinc Isotope Amount Ratio Determinations, Geostandards and Geoanalytical Research, 36, pp. 177-199, 2012.[6] Righter, K .: Metal-silicate partitioning of siderophile elements and core formation in the early Earth, Annual Reviews of Earth and Planetary Sciences, 31, pp 135-174, 2002.[7] Rose-Weston, L., Brenan, JM., Fei, Y., et al .: Effect of pressure, temperature and oxygen fugacity on metal-silicate partitioning of Te, Se and S: Implications for Earth differentiation, Geochimica et Cosmochimica Acta, 73, pp.4598-4615, 2009.[8] Roskosz, M., Luais, B., Watson, HC., et al .: Experimental quantification of the fractionation of Fe isotopes during metal segregation from a silicate melt, Earth and Planetary Science Letters, 248, pp. 851-867, 2006.[9] Shahar, A., Ziegler, K., Young, ED., et al .: Experimentally determined Si isotope fractionation between silicate and Fe metal and implications for Earth’s core formation, Earth and Planetary Science Letters, 288, pp. 228-234, 2009.[10] Siebert, J., Corgne, A., Ryerson, FJ .: Systematics of metal-silicate partitioning for many siderophile elements applied to Earth’s core formation, Geochimica et Cosmochimica Acta, 75, pp. 1451-1489, 2011.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.269
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2020
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