Unraveling the secrets of the Earth through nanogeology: A correlative microscopy approach
Bibliographic record
Abstract
Correlative analytical approaches involving high-spatial resolution microscopy techniques allow for the compositional measurements and spatial imaging of materials at the near-atomic scale. By combining electron backscatter diffraction (EBSD) mapping, electron channeling contrast imaging (ECCI), scanning transmission electron microscopy (STEM) and atom probe tomography (APT) on various geological materials such as minerals and glasses, we have successfully documented element mobility regulated by structural defects. Although these techniques were initially developed in the materials sciences, they are now being applied to a broad range of applications within many subdisciplines of geosciences including geochemistry, geochronology, and economic geology. In one set of experiments, we applied a correlative approach on naturally deformed pyrite from an orogenic gold mine in northern Canada to assess the impact of crystal-plastic deformation on the remobilization of trace elements. This study has led us to propose a new paragenetic model for metallic ore deposits in which deformation creates nanostructures that act as traps for base- and precious-metals. By applying our approach on pyrite that is rich with fluid inclusions, we have also documented two processes that led to proposing a new fluid inclusion-induced hardening model, which is in contrast to the more commonly reported weakening effect of fluids on minerals. To broaden the applications of our approach, we have applied the same suite of analytical techniques to a synthetic andesitic glass to assess whether nanoscale chemical heterogeneities can act as nucleation sites for gas bubbles. The combined results demonstrate the existence of nanoscale chemical heterogeneities within the melt and at the bubble-melt interface supporting the hypothesis that homogeneous nucleation could in fact be a variety of heterogeneous nucleation. The interactions between trace elements and structural defects plays a vital role in determining the mechanical properties of minerals, particularly in fluid-rich environments. These sub-nanometer scale exchanges consequently control meso- to tectonic-scale geological processes. Our research work not only demonstrates the latest advancements in analytical microscopy resolving long-standing geological problems but also brings us closer to bridging the gap between the fields of materials sciences and geosciences.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".