Dimple Grinding Coupled with Optical Microscopy for Porosity Analysis of Metallic Coatings
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Bibliographic record
Abstract
Dimple grinding is one of the steps used in a common method of preparing samples for transmission electron microscopy (TEM); the TEM sample preparation process also involves ion beam sputtering after the dimpling stage. During dimpling, a spherical depression is machined into the sample, leaving a thicker rim to support and facilitate sample handling. In this paper, an alternative application for dimple grinding is developed; dimple grinding combined with optical microscopy is utilized to quantify internal porosity present within coatings. This technique essentially permits three dimensional porosity quantification across the coating thickness using a simple polishing method which provides analysis of areas larger than those observed during standard cross sectional microscopy. The application of this technique to nine electroless nickel-phosphorus (Ni-P) coatings deposited on Mg substrates is demonstrated. An analysis linking medium P content in the Ni-P coatings and high coating thickness to lower porosity is also performed. The lowest porosity was observed for medium P content coatings (5.2 wt% P), while the largest porosity occurred for the high P content coatings (10.0 wt% P). Porosity levels decreased continuously with increasing coating thickness (from 28 µm to 57 µm).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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