Microscopy and microanalysis of complex nanosized strengthening precipitates in new generation commercial Al–Cu–Li alloys
Bibliographic record
Abstract
Precipitates (ppts) in new generation aluminum-lithium alloys (AA2099 and AA2199) were characterised using scanning and transmission electron microscopy and atom probe tomography. Results obtained on the following ppts are reported: Guinier-Preston zones, T1 (Al2 CuLi), β' (Al3 Zr) and δ' (Al3 Li). The focus was placed on their composition and the presence of minor elements. X-ray energy-dispersive spectrometry in the electron microscopes and mass spectrometry in the atom probe microscope showed that T1 ppts were enriched in zinc (Zn) and magnesium up to about 1.9 and 3.5 at.%, respectively. A concentration of 2.5 at.% Zn in the δ' ppts was also measured. Unlike Li and copper, Zn in the T1 ppts could not be detected using electron energy-loss spectroscopy in the transmission electron microscope because of its too low concentration and the small sizes of these ppts. Indeed, Monte Carlo simulations of EEL spectra for the Zn L2,3 edge showed that the signal-to-noise ratio was not high enough and that the detection limit was at least 2.5 at.%, depending on the probe current. Also, the simulation of X-ray spectra confirmed that the detection limit was exceeded for the Zn Kα X-ray line because the signal-to-noise ratio was high enough in that case, which is in agreement with our observations.
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.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".