Oxidation behaviour of PM-C26M FeCrAl alloy in low-temperature steam 400 – 900 °C
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
Iron-chromium-aluminum (FeCrAl) alloys are the primary candidate for serving as an accident tolerant fuel cladding, replacing zirconium (Zr)-based cladding. This preference stems from the high corrosion resistance under both operating and accident conditions in light water reactors (LWRs). To successfully implement this alloy as a cladding material in LWRs, the corrosion behavior under various conditions needs to be understood. While recent studies have focused on high-temperature steam conditions (>1000 °C) and operating conditions (∼300 °C), there is a notable gap in research exploring the steam temperature range above 300 °C and below 1000 °C. This study specifically investigated the formation of oxide layers on powder metallurgy (PM)-C26M FeCrAl in steam at temperatures ranging from 400 °C to 900 °C. It was found that within the temperature range of 400 °C to 600 °C, a duplex oxide layer emerges, with Fe-oxide in the outer layer and Cr/Al-oxide in the inner layer. At 500 °C, the outer layer consists of α-Fe 2 O 3 crystals with Cr/Al-oxides in the inner layer. The initial occurrence of a single oxide layer mostly comprised of alumina (Al 2 O 3 ) is observed at 700 °C, remaining consistent from the 700 °C to 900 °C range. The Al 2 O 3 layer is nanocrystalline, but not as thick or as uniform in composition as that observed in high-temperature steam environments. Notably, the Al 2 O 3 layer has Fe, Cr, and molybdenum (Mo) precipitates dispersed throughout. Increasing the temperature decreases the presence of these precipitates in the oxide layer, and an increase in either temperature or time results in an increase in the thickness of Al 2 O 3 layer.
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 | 0.000 |
| 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) | 0.002 | 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