Unraveling Polymorphic Pyrrhotite Electrochemical Oxidation by Underlying Electronic Structures
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Bibliographic record
Abstract
Metal sulfide oxidation is a common, yet poorly understood, phenomenon that significantly affects surface properties. In this paper, we studied the electrochemical oxidation of polymorphic pyrrhotites (Fe1–xS) to gain insights into the relationship between their electrochemical oxidation rate and electronic structures. Surface composition of oxidized pyrrhotites, as shown by time-of-flight secondary ion mass spectrometry (ToF-SIMS) and X-ray photoelectron spectroscopy (XPS), suggested that one key step for pyrrhotite oxidation is the outward diffusion of metal cations to form polysulfide and oxides. This diffusion process involves the rupture of Fe–S bonds and, hence, depends on the Fe–S bond strength. According to the ToF-SIMS, the Fe–S bond strength in the defective layer (>100 nm), the layer right underneath the polysulfide layer (∼20 nm), was modified by the incorporation of oxygen atoms, which mainly existed in the form of OH– and H2O. It was found that oxygen anions are much more abundant in the defective layer of monoclinic pyrrhotite (Fe7S8) than that of hexagonal pyrrhotite (Fe9S10), resulting in a much weaker Fe–S bond with the former than the latter. The oxygen abundance difference can be explained by their electronic structures. Density functional theory (DFT) calculation showed that monoclinic pyrrhotite (Fe7S8) get a higher Fe 3d and S 3p band center than hexagonal pyrrhotite (Fe9S10). Therefore, monoclinic pyrrhotite could incorporate oxygen atoms easier than hexagonal pyrrhotite. This presented a clear relation between polymorphic pyrrhotite electronic structures and their electrochemical oxidation rate and also fundamentally explained why the sulfides with a slight bulk metal–sulfur bond strength difference could demonstrate a significant oxidation rate difference.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it