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
The iron-chromium-aluminum alloy (FeCrAl) is an exceptional support for highly exothermic and endothermic reactions that operate above 700 °C in chemically aggressive environments, where low heat and mass transfer rates limit reaction yield. FeCrAl two- and three-dimensional structured networks—monoliths, foams, and fibers—maximize mass transfer rates, while their remarkable thermal conductivity minimizes hot spots and thermal gradients. Another advantage of the open FeCrAl structure is the low pressure drop due to the high void fraction and regularity of the internal path. The surface Al2O3 layer, formed after an initial thermal oxidation, supports a wide range of metal and metal oxide active phases. The aluminum oxide that adheres to the metal surface protects it from corrosive atmospheres and carbon (carburization), thus allowing FeCrAl to operate at a higher temperature. The top applications are industrial burners, in which compact knitted metal fibers distribute heat over large surface areas, and automotive tail gas converters. Future applications include producing H2 and syngas from remote natural gas in modular units. This Review summarizes the specific preparation techniques, details process operating conditions and catalyst performance of several classes of reactions, and highlights positive and challenging aspects of FeCrAl.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.072 |
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