Surface Morphology of Thermal, Furnace and Pyrolytic Carbon Blacks by Nitrogen Adsorption - Relation to the Electrical Conductivity
Bibliographic record
Abstract
Abstract The surface morphology of various carbon blacks was studied by low-pressure nitrogen adsorption. The shape of their low-pressure nitrogen isotherm depends on the concentration of surface defects. This defect concentration on the surface is different for thermal blacks, even for those of the same grade. Different surface morphologies were also observed for carbon blacks obtained by pyrolysis of truck tires. The concentration of defects increased with pyrolysis pressure. For the various furnace blacks, however, similar surface morphologies were observed. The electrical conductivity of thermal and pyrolytic carbon blacks decreases with increasing defect concentration. However, in spite of a similar surface morphology, different conductivities were observed for furnace blacks. The carbon black surface morphology is therefore not a determining factor for the electrical conductivity. Furthermore, the graphitic character of the carbon black surface was studied by secondary ion mass spectroscopy (SIMS). For thermal, furnace and pyrolytic carbon blacks, the conductivity increased with increasing graphitic character of the carbon black surface, thus underlining the importance of this parameter.
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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 | 0.001 | 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".