Formation of biologically influenced palladium microstructures by Desulfovibrio desulfuricans and Desulfovibrio ferrophilus IS5
Bibliographic record
Abstract
A range of Desulfovibrio spp. can reduce metal ions to form metallic nanoparticles that remain attached to their surfaces. The bioreduction of palladium (Pd) has been given considerable attention due to its extensive use in areas of catalysis and electronics and other technological domains. In this study we report, for the first time, evidence for Pd(II) reduction by the highly corrosive Desulfovibrio ferrophilus IS5 strain to form surface attached Pd nanoparticles, as well as rapid formation of Pd(0) coated microbial nanowires. These filaments reached up to 8 µm in length and led to the formation of a tightly bound group of interconnected cells with enhanced ability to attach to a low carbon steel surface. Moreover, when supplied with high concentrations of Pd (≥ 100 mmol Pd(II) g −1 dry cells), both Desulfovibrio desulfuricans and D. ferrophilus IS5 formed bacteria/Pd hybrid porous microstructures comprising millions of cells. These three-dimensional structures reached up to 3 mm in diameter with a dose of 1200 mmol Pd(II) g −1 dry cells. Under suitable hydrodynamic conditions during reduction, two-dimensional nanosheets of Pd metal were formed that were up to several cm in length. Lower dosing of Pd(II) for promoting rapid synthesis of metal coated nanowires and enhanced attachment of cells onto metal surfaces could improve the efficiency of various biotechnological applications such as microbial fuel cells. Formation of biologically stimulated Pd microstructures could lead to a novel way to produce metal scaffolds or nanosheets for a wide variety of applications.
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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".