Influence of Alloying Elements on the Electrochemical Behavior of Cantor High Entropy Alloys in Chloride Solutions
Bibliographic record
Abstract
Abstract FeCoCrNi-based high entropy alloys (HEAs) are often used as prototype model alloys and have been developed broadly through modifying or replacing constituents with other elements to serve in extremely harsh environments such as in nuclear and marine engineering. Most previous studies were focused on the microstructure, mechanical properties, and oxidation behavior of FeCoCrNi-based HEAs. To date, very little work has been published on the corrosion behavior of HEAs in aqueous environments. In this study, the corrosion behavior of Cantor HEAs, including Fe20Co20Cr20Ni20Cu20 (H4Cu20), Fe20Co20Cr20Ni-20Cu15Al5 (H4Cu15Al5), and Fe20Co20Cr20Ni20Cu10Al10 (H4Cu10Al10), also known as H4C alloys, are investigated in aerated 3.5 wt% NaCl solutions at room temperature via electrochemical measurements. A common stainless steel (UNS S30403), and the original Cantor HEA (Fe20Co20Cr20Ni20Mn20, H4Mn20) are also evaluated as comparisons. Results confirmed that the addition of Al into the FeCoCrNi-based HEA improves the general corrosion resistance of Cantor HEAs. Among all five alloys, H4Cu10Al10 has the best general corrosion resistance with the slowest cathodic kinetics. The main types of corrosion on these HEAs were interdendritic and pitting corrosion after anodic polarization. Polarization experiments and post-characterization revealed that although the H4C alloys exhibit low pitting potential and low resistance to pitting initiation, the formed localized corrosion was interdendritic corrosion rather than big pits. Overall, results indicate that there is no significant advantage of using Cantor HEAs over common stainless steel in terms of corrosion consideration in aqueous chloride environments.
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 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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".