The Effect of Bismuth and Tin on Methane and Acetate Production in a Microbial Electrosynthesis Cell Fed with Carbon Dioxide
Bibliographic record
Abstract
This study investigates the impacts of bismuth and tin on the production of CH4 and volatile fatty acids in a microbial electrosynthesis cell with a continuous CO2 supply. First, the impact of several transition metal ions (Ni2+, Fe2+, Cu2+, Sn2+, Mn2+, MoO42−, and Bi3+) on hydrogenotrophic and acetoclastic methanogenic microbial activity was evaluated in a series of batch bottle tests incubated with anaerobic sludge and a pre-defined concentration of dissolved transition metals. While Cu is considered a promising catalyst for the electrocatalytic conversion of CO2 to short chain fatty acids such as acetate, its presence as a Cu2+ ion was demonstrated to significantly inhibit the microbial production of CH4 and acetate. At the same time, CH4 production increased in the presence of Bi3+ (0.1 g L−1) and remained unchanged at the same concentration of Sn2+. Since Sn is of interest due to its catalytic properties in the electrochemical CO2 conversion, Bi and Sn were added to the cathode compartment of a laboratory-scale microbial electrosynthesis cell (MESC) to achieve an initial concentration of 0.1 g L−1. While an initial increase in CH4 (and acetate for Sn2+) production was observed after the first injection of the metal ions, after the second injection, CH4 production declined. Acetate accumulation was indicative of the reduced activity of acetoclastic methanogens, likely due to the high partial pressure of H2. The modification of a carbon-felt electrode by the electrodeposition of Sn metal on its surface prior to cathode inoculation with anaerobic sludge showed a doubling of CH4 production in the MESC and a lower concentration of acetate, while the electrodeposition of Bi resulted in a decreased CH4 production.
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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".