Direct Observation of PFIB-Induced Clustering in Precipitation-Strengthened Al Alloys by Atom Probe Tomography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The effect of sample preparation on a pre-aged Al–Mg–Si–Cu alloy has been evaluated using atom probe tomography. Three methods of preparation were investigated: electropolishing (control), Ga+ focused ion beam (FIB) milling, and Xe+ plasma FIB (PFIB) milling. Ga+-based FIB preparation was shown to introduce significant amount of Ga contamination throughout the reconstructed sample (≈1.3 at%), while no Xe contamination was detected in the PFIB-prepared sample. Nevertheless, a significantly higher cluster density was observed in the Xe+ PFIB-prepared sample (≈25.0 × 1023 m−3) as compared to the traditionally produced electropolished sample (≈3.2 × 1023 m−3) and the Ga+ FIB sample (≈5.6 × 1023 m−3). Hence, the absence of the ion milling species does not necessarily mean an absence of specimen preparation defects. Specifically, the FIB and PFIB-prepared samples had more Si-rich clusters as compared to electropolished samples, which is indicative of vacancy stabilization via solute clustering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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