Preparation of Efficient Carbon-Based Adsorption Material Using Asphaltenes from Asphalt Rocks
Bibliographic record
Abstract
In this work, the asphaltenes from natural Indonesia asphalt rocks were taken as raw materials for the preparation of micromesoporous enriched carbon material through pyrolysis (<500 °C) and KOH activation (<900 °C) processes. It is found that, during the pyrolysis process, the asphaltenes could be converted to noncondensable gas (36.02%), pyrolytic tar (26.57%), and residual char (37.44%). When the char was mixed together with KOH for heating, more carbons would be released due to the activation reaction, forming a carbon network. The optimal activation conditions were obtained at KOH/char ratio of 3:1 and 800 °C for 30 min. Results also show that almost all of the nitrogen atoms stay in the solid carbon during heating with little releasing to the gas or liquid products. The final obtained porous carbon materials are determined to possess a specific surface area of 1735 m2/g with rich micropores (∼2.0 nm). Instrumental characterizations show that there are abundant heteroatomic groups, including S═O, —OH, and —N═, on the activated carbon surface. Further tests by adsorption indicate that the adsorption of methylene blue on the porous carbon material is monolayer adsorption. The maximal adsorption capacity is determined to be at 556.00 mg/g, much higher than that of some commercial activated carbons. It is also indicated that the adsorption kinetics follows the pseudo-second-order kinetic model. These findings suggest that the asphaltene derived carbon material would be promising efficient adsorbents. It also sheds lights on the resourcilization of asphaltenes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".