Electrografted Interfaces on Metal Oxide Electrodes for Enzyme Immobilization and Bioelectrocatalysis
Bibliographic record
Abstract
Abstract In this work, we demonstrate that diazonium electrografting of biocompatible interfaces on transparent conducting oxide indium tin oxide (ITO) can be controlled and optimized to achieve low charge transfer resistance, allowing highly efficient electron transfer to an immobilized model enzyme, the oxygen‐tolerant [NiFe]‐hydrogenase from Ralstonia eutropha. The use of a radical scavenger enables control of the interface thickness, and thus facilitates maximization of direct electron transfer processes between the enzyme's active center and the electrode. Using this approach, amine and carboxylic acid functionalities were grafted on ITO, allowing enzyme immobilization both under moderate electrostatic control and covalently via amide bond formation. Despite an initial decrease in catalytic activity, covalent immobilization led to an improvement in current stability compared to just electrostatically immobilized enzyme. Given the superior stability of electrografted interfaces in comparison to adsorbed or self‐assembled interfaces, we propose electrografting as an alternative approach for the functional immobilization of redox‐active enzymes on transparent conducting oxide (TCO) electrodes in bioelectronic 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".