Effect of Metal Salt on the Pore Structure Evolution of Pitch-Based Activated Carbon Microfibers
Bibliographic record
Abstract
The effect of palladium acetylacetonate on the pore structure evolution of isotropic petroleum pitch-based activated carbon fibers (ACFs) is characterized by comparing the pore structure evolution of ACFs that have been prepared from pure pitch and from palladium acetylacetonate-containing pitch. The pore structure was interpreted by applying chi-theory, Brunauer−Emmett−Teller (BET) surface area analysis, Barrett−Joyner−Halenda (BJH) methodology, t -plots, adsorption potential distribution (APD), and nonlocal density functional theory (NL-DFT) to experimental N 2 adsorption isotherms. Pore size and pore volume calculations from chi-theory are in agreement with those from APD and NL-DFT, respectively, whereas, those from the BET, BJH, and t -plot methods are not. However, chi-theory underestimates the total surface area. The validated porosity and surface area results, pore size distribution, and APD were then studied as a function of burnoff value. The pore structure evolution analysis of both types of ACFs showed that the addition of palladium acetylacetonate to the pitch, prior to fiber formation, causes (i) the formation of macropores, (ii) a small increase in microporosity during the early stages of activation, and (iii) increased mesoporosity at burnoff values of >60%. The presented data and analysis provide a new understanding of the porous structure of novel pitch-based activated carbon adsorbents and potential hydrogen storage materials.
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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 | 0.001 |
| 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 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".