A conductive hydrogel based on alginate and carbon nanotubes for probing microbial electroactivity
Bibliographic record
Abstract
Some bacteria can act as catalysts to oxidize (or reduce) organic or inorganic matter with the potential of generating electrical current. Despite their high value for sustainable energy, organic compound production and bioremediation, a tool to probe the natural biodiversity and to select most efficient microbes is still lacking. Compartmentalized cell culture is an ideal strategy for achieving such a goal but the appropriate compartment allowing cell growth and electron exchange must be tailored. Here, we develop a conductive composite hydrogel made of a double network of alginate and carbon nanotubes. Homogeneous mixing of carbon nanotubes within the polyelectrolyte is obtained by a surfactant assisted dispersion followed by a desorption step for triggering electrical conductivity. Dripping the mixture in a gelling bath through simple extrusion or a double one allows the formation of either plain hydrogel beads or liquid core hydrogel capsules. The process is shown to be compatible with the bacterial culture (Geobacter sulfurreducens). Bacteria can indeed colonize the outer wall of plain beads or the inner wall of the conductive capsules' shell that function as an anode from which electrons produced by the cells are collected.
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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".