Constraints on the Genesis of Cobalt Deposits: Part I. Theoretical Considerations
Bibliographic record
Abstract
Abstract Cobalt is in high demand because of the key role that cobalt-lithium-ion batteries are playing in addressing the issue of global warming, particularly in facilitating the transition from the internal combustion engine to electrically driven vehicles. Here, we review the properties of cobalt and the history of its discovery, briefly describe its mineralogy, and explore the processes that concentrate it to potentially exploitable levels. Economic cobalt deposits owe their origin to the compatible nature of Co2+, its concentration in the mantle in olivine, and its release, after high degrees of partial melting, to komatiitic and (to a lesser extent) basaltic magmas. Primary magmatic deposits, in which Co is subordinate to Ni, develop through the separation of immiscible sulfide liquids from mafic and ultramafic magmas and the very strong partitioning of these metals into the sulfide liquid. We evaluate the factors that concentrate cobalt to economic levels by these processes. Cobalt is also concentrated by aqueous fluids, either at ambient temperature in laterites developed over ultramafic rocks or hydrothermally in sediment-hosted copper deposits and in cobalt-rich vein deposits, where it crystallizes mainly as sulfide and arsenic-bearing minerals, respectively. Using the available thermodynamic data for aqueous Co species, we evaluate cobalt speciation as a function of temperature and show that, whereas it is transported at ambient temperature in most environments as the simple ion (Co2+), it is most mobile in hydrothermal systems as chloride species. Based on thermodynamic data compiled from a variety of sources, we evaluate stability relationships among some of the principal cobalt sulfide and oxide minerals as a function of temperature, pH, fO2, and αH2S and, in conjunction with the aqueous speciation data, determine their solubility. This information is used, in turn, to predict the physicochemical conditions most favorable for cobalt transport and ore formation by hydrothermal fluids. As thermodynamic data are not available for the cobalt arsenide and sulfarsenide minerals that form the vein-type ore deposits, we use chemographic analysis to qualitatively evaluate their stability relationships and predict the physicochemical controls of ore formation. The data and interpretations of processes presented in this paper provide the theoretical basis for a companion paper in this issue in which we develop plausible models for the genesis of the principal cobalt deposit types.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".