Impact of BiBO<sub>3</sub>, NaF and BiF<sub>3</sub> Substitution on the Thermoelectric Properties of Bi<sub>2</sub>Ca<sub>2</sub>Co<sub>2</sub>O<sub>y</sub> Ceramics
Bibliographic record
Abstract
In this work, we studied the impact of (i) partial substitution of bismuth oxide (Bi2O3) by bismuth borate (BiBO3), (ii) dual-substitution of Bi2O3 by BiBO3 and sodium fluoride (NaF), and (iii) dual-substitution of Bi2O3 by BiBO3 and bismuth fluoride (BiF3) on the thermoelectric characteristics of Bi2Ca2Co2Oy layered cobaltite.Thermoelectric cobaltites were synthesized using the sol-gel method.The phase composition of prepared materials was examined by the X-ray diffraction (XRD) analysis.The values of power factor (PF) and figure of merit (ZT) were calculated through measurements of electrical resistivity (ρ), Seebeck coefficient (S), and thermal conductivity (k).The XRD analysis confirms that all the samples consist of a nearly pure Bi2Ca2Co2Oy phase.When compared to the reference (pristine) sample, the dual NaF/BiBO3 substitution leads to a sharp decrease in ρ due to the partial substitution of NaF for Bi2O3, which increases the concentration of charge carriers (holes).At the same time, partial substitution of BiF3 for Bi2O3 led to a decrease in hole concentration and, hence, an increase in ρ.Seebeck coefficients were positive for all the samples, indicating p-type conductivity.The maximum PF and ZT values achieved in the NaF/BiBO3 co-substituted composition are 18% and 13% higher, respectively, than the reference Bi2Ca2Co2Oy.
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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".