Закрытое государство и тупики цивилизации (институциональный исторический анализ)
Bibliographic record
Abstract
Coal water slurry (CWS) has been considered a cleaner and sustainable alternative to coal. However, the challenging suspension of coal particles in CWS has created a major obstacle to its use in industry. This study presents a novel approach to enhance the stability and rheological properties of coal water slurry (CWS) through the utilization of carboxyalkylated lignin (CL) as a dispersant. The generated CL samples had high water solubility of around 9 g/L and a charge density of around 2 mmol/g. All CLs were able to stabilize the coal suspension, and their performance decreased due to the increase in the alkyl chain length of carboxyalkylated lignin. Carboxymethylated lignin (CL-1) improved the stability of the coal suspensions with the lowest instability index of less than 0.6. The addition of CLs reduced the contact angle of the coal surface from 45.3° to 34.6°, and the increase in the alkyl chain length hampered its effect on contact angle changes. The zeta potential measurements confirmed that the adsorption of CL enhanced the electrostatic repulsion between coal particles in suspensions, and the zeta potential decreased with the increased alkyl chain length of CLs due to increased steric hindrance. The rheology results indicated that CLs demonstrated shear thinning behavior. This innovative method showcases the affinity of carboxyalkylated lignin to improve the performance of CWS, offering an environmentally friendly alternative for producing a cleaner product, i.e., sustainable coal water slurry, with improved suspension stability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".