EVOLUTION LIGNITE MESOPORE STRUCTURE DURING DRYING. EFFECT OF TEMPERATURE AND HEATING TIME
Bibliographic record
Abstract
The knowledge of the intrinsic pore structure of coals is significant in elucidating the kinetics of mass transport and chemical reaction that leads to design of more efficient coal combustion and conversion equipment. The results of pore structure studies of Greek lignite are reported in this work. Isothermal drying of Greek lignite samples, under vacuum, caused mesopore structure evolution despite the severe (∼50%) particle size contraction due to heating. Mesopore volume and surface area were increased as the drying temperature was raised to 200°C while further drying up to 250°C caused a mesopore volume and surface area decrease. Lignite drying at 100°C for up to 3 h resulted in a monotonic increase of the mesopore structure properties while heating for a longer period i.e., 6 h, despite a slight increase of weight loss, caused pore volume and surface area reduction. Nitrogen sorption (77 K) hysteresis data obtained for partially dried samples have been processed to deduce BET surface area and pore size distributions (PSD) by using both the Roberts and a new method based on a Corrugated Pore Structure Model (CPSM-nitrogen) methods. The latter method was applied successfully in hysteresis loop simulations and predicted pore surface areas consistent with the respective BET values. Bimodal PSD have been detected with one peak at 3 nm and the second at 20 nm while surface area varied over the range 2.98–5.30 m2/g. Dry Greek lignite has shown a higher mesopore volume than that of several American and Canadian coals of varying rank. Mesopore volume distribution of dry Greek lignite, obtained from nitrogen sorption data, agree well with those deduced from mercury penetration data corrected for coal compressibility.
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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".