Evaluation of the suitability and performance of cassava waste (peel) extracts in a microbial fuel cell for supplementary and sustainable energy production
Bibliographic record
Abstract
In a number of energy-poor nations, peel from cassava processing represents one of the most abundant sources of lignocellulosic biomass. This peel is mostly discarded indiscriminately and eventually constitutes a problem to the environment. However, energy can be extracted from this peel in a microbial fuel cell. In this study, the viability of cassava peel extract as a substrate in a single-chamber air cathode microbial fuel cell is demonstrated, and optimum performance conditions are explored. The effects of different pretreatments on the extract are also discussed in the context of observed changes in the internal resistances, conductivity and Coulombic efficiencies. At the best conditions examined, the extract from cassava peel fermented for 168 h and adjusted to a pH of 7.63 attained a peak voltage of 687 mV ± 21 mV, a power density of 155 mW m −3 of reactor volume and a Coulombic efficiency of 11 %. Although this energy is limited to direct use, systems exist that can effectively harvest and boost the energy to levels sufficient for supplementary energy usage in cassava producing regions.
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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 | 0.018 | 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 | 0.001 |
| 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".