Environmental Resistance of High Entropy Alloys: Impact of Downstream Hydrogen Combustion on Oxidation Resistance
Bibliographic record
Abstract
Abstract This study explores the environmental resistance of AlCoCrFeNi-based high entropy alloys (HEAs) placed downstream from a combustor using hydrogen fuel. High entropy alloys are interesting candidates for gas turbines due to their severely mismatched lattice structure leading to sluggish diffusion, which is theorized to provide superior environmental resistance. Three HEAs with different doping elements, namely Al6Co21Cr21Fe21Ni30, Al4Co21Cr21Fe21Ni30Ti2, and Al4Co20Cr20Fe20Mo1Ni30Ti2 (at.%), were compared against Hastelloy X in terms of oxidation and corrosion. Samples were impinged by the flame within a demonstrator hydrogen combustor cell, which was run for a total of 10 hours. The combustor cell burned a 100% hydrogen flame using a combination of premixed/micromixed fuel injection to provide a stable flame with a calculated adiabatic temperature of 1800 K. In-situ imaging and temperature measurements continuously monitored the samples and combustion conditions within the chamber. Ex-situ scanning electron microscopy (SEM) and X-ray diffraction (XRD) analyses revealed the depth of oxidation, oxide species, and damage caused by the high-temperature flame. The results highlight the consequences of burning pure hydrogen on the metals downstream of a hydrogen combustor. Aluminum stimulated the formation of a vapour-resistant Al2O3 scale, leading to sluggish oxidation kinetics. Ti increased the oxidation rate by favorizing the formation of Fe-rich oxides, and Mo reduced the oxide thickness but induced significant formation of subscale pores.
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".