Treatment of the real boiler cleaning wastewater in an anaerobic fluidized bed microbial fuel cell: Organic matter degradation, bioelectrochemistry, and kinetics
Bibliographic record
Abstract
A single chambered air cathode anaerobic fluidized bed microbial fuel cell (AFB‐MFC) was simultaneously used to dispose of the real boiler cleaning wastewater (BCW) containing a high concentration of citric acid and to generate renewable energy. At the temperature of 40 °C and flow rate of 5.22 mL/s, the removal efficiency and power density were improved in AFB‐MFC with the abiotic cathode of the Pt/C modified carbon cloth. With the real boiler cleaning wastewater fed as substrate, the maximal removal efficiency of chemical oxygen demand (COD) in AFB‐MFC was up to 90 %, which was higher than the corresponding value of 84 % obtained in the anaerobic biological fluidized bed reactor (ABFBR). The maximum voltage and the maximum power density were 424.6 mV and 18.68 mW/m2, respectively, when the external resistance was 5000 Ω. Furthermore, the Haldane inhibition model was well fitted with experiment data (R2 = 0.97–0.98) in AFB‐MFC/ABFBR. The inhibition of citric acid degradation in ABFBR was stronger than that of AFB‐MFC. The bioelectrochemical system of AFB‐MFC not only improved the charge transfer and but also accelerated the reaction rate of citric acid. The reduction of the ferric ion and oxidation of ferrous ion in AFB‐MFC played important roles in the degradation reaction of critic acid.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".