Preparation of new ferroelectric Li<sub>0.95</sub>Ta<sub>0.57</sub>Nb<sub>0.38</sub>Cu<sub>0.15</sub>O<sub>3</sub> materials as photocatalysts in microbial fuel cells
Bibliographic record
Abstract
Abstract A microbial fuel cell (MFC) is a device for both the generation of bioelectricity and the treatment of wastewater. However, its performance is affected by several parameters, and more particularly the materials used as the active phase at the cathode. In order to develop new, more efficient cathodes, two new non‐stoichiometric ferroelectric cathode materials are studied in this work. These electrodes have been synthesized according to two heat treatment modes (slow cooling and rapid cooling) from non‐stoichiometric ferroelectric materials with the formula Li0.95Ta0.57Nb0.38Cu0.15O3. The synthesized phases were characterized by X‐ray diffraction (XRD), transmission electronic microscopy (TEM), particle size distribution (PSD), and differential scanning calorimetry (DSC). The main characteristics of these phases are the Curie temperatures, 1217 and 1197 °C, and the specific surfaces of 0.572 and 0.801 m2/g for the slow and rapid cooling phases, respectively. These materials were subsequently tested as photocathodes in a single chamber MFC in terms of the bioenergy production and wastewater treatment, by measuring the output power density and the rate of removal of COD in the presence of a light source. For the samples prepared by slow and rapid cooling, the values of maximum power density were 20.10 and 205.35 mW/m3, respectively. The COD removal rates were 74 and 80 %, respectively. Accordingly, the phase prepared by rapid cooling was shown to be more efficient in terms of power generation and wastewater treatment with a significant improvement in photocatalytic activity.
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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".