Analyzing the Influence of Alloying Elements and Impurities on the Localized Reactivity of Titanium Grade-7 by Scanning Electrochemical Microscopy
Bibliographic record
Abstract
Scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDX) was applied to investigate the grain boundaries on ASTM grade-7 titanium (Ti-7) with a freshly polished surface, and the results showed that the alloying element, Pd, and the impurity, Fe, cosegregated to grain boundaries. Scanning electrochemical microscopy (SECM) was used to study the variations in reactivity on Ti-7 exposed to an aerated neutral solution of 0.1 M NaCl. Locations that possessed an enhanced reactivity compared to the oxide-covered (TiO(2)) surface of the grains on SECM images were proposed to be the boundaries. These areas were further activated by the application of a cathodic bias, and interconnection of the active locations allowed the construction of "grain boundary maps". Variations in surface reactivity were quantitatively analyzed by fitting probe approach curves (PACs) to curves simulated with a model based on finite element analyses using the platform of COMSOL multiphysics software. The difference in reactivity between active grain boundaries and oxide-covered grains was up to a factor of 100 on freshly polished surfaces. This difference decreased to a factor of 10-15 after longer-term exposure of the Ti-7 to the aerated solution, indicating partial passivation of the Pd/Fe-stabilized beta-phase in the grain boundaries. PAC analyses of oxide-covered grains showed that the reactivity increased logarithmically as the bias potential to the Ti-7 was decreased, consistent with reduction of the insulating TiO(2) layer to a more conductive TiOOH layer.
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How this classification was reachedexpand
Full frame distilled prediction
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".