From phase decomposition to evaporation: A multi-modal evaluation of thermally degraded model lightweight high-entropy alloy
Bibliographic record
Abstract
Lightweight high-entropy alloys (LHEAs) have the potential to replace conventional lightweight materials due to their superior mechanical properties and thermal stability. However, the thermal degradation pattern of LHEAs from phase decomposition to evaporation is not clear. We develop a new Al-based dual phase (FCC + HCP) LHEA—AlTi0.45CuZn, and further investigate its thermal degradation behavior for potential high-temperature structural applications. Using multimodal advanced characterization techniques such as differential scanning calorimetry/thermogravimetric analysis, scanning/transmission electron microscopy, and synchrotron X-ray diffraction/pair distribution function (XRD/PDF), a sequence of thermal degradation events beyond the thermal phase stability limit—between 250 and 360 °C—is observed. These include phase decomposition at ~360 °C, Zn evaporation at ~750 °C, and LHEA melting at 880 °C which results in ~25% cumulative weight loss. The formation of Al-Ti phase off the AlTi0.45CuZn matrix is due to the largest negative mixing enthalpy for Al-Ti than other binary pairs. Similarly, Zn evaporation from AlTi0.45CuZn LHEA is due to its faster evaporation rate than other constituent elements. The high-resolution synchrotron XRD and PDF results support the aforementioned observations; in addition, they reveal local atomic arrangements, local strain, and sluggish grain growth in the LHEA. Among other LHEAs of close density range (5.55≤ρ≤5.85 g/cc), the investigated LHEA exhibits outstanding nano-indentation hardness values due to the coupled grain size effect and HCP phase strengthening of the FCC matrix. As the search for LHEAs for lightweight applications grows, this study shows the potential use of AlTi0.45CuZn LHEA for structural applications even at elevated temperatures.
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".