Unveiling graphite coated with nano-nickel ferrite for two-stage gaseous biofuel generation from potato processing wastewater
Bibliographic record
Abstract
Anaerobic digestion (AD) process couples the privilege of biowaste reduction and bioenergy production. Hereby, enhancing AD of potato processing wastewater (PPW) in one-stage vs. two-stage AD process using graphite rods, 50, 100 and 200 mg g −1 volatile solids (VS) nano-nickel ferrite and graphite rod coated with nano-nickel ferrite was explored in batch assay at mesophilic conditions (37 °C). Nano-nickel ferrite was prepared and systematically scrutinized using FTIR , XRD , EDX spectral analysis and scanning electron microscopy. Graphite rods coated with nano-nickel ferrite achieved the highest hydrogen (226 mL H 2 g −1 COD) and methane (320 mL CH 4 g −1 COD) yields at mesophilic conditions (37 °C) in two-stage AD process compared to that of the control (142 mL H 2 g −1 COD and 216 mL CH 4 g −1 COD). In addition, One-stage AD graphite rods coated with nano-nickel ferrite achieved the highest methane (280 mL CH 4 g −1 COD) yield at mesophilic conditions of all the tested conditions at one-stage AD. In addition, coating the nano-nickel ferrite on the graphite rods avoids its wash out from the system. Correspondingly, total energy recovery from PPW was increased, with the highest recovery observed in two-stage digestion using graphite rods coated with nano-nickel ferrite, reaching 7.9 × 10⁸ kJ, which is more than 1.5 times compared to control assays. The future perspectives and practical implications of coupling biowaste reduction and bioenergy production from PPW revealed a significant opportunities in many aspects including waste management , renewable energy generation, resource recovery, and compliance with environmental regulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".