Bibliographic record
Abstract
For gas turbines and advanced nuclear power reactors, ceramic materials are used to provide thermal insulation to metallic components. Reducing the thermal conductivity of these ceramic materials allows further decrease in either metal surface temperature or thickness of the insulating materials. In this paper, our past research on the effects of oxide dopants is summarized with a focus on thermal properties. Metal oxides of different valence, ionic radius, and mass were incorporated into yttria partially stabilized zirconia (7 wt% Y2O3-ZrO2) using mechanical alloying process. The powder blends were consolidated using sintering and plasma spraying. The oxides investigated included trivalent Yb2O3, Sc2O3 and Cr2O3, tetravalent CeO2 and TiO2, and pentavalent Nb2O5 and Ta2O5. While all oxides provided improvement to thermal conductivity reduction, the most significant effect on reducing the thermal conductivity of 7YSZ was found by using trivalent oxides. Furthermore, the effect of dopant was also heavily influenced by the molar percentage of dopants.
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".