Carbon dioxide adsorption by modified carbon nanotubes
Bibliographic record
Abstract
Abstract In this study the CO2 adsorption of three different diameters of multi‐walled carbon nanotubes (MWCNT) and single‐walled carbon nanotube (SWCNT) was investigated for a mixture of CO2/Ar at a temperature of 70 °C and atmospheric pressure. The largest diameter of MWCNT showed the highest CO2 uptake of 65.2 mg CO2 adsorbed per g adsorbent. One of the MWCNTs were modified with urea (CH4N2O) under two different loading durations with the aim of improving adsorption capacity. After such a functionalization, the CO2 uptake increased from 53.9 to 64.1 mg CO2 adsorbed per g adsorbent after 4 h loading duration. These findings indicate considerable potential of functionalized carbon nanotubes in comparison with other silica and carbon adsorbents. © 2015 Curtin University of Technology and John Wiley & Sons, Ltd.
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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".