Fabrication and Characterization of Nanotemplated Carbon Monolithic Material
Bibliographic record
Abstract
A novel hierarchical nanotemplated carbon monolithic rod (NTCM) was prepared using a novel facile nanotemplating approach. The NTCM was obtained using C60-fullerene modified silica gels as hard templates, which were embedded in a phenolic resin containing a metal catalyst for localized graphitization, followed by bulk carbonization, and template and catalyst removal. TEM, SEM, and BET measurements revealed that NTCM possessed an integrated open hierarchical porous structure, with a trimodal pore distribution. This porous material also possessed a high mesopore volume and narrow mesopore size distribution. During the course of carbonization, the C60 conjugated to aminated silica was partly decomposed, leading to the formation of micropores. The Raman signature of NTCM was very similar to that of multiwalled carbon nanotubes as exemplified by three major peaks as commonly observed for other carbon materials, i.e., the sp3 and sp2 carbon phases coexisted in the sample. Surface area measurements were obtained using both nitrogen adsorption/desorption isotherms (BET) and with a methylene blue binding assay, with BET results showing the NTCM material possessed an average specific surface area of 435 m2 g(-1), compared to an area of 372 m2 g(-1) obtained using the methylene blue assay. Electrochemical studies using NTCM modified glassy carbon or boron doped diamond (BDD) electrodes displayed quasi-reversible oxidation/reduction with ferricyanide. In addition, the BDD electrode modified with NTCM was able to detect hydrogen peroxide with a detection limit of below 300 nM, whereas the pristine BDD electrode was not responsive to this target compound.
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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".