Synthesis of Mesoporous Carbons from Bituminous Coal Tar Pitch Using Combined Nanosilica Template and KOH Activation
Bibliographic record
Abstract
Mesoporous carbons (MCs) facilitate mass transport in pore networks and enhance the performance of porous carbon. By combining a nanosilica template with KOH activation, highly porous MCs with BET specific surface areas ( S BET ) greater than 1000 m 2 /g were synthesized from unmodified commercial coal tar pitch. The MCs had a honeycomblike morphology with randomly arranged macropores. An increase in template amount resulted in an increase in pores larger than 20 nm, the size of silica template. An MC sample activated at 850 °C for 2 h with a KOH-to-carbon ratio of 2.7:1 and a pitch-to-template ratio of 3:1 had an S BET value of 1366 m 2 /g, 65 vol % mesopores, 19 vol % macropores, and an average pore diameter of 25 nm. Whereas the silica template was largely responsible for macropores and large mesopores, KOH created new micropores and enlarged existing pores through KOH–carbon reactions. Moreover, KOH enhanced the formation of carbonyl, carboxyl, and lactonic groups on the carbon surface. The feasibility of synthesizing MCs from an unmodified commercial carbon precursor with a simpler route was demonstrated.
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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 | 0.001 |
| 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 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".