Bismuth-Doped Carbon Dots Decorated <i>Escherichia coli</i> for Enhanced Hydrogen Production
Bibliographic record
Abstract
Photosynthetic inorganic biohybrid systems (PBSs) combining an inorganic photosensitizer with intact living cells provide an innovative view for solar hydrogen production. However, typical whole-cell biohybrid systems often suffer from sluggish electron transfer kinetics during transmembrane diffusion, which severely limits the efficiency of solar hydrogen production. Here, a unique biohybrid system with a quantum yield of 8.42% was constructed by feeding bismuth-doped carbon dots (Bi@CD S ) to Escherichia coli ( E. coli ). In this biohybrid system, Bi@CD S can enter the cells and transfer the electrons upon light irradiation, greatly reducing the energy loss and shortening the distance of electron transfer. More importantly, the photocatalytic hydrogen production of the E. coli –Bi@CDs biohybrid system reached up to 0.95 mmol within 3 h under light irradiation (420–780 nm, 2000 W m –2 ), which is 1.36 and 2.38 times higher than that in the E. coli –CDs biohybrid system and the E. coli system, respectively. In addition, the mechanism of enhanced hydrogen production was further explored. It was found that the accelerated decomposition of glucose, the accelerated production of pyruvate, the inhibition of lactic acid, and the increase of formic acid were the reasons for the increase of hydrogen production. This work provides a novel strategy for improving the hydrogen production in photosynthetic inorganic biohybrid systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".