Formation of Dimpled Tantalum Surfaces from Electropolishing
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Bibliographic record
Abstract
Electropolishing of tantalum in concentrated acids has recently been reported to result in highly ordered arrays of nanoscale dimples. In this paper we study in more detail the electrochemical conditions affecting the formation of regularly dimpled surfaces on tantalum. Solution aging and anodization potential were found to play important roles. The chronoamperometric curves at different anodization potentials give some insight into the changing balance of processes leading to dimpling during electropolishing. We have found that dimpled tantalum can be reproducibly prepared within the anodization potential range of . Higher voltages lead to anisotropic etching of the Ta grains and the resulting surface nanostructure is no longer ordered. Overall, the dimple-formation process can be said to be robust and tunable, with great promise for nanotemplating applications.
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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 | 0.001 | 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 | 0.000 |
| 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 it