Cross-linked glucose oxidase clusters for biofuel cell anode catalysts
Bibliographic record
Abstract
The efficient localization of increased levels of active enzymes onto conducting scaffolds is important for the development of enzyme-based biofuel cells. Cross-linked enzyme clusters (CEC) of glucose oxidase (GOx) constrained to functionalized carbon nanotubes (CEC-CNTs) were generated in order to evaluate the potential of using CECs for developing GOx-based bioanodes functioning via direct electron transfer from the GOx active site to the CNT scaffold. CEC-CNTs generated from several weight-to-weight ratios of GOx:CNT were examined for comparable catalytic activity to free GOx into the solution, with CEC-CNTs generated from a 100% GOx solution displaying the greatest enzymatic activity. Scanning transmission electron microscopic analysis of CEC-CNTs generated from 100% GOx to CNT (wt/wt) ratios revealed that CEC clusters of ∼78 µm2 localized to the CNT surface. Electrochemical analysis indicates that the enzyme is engaged in direct electron transfer, and biofuel cells generated using GOx CEC-CNT bioanodes were observed to have a peak power density of ∼180 µW cm(-2). These data indicate that the generation of nano-to-micro-sized active enzyme clusters is an attractive option for the design of enzyme-specific biofuel cell powered implantable devices.
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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) | 0.001 | 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".