Effects of Li doping on microstructural and electrical properties of ZnO–MgO–Al<sub>2</sub>O<sub>3</sub> linear resistance ceramics
Post-publication record
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Bibliographic record
Abstract
In this article, The ZnO-MgO-Al 2 O 3 linear resistance ceramics doped with Li 2 O have been prepared by the conventional ceramic method.The microstructure and the crystal characteristics were investigated by field emission scanning electron microscopy (FESEM) equipped with energy dispersive spectrometer (EDS) and X-ray diffraction (XRD) respectively.With the increasing of Li 2 O content, the grain growth of ZnO-based linear resistance ceramics was enhanced and the resistivity was also influenced significantly.The experimental result indicates that the doping of Li 2 O can reduces the nonlinear coefficient and improves the resistance temperature coefficient of the ZnO-based linear resistance ceramics obviously.The samples at the Li 2 O content of 8 mol% exhibit excellent electrical properties with the resistivity of 589.34 Ω cm and the resistance temperature coefficient of 0.8 * 10 -4 / ºC.Moreover, the nonlinear coefficient of the ZnO-based linear resistance ceramics decreases from 1.28 to 1.14 as the Li 2 O concentration ranging from 0 to 8.0 mol% and the relative density increases from 91.94% to 97.93%.
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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".