Bibliographic record
Abstract
Abstract Lignin, a major polymeric constituent of woody plant tissue, is an abundant source of natural organic matter available as a waste product from the pulp and paper and the fuel ethanol industries. In this study, the sorptive capacity of acid hydrolysis lignin for naphthalene, a representative nonpolar hydrophobic organic compound (HOC), was investigated. When powdered lignin is mixed with distilled water, dissolved and/or colloidal organic matter leaches into the aqueous phase imparting a cloudy yellowish colour. A washing and filtering protocol was developed for pretreating the lignin employed in the sorption studies. Results from batch sorption experiments showed that acid hydrolysis lignin has a strong affinity for naphthalene. The Freundlich isotherm coefficients obtained indicate that the sorption isotherm for naphthalene on hydrolysis lignin is nearly linear. A modified Freundlich equation was employed in order to compare sorption data for HOCs on lignin and activated carbon through the use of unit equivalent coefficients. The results presented in this research and in the literature suggest that the two sorbents are comparable in terms of sorption coefficients. It was determined that acid hydrolysis lignin is unsuitable for use in a packed bed since pumping a naphthalene solution through a column packed with lignin caused the wet lignin to become significantly hardened over time, resulting in a large pressure drop across the system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".