Hydrogen production from energetic poplar and waste sludge by electrohydrogenesis using membraneless microbial electrolysis cells
Bibliographic record
Abstract
Membraneless microbial electrolysis cells (MECs) are potentially considered to produce biohydrogen (bioH 2 ) in a green manner and simultaneously minimize agricultural and wastewater facility wastes. However, effective, sustainable, and cost-effective system configuration and improvement of operating variables, working at ambient conditions, are needed to make the MEC a sustainable process. Therefore, this study investigates the bioH 2 production from poplar leaves and anaerobic sludge mixture by incorporating nanomaterials comprising Al 2 O 3 , MgO, and Fe 2 O 3 metal oxides at various dosages. Moreover, the effects of applied cell voltage (0.5–1.5 V) and inoculum amount (20–40 mL) on bioH 2 production and organic matter removal performance are evaluated. The maximum bioH 2 production value is 417 mL at an applied voltage of 1.5 V with a chemical oxygen demand (COD) removal efficiency of 37.6 % under operating times of 5 min using 40 ml of inoculum. The bioH 2 production of the MEC system is reduced with the decrease in inoculum amount. The highest bioH 2 production of 828 mL is obtained at improved conditions in the presence of 1 g of Fe 2 O 3 metal oxide. Overall, this study provides the potentiality of simultaneous waste minimization and bioH 2 production under ambient conditions that highlight the waste-to-energy pathway for membraneless and green bioelectrochemical process.
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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 | 0.001 |
| 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 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".