Enhancing Biohybrid CO<sub>2</sub> to Multicarbon Reduction via Adapted Whole-Cell Catalysts
Bibliographic record
Abstract
Catalytic CO2 conversion to renewable fuel is of utmost importance to establish a carbon-neutral society. Bioelectrochemical CO2 reduction, in which a solid cathode interfaces with CO2-reducing bacteria, represents a promising approach for renewable and sustainable fuel production. The rational design of biocatalysts in the biohybrid system is imperative to effectively reduce CO2 into valuable chemicals. Here, we introduce methanol adapted Sporomusa ovata (S. ovata) to enhance the slow metabolic activity of wild-type microorganisms to our semiconductive silicon nanowires (Si NWs) array for efficient CO2 reduction. The adapted whole-cell catalysts enable an enhancement of CO2 fixation with a superior faradaic efficiency on the poised Si NWs cathode. The synergy of the high-surface-area cathode and the adapted strain achieves a CO2-reducing current density of 0.88 ± 0.11 mA/cm2, which is 2.4-fold higher than the wild-type strain. This new generation of biohybrids using adapted S. ovata also decreases the charge transfer resistance at the cathodic interface and facilitates the faster charge transfer from the solid electrode to bacteria.
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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) | 0.000 | 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".