Electrical Resistivity Measurements: A Sensitive Tool for Studying Aluminium Alloys
Bibliographic record
Abstract
This paper examines the challenges which are encountered when using electrical resistivity measurements for characterization of microstructures in aluminum alloys. Experimental examples are provided of electrical resistivity studies conducted on two aluminum alloys, a heattreatable alloy (AA6111) and a non-heat-treatable alloy (AA5754), which demonstrate how the technique can be used to characterize changes in the microstructure. Results on AA6111 show that the dependence of the measurement on solute atoms and fine scale precipitates makes deconvolution of the resistivity signal non-trivial and therefore, utilization of supplementary technique(s) in conjunction with electrical resistivity measurements is essential. In the next example, room temperature electrical resistivity measurements as a function of cold work for AA5754 illustrate a larger resistivity contribution from dislocations in this alloy as compared to that reported for pure aluminum. The interaction of solutes and dislocations is cited as the possible source for the increased dislocation contribution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".