Temperature Dependence and Gas-Sensing Response of Conduction for Mixed Conducting SrFe[sub y]Co[sub z]O[sub x] Thin Films
Bibliographic record
Abstract
A series of thin films on sapphire substrates was prepared by laser deposition and the conductance responses to both temperature and gas composition in mixtures were examined. All films exhibited p-type semiconductor behavior with film conductivities at 500°C between 20 and 200 S/cm for films exposed to 100% atm and 0.4-25 S/cm for films exposed to 0.2% At 500°C, thin films of compositions were found to be the most conductive for oxygen partial pressures between atm. and films were found to be the least conductive under these conditions. and films were found to exhibit regions where conductivity exhibited temperature independence between for oxygen concentrations between 0.2 and 100% The temperature independence was interpreted as the result of a balancing of two opposing thermal effects: thermal activation of charge carriers and thermal-induced oxygen stoichiometry changes. For some films, enhanced oxygen sensitivity was observed over narrow regions, and is attributed to cubic perovskite to brownmillerite phase transitions. CO and gases could be detected in background air for conditions where there is negligible temperature dependence of conduction. © 2002 The Electrochemical Society. All rights reserved.
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".