Porous Graphitized Carbon Monolith as an Electrode Material for Probing Direct Bioelectrochemistry and Selective Detection of Hydrogen Peroxide
Bibliographic record
Abstract
For the first time, graphitized carbon particles with a high surface area have been prepared and evaluated as a new material for probing direct electrochemistry of hemoglobin (Hb). Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) imaging revealed that the carbon monolithic skeleton was constructed by a series of mesopores with irregular shapes and an average pore diameter of ~5.6 nm. With a surface area of 239.6 m(2)/g, carbon particles exhibited three major Raman peaks as commonly observed for carbon nanotubes and other carbon materials, i.e., the sp(3) and sp(2) carbon phases coexisted in the sample. A glassy carbon electrode modified with carbon monoliths and didodecyldimethylammonium bromide exhibited direct electron transfer between Hb molecules and the underlying electrode with a transfer rate constant of 6.87 s(-1). The enzyme electrode displayed a pair of quasi-reversible reduction-oxidation peaks at -0.128 and -0.180 V, reflecting the well-known feature of the heme [Fe(3+)/Fe(2+)] redox couple: a surface-controlled electrochemical process with one electron transfer. This reagentless biosensing approach was capable of detecting H(2)O(2), a simple molecule but plays an important role in analytical and biological chemistry, as low as 0.1 μM with linearity of 0.1-60 μM and a response time of <0.8 s, comparing favorably with other carbon based electrodes (5 s).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".